Tom Froese’s research while affiliated with Okinawa Institute of Science and Technology Graduate University and other places

Habitual human behaviors shape nearly every aspect of life, from personal health and relationships to organizational success, disease transmission, and ecological sustainability. However, efforts to change behavior often fail to account for the complexity and multiscale nature of habit formation, leading to interventions that struggle to produce lasting effects. A persistent challenge is the intention-action gap, the discrepancy between what we intend to do and what we do in practice – an issue that traditional models of habit formation fail to fully explain. Here, we introduce the wayshaping framework, drawing on recent advances in cognitive science to emphasize the multiscale, complex and anticipatory nature of behavior. This framework makes three key contributions that significantly reframe how we understand and approach behavior change: (1) it reconceptualizes the individual as a multilevel, multiscale collective intelligence, offering a novel perspective on the organizing and developmental dynamics underlying habit formation; (2) it reinterprets the intention-action gap as a set of interdependent coordination challenges – non-linearity, alignment, and anticipation; and (3) it outlines principled skills for navigating these challenges and shaping habits in line with our intentions. By integrating insights from embodied cognitive science, complexity theory, behavior change research, and design, the wayshaping framework reframes individual habit change as a process of multiscale realignment. It thus provides a novel, unifying theoretical foundation for interdisciplinary research that has concrete and practical value in shaping sustainable behavior change.

Habitual human behaviors shape nearly every aspect of life, from personal health and relationships to organizational success, disease transmission, and ecological sustainability. However, efforts to change behavior often fail to account for the complexity and multiscale nature of habit formation, leading to interventions that struggle to produce lasting effects. A persistent challenge is the intention-action gap, the discrepancy between what we intend to do and what we do in practice – an issue that traditional models of habit formation fail to fully explain. Here, we introduce the wayshaping framework, drawing on recent advances in cognitive science to emphasize the multiscale, complex and anticipatory nature of behavior. This framework makes three key contributions that significantly reframe how we understand and approach behavior change: (1) it reconceptualizes the individual as a multilevel, multiscale collective intelligence, offering a novel perspective on the organizing and developmental dynamics underlying habit formation; (2) it reinterprets the intention-action gap as a set of interdependent coordination challenges – non-linearity, alignment, and anticipation; and (3) it outlines principled skills for navigating these challenges and shaping habits in line with our intentions. By integrating insights from embodied cognitive science, complexity theory, behavior change research, and design, the wayshaping framework reframes individual habit change as a process of multiscale realignment. It thus provides a novel, unifying theoretical foundation for interdisciplinary research that has concrete and practical value in shaping sustainable behavior change.

The Sense of Agency (SoA), the subjective feeling of controlling one’s actions and theirconsequences, has been explained through two primary theoretical frameworks: thecomparator model and retrospective views. While the comparator model focuses on theconsistency between the sensory prediction generated through internal models and theactual sensory input, retrospective theories emphasize the detection of regularitiesbetween one’s own actions and sensory input and self-attribution based on thisinformation. However, how the two types of processes contribute to the exploration ofcontrol remains unclear. In the present study, we explored this question by examining theeffect of updating the internal model for motor control on the SoA in a control detectiontask. Participants first adapted to a rotation of visual feedback while controlling a dot onthe screen, then conducted free movements to choose the dot they felt they could controlmost effectively among five dots with different rotation angles (i.e., the control detectiontask). Experiment 1 used a tracking task for the motor adaptation, while Experiment 2used a reaching task to replicate the result of Experiment 1. The results of the twoexperiments showed that the motor adaptation in both tasks did not have a significanteffect on the control detection task. In other words, it is likely that the updating of theinternal model only has a minimal effect on the control detection. Our findings indicatedthat the regularity detection process is likely to dominate in the exploration of the SoA,compared to the predictive process, which requires the internal model to generatepredictions for each movement. These findings provide important insights forunderstanding the sense of agency in the context of exploratory behaviors within the novelenvironments.

While psychologists have extensively discussed the notion of a “theory crisis” arising from vague and incorrect hypotheses, there has been no debate about such a crisis in biology. However, biologists have long discussed communication failures between theoreticians and empiricists. We argue such failure is one aspect of a theory crisis because misapplied and misunderstood theories lead to poor hypotheses and research waste. We review its solutions and compare them with methodology-focused solutions proposed for replication crises. We conclude by discussing how promoting inclusion, diversity, equity, and accessibility (IDEA) in theoretical biology could contribute to ameliorating breakdowns in the theory-empirical cycle.

Many organisms, ranging from modern humans to extinct species, exhibit movement patterns that can be described by Lévy walk dynamics. It has been demonstrated that such behavior enables optimal foraging when resource distribution is sparse. Here, we analyze a dataset of football player trajectories, recorded during the matches of the Japanese football league, to elucidate the presence of statistical signatures of Lévy walks, such as the heavy-tailed distribution of distances traveled between significant turns and the characteristic superdiffusive behavior. We conjecture that the competitive environment of a football game leads to bursty movement dynamics reminiscent of that observed in hunter-gathering populations and more broadly in any biological organisms foraging for resources, whose exact distribution is unknown to them. Apart from analyzing individual players’ movements, we investigate the dynamics of the whole team by studying the movements of its center of mass (team’s centroid). Remarkably, the trajectory of the centroid also exhibits Lévy walk properties, marking the first instance of such type of motion observed at the group level. Our work concludes with a comparative analysis of different teams and some discussion on the relevance of our findings to sports science and science more generally.

