A study on sensory processing dysfunction in schizophrenia

Schizophrenia (SZ) is marked by deficits in auditory information processing and abnormal EEG dynamics that are not fully captured by conventional linear analysis. To address this gap, we develop a nonlinear fractional-order delay differential model inspired by case–control EEG data from the Consortium on the Genetics of Schizophrenia (COGS-2). We first establish conditions for asymptotic stability of the system and then perform Hopf bifurcation analysis to determine critical delays at which stability is lost and oscillatory activity emerges. These theoretical results are validated through numerical simulations using a predictor–corrector scheme, which illustrate transitions between stable and oscillatory regimes. The findings provide a mechanistic link between delayed feedback, memory effects, and the abnormal rhythms observed in SZ EEG. Overall, this study demonstrates that fractional-order delay models are well suited for capturing the complex temporal structure of neural dynamics in SZ and for explaining sensory processing deficits.

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Publication Details

Journal
Discover Applied Sciences
Published
2025-11-21
DOI
https://doi.org/10.1007/s42452-025-07915-0
Primary Topic
Neural dynamics and brain function
Type
article
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article

A study on sensory processing dysfunction in schizophrenia

S. Panigrahi, Sunita Chand
Discover Applied Sciences
Neural dynamics and brain function
article

A study on sensory processing dysfunction in schizophrenia

S. Panigrahi, Sunita Chand
article en

Abstract

Schizophrenia (SZ) is marked by deficits in auditory information processing and abnormal EEG dynamics that are not fully captured by conventional linear analysis. To address this gap, we develop a nonlinear fractional-order delay differential model inspired by case–control EEG data from the Consortium on the Genetics of Schizophrenia (COGS-2). We first establish conditions for asymptotic stability of the system and then perform Hopf bifurcation analysis to determine critical delays at which stability is lost and oscillatory activity emerges. These theoretical results are validated through numerical simulations using a predictor–corrector scheme, which illustrate transitions between stable and oscillatory regimes. The findings provide a mechanistic link between delayed feedback, memory effects, and the abnormal rhythms observed in SZ EEG. Overall, this study demonstrates that fractional-order delay models are well suited for capturing the complex temporal structure of neural dynamics in SZ and for explaining sensory processing deficits.

Discover Applied SciencesVol. 7(12)
Siksha O Anusandhan University (IN)
Openalex Percentile: Top 64%
Neural dynamics and brain function
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