From brain networks to the patient-environment system in clinical neuroimaging
Abstract
Despite substantial advances in clinical neuroimaging, its impact on defining and treating psychiatric disorders remains limited. Current approaches in clinical brain imaging frame psychiatric disorders as dysfunctions of brain-based information processing. Here, we propose a shift in this explanatory focus, from how aberrant neural processes generate maladaptive behavior to the brain's participation in the dynamics of the patient– environment system. Drawing on organism-environment approaches, we conceptualize behavior as emerging from context-dependent coordinated interactions among brain, body, and environment. Within this framework, we conceptualize psychiatric disorders as excessive stability or flexibility in patient-environment dynamics that impair the patient's capacity to adapt to changing situations. After examining the ontological commitments of current clinical neuroimaging and recasting psychiatric disorders in terms of patient–environment dynamics, we outline concrete strategies for operationalizing this framework. These progress from combining ecological momentary assessment with neuroimaging, to naturalistic brain and body imaging that jointly tracks neural, bodily, and environmental dynamics, and finally to explicit dynamical models of the patient–environment system in which maladaptive stability or flexibility can be formally defined and identified. By making these dynamics measurable, we aim to turn a conceptual reframing into a concrete empirical program, recasting the brain not as the seat of psychiatric disorders but as one participant in the patient–environment dynamics.
Related
- Central nervous system effects of GLP-1 receptor agonists: A systematic review of human neuroimaging studies
- Clinical and neuroimaging features, and associations with early post-stroke cognition in patients with intracerebral hemorrhage in Taiwan
- Season-dependent trait–environment filtering influences interaction networks in mixed-species bird flocks
- Learning Environment-Associated Marker Rankings with Attention-Based Graph Neural Networks
- White Feces Syndrome is closely linked to impaired antioxidant capacity, the aquaculture environment, and microbial dysbiosis in Litopenaeus vannamei reared in small-pond culture system
BibTeX
@misc{corredor2026from,
title = {{From brain networks to the patient-environment system in clinical neuroimaging}},
author = {david corredor and Maxime Carriere and Anaïs Vallet and MELINA GASTELUM and Vicente Raja and Francis Eustache and berengere guillery},
howpublished = {PsyArXiv},
year = {2026},
month = sep,
doi = {10.31234/osf.io/4yqp3_v4},
url = {https://osf.io/preprints/psyarxiv/4yqp3_v4/},
note = {CC0},
}
RIS
TY - UNPB
TI - From brain networks to the patient-environment system in clinical neuroimaging
AU - david corredor
AU - Maxime Carriere
AU - Anaïs Vallet
AU - MELINA GASTELUM
AU - Vicente Raja
AU - Francis Eustache
AU - berengere guillery
PY - 2026
DA - 2026/09/10
PB - PsyArXiv
DO - 10.31234/osf.io/4yqp3_v4
UR - https://osf.io/preprints/psyarxiv/4yqp3_v4/
AB - Despite substantial advances in clinical neuroimaging, its impact on defining and treating psychiatric disorders remains limited. Current approaches in clinical brain imaging frame psychiatric disorders as dysfunctions of brain-based information processing. Here, we propose a shift in this explanatory focus, from how aberrant neural processes generate maladaptive behavior to the brain's participation in the dynamics of the patient– environment system. Drawing on organism-environment approaches, we conceptualize behavior as emerging from context-dependent coordinated interactions among brain, body, and environment. Within this framework, we conceptualize psychiatric disorders as excessive stability or flexibility in patient-environment dynamics that impair the patient's capacity to adapt to changing situations. After examining the ontological commitments of current clinical neuroimaging and recasting psychiatric disorders in terms of patient–environment dynamics, we outline concrete strategies for operationalizing this framework. These progress from combining ecological momentary assessment with neuroimaging, to naturalistic brain and body imaging that jointly tracks neural, bodily, and environmental dynamics, and finally to explicit dynamical models of the patient–environment system in which maladaptive stability or flexibility can be formally defined and identified. By making these dynamics measurable, we aim to turn a conceptual reframing into a concrete empirical program, recasting the brain not as the seat of psychiatric disorders but as one participant in the patient–environment dynamics.
ER -