Andre Marquand is associate professor and principal investigator at Radboud University’s Donders Institute for Brain, Cognition and Behavior in Nijmegen, the Netherlands. His work focuses on the application of statistical and machine-learning methods to further our understanding of human brain function.
Andre F. Marquand
Associate professor
Radboud University
From this contributor
How normative modeling can reframe autism’s heterogeneity
Normative modeling could capture variability among autistic people and allow for individualized assessments.
How normative modeling can reframe autism’s heterogeneity
By
Richard Bethlehem, Andre F. Marquand
25 February 2020 | 4 min read
Explore more from The Transmitter
Autism-linked genes alter sleep behavior, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 13 April.
Autism-linked genes alter sleep behavior, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 13 April.
By
Jill Adams
14 April 2026 | 2 min read
This paper changed my life: Erin Calipari ponders the nuances of rewarding and aversive stimuli
A 1960s study by Kelleher and Morse found that lever pressing in squirrel monkeys depended not on whether they received a reward or shock, but on the rules of the task. This taught Calipari to think deeply about factors that influence how behavior is generated and maintained.
This paper changed my life: Erin Calipari ponders the nuances of rewarding and aversive stimuli
A 1960s study by Kelleher and Morse found that lever pressing in squirrel monkeys depended not on whether they received a reward or shock, but on the rules of the task. This taught Calipari to think deeply about factors that influence how behavior is generated and maintained.
By
Erin Calipari
14 April 2026 | 5 min read
Why neural foundation models work, and what they might—and might not—teach us about the brain
These models can partly generalize across species, brain regions and tasks, suggesting that a set of machine-learnable rules govern neural population activity. But will we be able to understand them?
Why neural foundation models work, and what they might—and might not—teach us about the brain
These models can partly generalize across species, brain regions and tasks, suggesting that a set of machine-learnable rules govern neural population activity. But will we be able to understand them?
By
Juan Gallego
13 April 2026 | 8 min read