PSYCHIATRIC DISORDERS AS DYSFUNCTIONS OF SLEEP–IMMUNE–BRAIN NETWORK DYNAMICS: A SYSTEMS-LEVEL NEUROCOGNITIVE FRAMEWORKABSTRACT

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Background:Sleep disturbances and neuroimmune activation are increasingly recognized as core processes in the pathophysiology of psychiatric disorders. However, these domains have largely been investigated in isolation, limiting the development of integrative mechanistic frameworks capable of explaining transdiagnostic symptom overlap, clinical heterogeneity, and treatment resistance.Objective: This integrative review proposes a systems-level neurocognitive framework in which psychiatric disorders are conceptualized as emergent phenomena arising from dysregulated interactions among sleep regulation, neuroimmune signaling, and large-scale brain network dynamics.Methods: We conducted a narrative integrative review synthesizing evidence from sleep science, psychoneuroimmunology, and network neuroscience across mood, anxiety, trauma-related, and psychotic disorders. Findings from experimental, clinical, and neuroimaging studies were examined to identify convergent mechanisms linking sleep disruption, inflammatory activation, and neural network instability.Results: Converging evidence indicates that circadian misalignment, stress-system dysregulation, microglial and astroglial activation, neurotransmitter imbalance, and kynurenine pathway metabolism interact through nonlinear feedback loops that destabilize cortico-limbic circuits and large-scale brain networks, including default mode, salience, and executive control systems. These interactions promote maladaptive attractor states characterized by impaired synaptic plasticity, altered network connectivity, and persistent hyperarousal. Conclusions:Conceptualizing psychiatric disorders as disorders of coupled sleep–immune–brain systems provides a unifying mechanistic framework that transcends traditional diagnostic boundaries. This systems-level perspective highlights sleep and neuroimmune processes as central regulators of neural network stability and identifies promising targets for biomarker development and mechanism-based, precision-oriented interventions.