Abstract

All vertebrate brains contain a dense matrix of thin fibers that release serotonin (5-hydroxytryptamine), a neurotransmitter that modulates a wide range of neural, glial, and vascular processes. Perturbations in the density of this matrix have been associated with a number of mental disorders, including autism and depression, but its self-organization and plasticity remain poorly understood. We introduce a model based on reflected Fractional Brownian Motion (FBM), a rigorously defined stochastic process, and show that it recapitulates some key features of regional serotonergic fiber densities. Specifically, we use supercomputing simulations to model fibers as FBM-paths in two-dimensional brain-like domains and demonstrate that the resultant steady state distributions approximate the fiber distributions in physical brain sections immunostained for the serotonin transporter (a marker for serotonergic axons in the adult brain). We suggest that this framework can support predictive descriptions and manipulations of the serotonergic matrix and that it can be further extended to incorporate the detailed physical properties of the fibers and their environment.

Department(s)

Physics

Comments

This research was supported by the National Science Foundation (grants #1822517 and #1921515 to SJ and ND), the National Institute of Mental Health (grant #MH117488 to SJ and ND), the California NanoSystems Institute (Challenge grants to SJ and ND), the Research Corporation for Science Advancement (a Cottrell SEED Award to TV), and the German Research Foundation (DFG grant #ME 1535/7-1 to RM).

Keywords and Phrases

5-hydroxytryptamine; anomalous diffusion; brain; density; fibers; fractional Brownian motion; serotonin; stochastic process

International Standard Serial Number (ISSN)

1662-5188

Document Type

Article - Journal

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2020 The Authors, All rights reserved.

Creative Commons Licensing

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Publication Date

24 Jun 2020

Included in

Physics Commons

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