Our paper on how neurons represent past and future events to form a continuous timeline--just like how we intuitively experience time--is now published! https://t.co/W95TyoDkHl

We are pleased to have @RuiiiChaos join us tomorrow, Tuesday, Nov 4th, 12pm (EST) to present on time-perception modeling across levels of analysis. The zoom is open to public with details in the flyer! @PsychPrinceton

Hariri Institute Graduate Student Fellow @ryan_senne explores the science of decision-making at the intersection of machine learning, statistical modeling, and neurological research. Read more about his research here: https://t.co/m8CLbgYUdL

Excited to share our new paper out now @Nature, where we identified neural signatures of stress susceptibility and resilience in the amygdala-ventral hippocampal network to enable control of anhedonia! < https://t.co/8sd31UV0Ng> Thread below:

Hippocampus generates an internal model of Euclidean space. We ventured in a spatial odyssey exploring how much of the internal model is a priori, innate (Nature) and what is contributed by postnatal experience of Euclidean geometry (Nurture) Our answer@ https://t.co/HkwkvAj4oO👇

How does our brain make sense of the temporal aspect of our experiences? A great @nature paper by @PTacikowski @GuldamlaKalendr @DavideCili and @ItzhakFried describes how it is encoded by neurons in the hippocampal and entorhinal cortex

Curious about how the brain distinguishes between present and past/future? Check out our recent paper in @NatureComms: https://t.co/FnVifqwrvv Thanks to the great co-authors: D. Croote, @giuls90210, L. Lerman, @markgbaxter, D. Schiller. @IcahnMountSinai @unige @SchwartZzz_lab

A hippocampal astrocytic sequence emerges during learning and memory https://t.co/z5EdZJQwol #biorxiv_neursci

A thread on the history of RL/ML based on Andy Barto's talk #RLC2024: the Reinforcement Learning Conference. Beyond seeing friends & giving talks/panel, talking to @RichardSSutton & hearing Andy Barto revived a need for attention to historical psych/neuro influences on AI. 1/n🧵

Bright, I. M., Meister, M. L., Cruzado, N. A., Tiganj, Z., Buffalo, E. A., & Howard, M. W. (2020). A temporal record of the past with a spectrum of time constants in the monkey entorhinal cortex. Proceedings of the National Academy of Sciences, 117(33), 20274-20283.

Henke, J., Bunk, D., von Werder, D., Häusler, S., Flanagin, V. L., & Thurley, K. (2021). Distributed coding of duration in rodent prefrontal cortex during time reproduction. Elife, 10, e71612.

4/4 Together the population represents a continuous timeline of the duration as an ongoing experience in the real Laplace domain

3/4 Cells that ramp up exponentially with a continuous spectrum of rates all peaked at the end point, like the mirrored version of the other group. Therefore time until the end point, a future event, can be viewed as the red lines that move closer to present (d)

Cells that peaked at the start point decay exponentially with a continuous spectrum of rates, like what's observed in Bright et al (2020). So time since the start point, a past event, can be viewed as blue lines that shift away from present as more cells come back to baseline (c)

1/4 We analyzed recordings from Henke et al (2021) when gerbils timed their running to match a target duration with hierarchical Bayesian models. We found two groups of cells preferentially peaked at the start point (a) or the end point (b) of running duration

Imagine singing Hey Jude In the pause between “Hey Jude” and “Don’t make it bad”, your memory of the former recedes, while your anticipation for the latter increases at every moment Here we show ramping cells carry a continuous timeline from past to planned future@marcwhoward777

Ramping cells in rodent mPFC encode time to past and future events via real Laplace transform https://t.co/ruMQLxzBo0 #biorxiv_neursci