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Neuroimage Clin. 2019 Feb 2;22:101706. doi: 10.1016/j.nicl.2019.101706. [Epub ahead of print]

Neurophysiological markers of network dysfunction in neurodegenerative diseases.

Author information

1
Academic Unit of Neurology, Trinity Biomedical Sciences Institute, 152-160 Pearse St., Trinity College Dublin, The University of Dublin, Ireland. Electronic address: mcmackr@tcd.ie.
2
Academic Unit of Neurology, Trinity Biomedical Sciences Institute, 152-160 Pearse St., Trinity College Dublin, The University of Dublin, Ireland; Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, 152-160 Pearse St., Trinity College Dublin, The University of Dublin, Ireland. Electronic address: bedep@tcd.ie.
3
Academic Unit of Neurology, Trinity Biomedical Sciences Institute, 152-160 Pearse St., Trinity College Dublin, The University of Dublin, Ireland; Beaumont Hospital Dublin, Department of Psychology, Beaumont Road, Beaumont, Dublin 9, Ireland. Electronic address: niallpender@beaumont.ie.
4
Academic Unit of Neurology, Trinity Biomedical Sciences Institute, 152-160 Pearse St., Trinity College Dublin, The University of Dublin, Ireland; Beaumont Hospital Dublin, Department of Neurology, Beaumont Road, Beaumont, Dublin 9, Ireland. Electronic address: hardimao@tcd.ie.
5
Academic Unit of Neurology, Trinity Biomedical Sciences Institute, 152-160 Pearse St., Trinity College Dublin, The University of Dublin, Ireland. Electronic address: Bahman.Nasseroleslami@tcd.ie.

Abstract

There is strong clinical, imaging and pathological evidence that neurodegeneration is associated with altered brain connectivity. While functional imaging (fMRI) can detect resting and activated states of metabolic activity, its use is limited by poor temporal resolution, cost and confounding vascular parameters. By contrast, electrophysiological (e.g. EEG/MEG) recordings provide direct measures of neural activity with excellent temporal resolution, and source localization methodologies can address problems of spatial resolution, permitting measurement of functional activity of brain networks with a spatial resolution similar to that of fMRI. This opens an exciting therapeutic approach focussed on pharmacological and physiological modulation of brain network activity. This review describes current neurophysiological approaches towards evaluating cortical network dysfunction in common neurodegenerative disorders. It explores how modern neurophysiologic tools can provide markers for diagnosis, prognosis, subcategorization and clinical trial outcome measures, and how modulation of brain networks can contribute to new therapeutic approaches.

KEYWORDS:

Biomarker; EEG; MEG; Network; Neurodegeneration; TMS

PMID:
30738372
DOI:
10.1016/j.nicl.2019.101706
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