Dataset Information

Prosody Predicts Contest Outcome in Non-Verbal Dialogs.

ABSTRACT: Non-verbal communication has important implications for inter-individual relationships and negotiation success. However, to what extent humans can spontaneously use rhythm and prosody as a sole communication tool is largely unknown. We analysed human ability to resolve a conflict without verbal dialogs, independently of semantics. We invited pairs of subjects to communicate non-verbally using whistle sounds. Along with the production of more whistles, participants unwittingly used a subtle prosodic feature to compete over a resource (ice-cream scoops). Winners can be identified by their propensity to accentuate the first whistles blown when replying to their partner, compared to the following whistles. Naive listeners correctly identified this prosodic feature as a key determinant of which whistler won the interaction. These results suggest that in the absence of other communication channels, individuals spontaneously use a subtle variation of sound accentuation (prosody), instead of merely producing exuberant sounds, to impose themselves in a conflict of interest. We discuss the biological and cultural bases of this ability and their link with verbal communication. Our results highlight the human ability to use non-verbal communication in a negotiation process.

SUBMITTER: Dreiss AN

PROVIDER: S-EPMC5132166 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Prosody Predicts Contest Outcome in Non-Verbal Dialogs.

Dreiss Amélie N AN Chatelain Philippe G PG Roulin Alexandre A Richner Heinz H

PloS one 20161201 12

Non-verbal communication has important implications for inter-individual relationships and negotiation success. However, to what extent humans can spontaneously use rhythm and prosody as a sole communication tool is largely unknown. We analysed human ability to resolve a conflict without verbal dialogs, independently of semantics. We invited pairs of subjects to communicate non-verbally using whistle sounds. Along with the production of more whistles, participants unwittingly used a subtle proso ...[more]

PMID: 27907039

Similar Datasets

Project description:Epilepsy is increasingly considered a disorder of brain networks. Studying these networks with functional connectivity can help identify hubs that facilitate the spread of epileptiform activity. Surgical resection of these hubs may lead patients who suffer from drug-resistant epilepsy to seizure freedom. Here, we aim to map non-invasively epileptogenic networks, through the virtual implantation of sensors estimated with electric and magnetic source imaging, in patients with drug-resistant epilepsy. We hypothesize that highly connected hubs identified non-invasively with source imaging can predict the epileptogenic zone and the surgical outcome better than spikes localized with conventional source localization methods (dipoles). We retrospectively analysed simultaneous high-density electroencephalography (EEG) and magnetoencephalography data recorded from 37 children and young adults with drug-resistant epilepsy who underwent neurosurgery. Using source imaging, we estimated virtual sensors at locations where intracranial EEG contacts were placed. On data with and without spikes, we computed undirected functional connectivity between sensors/contacts using amplitude envelope correlation and phase locking value for physiologically relevant frequency bands. From each functional connectivity matrix, we generated an undirected network containing the strongest connections within sensors/contacts using the minimum spanning tree. For each sensor/contact, we computed graph centrality measures. We compared functional connectivity and their derived graph centrality of sensors/contacts inside resection for good (n = 22, ILAE I) and poor (n = 15, ILAE II-VI) outcome patients, tested their ability to predict the epileptogenic zone in good-outcome patients, examined the association between highly connected hubs removal and surgical outcome and performed leave-one-out cross-validation to support their prognostic value. We also compared the predictive values of functional connectivity with those of dipoles. Finally, we tested the reliability of virtual sensor measures via Spearman's correlation with intracranial EEG at population- and patient-level. We observed higher functional connectivity inside than outside resection (P < 0.05, Wilcoxon signed-rank test) for good-outcome patients, on data with and without spikes across different bands for intracranial EEG and electric/magnetic source imaging and few differences for poor-outcome patients. These functional connectivity measures were predictive of both the epileptogenic zone and outcome (positive and negative predictive values ≥55%, validated using leave-one-out cross-validation) outperforming dipoles on spikes. Significant correlations were found between source imaging and intracranial EEG measures (0.4 ≤ rho ≤ 0.9, P < 0.05). Our findings suggest that virtual implantation of sensors through source imaging can non-invasively identify highly connected hubs in patients with drug-resistant epilepsy, even in the absence of frank epileptiform activity. Surgical resection of these hubs predicts outcome better than dipoles.

Dataset Information

Prosody Predicts Contest Outcome in Non-Verbal Dialogs.

Publications

Prosody Predicts Contest Outcome in Non-Verbal Dialogs.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets