paper-with-me

홈 › Papers

Robust Functional Magnetoencephalographic Brain Measures with 1.0 Millimeter Spatial Separation

2022-11-08 · Don Krieger, Paul Shepard, David O. Okonkwo

Neuroelectric currents were extracted from free-running magnetoencephalographic (MEG) rest and task recordings from 617 normative subjects (ages: 18-87). State-dependent neuroelectric differential activation (DA) with spatial resolution comparable to that of local field potentials was detected in the majority of this cohort. Rest-high (rest greater than task) or task-high DA was found in the majority of individual subjects in more than 13,000 1 mm^3 voxels per subject. On average, 6% of the DA voxels bordered a second voxel whose DA was opposite, i.e., one was rest-high and the other was task-high. 516 subjects showed more than 100 such opposite voxel pairs 1 mm apart; 226 subjects showed more than 1000. The number of bordering voxel pairs with the same DA was consistently higher for almost all subjects and averaged 20%, ruling out the possibility that opposite bordering voxels occur simply by chance. For 65 brain regions, more than 10% of the cohort showed significantly more same than opposite pairs. These findings taken together support the conclusion that neuroelectric DA is consistently distinguishable at single 1 mm^3 brain voxels with 1-mm spatial separation. When restricted to voxels with near-zero rest or task counts, significantly more rest-high than task-high voxels were found in 35 regions for at least 10 percent of the subjects. This inequality was not found when all DA-voxels were included. This supports the conclusion that the DA found in many rest-high voxels with near-zero task counts is due in part to task-dependent inhibition.

📄 PDF Abstract BibTeX arXiv:2211.03978

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Normative atlases of neuroelectric brain activity and connectivity from a large human cohort

2018-11-17

Magnetoencephalographic (MEG) recordings from a large normative cohort (n = 619) were processed to extract measures of regional neuroelectric activity. The overall objective of the effort was to use these measures to ide…

Localization of Brain Activity from EEG/MEG Using MV-PURE Framework

2018-09-11 · Tomasz Piotrowski, Jan Nikadon, Alexander Moiseev

We consider the problem of localization of sources of brain electrical activity from electroencephalographic (EEG) and magnetoencephalographic (MEG) measurements using spatial filtering techniques. We propose novel reduc…

EEGElectroencephalogram (EEG)

Weight-conserving characterization of complex functional brain networks

2011-03-26 · Mikail Rubinov, Olaf Sporns

Complex functional brain networks are large networks of brain regions and functional brain connections. Statistical characterizations of these networks aim to quantify global and local properties of brain activity with a…

Loss of brain inter-frequency hubs in Alzheimer's disease

2017-03-10

Alzheimer's disease (AD) causes alterations of brain network structure and function. The latter consists of connectivity changes between oscillatory processes at different frequency channels. We proposed a multi-layer ne…

Diagnostic

MV-PURE Spatial Filters with Application to EEG/MEG Source Reconstruction

2017-12-08 · Tomasz Piotrowski, Jan Nikadon, David Gutierrez

In this paper we propose spatial filters for a linear regression model which are based on the minimum-variance pseudo-unbiased reduced-rank estimation (MV-PURE) framework. As a sample application, we consider the problem…

EEG