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Related Experiment Video

Updated: Jul 19, 2025

Three-dimensional Tissue Engineered Aligned Astrocyte Networks to Recapitulate Developmental Mechanisms and Facilitate Nervous System Regeneration

Three-dimensional Tissue Engineered Aligned Astrocyte Networks to Recapitulate Developmental Mechanisms and Facilitate Nervous System Regeneration

Published on: January 10, 2018

Building transformers from neurons and astrocytes.

Leo Kozachkov^1,2, Ksenia V Kastanenka³, Dmitry Krotov¹

¹Massachusetts Institute of Technology-International Business Machines, Watson Artificial Intelligence Laboratory, IBM Research, Cambridge, MA 02142.

Proceedings of the National Academy of Sciences of the United States of America

|August 14, 2023

Summary

This summary is machine-generated.

Glial cells, including astrocytes, are vital for brain function. New research shows neuron-astrocyte networks can perform computations similar to AI Transformers, potentially explaining brain flexibility.

Keywords:

Transformers artificial intelligence astrocytes glia neuroscience

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Last Updated: Jul 19, 2025

Three-dimensional Tissue Engineered Aligned Astrocyte Networks to Recapitulate Developmental Mechanisms and Facilitate Nervous System Regeneration

Three-dimensional Tissue Engineered Aligned Astrocyte Networks to Recapitulate Developmental Mechanisms and Facilitate Nervous System Regeneration

Published on: January 10, 2018

Isolation and Direct Neuronal Reprogramming of Mouse Astrocytes

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Published on: July 7, 2022

3D Bioprinting of Murine Cortical Astrocytes for Engineering Neural-Like Tissue

3D Bioprinting of Murine Cortical Astrocytes for Engineering Neural-Like Tissue

Published on: July 16, 2021

Area of Science:

Neuroscience
Artificial Intelligence
Computational Biology

Background:

Glial cells constitute 50-90% of human brain cells, performing critical developmental, structural, and metabolic roles.
Astrocytes, a type of glial cell, are increasingly recognized for their direct involvement in cognitive functions like learning and memory.
The precise computational role of neuron-astrocyte interactions remains an underexplored area, despite known feedback loops.

Purpose of the Study:

To bridge the understanding gap in the computational role of neuron-astrocyte interactions.
To explore the potential of neuron-astrocyte networks to perform complex computations.
To provide a testable framework for neuron-astrocyte communication.

Main Methods:

Leveraging recent advancements in artificial intelligence (AI) and astrocyte imaging technologies.
Analyzing neuron-astrocyte networks through the lens of computational principles.
Comparing the computational capabilities of neuron-astrocyte networks to AI architectures like Transformers.

Main Results:

Demonstrated that neuron-astrocyte networks can naturally perform the core computations characteristic of Transformer AI models.
Established a normative and experimentally testable model for neuron-astrocyte communication.
Identified parallels between the computational power of neuron-astrocyte networks and the success of Transformers in diverse tasks.

Conclusions:

Neuron-astrocyte networks possess computational capabilities analogous to advanced AI.
This finding offers a potential explanation for the brain's ubiquity, flexibility, and power in processing information.
The study provides a novel framework for understanding brain function through the integration of neuroscience and AI.