| Autor: |
Daisuke Koshiyama, Makoto Miyakoshi, Kumiko Tanaka-Koshiyama, Yash B. Joshi, Juan L. Molina, Joyce Sprock, David L. Braff, Gregory A. Light |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
Frontiers in Psychiatry, Vol 11 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
1664-0640 |
| DOI: |
10.3389/fpsyt.2020.608154 |
| Popis: |
Background: Patients with schizophrenia show abnormal spontaneous oscillatory activity in scalp-level electroencephalographic (EEG) responses across multiple frequency bands. While oscillations play an essential role in the transmission of information across neural networks, few studies have assessed the frequency-specific dynamics across cortical source networks at rest. Identification of the neural sources and their dynamic interactions may improve our understanding of core pathophysiologic abnormalities associated with the neuropsychiatric disorders.Methods: A novel multivector autoregressive modeling approach for assessing effective connectivity among cortical sources was developed and applied to resting-state EEG recordings obtained from n = 139 schizophrenia patients and n = 126 healthy comparison subjects.Results: Two primary abnormalities in resting-state networks were detected in schizophrenia patients. The first network involved the middle frontal and fusiform gyri and a region near the calcarine sulcus. The second network involved the cingulate gyrus and the Rolandic operculum (a region that includes the auditory cortex).Conclusions: Schizophrenia patients show widespread patterns of hyper-connectivity across a distributed network of the frontal, temporal, and occipital brain regions. Results highlight a novel approach for characterizing alterations in connectivity in the neuropsychiatric patient populations. Further mechanistic characterization of network functioning is needed to clarify the pathophysiology of neuropsychiatric and neurological diseases. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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