Coherence a measure of the brain networks: past and present. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Bowyer, Susan
• Is Part Of: Neuropsychiatric electrophysiology. Volume 2:Issue 1(2016)
• Page Start: 1
• Page End: 12
• Publication Date: 2016-12
• Subjects: Neuronal oscillations -- Connectivity -- Networks -- Coherence -- EEG -- MEG; Neuropsychiatry -- Periodicals; Electrophysiology -- Periodicals; Brain -- Electric properties -- Periodicals; 616.807547
• DOI: 10.1186/s40810-015-0015-7
• Languages: English
• ISSNs: 2055-4788

Abstract

Abstract Brian connectivity describes the networks of functional and anatomical connections across the brain. The functional network communications across the brain networks dependent on neuronal oscillations. Detection of the synchronous activation of neurons can be used to determine the wellbeing or integrity of the functional connectivity in the human brain networks. Well-connected highly synchronous functional activity can be measured by Electroencephalography (EEG) or Magnetoencephalography (MEG) and then analyzed with several types of mathematical algorithms. Coherence is one mathematical method that can be used to determine if two or more sensors, or brain regions, have similar neuronal oscillatory activity with each other. Since the 1960's, coherence has generally been assessed on the similarity of the frequency content across EEG sensors. Recently coherence, after it has been imaged in the brain, has been used to assess how coherent or connected specific locations in the brain are networked together in several different neurological disorders. Statistical analysis can then be performed on the coherence results to verify evidence of normal or abnormal network activity in a patient. In this review we highlight how functional brain connectivity is assessed in Source space using coherence technique measured by MEG.