Biology subjects

Perestenko, P. V.

Publications and source records attributed to Perestenko, P. V..

3 recordsLinked to original sources

bioRxiv2026

Generative replay across hippocampal-neocortical circuits

Flexible behaviour requires predictions that extend beyond direct experience, yet the neural mechanisms that support this process remain unclear. A candidate mechanism occurs during hippocampal sharp-wave ripples (SWRs), in which generative replay combines representations for discrete past events into novel activity patterns. However, it remains unknown whether comparable computations occur in neocortex. Using simultaneous electrophysiology and calcium imaging across hippocampus and neocortex, we record neural activity in freely moving mice during an inference task and in subsequent sleep. We show that neuronal sequences in primary visual cortex (V1) encode relationships that were never directly experienced, providing evidence for generative replay outside the hippocampus. Generative replay in V1 is predicted by preceding hippocampal activity, suggesting that hippocampal activity provides a teaching signal to reorganise neocortical representations during sleep. These findings identify a hippocampal-neocortical mechanism for generative replay which may support the construction of a hierarchical generative model to enable flexible behaviour.

neuroscience↗

bioRxiv2023

Organizing the coactivity structure of the hippocampus from robust to flexible memory

New memories are integrated into prior knowledge of the world. But what if consecutive memories exert opposing demands on the host brain network? We report that acquiring a robust (food-context) memory constrains the hippocampus within a population activity space of highly correlated spike trains that prevents subsequent computation of a flexible (object-location) memory. This densely correlated firing structure developed over repeated mnemonic experience, gradually coupling neurons of the superficial CA1 pyramidale sublayer to whole population activity. Applying hippocampal theta-driven closed-loop optogenetic suppression to mitigate this neuronal recruitment during (food-context) memory formation relaxed the topological constraint on hippocampal coactivity and restored subsequent flexible (object-location) memory. These findings uncover an organizational principle for the peer-to-peer coactivity structure of the hippocampal cell population to successfully meet memory demands.

neuroscience↗

bioRxiv2019

An Emergent Neural Coactivity Code for Dynamic Memory

Coincidental spike discharge amongst distributed groups of neurons is thought to provide an efficient mechanism for encoding percepts, actions and cognitive processes1-3. Short timescale coactivity can indeed bind neurons with similar tuning, giving rise to robust representations congruent with those of the participating neurons4-6. Alternatively, coactivity may also play a role in information processing through encoding variables not represented by individual neurons. While this type of emergent coactivity-based coding has been described for physically well-defined variables, including percepts and actions7-10, its role in encoding abstract cognitive variables remains unknown. Coactivity-based representation could provide a flexible code in dynamic environments, where animals must regularly learn short-lived behavioural contingencies. Here, we tested this possibility by training mice to discriminate two new behavioural contingencies every day, while monitoring and manipulating neural ensembles in the hippocampal CA1. We found that, while the spiking of neurons within their place fields is organised into congruent coactivity patterns representing discrete locations during unsupervised exploration of the learning enclosure, additional neurons synchronised their activity into spatially-untuned patterns that discriminated opposing learning contingencies. This contingency discrimination was an emergent property of millisecond timescale coactivity rather than the tuning of individual neurons, and predicted trial-by-trial memory performance. Moreover, optogenetic suppression of plastic inputs from the upstream left CA3 region during learning selectively impaired the computation of contingency-discriminating, but not space-representing CA1 coactivity patterns. This manipulation, but not silencing the more stable right CA3 inputs, impaired memory of the contingency discrimination. Thus, the computation of an emergent, coactivity-based discrimination code necessitates plastic synapses and supports dynamic, two-contingency memory.

neuroscience↗