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Neurotics Magazine - first and only issue - year 2013

Neuroscience in context

In this issue:

Brain imaging techniques Human media interaction Philosophical reflection

Neurotics Magazine is powered by Technolab 速, University of Twente

CONTENTS Introduction


Case 1: Brain imaging and its techniques



NIM and MIRA – Who are they?


Interview with Prof. David Norris of the NIM group


Improving fMRI


Diffusion tensor imaging: how water molecules reveal the brain


Improving diagnosis using cognitive neuroscience - a physicists’ view


Case 2: Human media interaction



Brain computer interaction - The Brain in the game


Human factors


Social science meets mathematics - how to make technology social


Philosophical reflection

Introduction to PSTS


Mediated experience. How fMRI technologies influence scientific knowledge 29

Column: The Fourth Discontinuity – Who are ‘we’ or rather what are ‘we’?


Kant’s Metaphyiscs of Morality and Neuroimaging


INTRODUCTION Dear reader, Welcome to the Neurotics magazine! In this magazine we will take you along in our quest to find out how the current scientific practices relating to the University of Twente play a role in the world in which we nowadays live, and what this means to your and our life. The structure of the magazine is such that we present a case for engineering sciences as well as sciences with a more social orientation; they are however related to each other in terms of their intended practical uses. After a thorough investigation relating to the research goals, problems, methodologies and practicalities in these cases we endeavor to place this all into context by making use of a philosophical reflection. In this reflection we sketch meaning and impact on your and our life as well as possible future impacts on society as a whole. We aim to keep the magazine interesting by thoroughly explore and deliberately chosen subjects, however still keeping the articles clear and understandable for everyone who cherishes an interest in the topics covered. For the engineering sciences we have chosen the topic of brain imaging and the technology under development to make this possible. Also we address the goals the scientist are working on like providing cures for diseases and a better understanding of the workings of our brain. This fascinating world is providing cutting-edge technology which makes the boundary between humans and machines slowly les distinct; it might even disappear in the end. The social oriented sciences are covered by the topic of human media interaction. This field of science is concerned with the relation between the brain imaging technology developed and the application of these technologies in the social world. Subjects covered are the problems with using technology to solve social problems, differences in approach for technical and social research and the way in which current level of technology can be integrated with the brain. Also matters of developing technical artifacts which display social behavior is touched upon and the way in which engineering science is related to social science. Finally we place the cases into context by reflecting upon them using different perspectives. In taking the anthropological perspective we reflect on the cases by asking the question what is means for our self-image to be able to precisely know the inner workings of our brain and the consequences this might have. By taking the epistemological perspective we cover the way in which we might consider the efforts made by science, and how this knowledge is created. In the last topic we discuss an ethical perspective providing insight into a possible ethical stance which can be taken regarding the development of brain imaging and brain computer interaction technology. If reading this magazine will make you feel more informed about the topics discussed, as well as improved your ability to discuss the impact of the topics in your daily life we will feel delighted. Please feel free to visit our website at or find us on facebook! Regards, Anna, Laura, Tom and Mark Editors of Neurotics Magazine


Brain imaging

CASE 1: BRAIN IMAGING AND ITS TECHNIQUES Introduction In this edition of Neurotics magazine, we are all about brain imaging! Brain imaging is a field which has revolutionized neurosciences and deeply troubled former understanding of ‘being human’. It has given way to insights about essential anthropological questions - who we are, what we are; how we, humans, think, make decisions, fall in love or suffer from pain; it has even driven some of us to see ourselves as mere machines. So it is not an exaggeration to claim that the human brain is the most enigmatic organ known. It performs a variety of tasks which are responsible for the functioning of our whole bodies. Everything we can think, feel, touch, hear or smell is processed by this extremely complex system. Hence it is no wonder scientists are fascinated with the idea of decoding brain signals and processes; they are eager to read the mind like a book. The fields concentrating on the discovery of brain functions and the roles of different brain regions are the Neurosciences. They use technologies that can measure and visualize brain activities. The realm concerned with techniques which are capable of this are summarized under the term Neuroimaging.

Brain signals – how can we read them? An impression.


In the history of neuroimaging, pioneer scholar Franz Joseph Gall in the 1790s was the first scientist attempting to map the functions of different brain regions. His theory was grounded on the assumption that different mental functions are localized in different parts of the cortex. In his theory he assumed that the quality of a particular faculty directly depends on the size of the corresponding cortical area. This theory gave rise to the famous practice of determining an individual’s personality by looking at and measuring the shape of her skull; the assumption proved to be wrong, but in connection with Darwinist approaches nevertheless gave way to justify inhuman treatment of races which were assumed to be less developed and therefore to need ‘guidance’ or even to be biologically inferior or weaker and therefore unavoidable victims of natural selection. Even though nowadays the consequences might not be as dramatic, questions that arise from the success of the ongoing research are nevertheless ethically relevant; a reflection on how to deal with the results seems unavoidable. For example, they can endanger the personal freedom of opinion or one’s integrity. Techniques, which in the future might be able to fully read or even control our minds, threaten our most reliable freedom – the freedom of thought; thus giving way to such possibilities seems to tickle out hostile intuitions. But also from an anthropological or psychological perspective, they bear significance for concepts of human self-understanding, like the ‘free will’, the ‘mind’ and the extent of human determinism. But to map and understand the brain also gives way to new possibilities of improving quality of life. In medical engineering, patients suffering from neuronal dysfunctions, for example Parkinson disease, can be and already are treated through electrical stimulation of certain neuronal structures. Furthermore, Brain-Computer-Interfaces (BCI’s) are being developed. They are able to establish direct communication between the human brain and a computer; in doing so, they open up a new world for the disabled. And all these applications firstly require a deeper understanding of the brain and its working and a possibility to decode brain signals on which they rely.

Our brain – just a machine? Impressions from

So in order to investigate the brain and its functions further, scientists seek trustworthy technologies that can provide them with reliable information about brain structures and their processing mechanisms. Thus the development of neuroimaging technologies has a significant impact on the scientific world. It enables scientists to get the

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Brain imaging

most desirable information for their investigations – a clear picture of the internal structure of the brain, even in vivo. Research in neuroimaging technologies have come a long way from imprecise X-ray imaging techniques to powerful high-resolution Magnetic Resonance Imaging (MRI) technologies that can measure brain activities and physiologies with high resolutions and 3D data. The MRI technology detects changes of magnetic fields induced through neuronal activities. Despite the outstanding achievements in this area of research, there are still a variety of technical weaknesses scientists hope to overcome. Scholars all around the world are involved in a number of scientific research projects. Their goals are challenging and complex. They are working on improving MRI techniques and developing novel methods of diagnostic and computational data modeling using the collected neuronal data.


Are we still different?

In this edition of the Neurotics, we have investigated the state-of-art in neuroimaging sciences and directly spoken to researchers from the NIM group. We present a choice of their most interesting research project and significant distributions and reflect on their work and research practices. Our standard as always is to provide our readers with the latest news on scientific research from first-hand information.

Sources: thepsychologist%5Ccowey.pdf BBCfour documentary “Scientific Racism: The Eugenics of Social Darwinism” retrieved from

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One contributor to the ongoing research is the Institute for Biomedical Technology and Technical Medicine - MIRA - of the University of Twente in Enschede, Netherlands. A part of MIRA is NIM, short for NeuroImaging group, which consists of a multi-disciplinary team with a focus on imaging neurosciences. NIM is covering a range of research fields - from the development of novel methods for data imaging and signal processing to analysis of the accumulated data and its use for diagnostic systems. They are working on improving the technologies that measure and picture active brain areas as well as on technologies that use these data to derive implications for the brain’s functions. NIM’s scientists seek for imaging technologies which have a minimal image distortion and power deposition in MRI measurements. To achieve this goal, they employ some of the most advanced statistical analysis techniques and improve current imaging techniques. Parts of these improvements involve developing biomarkers based on nanotechnology and finding the link between a subject’s genetic makeup and specific scan results.

So who are NIM and MIRA, and how do they work together? The Neuroimaging Group operates as collaboration with Donders Institute, Radboud University and the University of Twente. At University of Twente’s Institute for biomedical Engineering and Technical Medicine (MIRA), 180 scientists work with hospitals, businesses and governmental organizations. Having a management team and using entrepreneurial expertise, MIRA has a multidisciplinary approach to cut down the time it takes for a technology to go from the lab to the clinic and increase spin-off company success. Therefore, the management team, consisting of a scientific, a managing and a medical director, is advised by the Scientific Advisory Board and the Socio-economic committee. However, MIRA’s main goal is to develop technological products for clinical practice through both fundamental and applied research. Within MIRA there are three different research tracks, so called Strategic Research Orientations (SRO’s), currently underway: Tissue Regeneration, Imaging and Diagnostics, Neural and Motor Systems, each of which is also lead by an entrepreneurial chair. The graphic below shows how the different groups of MIRA (Tissue Regeneration, Imaging & Diagnostics, Neural & Motor Systems) concentrate on moving fundamental research to a clinical setting by doing applied research in strategic fields.


Brain imaging



MIRA Institute for Biomedical Technology and Technical Medicine (2012). [Graphic Illustration of MIRA organization]. Retrieved from

MIRA Institute for Biomedical Technology and Technical Medicine (2012). [Graphic Illustration of MIRA organization]. Retrieved from Each research track is made up several smaller research groups, 18 in totals, lead by principal investigators. The Neuroimaging group (NIM) within the Imaging and Diagnostics research track is directed by Prof. David Norris, Prof. Christian Beckmann, and Dr. Bennie ten Haken. Research by this group conducted at Donders Institude, Radboud University and University of Twente fall in line with one of the group’s three research lines: MR techniques in brain function, Statistical Imaging Neuroscience, or Magnetic Detection. Through utilizing imaging techniques such as MRI, fMRI, EEG, and MEG, the NIM group develops technology for several different research areas including diagnosis systems, biomarkers, and signal processing. David Norris is the principal investigator of MR Techniques in brain function at the Donders Center for Cognitive Neuroimaging. His group works toward improving fMRI techniques and developing very high-resolution fMRI technology. The Statistical Imaging Neuroscience group, located at the Donders Centre in Nijmegen, develops analysis tool for the large amount of data generated by neuroimaging. Lead by Dr. Christian Beckmann, they use techniques such as computational modeling, Bayesian modeling, and connectomics to improve pharmacological neuroscience, biomarker development and imaging genetics. The Magnetic Detection group works toward improving the detector itself. Working in conjunction with researchers developing low temperature systems, they use physics and medicine to explore new magnetic detection techniques often using novel biomaterials.

Written by Mark Burdick Sources: (1) MIRA Institute for Biomedical Technology and Technical Medicine (2012). [Graphic Illustration of MIRA organization]. Retrieved from (2)

MIRA Institute for Biomedical Technology and Technical Medicine (2012). Retrieved from page 6 - Neurotics Magazine - first and only issue

We interviewed the principal investigator of Neuroimaging group (NIM) group Prof. David Norris. We spoke to him about NIM’s work, experiences of academia-industry collaborations and the Dutch government’s funding of science.

Brain imaging


Neurotics: How does the structure of the NeuroImaging group look like and how did it develop?

Norris: The main players in the NIM group a kind of split between Twente and Nijmegen. Here in Nijmegen there is Christian Beckmann, who is a hundred percent Twente guy. Myself, I’m only kind of part time Twente. And AnneMarie van Cappellen van Walsum, who is in the anatomy department. So we have a fair number of people here who are funded by Twente, but not all of my group.


So why does it all work like this? Well, what you’re visiting now is the Donders Centre for Cognitive Neuroimaging. That’s a very unique institution in maybe Dutch science in total. It was originally founded 10 years ago from a grant from NOW as a national centre for neuroimaging. The Donders has a so-called participation model, which has proven enormously successful. The participation model works on the basis that any participant at the Donders pays a fixed amount of money per year. And they put a so called principal investigator in the Donders. This was to avoid the situation which has been seen in some other neuroimaging centers that you have an enormous great park of imaging equipment and not a lot of expertise actually at the imaging center: people come in, do their research and then go away. For example, a lot of psychology departments were interested in scanning and all the scanners were in radiology departments and these were in different faculties. Thereby people had the idea that they would go, paid for 3 hours, they got some images, they went away again and they tried to analyze them. And those were of limited success.

Norris: Christian Beckmann (note by Neurotics: Principal Investigator in Statistical Imaging Neurosciences in University of Twente) is a statistician and he has a great experiance of analysis of fMRI data. So we take his tradition and move it forward. On the other hand, my group is more technically oriented. We are looking at how to improve measurements, how to find new ways of using them. So there is a certain overlap, because we’ve done quite a lot of looking at ways of measuring connectivity, but more coming from the measurement side. Christian does a lot of analysis, looking at detecting brain networks. So we sit pretty close to each other, with different expertise.

