BEGIN:VCALENDAR VERSION:2.0 PRODID:-//132.216.98.100//NONSGML kigkonsult.se iCalcreator 2.20.4// BEGIN:VEVENT UID:20250825T004554EDT-7135UMZUFm@132.216.98.100 DTSTAMP:20250825T044554Z DESCRIPTION:Retrospective Learning in the Brain\n\nBy Dr. Vijay Mohan K Nam boodiri from the Weill Institute for Neurosciences at the University of Ca lifornia\, San Francisco.\n\nIn-person event hosted by the 9IÖĆ×÷ł§Ăâ·Ń's Depart ment of Psychology\, will be held in Room 522 McIntyre Medical Building. A wine and cheese reception will follow.\n\nRetrospective Learning in the B rain\n A hallmark of intelligence is the ability to learn associations betw een causes and effects (e.g.\, environmental cues and associated rewards). The near consensus understanding of the last few decades is that animals learn cause-effect associations from errors in the prediction of the effec t (e.g.\, a reward prediction error or RPE). This theory has been hugely i nfluential in neuroscience as decades of evidence suggested that mesolimbi c dopamine (DA)— known to be critical for associative learning—appears to signal RPE. Though some evidence questioned whether DA signals RPE\, the R PE hypothesis remained the best explanation of learning because no other n ormative theory of learning explained experimental observations inconsiste nt with RPE while also capturing phenomena explained by RPE. My lab has re cently provided such an alternative. Specifically\, we proposed a new theo ry of associative learning (named ANCCR\, read “anchor”) which postulates that animals learn associations by retrospectively identifying causes of m eaningful effects such as rewards and that mesolimbic dopamine conveys tha t a current event is meaningful. The core idea is simple: you can learn to predict the future by retrodicting the past\, and you retrodict the past only after meaningful events. Here\, I will present the basic formulation of this theory\, some experimental data focused on distinguishing predicti ons of ANCCR and RPE\, unpublished experimental results demonstrating that behavioral and dopaminergic learning rates from cue-reward experiences ar e quantitatively scaled by reward sparsity\, and end with discussions rega rding the implications of the theory for translational applications for so me neuropsychological disorders involving maladaptive associative memories .\n\n \n DTSTART:20240405T193000Z DTEND:20240405T213000Z SUMMARY:Bindra Lecture URL:/psychiatry/channels/event/bindra-lecture-355942 END:VEVENT END:VCALENDAR