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Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

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Published on: March 21, 2019

Hierarchical dynamic coding coordinates speech comprehension in the human brain.

Laura Gwilliams^1,2,3, Alec Marantz^4,5, David Poeppel⁴

¹Department of Psychology, Stanford University, Stanford, CA 94305.

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

|October 17, 2025

Summary

This summary is machine-generated.

The brain uses a hierarchical dynamic coding (HDC) system to process speech, maintaining and updating language features in parallel. This dynamic neural code ensures smooth comprehension of complex language sequences.

Keywords:

decoding hierarchy language machine learning speech

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Area of Science:

Neuroscience
Cognitive Science
Linguistics

Background:

Speech comprehension requires the brain to process acoustic signals into meaning through a hierarchy of language features.
The coordination of these rapidly unfolding hierarchical features in the brain remains poorly understood.

Purpose of the Study:

To investigate the neural mechanisms underlying the coordination of hierarchical language features during speech comprehension.
To test the "hierarchical dynamic coding" (HDC) hypothesis, proposing parallel representation of feature sequences.

Main Methods:

Magnetoencephalography (MEG) was used to record brain activity in 21 participants listening to English stories.
Time-resolved decoding of brain activity was employed to track language feature representations.
Analyses focused on phonetic, word form, lexical-syntactic, syntactic, and semantic levels.

Main Results:

The brain simultaneously represents and maintains sequences of hierarchical language features.
The duration of these neural representations is dependent on their level within the language hierarchy.
Dynamic neural codes, evolving at speeds matching linguistic levels, maintain these representations, preventing interference.

Conclusions:

The hierarchical dynamic coding (HDC) model explains how the brain maintains and updates the language hierarchy during natural speech.
This mechanism preserves information over time and minimizes interference between successive linguistic elements.
Findings bridge linguistic theories with their neural underpinnings.