TY - JOUR
T1 - Decoding brain basis of laughter and crying in natural scenes
AU - Nummenmaa, Lauri
AU - Malèn, Tuulia
AU - Nazari-Farsani, Sanaz
AU - Seppälä, Kerttu
AU - Sun, Lihua
AU - Santavirta, Severi
AU - Karlsson, Henry K.
AU - Hudson, Matthew
AU - Hirvonen, Jussi
AU - Sams, Mikko
AU - Scott, Sophie
AU - Putkinen, Vesa
N1 - Funding Information:
The study was supported by the Sigrid Juselius Foundation and Academy of Finland (grants numbers 294897 and 332225 , to L.N.), the Päivikki and Sakari Sohlberg Foundation (personal grant to T.M.) and the State research funding for expert responsibility area (ERVA) of the Tyks Turku University Hospital (T.M., SN-F, and L.N.).
Publisher Copyright:
© 2023
PY - 2023/6
Y1 - 2023/6
N2 - Laughter and crying are universal signals of prosociality and distress, respectively. Here we investigated the functional brain basis of perceiving laughter and crying using naturalistic functional magnetic resonance imaging (fMRI) approach. We measured haemodynamic brain activity evoked by laughter and crying in three experiments with 100 subjects in each. The subjects i) viewed a 20-minute medley of short video clips, and ii) 30 min of a full-length feature film, and iii) listened to 13.5 min of a radio play that all contained bursts of laughter and crying. Intensity of laughing and crying in the videos and radio play was annotated by independent observes, and the resulting time series were used to predict hemodynamic activity to laughter and crying episodes. Multivariate pattern analysis (MVPA) was used to test for regional selectivity in laughter and crying evoked activations. Laughter induced widespread activity in ventral visual cortex and superior and middle temporal and motor cortices. Crying activated thalamus, cingulate cortex along the anterior-posterior axis, insula and orbitofrontal cortex. Both laughter and crying could be decoded accurately (66–77% depending on the experiment) from the BOLD signal, and the voxels contributing most significantly to classification were in superior temporal cortex. These results suggest that perceiving laughter and crying engage distinct neural networks, whose activity suppresses each other to manage appropriate behavioral responses to others’ bonding and distress signals.
AB - Laughter and crying are universal signals of prosociality and distress, respectively. Here we investigated the functional brain basis of perceiving laughter and crying using naturalistic functional magnetic resonance imaging (fMRI) approach. We measured haemodynamic brain activity evoked by laughter and crying in three experiments with 100 subjects in each. The subjects i) viewed a 20-minute medley of short video clips, and ii) 30 min of a full-length feature film, and iii) listened to 13.5 min of a radio play that all contained bursts of laughter and crying. Intensity of laughing and crying in the videos and radio play was annotated by independent observes, and the resulting time series were used to predict hemodynamic activity to laughter and crying episodes. Multivariate pattern analysis (MVPA) was used to test for regional selectivity in laughter and crying evoked activations. Laughter induced widespread activity in ventral visual cortex and superior and middle temporal and motor cortices. Crying activated thalamus, cingulate cortex along the anterior-posterior axis, insula and orbitofrontal cortex. Both laughter and crying could be decoded accurately (66–77% depending on the experiment) from the BOLD signal, and the voxels contributing most significantly to classification were in superior temporal cortex. These results suggest that perceiving laughter and crying engage distinct neural networks, whose activity suppresses each other to manage appropriate behavioral responses to others’ bonding and distress signals.
UR - http://www.scopus.com/inward/record.url?scp=85152361375&partnerID=8YFLogxK
U2 - 10.1016/j.neuroimage.2023.120082
DO - 10.1016/j.neuroimage.2023.120082
M3 - Article
C2 - 37030414
AN - SCOPUS:85152361375
SN - 1053-8119
VL - 273
SP - 1
EP - 9
JO - NeuroImage
JF - NeuroImage
M1 - 120082
ER -