조현병과 뇌파
Electroencephalography and Schizophrenia
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참고문헌
초록
Electroencephalography (EEG) and event-related potentials (ERPs) are useful measures of information processing that are believed to reflect the cognitive processing of the brain. Recently, these electrophysiological markers have been studied repeatedly to examine patients with schizophrenia. Among the ERPs components, P50, P300, mismatch negativity, loudness dependence of auditory evoked potentials, and 40 Hz auditory steady state response are meaningful neurophysiological markers of schizophrenia. The employment of novel ERP paradigms designed to carefully characterize the early spectrum of perceptual and cognitive information processing allows investigators to identify the neurophysiological basis of cognitive dysfunction in schizophrenia and examine the associated clinical and functional impairments. Lately, functional neural networks using resting state EEG have been studied extensively in patients with schizophrenia. In this article, qEEG, several ERP components, and functional neural networks that were considered useful neurophysiological markers of schizophrenia are reviewed and their clinical implications are discussed.
Abstract
Electroencephalography (EEG) and event-related potentials (ERPs) are useful measures of information processing that are believed to reflect the cognitive processing of the brain. Recently, these electrophysiological markers have been studied repeatedly to examine patients with schizophrenia. Among the ERPs components, P50, P300, mismatch negativity, loudness dependence of auditory evoked potentials, and 40 Hz auditory steady state response are meaningful neurophysiological markers of schizophrenia. The employment of novel ERP paradigms designed to carefully characterize the early spectrum of perceptual and cognitive information processing allows investigators to identify the neurophysiological basis of cognitive dysfunction in schizophrenia and examine the associated clinical and functional impairments. Lately, functional neural networks using resting state EEG have been studied extensively in patients with schizophrenia. In this article, qEEG, several ERP components, and functional neural networks that were considered useful neurophysiological markers of schizophrenia are reviewed and their clinical implications are discussed.
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