Oliver Vikbladh

Cofounder @cursive_ai

[Oliver Vikbladh @vikbladh]

Preprint for "Consolidation of Sequential Planning" with @evanrussek and @NeilBurgess10. We demonstrate the neural representations supporting sequential planning and the effect of memory consolidation upon them: https://t.co/JnRNr0tNEj. As talk, see also: https://t.co/Ya8YDFQCAy

[Neil Burgess @NeilBurgess10]

@EdvardMoser Really impressive identification of this functional circuit!

Even better it just needs continuous attractor dynamics & firing rate adaptation (or similar) to work, which also makes some new predictions (model with @zilong_ji, Tianhao Chu, Si Wu)

https://t.co/rc4oytmlWC...

[Kevin Miller @kevinjmiller10]

Cognitive models of behavior are a key part of neuroscience. But discovering them is hard!

In new work from @GoogleDeepMind Neuroscience and collaborators @HHMIJanelia, we demonstrate an approach that uses LLMs and large datasets to discover models automatically.

[Isaac Fradkin @FradkinIsaac]

I’m excited to share our new, open-access paper published today in @NatMentHealth, “Latent mechanisms of language disorganization relate to specific dimensions of psychopathology”. https://t.co/vcXyFDEMIT

[Ari Kahn @ari_e_kahn]

New preprint with @DaniSBassett and @nathanieldaw!

How do humans learn predictive representations? We propose a trial-by-trial learning rule that incorporates trace updating to learn the SR.

https://t.co/FIIsGOQ8td

[Evan Russek @evanrussek]

👀🍟Now out in Cognitive Science 😋🤖

We present a new approach that combines cognitive models and neural networks to predict latent preferences.

https://t.co/LOuCeiRPqM

[Oliver Vikbladh @vikbladh]

@paul_b_sharp @evanrussek lastly, the task doesn't cover all planning settings but it seems to me to be highly representative of how some planning proceeds, (when start state is fixed, its not obvious where the rewarding states are). e.g. "do you know some place we might get food around here?"

[Oliver Vikbladh @vikbladh]

@paul_b_sharp @evanrussek whether the consolidation is going on through offline sampling or online planning is also something we should dig into more. Of course, its a lot easier to detect rollouts here this way than offline because we can time lock their onset to the start of trial.

[Oliver Vikbladh @vikbladh]

@paul_b_sharp Thats cool :). Look forward to hear what you think.

[Oliver Vikbladh @vikbladh]

@evanrussek @NeilBurgess10 By showing the evolution of the representational basis for rollouts (MTL to PFC), we address the fundamental question of what systems consolidation is actually for. Not simply how representations change, but directly, how they contribute to subsequent flexible behaviour.

[Oliver Vikbladh @vikbladh]

Preprint for "Consolidation of Sequential Planning" with @evanrussek and @NeilBurgess10. We demonstrate the neural representations supporting sequential planning and the effect of memory consolidation upon them: https://t.co/JnRNr0tNEj. As talk, see also: https://t.co/Ya8YDFQCAy

[Oliver Vikbladh @vikbladh]

@evanrussek @NeilBurgess10 Using this method we can not only decode the contents of rollouts through the transition structure, but also, across trials within participants, decode the speed of sequential simulation. Faster reaction times are related to faster rollouts - i.e. thinking fast means acting fast.