2019
DOI: 10.48550/arxiv.1910.05761
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Inferring network structure and local dynamics from neuronal patterns with quenched disorder

Abstract: An inverse procedure is proposed and tested which aims at recovering the a priori unknown functional and structural information from global signals of living brains activity. To this end we consider a Leaky-Integrate and Fire (LIF) model with short term plasticity neurons, coupled via a directed network. Neurons are assigned a specific current value, which is heterogenous across the sample, and sets the firing regime in which the neuron is operating in. The aim of the method is to recover the distribution of i… Show more

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Cited by 2 publications
(12 citation statements)
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“…As mentioned above, individual excitability acts as a key component of the dynamics and yields irregular patterns of activity like those displayed in real measurements. The reconstruction scheme was applied in [5] to longitudinal wide-field fluorescence microscopy data of cortical functionality in groups of awake mice and enabled us to identify altered distributions in neuron excitability immediately after the stroke, and in agreement with earlier observation [14][15][16]. Conversely, rehabilitation allowed to recover a distribution similar to pre-stroke conditions.…”
Section: Introductionsupporting
confidence: 63%
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“…As mentioned above, individual excitability acts as a key component of the dynamics and yields irregular patterns of activity like those displayed in real measurements. The reconstruction scheme was applied in [5] to longitudinal wide-field fluorescence microscopy data of cortical functionality in groups of awake mice and enabled us to identify altered distributions in neuron excitability immediately after the stroke, and in agreement with earlier observation [14][15][16]. Conversely, rehabilitation allowed to recover a distribution similar to pre-stroke conditions.…”
Section: Introductionsupporting
confidence: 63%
“…Motivated by this, in [5] we proposed and tested against both synthetic and real data, an inverse scheme to quantify the statistics of neurons' excitability, while inferring, from global activity measurements, the, a priori unknown, distribution of network connectivities. The method employs an extended model of Leaky-Integrate and Fire (LIF) neurons, with short-term plasticity.…”
Section: Introductionmentioning
confidence: 99%
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