Poster No:
808
Submission Type:
Late-Breaking Abstract Submission
Authors:
Paul Sowman1, Judy Zhu2, Julian Maclaren3, YiFan Gu4, Eric Larson5, Adrian Lee5, Simon Carlile6
Institutions:
1Auckland University of Technology, Auckland, Auckland, 2Macquarie University, Sydney, New South Wales, 3Google Resarch, Sydney, New South Wales, 4Google Research, Sydney, New South Wales, 5University of Washington, Seattle, WA, 6Google Research, Sydney, New SOuth Wales
First Author:
Co-Author(s):
Judy Zhu
Macquarie University
Sydney, New South Wales
Introduction:
Understanding neural dynamics during natural, free-flowing conversations is essential for advancing our knowledge of social communication neuroscience. While previous research has largely relied on structured language tasks, fewer studies have examined the neural correlates of natural dialogues. This study investigated how beta-band oscillatory activity (13-30 Hz) differs between naturalistic conversation and structured speech repetition conditions, focusing on two critical temporal windows during speech processing.
Methods:
Twenty participants engaged in video-mediated conversations with an interviewer while undergoing concurrent MEG/EEG recording. Participants alternated between free-flowing conversation and nursery rhyme repetition tasks. We analysed neural responses during two distinct temporal windows: the early listening period (first 500ms following interviewer's turn onset) and the pre-response period (500ms preceding participant's speech onset). Brain activity was reconstructed using LCMV beamforming with the HCP parcellation atlas. Support vector machine (SVM) classification was employed to distinguish between conversation and repetition conditions across theta (4-8 Hz), alpha (8-12 Hz), and beta (13-30 Hz) frequency bands. Participants completed a Relational Communication Scale questionnaire to assess their subjective experience of social presence during the interactions.
Results:
SVM classification revealed robust discrimination between conversation and repetition conditions, with notably higher accuracy in the beta-band (0.76 ± 0.12 and 0.77 ± 0.14 for early listening and pre-response periods, respectively) compared to theta and alpha bands. Five brain regions, including bilateral temporal areas, showed significant modulation during the early listening period. The pre-response period engaged a broader network of eight regions, including additional frontal areas. Beta power was consistently higher during conversation than repetition across most regions. Significantly, beta power differences correlated with participants' subjective ratings of social presence, particularly in frontal regions. These correlations suggest reduced social engagement may require more cognitive effort for speech processing.
Conclusions:
Our findings reveal that beta-band oscillatory activity serves as a key neural marker for differentiating speech processing based on conversational context and temporal position within an interaction. The engagement of an expanded frontotemporal network during the pre-response period compared to early listening suggests additional cognitive resources are recruited when preparing conversational responses. The correlation between beta power and social presence ratings provides evidence that the neural mechanisms supporting natural conversation are modulated by the subjective experience of social connection. These results advance our understanding of the neural dynamics underlying natural social communication and have implications for clinical populations with social communication difficulties.
Language:
Language Comprehension and Semantics 1
Modeling and Analysis Methods:
Multivariate Approaches
Novel Imaging Acquisition Methods:
MEG 2
Keywords:
MEG
Other - Speech, Language, and Communication Neuroscience
1|2Indicates the priority used for review
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Was this research conducted in the United States?
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Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
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