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Nummenmaa L, Malèn T, Nazari-Farsani S, Seppälä K, Sun L, Santavirta S, Karlsson HK, Hudson M, Hirvonen J, Sams M, Scott S, Putkinen V. Decoding brain basis of laughter and crying in natural scenes. Neuroimage 2023; 273:120082. [PMID: 37030414 DOI: 10.1016/j.neuroimage.2023.120082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 03/08/2023] [Accepted: 03/31/2023] [Indexed: 04/08/2023] Open
Abstract
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 minutes of a full-length feature film, and iii) listened to 15 minutes 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.
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Neurobiological correlates and attenuated positive social intention attribution during laughter perception associated with degree of autistic traits. J Neural Transm (Vienna) 2023; 130:585-596. [PMID: 36808307 PMCID: PMC10049931 DOI: 10.1007/s00702-023-02599-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 02/03/2023] [Indexed: 02/21/2023]
Abstract
Laughter plays an important role in group formation, signaling social belongingness by indicating a positive or negative social intention towards the receiver. In adults without autism, the intention of laughter can be correctly differentiated without further contextual information. In autism spectrum disorder (ASD), however, differences in the perception and interpretation of social cues represent a key characteristic of the disorder. Studies suggest that these differences are associated with hypoactivation and altered connectivity among key nodes of the social perception network. How laughter, as a multimodal nonverbal social cue, is perceived and processed neurobiologically in association with autistic traits has not been assessed previously. We investigated differences in social intention attribution, neurobiological activation, and connectivity during audiovisual laughter perception in association with the degree of autistic traits in adults [N = 31, Mage (SD) = 30.7 (10.0) years, nfemale = 14]. An attenuated tendency to attribute positive social intention to laughter was found with increasing autistic traits. Neurobiologically, autistic trait scores were associated with decreased activation in the right inferior frontal cortex during laughter perception and with attenuated connectivity between the bilateral fusiform face area with bilateral inferior and lateral frontal, superior temporal, mid-cingulate and inferior parietal cortices. Results support hypoactivity and hypoconnectivity during social cue processing with increasing ASD symptoms between socioemotional face processing nodes and higher-order multimodal processing regions related to emotion identification and attribution of social intention. Furthermore, results reflect the importance of specifically including signals of positive social intention in future studies in ASD.
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Sivasathiaseelan H, Marshall CR, Benhamou E, van Leeuwen JEP, Bond RL, Russell LL, Greaves C, Moore KM, Hardy CJD, Frost C, Rohrer JD, Scott SK, Warren JD. Laughter as a paradigm of socio-emotional signal processing in dementia. Cortex 2021; 142:186-203. [PMID: 34273798 PMCID: PMC8438290 DOI: 10.1016/j.cortex.2021.05.020] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 04/01/2021] [Accepted: 05/21/2021] [Indexed: 11/03/2022]
Abstract
Laughter is a fundamental communicative signal in our relations with other people and is used to convey a diverse repertoire of social and emotional information. It is therefore potentially a useful probe of impaired socio-emotional signal processing in neurodegenerative diseases. Here we investigated the cognitive and affective processing of laughter in forty-seven patients representing all major syndromes of frontotemporal dementia, a disease spectrum characterised by severe socio-emotional dysfunction (twenty-two with behavioural variant frontotemporal dementia, twelve with semantic variant primary progressive aphasia, thirteen with nonfluent-agrammatic variant primary progressive aphasia), in relation to fifteen patients with typical amnestic Alzheimer's disease and twenty healthy age-matched individuals. We assessed cognitive labelling (identification) and valence rating (affective evaluation) of samples of spontaneous (mirthful and hostile) and volitional (posed) laughter versus two auditory control conditions (a synthetic laughter-like stimulus and spoken numbers). Neuroanatomical associations of laughter processing were assessed using voxel-based morphometry of patients' brain MR images. While all dementia syndromes were associated with impaired identification of laughter subtypes relative to healthy controls, this was significantly more severe overall in frontotemporal dementia than in Alzheimer's disease and particularly in the behavioural and semantic variants, which also showed abnormal affective evaluation of laughter. Over the patient cohort, laughter identification accuracy was correlated with measures of daily-life socio-emotional functioning. Certain striking syndromic signatures emerged, including enhanced liking for hostile laughter in behavioural variant frontotemporal dementia, impaired processing of synthetic laughter in the nonfluent-agrammatic variant (consistent with a generic complex auditory perceptual deficit) and enhanced liking for numbers ('numerophilia') in the semantic variant. Across the patient cohort, overall laughter identification accuracy correlated with regional grey matter in a core network encompassing inferior frontal and cingulo-insular cortices; and more specific correlates of laughter identification accuracy were delineated in cortical regions mediating affective disambiguation (identification of hostile and posed laughter in orbitofrontal cortex) and authenticity (social intent) decoding (identification of mirthful and posed laughter in anteromedial prefrontal cortex) (all p < .05 after correction for multiple voxel-wise comparisons over the whole brain). These findings reveal a rich diversity of cognitive and affective laughter phenotypes in canonical dementia syndromes and suggest that laughter is an informative probe of neural mechanisms underpinning socio-emotional dysfunction in neurodegenerative disease.
