University of Twente Student Theses


The Influence of Spike-Timing Dependent Plasticity on Synaptic Connectivity of Coupled Inhibitory Neurons

Geerts, S.J. (2019) The Influence of Spike-Timing Dependent Plasticity on Synaptic Connectivity of Coupled Inhibitory Neurons.

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Abstract:Inhibitory neurons exist throughout the brain, and many brain nuclei function inhibitory on other nuclei as well, some involved in diseases such as Parkinson's disease. Investigating the coupling of these neurons might lead to new insight for developing techniques such as deep brain stimulation further. The effect of spike-timing-dependent plasticity (STDP) is studied on a leaky integrate-and-fire model to characterise the final weight configurations. To simplify analysis, a sinusoidal-coupled phase-difference model is investigated. The framework of STDP is reformulated as phase-difference-dependent plasticity (PDDP) to study multiplicative learning rules. Moreover, weight dynamics is analysed using phase averages. The aim is to study the effect of two main parameters, the strength of additive noise and the difference in intrinsic frequency on the synaptic connectivity. It is concluded that large noise induces stable bidirectional coupling. Bistability of unidirectional coupling and weak bidirectional coupling is observed in the phase-difference model. Moreover, increasing the intrinsic frequency difference interchanges the type of unidirectional coupling for small additive noise. Typically, in both models we observe decoupling of the neurons to be unstable, therefore, neurons will never decouple but synchronise in firing frequency. Stable firing patterns are only observed for large synaptic weight values compared to detuning frequency.
Item Type:Essay (Bachelor)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:31 mathematics, 42 biology, 50 technical science in general
Programme:Applied Mathematics BSc (56965)
Keywords:Firing patterns, LIF, PDDP, Phase-difference, STDP, Weight stability
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