Journal club presentation by F.Zareayan

Stable population coding for working memory coexists with heterogeneous neural dynamics in prefrontal cortex

John D. Murraya, Alberto Bernacchiab, Nicholas A. Royc, Christos Constantinidisd, Ranulfo Romoe,f,1,
and Xiao-Jing Wang
g,h,1

Link to paper

Abstract
Working memory (WM) is a cognitive function for temporary maintenance and manipulation of information, which requires
conversion of stimulus-driven signals into internal representations that are maintained across seconds-long mnemonic delays. Within primate prefrontal cortex (PFC), a critical node of the brain’s WM network, neurons show stimulus-selective persistent activity during WM, but many of them exhibit strong temporal dynamics and heterogeneity, raising the questions of whether, and how, neuronal populations in PFC maintain stable mnemonic representations of stimuli during WM. Here we show that despite complex and heterogeneous temporal dynamics in single-neuron activity, PFC activity is endowed with a population-level coding of the mnemonic stimulus that is stable and robust throughout WM maintenance. We applied population-level analyses to hundreds of recorded single neurons from lateral PFC of monkeys performing two seminal tasks that demand parametric WM: oculomotor delayed response and vibrotactile delayed discrimination.
We found that the high-dimensional state space of PFC population activity contains a low-dimensional subspace in which stimulus representations are stable across time during the cue and delay epochs, enabling robust and generalizable decoding compared with time-optimized subspaces. To explore potential mechanisms, we applied these same population-level analyses to theoretical neural circuit models of WM activity. Three previously proposed models failed to capture the key population-level features observed empirically. We propose network connectivity properties, implemented in a linear network model, which can underlie these features. This work uncovers stable population-level WM representations in PFC, despite strong temporal neural dynamics, thereby providing insights into neural circuit mechanisms supporting WM

 

About This Event

Start date08/30/2017 12:00
End date08/30/2017 14:00

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    In July, 2017 we held a one-day mini-symposium at IUST, for the interchange of scientific expertise and findings between different projects of the our lab and external collaborating teams. The lectures were organized in two panels: Invited talks (given by principle investigators cooperating with our lab) and Project presentations (delivered by PhD students). Topics ranging all the way from the dynamics of neural coding in primate brain to computational approaches in modeling the neural system were covered through these lectures. Importantly we had the honor to host Dr. Fatemeh Bakouie (Shahid Beheshti University), Dr. Zeinab Fazlali (IPM School of Cognitive Sciences), Prof. Dr. Shahriyar Gharibzadeh (Amirkabir University of Technology) and Dr. Marzieh Zare (IPM School of Computer Sciences), to present their ongoing research lines in the symposium.
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