Strategic routes for learning in the human brain
When:
—
Venue:
Birkbeck Main Building, Malet Street
No booking required
Wednesday lunchtime seminars, Department of Psychological Sciences:
Prof Zoe Kourtzi, University of Cambridge
"Strategic routes for learning in the human brain"
Abstract:
When immersed in a new environment we are challenged to make sense of initially incomprehensible event streams. Yet, quite rapidly, the brain is able to find meaningful structures, helping us to predict and prepare for future actions. We combine behavioural and brain imaging measurements with computational modeling, to understand the dynamics of learning complex structures. We show that individuals adapt to changes in the environment's statistics and extract predictive structures. Importantly, extracting complex structures relates to individual decision strategy: faster learning relates to selecting the most probable outcomes (i.e. maximising) and is implemented by interactions between executive and motor cortico-striatal mechanisms, while learning the exact stimulus statistics (i.e. matching) is implemented by visual cortico-striatal circuits. Our findings provide evidence for alternate routes to learning of behaviorally-relevant statistics that facilitate our ability to predict future events in variable environments.
Biography:
My work aims to understand the role of lifelong learning and experience in enabling humans of all ages to translate sensory experience into complex decisions and adaptive behaviours. After completing my PhD on object recognition at Rutgers University, I started my work on human brain imaging as a postdoctoral fellow at MIT and Harvard University. I then received a McDonnell-Pew award to combine animal and human brain imaging and moved to the Max Planck Institute for Biological Cybernetics as a Senior Research Scientist. I moved to the University of Birmingham as a Chair in Brain Imaging in 2005, and to the University of Cambridge as a Chair in Experimental Psychology in 2013. I am a Fellow at Downing College, Cambridge and the Alan Turing Institute.
Contact name:
Dr. Alex Shepherd
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