Sepehr Razavi

The Social Computation and Representation Lab talk series is back tomorrow! And no better way to start the new academic year than by following @setayeshradkani.bsky.social 's talk as she weaves together two complementary strands of her investigations into social cognition.

In so doing, they developed a Bayesian computational model that synthesizes and explains this variability by revealing the cognitive logic of how observers interpret and learn from punishment.

The Social Computation and Representation Lab talk series is back tomorrow! And no better way to start the new academic year than by following @setayeshradkani.bsky.social 's talk as she weaves together two complementary strands of her investigations into social cognition.

The first reveals a fundamental asymmetry between experiential and observational evidence accumulation, i.e., learning from our own experiences versus observing others’ similar experiences. The geometry of neuronal population activity in monkeys’ ACC provided a mechanistic explanation for this.

The Social Computation and Representation Lab talk series is back tomorrow! And no better way to start the new academic year than by following @setayeshradkani.bsky.social 's talk as she weaves together two complementary strands of her investigations into social cognition.

Setayesh's talk will start with a puzzle: that while we use our observations to form and update beliefs about hidden states of the world, the same observation will not always lead to similar inferences across different individuals and even within individuals across different contexts.

Mood a bit dampened by a somewhat humiliating ‘random’ check in the process of entering the US but still very excited to present some of the work we’ve been doing at the Social Computation and Representation lab, starting at Computational Psychiatry in New Haven tomorrow!

Coming up next week at the SoCR lab talk series is @alimahmoodi.bsky.social, who will be discussing his recent thought-provoking perspective, which advocates for a computational view of neural mechanisms of social cognition (contra an anatomical one).

This Thursday, we’re delighted to welcome @carocharp.bsky.social, PI of the Social Learning and Decisions Lab at the University of Maryland. She will be delivering what promises to be an insightful talk: 'Seeking advice and seeking feedback: cognitive mechanisms and relevance for psychopathology.'

Very happy to announce next week's SoCR lab guest, Andreas Hula, who will be talking about the uses and misuses of I-POMDPs in model-building human social decision-making 🧵

In this talk Andreas will speak about the implementation of I-POMDPs, results obtained through practical studies and observations on challenges and further approaches to making behaviour in experiments tractable, starting from a well-known implementation of I-POMDPs for a multi-round trust task.

Very happy to announce next week's SoCR lab guest, Andreas Hula, who will be talking about the uses and misuses of I-POMDPs in model-building human social decision-making 🧵

These processes provide interpretable parametrizations of agent interactions, with factors like fairness mindedness/inequality aversion, irritability or risk aversion, whilst also having established procedures for learning, models of other actors/theory of mind and planning.

Very happy to announce next week's SoCR lab guest, Andreas Hula, who will be talking about the uses and misuses of I-POMDPs in model-building human social decision-making 🧵

It's a pleasure for me to announce our next Social Computation and Representation Lab invited speaker @mkwittmann.bsky.social for a talk on dimensionality reduction and basis functions in social cognition

A dominant framework in social neuroscience is agent-centric representation: information about beliefs, abilities, or attitudes is tagged to individuals such as oneself or an interaction partner.

It's a pleasure for me to announce our next Social Computation and Representation Lab invited speaker @mkwittmann.bsky.social for a talk on dimensionality reduction and basis functions in social cognition