Age of onset modulates resting‐state brain network dynamics in Friedreich Ataxia

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

This magnetoencephalography (MEG) study addresses (i) how Friedreich ataxia (FRDA) affects the sub‐second dynamics of resting‐state brain networks, (ii) the main determinants of their dynamic alterations, and (iii) how these alterations are linked with FRDA‐related changes in resting‐state functional brain connectivity (rsFC) over long timescales. For that purpose, 5 min of resting‐state MEG activity were recorded in 16 FRDA patients (mean age: 27 years, range: 12–51 years; 10 females) and matched healthy subjects. Transient brain network dynamics was assessed using hidden Markov modeling (HMM). Post hoc median‐split, nonparametric permutations and Spearman rank correlations were used for statistics. In FRDA patients, a positive correlation was found between the age of symptoms onset (ASO) and the temporal dynamics of two HMM states involving the posterior default mode network (DMN) and the temporo‐parietal junctions (TPJ). FRDA patients with an ASO <11 years presented altered temporal dynamics of those two HMM states compared with FRDA patients with an ASO > 11 years or healthy subjects. The temporal dynamics of the DMN state also correlated with minute‐long DMN rsFC. This study demonstrates that ASO is the main determinant of alterations in the sub‐second dynamics of posterior associative neocortices in FRDA patients and substantiates a direct link between sub‐second network activity and functional brain integration over long timescales.

Abstract

Related collections

Most cited references 52

Record: found
Abstract: found
Article: not found

The brain's default network: anatomy, function, and relevance to disease.

Randy L. Buckner, Jessica Andrews-Hanna, Daniel Schacter (2008)

Thirty years of brain imaging research has converged to define the brain's default network-a novel and only recently appreciated brain system that participates in internal modes of cognition. Here we synthesize past observations to provide strong evidence that the default network is a specific, anatomically defined brain system preferentially active when individuals are not focused on the external environment. Analysis of connectional anatomy in the monkey supports the presence of an interconnected brain system. Providing insight into function, the default network is active when individuals are engaged in internally focused tasks including autobiographical memory retrieval, envisioning the future, and conceiving the perspectives of others. Probing the functional anatomy of the network in detail reveals that it is best understood as multiple interacting subsystems. The medial temporal lobe subsystem provides information from prior experiences in the form of memories and associations that are the building blocks of mental simulation. The medial prefrontal subsystem facilitates the flexible use of this information during the construction of self-relevant mental simulations. These two subsystems converge on important nodes of integration including the posterior cingulate cortex. The implications of these functional and anatomical observations are discussed in relation to possible adaptive roles of the default network for using past experiences to plan for the future, navigate social interactions, and maximize the utility of moments when we are not otherwise engaged by the external world. We conclude by discussing the relevance of the default network for understanding mental disorders including autism, schizophrenia, and Alzheimer's disease.

0 comments Cited 1218 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Functional connectivity in the motor cortex of resting human brain using echo-planar MRI.

B. Biswal, F Z Yetkin, V M Haughton … (1995)

An MRI time course of 512 echo-planar images (EPI) in resting human brain obtained every 250 ms reveals fluctuations in signal intensity in each pixel that have a physiologic origin. Regions of the sensorimotor cortex that were activated secondary to hand movement were identified using functional MRI methodology (FMRI). Time courses of low frequency (< 0.1 Hz) fluctuations in resting brain were observed to have a high degree of temporal correlation (P < 10(-3)) within these regions and also with time courses in several other regions that can be associated with motor function. It is concluded that correlation of low frequency fluctuations, which may arise from fluctuations in blood oxygenation or flow, is a manifestation of functional connectivity of the brain.

0 comments Cited 1135 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Improved Localizadon of Cortical Activity by Combining EEG and MEG with MRI Cortical Surface Reconstruction: A Linear Approach.

A M Dale, M I Sereno (1993)

