陶氏病
神经科学
集合(抽象数据类型)
动力学(音乐)
神经活动
平衡
认知科学
计算机科学
生物
心理学
医学
细胞生物学
神经退行性变
疾病
内科学
程序设计语言
教育学
作者
James N. McGregor,Clayton A. Farris,Sahara Ensley,Aidan Schneider,Chao Wang,Yuqi Liu,Jianhong Tu,Halla Elmore,Keenan D. Ronayne,Ralf Weßel,Eva L. Dyer,Kiran Bhaskaran‐Nair,David M. Holtzman,Keith B. Hengen
标识
DOI:10.1101/2023.09.01.555947
摘要
ABSTRACT The homeostatic regulation of neuronal activity is essential for robust computation; key set-points, such as firing rate, are actively stabilized to compensate for perturbations. From this perspective, the disruption of brain function central to neurodegenerative disease should reflect impairments of computationally essential set-points. Despite connecting neurodegeneration to functional outcomes, the impact of disease on set-points in neuronal activity is unknown. Here we present a comprehensive, theory-driven investigation of the effects of tau-mediated neurodegeneration on homeostatic set-points in neuronal activity. In a mouse model of tauopathy, we examine 27,000 hours of hippocampal recordings during free behavior throughout disease progression. Contrary to our initial hypothesis that tauopathy would impact set-points in spike rate and variance, we found that cell-level set-points are resilient to even the latest stages of disease. Instead, we find that tauopathy disrupts neuronal activity at the network-level, which we quantify using both pairwise measures of neuron interactions as well as measurement of the network’s nearness to criticality , an ideal computational regime that is known to be a homeostatic set-point. We find that shifts in network criticality 1) track with symptoms, 2) predict underlying anatomical and molecular pathology, 3) occur in a sleep/wake dependent manner, and 4) can be used to reliably classify an animal’s genotype. Our data suggest that the critical set-point is intact, but that homeostatic machinery is progressively incapable of stabilizing hippocampal networks, particularly during waking. This work illustrates how neurodegenerative processes can impact the computational capacity of neurobiological systems, and suggest an important connection between molecular pathology, circuit function, and animal behavior.
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