Neural tracking in infants - An analytical tool for multisensory social processing in development
Sarah Jessen1, Jonas Obleser2, Sarah Tune2
1Department of Neurology, University of Lübeck, Ratzeburger Allee 160, 23562 Lübeck, Germany; Center of Brain, Behavior, and Metabolism, University of Lübeck, Germany.
Developmental Cognitive Neuroscience
|November 15, 2021
Summary
This tutorial introduces neural tracking using linear models to analyze electroencephalographic (EEG) data in infants. It offers a method for studying early social processing in naturalistic settings.
Area of Science:
- Cognitive Neuroscience
- Developmental Psychology
- Neuroscience
Background:
- Humans possess innate social cue detection abilities.
- Investigating early social processing under naturalistic conditions is increasingly important.
- Linking neural responses to continuous dynamic input is challenging.
Purpose of the Study:
- To introduce linear models for analyzing neural tracking responses in electroencephalographic (EEG) data.
- To provide a step-by-step guide for applying neural tracking to infant EEG.
- To compare forward vs. backward and individual vs. generic models.
Main Methods:
- Utilizes linear models to investigate neural tracking.
- Applies methods to infant EEG data.
- Includes theoretical introductions and practical MATLAB code examples.
Main Results:
- Neural tracking offers a viable approach for analyzing continuous EEG data.
- Comparison of different modeling approaches (forward/backward, individual/generic) is discussed.
- Demonstrates the application of neural tracking to infant social processing.
Conclusions:
- Neural tracking is a promising method for studying early social processing.
- The tutorial provides practical tools and insights for researchers.
- This approach enhances ecological validity in infant neuroscience research.
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