Biology subjects

Compte, A.

Publications and source records attributed to Compte, A..

4 recordsLinked to original sources

bioRxiv2018

Active information maintenance in working memory by a sensory cortex

Working memory is a critical function of the brain to maintain and manipulate information over delay periods of seconds. Sensory areas have been implicated in working memory; however, it is debated whether the delay-period activity of sensory regions is actively maintaining information or passively reflecting top-down inputs. We hereby examined the anterior piriform cortex, an olfactory cortex, in head-fixed mice performing a series of olfactory working memory tasks. Information maintenance is necessary in these tasks, especially in a dual-task paradigm in which mice are required to perform another distracting task while actively maintaining information during the delay period. Optogenetic suppression of the piriform cortex activity during the delay period impaired performance in all the tasks.Furthermore, electrophysiological recordings revealed that the delay-period activity of the anterior piriform cortex encoded odor information with or without the distracting task.Thus, this sensory cortex is critical for active information maintenance in working memory.

neuroscience↗

bioRxiv2017

Subgenual anterior cingulate cortex controls sadness-induced modulations of cognitive and emotional network hubs

The regulation of cognitive and emotional processes is critical for proper executive functions and social behavior, but its specific mechanisms remain unknown. Here, we addressed this issue by studying with functional magnetic resonance imaging the changes in network topology that underlie competitive interactions between emotional and cognitive networks in healthy participants. Our behavioral paradigm contrasted periods with high emotional and cognitive demands by including a sadness provocation task followed by a spatial working memory task. We hypothesized that this paradigm would enhance the modularity of emotional and cognitive networks and reveal the hub areas that regulate the flow of information between them. By applying graph analysis methods on functional connectivity between 20 regions of interest in 22 participants we identified two main brain network modules, one cognitive and one emotional, and their hub areas: the left dorsolateral prefrontal cortex (dlPFC) and the left medial frontal pole (mFP). These hub areas did not modulate their mutual functional connectivity following sadness but they did so through an interposed area, the subgenual anterior cingulate cortex (sACC). Our results identify dlPFC and mFP as areas regulating interactions between emotional and cognitive networks, and suggest that their modulation by sadness experience is mediated by sACC.

neuroscience↗

bioRxiv2017

Mean-Field Equations For Neuronal Networks With Arbitrary Degree Distributions

The emergent dynamics in networks of recurrently coupled spiking neurons depends on the interplay between single-cell dynamics and network topology. Most theoretical studies on network dynamics have assumed simple topologies, such as connections which are made randomly and independently with a fixed probability (Erdos-Renyi network) (ER), or all-to-all connected networks. However, recent findings from slice experiments suggest that the actual patterns of connectivity between cortical neurons are more structured than in the ER random network. Here we explore how introducing additional higher-order statistical structure into the connectivity can affect the dynamics in neuronal networks. Specifically, we consider networks in which the number of pre-synaptic and post-synaptic contacts for each neuron, the degrees, are drawn from a joint degree distribution. We derive mean-field equations for a single population of homogeneous neurons and for a network of excitatory and inhibitory neurons, where the neurons can have arbitrary degree distributions. Through analysis of the mean-field equations and simulation of networks of integrate-and-fire neurons, we show that such networks have potentially much richer dynamics than an equivalent ER network. Finally, we relate the degree distributions to so-called cortical motifs.

neuroscience↗

bioRxiv2016

UP-DOWN cortical dynamics reflect state transitions in a bistable balanced network

In the idling brain, neuronal circuits often exhibit transitions between periods of sustained firing (UP state) and quiescence (DOWN state). Although these dynamics occur across multiple areas and behavioral conditions, the underlying mechanisms remain unclear. Here we analyze spontaneous population activity from the somatosensory cortex of urethane-anesthetized rats. We find that UP and DOWN periods are variable (i.e. non-rhythmic) and that the population rate shows no significant decay during UP periods. We build a network model of excitatory (E) and inhibitory (I) neurons that exhibits a new bistability between a quiescent state and a balanced state of arbitrarily low rate. Fluctuating inputs trigger state transitions. Adaptation in E cells paradoxically causes a marginal decay of E-rate but a marked decay of I-rate, a signature of balanced bistability that we validate experimentally. Our findings provide evidence of a bistable balanced network that exhibits non-rhythmic state transitions when the brain rests.

neuroscience↗