A Framework for Simulation and Analysis of Dynamically Organized Distributed Neural Networks

Shaposhnyk, Vladyslav; Dutoit, Pierre; Contreras-Lámus, Victor; Perrig, Stephen; Villa, Alessandro E. P.

doi:10.1007/978-3-642-04274-4_29

Cited by 4 publications

(8 citation statements)

References 12 publications

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“…In the other modules the afferent and the efferent layers were formed by 450 and 900 excitatory cells, respectively. Synaptogenesis includes also the establishment of the connections between neural modules following a self-reflective mapping such that the number of inter-module projections from a particular efferent neuron is proportional to the number of intra-module projections of the same neuron (Shaposhnyk et al, 2009). Then, cells of the afferent and efferent layers receive and send excitatory projections to and from other neuronal modules in addition to their intra-module connections (of both excitatory and inhibitory types like any other cell).…”

Section: Hierarchical Network Of Modulesmentioning

confidence: 99%

“…In the present study we simulate the activity of interconnected modules of spiking neurons undergoing ontogenic and epigenetic developmental phases Villa, 2007, 2010). In addition to multiple spike trains we record neuromimetic signals, called electrochipograms (EChG), similar to ECoG and LFP, by the means of realistic virtual electrodes (Shaposhnyk et al, 2009). The neural circuit is characterized by two layers of feed-forward networks and we study the emergent properties of stimulus response in presence of feedback projections between the layers of networks and intra-layer projections (horizontal projections).…”

Section: Introductionmentioning

confidence: 99%

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Reciprocal projections in hierarchically organized evolvable neural circuits affect EEG-like signals

Shaposhnyk¹,

Villa²

2012

Brain Research

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Modular architecture is a hallmark of many brain circuits. In the cerebral cortex, in particular, it has been observed that reciprocal connections are often present between functionally interconnected areas that are hierarchically organized. We investigate the effect of reciprocal connections in a network of modules of simulated spiking neurons. The neural activity is recorded by means of virtual electrodes and EEG-like signals, called electrochipograms (EChG), analyzed by time- and frequency-domain methods. A major feature of our approach is the implementation of important bio-inspired processes that affect the connectivity within a neural module: synaptogenesis, cell death, spike-timing-dependent plasticity and synaptic pruning. These bio-inspired processes drive the build-up of auto-associative links within each module, which generate an areal activity, recorded by EChG, that reflect the changes in the corresponding functional connectivity within and between neuronal modules. We found that circuits with intra-layer reciprocal projections exhibited enhanced stimulus-locked response. We show evidence that all networks of modules are able to process and maintain patterns of activity associated with the stimulus after its offset. The presence of feedback and horizontal projections was necessary to evoke cross-layer coherence in bursts of -frequency at regular intervals. These findings bring new insights to the understanding of the relation between the functional organization of neural circuits and the electrophysiological signals generated by large cell assemblies. This article is part of a Special Issue entitled "Neural Coding".

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Section: Hierarchical Network Of Modulesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Reciprocal projections in hierarchically organized evolvable neural circuits affect EEG-like signals

Shaposhnyk¹,

Villa²

2012

Brain Research

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“…In our implementation the virtual electrode measures the potentials over a certain 'area' of the 2D lattice neuronal network according to an appropriate weighted sum [8]. The main parameters of the electode are its position over the neural network and its sensibility function.…”

Section: Electrochipogramsmentioning

confidence: 99%

“…The sensibility function depends only on the distance between a given point of the lattice and the centre of the electrode field. According to this model, all neurons located at the same radial distance from the center of the electrode field make an equivalent contribution to the final electrode output and thus form an equi-potential layer [8]. In this study, the sensibility radius was set equal to 9 with a linear decaying function.…”

Section: Electrochipogramsmentioning

confidence: 99%

“…The outcome is the implementation of each neural network into a Ubidule and a network of Ubidules as a Ubinet. Within each Ubidule the emergence of functional connectivity driven by neural development, cell and synaptic pruning, and selective external stimuli was assessed by recording Electrochipograms (EChG) which are analog signals similar to EEG generated by virtual electrodes located into each Ubidule [8].…”

Section: Introductionmentioning

confidence: 99%

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Functional Connectivity Driven by External Stimuli in a Network of Hierarchically Organized Neural Modules

Shaposhnyk

Dutoit

Perrig

et al. 2010

Artificial Neural Networks – ICANN 2010

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Abstract. Complex neural modules with embedded neural development and synaptic plasticity features have been connected to form a hierarchical recurrent circuit. Virtual electrodes have been used to record a "neural" generated signal, called electrochipogram EChG, from each module. The EChG are processed by frequency domain methods to determine the modifications in functional connectivity by assessing quadratic phase coupling. The experimental paradigm is aimed to describe what happened prior to, at the beginning, towards the end, and after repeating an external input at fixed frequency. The results are discussed by comparing with the same signal processing methods applied to a human study.

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An Effect of Short and Long Reciprocal Projections on Evolution of Hierarchical Neural Networks

Shaposhnyk

Villa

2012

Artificial Neural Networks and Machine Learning – ICANN 2012

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A Framework for Simulation and Analysis of Dynamically Organized Distributed Neural Networks

Cited by 4 publications

References 12 publications

Reciprocal projections in hierarchically organized evolvable neural circuits affect EEG-like signals

Reciprocal projections in hierarchically organized evolvable neural circuits affect EEG-like signals

Functional Connectivity Driven by External Stimuli in a Network of Hierarchically Organized Neural Modules

An Effect of Short and Long Reciprocal Projections on Evolution of Hierarchical Neural Networks

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