Can scale-freeness offset delayed signal detection in neuronal networks?

Abstract

-First spike latency following stimulus onset is of significant physiological relevance. Neurons transmit information about their inputs by transforming them into spike trains, and the timing of these spike trains is in turn crucial for effectively encoding that information. Random processes and uncertainty that underly neuronal dynamics have been shown to prolong the time towards the first response in a phenomenon dubbed noise-delayed decay. Here we study whether Hodgkin-Huxley neurons with a tunable intensity of intrinsic noise might have shorter response times to external stimuli just above threshold if placed on a scale-free network. We show that the heterogeneity of the interaction network may indeed eradicate slow responsiveness, but only if the coupling between individual neurons is sufficiently strong. Increasing the average degree also favors a fast response, but it is less effective than increasing the coupling strength. We also show that noise-delayed decay can be offset further by adjusting the frequency of the external signal, as well as by blocking a fraction of voltage-gated sodium or potassium ion channels. For certain conditions, we observe a double peak in the response time depending on the intensity of intrinsic noise, indicating competition between local and global effects on the neuronal dynamics.

Effects of channel noise on synchronization transitions in Newman–Watts neuronal network with time delays

“…Since Hodgkin and Huxley's pioneering work [31], the role of noise has been extensively studied in the generation and propagation of the membrane potential of neurons, and stochastic resonance (SR) and coherence resonance (CR) have been found in various neuronal systems (see e.g., [32][33][34]). In recent decade, some SR and CR phenomena due to channel noise in neuronal networks have been found, such as sodium and potassium channel block reduced and enhanced spiking coherence of neuronal network, respectively [35,36], channel noise enhanced propagation of pacemaker signals across neuronal networks [37] and weak signal across feed-forward neuronal networks [38], and channel noise decreased mean latency and jitter of the first spikes in response to subthreshold signal [39,40] and degraded signal detection capability of neuronal network [41], as well as channel block resonantly enhanced spiking regularity of clustered neuronal networks [42]. It is also shown that noise can induce and enhance synchronization in excitable media [43], coupled thermo-sensitive neurons [44], and neuronal networks [45].…”

Effects of autapse and channel blockage on firing regularity in a biological neuronal network

“…In equation (1), GNa, GK and GL denote sodium, potassium and leakage ion channel conductance, respectively. In the model, the leakage conductance is constant, GL=0.3mScm -2 , whereas the others dynamically change as follows [30,34,37,38]:…”

“…For a given membrane, by a fine-tuned addition of these toxins a certain portion of potassium-and sodium ion channels could be disabled or blocked and hence the number of active (working) ion channels can be reduced. There are also plenty of studies based on different computational neuron models, where the impacts of changing the number of particular ion channels on firing dynamics of a single neuron or neuronal networks' is examined [30][31][32][33][34][35][36][37][38]. In these studies, it is uncovered that channel blocking has crucial impacts on firing dynamics.…”

Autaptic Modulation of Electrical Activity in a Network of Neuron-Coupled Astrocyte

“…Based on the wellknown neuron models, networks with different topological connections have been set to investigate the synchronization stability [36,37], pattern selection, and mode transition in collective behaviors [38][39][40][41][42][43][44][45]. Indeed, reliable and biophysical neuron model is critical and important for further investigation on neurodynamics and potential mechanism of some neuronal diseases [46].…”