News Briefs

New research finds the risk of psychotic-like experiences can start in childhood

It has long been understood that environmental and socioeconomic factors – including income disparity, family poverty, and air pollution – increase a person’s risk of developing psychotic-like experiences, such as subtle hallucinations and delusions that can become precursors to a schizophrenia diagnosis later in life. Research has long focused on young adults but now, thanks to the data from the Adolescent Brain Cognitive Development (ABCD) Study, researchers at the University of Rochester have found these risk factors can be observed in preadolescent children.

The research published in Frontiers in Psychiatry and lead by David Dodell-Feder, Ph.D., assistant professor of Psychology and Neuroscience, found that the more urban of an environment a child lived in – proximity to roads, houses with lead paint risks, families in poverty, and income disparity – the greater number of psychotic like experiences they had over a year’s time. These findings are in line with past research conducted in young adults, but have not been found like this in preadolescence.

“It is disconcerting that the association between these exposures and psychotic-like experiences are already present in late childhood,” said Dodell-Feder. “The fact that the impact of these exposures may occur as early as pre-adolescence highlights the importance of early prevention.”

The University of Rochester Medical Center is one of 21 research sites across the country collecting data for the National Institutes of Health ABCD Study. Since 2017, 340 children from the greater Rochester area have been participating in the 10-year study. In all, the study is following 11,750 children through early adulthood looking at how biological development, behaviors, and experiences impact brain maturation and other aspects of their lives, including academic achievement, social development, and overall health.

How the brain interprets motion while in motion

New findings about how the brain interprets sensory information may have applications for treating brain disorders and designing artificial intelligence. Greg DeAngelis, Ph.D., the George Eastman Professor of Brain and Cognitive Sciences at the University of Rochester, led the research published in eLife that describes a novel neural mechanism involved in causal inference – a key to learning, reasoning, and decision making – that helps the brain detect object motion during self-motion. This neural mechanism has a particular combination of response properties, which makes it well-suited to contribute to the task of distinguishing between self-motion and the motion of other objects.

“Although the brain probably uses multiple tricks to solve this problem, this new mechanism has the advantage that it can be performed in parallel at each local region of the visual field, and thus may be faster to implement than more global processes,” DeAngelis said. “This mechanism might also be applicable to autonomous vehicles, which also need to rapidly detect moving objects.”