SINKRONISASI JARINGAN SARAF MODEL NEURON MORRIS-LECAR DENGAN SHORT-TERM SYNAPTIC PLASTICITY (STSP)

Retno Dwi Astuti, NIM.: 17106020001 (2023) SINKRONISASI JARINGAN SARAF MODEL NEURON MORRIS-LECAR DENGAN SHORT-TERM SYNAPTIC PLASTICITY (STSP). Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

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Abstract

A study of neural network synchrony using the Morris-Lecar neuron model coupled with Short-Term Synaptic Plasticity (STSP) has been conducted. This research was designed to simulate neuronal connectivity and synaptic patterns at certain connection probabilities, model a neural network and analyze synchrony activity, examine the post-synaptic conductance patterns in the modeled neural network, investigate the dynamics of the neural network membrane potentials in the synchronous state, analyze the Short-Term Plasticity (STP) synaptic transmission patterns, and determine the frequency of neural network synchrony. This computational-based study was executed using the Brian2 Simulator and the differential equation solution was solved by the Euler method. The total number of neurons in the modeled network was 60, consisting of 50 excitatory neurons (ne) and 10 inhibitory neurons (ni). The inter-neuron connection probability varied from 0,5 to 0,8 for excitatory neuron connection probability (pe) and 0,1 to 0,4 for inhibitory neuron connection probability (pi). The results reveal that the higher the connectivity probability, the more connections and synapses are formed. The greater the value of pe, the more synchronous the neural network activity is. In contrast, the higher the value of pi, the less synchronous the neural network activity is. A synchronous neural network implies that the spikes occur coincidentally. Coincidental spikes lead to easily detectable membrane potentials and postsynaptic conductance. Furthermore, spikes affect the release of neurotransmitters, thereby affecting synaptic transmission patterns. The final average frequency of this neural network synchrony is 15,1959 Hz.

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