2024/03/16 by Ryota Kobayashi, Kobayashi, Ryota, Shigeru Shinomoto +1
Neuroscience · Physics and Astronomy · #FOS: Biological sciences #Neural dynamics and brain function #Neurons and Cognition (q-bio.NC) #Photoreceptor and optogenetics research #Quantitative Methods (q-bio.QM) #Spectroscopy and Quantum Chemical Studies
paper · pdf · doi:10.48550/arxiv.2403.10993
openalex publication_date 2024/03/16 · openalex created_date 2024/03/21 · openalex updated_date 2026/07/28
This article presents a mini-review about the progress in inferring monosynaptic connections from spike trains of multiple neurons over the past twenty years. First, we explain a variety of meanings of ``neuronal connectivity'' in different research areas of neuroscience, such as structural connectivity, monosynaptic connectivity, and functional connectivity. Among these, we focus on the methods used to infer the monosynaptic connectivity from spike data. We then summarize the inference methods based on two main approaches, i.e., correlation-based and model-based approaches. Finally, we describe available source codes for connectivity inference and future challenges. Although inference will never be perfect, the accuracy of identifying the monosynaptic connections has improved dramatically in recent years due to continuous efforts.