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Brain Inspired

BI 194 Vijay Namboodiri & Ali Mohebi: Dopamine Keeps Getting More Interesting

Sep 27, 2024
Vijay Namboodiri, who runs the Nam Lab at UCSF, teams up with Ali Mohebi, an assistant professor at UW-Madison, to dive deep into the intricacies of dopamine. They challenge the classic narrative of dopamine's role in reward prediction, proposing a retrospective view that redefines how we understand causal relationships. Their discussions cover sign tracking versus goal tracking in learning, the implications for addiction, and the need for new models that integrate temporal differences. They also touch on how our past experiences inform current decisions, shaping our understanding of learning.
01:37:21

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Quick takeaways

  • Dopamine's role extends beyond being a pleasure signal; it fundamentally influences motivation and expectation in cognitive processes.
  • The distinction between retrospective and prospective learning highlights the complex ways individuals analyze past experiences or anticipate future outcomes.

Deep dives

Understanding Algorithmic Thinking

A key aspect of algorithmic thinking involves identifying invariants within data, which are elements that remain unchanged under various conditions. This approach emphasizes the importance of developing models that capture these invariants as they provide reliable foundations for prediction and analysis. The ability to pinpoint what is constant allows researchers to build robust algorithms, making it essential for any computational framework. Therefore, the objective should be to focus on these core invariants when modeling behavior and decision-making processes.

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