A common framework of signal processing in the induction of cerebellar LTD and cortical STDP

• Published in: Neural networks Vol. 43; pp. 114 - 124
• Main Authors: Honda, Minoru, Urakubo, Hidetoshi, Koumura, Takuya, Kuroda, Shinya
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.07.2013; Elsevier
• Subjects: Action Potentials - physiology; Applied sciences; Artificial intelligence; Biological and medical sciences; Cell Communication - physiology; Central nervous system; Central neurotransmission. Neuromudulation. Pathways and receptors; Cerebellar LTD; Cerebellum - physiology; Computer science; control theory; systems; Connectionism. Neural networks; Cortical STDP; Detection, estimation, filtering, equalization, prediction; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; Information, signal and communications theory; Learning - physiology; Mathematical models; Neural networks; Neuronal Plasticity - physiology; Nonlinearity; Pathways; Plasticity; Signal and communications theory; Signal processing; Signal, noise; Signaling pathways; Spiking; Synapses - physiology; System model; Telecommunications and information theory; Upstream; Vertebrates: nervous system and sense organs; Signaling pathways; Cerebellar LTD; Cortical STDP; System model; Time frequency domain method; Induction; Cell biology; Depression; Neural network; Long term; Modeling; Timed system; Digital filter; Synapse; Synaptic plasticity; Signal processing; Pairing
• ISSN: 0893-6080; 1879-2782
• DOI: 10.1016/j.neunet.2013.01.018

Cerebellar long-term depression (LTD) and cortical spike-timing-dependent synaptic plasticity (STDP) are two well-known and well-characterized types of synaptic plasticity. Induction of both types of synaptic plasticity depends on the spike timing, pairing frequency, and pairing numbers of two different sources of spiking. This implies that the induction of synaptic plasticity may share common frameworks in terms of signal processing regardless of the different signaling pathways involved in the two types of synaptic plasticity. Here we propose that both types share common frameworks of signal processing for spike-timing, pairing-frequency, and pairing-numbers detection. We developed system models of both types of synaptic plasticity and analyzed signal processing in the induction of synaptic plasticity. We found that both systems have upstream subsystems for spike-timing detection and downstream subsystems for pairing-frequency and pairing-numbers detection. The upstream systems used multiplication of signals from the feedback filters and nonlinear functions for spike-timing detection. The downstream subsystems used temporal filters with longer time constants for pairing-frequency detection and nonlinear switch-like functions for pairing-numbers detection, indicating that the downstream subsystems serve as a leaky integrate-and-fire system. Thus, our findings suggest that a common conceptual framework for the induction of synaptic plasticity exists despite the differences in molecular species and pathways.