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EEG-Based Intersubject Correlations Reflect Selective Attention in a Competing Speaker Scenario
Marc Rosenkranz1, Björn Holtze1, Manuela Jaeger1,2
1Neuropsychology Lab, Department of Psychology, University of Oldenburg, Oldenburg, Germany.
Frontiers in Neuroscience
|July 1, 2021
Summary
Intersubject correlation (ISC) of electroencephalogram (EEG) data reveals how attention modulates neural responses to speech. Higher ISCs occurred when participants focused on the same story, reflecting selective attention.
Area of Science:
- Neuroscience
- Cognitive Science
- Auditory Perception
Background:
- Studying brain activity during naturalistic sensory experiences like speech is challenging.
- Intersubject correlation (ISC) using electroencephalogram (EEG) is a promising method to analyze shared neural responses.
- Prior research suggests attention influences EEG-based ISCs.
Purpose of the Study:
- To investigate how selective attention affects intersubject correlation (ISC) in electroencephalogram (EEG) data during competing speech.
- To determine if ISCs predict attentional focus in a multi-talker environment.
Main Methods:
- Utilized a competing-speaker paradigm with 41 participants.
- Recorded electroencephalogram (EEG) data while participants attended to one of two simultaneous speech streams.
- Calculated intersubject correlations (ISCs) between participants' EEG signals.
Main Results:
- ISCs were significantly higher when participants attended to the same story compared to different stories.
- ISCs between individual and group data predicted the attended speech stream (left or right).
- The strength of shared neural responses correlated with the neural representation of attended and ignored speech envelopes.
Conclusions:
- Differences in ISC magnitude reflect the level of selective attentional engagement with speech.
- EEG-based ISC is a valuable tool for quantifying attentional effects in auditory processing.
- Findings elucidate the neural mechanisms underlying attention in complex auditory scenes.
