Effect of the small-world structure on encoding performance in the primary visual cortex: an electrophysiological and modeling analysis

Shi, Li; Niu, Xiaoke; Wan, Hong

doi:10.1007/s00359-015-0996-5

Cited by 7 publications

(9 citation statements)

References 43 publications

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“…Moreover, correlations between three units are necessary to recapitulate spatiotemporal spiking patterns [30]. Computationally, triplet motifs may improve coding [31,32] and enhance perceptual accuracy and the prediction of responses in visual cortex [28,33]. The causal relation from underlying synaptic connections to functional connections and correlations in activity within a network is complex [29,34].…”

Section: Introductionmentioning

confidence: 99%

Cyclic transitions between higher order motifs underlie sustained asynchronous spiking in sparse recurrent networks

2020

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A basic-yet nontrivial-function which neocortical circuitry must satisfy is the ability to maintain stable spiking activity over time. Stable neocortical activity is asynchronous, critical, and low rate, and these features of spiking dynamics contribute to efficient computation and optimal information propagation. However, it remains unclear how neocortex maintains this asynchronous spiking regime. Here we algorithmically construct spiking neural network models, each composed of 5000 neurons. Network construction synthesized topological statistics from neocortex with a set of objective functions identifying naturalistic low-rate, asynchronous, and critical activity. We find that simulations run on the same topology exhibit sustained asynchronous activity under certain sets of initial membrane voltages but truncated activity under others. Synchrony, rate, and criticality do not provide a full explanation of this dichotomy. Consequently, in order to achieve mechanistic understanding of sustained asynchronous activity, we summarized activity as functional graphs where edges between units are defined by pairwise spike dependencies. We then analyzed the intersection between functional edges and synaptic connectivity-i.e. recruitment networks. Higherorder patterns, such as triplet or triangle motifs, have been tied to cooperativity and integration. We find, over time in each sustained simulation, low-variance periodic transitions between isomorphic triangle motifs in the recruitment networks. We quantify the phenomenon as a Markov process and discover that if the network fails to engage this stereotyped regime of motif dominance "cycling", spiking activity truncates early. Cycling of motif dominance generalized across manipulations of synaptic weights and topologies, demonstrating the robustness of this regime for maintenance of network activity. Our results point to the crucial role of excitatory higher-order patterns in sustaining asynchronous activity in sparse recurrent networks. They also provide a possible explanation why such connectivity and activity patterns have been prominently reported in neocortex.

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Section: Introductionmentioning

confidence: 99%

Cyclic transitions between higher order motifs underlie sustained asynchronous spiking in sparse recurrent networks

2020

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“…Researchers have found that biological networks generally have the characteristics of small-world network properties, that is, the network has a large clustering coefficient and a short characteristic path length (Watts and Strogatz, 1998 ; Strogatz, 2001 ). Shi et al found in electrophysiological recordings of primary visual cortex in mice that their coding properties have small-world structural properties (Shi et al, 2015 ). He et al applied the reciprocal of global efficiency instead of the traditional characteristic path length in the study of magnetic resonance brain network characteristics, effectively avoiding the problem of isolated points of the network (Liao et al, 2017 ).…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of Standardized Infinity Reference and Average Reference for EEG of Three Typical Brain States

Zheng

et al. 2018

Front. Neurosci.

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The choice of different reference electrodes plays an important role in deciphering the functional meaning of electroencephalography (EEG) signals. In recent years, the infinity zero reference using the reference electrode standard technique (REST) has been increasingly applied, while the average reference (AR) was generally advocated as the best available reference option in previous classical EEG studies. Here, we designed EEG experiments and performed a direct comparison between the influences of REST and AR on EEG-revealed brain activity features for three typical brain behavior states (eyes-closed, eyes-open and music-listening). The analysis results revealed the following observations: (1) there is no significant difference in the alpha-wave-blocking effect during the eyes-open state compared with the eyes-closed state for both REST and AR references; (2) there was clear frontal EEG asymmetry during the resting state, and the degree of lateralization under REST was higher than that under AR; (3) the global brain functional connectivity density (FCD) and local FCD have higher values for REST than for AR under different behavior states; and (4) the value of the small-world network characteristic in the eyes-closed state is significantly (in full, alpha, beta and gamma frequency bands) higher than that in the eyes-open state, and the small-world effect under the REST reference is higher than that under AR. In addition, the music-listening state has a higher small-world network effect than the eyes-closed state. The above results suggest that typical EEG features might be more clearly presented by applying the REST reference than by applying AR when using a 64-channel recording.

