Abstract

Music sharing trends have been shown to change during times of socio-economic crises. Studies have also shown that music can act as a social surrogate, helping to significantly reduce loneliness by acting as an empathetic friend. We explored these phenomena through a novel study of online music sharing during the Covid-19 pandemic in India. We collected tweets from the popular social media platform Twitter during India’s first and second wave of the pandemic (n = 1,364). We examined the different ways in which music was able to accomplish the role of a social surrogate via analyzing tweet text using Natural Language Processing techniques. Additionally, we analyzed the emotional connotations of the music shared through the acoustic features and lyrical content and compared the results between pandemic and pre-pandemic times. It was observed that the role of music shifted to a more community focused function rather than tending to a more self-serving utility. Results demonstrated that people shared music during the Covid-19 pandemic which had lower valence and shared songs with topics that reflected turbulent times such as Hardship and Exclusion when compared to songs shared during pre-Covid times. The results are further discussed in the context of individualistic versus collectivistic cultures.

Abstract

It is our pleasure to welcome you to the 8th Annual Conference on Cognitive Science (ACCS8) held online and organized by the Amrita Mind Brain Center, Amrita Vishwa Vidyapeetham (Amrita University), Kerala India from January 20-22, 2022. Cognitive Science is an interdisciplinary domain that challenges researchers and scientists to examine cognitive processes and understand how the mind works, functions, and behaves. Given the interdisciplinary nature of cognitive science, The Government of India and the Department of Science and Technology had formed the Association for Cognitive Science (ACS) in 2013. In the last seven years, the ACS has been organizing an Annual Conference of Cognitive Science (ACCS) at some of the top universities in India including IIT Kanpur, IIT Gandhinagar, IIT Guwahati, IISc Bangalore, BITS Pilani Goa and University of Hyderabad. In the 2022 event organized by Amrita Vishwa Vidyapeetham, ACCS8 had 700 participants of which several of them were researchers or PhD students. The 30 oral and 61 poster presentations allowed 3 tracks of talks and 3 tracks of poster jam sessions. 2022’s ACCS has been graced by a wonderful array of 6 keynote speakers from various regions across the world. Prof. Nandini Chatterjee Singh from UNESCO MGIEP (India) talked on Game-based courses for learning – results of an online digital game-based course to build social and emotional skills in adolescents. Prof. Claudia Gandini Wheeler-Kingshott of University College London (UK) addressed on Principles of quantitative magnetic resonance imaging and relevance to clinical applications. Prof. Kenji Doya of Okinawa Institute of Science and Technology (Japan) spoke on Neural Circuits for Mental Simulation. Prof. Egidio D’Angelo of University Pavia (Italy) addressed Bottom-up and top-down strategies for multiscale brain modelling. Prof. Ned Block of New York University (USA) spoke on an empirical argument that perception is non-conceptual. Prof. Bhavani Rao R of Amrita University (India) addressed on “Humane” Computer Interaction – The role of HCI in facilitating social and vocational empowerment.

Abstract

Functional connectivity derived from functional MRI reflects the neuronal synchronization between brain regions anchored through an anatomical infrastructure of white matter pathways that can be computed from diffusion MRI. The inter-relation between the structure-function topography is of high interest in

Abstract

Predicting Individual Differences from Brain Responses to Music using Functional Network Centrality

Abstract

Music sharing trends have been shown to change during times of socio-economic crises. Studies have also shown that music can act as a social surrogate, helping to significantly reduce loneliness by acting as an empathetic friend. We explored these phenomena through a novel study of online music sharing during the Covid-19 pandemic in India. We collected tweets from the popular social media platform Twitter during India’s first and second wave of the pandemic (n = 1,364). We examined the different ways in which music was able to accomplish the role of a social surrogate via analyzing tweet text using Natural Language Processing techniques. Additionally, we analyzed the emotional connotations of the music shared through the acoustic features and lyrical content and compared the results between pandemic and pre-pandemic times. It was observed that the role of music shifted to a more community focused function rather than tending to a more self-serving utility. Results demonstrated that people shared music during the Covid-19 pandemic which had lower valence and shared songs with topics that reflected turbulent times such as Hardship and Exclusion when compared to songs shared during pre-Covid times. The results are further discussed in the context of individualistic versus collectivistic cultures.

