@ARTICLE{10.3389/fnagi.2019.00248, AUTHOR={Zifman, Noa and Levy-Lamdan, Ofri and Suzin, Gil and Efrati, Shai and Tanne, David and Fogel, Hilla and Dolev, Iftach}, TITLE={Introducing a Novel Approach for Evaluation and Monitoring of Brain Health Across Life Span Using Direct Non-invasive Brain Network Electrophysiology}, JOURNAL={Frontiers in Aging Neuroscience}, VOLUME={11}, YEAR={2019}, URL={https://www.frontiersin.org/articles/10.3389/fnagi.2019.00248}, DOI={10.3389/fnagi.2019.00248}, ISSN={1663-4365}, ABSTRACT={ObjectiveEvaluation and monitoring of brain health throughout aging by direct electrophysiological imaging (DELPHI) which analyzes TMS (transcranial magnetic stimulation) evoked potentials.MethodsTranscranial magnetic stimulation evoked potentials formation, coherence and history dependency, measured using electroencephalogram (EEG), was extracted from 80 healthy subjects in different age groups, 25–85 years old, and 20 subjects diagnosed with mild dementia (MD), over 70 years old. Subjects brain health was evaluated using MRI scans, neurocognitive evaluation, and computerized testing and compared to DELPHI analysis of brain network functionality.ResultsA significant decrease in signal coherence is observed with age in connectivity maps, mostly in inter-hemispheric temporal, and parietal areas. MD patients display a pronounced decrease in global and inter-hemispheric frontal connectivity compared to healthy controls. Early and late signal slope ratio also display a significant, age dependent, change with pronounced early slope, phase shift, between normal healthy aging, and MD. History dependent analysis demonstrates a binary step function classification of healthy brain vs. abnormal aging subjects mostly for late slope. DELPHI measures demonstrate high reproducibility with reliability coefficients of around 0.9.ConclusionThese results indicate that features of evoked response, as charge transfer, slopes of response, and plasticity are altered during abnormal aging and that these fundamental properties of network functionality can be directly evaluated and monitored using DELPHI.} }