Back to search

Article

A computational architecture incorporating shallow brain networks: integrating parallel cortical and subcortical processing

2025-02-25

Abstract excerpt

Artificial neural networks commonly have deep hierarchical structures that were originally inspired by the neuroanatomical evidence of cortico-cortical connectivity pattern found in the mammalian brain. Largely neglected in those models are non-hierarchical aspects of brain architecture, namely the subcortical pathways and the interactions between cortical and subcortical areas regardless of their hierarchical loc...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
bdecc941-9702-556d-9a40-cf4b6d105842
DOI
10.1101/2025.02.24.639932
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
A computational architecture incorporating shallow brain networks: integrating parallel cortical and subcortical processingDOI 10.1101/2025.02.24.639932
Cortical Hierarchy, Dual Counterstream Architecture and The Importance of Top-Down Generative NetworksSemantic proximity
A connectivity-constrained computational account of topographic organization in primate high-level visual cortexSemantic proximity
Why, where and how do top-down and bottom-up signals interact in the primate brain?Semantic proximity
Why, where and how do top-down and bottom-up signals interact in the primate brain?Semantic proximity
Why, where and how do top-down and bottom-up signals interact in the primate brain?Semantic proximity
Why, where and how do top-down and bottom-up signals interact in the primate brain?Semantic proximity
Why, where and how do top-down and bottom-up signals converge in the primate brain?Semantic proximity
Interpretable brain decoding from sensations to cognition to action: graph neural networks reveal the representational hierarchy of human cognitionSemantic proximity
The neural architecture of language: Integrative modeling converges on predictive processingSemantic proximity
A controller-peripheral architecture and costly energy principle for learningSemantic proximity
DNNBrain: a unifying toolbox for mapping deep neural networks and brainsSemantic proximity
The Multilayer Processing Theory of Human IntelligenceSemantic proximity
Select a neighboring publication to make it the new centre.