Abstract

Reading, much like music listening, is an immersive experience that transports readers while taking them on an emotional journey. Listening to complementary music has the potential to amplify the reading experience, especially when the music is stylistically cohesive and emotionally relevant. In this paper, we propose the first fully automatic method to build a dense soundtrack for books, which can play high-quality instrumental music for the entirety of the reading duration. Our work employs a unique text processing and music weaving pipeline that determines the context and emotional composition of scenes in a chapter. This allows our method to identify and play relevant excerpts from the soundtrack of the book’s movie adaptation. By relying on the movie composer’s craftsmanship, our book soundtracks include expert-made motifs and other scene-specific musical characteristics. We validate the design decisions of our approach through a perceptual study. Our readers note that the book soundtrack greatly enhanced their reading experience, due to high immersiveness granted via uninterrupted and style-consistent music, and a heightened emotional state attained via high precision emotion and scene context recognition.

Abstract

Movement is a universal response to music, with dance often taking place in social settings. Although previous work has suggested that socially relevant information, such as personality and gender, are encoded in dance movement, the generalizability of previous work is limited. The current study aims to decode dancers’ gender, personality traits, and music preference from music‑induced movements. We propose a method that predicts such individual difference from free dance movements, and demonstrate the robustness of the proposed method by using two data sets collected using different musical stimuli. In addition, we introduce a novel measure to explore the relative importance of different joints in predicting individual differences. Results demonstrated near perfect classification of gender, and notably high prediction of personality and music preferences. Furthermore, learned models demonstrated generalizability across datasets highlighting the importance of certain joints in intrinsic movement patterns specific to individual differences. Results further support theories of embodied music cognition and the role of bodily movement in musical experiences by demonstrating the influence of gender, personality, and music preferences on embodied responses to heard music.

Abstract

The experience often described as feeling moved, understood chiefly as a social-relational emotion with social bonding functions, has gained significant research interest in recent years. Although listening to music often evokes what people describe as feeling moved, very little is known about the appraisals or musical features contributing to the experience. In the present study, we investigated experiences of feeling moved in response to music using a continuous rating paradigm. A total of 415 US participants completed an online experiment where they listened to seven moving musical excerpts and rated their experience while listening. Each excerpt was randomly coupled with one of seven rating scales (perceived sadness, perceived joy, feeling moved or touched, sense of connection, perceived beauty, warmth [in the chest], or chills) for each participant. The results revealed that musically evoked experiences of feeling moved are associated with a similar pattern of appraisals, physiological sensations, and trait correlations as feeling moved by videos depicting social scenarios (found in previous studies). Feeling moved or touched by both sadly and joyfully moving music was associated with experiencing a sense of connection and perceiving joy in the music, while perceived sadness was associated with feeling moved or touched only in the case of sadly moving music. Acoustic features related to arousal contributed to feeling moved only in the case of joyfully moving music. Finally, trait empathic concern was positively associated with feeling moved or touched by music. These findings support the role of social cognitive and empathic processes in music listening, and highlight the social-relational aspects of feeling moved or touched by music.

Abstract

Music listening is a great resource for mental well-being, pleasure, and self-regulation, but it may also be maladaptive. Depression, for instance, has been shown to relate to music use that is characterized by rumination, avoidance, and mood worsening. However, we know little of the role of individual differences in such maladaptive music use. Hence, this study focused on examining the role of personality, empathic traits, emotional contagion, and the types of musical reward as predictors of maladaptive music listening. Participants (N=318) answered an online survey comprising measures for the abovementioned traits in addition to the Healthy-Unhealthy Music Scale (HUMS) as a measure of maladaptive music use. Results demonstrated that Unhealthy musical engagement was predicted by a variety of traits representing general negative emotionality (e.g., Neuroticism, Personal Distress, contagion for negative emotions). Structural equation modeling highlighted the importance of the empathic trait Personal Distress in mediating Unhealthy musical engagement. Finally, we deliberate if maladaptive strategies are indeed “maladaptive” for such individuals or merely a coping mechanism, which is indeed adaptive for them, aiding to combat depressive and anxious states thereby preventing them from “tipping over” into depression.

Abstract

This chapter provides a behind-the-scenes account of the birth of a naturalistic approach to the neuroscience of the musical aesthetic experience. The story starts from a lab talk giving the inspiration to translate the naturalistic paradigm initially applied to neuroimaging studies of the visual domain into music research. The circumstantial co-presence of neuroscientists and computational musicologists at the same center did the trick, permitting the identification of controlled variables for brain signal processing from the automatic extraction of the acoustic features of real music. This approach is now well accepted by the music neuroscience community while still waiting for full exploitation by aesthetic research.