Connectivity analyses of the brain are performed to map out the communication networks needed for the brain to function. The synchronized activity within this neuronal network can be detected by MEG and EEG then imaged using network connectivity analysis. The human brain is a vast network of connected pathways that communicate through synchronized electric brain activity along fiber tracts. In this review we highlight how functional brain connectivity is assessed in Source space using coherence technique measured by MEG. Statistical analysis can then be performed on the coherence results to verify evidence of normal or abnormal network activity in a patient. 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. Since the 1960’s, coherence has generally been assessed on the similarity of the frequency content across EEG sensors. 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. Well-connected highly synchronous functional activity can be measured by Electroencephalography (EEG) or Magnetoencephalography (MEG) and then analyzed with several types of mathematical algorithms. 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. The functional network communications across the brain networks dependent on neuronal oscillations. Brian connectivity describes the networks of functional and anatomical connections across the brain.

Cyclical coherence meaning