Neurotics: And what is the amount of freedom you have in deciding what you invest in fundamental and what you invest in applied research?

Norris: Well, in terms of doing pure physics or pure mathematics, we’re not doing any fundamental research. But I look quite a lot for example at the relationship between activation and the blood flow response. You could see that as being a kind of fundamental research. I think you have a kind of mental program of where you would like to go in your research. And then you have to see what’s practical. A lot of the time these days you are just driven by what grants you can apply for funding. So you try to find grants, which overlap to a large degree with what you really like to do. The nice thing about the Donders is, it has a very flat structure. So, although we have directors, actually I’m one of the two, the directors do not tell the principal investigators what research to do.

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Neurotics: How does the NIM then get to its topics like for example, Statistical Neuroimaging and Improving fMRI?

Norris: Top sectors are bad for us because we don’t really fit into any of the sectors. So that is awkward. These top sectors models are very complicated; I won’t say I’m absolutely against them. Because I can see that in a country like the Netherlands, which is small but has some very big industrial players, it is very important that the sectors, which can earn their way, get a lot of support. However, I think there is a genuine virtue in increasing human knowledge, which is just beyond the measure of what, it can do for the economy and I think that’s been lost. On the other hand, what I see is missing a bit is having a culture of universities which choose more enterprising so that it is easier for universities to setup spin off companies. I believe, being able to setup spin off companies it is much easier to move between companies and academia and back again where as in Europe you commit to an academic career and you’re in an academic career and it’s not so easy to switch around them.


Brain imaging

Neurotics: There is also then a new structure of research funding by the government - so called top sectors. Do you think it’s a good idea to pick some more important topics, which are funded very well and others less?

Organogram of the Donders Institute; of which the NIM-group is a part

Neurotics: Wouldn’t you feel that institute then is becoming more like a company, because they develop methods for industry?


Norris: Yes, we develop methods. If you look at MRI, it is a commercial product. But more than 80% of the big development in MRI is being done in academia. On the other hand, we did a project which was looking at the measuring brain activity in the grey matter of the brain. You can say that the company tries to develop this, but there is no proven market. And techniques did not entirely exist. We got a ground from FWO (Fonds Wetenschappelijk Onderzoek) to do this. And now we are getting more applications, because we tried to find out the areas of using it. Maybe in another 5 years it will be so advanced so people will use it as a routine method that could be implemented on standard scanners.

Neurotics: Are you agreed that this kind of industrial research is mostly done in the universities and the companies actually use the research for their benefit but they do not pay for it.

Norris: Yes, that’s right. For MRI there are 3 big manufactures: General Electrics, Philips and Siemens. They have crosspatenting agreement, which is very interesting. Because what it basically means is that they do not charge each other royalties or each other patents. So anything Philips develops Siemens and GE can use for nothing. They just exchange these things, so the effect they have is that if they pool their patents they keep anybody else of other manufactures out of the market, so the big three stay the big three.

Neurotics: Would you feel that at the last 20 years the commercial interest has taken over and maybe even decides what is being researched?

Norris: No, that’s not the way it works. How it’s used to be, for example, is that if you want to program a scanner that was often quite difficult. So now many manufactures made it relatively easy to program their scanners. But they try increasingly to grab the IP, which is something I’m actually against, quite strongly against. We, for example, have an IP agreement with Siemens, but IP agreement still means that if I have an idea the IP stays with us and does not automatipage 8 - Neurotics Magazine - first and only issue

cally go to Siemens for nothing. But particularly GE they got terrible IP agreement. As soon you buy their piece of equipment so basically any idea you have is the property of GE, because you use their equipment.

Neurotics: You explained the research is being performed in order to understand the brain structure better; why do you need to understand this structure better?

Norris: The reason is both neuroscience and medical application. We want to show the workings of the brain better, for example directions of connections in the brain and how they work (or are dysfunctional). This knowledge can be taken almost immediately to the medical field because the structure of the brain is closely related to a whole range of psychiatric disorders. For example it would be possible to assess the extent to which improvement of patients with a certain illness can recover, and tailoring of therapy is made possible. This requires a lot of methods development and understanding to be finally able to provide a working treatment.

Brain imaging

So I think the universities should have their clear rules to protect the researchers into deals with the companies. It is a big issue, I know groups in the United States which are being in the negotiations for years with Siemens and IP.

Neurotics: When all things (in this interview) are considered, where is the biggest challenge of NIM to be found at the moment?


Norris: There is a lot expected form a modern academic researcher; you have to be good at fund raising, leadership and research all at the same time. There is a lot of work to be done in the field of MRI, and the challenge is to find funding and good people for it. So everything is challenging, but rewarding as well.

Neurotics: What were the great successes so far and/or expectations, which were fulfilled?

Norris: A lot of things have worked very well, on the technical field of multiplexed imaging and improving speed and accuracy of the scanner. A lot of difficult technical challenges had to be solved for this improvement to be possible. I have no regrets whatsoever of going in this field, despite of the pressure. The nice thing is being able to do research which is not only intellectually satisfying but also practically satisfying by making an actual product.

Edited by Anna Kostenko

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Interview by the Neurotics team: Anna Kostenko, Tom van Eerde, Mark Burdick, Laura Fichtner

Brain imaging

IMPROVING FMRI What is Functional Magnetic Resonance Imaging? Functional Magnetic Resonance Imaging (fMRI) is a non-invasive indirect neuroimaging procedure that can be used to study the functioning of the human body, especially the brain, in vivo. Therefore, in neuroscience research, the functional aim of using fMRI technology is to investigate which brain structures are activated during the performance of different tasks and how this is done. On the physiological side, fMRI uses the biological fact that any brain activity is correlated with an increased local brain metabolism; for example cells in activated brain regions start to consume more oxygen than others. These changes cause structural changes in the brain tissue which can then be detected. (Schad, Lothar, Peck, Kyung K., & Holodny, Andrei I.,2008)

In functional Magnetic Resonance Imaging (fMRI), preposition for an accurate image reconstruction from the magnetic responses detected is the exact information about the MR signal’s origin. This spatial information can be generated by space-dependent magnetic fields – so-called gradient echo field - generated by Gradient Coils (see Fig1) and additionally applied across an excited brain slice. Currently, two main acquisition techniques to acquire image data exist. To build an image of a single brain slice, Echo Planar Imaging (EPI) employs a single ‘shot’ of an FR pulse, followed by multiple switchings of the gradient field by means of a magnet (see Fig1). In contrast, the Spin echo technique employs two FR signals; first an initial FR impulse, followed by a second pulse which switches the gradient field. This technique offers a superior localization of the activated brain tissue, but works quite slowly compared to EPI.



On the technical side, functional Magnetic Resonance Imaging uses electromagnetic radiofrequency (FR) pulses (see Fig1), which activate nucleuses in the brain tissues. Activated nucleuses, in response, also produce magnetic signals which can be measured and then transformed into images by so-called MR scanners. Since areas different metabolism and chemical makeup respond differently, this images show brain structures in regard to their different local activities. (Deichmann, Ralf, 2009)

fMRI scanning model From

Despite the fact that during the past few decades significant advances have been made to both acquisition technologies, one of the main problems of fMRI techniques still remains - an image distortion caused by multiple factors. One of them is random brain activity that invokes subsequent changes in the magnetic field and therefore also in the output scanner signal. Secondly, the MRI scanner hardware causes a noise, which corrupts images. Additionally, head and brain movements of the test-patient in the scanner produce a specific physiological noise. Ultimately, the qualitative imaging of the entire human brain is still a major challenge for fMRI techniques. In order to get insight in this topic Neurotics journalists talked to PhD researcher Jennifer Bersch at the Donders Institute for Cognitive Neuroimaging in Nijmegen. We asked her about her work, the organization of the research and her research perspectives. Bersch is working in a research group, which aims to improve fMRI techniques. “We want it to be faster and get better images”, Bersch says. From her point of view, the big problem of MRI is that it takes too much time to produce the wanted images. When someone has to be in an MR scanner for approximately 10 minutes, the person will move at some point, since no one can stay motionless for such a long time. Moreover, the magnetic field also varies over time due to changes in the patient’s blood flow. As a result, images have too much distortion. So in order to improve the image quality, the main idea of Bersch’ research is that if the scanning time gets shorter, fewer changes, causing different kinds of noises and consequently image distortions, occur.

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The most intriguing and challenging aspect in her research is that “you never know what exactly might help you to find a right way”, Bersch says. The big problem is that by exciting multiple slices, the transmitted RF power increases. In turn, all commercial MR scanners have so-called SRA-power (power absorbed in tissue per unit mass) limitation prescribed by the FDA (Food and Drug Administration) in order to prevent the potential effects of heating of patients (R. Jason Stafford, 2005). Thus, if a designed sequence runs into SRA-problem, scientists have to find a way around. Moreover, fMRI technology is a complex solution, which includes MR scanner hardware and a set of functional applications, which each have their own restrictions. So for young researchers in the field, it takes lots of time to get themselves A different use for resonance acquainted with the technology to find a way to overcome constrains and come up with an innovation.


However, the young PhD explains, working in a team and collaborating with the “Sequence” community, as she calls it, significantly helps her: “We have physicians, mathematicians, psychologists, and electrical engineers in our group, so you always can find someone who can help you to break the deadlock.” Every Monday, Bersch has a meeting with the principal investigator Prof. David Norris (see interview feature in this edition), who splits the tasks within the group and checks on the progress. On Tuesdays, PhD students regularly participate in colloquia in order to share knowledge and get themselves acquainted with the work done by the different research groups.

Brain imaging

Ultimately, for her, the technological problem of “How can we decrease distortion in fMR Imaging?” is translated into her scientific research under the motto “How can we develop fast acquisition methods?” In order to find a solution, she especially focuses on implementing sequences, which use multiplex RF pulses. This means that during excitation there is not just one slice excited, but a certain number of slices simultaneously. In this way, it might be possible to get a shorter acquisition time, because the factor of acceleration is determined by the number of simultaneously excited slices.

Even though hired by the Donders Institute, Jennifer Bersch in fact works for the Siemens Company which funds her fMRI research project. Siemens is one of the major players in the market of MRI and collaborating with the Donders Institute seems to be profitable for them. Obviously, in their production of MRI scanners, Siemens can make use of the scientific knowledge produced by her group. Such partnerships between the industry and a research institute are beneficial for all, Bersch notes. There is a strict guideline that regulates upcoming deadlines, but if the researchers do their work ahead of the time, they are free to do research on whatever they are interested in.

Written by Anna Kostenko

References: -Schad, Lothar, Peck, Kyung K., & Holodny, Andrei I. (2008). Functional MRI magnetic resonance tomography. In Maximilian F. Reiser, Wolfhard Semmler & Hedvig Hricak (Eds.), (pp. 1291-1321): Springer Berlin Heidelberg. -Deichmann, R. (2009). Principles of MRI and Functional MRI fMRI Techniques and Protocols. In M. Filippi (Ed.), (Vol. 41, pp. 3-29): Humana Press. - R. Jason Stafford, 2005.High Field MRI: Technology, Applications, Safety, and Limitations.The University of Texas M. D. Anderson Cancer Center, Houston, TX.

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The aspect of her job the PhD finds most motivating is that her research and its results have a real medical application. “With my physics background I could do, for instance, astrophysics research, but with medical application I feel that I do something real which helps medical practice get better images and consequently do better diagnostics”, she says. At the end of the talk, we asked her to tell us a story of success. “Well, when you have tons of errors and your echo sequence doesn’t work at all, then one day you finally get images – that’s what I call a real success story”, laughs Jennifer Bersch.

