SIMULASI PEMBENTUKAN SINAPSIS, SINYAL ANTAR NEURON, DAN MODEL PLASTISITAS SINAPSIS

Ahyunadi, NIM.: 1710602005 (2022) SIMULASI PEMBENTUKAN SINAPSIS, SINYAL ANTAR NEURON, DAN MODEL PLASTISITAS SINAPSIS. Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

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Abstract

Synapses are plastic junctions between neurons. Research on synapse modeling in computational neural network studies is still being developed because there are still many debates that arise from neuroscientists regarding the modeling or the parameters used. Synapses have an important role for neurons where through synapses, information obtained by neurons can be transmitted to other neurons. In this study, simulations of synapse formation were made with variations in connection probabilities, simulations of signals between neurons with variations in the addition of synaptic weights and signal delay times, simulations of STDP synapses and STDP inverse models. The simulation was created using the Brian2 Simulator. Synapse formation is made with a variation of the connection probability 0.2; 0.5; and 1.0 and the number of neurons set is 15 neurons. In making a signal simulation between neurons with the addition of synaptic weights and delay time, the number of neurons is set to 4, namely neurons 0, 1, 2, and 3. Each of these neurons has the same membrane potential differential equation, but has different values for the parameters. I and t. Neuron 0 has I = 3 and t = 10 ms. Neurons 1, 2 and 3 have I = 0 and t = 100 ms. The STDP synapse model simulation was made with 100 neurons, t_max 50 ms, _pre and _post 20 ms, A_pre 0.02 and A_post 1.05. While the STDP inverse synapse model is made with the same parameters and values as STDP with a negative A_pre value. The visual form of each simulation result is shown in the research results section

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