2023
DOI: 10.3389/fpsyt.2023.1158404
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The time scales of irreversibility in spontaneous brain activity are altered in obsessive compulsive disorder

Abstract: We study how obsessive-compulsive disorder (OCD) affects the complexity and time-reversal symmetry-breaking (irreversibility) of the brain resting-state activity as measured by magnetoencephalography (MEG). Comparing MEG recordings from OCD patients and age/sex matched control subjects, we find that irreversibility is more concentrated at faster time scales and more uniformly distributed across different channels of the same hemisphere in OCD patients than in control subjects. Furthermore, the interhemispheric… Show more

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Cited by 5 publications
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“…Indeed, it has previously been suggested that the brain at rest can be interpreted as a fundamental default mode and that the brain activity during a specific task may be described in terms of generic properties of the background brain activity [4]. Moreover, it has been demonstrated that the activity of the brain at rest is affected by neurological and psychiatric disorders like autism, epilepsy, Parkinson's disease, schizophrenia, and obsessive-compulsive disorder [5][6][7][8]. In the same line, resting-state EEG measures have also been shown to be useful for the detection of cognitive decline in mild cognitive impairment and Alzheimer's disease [9] and for decoding and predicting cognitive performance [10].…”
Section: Introductionmentioning
confidence: 99%
“…Indeed, it has previously been suggested that the brain at rest can be interpreted as a fundamental default mode and that the brain activity during a specific task may be described in terms of generic properties of the background brain activity [4]. Moreover, it has been demonstrated that the activity of the brain at rest is affected by neurological and psychiatric disorders like autism, epilepsy, Parkinson's disease, schizophrenia, and obsessive-compulsive disorder [5][6][7][8]. In the same line, resting-state EEG measures have also been shown to be useful for the detection of cognitive decline in mild cognitive impairment and Alzheimer's disease [9] and for decoding and predicting cognitive performance [10].…”
Section: Introductionmentioning
confidence: 99%