Brain imaging HMI Reflection

DIFFUSION TENSOR IMAGING – HOW WATER MOLECULES REVEAL BRAIN STRUCTURES DTI technology – possibilities and limitations Diffusion Tensor Imaging (DTI) is special method using Magnetic Resonance Imaging technologies to reveal anatomic structures of the brain with regard to connections between different brain regions. The atomic structures considered here are the axonal paths and functional connections between different axons; therefore brain connectivity is determined by axons and their course. DTI has first been introduces in the mid 1990’s and contributed to the analysis of different mental diseases such as the underdiagnosed Susac’s syndrome(Kleffner et al., 2010) and brain injuries. For example a resent paper of the Annals of the New York Academy of Science emphasized the importance of DTI for the diagnosis of traumatic brain injuries from which many soldiers injured in the wars in Iraq and Afghanistan suffer. Here DTI technology has revealed the severe consequences these injuries have on the functioning of different brain regions due to its possibility to evaluate connections between them. Cognitive deficits following those injuries can now be identified and explained and hence methods of treatment can be evaluated more accurately. (Maruta, Lee, Jacobs, & Ghajar, 2010) DTI bases on the translational movement of water molecules, called the Brownian or thermal movement. Through applying a magnetic gradient, phase differences in the molecules are measured and water motion is detected; this is done by using MRI scanners. The amount of water diffusion for a given pixel is then calculated with the help of a diffusion coefficient. In the retrieved image, areas with a lower coefficient appear more intense. Because it uses water molecules, the results of DTI are dominated by anatomy and not by physiology; this also is its advantage over other MRI techniques. Because the diffusion of water molecules is of a passive nature, it does not need physiological processes or metabolic energy; hence the molecules also possess thermal movement in dead tissue. To illustrate this, Mori and Zhang from the Johns Hopkins University in Baltimore, Maryland MRI scanner at the Donders’ institute in Nijmegen describe the effect as ink dropping on a paper: “After the ink is dropped, it begins to spread as the time lapses […]. The spreading of the ink is due to the thermal motion of its molecules, and the shape of the ink stain reveals something about the underlying fiber structure of the paper.”(Mori & Zhang, 2006) Because it carries information about diffusion contrasts and fiber orientation independent of physiological processes, DTI can produce an image of the complex structure of the brain’s white matter. Even though there is other methods like electron microscopy and staining technologies that fulfill the same purposes, DTI has several advantages over them. It can produce 3D images, needs little time and storage space (only a few megabytes), but most of all the method is completely non-invasive. On the other hand, the loss of biological information is still an issue. Therefore, it is important for scientists to understand which anatomical information can be retrieved with confidence. Challenges exist when it comes to spatial resolution and contrasts between regions with similar biochemical properties. These difficulties mainly arise from the averaging over time and space the used MRI scanners need and the limited number of adjustable variables in the algorithms. Moreover, physical motions can interfere with the DTI signals and changes of axons on a macroscopic level cannot be considered.

DTI – how valid are the results? Facing these obstacles, Michiel Kleinnijnhuis, PhD at the Donders Institute in Nijmegen, is trying to find out in how far the results about axonal brain structures derived from DTI reflect the actual underlying structures and hence how valid the information acquired from DTI is. A Neurotics journalist visited him in his office and spoke to him about his project and the organization of the research. As the main reason for the present emphasis on DTI technologies, he suspects the current shift in neurosciences from the function of specific brain areas to the connectivity approach that focuses on the connectional aspects of different regions. Since DTI does not directly measure the paths of axons but the movement of water molecules, models of these strucpage 12 - Neurotics Magazine - first and only issue

tures are reconstructed from the water molecule movements. Therefore, the conjecturable connectivity of axonal paths depends on a physical theory that needs assumptions and works with possibilities. A simple model makes this approach visible:

Everyday research practices – difficulties and pleasures When looking for patients for his experiments, the PhD has to contact neurologists at the nearby hospital working with Donders. Unfortunately, they are not always as cooperative, because they do not see the financial benefit for their department. “Mostly this is solved by writing a paper together, so just to offer co-authorship, but sometimes they want more. And that also touches on that in the hospital every department has to act like a company. They have to earn money. So I guess that’s a big component”, he says. Still, sometimes both sides benefit from such collaborations. Because part of his research investigates the exact course of fiber bundles, the information can be used by the surgeons. In a recent example, patients encountered a temporal inability to speak after certain surgeries. At first medicals did not have a clue how this came about. With the help of Kleinijnhuis’ work, they are now able to trace connections between the region of the surgeries and the so called superior cerebellar peduncle, which is suspected of being the main cause of the mutism. Therefore, his results can be used for preoperative planning. Even though this example shows how his research results can be applied directly, Kleinijnhuis sees his position in purely fundamental research. This is what motivated him to apply for a PhD job at the Donders Institute in the first place. After having completed a Bachelor in physics and a Master in cognitive neurosciences, he went to work in different companies. But the restrictions he had to face there and the orientation on the commercial outcome constrained his scientific spirit: “What I like most about fundamental research is the fact that you don’t know exactly where you’re going when you start.” This triggers an atmosphere of creativity he values most at the institute. The colloquia and seminars PhD students are required to attend within the institute make an exchange of ideas and inspirations possible and desirable. Hence, he sees issues arising from new constraints on young academics. Earlier, PhD students enjoyed a great freedom in processing their thesis. But new regulations force them to give page 13 - Neurotics Magazine - first and only issue


To sum up: the technological problem “How can we find out about axonal patterns and neuronal connectivity?” is translated into the scientific Additional difficulties problem of “How can we make statements about these patterns, given the water diffusion which is measurable through DTI?”. In order to answer this question, Michiel is comparing the results calculated through the theoretical framework with verifiable brain connections. Therefore, he is using both artificially created phantoms with a definite axonal pattern and ex vivo brains with knowable structures. In doing this, he is then making use of the fact (mentioned above) that water diffusion is independent from physiology.


But working with mere possibilities is not the only uncertainty, Kleinijnhuis explains. More assumptions have to be made when fibers cross. The Clarification of movements following graphic demonstrates the difficulties. The black lines exemplary indicate how neuronal patterns, reconstructed from DTI results, might look. The red arrows indicate the possibilities of neuronal connectivity; so there are two possibilities of connectional paths. Either the lower axon is connected to the upper one, following the arrow pointing upwards, or it is connected to the left one, following the arrow pointing to the left side. So to find out which of the paths is the right one, more variables have to be taken into account and the accuracy of the drawn conclusion verified against factual path connections.

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The picture shows water molecules that move between axons. Due to the Brownian movement they move with certain possibilities in all directions. The only obstacles which they assumable encounter are the axons; they cannot cross them. Therefore, they are likely to move along the axis of axonal paths in an average (yellow lines indicate axis of average movements). So the results are based on probabilities and averages, but they do not directly correspond to axonal paths, because the molecules can, with a low probability, also move in different directions or encounter other obstacles which are not considered here.

Brain imaging HMI Reflection

a report on the advance of their work to the government every six months. Even though Kleinijnhuis understands that the public likes to know about how and on what their tax money is spent, he feels that this pressure might restrain academic free-mindedness. For him, fundamental research does not always have to be connected to direct applications. The aim is to understand further the human brain. Before gaining new insights, one cannot always know about possible applications in advance. Having had practical experiences, he was not disappointed by the practice of scientific research but surprised by the free spirit at the Donders. Still, he sees that many new PhD or Master students start with high expectations and are then disappointed when the project does not go as smoothly as they expected. Issues with theories, calculations and technological devices which call for revision and unusual modi operandi are often not taken into consideration and unsettle young researchers. On the other hand, the freedom they enjoy is not self-evident: “It depends a lot on the project, the institute and the supervisor in how far you are regulated in your research topic and methods.” Reflecting on his development through the course of his research, the PhD says: “At first you only absorb knowledge. But later you feel that you want to give something back and engage in the institute, for example through setting up collaborations and working in education.”And his approach seems to work, since he has been offered a post-doc job after his thesis. The new challenges that will come up in this position, like shaping collaboration work with the nearby hospital and writing proposals in order to get grants for projects himself, excite him. He sees the future of Neuroimaging positive. Even though Neuroscience PhD student Michiel Kleinnijnstruggling with always shorter funds, the institute is expanding and enjoys huis with one of the ex vivo brain probes he worldwide recognition. For him, this is indicated through many publications works with in his research. in renovated science journals such as the Journal of Neuroscience, PNAS and Nature Neuroscience and their high number of citations. In this regard, it seems pardonable that the structure of the groups at the Donders is not always as clear as it could be. When confronted with the fact that he is enlisted as a member of NIM group on their homepage, Kleinijnhuis is surprised: “Maybe my name is on the list because I’m in David´s [Prof. David Norris] group”, he suspects and: “My supervisor in the anatomy department, she is part of the NIM group, so maybe I’m also NIM member.” Even though working mainly with the group MR Techniques for Brain Function of the Centre for Cognitive Neuroimaging at Donders, his PhD is founded through public money within a project which among others, was initiated by the Department of Anatomy of the Medical Centre at the Radboud University in Nijmegen and the Technical Medicine in Enschede.

Written by Laura Fichtner

Sources: Personal Interview (Laura Fichtner) with Michiel Kleinnijnhuis, PhD student at the Donders Institute, Nijmegen Kleffner, I., Deppe, M., Mohammadi, S., Schwindt, W., Sommer, J., Young, P., & Ringelstein, E. B. (2010). Neuroimaging in Susac’s syndrome: Focus on DTI. Journal of the Neurological Sciences, 299(1–2), 92-96. doi: 10.1016/j.jns.2010.08.028 Maruta, J., Lee, S. W., Jacobs, E. F., & Ghajar, J. (2010). A unified science of concussion. Annals of the New York Academy of Sciences, 1208(1), 58-66. doi: 10.1111/j.1749-6632.2010.05695.x Mori, S., & Zhang, J. (2006). Principles of Diffusion Tensor Imaging and Its Applications to Basic Neuroscience Research. Neuron, 51(5), 527-539. doi: 10.1016/j.neuron.2006.08.012

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The complex nature of our minds makes it hard to analyze what goes on when this mind is not functioning as it is expected to. The current treatment practices of psychiatric diseases, which are believed to be caused by malfunctioning of the brain, are focused on the symptoms caused by these malfunctions instead of what is the source of the problem. This is because the source of the problem on a neural level remains mostly hidden to scientists. Diagnoses of psychiatric diseases are made based on certain sets of symptoms associated with a disorder. Examples of these diseases are ADHD (Attention Deficit Hyperactivity Disorder) and autism. As explained before, part of the research is being performed at Donders’ Institute for brain, cognition and behavior, located near the University Hospital in Nijmegen. Here scientists work together to find out how the mechanisms in our heads are able to function by using advanced MRI-techniques and statistics developed by the NIM-group – collaborating with the Donders’ Institute - to measure the brain’s characteristics. All MRI techniques work in an indirect fashion, which means that certain properties of the brain are used as an indicator for their activities.

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Magnetism and the workings of the brain; the relevant basics

Curious about the structure of the research? Mark helps in “NIM and MIRA, who are they?” (p. 6) For Laura’s expert explanation of the workings of MRI principles and technology read “Diffusion Tensor Imaging”. (p. 12)

Twenty years of MRI, expanding possibilities in vivo

Example result of a classic

The advantage of this DTI-technique is the possibility to measure these connections in a living subject, or in vivo, which was not possible before on a network level. The acquirement of knowledge about the inner workings of the brain while it is functioning allows the practice of longitudinal scanning, so multiple scans of the same subject over time, in which the development of a specific brain is monitored. This time could even entail the entire life of someone. This allows for new insights, since the brain can be studied while it is operational. The difference between ex-vivo (a non-living subject) and in-vivo can be compared with using a video instead of still images as a source of acquiring knowledge. This ‘video-style’ enables scientist to describe when a brain develops in a regular way, and when this development is irregular because of the difference over time which take place in a living brain.

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In the last decade a different technique, called DTI or diffusion tensor imaging (see box) is used to study the brain at the network level, instead of the cell-level. This networklevel approach means it is now possible to study not only what parts of the brain are active, but also how parts of the brain are connected to each other by nerves and in which way they work together. This method is based on measuring the diffusion of water molecules in the brain. The assumption is made that water molecules diffuse in MRI: Magnetism again leads the way the brain by following the path with the least resistance, since the passing of a molecule through a membrane (such as the cell wall of a nerve cell) needs more energy when compared to just moving in parallel to it. This means that when the movement of these molecules is tracked through the brain, you are actually viewing a 3D-map of the nerves in the brain. The measurement of these connections however does not, or maybe not yet, imply these connections are also used.


The classical way to measure how our brain works is to use fMRI (functional MRI). In a nutshell this technique measures the activity of the brain cells and their respective regions by measuring difference in magnetization between oxygen-rich and oxygenpoor blood. In measuring this characteristic it is possible to see where brain activity is high and low, since it is presumed the brain cells need oxygen when they have to perform an action. This means a specific task performed by a test subject (function) is linked to certain parts of the brain becoming more active. Hence the name: functional MRI.

