GLORIA

GEOMAR Library Ocean Research Information Access

Your search history is empty.

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
  • Proceedings of the National Academy of Sciences  (1)
  • Sejnowski, Terrence J.  (1)
  • Turetsky, Bruce I.
Material
Publisher
  • Proceedings of the National Academy of Sciences  (1)
Language
Years
Subjects(RVK)
  • 1
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 116, No. 9 ( 2019-02-26), p. 3847-3852
    Abstract: Natural systems, including the brain, often seem chaotic, since they are typically driven by complex nonlinear dynamical processes. Disruption in the fluid coordination of multiple brain regions contributes to impairments in information processing and the constellation of symptoms observed in neuropsychiatric disorders. Schizophrenia (SZ), one of the most debilitating mental illnesses, is thought to arise, in part, from such a network dysfunction, leading to impaired auditory information processing as well as cognitive and psychosocial deficits. Current approaches to neurophysiologic biomarker analyses predominantly rely on linear methods and may, therefore, fail to capture the wealth of information contained in whole EEG signals, including nonlinear dynamics. In this study, delay differential analysis (DDA), a nonlinear method based on embedding theory from theoretical physics, was applied to EEG recordings from 877 SZ patients and 753 nonpsychiatric comparison subjects (NCSs) who underwent mismatch negativity (MMN) testing via their participation in the Consortium on the Genetics of Schizophrenia (COGS-2) study. DDA revealed significant nonlinear dynamical architecture related to auditory information processing in both groups. Importantly, significant DDA changes preceded those observed with traditional linear methods. Marked abnormalities in both linear and nonlinear features were detected in SZ patients. These results illustrate the benefits of nonlinear analysis of brain signals and underscore the need for future studies to investigate the relationship between DDA features and pathophysiology of information processing.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    RVK:
    RVK:
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2019
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...