DocumentCode :
5111
Title :
EEG Markers for Characterizing Anomalous Activities of Cerebral Neurons in NAT (Neuronal Activity Topography) Method
Author :
Musha, Toshimitsu ; Matsuzaki, Hideaki ; Kobayashi, Yoshiyuki ; Okamoto, Yuji ; Tanaka, Mitsuru ; Asada, Takashi
Author_Institution :
Brain Functions Lab., Inc., Yokohama, Japan
Volume :
60
Issue :
8
fYear :
2013
fDate :
Aug. 2013
Firstpage :
2332
Lastpage :
2338
Abstract :
A pair of markers, sNAT and vNAT, is derived from the electroencephalogram (EEG) power spectra (PS) recorded for 5 min with 21 electrodes (4-20 Hz) arranged according to the 10-20 standard. These markers form a new diagnosis tool “NAT” aiming at characterizing various brain disorders. Each signal sequence is divided into segments of 0.64 s and its discrete PS consists of eleven frequency components from 4.68 (3 × 1.56) Hz through 20.34 (13 × 1.56) Hz. PS is normalized to its mean and the bias of PS components on each frequency component across the 21 signal channels is reset to zero. The marker sNAT consists often frequency components on 21 channels, characterizing neuronal hyperactivity or hypoactivity as compared with NLc (normal controls). The marker vNAT consists of ten ratios between adjacent PS components denoting the over- or undersynchrony of collective neuronal activities as compared with NLc. The likelihood of a test subject to a specified brain disease is defined in terms of the normalized distance to the template NAT state of the disease in the NAT space. Separation of MCI-AD patients (developing AD in 12-18 months) from NLc is made with a false alarm rate of 15%. Locations with neuronal hypoactivity and undersynchrony of AD patients agree with locations of rCBF reduction measured by SPECT. The 2D diagram composed of the binary likelihoods between ADc and NLc in the two representations of sNAT and vNAT enables tracing the NAT state of a test subject approaching the AD area, and the follow-up of the treatment effects.
Keywords :
biomedical electrodes; diseases; electroencephalography; medical disorders; medical signal processing; neurophysiology; single photon emission computed tomography; spectral analysis; 2D diagram; EEG markers; MCI-AD patient; NAT space; NLc; PS component bias; SPECT; adjacent PS component; anomalous activity characterization; binary likelihood; biomedical electrode; brain disease; cerebral neuron; collective neuronal activity oversynchrony; collective neuronal activity undersynchrony; diagnosis tool; discrete PS; electroencephalogram power spectra; frequency 4 Hz to 20 Hz; frequency component; marker sNAT; marker vNAT; neuronal activity topography method; neuronal hyperactivity; neuronal hypoactivity; normal control; rCBF reduction; signal channel; signal segmentation; signal sequence; template NAT state; time 0.64 s; time 5 min; Diseases; Electrodes; Electroencephalography; Modulation; Neurons; Sensitivity; Single photon emission computed tomography; Alzheimer's disease; electroencephalogram (EEG); likelihood; neuronal activity; power spectral; Aged; Aged, 80 and over; Algorithms; Brain; Brain Diseases; Brain Mapping; Diagnosis, Computer-Assisted; Electroencephalography; Humans; Nerve Net; Neurons; Reproducibility of Results; Sensitivity and Specificity;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2013.2255101
Filename :
6492242
Link To Document :
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