High-Density Exploration of Activity States in a Multi-Area Brain Model.

IF 2.7 4区 医学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Neuroinformatics Pub Date : 2024-01-01 Epub Date: 2023-11-20 DOI:10.1007/s12021-023-09647-1
David Aquilué-Llorens, Jennifer S Goldman, Alain Destexhe
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引用次数: 0

Abstract

To simulate whole brain dynamics with only a few equations, biophysical, mesoscopic models of local neuron populations can be connected using empirical tractography data. The development of mesoscopic mean-field models of neural populations, in particular, the Adaptive Exponential (AdEx mean-field model), has successfully summarized neuron-scale phenomena leading to the emergence of global brain dynamics associated with conscious (asynchronous and rapid dynamics) and unconscious (synchronized slow-waves, with Up-and-Down state dynamics) brain states, based on biophysical mechanisms operating at cellular scales (e.g. neuromodulatory regulation of spike-frequency adaptation during sleep-wake cycles or anesthetics). Using the Virtual Brain (TVB) environment to connect mean-field AdEx models, we have previously simulated the general properties of brain states, playing on spike-frequency adaptation, but have not yet performed detailed analyses of other parameters possibly also regulating transitions in brain-scale dynamics between different brain states. We performed a dense grid parameter exploration of the TVB-AdEx model, making use of High Performance Computing. We report a remarkable robustness of the effect of adaptation to induce synchronized slow-wave activity. Moreover, the occurrence of slow waves is often paralleled with a closer relation between functional and structural connectivity. We find that hyperpolarization can also generate unconscious-like synchronized Up and Down states, which may be a mechanism underlying the action of anesthetics. We conclude that the TVB-AdEx model reveals large-scale properties identified experimentally in sleep and anesthesia.

Abstract Image

多区域脑模型中活动状态的高密度探索。
为了仅用几个方程模拟全脑动力学,局部神经元种群的生物物理、介观模型可以使用经验神经束成像数据连接起来。神经群体的中观平均场模型的发展,特别是自适应指数(AdEx)平均场模型,成功地总结了神经元尺度现象,导致与意识(异步和快速动态)和无意识(同步慢波,上下状态动态)脑状态相关的全局脑动力学的出现。基于在细胞尺度上运作的生物物理机制(例如,睡眠-觉醒周期或麻醉剂期间对尖峰频率适应的神经调节调节)。使用虚拟脑(TVB)环境连接平均场AdEx模型,我们之前已经模拟了大脑状态的一般特性,发挥了尖峰频率适应作用,但尚未对可能也调节不同大脑状态之间脑尺度动态转换的其他参数进行详细分析。我们利用高性能计算对TVB-AdEx模型进行了密集的网格参数探索。我们报告了适应诱导同步慢波活动的显著鲁棒性。此外,慢波的发生往往与功能和结构连通性之间的密切关系并行。我们发现超极化也可以产生类似无意识的同步上下状态,这可能是麻醉药作用的一种机制。我们的结论是,TVB-AdEx模型揭示了在睡眠和麻醉中实验确定的大规模特性。
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来源期刊
Neuroinformatics
Neuroinformatics 医学-计算机:跨学科应用
CiteScore
6.00
自引率
6.70%
发文量
54
审稿时长
3 months
期刊介绍: Neuroinformatics publishes original articles and reviews with an emphasis on data structure and software tools related to analysis, modeling, integration, and sharing in all areas of neuroscience research. The editors particularly invite contributions on: (1) Theory and methodology, including discussions on ontologies, modeling approaches, database design, and meta-analyses; (2) Descriptions of developed databases and software tools, and of the methods for their distribution; (3) Relevant experimental results, such as reports accompanie by the release of massive data sets; (4) Computational simulations of models integrating and organizing complex data; and (5) Neuroengineering approaches, including hardware, robotics, and information theory studies.
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