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Journal Article

The CABB dataset: A multimodal corpus of communicative interactions for behavioural and neural analyses

MPS-Authors
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Rasenberg,  Marlou
Multimodal Language Department, MPI for Psycholinguistics, Max Planck Society;
Center for Language Studies, External Organizations;

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Holler,  Judith
Communication in Social Interaction, Radboud University Nijmegen, External Organizations;
Other Research, MPI for Psycholinguistics, Max Planck Society;
Donders Institute for Brain, Cognition and Behaviour, External Organizations;

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Ozyurek,  Asli
Multimodal Language Department, MPI for Psycholinguistics, Max Planck Society;
Donders Institute for Brain, Cognition and Behaviour, External Organizations;
Center for Language Studies, External Organizations;

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Pouw,  Wim
Other Research, MPI for Psycholinguistics, Max Planck Society;
Donders Institute for Brain, Cognition and Behaviour, External Organizations;

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Trujillo,  James P.
Communication in Social Interaction, Radboud University Nijmegen, External Organizations;
Other Research, MPI for Psycholinguistics, Max Planck Society;
Donders Institute for Brain, Cognition and Behaviour, External Organizations;

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Fulltext (public)

Eijk_etal_2022_CABB dataset.pdf
(Publisher version), 4MB

Supplementary Material (public)

Eijk_etal_2022suppl1_CABB dataset.pdf
(Supplementary material), 160KB

Eijk_etal_2022suppl2_CABB dataset.pdf
(Supplementary material), 454KB

Citation

Eijk, L., Rasenberg, M., Arnese, F., Blokpoel, M., Dingemanse, M., Doeller, C. F., et al. (2022). The CABB dataset: A multimodal corpus of communicative interactions for behavioural and neural analyses. NeuroImage, 264: 119734. doi:10.1016/j.neuroimage.2022.119734.


Cite as: https://hdl.handle.net/21.11116/0000-000B-62E7-2
Abstract
We present a dataset of behavioural and fMRI observations acquired in the context of humans involved in multimodal referential communication. The dataset contains audio/video and motion-tracking recordings of face-to-face, task-based communicative interactions in Dutch, as well as behavioural and neural correlates of participants’ representations of dialogue referents. Seventy-one pairs of unacquainted participants performed two interleaved interactional tasks in which they described and located 16 novel geometrical objects (i.e., Fribbles) yielding spontaneous interactions of about one hour. We share high-quality video (from three cameras), audio (from head-mounted microphones), and motion-tracking (Kinect) data, as well as speech transcripts of the interactions. Before and after engaging in the face-to-face communicative interactions, participants’ individual representations of the 16 Fribbles were estimated. Behaviourally, participants provided a written description (one to three words) for each Fribble and positioned them along 29 independent conceptual dimensions (e.g., rounded, human, audible). Neurally, fMRI signal evoked by each Fribble was measured during a one-back working-memory task. To enable functional hyperalignment across participants, the dataset also includes fMRI measurements obtained during visual presentation of eight animated movies (35 minutes total). We present analyses for the various types of data demonstrating their quality and consistency with earlier research. Besides high-resolution multimodal interactional data, this dataset includes different correlates of communicative referents, obtained before and after face-to-face dialogue, allowing for novel investigations into the relation between communicative behaviours and the representational space shared by communicators. This unique combination of data can be used for research in neuroscience, psychology, linguistics, and beyond.