Riečanský, I., Kašpárek, T., Řehulová, J., Katina, S. and Přikryl, R. (2010) Aberrant EEG responses to gamma-frequency visual stimulation in schizophrenia. Schizophrenia Research, 124(1-3), pp. 101-109. (doi: 10.1016/j.schres.2010.06.022)
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Abstract
Disturbance in the integration of visual information is one of the hallmarks of schizophrenia. In the spatial domain, visual integration is compromised, resulting in impaired perceptual grouping and contour integration. In the time domain, in contrast, visual integration is enhanced, as manifested by increased backward masking and lower ability of patients to detect successively presented visual stimuli as asynchronous. There ismuch evidence that integrative processes in the brain are supported by dynamic synchronization, or phase-locking, of neural firing. In particular, synchrony in the gamma band (N30 Hz) has been related to local visual information binding whereas synchrony in lower frequencies has been linked to global-scale integration. We recorded EEG signals evoked by steady-state gamma-frequency (40 Hz) photic stimulation in order to directly test the phase-locking of neural responses in schizophrenia. Compared with healthy control subjects, patients showed higher phase-locking of early evoked activity in the gamma band (36–44 Hz) over the posterior cortex, but lower phase-locking in theta (4–8 Hz), alpha (8–13 Hz) and beta (13–24 Hz) frequencies over the anterior cortex. Phase-locking of evoked responses separated schizophrenia and control subjects with accuracy of 86%. This result suggests that schizophrenia is associatedwith an enhanced early low-level integration in the visual cortex but a deficient high-level integration of visual information within the brain global workspace.
Item Type: | Articles |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Katina, Dr Stanislav |
Authors: | Riečanský, I., Kašpárek, T., Řehulová, J., Katina, S., and Přikryl, R. |
Subjects: | Q Science > QA Mathematics R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry |
College/School: | College of Science and Engineering > School of Mathematics and Statistics > Statistics |
Research Group: | Statistical Modelling |
Journal Name: | Schizophrenia Research |
ISSN: | 0920-9964 |
ISSN (Online): | 1573-2509 |
Published Online: | 09 August 2010 |
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