Neural network classification of EEG during camouflaged object identification

• Published in: International journal of medical informatics (Shannon, Ireland) Vol. 44; no. 3; pp. 169 - 175
• Main Author: Rzempoluck, Edward J.
• Format: Journal Article
• Language: English
• Published: Ireland Elsevier Ireland Ltd 01.05.1997
• Subjects: Adult; Attention - physiology; Blinking - physiology; Camouflage; Cerebral Cortex - physiology; Discrimination Learning - physiology; Electroencephalography - classification; Electroencephalography - instrumentation; Female; Humans; Male; Middle Aged; Neural networks; Neural Networks (Computer); Pattern Recognition, Visual - physiology; Perceptual Masking - physiology; Reaction Time - physiology; Regression Analysis; Scalp potentials; Signal Processing, Computer-Assisted - instrumentation; Visual perception; Visual Perception - physiology; Scalp potentials; Neural networks; Camouflage; Visual perception
• ISSN: 1386-5056; 1872-8243
• DOI: 10.1016/S1386-5056(97)85798-X

A generalized regression neural network (GRNN) was trained to discriminate between EEGs recorded while subjects identified a camouflaged target object (picture condition) from EEGs recorded during a visually matched control task (control condition). In the picture condition subjects, three female and two male right handers, ages 23-47, viewed images depicting camouflaged target objects and signaled identification by blinking. In the control condition subjects viewed a neutral screen and blinked at will. EEGs made immediately preceding and following the blink were band-pass filtered at 2–8 Hz. The network achieved a marked increase in discriminability in the final 250 ms preceding target identification, with chance level of discrimination before and after. Network performance using scrambled data was also at chance level.