Kazuo Okanoya

High-throughput tracking yields rich time-series data of animal behaviour, yet extracting biological insight remains a bottleneck, even for simple control– treatment comparisons. Existing analyses struggle to pinpoint the multiple, nonlinearly intertwined differences hidden in the data and fail to generalise across diverse recording set-ups. Here we present DiverScan, a deep-learning framework for attention-guided exploratory analysis of behavioural time series. DiverScan disentangles condition-dependent behavioural differences by pairing a loss function tailored to data exploration with an attention-branch architecture, and highlights condition-specific behavioural features visually and with explanatory text generated by a large language model. DiverScan is validated on a synthetic benchmark and on datasets from seven laboratories spanning multiple species and both single- and multi-animal behaviour. Beyond recovering known phenotypes, we demonstrate that DiverScan helps researchers generate new hypotheses across these diverse datasets. Available as Jupyter notebooks with a graphical user interface and flexible input formats, DiverScan can integrate into existing behavioural-analysis pipelines.

All languages have statistically coherent subsequences (e.g., words) whose frequency distribution follows a power law. These properties facilitate language learning in humans, making them good candidates for arising through cultural transmission as a way to help faithful transmission across generations. Recently, both properties were found in whale song, which is also culturally transmitted, leading to the strong prediction that they should be found wherever complex sequential signaling is culturally transmitted. Here, we use the same tools used to analyze human data and whale song to reveal that culturally transmitted Bengalese finch song also has statistically coherent subsequences whose distribution follows a power law. We additionally show that statistical coherence increases over development, but the power law is present throughout, suggesting that it reflects a fundamental principle of learned representations. Finding these parallels between evolutionarily distant species illustrates the importance of cultural transmission in shaping communication and suggests that core properties of language arise through convergent evolution.

In this concluding chapter, we focus on outlining the next frontier in research on rhythm cognition and rhythmic communication (RCC), synthesising conceptual, methodological, comparative, and applied directions, as they emerge from the contributions to the Nature Beats volume . While consensus has grown regarding the composite nature of rhythmic competence and the need for integrated quantitative approaches, the field remains marked by conceptual heterogeneity and inconsistent operational criteria. To advance RCC research, the chapter identifies pressing needs for conceptual clarity, methodological standardisation, and ecologically grounded definitions of rhythmic phenomena across modalities and species. We also highlight future research trajectories for major theoretical frameworks, including the Vocal Learning–Beat Perception and Synchronisation hypothesis, Gradual Audiomotor Evolution hypothesis, Neural Resonance Theory, socio-ecological hypotheses of synchrony, and evolutionary accounts linking rhythm to social bonding and stress regulation. A bottom-up, species-specific, and comparative approach is advocated to capture the full structural and functional diversity of RCC and to evaluate mechanisms spanning neural oscillations and functional connectivity, biomechanics, development, reward systems, and environmental constraints. Finally, the chapter emphasises the translational value of RCC research. Rhythm-based interventions hold promise for educational, clinical, welfare, conservation, and human-animal interaction contexts. By integrating mechanistic, evolutionary, and applied perspectives, future research can uncover the biological principles underlying rhythmic behaviour and its central role in communication, cognition, and sociality across the animal kingdom.

The issue addressed in this peer commentary chapter is a rather narrow one. Across the great diversity of animal rhythmic behaviours, which are the ones that might be related by either homology (i.e. by common descent) or analogy (i.e. by convergent evolution) to our capacity for precise and sustained group synchrony such as it occurs in human music, dance, and drill? Candidate species to fill such a role, whether by homology or analogy, would help us understand biological aspects, if any, of the nature and origin of the human capacity. Recent decades have seen an upsurge in proposals regarding species that may fill this role, but so far none of them have achieved consensus status regarding their relevance to our understanding of the human capacity. As a step toward resolving some of the outstanding issues, a number of colleagues were invited to comment on the treatment of the comparative study of musical rhythmicity I present in this chapter. Their commentaries and my response follow that treatment. Though one peer commentary exercise of this kind can hardly be expected to settle the many technical and programmatic issues involved, in the setting of the broader treatment of rhythmicity afforded by this volume, it can nevertheless help delineate conceptual and empirical matters that deserve further close scrutiny.