Domain-specific and domain-general neural network engagement during human-robot interactions.
Ann HogenhuisRuud HortensiusPublished in: The European journal of neuroscience (2022)
To what extent do domain-general and domain-specific neural network engagement generalize across interactions with human and artificial agents? In this exploratory study, we analysed a publicly available functional MRI (fMRI) data set (n = 22) to probe the similarities and dissimilarities in neural architecture while participants conversed with another person or a robot. Incorporating trial-by-trial dynamics of the interactions, listening and speaking, we used whole-brain, region-of-interest and functional connectivity analyses to test response profiles within and across social or non-social, domain-specific and domain-general networks, that is, the person perception, theory-of-mind, object-specific, language and multiple-demand networks. Listening to a robot compared to a human resulted in higher activation in the language network, especially in areas associated with listening comprehension, and in the person perception network. No differences in activity of the theory-of-mind network were found. Results from the functional connectivity analysis showed no difference between interactions with a human or robot in within- and between-network connectivity. Together, these results suggest that although largely similar regions are activated when speaking to a human and to a robot, activity profiles during listening point to a dissociation at a lower level or perceptual level, but not higher order cognitive level.
Keyphrases
- functional connectivity
- resting state
- endothelial cells
- neural network
- induced pluripotent stem cells
- healthcare
- mental health
- clinical trial
- magnetic resonance imaging
- randomized controlled trial
- machine learning
- study protocol
- white matter
- multiple sclerosis
- computed tomography
- electronic health record
- blood brain barrier
- artificial intelligence
- data analysis
- deep learning