TY - JOUR
T1 - Social touch in the age of computational ethology
T2 - Embracing as a multidimensional and complex behaviour
AU - Ocklenburg, Sebastian
AU - Packheiser, Julian
AU - Hidalgo-Gadea, Guillermo
N1 - Funding Information:
Open Access funding enabled and organized by Projekt DEAL. This work was supported by the German Research Foundation DFG in the context of the Research Training Group “Situated Cognition” (GRK 2185/1), in German: “Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - Projektnummer GRK 2185/1”. Julian Packheiser was supported by the German National Academy of Sciences Leopoldina (LPDS2021-05).
Publisher Copyright:
© 2022, The Author(s).
PY - 2023
Y1 - 2023
N2 - Social affective touch is an important aspect of close relationships in humans. It has been also observed in many non-human primate species. Despite the high relevance of behaviours like embraces for personal wellbeing and mental health, they remain vastly under-investigated in psychology. This may be because psychology often relies on a limited repertoire of behavioural measurements such as error rates and reaction time measurements. These are, however, insufficient to capture the multidimensional complexity of highly interactive dyadic behaviours like embraces. Based on recent advances in computational ethology in animal models, the rapidly emerging field of human computational ethology utilizes an accessible repertoire of machine learning methods to track and quantify complex natural behaviours. We highlight how such techniques can be utilized to investigate social touch and which preliminary conditions, motor aspects and higher-level interactions need to be considered. Ultimately, integration of computational ethology with mobile neuroscience techniques such as ultraportable EEG systems will allow for an ecologically valid investigation of social affective touch in humans that will advance psychological research of emotions.
AB - Social affective touch is an important aspect of close relationships in humans. It has been also observed in many non-human primate species. Despite the high relevance of behaviours like embraces for personal wellbeing and mental health, they remain vastly under-investigated in psychology. This may be because psychology often relies on a limited repertoire of behavioural measurements such as error rates and reaction time measurements. These are, however, insufficient to capture the multidimensional complexity of highly interactive dyadic behaviours like embraces. Based on recent advances in computational ethology in animal models, the rapidly emerging field of human computational ethology utilizes an accessible repertoire of machine learning methods to track and quantify complex natural behaviours. We highlight how such techniques can be utilized to investigate social touch and which preliminary conditions, motor aspects and higher-level interactions need to be considered. Ultimately, integration of computational ethology with mobile neuroscience techniques such as ultraportable EEG systems will allow for an ecologically valid investigation of social affective touch in humans that will advance psychological research of emotions.
KW - Behavioural neuroscience
KW - Computational ethology
KW - Embracing
KW - Hugging
KW - Social touch
UR - http://www.scopus.com/inward/record.url?scp=85127431050&partnerID=8YFLogxK
U2 - 10.1007/s12144-022-03051-9
DO - 10.1007/s12144-022-03051-9
M3 - Article
AN - SCOPUS:85127431050
SN - 1046-1310
VL - 42
SP - 18539
EP - 18548
JO - Current Psychology
JF - Current Psychology
ER -