Emergence of the small-world architecture in neural networks by activity dependent growth

Gafarov, Fail

doi:10.1016/j.physa.2016.06.016

Cited by 10 publications

(8 citation statements)

References 45 publications

(62 reference statements)

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“…They inferred that the formation of small‐worldness was associated with the improvement of the information process in neuronal networks . Based on mathematically modelling the growth and development of neuronal networks, Gafarov analyzed the synaptic connection patterns and demonstrated that the mature neuronal network has a small cosmopolitan nature and the connection is non‐Gaussian distribution .…”

Section: Introductionmentioning

confidence: 99%

Characterization of in vitro neural functional connectivity on a neurofluidic device

Shen

Wang

et al. 2019

Electrophoresis

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Understanding the mechanism of functional connectivity in neural system is of great benefit to lot of researches and applications. Microfluidics and microelectrode arrays (MEAs) have been frequently utilized for in vitro neural cultures study. However, there are few studies on the functional connectivity of neural cultures grown on a microfluidic chip. It is intriguing to unveil the influences of microfluidic structures on in vitro neuronal networks from the perspective of functional connectivity. Hence, in the present study, a device was established, which comprised a microfluidic chamber for cell growth and a MEA substrate for recording the electrophysiological response of the neuronal networks. The network topology, neural firing rate, neural bursting rate and network burst frequency were adopted as representative characteristics for neuronal networks analysis. Functional connectivity was estimated by means of cross‐covariance analysis and graph theory. The results demonstrated that the functional connectivity of the in vitro neuronal networks formed in the microchannel has been apparently reinforced, corresponding to improve neuronal network density and increased small‐worldness.

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Section: Introductionmentioning

confidence: 99%

Characterization of in vitro neural functional connectivity on a neurofluidic device

Shen

Wang

et al. 2019

Electrophoresis

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“…The coupling between the neurons is described by the synaptic current I syn . In the model, GPe and GPi neurons are connected through a Watts and Strogatz (WS) smallworld topology (Watts and Strogatz 1998;Bullmore and Sporns 2009;Stam and Reijneveld 2007;Gafarov 2016;De Santos-Sierra et al 2014;Netoff et al 2004;Bertalan et al 2017;Fang et al 2017), where neurons nearby are densely connected; additionally, a small number of large distance connections exist. Following the experimental findings (Gouty-Colomer et al 2018) which suggest sparse connec-tions in the STN area, we chose a modified small-world topology with sparse internal connectivity.…”

Section: Description Of the Basal Ganglia Synaptic Connectivitymentioning

confidence: 99%

“…The coupling between the neurons is described by the synaptic current . In the model, GPe and GPi neurons are connected through a Watts and Strogatz (WS) small-world topology (Watts and Strogatz 1998 ; Bullmore and Sporns 2009 ; Stam and Reijneveld 2007 ; Gafarov 2016 ; De Santos-Sierra et al. 2014 ; Netoff et al.…”

Section: Mathematical Modelling Of Basal Ganglia and Thalamic Neuronsmentioning

confidence: 99%

Deep brain stimulation for movement disorder treatment: exploring frequency-dependent efficacy in a computational network model

et al. 2021

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A large-scale computational model of the basal ganglia network and thalamus is proposed to describe movement disorders and treatment effects of deep brain stimulation (DBS). The model of this complex network considers three areas of the basal ganglia region: the subthalamic nucleus (STN) as target area of DBS, the globus pallidus, both pars externa and pars interna (GPe-GPi), and the thalamus. Parkinsonian conditions are simulated by assuming reduced dopaminergic input and corresponding pronounced inhibitory or disinhibited projections to GPe and GPi. Macroscopic quantities are derived which correlate closely to thalamic responses and hence motor programme fidelity. It can be demonstrated that depending on different levels of striatal projections to the GPe and GPi, the dynamics of these macroscopic quantities (synchronisation index, mean synaptic activity and response efficacy) switch from normal to Parkinsonian conditions. Simulating DBS of the STN affects the dynamics of the entire network, increasing the thalamic activity to levels close to normal, while differing from both normal and Parkinsonian dynamics. Using the mentioned macroscopic quantities, the model proposes optimal DBS frequency ranges above 130 Hz.

