Suppr超能文献

使用EPIK对静息态网络进行基于皮质深度的人类功能磁共振成像。

Cortical depth-dependent human fMRI of resting-state networks using EPIK.

作者信息

Pais-Roldán Patricia, Yun Seong Dae, Palomero-Gallagher Nicola, Shah N Jon

机构信息

Institute of Neuroscience and Medicine 4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany.

Institute of Neuroscience and Medicine 1, Structural and Functional Organisation of the Brain, Forschungszentrum Jülich, Jülich, Germany.

出版信息

Front Neurosci. 2023 May 18;17:1151544. doi: 10.3389/fnins.2023.1151544. eCollection 2023.

Abstract

INTRODUCTION

Recent laminar-fMRI studies have substantially improved understanding of the cortical responses in multiple sub-systems; in contrast, the laminar component of spread over the whole brain has been less studied due to technical limitations. Animal research strongly suggests that the supragranular layers of the cortex play a critical role in maintaining communication within the default mode network (DMN); however, whether this is true in this and other human cortical networks remains unclear.

METHODS

Here, we used EPIK, which offers unprecedented coverage at sub-millimeter resolution, to investigate cortical broad resting-state dynamics with depth specificity in healthy volunteers.

RESULTS

Our results suggest that human DMN connectivity is primarily supported by intermediate and superficial layers of the cortex, and furthermore, the preferred cortical depth used for communication can vary from one network to another. In addition, the laminar connectivity profile of some networks showed a tendency to change upon engagement in a motor task. In line with these connectivity changes, we observed that the amplitude of the low-frequency-fluctuations (ALFF), as well as the regional homogeneity (ReHo), exhibited a different laminar slope when subjects were either performing a task or were in a resting state (less variation among laminae, i.e., lower slope, during task performance compared to rest).

DISCUSSION

The identification of varied laminar profiles concerning network connectivity, ALFF, and ReHo, observed across two brain states (task vs. rest) has major implications for the characterization of network-related diseases and suggests the potential diagnostic value of laminar fMRI in psychiatric disorders, e.g., to differentiate the cortical dynamics associated with disease stages linked, or not linked, to behavioral changes. The evaluation of laminar-fMRI across the brain encompasses computational challenges; nonetheless, it enables the investigation of a new dimension of the human neocortex, which may be key to understanding neurological disorders from a novel perspective.

摘要

引言

最近的层流功能磁共振成像(fMRI)研究极大地增进了我们对多个子系统中皮质反应的理解;相比之下,由于技术限制,全脑范围内扩散的层流成分研究较少。动物研究有力地表明,皮质的颗粒上层在维持默认模式网络(DMN)内的通信中起关键作用;然而,在人类的这个以及其他皮质网络中是否如此仍不清楚。

方法

在此,我们使用了EPIK,它能在亚毫米分辨率下提供前所未有的覆盖范围,以研究健康志愿者中具有深度特异性的皮质广泛静息态动力学。

结果

我们的结果表明,人类DMN的连通性主要由皮质的中层和表层支持,此外,用于通信的首选皮质深度可能因网络而异。此外,一些网络的层流连通性图谱在参与运动任务时显示出变化趋势。与这些连通性变化一致,我们观察到,当受试者执行任务或处于静息状态时,低频波动(ALFF)的幅度以及局部一致性(ReHo)在层流上呈现出不同的斜率(与静息相比,任务执行期间各层之间的变化较小,即斜率较低)。

讨论

在两种脑状态(任务与静息)下观察到的与网络连通性、ALFF和ReHo相关的不同层流图谱,对于网络相关疾病的特征描述具有重要意义,并提示层流fMRI在精神疾病中的潜在诊断价值,例如区分与行为变化相关或不相关的疾病阶段的皮质动力学。全脑范围内的层流fMRI评估存在计算挑战;尽管如此,它能够研究人类新皮质的一个新维度,这可能是从新角度理解神经疾病的关键。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcff/10232833/9994f0422867/fnins-17-1151544-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验