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The fading self in space-disruption of default spatial representation across neurological disorders.

Ravinder Jerath, Varsha Malani

Frontiers in Systems Neuroscience December 29, 2025 DOI: 10.3389/fnsys.2025.1655500 (opens in new tab)

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Characteristics Review Peer reviewed
Topics Default mode network
Keywords Schizophrenia Cognitive map Auditory hallucinations Body schema Dsr Default spatial representation
Key findings Argues that diverse neurological and psychiatric conditions—including contralateral neglect, psychogenic paralysis, disorders of consciousness, autism, Alzheimer's disease, schizophrenia, and depersonalization/derealization—may share a common etiology in the pathologic disintegration of a "default spatial representation" (DSR). The authors propose that this breakdown is associated with anomalous activation and connectivity in large-scale brain networks such as the default mode network and attention networks, and advocate a network-based diagnostic and treatment strategy aimed at restoring self-in-space.

Abstract

Neurological disorders stem from an intermingled change to self-in-space. While many of these disorders present as spatial deficits-contralateral neglect syndrome, for example-they manifest from the same etiology: disruption to the brain's "default spatial representation" (DSR). DSR is a basic internally generated representation of space that delineates where the self is located in space-without attentional focus from an external drive. We review how pathologic disintegration of DSR is associated with anomalous activation and connectivity within distinct large-scale brain networks (e.g., the default mode network and a comprehensive attention-networked system), leading to a heterogeneous presentation of clinically assessed outcomes. The outcomes include psychogenic paralysis of limbs, left-side neglect, rectified sense of other locations, disorders of consciousness, symptoms related to autism spectrum disorder, Alzheimer's disease, schizophrenia, and depersonalization/derealization disorder. By consolidating evidence from neuroimaging, lesion-symptom mapping, and computational assessment, we aim to reconceptualize these disorders not as separate and independent maladies, but as manifestations of a deeper, shared etiology, supporting a network-based assessment strategy for diagnosis and treatment that seeks to restore self-in-space.

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