BI 039 Anne Churchland: Decisions, Lapses, and Fidgets

BI 039 Anne Churchland: Decisions, Lapses, and Fidgets

BI 039 Anne Churchland: Decisions, Lapses, and Fidgets

 
 
00:00 / 01:19:09
 
1X
 

Anne and I discuss her work elucidating how populations of neurons underly decision-making in mouse brains. We talk about how movement related activity dominates neural activity during decisions, how lapses may reflect exploration of options, a rubric for characterizing animal experiments, her Anne’s List repository to help all of us invite female systems neuroscientists to speak at conferences, and a lot more

BI 038 Máté Lengyel: Probabilistic Perception and Learning

BI 038 Máté Lengyel: Probabilistic Perception and Learning

BI 038 Máté Lengyel: Probabilistic Perception and Learning

 
 
00:00 / 01:18:37
 
1X
 

Máté and I discuss his work on probabilistic internal models to understand perception and learning and their inherent uncertainty in our brains, bayesian theory, how his models relate to modern deep learning, and lots more.

BI 036 Roshan Cools: Cognitive Control and Dopamine

BI 036 Roshan Cools: Cognitive Control and Dopamine

BI 036 Roshan Cools: Cognitive Control and Dopamine

 
 
00:00 / 01:11:08
 
1X
 

Roshan and I discuss her work on the role of dopamine on our meta-control of cognition (cognitive control) in the basal ganglia and prefrontal cortex, the role of dopamine in reinforcement learning, how artificial intelligence might incorporate principles of neuromodulation to improve algorithms, being a woman in science, and much more.

BI 035 Tim Behrens: Abstracting & Generalizing Knowledge, & Human Replay

BI 035 Tim Behrens: Abstracting & Generalizing Knowledge, & Human Replay

BI 035 Tim Behrens: Abstracting & Generalizing Knowledge, & Human Replay

 
 
00:00 / 01:11:03
 
1X
 

Tim and I talk about the upcoming Cognitive Computational Neuroscience conference, where he’ll be delivering a keynote address, conferences in general, his Tolman Eichenbaum machine that mimics neurons in the hippocampus and entorhinal cortex to abstract and generalize the structure of knowledge, his work using MEG to measure replay in humans, and more.