Abstract We describe a comprehensive linear approach to the problem of imaging brain activity with high temporal as well as spatial resolution based on combining EEG and MEG data with anatomical constraints derived from MRI images. The "inverse problem" of estimating the distribution of dipole strengths over the cortical surface is highly underdetermined, even given closely spaced EEG and MEG recordings. We have obtained much better solutions to this problem by explicitly incorporating both local cortical orientation as well as spatial covariance of sources and sensors into our formulation. An explicit polygonal model of the cortical manifold is first constructed as follows: (1) slice data in three orthogonal planes of section (needle-shaped voxels) are combined with a linear deblurring technique to make a single high-resolution 3-D image (cubic voxels), (2) the image is recursively flood-filled to determine the topology of the gray-white matter border, and (3) the resulting continuous surface is refined by relaxing it against the original 3-D gray-scale image using a deformable template method, which is also used to computationally flatten the cortex for easier viewing. The explicit solution to an error minimization formulation of an optimal inverse linear operator (for a particular cortical manifold, sensor placement, noise and prior source covariance) gives rise to a compact expression that is practically computable for hundreds of sensors and thousands of sources. The inverse solution can then be weighted for a particular (averaged) event using the sensor covariance for that event. Model studies suggest that we may be able to localize multiple cortical sources with spatial resolution as good as PET with this technique, while retaining a much finer grained picture of activity over time.

0 comments Cited 420 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Gilles Naeije:

ORCID: https://orcid.org/0000-0003-1580-1970

gilles.naeije@erasme.ulb.ac.be

Journal

Journal ID (nlm-ta): Hum Brain Mapp

Journal ID (iso-abbrev): Hum Brain Mapp

Journal ID (doi): 10.1002/(ISSN)1097-0193

Journal ID (publisher-id): HBM

Title: Human Brain Mapping

Publisher: John Wiley & Sons, Inc. (Hoboken, USA )

ISSN (Print): 1065-9471

ISSN (Electronic): 1097-0193

Publication date (Electronic): 15 September 2021

Publication date Collection: November 2021

Volume: 42

Issue: 16 ( doiID: 10.1002/hbm.v42.16 )

Pages: 5334-5344

Affiliations

[ ¹ ] Laboratoire de Cartographie fonctionnelle du Cerveau (LCFC) UNI—ULB Neuroscience Institute, Université libre de Bruxelles (ULB) Brussels Belgium

[ ² ] Department of Neurology, CUB Hôpital Erasme Université libre de Bruxelles (ULB) Brussels Belgium

[ ³ ] Department of Functional Neuroimaging CUB Hôpital Erasme, Université libre de Bruxelles (ULB) Brussels Belgium

[ ⁴ ] Department of Neurology and Neurosurgery McGill University Montreal Canada

Author notes

[*] [* ] Correspondence

Gilles Naeije, Laboratoire de Cartographie fonctionnelle du Cerveau (LCFC), UNI—ULB Neuroscience Institute, Université libre de Bruxelles (ULB), Brussels, Belgium.

Email: gilles.naeije@ 123456erasme.ulb.ac.be

Author information

Gilles Naeije https://orcid.org/0000-0003-1580-1970

Article

Publisher ID: HBM25621

DOI: 10.1002/hbm.25621

PMC ID: 8519851

PubMed ID: 34523778

SO-VID: c7576b69-7e4b-44f4-948e-e4d9e2ce35a4

License:

This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

History

Date revision received : 19 July 2021

Date received : 02 June 2021

Date accepted : 20 July 2021

Page count

Figures: 7, Tables: 2, Pages: 11, Words: 8766

Funding

Funded by: Fonds De La Recherche Scientifique ‐ FNRS , doi 10.13039/501100002661;

Award ID: J.0095.16.F

Funded by: Fonds Erasme , doi 10.13039/100015400;

Award ID: Voies du savoir

Funded by: Friedreich's Ataxia Research Alliance , doi 10.13039/100002108;

Custom metadata

source-schema-version-number 2.0

cover-date November 2021

details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.8 mode:remove_FC converted:15.10.2021

ScienceOpen disciplines: Neurology

Keywords: biomarker,friedreich ataxia,hidden markow modeling,meg,resting state functional connectivity,resting‐state brain network dynamics

Data availability:

ScienceOpen disciplines: Neurology

Keywords: biomarker, friedreich ataxia, hidden markow modeling, meg, resting state functional connectivity, resting‐state brain network dynamics

Age of onset modulates resting‐state brain network dynamics in Friedreich Ataxia

Read this article at

Abstract

Abstract

Related collections

Nanoparticles to cross the blood-brain barrier (BBB)

Most cited references 52

The brain's default network: anatomy, function, and relevance to disease.

Functional connectivity in the motor cortex of resting human brain using echo-planar MRI.

Improved Localizadon of Cortical Activity by Combining EEG and MEG with MRI Cortical Surface Reconstruction: A Linear Approach.

Author and article information

Contributors

Journal

Affiliations

Author notes

Author information

Article

History

Page count

Funding

Categories

Custom metadata

Comments

Comment on this article

Similar content 114

Cited by 6

Most referenced authors 699