Modeling Normal and Imbalanced Neural Avalanches: A Computational Approach to Understanding Criticality in the Brain and Its Potential Role in Schizophrenia

Author:

Mongomery Richard MurdochORCID

Abstract

AbstractNeural avalanches, characterized by bursts of activity followed by periods of quiescence, have been observed in the brain and are thought to reflect the critical dynamics necessary for optimal information processing. Deviations from normal avalanche behavior have been hypothesized to underlie various neurological disorders, particularly schizophrenia. Schizophrenia is a complex psychiatric disorder associated with altered perception, cognition, and behavior, and recent theories suggest that disruptions in the brain’s critical dynamics may contribute to its pathophysiology. In this study, we present a computational model to investigate the properties of normal and imbalanced neural avalanches, with a focus on understanding the potential role of criticality in schizophrenia. We generate avalanche sizes using the Pareto distribution with a power law exponent of -3/2, which is consistent with experimental observations. The model incorporates increasing avalanche sizes over time to simulate the growth of neural activity. We introduce imbalance by adding lateness or earliness to the avalanche sizes, mimicking the potential disruptions in critical dynamics that may occur in schizophrenia. The mean and standard deviation of avalanche sizes are calculated to characterize the normal and imbalanced behavior. The results are visualized using line plots, with shaded areas representing the standard deviation range. Our model provides a framework for understanding the differences between normal and imbalanced neural avalanches, offering insights into the potential mechanisms underlying the altered critical dynamics in schizophrenia. By exploring the relationship between neural avalanches and schizophrenia, this study contributes to the ongoing efforts to elucidate the neurobiological basis of this disorder and may inform future research on potential diagnostic markers and therapeutic interventions targeting the brain’s critical dynamics.

Publisher

Cold Spring Harbor Laboratory

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3