Brain imaging HMI

At the moment it is presupposed that diseases like autism and ADHD are caused by early developmental problems which occur in the brain of the patient. If these developmental problems can be measured directly by their specific characteristics it is possible to describe ‘biomarkers’ for problems in the brain. A classic classic example of the development of biomarkers is the usage of certain traceable elements to see what is located at which part in the body. Developing biomarkers for brain diseases case is somewhat different, since the scientists are looking for a certain ‘signature change’ in the brain which presupposes a condition in the future. This ‘signature change’ is what is referred to as the biomarker in this case. If for example the state of the brain connections has deviated from a ‘standard’ Simplified representation of research performed pattern in a specific way, this deviation can be associated with developing ADHD. This reliable measurement of the brain itself has the advantage of at the Donders”Institute making a more reliable diagnose; not the behavior of the patient is used as the research object; but the physical state of the patient’s mind. This leads to improved reliability of diagnose because an external observer, such as a physician or psychiatrist, cannot be precise when judging symptoms in comparison with a scan of the brain’s connections and their development. A step further down the road for easy and reliable diagnosis of psychiatric diseases which is also undertaken at the Donders’ Institute is the description of genetic biomarkers for a specific brain structure deviation. This can ultimately lead to the specific genes or gene characteristics which cause the development of psychiatric diseases at a later age of the patient. Advantages of using biomarkers compared to scans is the lower impact on the patient (no need to go into scanner), and also the possibility of lower costs (no patient has to spend time in a facility). In the future it might even be normal to scan everyone’s DNA for defects leading to problems as we get older.

The researcher One of the researchers who are active in this study of the connectivity and organization of the brain, is Marcel Zwiers, a physicist. He is specialized in developing image processing software, which enables him to structurally make sense of the data which are being generated by the MRI-scanners at the institute. His aim is to help find the physical cause in the brain which leads to psychiatric diseases, specifically ADHD and autism.


His research focuses currently on two sets of subjects, patients who have been diagnosed with ADHD, and the general healthy population. His current research practice is to make a comparison between the genetic makeup and brain scans of the regular healthy public, and the genetic makeup and brain scans of patients which have been diagnosed with ADHD. It is assumed ADHD patients have a structure of brain connections which are different when compared to the regular healthy subjects. The ultimate aim of the researchers is to find a clearly measurable link between the ADHD-patients’ genetic makeup and their brain connections. The specific challenge Marcel is facing lies in the reliable diagnose of the dysfunctional brain. The classical way in which interpretation of a brain scan is performed relies upon a radiologist who uses his experience and subjective judgment skills to infer problems in the brain. This is not possible with scans of patients which have a psychiatric disease because “You see nothing”, as Marcel explains. The differences between a brain scan of a healthy patient and a psychiatrically diseased patient are too subtle to be noticed by a human judge. So the actual problem Marcel is trying to solve is to move the problems associated with ADHD and autism from the field of psychiatry to the field of neurology, enabling better diagnose, and perhaps treatment at the source of the problem. At the moment the biggest problem in achieving this goal of transferring the treatment from the psychiatry to neurology is of a technical nature. The state-of-the-art knowledge is not specific enough to help determine what parts of the brain connections are supposed to be different for patients and healthy subjects. Causes for this lack of knowledge are to be found in insufficient resolution of the scanned images and the limited scan time per patient in clinical and research practice. For example, at the Donders’ Institute scans take up to one hour, and is primarily limited by the time a patient can spend in the scanner. In clinical practice this time would be too long and twenty minutes are the longest time a patient spends in a commercial MRI scanner. This problem is now being addressed by using large groups of healthy subjects and diagnosed patients to build a database with brain scans. This forms the data set upon which statistical techniques and the software developed by Marcel will finally be able to distinguish a healthy brain from a psychiatrically diseased one

So? The specific mechanism which enables our brain to perform all of its tasks is slowly being disentangled by skilled researchers and advanced techniques. Using the principle of magnetic resonance imaging and diffusion tensor imaging in particular the blueprint and final workings of this mechanism is becoming clearer. This information allows for researchers to locate specific problems in the process of making the mechanism from the blueprint. In the future it might therefore be possible to look at DNA to reliably predict what is going to happen in the development of a subjects’ brain. This allows for development of reliable diagnose and perhaps treatment of malfunctions related to this brain mechanism, such as ADHD and autism. However; big hurdles have to be taken and a lot of time, funding and effort is needed to reach this goal

Written by Tom van Eerde

Disentangling the hidden structure

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Sources: Blinowska, K., #252, ller-Putz, G., Kaiser, V., Astolfi, L., Vanderperren, K., . . . Lemieux, L. (2009). Multimodal Imaging of Human Brain Activity: Rational, Biophysical Aspects and Modes of Integration. Computational Intelligence and Neuroscience, 2009. doi: 10.1155/2009/813607

Harshman, R. A., & Lundy, M. E. (1994). PARAFAC: Parallel factor analysis. Computational Statistics & Data Analysis, 18(1), 39-72. doi: 10.1016/0167-9473(94)90132-5 Honey, G., & Bullmore, E. (2004). Human pharmacological MRI. Trends in Pharmacological Sciences, 25(7), 366-374. doi: 10.1016/j. tips.2004.05.009 Lasserre, J. A., Bishop, C. M., & Minka, T. P. (2006, 17-22 June 2006). Principled Hybrids of Generative and Discriminative Models. Paper presented at the Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on.

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Eerde, T.L. van, & Burdick, M., personal communication with Marcel Zwiers, October 5, 2012)

Rifai, N., Gillette, M. A., & Carr, S. A. (2006). Protein biomarker discovery and validation: the long and uncertain path to clinical utility. [10.1038/ nbt1235]. Nat Biotech, 24(8), 971-983. Ulusoy, I., & Bishop, C. M. (2005, 20-25 June 2005). Generative versus discriminative methods for object recognition. Paper presented at the Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on. Vasilescu, M., & Terzopoulos, D. (2007). Multilinear (Tensor) ICA and Dimensionality Reduction

HMI Reflection

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Imaging genetics is a new technique which combines genetic testing and neuroimaging to create new research possibilities for understanding some of the most complex neurological diseases. Imaging genetics is an emerging field likely to grow as it shows promise at explaining psychiatric diseases, for example depression, ADHD, and Alzheimer’s just to name a few. As with any emerging field, research limitations still exist but there is already uncertainty as to whether the world is ready for such powerful genetic diagnostics (Toga, 2005). Janita Bralten, working out of the Donder’s Institute, is at the forefront of research in imaging genetics. Specifically, she investigates the causes of ADHD and Alzheimer’s disease, “The medications that are out now for Alzheimer’s disease and ADHD are not solving the problem… By understanding what’s going on you might be able to solve it or prevent it.” Imaging genetics puts a new tool in the researcher’s belt, which Bralten believes will be important for understanding the diseases. She explained, “by adding a genetic component you can more easily see the biological mechanisms of what is going on” (2). This genetic information provides doctors with information about a patient’s possible disposition toward a certain disease. Imaging genetics takes two parts: genetics and neuroimaging. The genetic component gives information about which genes involved in a specific system in a patient’s brain. “The largest problem we face is that the impact [of single gene variation] is so small you would need hundreds of thousands of individuals… so you have to find other ways to find genetics variance and that is why we try to make biological units to investigate those instead of all the variation that’s out there.” This means gaining an understanding of which brain systems are involved with certain diseases. “We know some of the main steps. We know, for example, dopamine [is involved] and medication can get rid of some symptoms but what is going on from developmental stages on, we are not at the end result.”


Brain imaging



The dopamine pathway is disrupted in ADHD while serotonin is involved in Parkinson’s disease (5).

The neuroimaging component involves using the genetic research to know which parts of the brain to investigate. Brain structure differs in measurable ways between people and groups; these differences define a brain’s phenotype. “My research is a step toward the functional so I would find genetic variance that influences a specific brain phenotype.” Using a specific person’s genetic data and their brain phenotype, Bralten can begin to piece together how the two correlate. “So one [genetic] variant alone might not do anything but many of these together might, or gene-gene interactions, which is now a hot topic, or gene-environment interactions.” Once a set of genes is correlated with a difference in brain structure the research moves into a new phase. “The next step is to test, functionally, what if this and this genetic variant is changed what do we see… Then when the functional work is done, the next step is to see how can I influence it.” (4)

Pink shows similarity while blue shows differences in brain structure of identical vs. Fraternal Twins (3).

Research of this kind has many implications for brain research both in short-term and more distant future: “There are several years of research already done trying to get to the genetics of some specific disorder like ADHD and it’s just not working out because it just too complex. So you need some steps in between to get to what’s going on. And maybe page 18 - Neurotics Magazine - first and only issue

Brain imaging

even new diagnostic subtypes of disorders based on imaging or genetics.” This would include a reorganization of how mental diseases are grouped and diagnosed. Several things also work to limit the current reach of imaging genetics research. “One of the limitations is computer space. If you run a really large analysis you need different computers because normal computers cannot handle the analysis. So we have access to a cluster computer in Amsterdam…” A second major limitation is money, “We make MRIs of individuals and that’s a costly thing.” With new investments coming from industry more and more often, Janita sees this as a good thing: “I think it’s quite good. More information can go out to the public about what you’re doing.” As well, industry opens other new avenues for revenues “One of the things they might do in this department is to get the next generation sequencing as a commercial product out there.” The last concern Janita expressed about the future of her type of research was about the public’s knowledge of science. “The gap between science and the normal public can be large because they don’t know what can happen if they sequence their whole genome in ten years; do they know what it actually means if a variant is found.” Understanding these highly technical procedures can help non-experts know what results do and don’t mean. Written by Mark Burdick References:

(1) Toga, Arthur; Thompson, Paul. (2005). Genetics of Brain Structure and Intelligence. Annul Review Neuroscience. Vol. 28:1–23. doi: 10.1146/ annurev.neuro.28.061604.135655 (2)

Bralten, Janita. Personal Interview. 5 October, 2012 Review Neuroscience. Vol. 28:1–23. doi: 10.1146/ an-


(3) Genetics of Brain Structure and Intelligence. (2005). [graphic] Annul nurev.neuro.28.061604.135655

(4) Bralten, Janita. (2011). Association of the Alzheimer’s gene SORL1 with hippocampal volume in young, healthy adults. American Journal of Psychiatry; 168,10:1083-9 doi: 21730226 (5) Dopamine & Serotonin Pathways. (2005). [graphic illustration] American Author. 2012 Retrieved php?page_


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CASE 2: HUMAN MEDIA INTERACTION Introduction Nowadays, human-computer relations and interactions are crucial for every field of human existence. In their many realizations, they combine present knowledge from neurosciences and the state-of-art of engineering and information technologies. Communication with and through computers and other intelligent agents have become a normal part in our lives and therefore influence our social, political and personal behavior; but their own development and use are also vice versa influenced by such factors. Due to this, understanding the physiology and technology alone does not do justice to issues about how the interaction is and should be performed. Questions which arise are for example: How do people react to non-human agents and how can the cooperation between the two be improved, satisfying human needs? Do mental protheses really improve the life of so-called “locked-in patients�? How and why do people use new technologies and how can they be designed to make the interaction joyful and practical?



Astoundingly, at first sight it seems as if the significance of the new research fields for the social sciences, which the progress of the natural and engineering sciences in the realm poses, is underrated by many scientists from both disciplines. Due to false estimations, social scientists are not as much involved in the research as might be needed - hence they are often also not aware of what is going on and where their important tasks might lie. However, at the University of Twente in Enschede, Netherlands social scientists are involved in the research - even though they are still hard to find among physicists and engineers.

At Twente, a group of researchers working in the field of Human Media Interaction is located within the Department of Electrical Engineering, Mathematics and Computer Science (EEMCS). In its research on the interaction with technological devices, mainly computers, the group focuses on tools that present users with information and allow them to manipulate and command a machine. Parts of their work are the development and improvement of tools to analyze human behavior, the improvement of technologies in a way that they fulfill human needs and the creation of virtual surroundings for social experiments. An example is the Social Mirror showcase, a virtual surrounding which allows members of a group to visualize their behavior within the group and successfully reflect on it. Other applications on which the HMI group works are speech detection systems, which can identify social structures, intelligent video conference systems or persuasive technologies which aim at changing behavior patterns, for example motivate children to move more. In all their projects, their main concerns are how humans interact with technology, how interfaces can be build which are understandable and intuitive and which help and support users in a way that the technology itself remains in the background and stays invisible. Therefore, their work involves an amazing broadness of sciences and disciplinary fields; it interdisciplinary connects technological research to different social sciences such as psychology and sociology. Neurotics journalists have traced the social scientists involved in the group and spoke to them about the aims and methods of their research on different topics and the role of social sciences in this technical world.