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“…390 The necessity of higher-order patterns for stable activity has strong implications for 391 neural coding. Previous work has already demonstrated that correlations enhance 392 coding, with triplet correlations having an advantage over pairwise 393 [5,16,18,[21][22][23][52][53][54]. The neural code must rest upon a foundation of stable 394 propagation of spikes, which we have shown in turn rests on higher-order motifs and 395 coordinated integration.…”

mentioning

confidence: 77%

“…The term 'motif' refers to a pattern formed by a group of units in a network. Previously 170 we found that triplet motifs were informative of synaptic integration [19] and also 171 increased the power of encoding models [18,[21][22][23]. Here we focused our analysis on 172 similar patterns of connectivity in the recruitment network, involving groups of three 173 units [43].…”

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confidence: 98%

Cyclic transitions between higher order motifs underlie sustained activity in asynchronous sparse recurrent networks

Bojanek

Zhu

MacLean

2019

Preprint

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Many studies have demonstrated the prominence of higher-order patterns in excitatory synaptic connectivity as well as activity in neocortex. Surveyed as a whole, these results suggest that there may be an essential role for higher-order patterns in neocortical function. In order to stably propagate signal within and between regions of neocortex, the most basic -yet nontrivial -function which neocortical circuitry must satisfy is the ability to maintain stable spiking activity over time. Here we algorithmically construct spiking neural network models comprised of 5000 neurons using topological statistics from neocortex and a set of objective functions that identify networks which produce naturalistic low-rate, asynchronous, and critical activity. We find that the same network topology can exhibit either sustained activity under one set of initial membrane voltages or truncated activity under a different set. Yet these two outcomes are not readily differentiated by rate or criticality. By summarizing the statistical dependencies in the pairwise activity of neurons as directed weighted functional networks, we examined the transient manifestations of higher-order motifs in the functional networks across time. We find that stereotyped low variance cyclic transitions between three isomorphic triangle motifs, quantified as a Markov process, are required for sustained activity. If the network fails to engage the dynamical regime characterized by a recurring stable pattern of motif dominance, spiking activity ceased. Motif cycling generalized across manipulations of synaptic weights and across topologies, demonstrating the robustness of this dynamical regime for sustained spiking in critical asynchronous network activity. Our results point to the necessity of higher-order patterns amongst excitatory connections for sustaining activity in sparse recurrent networks. They also provide a possible explanation as to why such excitatory synaptic connectivity and activity patterns have been prominently reported in neocortex. Author summaryHere we address two questions. First, it remains unclear how activity propagates stably through a network since neurons are leaky and connectivity is sparse and weak. Second, higher order patterns abound in neocortex, hinting at potential functional relevance for their presence. Several lines of evidence suggest that higher-order network interactions September 16, 2019 1/23 may be instrumental for spike propagation. For example, excitatory synaptic connectivity shows a prevalence of local neuronal cliques and patterns, and propagating activity in vivo displays elevated clustering dominated by specific triplet motifs. In this study we demonstrate a mechanistic link between activity propagation and higher-order motifs at the level of individual neurons and across networks. We algorithmically build spiking neural network (SNN) models to mirror the topological and dynamical statistics of neocortex. Using a combination of graph theory, information theory, and probabilistic tools, we show that higher ...

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Effect of the small-world structure on encoding performance in the primary visual cortex: an electrophysiological and modeling analysis

Cited by 7 publications

References 43 publications

Cyclic transitions between higher order motifs underlie sustained asynchronous spiking in sparse recurrent networks

Cyclic transitions between higher order motifs underlie sustained asynchronous spiking in sparse recurrent networks

A Comparative Study of Standardized Infinity Reference and Average Reference for EEG of Three Typical Brain States

Cyclic transitions between higher order motifs underlie sustained activity in asynchronous sparse recurrent networks

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