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Higher Mental Functions of the Brain: Language

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Language is a system of communication that allows the expression of thoughts, ideas, and feelings. The brain processes language in both hemispheres.
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Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.

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Updated: Jun 28, 2025

Utilizing Repetitive Transcranial Magnetic Stimulation to Improve Language Function in Stroke Patients with Chronic Non-fluent Aphasia

Utilizing Repetitive Transcranial Magnetic Stimulation to Improve Language Function in Stroke Patients with Chronic Non-fluent Aphasia

Published on: July 2, 2013

Predicting Language Function Post-Stroke: A Model-Based Structural Connectivity Approach.

Franziska E Hildesheim^1,2,3, Anja Ophey⁴, Anna Zumbansen^5,6

¹Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, QC, Canada.

Neurorehabilitation and Neural Repair

|April 11, 2024

Summary

This summary is machine-generated.

Predicting post-stroke language recovery is crucial for personalized aphasia treatment. Connectivity disruption in the language network, assessed via routine MRI, significantly improves prediction accuracy beyond traditional measures.

Keywords:

Random Forest aphasia diffusion tensor imaging predictive modeling stroke structural connectivity

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Utilizing Repetitive Transcranial Magnetic Stimulation to Improve Language Function in Stroke Patients with Chronic Non-fluent Aphasia

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Transcranial Direct Current Stimulation tDCS of Wernicke's and Broca's Areas in Studies of Language Learning and Word Acquisition

Transcranial Direct Current Stimulation tDCS of Wernicke's and Broca's Areas in Studies of Language Learning and Word Acquisition

Published on: July 13, 2019

Area of Science:

Neuroscience
Medical Imaging
Computational Biology

Background:

Accurate prediction of post-stroke language function is vital for tailoring rehabilitation strategies for patients with aphasia.
Individualized treatment plans depend on understanding a patient's unique recovery potential.

Purpose of the Study:

To develop a predictive framework integrating language network connectivity disruption from routine MRI into Random Forest models.
The goal is to enhance the prediction of language function recovery after stroke.

Main Methods:

Assessed language function in 76 stroke patients using Token Test, Boston Naming Test, and Semantic Verbal Fluency.
Calculated structural connectivity disruption by analyzing infarct masks on diffusion tensor imaging tractograms.
Developed multivariable Random Forest models to predict language outcomes.

Main Results:

Random Forest models demonstrated moderate to high variance explained for all language tests (e.g., 76.2% for TT at follow-up).
Initial language and non-verbal cognitive abilities were key predictors.
Language network connectivity disruption provided additional predictive value, with specific regions like the middle temporal gyrus being significant.

Conclusions:

Language network connectivity disruption offers significant predictive value beyond lesion characteristics and baseline function.
Utilizing routine clinical MRI for connectivity assessment represents a practical advancement for clinical application in stroke recovery.