Sources Personal conversation with Professor Kees Aarts, Scientific Director of the Institute for Innovation and Governance Studies (IGS) at the University of Twente


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What is Social Research?

Social research refers to research performed by social scientists which aims at producing generalizations about social life. While such generalizations are the most fundamental goal of social research, there are many other more specific goals that contribute to this larger goal. First of all, social research seeks to identify general social patterns and relationships through examination of many comparable social situations or cases. Secondly, it aims to improve and expand the pool of ideas known as theories by testing their implications with the collected data (for example, with statistical data published by government agencies) that bear directly on the theory. The third goal is to make prediction about the future using accumulated social scientific knowledge in the field of history (past successes and failures) and knowledge of general patterns (Ragin, 1994).

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Social science is the scientific study of human actions with focus on elements of thought and behavior that are in some degree social (nonbiological). Source? Is this a quote?

There are two basic social research strategies, which are used in order to achieve the goals above. Qualitative research seeks to understand a given social phenomena from the perspectives of people it involves. It is especially effective in obtaining culturally specific information about the values, opinions, behaviors, and social contexts of particular populations. Quantitative research aims to confirm hypotheses about social phenomena by statistical analysis. It is used in order to quantify variation, predict causal relationships and describe characteristics of a population (Mack, Woodsong, 2005).


Written by Anna Kostenko References: -Atasha Mack,Cynhia Woosong, 2005. Qualitative Research Methods Qualitative Research Methods: A Data Collector’s Field Guide - Charles Ragin, 1994.Constructing Social Research: The Unity and Diversity of Method


The Game Brain Computer Interfaces (BCI’s) are applications which establish a direct communication between neuronal activities or evoked brain signals and a computer. Through EEG technologies, neuronal potentials, which indicate a certain brain activity, are used to command a computer or program. The imagination of a particular movement for example can represent a certain command. Thus, BCI’s do not work with one-to-one translation of ‘thoughts’ and require user training, so-called neurofeedback training. But not only the user, also the program has to be trained - it has to be able to adjust to a specific user, since brain signals differ from person to person and from day to day. There is a lot of research done on the subject, but still BCI’s haven really gotten out of the lab. The applications are often bound to a big technological effort; their use requires a long training and the results are not as stable or predictable.

Brain computer interfaces allow users to control devices through brain signals

Most BCI’s are meant for medical applications in rehabilitation trainings or to help locked-in patients to communicate or steer a wheel chair. Locked-in patients are people who, due to disabilities, are not able to communicate or interact with the world through usual bodily output channels such as speech or movement. But unfortunately, in most cases, BCI’s in medical applications fail to work completely accurate and do not improve the quality of life of page 21 - Neurotics Magazine - first and only issue

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the patients. Especially in critical applications - applications which require a definite yes-or-no answer - unpredictability poses a big problem. Neurons and brain signals are constantly changing; measured signals are only read correctly in approximately 80 percent of the cases.

Forced to deal with this issue, the Brain Computer Interaction group in the HMI department at Twente has decided to make a challenge out of the problem. They are developing applications for ‘abled’ users, namely gamers. The group feels that there is a big public interest in the topic, thus they focus on user experiences and turn the problem of unreliability into a fun factor, posing exciting challenges in computer games. For the famous online game World of Warcraft, played by millions of people around the world, they have developed a new BCI application. Through measuring brain activity with an EEG cap, the gamer can control transformations of his avatar through her mental states. Different moods imply different transformations; signals correlated with relaxation transform the player into an elf, signals correlated with aggression transform her into a wolf. The fact that these transformations do not always work makes it a challenge, since total predictability in a game is boring anyways. But BCI applications in games can also be a way to adjust the level of the game to the user’s experience and in this way keep her in the ‘flow’ of the game.



The Player Researcher Dr. Femke Nijboer is part of the BCI group. She is Amyotrophic Lateral Sclerosis (ALS) a real cross-over and has always worked in-between the disALS is a muscle disease caused by neuronal degenciplines. Originally, she studied experimental psychology and eration in the brain’s motor system. In the course earned her doctor’s degree in neuro and behavioral sciences. of the disease, patients more and more lose conThere, her task was to apply neurosciences in technology, trol over all their body functions, while the mind which eventually lead her to brain computer interfaces. For six still works as usual. People suffering from severe years she regularly went to the homes of locked-in patients ALS syndromes are imprisoned in their own body suffering from amyotrophic lateral sclerosis (ALS) and tried BCI and in a late stage can, if at all, only communicate technologies out with them – often being disappointed by the through eye movements. After 3-5 years, most bad results. In an interview with Neurotics, she explained the victims of ALS die from consequences of respiradifferent expertise her work required. She needed engineering tory system failures. The cause of the disease it unexpertise, because she had to make the technical system work; known until today, there is no effective treatment neuroscience expertise, because she had to be able classify the available. different mental states from the EEG measurements; psychology expertise, because she had to investigate how psychological factors such as motivation or depression influence BCI use and nervenlaehmung-als-eingesperrt-im-eigenenresults and finally medical expertise, because she also investikoerper-a-564501.html gated the quality of life of patients and the relation between h t t p : / / w w w. s c i e l o . b r / p d f / a n p / v 6 7 n 3 a / ALS and depression. Nijboer seems to be an all round talent v67n3aa40.pdf and sees herself working from both sides, from the engineering and the psychology perspective; her general interest lies in the connection between brain activity and output behavior. In the BCI group, she is involved in the research around user experiences of brain-computer interactions and the development of game applications. Thus, she brings to the mainly technical surrounding her practical know-how and a social science flavor, namely psychological expertise. Her newest project is the investigation of legal and ethical aspects of BCI technologies; for this research project she recently won the Dutch Vendi grant. Her motivation is her impression that there is a little bubble of BCI scientists who are doing their best to improve the technology; but still, BCI’s do not really seem to work and they are difficult to get “to the real world”. Furthermore, she wants to find out what “all the neurosciences mean in our society”. She feels we are steering towards a perception of ourselves where our whole life is structured around brain signals and structures – there is an overwhelming focus on technology which promotes a forgetting about the role of social factors in human behavior.

The Rules Experimental psychologist and BCI expert Femke Nijboer

Being a psychologist and social scientist, Nijboer mainly works with engineers from computer or electrical sciences. She thinks that, even though the HMI department is also concerned with how social sciences connect to technology and thus is “the least informatics department in the faculty”, the tasks of the social sciences are underrated and social scientists are more and more replaced by hardcore engineers. There seems to be too much emphasis on algorithms and machine learning and not enough focus on the user’s experience and skills.

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Even though she knows both approaches, the social science and the engineering one, her account of the different discipline represents a commonly held view. Asked what social sciences are for her, she says: “I guess social sciences are all the sciences that don’t use mathematics.” As she sees it, the sciences using mathematics are capable of having universal laws which always apply; they can find certainty or proof and thus make statements about ‘truth’ - social sciences can only support or reject hypotheses, but never prove or disprove them. Their methodology starts with either the study of literature or with big amounts of data from observations. Then, a hypothesis is derived and an experiment to test it is designed. The results of the experiment either support or speak against the hypothesis, but they can never label it as right or wrong, only as likely or unlikely to be true. For her, this also is the reason why many people tend to think social science in a sense are not ‘real’ sciences.

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When working together, the different backgrounds of the scientists become most obvious in different vocabulary and a different way of looking at how science should work – Nijboer sees psychology or social sciences in general as a more rigorous way of doing science, because they work mainly with theories and models - engineers on the contrary seem concentrate more on “fixing things” – their work is data driven and they do not tend to use models as much. In BCI technologies, this also makes sense due to the fact that there is hardly any theory about them. The research is solely applied research; the technology only “needs to work”. But due to her background, Nijboer herself still uses social science and psychology methods in her work; tools like questionnaires and observations are needed in evaluating user experiences.

The Goal

In the HMI department, the future of the Brain Computer Interaction group seems unclear at the moment. The PhD’s who worked in the field for a long time are not able to find grants to continue their research, thus Nijboer is concerned that with them their knowledge will disappear. They are trying their best to get new grant on an EU level, but it has become difficult. “Brussels does not believe in [non-invasive] BCI’s anymore”, she explains. A reason is that research in the US, which in comparison to most European methods often works with invasive brain implants, is already much more advanced.

Written by Laura Fichtner Sources: Personal interview with Dr. Femke Nijboer Boris Reuderink, A. N. (2009). Affective Pacman: A Frustrating Game for Brain-Computer Interface Experiments. A. Nijholt, D. Reidsma, and H. Hondorp (Eds.): INTETAIN 2009 , 221-227. Nijholt, A. (2008). BCI for Games: A ‘State of the Art’ Survey. S.M. Stevens and S. Saldamarco (Eds.) ICEC 2008 , 225-228. page 23 - Neurotics Magazine - first and only issue


Femke Nijboer though sees the future of (non-invasive) BCI’s critical. She doubts they will ever be a serious alternative to other medical applications. Still, they have one big advantage in neuroscience and psychology research - they allow to measure brain activity and also to adapt experiments in real time. In normal MRI scanners, this possibility is not given, because images are always only analyzed afterwards.


The goal in using BCI’s in game applications is not only to provide extra challenges. They give researchers more freedom to try new ideas and approaches out – working with ‘disabled’ users always brings about limitations, since their condition has to be considered much more. Furthermore, using gamers for experiments in new fields has several advantages, because they are “early adaptors. They are quite happy to play with technology, to accept that strong efforts have to be made in order to get minimal advantage, and they are used to the fact that games have to be mastered by training, allowing them to go from one level to Using mental states, players can transform to different characters in the game the next level and to get a higher ranking than their competitors. Moreover, there are enormous numbers of gamers. Having advantage by being the first to introduce a new type of game or a new game element may bring game companies enormous profits. This certainly is an impetus to invest in research and development in brain-computer interfacing.” (Nijholt, 2008) In another experiment, the influence of frustration on BCI signals is tested with the help of an advanced version of the ‘Pacman’. The researches secretly build random malfunctioning of devices into the game and then measure how frustration evoked through poorly working devices influence BCI signals and applications. (Boris Reuderink, 2009)

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HUMAN FACTORS Intro Human factors (also known as ergonomics) research is concerned with making interaction with computers and technological artifacts more seamless and intuitive. Researchers in this field concentrate on how people interact with an environment or object to make a design more suited toward human use. Work in this field often includes combining data, experiment designs, and analysis techniques from psychology and sociology with the design and engineering of components or interfaces. Examples of ergonomics are everywhere from the design of car dashboards to the handles of household tools. Some important parameters human factors researchers investigate are environmental, organizational, physical, cognitive, social and others but the three biggest fields within ergonomics concentrate on either physical, cognitive, or organization ergonomics. Physical ergonomics are mostly concerned with anatomical, biochemical, and physiological properties and limitations while cognitive ergonomics covers memory, perception, motor, and reasoning abilities. Organizational ergonomics looks at sociotechnical systems to improve policies and processes.


Social sciences play an important role in human factors research. Often, the first step includes the production of a physical model then a study is designed to show how the artifact is actually used. Data is collected that can show unintended use patterns; from this data, the artifact can be reengineered to better suit the users. Experiment design and analysis is done through techniques developed in the social sciences to study human behavior; practitioners of ergonomics takes the extra step of using these findings to alter the design of a product or organization. At Twente University’s Human Media Interaction group, human factors research helps to inform several project teams of ways to improve the design of their system. The team’s main concern is to find new ways for people to communicate with computer applications. This research often starts with people going into the field to observe a certain setting. For example, the HMI group at Twente have studied setting such as playgrounds or zoos both in person and through reading literature from the social sciences on these locations. Following this, a model version is made. In the case of the zoo, this meant designing a robot to guide people on tours. In making a virtual playground, projectors shine light on the ground depending on the behaviors of children. In both cases, data was gathered about user reaction to help inform future versions. These data gathering techniques can range from simply observing how people react to different variations of the model (as in the case of the robot guide) to compiling information about the position and speed of kids playing (as in the case of the virtual playground).


The collaboration between engineering and social sciences has been changing as Betsy van Dijk, who started the human factors group at Twente, explained.

Written by Mark Burdick

Sources: (1)

Salvendy, Gavriel. (2012). Handbook of Human Factors and Ergonomics. John Wiley & Sons inc.

