The interplay of inhibitory and electrical synapses results in complex persistent activity
Inhibitory neurons play a crucial role in maintaining persistent neuronal activity. Although connected extensively through electrical synapses (gap-junctions), these neurons also exhibit interactions through chemical synapses in certain regions of the brain. When the coupling is sufficiently strong, the effects of these two synaptic modalities combine in a nonlinear way. Hence, in this work, we focus on the strong inhibition regime and identify the parametric conditions that result in the emergence of self-sustained oscillations in systems of coupled excitable neurons, in the presence of a brief sub-threshold stimulus. Our investigation on the dynamics in a minimal network of two neurons reveals a rich set of dynamical behaviors viz., periodic and various complex oscillations including period-n (n=2,4,8...) dynamics and chaos. We further extend our study by considering a system of inhibitory neurons arranged in a one-dimensional ring topology and determine the optimal conditions for sustained activity. Our work highlights the nonlinear dynamical behavior arising due to the combined effects of gap-junctions and strong synaptic inhibition, which can have potential implications in maintaining robust memory patterns.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Optimal self-induced stochastic resonance in multiplex neural networks: electrical versus chemical synapses
Electrical and chemical synapses shape the dynamics of neural networks and their functional roles in information processing have been a longstanding question in neurobiology. In this paper, we investigate the role of syn…
Exact mean-field theory explains the dual role of electrical synapses in collective synchronization
Electrical synapses play a major role in setting up neuronal synchronization, but the precise mechanisms whereby these synapses contribute to synchrony are subtle and remain elusive. To investigate these mechanisms mean-…
Optimal percentage of inhibitory synapses in multi-task learning
Performing more tasks in parallel is a typical feature of complex brains. These are characterized by the coexistence of excitatory and inhibitory synapses, whose percentage in mammals is measured to have a typical value …
Multi-Task LearningThe role of gap junctions and clustered connectivity in emergent synchronisation patterns of inhibitory neuronal networks
Inhibitory interneurons, ubiquitous in the central nervous system, form networks connected through both chemical synapses and gap junctions. These networks are essential for regulating the activity of principal neurons, …
Robust entropy requires strong and balanced excitatory and inhibitory synapses
It is widely appreciated that well-balanced excitation and inhibition are necessary for proper function in neural networks. However, in principle, such balance could be achieved by many possible configurations of excitat…