Periodic Reporting for period 1 - JAL (Uncovering the Behavioural and Neural Correlates of Joint Action Learning)
Reporting period: 2020-09-01 to 2022-08-31
The ability to predict the timing of a partner’s actions is critical to performing joint actions such as team sports and group music-making. People can be remarkably good at predicting one another’s actions: Expert musicians, for example, can predict with millisecond accuracy when a partner will produce a tone. Although much work has investigated mechanisms of joint action, the processes by partners learn to coordinate timing are not clearly understood. The overarching aim of JAL was to investigate the behavioural and neural mechanisms by which joint action partners learn to achieve temporal coordination. Neural measurement was not possible due to COVID-19, so the implemented action focused exclusively on behaviour. To this end, JAL developed two empirical paradigms for capturing joint action learning processes in a laboratory setting, one for assessing how partners learn to take discrete turns, and one for assessing how partners learn to produce synchronous continuous actions. Overall findings suggest two distinct behavioural mechanisms of joint action learning: 1) Spontaneous emergence of rhythmicity as a means of scaffolding coordination when learning to take turns, 2) Utilization of sensory feedback associated a partner’s actions when learning to produce synchronous continuous movements. Taken together, JAL paves the way for understanding joint action learning, and provides an effective empirical framework that can be used by future researchers for capturing joint action learning processes.
JAL was implemented from Sep 1 2020 to Aug 31 2021. COVID-19 was ongoing throughout the period when JAL was active, so all research conducted focused exclusively on behavioural mechanisms of joint action learning. Two work packages (WPs) were implemented:
The first WP (WP1) developed and validated a paradigm for capturing joint action learning, using musical turn-taking as a model of joint action. In this paradigm, musical novices produced auditory tone sequences alone or in alternation with a partner. Findings revealed unique features of joint action learning: Specifically, partners imposed rhythmic patterns onto action sequences during joint learning that reflected the turn-taking structure; in contrast, individuals did not impose rhythmic patterns onto sequences when learning alone. Together, findings point towards the emergence of spontaneous rhythmicity as a unique feature of learning to produce turn-taking sequences, consistent with the view that rhythm may have evolved to scaffold social motor coordination. Findings can be exploited by dynamical systems models of how rhythms emerge during coordinated group actions. Findings from WP1 have been disseminated through presentation at an international conference [1], and through a manuscript preprint that has been posted on an Open Access repository [2] and submitted to an Open Access scientific journal.
The second WP (WP2) developed and validated an empirical paradigm for capturing how partners learn to coordinate synchronous continuous movements, in contrast with the discrete turn-taking actions investigated in WP1. Partners in the WP2 paradigm learned to synchronize continuous rhythmic movements by aligning continuous sounds produced by their actions. The paradigm was validated in a laboratory study that assessed how prediction of a partner is influenced by access to sensory information produced by their actions during learning. Preliminary findings revealed that partners learned to synchronize at above-chance levels, and that prediction was indeed modulated by sensory information. Specifically, partners predicted one another most accurately (displayed optimal synchrony) when both could hear one another during learning; when only one partner could hear the other that partner tended to proceed (anticipate) the other’s movements. Together, these findings are consistent with prior work on discrete joint action coordination, which indicates that bidirectional sensory feedback facilitates synchrony; findings are also consistent with work indicating that individuals anticipate the timing of non-adaptive rhythmic signals (e.g. auditory metronomes). Findings can be exploited in future work directly comparing learning mechanisms associated with discrete and continuous joint action learning. Preliminary findings from WP2 have been reported in Master’s thesis [3], and will be submitted for presentation at international conferences and to a scientific journal after analyses are finalized.
References
1. Zamm, A., S. Debener, and N. Sebanz. Distinct rhythms of joint and individual action: Evidence from an auditory sequence production paradigm. in Proceedings of the Annual Meeting of the Cognitive Science Society. 2021.
2. Zamm, A., S. Debener, and N. Sebanz, Learning to take turns together: The spontaneous emergence of rhythmic coordination. 2021.
3. Leeb, C., Match me if you can: Continuous dynamics of learning to coordinate auditory-motor rhythms with a partner, in Middle European interdisciplinary Master's Programme in Cognitive Science. 2021, Master's Thesis, University of Vienna: Vienna.
4. Kotz, S.A. A. Ravignani, and W.T. Fitch, The evolution of rhythm processing. Trends in cognitive sciences, 2018. 22(10): p. 896-910.