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Affiliation(s)
- Harri Sivasathiaseelan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.
| | - Charles R Marshall
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, United Kingdom
| | - Elia Benhamou
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Janneke E P van Leeuwen
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Rebecca L Bond
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Lucy L Russell
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Caroline Greaves
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Katrina M Moore
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Chris J D Hardy
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Chris Frost
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Department of Medical Statistics, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Jonathan D Rohrer
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sophie K Scott
- Institute of Cognitive Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Jason D Warren
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
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Avelino J, Garcia-Marques L, Ventura R, Bernardino A. Break the Ice: a Survey on Socially Aware Engagement for Human-Robot First Encounters. Int J Soc Robot 2021; 13:1851-1877. [PMID: 33437327 PMCID: PMC7792560 DOI: 10.1007/s12369-020-00720-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/26/2020] [Indexed: 11/24/2022]
Abstract
Society is starting to come up with exciting applications for social robots like butlers, coaches, and waiters. However, these robots face a challenging task: to meet people during a first encounter. This survey explores the literature that contributes to this task. We define a taxonomy based on psychology and sociology models: Kendon’s greeting model and Greenspan’s model of social competence. We use Kendon’s model as a framework to compare and analyze works that describe robotic systems that engage with people. To categorize individual skills, we use three components of Social Awareness that belong to Greenspan’s model: Social Sensitivity, Social Insight, and Communication. Under each section, we highlight some research gaps and propose research directions to address them. Through our analysis, we suggest significant research directions for enhanced first encounters. First, social scripts need to be evaluated under equal conditions. Second, interaction management and tracking for first encounters should consider state and observation uncertainties. Third, perception methods need lighter and robust integration in mobile platforms. Fourth, methods to explicitly define social norms are still scarce. Finally, research on social feedback and interaction recovery may fill the gaps of imperfect first encounters.
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Affiliation(s)
- João Avelino
- Institute for Systems and Robotics, Instituto Superior Técnico, University of Lisbon, Lisbon, Portugal
| | | | - Rodrigo Ventura
- Institute for Systems and Robotics, Instituto Superior Técnico, University of Lisbon, Lisbon, Portugal
| | - Alexandre Bernardino
- Institute for Systems and Robotics, Instituto Superior Técnico, University of Lisbon, Lisbon, Portugal
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Ethofer T, Stegmaier S, Koch K, Reinl M, Kreifelts B, Schwarz L, Erb M, Scheffler K, Wildgruber D. Are you laughing at me? Neural correlates of social intent attribution to auditory and visual laughter. Hum Brain Mapp 2019; 41:353-361. [PMID: 31642167 PMCID: PMC7268062 DOI: 10.1002/hbm.24806] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Revised: 08/30/2019] [Accepted: 09/15/2019] [Indexed: 01/17/2023] Open
Abstract
Laughter is a multifaceted signal, which can convey social acceptance facilitating social bonding as well as social rejection inflicting social pain. In the current study, we addressed the neural correlates of social intent attribution to auditory or visual laughter within an fMRI study to identify brain areas showing linear increases of activation with social intent ratings. Negative social intent attributions were associated with activation increases within the medial prefrontal cortex/anterior cingulate cortex (mPFC/ACC). Interestingly, negative social intent attributions of auditory laughter were represented more rostral than visual laughter within this area. Our findings corroborate the role of the mPFC/ACC as key node for processing “social pain” with distinct modality‐specific subregions. Other brain areas that showed an increase of activation included bilateral inferior frontal gyrus and right superior/middle temporal gyrus (STG/MTG) for visually presented laughter and bilateral STG for auditory presented laughter with no overlap across modalities. Similarly, positive social intent attributions were linked to hemodynamic responses within the right inferior parietal lobe and right middle frontal gyrus, but there was no overlap of activity for visual and auditory laughter. Our findings demonstrate that social intent attribution to auditory and visual laughter is located in neighboring, but spatially distinct neural structures.
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Affiliation(s)
- Thomas Ethofer
- Department of General Psychiatry, University of Tuebingen, Tuebingen, Germany.,Department of Biomedical Resonance, University of Tuebingen, Tuebingen, Germany
| | - Sophia Stegmaier
- Department of General Psychiatry, University of Tuebingen, Tuebingen, Germany
| | - Katharina Koch
- Department of General Psychiatry, University of Tuebingen, Tuebingen, Germany
| | - Maren Reinl
- Department of General Psychiatry, University of Tuebingen, Tuebingen, Germany
| | - Benjamin Kreifelts
- Department of General Psychiatry, University of Tuebingen, Tuebingen, Germany
| | - Lena Schwarz
- Department of General Psychiatry, University of Tuebingen, Tuebingen, Germany
| | - Michael Erb
- Department of Biomedical Resonance, University of Tuebingen, Tuebingen, Germany
| | - Klaus Scheffler
- Department of Biomedical Resonance, University of Tuebingen, Tuebingen, Germany.,Max-Planck-Institute for Biological Cybernetics, University of Tuebingen, Tuebingen, Germany
| | - Dirk Wildgruber
- Department of General Psychiatry, University of Tuebingen, Tuebingen, Germany
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