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Research PaperResearchia:202606.05028

Early psychosis shows deviations in scaling behaviour within a critical regime

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Abstract

Accumulating evidence suggests that large-scale brain activity exhibits scale-invariant dynamics consistent with operation in a near-critical regime. Such dynamics have been associated with long-range correlations, efficient information processing, and the emergence of collective organization. While altered criticality-related measures have been reported in psychiatric disorders, previous findings remain fragmented across observables and modalities, making it unclear whether different scaling me...

Submitted: June 5, 2026Subjects: Neuroscience; Neuroscience

Description / Details

Accumulating evidence suggests that large-scale brain activity exhibits scale-invariant dynamics consistent with operation in a near-critical regime. Such dynamics have been associated with long-range correlations, efficient information processing, and the emergence of collective organization. While altered criticality-related measures have been reported in psychiatric disorders, previous findings remain fragmented across observables and modalities, making it unclear whether different scaling measures capture a common alteration of large-scale brain dynamics. Here, we investigated scaling properties in resting-state fMRI data from individuals with early psychosis and healthy controls. We combined a phenomenological renormalization group (PRG) framework with power spectral density (PSD) and detrended fluctuation analysis (DFA) to characterize collective dynamics across scales. In healthy controls, resting-state activity exhibited non-trivial scaling behavior consistent with critical-like organization. Early psychosis participants showed the same overall phenomenology of scale-invariant organization, but with systematic shifts in scaling exponents across multiple observables. These findings indicate that early psychosis is not characterized by a simple loss of critical-like dynamics, but rather by a reorganization of collective dynamics within a preserved scaling regime. More broadly, our results suggest that combining coarse-graining approaches with temporal scaling analyses provides a principled framework for studying large-scale brain dynamics in psychiatric disorders.


Source: arXiv:2606.06290v1 - http://arxiv.org/abs/2606.06290v1 PDF: https://arxiv.org/pdf/2606.06290v1 Original Link: http://arxiv.org/abs/2606.06290v1

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Date:
Jun 5, 2026
Topic:
Neuroscience
Area:
Neuroscience
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