Sally Ozonoff is endowed professor of psychiatry and behavioral sciences at the University of California, Davis.
Sally Ozonoff
Professor
University of California, Davis MIND Institute
From this contributor
‘Baby sibs’ who evade autism remain at risk for attention deficit
Sally Ozonoff is looking for early signs of attention deficit hyperactivity disorder in videos of hundreds of younger siblings of children with autism.
‘Baby sibs’ who evade autism remain at risk for attention deficit
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.
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.
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?