Hoboken, NJ (2)

Interview with Betsy van Dijk

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Last decade has seen new policy for funding research in universities. Where universities used to be funded by the government and decided themselves what to do with the funding, policies have now changed. Often researchers have to present their plan in order to be eligible for a grant, and companies have a big say in providing these grants. It is argued this leads to more applied research performed in universities; often defined as research with a certain technical application in mind when it commences. In this process of developing an application often a transition has to be made in order to let technology make sense in the social world. This demands for a collaboration between the engineering and social sciences. To gain more insight into these transitions the Neurotics interviewed Vanessa Evers, member of the human media interaction group. The interview is presented below and afterwards a short reflection on how this transition works and what the differences are in methods for engineering research and social research will be discussed.

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Interview Vanessa Evers, working for the human media interaction group. -


Subject of interview: “The role of social sciences in engineering research” How is the HMI group structured in the university and could you explain how this came to be?

The group started as an entity twenty-five years ago and was focused on the theoretical part of the new discipline of computer science. The first members of the group were primarily physicists and mathematicians, since the work was very technical. Slowly the work became more oriented towards the design of interaction, natural language & speech recognition, and information retrieval & interaction. Nowadays we are occupied with subjects which relate to interfaces, such as interface design, virtual agents and virtual environments. This is primarily because the leader of our group has developed an interest into these fields, and this has been put into practice by focusing on these subjects in order to attract funding. As a result only the members who are interested in these topics have stayed in HMI, and others have left the group. -

You know what the HMI research is about, what is the role of social sciences in this research?

Furthermore we generate system behaviors in our department. HMI has developed an engine in order to generate such behaviors, called Elckerlyc. This engine plans and executes virtual agent behavior. We attempt to actually program social behavior into a computer system. In order for this system to work properly, it is also necessary to detect a human presence and interact with it in a ‘normal’ social way. This requires quite a lot of machine learning because different behaviors take place at the same time; such as speech, facial expression and movement of the body. This is related to social research since we are using machines to emulate social behavior, and therefore have to know this behavior. Finally there is research focused on evaluation. In this research we put humans into situations in which they have to interact with machines such as robots or virtual playgrounds. The designs of these studies are taken out of the field of social and psychological research. -

How does the collaboration work between social sciences and engineering sciences?

I would say the HMI group is situated right in-between the social sciences and the engineering sciences, and is some sort of translator between the sciences. This is because we all have a multidisciplinary approach in the HMIgroup, which is not always the standard case in other research groups. We can thus interpret and explain between the groups which are focused on the social sciences and groups which focus on engineering. -

Does the HMI-group also employ people who do not have a technical background?

Yes, however most of us have had at least a few technical subjects finished. There are a few linguists in the group, and 25 years ago this used to be a very technical subject. Now however ‘real’ technical people would not think this page 25 - Neurotics Magazine - first and only issue


There are three research lines which touch with the social sciences. First there is interpretation of produced material, for example video and audio but also measured brain activity. The aim here is to figure out what happened on basis of such an input, for example derive someone’s emotional state based upon video material. Also the nature of the interaction which often takes place is interpreted here, to see in which context the subjects are acting. Examples are: Are they family or not?; are they on friendly terms to each other? etc. This is a social aspect because the context of a social situation is being interpreted.

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is very technical anymore because the nature of the field has changed. Besides linguists we also have people with a background in design, and even someone with a media and communication background. - You are doing research about technologies which are supposed to interact with humans, but the research about behavior is not taking place in the HMI-group, but taken from other groups instead. Could you say something about this relationship? Often we do not know how the social world operates, I will give an example. We have developed robots for use at Schiphol airport to assist people not to miss their flights. These robots would come in the form of intelligent cars that should be able to navigate the difficult multicultural environment of the airport independently. This means we have to understand the social environment and context of the airport first, if we want to be able to program a robot correctly. Examples of this should be that robots do not attempt to navigate through families or groups, but go around them instead. For the HMI group this knowledge entails the total understanding of the social fabric which makes up Schiphol airport, and here lies the relationship between the engineering sciences and social sciences. We have to understand the social context of Schiphol airport in its totality order to be able to program rule based normative behavior into the robot.


- In your previous answer you mentioned the importance of knowledge about the social environment of Schiphol airport. How does the HMI group study this environment? We use a special research design for this. First there is a conceptual analysis phase, in order to describe factors which facilitate or hinder a high-quality type of interaction and user space. These are usual qualitative style studies. This information is used in order to develop and design the first prototypes, which can be used for evaluation purposes. This is where the process moves to a more quantitative approach, for example defining how much physical space between a human actor and a robot is considered to be optimal. We establish this distance by using experiments between human actors and prototype robots. So we start with qualitative data, and during the development we switch to quantitative data in order to be able to finish a design. -

To what extent does social science play a role in the development of virtual agents?

Well there are a few members specialized in the social side of this field, we have someone who is doing research on the topic of virtual humans, also there is someone who focuses on generating behavior for these kind of entities. One example of where social science practice comes in is the development of a method for interaction aimed severely mentally handicapped persons. Often these persons have almost no way of interacting with the world around them. For this group it is already very interesting to be able to roll a virtual ball to their parents and receive it back. This is a type of problem which requires study of their behavior before we can even attempt to come up with a technical solution.



You mentioned the research in multi-modal interaction, where is the social part in this research?

Multi modal interaction aims to use different sources of data to make the same inference. For example listening to audio and watch the facial expression of the same person, and decide the emotional state of this person based upon the combined data. The social part of this research lies in the interpretation of the different kinds of information retrieval. We are trying to use multi modal interaction in order to derive the context or intentions of agents. For example detect whether someone is angry in an audio recording. - The funding strategy of the Dutch government has changed towards a more practical applied model. Could you explain what this means for your work? Of course I have never worked in the ‘old’ situation, and I am used to the current way of doing research. I do however think that classical fundamental research performed in the past by for example Niels Bohr is not possible today. This because no scientist spends months and months of time in refining experiments and coming up with brilliant solutions, simply because even if such a scientist would exist there is no funding for it. If such a scientist would want to have funding, he would have to write the proposals himself, and thus no time is left for the actual research itself. In practice this means other people, such as PhD students, are hired to perform the actual research itself. This practice is very similar to the way consultancy firms solve problems in companies, my job in the university here is actually quite similar to the job as a consultant I used to have. - On what field lies the biggest challenge for the HMI group at the moment (for example in the research itself, the funding or something else) I think the most important challenge for the HMI-group is to continuously keep improving the research and increase the quality. In practice this means doing projects, and of course these projects need money in order to run. This facilitates the process of delivering excellent research with high quality. We want to deliver the best educated students which are available. Also our scientific work has to be relevant, this is sometimes hard to motivate to external people. I believe the continuous development of new technology makes our life better. And this does not have to be purely money-based.

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In the interview above the Neurotics attempted to establish where engineering research, social research and technical applications meet in practice. In the process of developing technical solutions for social problems - for example the problem that people get lost at Schiphol airport - different questions have to be answered in order to develop a solution. The primary problem of people getting lost is considered by the HMI department solvable by developing a technical product. Technical solutions for social problems require a multidisciplinary approach because hurdles are to be expected in engineering sciences (how does the physical word operate); social sciences (how do humans interact) and technical application (how do we develop a technical solution by making use of our social and engineering knowledge).

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So: What is the problem?

Social sciences – focused at studying human behavior - provide a different type of knowledge compared to the engineering sciences; which are focused at the behavior of nature . Both sciences focus on the systematic empirical approach towards their research object, however where quantitative (numerical) methods are accepted in engineering sciences; in social sciences it is still a topic of debate whether this is feasible; and scientists have opted to use qualitative data instead.


This (generalized) difference is important because it leaves room for a choice when developing a technological product. Either the social environment has to be described using quantitative methods, or the qualitative data need to be translated to quantitative data for use in a technological product, which operates in a quantified way. This is exactly where both types of data meet in the HMI department; application in a product. The interviewee also confirmed this because they have to perform a slow transformation from qualitative to quantitative data in order to make the end product work in a desired manner.

‘Can we solve this problem?’

Written and edited by Tom van Eerde Sources: Interview with Vanessa Evers in collaboration with Mark Burdic and Anna Kostenko Ladyman, J. (2001). Understanding philosophy of science: Routledge.

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The research and development practice described above is not new, and current practice is not unsuccessful. A quick view in where technology is successfully integrated in our world merely confirms this. The developments in cognitive neuroscience described in part one of the magazine leave room for a new way of quantified research in the social domain. That is why it is such an exciting new field. By directly studying the brain a lot of research problems in social science are addressed such as measurement bias (subjects influence the research because they know they are in the research) and measurement method comparability (every MRI-scanner of the same design delivers the same results. If the possibility of proper undisputed quantitative research in the social world becomes possible this thus improves the possibility of integrating technology into our life. This possibly just leaves us at the question whether we should want this. These type of questions are addressed in the last part of the Neurotics magazine.


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PHILOSOPHICAL REFLECTION A Reflection: Inevitable or Superfluous? Justifying a Need for Philosophy in Neurosciences Introduction In the last decades, the neurosciences experienced an explosive growth. This is largely due to the emergence of new measurement techniques such as neuroimaging (fMRI, DTI, SPECT) and imaging genetics. Consequently, we are witnessing a profound change in our understanding of mental activities today. We came from a state of total ignorance about brain states into a time where high resolution measurements of brain activities and even brain – computer interfaces are possible. The first two sections of this edition of the Neurotics looked at different sciences working with and on these developments. Going out and talking to those scientists who are passionate about their research on neuroscience’s techniques was a wonderful and exciting experience. We sincerely hope that we could share our enthusiasm with the faithful Neurotics reader. But as she already suspected, descriptions alone can never satisfy the philosophical soul. Hence our Neurotics team couldn’t but wonder how what we experienced in our research could be evaluated with the help of a Philosophy of Science, Technology and Society. We understand ourselves as a magazine which aims at bringing science closer to those who care, but also at reflecting on what is going on. And this is what we do in our last part. Our journalists have taken what they learned from the scientists and put it in a wider context. They approach the case from three ankles: an epistemic, an anthropological and an ethical one. All three parts address completely different questions and have gotten their attention and place. They shall be presented here shortly:

1. Anthropology and Human Self-Understanding Undoubtedly, the knowledge of the functional mechanisms underlying our mental life changed our understanding of the self. While during the Enlightenment era a human being was considered a spiritual being, consisting of an immaterial soul and spatial body, nowadays we are getting more and more evidence that at least a part of our consciousness can be explained in terms of physiological processes. A question which arises here are is for instance: in how far are we and our rationality distinct from mere machines? In the age of neurosciences, can there be something non-material about our mental life? These and similar questions are addressed in the column about the idea of The Fourth Discontinuity. Furthermore, it also provides the reader with some ideas about why asking such questions is necessary.


2. Epistemology and the Creation of Scientific Knowledge Neuroimaging techniques play an essential role in the generation of scientific knowledge. MRI scanners, for example, produce images of the human brain that are used further in scientific inquiries. Evidently, without neuroimaging contemporary neuroscience would not even be possible. But how are technological instruments involved in scientific research? What specific role do they play? What is their influence on how scientists ‘see’ a human body? To answer these questions we analyze neuroscience technology in terms of Don Ihde’s theory of Mediated Experience.

3. Ethical Issues from a Kantian Perspective Since neuroimaging provides us with insight into the workings of the human brain, it can also provide insight into moral behaviors. Kant’s meta-ethical perspective details a possibly undetectable aspect of the human mind that he says is required for morality to exist at all. If neuroimaging doesn’t find a noumenal part of the brain unaffected by our experiences or genetics, what does it mean for morals and how we hold each other accountable?

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Most of us would agree that we live in a technological epoch. In our everyday life we are surrounded with tremendous diversity of technological artefacts ranged from the simplest, like a knife or a bike, to complex technological systems, like nuclear power plants or space aircrafts. We feel that these things play an important role in our lives, inasmuch we may notice that our interactions with other people depends on computers and cells, our health state – on medical instruments and our ability to travel is bound up with automobiles.


When it comes to science the significance of technological artefacts instruments, laboratory equipment, appliances - becomes even more evident. Can you imagine astronomy without telescopes or biology without microscopes? What would scholars study if they could not even see the Is the scientific understanding of the world mediated by technologies? object of their studies? Evidently, the fact that modern scientific studies require instruments goes without saying. As, it is rather impossible to (from imagine contemporary neuroscience without neuroimaging instruments. Today neuroscientists are exploring the brain structure and neural activities underlining mental states, thanks to neuroimaging technologies. So scientific understanding of brain systems and processes is, to a great extent, built upon the data produced by devices such as fMRI scanners. It could be said that a scientific observation is under the influence of scientific instruments, which provide them with an access to the objects of their interest.