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“…Criticality has been claimed for explaining the brain since long ago (Bak, 1996), but it is in the last decade that a group of research articles have presented evidence of its presence and discussing its implications Fraiman et al, 2009;Haimovici et al, 2013;Hudetz et al, 2014;Marinazzo et al, 2014;Stramaglia, 2014;Tagliazucchi et al, 2012). However, criticality does not mean the same thing when studying the small-world properties of anatomical or functional (mathematically derived) networks (Bullmore & Sporns, 2009;Gafarov, 2016;Rubinov & Sporns, 2010;M.P. van den Heuvel, Stam, Boersma, & Hulshoff Pol, 2008), or the power-law distribution of functional data (Chialvo, 2004(Chialvo, , 2010Expert et al, 2011;Fraiman et al, 2009;Fraiman, Chialvo, & Breakspear, 2012;Sporns, Chialvo, Kaiser, & Hilgetag, 2004;Tagliazucchi et al, 2012), or the information transfer in an Ising model (Marinazzo et al, 2014) or when proposing non-linear functional dynamics on anatomically connected nodes (Haimovici et al, 2013).…”

Section: Predicting Rsns Of Pathological Networkmentioning

confidence: 99%

“…Even more, the functional maps can change with time from pathological patterns to normal patterns in the same structural network, which indicates that there might be functional mechanisms involved in reestablishing the critical conditions. Some recent studies have shown that the phenomenon of nerve growth can be driven by functional activity, which means that the anatomical reorganization is oriented to functional optimality (Gafarov, 2016(Gafarov, , 2018. However, in the case of severe damage or change in the topology of brain network, such as Callosotomy in adults, this mechanism does not seem to account for the full restoration of criticality.…”

Section: Predicting Rsns Of Pathological Networkmentioning

confidence: 99%

Modeling functional resting-state brain networks through neural message passing on the human connectome

et al. 2020

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Understanding the relationship between the structure and function of the human brain is one of the most important open questions in Neurosciences. In particular, Resting State Networks (RSN) and more specifically the Default Mode Network (DMN) of the brain, which are defined from the analysis of functional data lack a definitive justification consistent with the anatomical structure of the brain. In this work we show that a possible connection may naturally rest on the idea that information flows in the brain through a neural message-passing dynamics between macroscopic structures, like those defined by the human connectome (HC). In our model, each brain region in the HC is assumed to have a binary behavior (active or not), the strength of interactions among them is encoded in the anatomical connectivity matrix defined by the HC, and the dynamics of the system is defined by a neural message-passing algorithm, Belief Propagation (BP), working near the critical point of the human connectome. We show that in the absence of direct external stimuli the BP algorithm converges to a spatial map of activations that is similar to the DMN. Moreover, we computed, using Susceptibility Propagation (SP), the matrix of correlations between the different regions and show that the modules defined by a clustering of this matrix resemble several Resting States Networks determined experimentally. Both results suggest that the functional DMN and RSNs can be seen as simple consequences of the anatomical structure of the brain and a neural message-passing dynamics between macroscopic regions. We then show preliminary results indicating our predictions on how functional DMN maps change when the anatomical brain network suffers structural anomalies, like in Alzheimer's Disease and in lesions of the Corpus Callosum.

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Emergence of the small-world architecture in neural networks by activity dependent growth

Cited by 10 publications

References 45 publications

Characterization of in vitro neural functional connectivity on a neurofluidic device

Characterization of in vitro neural functional connectivity on a neurofluidic device

Deep brain stimulation for movement disorder treatment: exploring frequency-dependent efficacy in a computational network model

Modeling functional resting-state brain networks through neural message passing on the human connectome

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