Synch.Live: Collective problem-solving through flocking motion associated with higher connectedness to others

Journal article

Background: Collective self-organising behaviour is ubiquitous in nature, whereby complex patterns emerge from the local interactions between individuals. Yet in humans, most group behaviour is attributed to explicit central control or pre-planning, rather than to the synergistic decentralised interplay between individuals. Purpose: This paper introduces Synch.Live, a novel experimental paradigm for quantitatively studying collective motion in humans, framed as a game with an unspecified task and a group feedback mechanism that can be solved through cooperation by 10 participants walking together. We also present the results of a pilot study demonstrating its use. Study sample: 10 partitipants took part in each trial, forming 16 independent groups. Data collection and/or Analysis: We collected psychometrics, behavioural and trahectory data in order to explore the participants’ state of mind and the strategies they developed collectively to solve the group challenge. Results: We found that more than half of the groups participating in the study self-organised to achieve collective flocking motion, and winning players showed higher connectedness to others compared to those who failed. Furthermore, individuals with an awareness of working strategies were more likely to be part of winning groups, suggesting the importance of individual contributions to the collective task. Conclusion: This work demonstrates that solving an unspecified group challenge in response to group feedback is possible, and moreover, that flock-like collective movement has the potential to yield social benefits and well-being, suggesting new directions for exploring social aspects of consciousness and cognition.

Authors: Sas, MI; Mediano, PA; Rosas, FE; Leone, H; Sas, A

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: SAGE Publications
• Journal: Collective Intelligence
• Volume: 5
• Issue: 2
• Article number: 26339137261435117
• Publication date: 2026-04-22
• Acceptance date: 2026-02-11
• DOI: 10.1177/26339137261435117
• EISSN: 2633-9137
• ISSN: 2633-9137
• Language: English
• Keywords: social well-being; cognitive psychology; collective motion; flocking; consciousness; problem-solving; community; technology; behavioural science; collective intelligence