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Article overview
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Dynamics of multi-stable states during ongoing and evoked cortical activity | | Luca Mazzucato
; Alfredo Fontanini
; Giancarlo La Camera
; | | Date: |
1 Aug 2015 | | Abstract: | Single trial analyses of ensemble activity in alert animals demonstrate that
cortical circuits dynamics evolve through temporal sequences of metastable
states. Metastability has been studied for its potential role in sensory
coding, memory and decision-making. Yet, very little is known about the network
mechanisms responsible for its genesis. It is often assumed that the onset of
state sequences is triggered by an external stimulus. Here we show that state
sequences can be observed also in the absence of overt sensory stimulation.
Analysis of multielectrode recordings from the gustatory cortex of alert rats
revealed ongoing sequences of states, where single neurons spontaneously attain
several firing rates across different states. This single neuron
multi-stability represents a challenge to existing spiking network models,
where typically each neuron is at most bi-stable. We present a recurrent
spiking network model that accounts for both the spontaneous generation of
state sequences and the multi-stability in single neuron firing rates. Each
state results from the activation of neural clusters with potentiated
intra-cluster connections, with the firing rate in each cluster depending on
the number of active clusters. Simulations show that the models ensemble
activity hops among the different states, reproducing the ongoing dynamics
observed in the data. When probed with external stimuli, the model predicts the
quenching of single neuron multi-stability into bi-stability and the reduction
of trial-by-trial variability. Both predictions were confirmed in the data.
Altogether, these results provide a theoretical framework that captures both
ongoing and evoked network dynamics in a single mechanistic model. | | Source: | arXiv, 1508.0165 | | Services: | Forum | Review | PDF | Favorites | |
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