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Although most of us would admit that scientific instruments are important for a scientific research, we usually do not question their specific role a lot. We hardly ever ponder of how uses of these instruments influence on scientific experience. How they contribute to knowledge generated by scientists. However, neurotic journalists believe that those philosophical questions deserve to be addressed and answers on them would contribute significantly to our general understanding of how scientists generate knowledge and what makes them able to do that.

Relations between scientists and instruments Ihde starts from differentiating two dimensions of human’s experience. The first is the sensory perception on the bodily level - microperception. The second dimension is macroperception. It consists of the frameworks (cultural or scientific) within which bodily perception gains its meaning – as brain scans make sense only within neuroimaging scientific community, outside of it they are just some colored pictures. Going further Ihde distinguishes three different ways in which people can perceive the world with the help of technological artifacts: relation of mediation, alternity and background relation.

In the relation of mediation we are not related to our world directly but via a technological artefact, comparable to a perception of the world through glasses. The second kind of relation (alternity) refers to the case where we relate to artefact itself, as for example when some people care about their expensive and beautiful automobile. In the background relation a technological artefact stay in the background (i.e. we do not pay much attention to it) while still shaping our perception of the world. As, for example, does radiator that ‘invisibly’ and automatically, page 29 - Neurotics Magazine - first and only issue


We shall answer those questions using the example of fMRI instruments and applying Don Ihde’s Mediation theory to it. In the heart of this theory is the idea of the meaning of technological artefacts for human relation with the world. It is considered that each time we use a technological artefact we access the world through and by means of it, as we access the world of micro-organisms through a microscope. The term mediation here refers to a way in which a technological artefact influences on the relation between humans and their world. So it is said that artefacts mediate human experience - transform our access to the world in myriad ways, some of which open up to us new things which otherwise would be concealed, as micro-organisms would be concealed if we tried to see them by ‘naked eyes’. We believe that Mediation theory shall enable us to take a fresh approach to scientific instruments nature – think about them not as mere means to scientific ends, but as active and far from being ambivalent contributors of scientific knowledge.

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without human contribution and much attention heats an apartment. In this article we will focus on the relation of mediation, inasmuch fMRI technologies evidently play a role of a mediator between scientists and the area of their study – human brain. Scientists ‘see’ the brain by means and through fMRI scanning as short-sighted people see remote objects through glasses. It is important that micro and macroperception always come together and cannot exist separately. A bodily perception doesn’t make any sense without being interpreted within the particular culture or scientific context. In turn, interpretative frameworks are meaningless without something to interpret. Although micro and macro perceptions are bounded it is important to demarcate them, Don Ihde suggests. Because such a differentiation enables us to track how sensory perception on the bodily level contribute to our general understanding of how the world looks like. So how does this work in case of fMRI? What does fMRI allow scientists to see on microlevel, so what they see enables them to make scientific statements regarding the brain functions on macrolevel?

Mediated perception (micro level)



As it has been mentioned above on microlevel scientists perceive the world via fMRI technological interfaces: they “see” the human brain via fMRI scans. Ihde specifies two basic sets of relations with artifacts in which they mediate human perception: embodiment and hermeneutic. The former refers to the relation with technological artifacts where we use them in order to broad our area of sensibility. In this case technologies are transparent to some extent and do not call attention to themselves. What they do is allow us perceive the world with a minimal distortion, so mediated perception closely resembles unmediated. A good example of embodiment relation is wearing contact lenses – when one wears them, one does not pay attention to them; rather he or she sees the world through them. What is also important here is that the world perceived through contact lenses is the same world that one could perceive by naked eyes if one had good eyesight (Verbeek, 2005).

Fig. 2: This image shows an individual’s brain activation while viewing human movement. The warm colors represent functional magnetic resonance imaging (fMRI) increases to viewing human actions, overlaid on a high-resolution structural MRI scan. (from http://www. )

However, in case of fMRI technologies scientists are involved into another type of relationship – hermeneutic. Hermeneutic from Greek hermneutikos means interpretation. So here hermeneutic relations are relations of interpretations. In hermeneutic relations, we also deal with the world via technological artifact, but it is not transparent any more. Because, in contrast to embodiment, hermeneutic artifact provides a representation of the world, which have to be ‘read’ or interpreted first in order to become meaningful. In hermeneutic relations the world is not perceived through the artifact but by means of it. As we ‘read’ a thermometer in order to determine the temperature. Moreover, according to Ihde laboratory instruments transform hidden, imperceptible phenomena into something that can be observed, by virtue of their hermeneutic mediation. They ‘prepare’ the reality before humans can observe it.

Accordingly, fMRI scanners image metabolic function of the brain. The resulting map of brain activation is presented graphically by color-coding, which indicates the strength of activation across the brain (see Figure 2). However, this image of brain activities is drastically different from how it looks in the reality. In fact, brain activity cannot be seen by naked eyes at all, since on physiological level, it is the electricity produced by neurons. So fMRI scanners represent this electrical activity in a drastically different way – as colored images, which can be used then by the scientists, who know how to translate ‘colors’ into corresponding ‘brain processes’. In other words, fMRI scanners are hermeneutical devices (i.e. technological artefacts, which involve humans to hermeneutic kind of relation with them), which ‘prepare’ the reality in such a way that scientists see what otherwise would be imperceptible – electrical interaction between neurons. According to Don Ihde’s analysis, technological artefacts always transform our perception - i.e, perception through an artifact is always different from naked one. The transformation of perception is defined by amplification and reduction factors. While technological artifacts always strengthen specific aspects of the reality perceived, they at the same time weaken others. When the scientists uses an fMRI scanner in order to study the brain, they can see the brain activities that otherwise would be hidden. At the same time the fMRI scanner limits the perception in a way that scientists cannot see, for example, anatomical structure of the brain, which can be seen by naked eyes during autopsy studies. What is interesting here is that this technological limitation is deliberately built into almost all hermeneutic technologies to take away everything that does not belong to the sphere of particular scientific interest. In other words, fMRI scanner indeed shows brain activity only, but, at the same time, this allows scientists to concentrate on exactly what is important for their particular research. page 30 - Neurotics Magazine - first and only issue

Contemporary science and technologies (macro level)

Don Ihde argues that, nowadays technologies to a large extent determine the development of science, because “contemporary science is helpless without technologically mediated instrumental perceptions” (Ihde, 2001). It is hard to object to that claim, since if we look at science as what scientists do, we find that it is unlikely to conduct any modern research without scientific instruments. How could one study astronomy without a telescope? Or can you imagine the modern biology research without microscope?

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fMRI instruments mediate experience of scientists on bodily, microperception level. In turn, perception of scientists always takes place within macroperceptual framework where it gain its meaning. This framework could be described as the scientific one, e.g. that one in which scientific development takes place. So how does the technological mediation on the micro- level influence science on the macro- level?

That fact that fMRI instruments produce images of brain activity plays a crucial role in the generation of neuroscientific knowledge. In fact, fMRI shows the field of study - electrical interaction within the brain – that scientists would never have known about but for mediating technologies. Hence, it would be impossible to study brain processes without fMRI scanning, inasmuch it is evidently impossible to scrutinize that what is hidden and not perceivable at all!

Written by Anna Kostenko Sources: - 2001. “Don Ihde: The Technological Lifeworld.” In American Philosophy of Technology, ed. H. Achterhuis and trans. R. Crease. Bloomington: Indiana University Press. -2005. “Verbeek, P :What things do: Philosophical reflections on technology, agency and design”. University Park, PA: Penn State University Press.

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In conclusion, scientific knowledge of brain is, to a great extent, coshaped by neuroimaging devices such as fMRI scanners. fMRI instruments mediate scientists’ perception on microlevel, providing a representation of brain activities as color-coding patterns. On the other hand, fMRI scanners narrow down scientific perception in a way that scientists can observe brain activity exclusively, taking away everything unnecessary and allowing scientists to concentrate on the particular study of metabolic brain function. On macrolevel this means that fMRI devices constitute the object studied – brain activity – by adding a visual aspect to initially unobservable phenomena, so it becomes available for scientific inquiry. Thus, neuroscientific knowledge is a product not only of interpretations of the available measurements, but also of fMRI instruments with which scientific observations are carried out.


Going further Don Ihde distinguish two levels of possible impact of scientific instruments on scientific knowledge – so called weak and strong programs. In a weak program instruments create an interface between the reality and science, influencing the scientific interpretation of it. In a strong program instruments seen as a part of the objects studied, they are said to codetermine the content of scientific knowledge. Such instruments reveal unobservable objects and constitute them, so the objects become available for scientific research (Verbeek, 2005). As a fMRI scanner illustrates areas of brain activity as colored patterns. In other words, the fMRI scanner constitutes the phenomena by adding material visibility to it - so brain processing that previously had been invisible has transformed into an object that is being studied in science. Subsequently, this visibility of brain activity enables scientists to do their research and finally produce correspondent scientific knowledge. And now we can clearly track how perception on the micro level contributes to scientific understanding how the brain works. As on bodily level scientists ‘see’ brain scans produced by fMRI, which on macrolevel enables them to make a general conclusion that there are indeed physical processes in the brain, which correspond to what we, ordinary people, sometimes call mental or intellectual activity.

Brain imaging HMI Reflection

COLUMN: THE FOURTH DISCONTINUITY WHO ARE ‘WE’ OR RATHER WHAT ARE ‘WE’? How the Neurosciences transform humans into machines. In his book The Fourth Discontinuity, Bruce Mazlish sets out to a risky undertaking. Once again he wants to challenge human self-understanding as a privileged being in the world. When speaking of the fourth discontinuity, Mazlish means the distinction between human beings and machines. Since the beginning of humanity and begged by religious accounts, human beings have perceived themselves as special creatures in this world, favored among all other existences. This favor was assumed to be God given. But the developments of the sciences up to this day have continuously challenged this frame. And as presented below, brain and neuroscience research builds no exception here. But before addressing this fact, it is useful to give a short historical summary. The first three continuities identified by Mazlish were those established by Copernicus, Darwin and Freud. Copernicus broke human self-understanding as being in the center of the universe. Not the earth but the sun was the center of astronomic movements. Darwin then challenged the idea of the human species as being distinct from animals. On the contrary! With his theory he effectively tried to show how both kinds stem from the same ancestors through the workings of evolution. Since Darwin, the evolvement of animals and humans is considered as a process in which both influenced and depended on each other. Humans did not come to the world as they are now and thus the hands of a god have not created them to be significantly different from other living beings. Finally, Freud then challenged what was left to set humans apart from the rest – rationality. His idea of human beings driven by unconscious forces destroyed the discontinuity between rationality and irrationality. Humans were controlled by forces beyond their reasoning and stirred by a beastly drive, which he of course mainly saw in sexuality. (Mazlish, 1993) In this row, the discussion about the fourth discontinuity finds it place. It troubles the differentiation between human beings and machines. In his book, Mazlish beautifully works out the disappearances of these discontinuities. But moreover he also reveals a specific continuous process – the slow development of a very specific kind of weltanschauung. The more the distinctions between humans and machines melted, the more humans and nature as a whole were perceived to be mechanical, governed by few fundamental laws and hence subject to the same mechanized workings as automata . For Mazlish, the development more and more makes disparities only matters of degree, thus the extinction of the fourth discontinuity is unavoidable: “We hear the premonition that any dichotomy between the natural and the mechanical is a false one, which, at the hands of Man the maker, can and will be eliminated” [ (Mazlish, 1993), p. 9].

The Human Hard disk: An Impression from http://

But the fourth discontinuity seems to be all that was left to the pride of humankind. At least it states that humans are still different from what they create. They are living beings, blessed with a mind and a soul. They are still distinct from the artificial, creatures with an essence that goes beyond cold algorithms. Even though their bodies were subjects to mechanical laws, a view that the drawings of da Vinci already revealed, their minds were not. This view of course was supported by the success of the Cartesian mind-body distinction. Descartes wrote: “I thence concluded that I was a substance whose whole essence or nature consists only in thinking, and which, that it may exist, has need of no place, nor is dependent on any material thing; so that “I,” that is to say, the mind by which I am what I am, is wholly distinct from the body […]” (Descartes, 1637). But it is exactly this distinction which is challenged by the progression of a new understanding of human nature. This understanding is a paradigm which is supported if not founded by the modern view in neurosciences. They provide a solid basis for the assumption that the human mind is not even anything more than a computer, that electric signals in the complex net of our neutrons are all that we are. The human mind is no longer distinct from its own creations, from the realm of the artificial.

