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Language Development

Language Development

Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...

Language and Cognition

Language and Cognition

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.

Higher Mental Functions of the Brain: Language

Higher Mental Functions of the Brain: Language

Language is a system of communication that allows the expression of thoughts, ideas, and feelings. The brain processes language in both hemispheres.
Language formation and comprehension take place in the dominant hemisphere. The dominant hemisphere is responsible for understanding the meaning of spoken, written, or sign language, as well as the ability to communicate. For most people, the left hemisphere is the dominant one. The right hemisphere, then, gives tone and emotional context to the...

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Related Experiment Video

Updated: Oct 17, 2025

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants

Published on: October 4, 2015

Language function following preterm birth: prediction using machine learning.

Evdoxia Valavani¹, Manuel Blesa², Paola Galdi²

¹Usher Institute, Medical School, University of Edinburgh, Edinburgh, UK. evdoxia.valavani@ed.ac.uk.

Pediatric Research

|October 12, 2021

Summary

This summary is machine-generated.

Predicting language development in preterm infants is crucial. This study accurately forecasts language outcomes at two years using clinical data and diffusion MRI, enabling early intervention for those at risk.

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Last Updated: Oct 17, 2025

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants

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Published on: October 4, 2015

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Infant Auditory Processing and Event-related Brain Oscillations

Infant Auditory Processing and Event-related Brain Oscillations

Published on: July 1, 2015

Area of Science:

Neuroscience
Developmental Pediatrics
Medical Imaging

Background:

Preterm birth is a significant risk factor for impaired language development.
Early identification of language deficits in preterm infants is essential for timely intervention.

Purpose of the Study:

To predict language outcomes at 2 years corrected gestational age (CGA) in preterm infants.
To develop a model combining clinical and neuroimaging data for accurate language delay prediction.

Main Methods:

Diffusion MRI (dMRI) was performed on 89 preterm neonates at term-equivalent age.
A random forests classifier was employed with feature selection to predict language development (Bayley-III score <85) at 2 years CGA.

Main Results:

The prediction model achieved high accuracy (91% balanced accuracy, 86% sensitivity, 96% specificity).
Factors increasing language delay risk included specific dMRI metrics (PSFA, PSRD, PSAD), being a twin, and incomplete antenatal corticosteroid exposure.
Female sex and neonatal breastfeeding were associated with reduced risk of language delay.

Conclusions:

Combining perinatal clinical information and dMRI features enables accurate prediction of language deficits in preterm infants.
This predictive model can stratify preterm children at risk, facilitating targeted early interventions and improving long-term outcomes.