The Self-Optimization (SO) model can be considered as the third operational mode of the classical Hopfield Network (HN), leveraging the power of associative memory to enhance optimization performance. Moreover, is has been argued to express characteristics of minimal agency which, together with its biological plausibility, renders it useful for the study of artificial life. In this article, we draw attention to another facet of the SO model: its capacity for creativity. Drawing on the creativity studies literature, we argue that the model satisfies the necessary and sufficient conditions of a creative process. Moreover, we explore the dependency of different creative outcomes based on learning parameters, specifically the learning and reset rates. We conclude that the SO model allows for simulating and understanding the emergence of creative behaviors in artificial systems that learn.

Psilocybin is a classic psychedelic and a novel treatment for mood disorders. Psilocybin induces dose-dependent transient (4-6 hours) usually pleasant changes in perception, cognition, and emotion by non-selectively agonizing the 5-HT2A receptors and negatively regulating serotonin reuptake, and long-term positive antidepressant effect on mood and well-being. Long-term effects are ascribed to the psychological quality of the acute experience, increase in synaptodensity and temporary (1-week) down-regulation of 5-HT2A receptors. Electroencephalography, a non-invasive neuroimaging tool, can track the acute effects of psilocybin; these include the suppression of alpha activity, decreased global connectivity, and increased brain entropy (i.e. brain signal diversity) in eyes-closed resting-state. However, few studies investigated how these modalities are affected together through the psychedelic experience. The current research aimed to evaluate the psilocybin intoxication temporal EEG profile. 20 healthy individuals (10 women) underwent oral administration of psilocybin (0.26 mg/kg) as part of a placebo-controlled cross-over study, resting-state 5-minute eyes closed EEG was obtained at baseline and 1, 1.5, 3, 6, and 24 hours after psilocybin administration. Absolute power, relative power spectral density (PSD), power envelope global functional connectivity (GFC), Lempel-Ziv complexity (LZ), and a Complexity via State-Space Entropy Rate (CSER) were obtained together with measures of subjective intensity of experience. Absolute power decreased in alpha and beta band, but increased in delta and gamma frequencies. 24h later was observed a broadband decrease. The PSD showed a decrease in alpha occipitally between 1 and 3 hours and a decrease in beta frontally at 3 hours, but power spectra distribution stayed the same 24h later. The GFC showed decrease acutely at 1, 1.5, and 3 hours in the alpha band. LZ and showed an increase at 1 and 1.5 hours. Decomposition of CSER into functional bands shows a decrease in alpha band but increase over higher frequencies. Further, complexity over a source space showed opposing changes in the Default Mode Network (DMN) and visual network between conditions, suggesting a relationship between signal complexity, stimulus integration, and perception of self. In an exploratory attempt, we found that a change in gamma GFC in DMN correlates with oceanic boundlessness. Psychological effects of psilocybin may be wrapped in personal interpretations and history unrelated to underlying neurobiological changes, but changes to perception of self may be bound to perceived loss of boundary based on whole brain synchrony with the DMN in higher frequency bands.

Many organisms, ranging from modern humans to extinct species, exhibit movement patterns that can be described by lévy walk dynamics. It has been demonstrated that such behavior enables optimal foraging when resource distribution is sparse. In this paper, we study a dataset of football player trajectories, recorded during the matches of the Japanese football league to elucidate the presence of statistical signatures of lévy walks; such as the heavy-tailed distribution of distances traveled between significant turns and the characteristic superdiffusive behavior. We conjecture that the competitive environment of a football game leads to movement dynamics reminiscent of that observed in hunter-gathering populations and more broadly in any biological organisms foraging for resources, whose exact distribution is unknown to them. Apart from analyzing individual players’ movements, we investigate the dynamics of the whole team by studying the movements of its center of mass (team’s centroid). Remarkably, the trajectory of the centroid also exhibits Lévy walk properties, which implies the presence of team-level coordination. Our work concludes with a comparative analysis of different teams and some discussion on the relevance of our findings to sports science and science more generally.

It has been repeatedly reported that the collective dynamics of social insects exhibit universal emergent properties similar to other complex systems. In this note, we study a previously published data set in which the positions of thousands of honeybees in a hive are individually tracked over multiple days. The results show that the hive dynamics exhibit long-range spatial and temporal correlations in the occupancy density fluctuations, despite the characteristic short-range bees’ mutual interactions. The variations in the occupancy unveil a non-monotonic function between density and bees’ flow, reminiscent of the car traffic dynamic near a jamming transition at which the system performance is optimized to achieve the highest possible throughput. Overall, these results suggest that the beehive collective dynamics are self-adjusted towards a point near its optimal density.