Examining predictive coding accounts of typical and autistic neurocognitive development

Area of Science:

• Neuroscience
• Developmental Psychology
• Cognitive Science

Background:

• Predictive coding is a leading theory for perception and neural processing.
• Interest in predictive coding is growing across mind sciences.
• Limited research explores predictive coding in young neurotypical and autistic children.

Purpose of the Study:

• To review predictive coding theories of neurocognitive development in typical and autistic children.
• To examine existing electrophysiological evidence for these theories.
• To highlight the need for further pediatric research.

Main Methods:

• Literature review of predictive coding frameworks.
• Analysis of electrophysiological studies in child populations.
• Synthesis of findings on typical and autistic neurodevelopment.

Main Results:

• Predictive coding offers a framework for understanding typical and autistic neurocognitive development.
• Electrophysiological evidence provides some support for predictive coding models.
• Significant gaps exist in research concerning young children.

Conclusions:

• Further pediatric research is crucial to validate predictive coding accounts of neurodevelopment.
• Findings could inform educational, parenting, AI, and clinical strategies for autistic children.
• Predictive coding may offer new ways to manage sensory processing in autism.