Normalized Power Variance: A new Field Orthogonal to Power in EEG Analysis.
Yasunori AokiHiroaki KazuiRoberto D Pascual-MarquiRicardo Bruña FernandezKenji YoshiyamaTamiki WadaHideki KanemotoYukiko SuzukiTakashi SuehiroYuto SatakeMaki YamakawaMasahiro HataLeonides CanuetRyouhei IshiiMasao IwaseManabu IkedaPublished in: Clinical EEG and neuroscience (2022)
To date, electroencephalogram (EEG) has been used in the diagnosis of epilepsy, dementia, and disturbance of consciousness via the inspection of EEG waves and identification of abnormal electrical discharges and slowing of basic waves. In addition, EEG power analysis combined with a source estimation method like exact-low-resolution-brain-electromagnetic-tomography (eLORETA), which calculates the power of cortical electrical activity from EEG data, has been widely used to investigate cortical electrical activity in neuropsychiatric diseases. However, the recently developed field of mathematics "information geometry" indicates that EEG has another dimension orthogonal to power dimension - that of normalized power variance (NPV). In addition, by introducing the idea of information geometry, a significantly faster convergent estimator of NPV was obtained. Research into this NPV coordinate has been limited thus far. In this study, we applied this NPV analysis of eLORETA to idiopathic normal pressure hydrocephalus (iNPH) patients prior to a cerebrospinal fluid (CSF) shunt operation, where traditional power analysis could not detect any difference associated with CSF shunt operation outcome. Our NPV analysis of eLORETA detected significantly higher NPV values at the high convexity area in the beta frequency band between 17 shunt responders and 19 non-responders. Considering our present and past research findings about NPV, we also discuss the advantage of this application of NPV representing a sensitive early warning signal of cortical impairment. Overall, our findings demonstrated that EEG has another dimension - that of NPV, which contains a lot of information about cortical electrical activity that can be useful in clinical practice.
Keyphrases
- resting state
- functional connectivity
- working memory
- cerebrospinal fluid
- clinical practice
- end stage renal disease
- chronic kidney disease
- pulmonary artery
- high frequency
- ejection fraction
- coronary artery
- healthcare
- single molecule
- pulmonary hypertension
- prognostic factors
- deep learning
- machine learning
- density functional theory
- electronic health record
- subarachnoid hemorrhage
- pulmonary arterial hypertension
- brain injury
- patient reported
- cerebral ischemia
- bioinformatics analysis