Neuronal graphs: a graph theory primer for microscopic, functional networks of neurons recorded by Calcium imaging

Nelson, C. J. and Bonner, S. (2021) Neuronal graphs: a graph theory primer for microscopic, functional networks of neurons recorded by Calcium imaging. Frontiers in Neural Circuits, 15, 662882. (doi: 10.3389/fncir.2021.662882) (PMID:34177469) (PMCID:PMC8222695)

Abstract

Connected networks are a fundamental structure of neurobiology. Understanding these networks will help us elucidate the neural mechanisms of computation. Mathematically speaking these networks are 'graphs' - structures containing objects that are connected. In neuroscience, the objects could be regions of the brain, e.g. fMRI data, or be individual neurons, e.g. calcium imaging with fluorescence microscopy. The formal study of graphs, graph theory, can provide neuroscientists with a large bank of algorithms for exploring networks. Graph theory has already been applied in a variety of ways to fMRI data but, more recently, has begun to be applied at the scales of neurons, e.g. from functional calcium imaging. In this primer we explain the basics of graph theory and relate them to features of microscopic functional networks of neurons from calcium imaging - neuronal graphs. We explore recent examples of graph theory applied to calcium imaging and we highlight some areas where researchers new to the field could go awry.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Nelson, Dr Chas
• Authors: Nelson, C. J., and Bonner, S.
• College/School: College of Science and Engineering > School of Physics and Astronomy
• Journal Name: Frontiers in Neural Circuits
• Publisher: Frontiers Media
• ISSN: 1662-5110
• ISSN (Online): 1662-5110
• Published Online: 10 June 2021
• Copyright Holders: Copyright © 2021 Nelson and Bonner
• First Published: Frontiers in Neural Circuits 15:662882
• Publisher Policy: Reproduced under a Creative Commons licence

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
172865		EPSRC DTP 16/17 and 17/18	Tania Galabova	Engineering and Physical Sciences Research Council (EPSRC)	EP/N509668/1	Research and Innovation Services