Electroencephalography and Schizophrenia / 신경정신의학

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.

Measurement and performance analysis of functional neural network / 生物医学工程学杂志

The measurement of network is one of the important researches in resolving neuronal population information processing mechanism using complex network theory. For the quantitative measurement problem of functional neural network, the relation between the measure indexes, i.e. the clustering coefficient, the global efficiency, the characteristic path length and the transitivity, and the network topology was analyzed. Then, the spike-based functional neural network was established and the simulation results showed that the measured network could represent the original neural connections among neurons. On the basis of the former work, the coding of functional neural network in nidopallium caudolaterale (NCL) about pigeon's motion behaviors was studied. We found that the NCL functional neural network effectively encoded the motion behaviors of the pigeon, and there were significant differences in four indexes among the left-turning, the forward and the right-turning. Overall, the establishment method of spike-based functional neural network is available and it is an effective tool to parse the brain information processing mechanism.