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Updated: Jun 5, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain
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Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Spatial and temporal cognitive mapping: a neural network approach.

N A Schmajuk, C V Buhusi

    Trends in Cognitive Sciences
    |January 13, 2011
    PubMed
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    Cognitive maps and goal-seeking mechanisms enable adaptable behavior by integrating knowledge for planning. This research proposes recurrent associative networks for spatial and temporal cognitive mapping, aiding problem-solving.

    Area of Science:

    • Cognitive Psychology
    • Neuroscience
    • Computational Neuroscience

    Background:

    • Tolman's theory posits purposive cognitive behavior driven by goal pursuit.
    • Adaptable behavior arises from goal-seeking mechanisms and cognitive maps.
    • Cognitive maps integrate diverse knowledge, extending beyond spatial navigation.

    Purpose of the Study:

    • To mechanistically implement spatial and temporal cognitive maps using recurrent associative networks.
    • To describe problem-solving as a sequence of subgoals (plans) enabled by cognitive maps and goal-seeking.
    • To explore the neural substrates involved in cognitive mapping and goal-directed behavior.

    Main Methods:

    • Modeling spatial and temporal cognitive maps using recurrent associative networks.

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    Last Updated: Jun 5, 2026

    Modeling the Functional Network for Spatial Navigation in the Human Brain
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    Modeling the Functional Network for Spatial Navigation in the Human Brain

    Published on: October 13, 2023

    Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
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  • Representing spatial location adjacency and temporal event contiguity within networks.
  • Conceptualizing network predictions as 'imagining' spatial or temporal sequences.

    • Main Results:

    • Recurrent associative networks can mechanistically implement both spatial and temporal cognitive maps.
    • The integration of cognitive maps and goal-seeking systems provides a framework for understanding planning and problem-solving.
    • Hypothesized roles for the hippocampus in storing cognitive maps and the frontal cortex in goal-seeking and planning.

    Conclusions:

    • Cognitive mapping, encompassing both spatial and temporal domains, can be modeled using recurrent associative networks.
    • This framework offers insights into the neural basis of adaptable, goal-directed behavior and problem-solving.
    • The hippocampus and frontal cortex are implicated as key neural structures in these cognitive processes.