The first WP (WP1) developed and validated a paradigm for capturing joint action learning, using musical turn-taking as a model of joint action. In this paradigm, musical novices produced auditory tone sequences alone or in alternation with a partner. Findings revealed unique features of joint action learning: Specifically, partners imposed rhythmic patterns onto action sequences during joint learning that reflected the turn-taking structure; in contrast, individuals did not impose rhythmic patterns onto sequences when learning alone. Together, findings point towards the emergence of spontaneous rhythmicity as a unique feature of learning to produce turn-taking sequences, consistent with the view that rhythm may have evolved to scaffold social motor coordination. Findings can be exploited by dynamical systems models of how rhythms emerge during coordinated group actions. Findings from WP1 have been disseminated through presentation at an international conference [1], and through a manuscript preprint that has been posted on an Open Access repository [2] and submitted to an Open Access scientific journal.
The second WP (WP2) developed and validated an empirical paradigm for capturing how partners learn to coordinate synchronous continuous movements, in contrast with the discrete turn-taking actions investigated in WP1. Partners in the WP2 paradigm learned to synchronize continuous rhythmic movements by aligning continuous sounds produced by their actions. The paradigm was validated in a laboratory study that assessed how prediction of a partner is influenced by access to sensory information produced by their actions during learning. Preliminary findings revealed that partners learned to synchronize at above-chance levels, and that prediction was indeed modulated by sensory information. Specifically, partners predicted one another most accurately (displayed optimal synchrony) when both could hear one another during learning; when only one partner could hear the other that partner tended to proceed (anticipate) the other’s movements. Together, these findings are consistent with prior work on discrete joint action coordination, which indicates that bidirectional sensory feedback facilitates synchrony; findings are also consistent with work indicating that individuals anticipate the timing of non-adaptive rhythmic signals (e.g. auditory metronomes). Findings can be exploited in future work directly comparing learning mechanisms associated with discrete and continuous joint action learning. Preliminary findings from WP2 have been reported in Master’s thesis [3], and will be submitted for presentation at international conferences and to a scientific journal after analyses are finalized.
References
1. Zamm, A., S. Debener, and N. Sebanz. Distinct rhythms of joint and individual action: Evidence from an auditory sequence production paradigm. in Proceedings of the Annual Meeting of the Cognitive Science Society. 2021.
2. Zamm, A., S. Debener, and N. Sebanz, Learning to take turns together: The spontaneous emergence of rhythmic coordination. 2021.
3. Leeb, C., Match me if you can: Continuous dynamics of learning to coordinate auditory-motor rhythms with a partner, in Middle European interdisciplinary Master's Programme in Cognitive Science. 2021, Master's Thesis, University of Vienna: Vienna.
4. Kotz, S.A. A. Ravignani, and W.T. Fitch, The evolution of rhythm processing. Trends in cognitive sciences, 2018. 22(10): p. 896-910.
Taken together, JAL developed new empirical paradigms for measuring how people learn to perform two ubiquitous forms of joint action: turn-taking (WP1) and synchronous motion (WP2). These paradigms allow for investigating the relatively uncharted territory of joint action learning, and for assessing how joint action learning may differ from individual action learning. One important question that can be addressed with the paradigms developed by JAL is whether dyads and groups can learn to coordinate with the efficacy of a single individual, thereby forming a “joint motor system.” This question can be easily addressed through controlled laboratory studies using JAL paradigms, particularly in collaboration with computational modelers who can use findings from JAL paradigms to build mathematical models predicting how individuals versus groups learn to coordinate.
JAL’s empirical findings, particularly from WP1, suggest that there are indeed differences between individual and joint action learning and point towards the emergence of rhythm as a specific tool for learning to coordinate actions with others. This key insight not only makes a direct impact on the field of evolutionary social cognition – by providing evidence for the hypothesis that rhythm’s evolutionary purpose is to facilitate social coordination [4] – but will also hopefully inspire future work further investigating how rhythm facilitates cohesive group coordination.
References
Kotz, S.A. A. Ravignani, and W.T. Fitch, The evolution of rhythm processing. Trends in cognitive sciences, 2018. 22(10): p. 896-910.
JAL’s empirical findings, particularly from WP1, suggest that there are indeed differences between individual and joint action learning and point towards the emergence of rhythm as a specific tool for learning to coordinate actions with others. This key insight not only makes a direct impact on the field of evolutionary social cognition – by providing evidence for the hypothesis that rhythm’s evolutionary purpose is to facilitate social coordination [4] – but will also hopefully inspire future work further investigating how rhythm facilitates cohesive group coordination.
References
Kotz, S.A. A. Ravignani, and W.T. Fitch, The evolution of rhythm processing. Trends in cognitive sciences, 2018. 22(10): p. 896-910.