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随着年龄增长，大脑信号的整合性降低，分离性增强。

Brain signaling becomes less integrated and more segregated with age.

作者信息

Razban Rostam M, Antal Botond B, Dill Ken A, Mujica-Parodi Lilianne R

机构信息

Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, USA.

Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA.

出版信息

Netw Neurosci. 2024 Dec 10;8(4):1051-1064. doi: 10.1162/netn_a_00389. eCollection 2024.

DOI:10.1162/netn_a_00389
PMID:39735489
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11674493/
Abstract

The integration-segregation framework is a popular first step to understand brain dynamics because it simplifies brain dynamics into two states based on global versus local signaling patterns. However, there is no consensus for how to best define the two states. Here, we map integration and segregation to order and disorder states from the Ising model in physics to calculate state probabilities, and , from functional MRI data. We find that integration decreases and segregation increases with age across three databases. Changes are consistent with weakened connection strength among regions rather than topological connectivity based on structural and diffusion MRI data.

摘要

整合-分离框架是理解脑动力学的常用第一步，因为它基于全局与局部信号模式将脑动力学简化为两种状态。然而，对于如何最佳定义这两种状态尚无共识。在此，我们将整合和分离映射到物理学伊辛模型中的有序和无序状态，以从功能磁共振成像数据计算状态概率Pint和Pseg。我们发现，在三个数据库中，整合随年龄下降，分离随年龄增加。这些变化与基于结构和扩散磁共振成像数据的区域间连接强度减弱而非拓扑连通性一致。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da38/11674493/8d5b312d50c9/netn-8-4-1051-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da38/11674493/f76949a8957f/netn-8-4-1051-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da38/11674493/65297c2a7043/netn-8-4-1051-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da38/11674493/01c3b2081572/netn-8-4-1051-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da38/11674493/c026d92bc384/netn-8-4-1051-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da38/11674493/55f9c897082a/netn-8-4-1051-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da38/11674493/8d5b312d50c9/netn-8-4-1051-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da38/11674493/f76949a8957f/netn-8-4-1051-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da38/11674493/65297c2a7043/netn-8-4-1051-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da38/11674493/01c3b2081572/netn-8-4-1051-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da38/11674493/c026d92bc384/netn-8-4-1051-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da38/11674493/55f9c897082a/netn-8-4-1051-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da38/11674493/8d5b312d50c9/netn-8-4-1051-g006.jpg

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