Effects of dynamic synapses on noise-delayed response latency of a single neuron
Noise-delayed decay (NDD) phenomenon emerges when the first-spike latency of a periodically forced stochastic neuron exhibits a maximum for a particular range of noise intensity. Here, we investigate the latency response dynamics of a single Hodgkin-Huxley neuron that is subject to both a suprathreshold periodic stimulus and a background activity arriving through dynamic synapses. We study the first spike latency response as a function of the presynaptic firing rate f. This constitutes a more realistic scenario than previous works, since f provides a suitable biophysically realistic parameter to control the level of activity in actual neural systems. We first report on the emergence of classical NDD behavior as a function of f for the limit of static synapses. Secondly, we show that when short-term depression and facilitation mechanisms are included at synapses, different NDD features can be found due to the their modulatory effect on synaptic current fluctuations. For example a new intriguing double NDD (DNDD) behavior occurs for different sets of relevant synaptic parameters. Moreover, depending on the balance between synaptic depression and synaptic facilitation, single NDD or DNDD can prevails, in such a way that synaptic facilitation favors the emergence of DNDD whereas synaptic depression favors the existence of single NDD. This is the first time it has been reported the existence of DNDD effect in response latency dynamics of a neuron.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Energy analysis of bursting Hindmarsh-Rose neurons with time-delayed coupling
Mathematical modeling is an important tool to study the role of delay in neural systems and to evaluate its effects on the signaling activity of coupled neurons. Models for delayed neurons are often used to represent the…
Synaptic Delays for Temporal Feature Detection in Dynamic Neuromorphic Processors
Spiking neural networks implemented in dynamic neuromorphic processors are well suited for spatiotemporal feature detection and learning, for example in ultra low-power embedded intelligence and deep edge applications. S…
Firing dynamics of an autaptic neuron
Autapses are synapses that connect a neuron to itself in the nervous system. Previously, both experimental and theoretical studies have demonstrated that autaptic connections in the nervous system have a significant phys…
Computational principles of biological memory
Memories are stored, retained, and recollected through complex, coupled processes operating on multiple timescales. To understand the computational principles behind these intricate networks of interactions we construct …
Finite-Horizon Input-Output Dynamics of Minibatch Perturbations in AdamW
A minibatch can influence training beyond the update at which it is observed because AdamW stores past gradient information in its optimizer states. We study this delayed effect through paired trajectories that differ on…