2019
DOI: 10.3389/fncom.2019.00057
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Cellular and Network Mechanisms for Temporal Signal Propagation in a Cortical Network Model

Abstract: The mechanisms underlying an effective propagation of high intensity information over a background of irregular firing and response latency in cognitive processes remain unclear. Here we propose a SSCCPI circuit to address this issue. We hypothesize that when a high-intensity thalamic input triggers synchronous spike events (SSEs), dense spikes are scattered to many receiving neurons within a cortical column in layer IV, many sparse spike trains are propagated in parallel along minicolumns at a substantially h… Show more

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Cited by 3 publications
(3 citation statements)
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References 98 publications
(130 reference statements)
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“…With millisecond fidelity, precisely synchronized action potentials can propagate within a model of cortical network activity that mimics many of the characteristics of biological systems. This model demonstrates how time intervals and periodicity of operation can be determined by simulating synaptic learning in a neural circuit model based on neural connections (Durstewitz et al, 2000;He, 2019). Using a model of cortical network activity, Diesmann et al (1999) showed that precisely synchronized action potentials can propagate with millisecond accuracy.…”
Section: Population Propagation Of Neural Activity Under Weak Gabaerg...mentioning
confidence: 84%
“…With millisecond fidelity, precisely synchronized action potentials can propagate within a model of cortical network activity that mimics many of the characteristics of biological systems. This model demonstrates how time intervals and periodicity of operation can be determined by simulating synaptic learning in a neural circuit model based on neural connections (Durstewitz et al, 2000;He, 2019). Using a model of cortical network activity, Diesmann et al (1999) showed that precisely synchronized action potentials can propagate with millisecond accuracy.…”
Section: Population Propagation Of Neural Activity Under Weak Gabaerg...mentioning
confidence: 84%
“…process. Newton's second law derives the NALRI process 2930 and describes nonlinear stochastic systems in inelastic (e.g., economics 2931 ) and elastic (e.g., neurophysiology 32 , cardiology 33 ) fields. The explanatory power of the results is guaranteed by the explicit physical meaning of the model structure and parameters 2930 , by the precise dynamic 30 and fractal mechanisms 27 ,a n db y established statistical properties 34 .…”
Section: Introductionmentioning
confidence: 99%
“…Heart rate is controlled by a stochastic self-restoring mechanism. In recent years, there has been a growing interest in the nonlinear autoregressive integrated (NLARI) process derived by applying Newton's second law to stochastic self-restoring systems [34][35][36][37][38] . The NLARI process can exhibit the main HR features as mentioned above.…”
mentioning
confidence: 99%