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Updated: May 21, 2025

Modeling the Functional Network for Spatial Navigation in the Human Brain
Published on: October 13, 2023
Where are higher-order cognitive functions? The paradox of non-locality in awake cognitive mapping using a complex
Jesús Martín-Fernández1,2,3, Nayra Caballero-Estebaranz2,3,4, Esteban Félez2,5
1Department of Neurosurgery, Nuestra Señora de Candelaria University Hospital, Tenerife, Spain.
Abstract:
This study addresses the challenge in identifying and preserving higher-order cognitive functions within a complex dynamic systems framework during neurosurgery. Traditionally, neurosurgical practice has prioritized avoiding language and motor deficits, while higher-order functions-such as social cognition and executive processes-remain underexplored. These functions arise from dynamic large-scale networks operating in an optimal balance between synchronization and metastability rather than from isolated and localized cortical regions. This complexity highlights a paradox of non-locality in awake cognitive mapping: no single area "contains" a function, but certain "critical points" can transiently disrupt network dynamics when stimulated intraoperatively. Direct electrical stimulation provides unique real-time insights by inducing brief dyssynchronizations that elicit observable behavioral changes, allowing neurosurgeons and neuropsychologists to pinpoint crucial cortical and subcortical "connectome-stop points" and minimize damage. Preserving deep white-matter tracts is essential, given their limited neuroplasticity and the profound, often irreversible impact of tract lesions on cognition. To address these challenges, we propose a three-step awake cognitive mapping approach: (1) localizing critical points of networks via DES-driven behavioral impairment, (2) constant monitoring of multiple cognitive domains as tumor resection progresses, and (3) halting resection at connectome-stop points to prevent irreversible deficits. An illustrative case involving a right parietal glioma demonstrates how this methodology integrates computational neuroscience, network theory, and clinical practice to achieve optimal functional preservation and maintain the patient's quality of life.
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