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Symmetric Bihemispheric Postmortem Brain Cutting to Study Healthy and Pathological Brain Conditions in Humans

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How deep is the brain? The shallow brain hypothesis.

Mototaka Suzuki¹, Cyriel M A Pennartz², Jaan Aru³

¹Department of Cognitive and Systems Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands. mototaka@gmail.com.

Nature Reviews. Neuroscience

|October 27, 2023

Summary

Current deep learning models overlook subcortical input, unlike the brain. The shallow brain hypothesis proposes integrating parallel processing with hierarchical cortical networks for more efficient neural network computation.

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Published on: October 22, 2017

Area of Science:

Computational neuroscience
Artificial intelligence
Neurobiology

Background:

Deep learning and predictive coding models predominantly use hierarchical inference.
Neurobiological evidence shows direct subcortical connections to all cortical areas, challenging purely hierarchical models.

Purpose of the Study:

To propose the shallow brain hypothesis, integrating hierarchical cortical processing with parallel subcortical contributions.
To highlight computational principles potentially missed by current deep learning architectures.

Main Methods:

Conceptual analysis of neuroanatomy and computational architectures.
Comparison of proposed shallow brain architecture with deep hierarchical models.

Main Results:

Current hierarchical models may miss essential brain computational principles.
A shallow architecture leverages cortical microcircuits and thalamo-cortical loops.

Conclusions:

The shallow brain hypothesis offers a more biologically plausible and potentially more efficient computational framework.
This model better explains the mammalian brain's fast and flexible capabilities compared to deep hierarchical structures.