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Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Model-based neuroimaging for cognitive computing.

Roman R Poznanski¹

¹Department of Artificial Intelligence, Faculty of Computer Science & Information Technology, University of Malaya, 50603 Kuala Lumpur, Malaysia. roman.poznanski@um.edu.my

Journal of Integrative Neuroscience

|November 26, 2009

Summary

This summary is machine-generated.

The continuity of the mind arises from neocortex electrochemical dynamics, enabling a stream of consciousness. New brain-machine interfaces could decipher higher cognition by mapping qualia using dynamic continuity models.

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Area of Science:

Neuroscience
Cognitive Science
Computational Neuroscience

Background:

The mind's continuity is theorized to stem from the neocortex's electrochemical signature.
This involves global volume transmission and local extrasynaptic signaling within cortical neurons.

Purpose of the Study:

To propose a model where continuous dynamical systems define consciousness.
To explore how intentional metarepresentations facilitate semantic mapping of qualia during neuroimaging.
To outline the potential of model-based neuroimaging for deciphering higher cognitive functions.

Main Methods:

Conceptual modeling of spatiotemporal dynamics in the neocortex.
Linking dynamical systems continuity to the stream of consciousness.
Investigating the role of metarepresentations in qualia mapping.

Main Results:

Electrochemical dynamics in the neocortex, both global and local, are proposed as the basis for mental continuity.
Dynamic continuity templates (metarepresentations) enable semantic mapping of qualia during cognitive tasks.
A framework for model-based neuroimaging is suggested, requiring novel mathematical approaches.

Conclusions:

The continuity of the mind is fundamentally linked to the spatiotemporal dynamics of the neocortex.
This framework supports the semantic mapping of subjective experiences (qualia) via computational models.
Future advancements in brain-machine interfaces may leverage these concepts to decode complex cognitive operations.