- Thursday, November 3rd 2016 at 15:00 - 16:00 UK (Other timezones)
- General participation info | Participate online | + Phone in United States: +1 (224) 501-3316 Canada (toll-free): 1 877 777 3281 France (toll-free): 0 805 541 052 Germany (toll-free): 0 800 723 5274 Ireland (toll-free): 1 800 818 263 Israel (toll-free): 1 809 453 019 Netherlands (toll-free): 0 800 023 1954 Russia (toll-free): 8 800 100 6216 Sweden (toll-free): 0 200 330 924 Switzerland (toll-free): 0 800 000 452 United Kingdom (toll-free): 0 800 389 5276 United States (toll-free): 1 877 309 2070 Access Code: 668-856-797 Audio PIN: Shown after joining the meeting Meeting ID: 668-856-797
Multiple different neurocognitive players contribute to learning, which may be differentially engaged depending on task demands. While many studies implicate altered reward learning in patients with schizophrenia (SZ), parsing out the underlying mechanisms requires one to reliably attribute different aspects of their behavior to the relevant neural systems, and to understand how dysfunction in one system may impact the others. We developed new behavioral protocols and computational models that allowed us to extract the independent contributions to behavior of fast, capacity-limited working memory from the contributions of slow reinforcement learning. Across two experiments, we found that patients were significantly impaired at learning compared to match healthy controls. However, this impairment could be fully traced back to working memory contributions to learning, while reward-based value learning was spared. Our results show that SZ learning impairments are tied to WM function, and highlight the importance of targeted experimental design and mathematical modeling for disentangling multiple neuro-cognitive systems’ contributions to learning.
Anne Collins is Assistant Professor in the department of Psychology and a member of the The Helen Wills Neuroscience Institute at UC Berkeley.
She is currently hiring a post-doc, a lab manager, and will be accepting graduate students for Fall 2017.