Biology subjects

Vicente, A. F.

Publications and source records attributed to Vicente, A. F..

2 recordsLinked to original sources

bioRxiv2019

In vivo characterization of neurophysiological diversity in the lateral supramammillary nucleus during hippocampal sharp-wave ripples of adult rats

The extent of the networks that control the genesis and modulation of hippocampal sharp wave ripples (SPW-Rs), which are involved in memory consolidation, remains incompletely understood. Here, we performed a detailed in vivo analysis of single cell firing in the lateral supramammillary nucleus (lSuM) during theta and slow oscillations, including SPW-Rs, in anesthetized rats. We classified neurons as SPW-R-active and SPW-R unchanged according to whether or not they increased their firing during SPW-Rs. We show that lSuM SPW-R-active neurons increase their firing prior SPW-Rs peak power and prior hippocampal pyramidal cell activation. Moreover, lSuM SPW-R-active neurons show increased firing activity during theta and slow oscillations as compared to unchanged-neurons. SPW-R-active neurons are more active during high peak power SPW-Rs, whereas SPW-R-unchanged neurons are more active during long SPW-Rs. These results suggest that a sub-population of lSuM neurons can interact with the hippocampus during SPW-Rs, raising the possibility that the lSuM may modulate memory consolidation.

neuroscience↗

bioRxiv2019

Computing Hubs in the Hippocampus and Cortex

Neural computation, which relies on the active storage and sharing of information, occurs within large neuron networks in the highly dynamic context of varying brain states. Whether such functions are performed by specific subsets of neurons and whether they occur in specific dynamical regimes remain poorly understood. Using high density recordings in the hippocampus, medial entorhinal and medial prefrontal cortex of the rat, we identify computing microstates, or discreet epochs, in which specific computing hub neurons perform well defined storage and sharing operations in a brain state-dependent manner. We retrieve a multiplicity of distinct computing microstates within each global brain state, such as REM and nonREM sleep. Half of recorded neurons act as computing hubs in at least one microstate, suggesting that functional roles are not firmly hardwired but dynamically reassigned at the second timescale. We identify sequences of microstates whose temporal organization is dynamic and stands between order and disorder. We propose that global brain states constrain the language of neuronal computations by regulating the syntactic complexity of these microstate sequences.

neuroscience↗