ArticleProceedings of the National Academy of Sciences of the United States of America2019
Nonlinear dynamics underlying sensory processing dysfunction in schizophrenia.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- An open-access EEG dataset for speech decoding: Exploring the role of articulation and coarticulation.Scientific data · 2025Article
- Intraindividual Variability of Event-Related Potentials in Psychosis: A Registered Report.Biological psychiatry global open science · 2025Article
- The alterations of repetitive transcranial magnetic stimulation on the energy landscape of resting-state networks differ across the human cortex.Human brain mapping · 2024Article
- Transcranial Magnetic Stimulation Facilitates Neural Speech Decoding.Brain sciences · 2024Article
- Decoding imagined speech with delay differential analysis.Frontiers in human neuroscience · 2024Article
- Network-motif delay differential analysis of brain activity during seizures.Chaos (Woodbury, N.Y.) · 2023Article
- Latent brain state dynamics and cognitive flexibility in older adults.Progress in neurobiology · 2022Article
- Dynamical ergodicity DDA reveals causal structure in time series.Chaos (Woodbury, N.Y.) · 2021Article
- Sources of the frontocentral mismatch negativity and P3a responses in schizophrenia patients and healthy comparison subjects.International journal of psychophysiology : official journal of the International Organization of Psychophysiology · 2021Article
- Precision multidimensional neural population code recovered from single intracellular recordings.Scientific reports · 2020Article
- Impaired Sensory Processing During Low-Oxygen Exposure: A Noninvasive Approach to Detecting Changes in Cognitive States.Frontiers in psychiatry · 2020Article
- Cortical chimera states predict epileptic seizures.Chaos (Woodbury, N.Y.) · 2019Article
- Decomposing the constituent oscillatory dynamics underlying mismatch negativity generation in schizophrenia: Distinct relationships to clinical and cognitive functioning.International journal of psychophysiology : official journal of the International Organization of Psychophysiology · 2019Article
- Exploration of time-frequency reassignment and homologous inter-hemispheric asymmetry analysis of MCI-AD brain activity.BMC neuroscience · 2019Article
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11 authors.
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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.
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