Leonardo da Vinci’s Manpower from

Now, the absence of the discontinuity is getting evident in different ways. One is through human perception of the self. A discovery seems to take place which reveals the human to work just like an automat. This perception moves the two closer together. And as the results from neuroimaging techniques and the neurosciences in general more and more promote, this idea is not reduced to the body alone anymore. The mind itself appears as a machine determined by the neuronal software. Human page 32 - Neurotics Magazine - first and only issue

Mazlish wrote his book as early as 1993 and maybe the discontinuity by now has nearly faded. In the last twenty years, psychology has more and more become a natural science. Many experiments have proven Freud right, since our brain is likely to make decisions before we even ‘notice’ them (despite the fact that the question then is: who are we then and what is ‘making’ the decisions in our place?). The neurosciences also seem to support Pavlov’s account. Human thinking and behavior turns out more and more to be depended on certain brain structures, which program- like respond to input. In our elaboration on the brain imaging techniques, it became clear how scientists tend to see the human brain as a black box which can be understood through a sort of reverse engineering. In order to do that, mostly technological problems need to be solved. Once this is done and we have definite knowledge about brain structures and can measure activities in real time and without distortion, our problems vanish. We can fully understand what the human mind is and thus what it means to be human. In this view, there is no room for a mystery of the mind, no room for soul and also little room for personal identity and creativity. What was once promoted in the Cartesian world frame, the clear distinctiveness of the human mind as the source of all knowledge, somehow above the world and thus able to grasp it, turns out to be nothing more than an algorithm.

Now, what has been said so far might have put the reader in some trouble how to understand herself or encourage her in troubling the certainty of some of her views. But she still might be in doubt whether this topic is of any significance for our society. To point out its implications for the human commune and the future it might bring is the idea of this section. I will not answer, but pose the questions in order to reveal if not the necessity at least the possibility of a meaningful philosophical reflection. So what is described above is the paradigm in which neuroscience operates or towards which it eventually gravitates. But the scientific paradigm is always embedded in a huger paradigm, the leading world view of the time. What I would like to introduce here is an idea which appeared striking to me when reading Luciano Floridi’s article on The Children of the Fourth Revolution. There, his argument is that although there can be smart devices implemented as agents in our everyday life, there is no basis for assuming the possibility of strong AI, of artificial intelligence that is on par with the human version of the term. Rather, what the research on AI actually does is to investigate “the constraining conditions that make possible to build and embed artefacts in the world and interpage 33 - Neurotics Magazine - first and only issue


Today it seems as if in the past 15 years, neurosciences have developed this explanatory success and the Cartesian dream now has become an old hat. The concern Femke Nijboer expressed in her interview with Neurotics seems long to have become reality: in modern sciences humans are their brain. Other social factors which influence human behavior and interaction seem to become less acknowledged. The Dutch neurobiologist Dick Swaab has taken this account to its extreme in his book ‘Wij zijn ons brein’(We are our brain), published in 2010 (Letterenfonds). This reduction - if it even is one and not a mere disillusion – seems to put humans in line with machines. And what does such a reduction bring about for evaluating human nature? Machines basically only function or dysfunction. And their functionality is determined by whether they stick to the expected response. For many natural neuroscientists it already seems clear that this account now also is the key to the understanding of human nature. None of those interviewed by Neurotics expressed serious doubts on whether they are actually discovering anything about human nature. The impression arises that their concern is to make the right technologies work and thus enable reverse neuro-engineering of the brain. This is not surprising if we consider the fact that engineering has won the upper hand in this day and age anyways. But on the other hand, one has to bear in mind that the development might not be as modern as it seems. There is some evidence that such a development has started long time before neuroscience´s uprising. Mazlish demonstrates how the analogies of machine calculations and the human mind were already present to English mathematician and grandfather of the modern computer Charles Babbage in the 19th century. As Mazlish quoted him, he astoundingly noticed: “The analogy of these acts [of the calculating engine] and the operations of the mind almost forced upon me the figurative employment of the same terms.” [ (Mazlish, 1993), pp. 140-141].


Churchland also strengthened the role of neurosciences in supporting the identity theory in his book in 1999. This account sees mental states equivalent to physical brain states and thus is part of a mechanistic view on the human mind. Its thesis is that our brain is all that constitutes our mind. He writes: “A final argument derives from the growing success of the neurosciences in unraveling the nervous systems of many creatures and in explaining their behavioral capacities and deficits in terms of the structures discovered”. And further: “All that would be required would be that an explanatorily successful neuroscience develop to the point where it entails a suitable ‘mirror image’ of the assumptions and principles that constitute our common-sense conceptual framework for mental states, an image where brain-state terms occupy the positions held by mental-state terms in the assumptions and principles of common sense” [ (Churchland, 1999), p. 26].

Brain imaging

rationality and reasoning is nothing special and can be imitated by any machine whatsoever. Human behavior is only a mechanical response, the output dictated by the mental program, following the perceptional input. In such an account, known as Pavlov’s behaviorism, free will and conscious choices become illusions. Another contribution to the disappearing of the discontinuity is that the human being also more and more amalgamates with its own machine creations. Such happenings take place in the realm of human-media interactions and brain-computer interfaces. The closer both sides intertwine, the harder it seems to draw the line between them. The distinctions not only melt ideologically, but also physically. And how can we find them then, if there is no difference between the human and the artificial intelligence anyways?

Brain imaging HMI

act with it [AI] successfully” [ (Floridi, 2011), p. 228]. In order to provide this, what we need to do is “re-ontologising the world to fit reproductive, engineering AI” [ (Floridi, 2011), p. 228]. In other words, because artificial agents are far from having human intelligence, we need to restructure the world in order to allow the notion of AI. We have to change ourselves and our environment to fit it to the state-of-art of technology. Such a progress can of course take many ways, but I find it particularly remarkable to think about what this means according to the paradigm shift we have experienced and still are experiencing. If we reduce the mentality to a program and the mind to its physical brain states very much alike the states of a computer, we also develop a certain view on what it means to be intelligent. This current view allows for the notion of AI. If part of our intelligence would be phenomena of the mind not explainable through physics, this intelligence would not be translatable through machines. Hence, ordering the mind in purely physical terms paves the way for the rise up of AI. Of course, this is not the only direction of the development, since AI is a complex topic and involves many different considerations. But this argumentation does not aim at reintroducing the body-mind dualism anyways; rather it can show how science and its paradigms interact with society and the leading world view. Furthermore, it raises the question of what it is that we ‘discover’ and what the role of technology is within such ‘discoveries’. The continuity does not only lie in the similarity between humans and machines. If we shape our own mind to fit the idea of AI, it also implies a further power shift from the human power over technology to the power of technology over humans. And such a shift in general has implications on our life, socially and legally. What has been told so far has implications. Especially in cases related to severe crimes, we many times see discussions in court rooms around how far the suspect can be held responsible or if he is suffering from a mental disease, and also in how far we can know about if he actually has such a disease. But if human behavior is determined by brain structures, we should be able to ‘measure’ the answer to such questions. Another question in legal cases is also in how far somebody can be ‘cured’ from such a disease and thus be able to reintegrate into society. If such issues are determined by brain structures, can such structures also change? Do we have the technological possibilities to change them ourselves? In the present account, such a recovery should also be provable through brain imaging. Hence some questions worth reconsidering for example are: “How can we hold somebody legally responsible for a crime, if he was suffering from defect brain structures?”, “What is a mental disease and how can we measure it in brain activity?”, “In how far can someone recover from such a disease?”, “How can neurosciences be used in court rooms?” and “How safe are the results?”, also “How are we supposed to weigh other aspects such as childhood traumata?” and many more. The answer to such questions hugely depends on the current approaches in science and the available technologies.

Laura Fichtner



Churchland, P. M. (1999). Matter and Consciousness : A Contemporary Introduction to the Philosophy of Mind. MIT Press. Descartes, R. (1637). Discourse on the Method of Rightly Conducting the Reason, and Seeking Truth in the Sciences. The Project Gutenberg. Floridi, L. (2011). Children of the Fourth Revolution. Philos. Technol. , 227-232. Letterenfonds, N. (n.d.). Retrieved 1 18, 2013, from Mazlish, B. (1993). The Fourth Discontinuity - the co-evolution of humans and machines. New York: Yale University Press.

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Kant takes several steps to arrive at his description of the relation between humans and morality in his metaethical study; the first involves an analysis of what it means to be conscious of the self. A distinction between an internal order and an external order is made to separate subjective experiences from the actual world outside. Kant stressed how the external order is ultimately observed through a subjective, internally ordered, lens, since both are required for understanding to take place. This way of understanding, seeing nature and laws of nature as formalizations of appearances in the external world, enables a form a self-consciousness laden with this dual ordering: self-consciousness is a person’s understanding of the relation between the self and the world.

Brain imaging


The next step lies in the effects of these layers of ordering, which Kant sees as enabling self-consciousness but limiting awareness of certain transcendental topics such as God and morality. These, says Kant, cannot be reached with understanding because they contain transcendent elements beyond the realm of human experience, rather, a transcendental aspect with humans is required. At this point, Kant flips his approach around to a more bottomup, pragmatic methodology by asking what is required for a system of morality to work at all.


The crux of Kant’s moral system lies in his transcendental beliefs about freedom. It’s important to remember Kant’s Newtonian leaning since it shows the tension between his intense belief in causal relations and a transcendental aspect in humans. Kant said within each person there exists an aspect uncaused and unaffected by experiences. This unaffected part, being apart from nature and causal chains, enables moral freedom since people can be held accountable for their actions instead of simply appealing to circumstances or upbringing. The “noumenal” self is the name Kant gave to this transcendental aspect of humans. The noumenal self has other effects however since it enables a (different) kind of pure reason for moral situations. Such moral investigations appear through an interaction between two other Kantian ideas required for his moral philosophy: the categorical imperative and the goodwill. The categorical imperative provides an explanation of motivation; an action is required because of the nature of the situation itself. This force is connected with the concept of the “goodwill” which, like other human needs such as hunger, implicitly includes its motivation for fulfillment. The outcome of these concepts is a developed sense of duty discovered through a noumenal idea of goodness, which necessarily implies its requirement to be fulfilled.

fMRIs enable a new way to examine the brain by showing structure and, to a certain degree, processes and the activation of neurons. At places like the Donder’s Institute, scientists are developing other technologies that depend on different biomarkers with the aim of decreasing the hidden areas and aspects of the brain not yet detectable. This brings up the question of whether all areas and processes in the brain will one day be detectable and understood. Current research cannot make such a claim but as improvements are made, Kant’s noumenal self may have fewer and fewer places to hide. The noumenal self is more complex than this however. By its transcendental nature, Kant would likely say it’s forever undetectable. In a case where neuroimaging has become so advanced as to provide enough understanding to create a simulated brain maybe Kant’s claim could be tested since such a simulation wouldn’t be expected to have a noumenal self or goodwill. But this is a distant possibility and there have been other examples of purportedly impossible changes to the noumenal self. If an area of the brain could be shown to affect self-control and one’s goodwill, this would represent a clear disconnect from Kant’s philosophy since accountability and goodwill should be tied to a transcendental aspect within humans. Before modern neuroimaging, gruesome accidents often provided the best, most cutting edge picture of the brain. One patient, Phineas Gage, was involved in a traumatic brain injury where a metal rod was driven through his entire head. Miraculously, he survived but not without several changes to his character. He became short-tempered and violent, often times swearing profusely. These behaviors, not shown by him before, led his friends and family to say he no longer was the Phineas Gage they once knew. The question for Kant is this, was Phineas’ noumenal self affected by a metal rod? Can he still be held accountable in the way the noumenal self imposes accountability? Kant’s analysis represents a meta-ethical description of what is required for a system of morality to exist at all. If we agree with Kant about the importance of autonomy and accountability for morals but are led by brain imaging and neuroscience to question the existence of a noumenal self, is there a solution where morals can be saved? Only time will tell whether the noumenal self will be found but this analysis helps drive concerns about how we decide to call something moral or immoral. page 35 - Neurotics Magazine - first and only issue


This is the heart of what is at stake when neuroimaging research is juxtaposed with Kant’s morality. Is there or isn’t there a noumenal self? And to what extent can neuroimaging answer this question?

Written by Mark Burdick

[1] Kant, Immanuel. (1781). The Critique of Pure Reason. Published by Project Gutenberg [2] Kant, Immanuel. (1785). Groundwork for the Metaphysics of Morals. Yale University Press [3] Macmillan, Malcolm. (1999). “The Phineas Gage Information Page� at



Brain imaging


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What is mind? No matter. What is matter? Never mind. originally penned, in a slightly different form, by Thomas Hewitt Key (1799-1875) in Punch, vol. XXIX, #19 ( July 14, 1855)

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