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Mohd Hafiz Mohd

Publications and source records attributed to Mohd Hafiz Mohd.

2 recordsLinked to original sources

Collective dynamics in spiking neural networks: A systematic review

This study aims to identify typical collective phenomena that emerge in excitatory and inhibitory (E-I) spiking neural networks as reported in recent computational studies. The research methodology used is Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) procedures, comprising three primary stages: an initial search for literature in the SCOPUS database, a screening process based on specific inclusion and exclusion criteria, and a review of the selected literatures. Out of 491 documents from 2014 to 2024, six research papers are selected in the review stage. Four generic collective regimes have been identified, including synchrony, irregular behavior, stationary state, and oscillatory patterns. Our review findings suggest that the collective dynamics of E-I spiking neurons stem from the interplay of intrinsic neuronal characteristics, network topology, and external stimuli. Additionally, the prevalent use of Quadratic Integrate-and-Fire (QIF) neuron model in the literature highlights its significance as a robust candidate for exploring collective behaviors in large-scale neuronal networks. The findings outlined in this paper might be useful for individuals who lack prior familiarity with computational modelling of spiking neurons but have an interest in the field.

q-bio.NC↗

The interplay of common noise and finite pulses on biological neurons

The response of neurons is highly sensitive to the stimulus. The stimulus can be associated with a direct injection in vitro experimentation (e.g., time dependent and independent inputs); or post-synaptic potentials resulting from the interaction of many neurons. A typical incoming stimulus resembles a noise which in principle can be described as a random variable. In computational neuroscience, the noise has been extensively studied for different setups. In this study, we investigate the effect of noisy inputs in a minimal network of two identical leaky integrate-and-fire (LIF) neurons interacting with finite pulses. In particular, we consider a Gaussian white noise as a standard function for stochastic modelling of neurons, while taking into account the pulse width as an elementary component for the signal transmission. By exploring the role of noise and finite pulses, the two neurons show a synchronous spiking behaviour characterized by fluctuations in the interspike intervals. Above some critical values the synchronous regime collapses onto asynchronous dynamics. The abrupt change in such dynamics is accompanied by a hysteresis, i.e., the coexistence of synchronous and asynchronous firing behaviour.

q-bio.NC↗