Published December 1, 2019 | Version v1
Journal article

Objective and efficient inference for couplings in neuronal network

  • 1. Laboratory for Neural Computation and Adaptation, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351-0198 (Japan)
  • 2. Department of Mathematical and Computer Science, Tokyo Institute of Technology, Tokyo 152-8550 (Japan)

Description

Inferring directional couplings from the spike data of networks is desired in various scientific fields such as neuroscience. Here, we apply a recently proposed objective procedure to the spike data obtained from the Hodgkin–Huxley type models and in vitro neuronal networks cultured in a circular structure. As a result, we succeed in reconstructing synaptic connections accurately from the evoked activity as well as the spontaneous one. To obtain the results, we invent an analytic formula approximately implementing a method of screening relevant couplings. This significantly reduces the computational cost of the screening method employed in the proposed objective procedure, making it possible to treat large-size systems as in this study. (ml 2019)

Availability note (English)

Available from http://dx.doi.org/10.1088/1742-5468/ab3219

Additional details

Identifiers

Publishing Information

Journal Title
Journal of Statistical Mechanics
Journal Volume
2019
Journal Issue
12
Journal Page Range
[14 p.]
ISSN
1742-5468

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
52042364
Subject category
S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
Descriptors DEI
APPROXIMATIONS; NEURAL NETWORKS; SCREENING
Descriptors DEC
CALCULATION METHODS