Performance Neuroscience for the Public Good

The Flow Research Collective is a nonprofit research institute studying the states of consciousness that govern human performance, mental health, and adaptive capacity. Our work spans flow, intuition, purpose, resilience, and other optimal states.

We focus on how these states emerge, how they function in the brain and body, and how they shape behavior under pressure. We conduct foundational and applied research across neuroscience, psychology, and physiology, working with elite populations—including military, first responders, athletes, and high performers—while developing models and methods that scale to the general public.

This research also extends into emerging domains, including the downstream challenges introduced by artificial intelligence and other advanced technologies.

COLLABORATORS

Our scientific collaborators span a network of labs working at the intersection of neuroscience, psychology, philosophy, cognitive science, and complex systems.

At UC Davis, we partner with Richard Huskey, whose group studies the cognitive neuroscience of flow, attention, and the mechanisms underlying peak performance.

At University of Montreal, Guillaume Dumas brings expertise in hyperscanning, interpersonal synchrony, and the neural dynamics of social coordination.

Karl Friston at University College London provides a theoretical backbone, linking our empirical work to predictive processing, free-energy minimization, and the mathematics of dynamical brain states.

Scott Kelso at the Center for Complex Systems and Brain Sciences at Florida Atlantic University contributes decades of foundational work on coordination dynamics and metastability, grounding our ideas about flow and intuition in physical law and nonlinear systems.

Marcelo Bigliassi at FIU anchors the applied side, using EEG and psychophysiology in real-world performance tasks—from cycling to task-absorption—to test whether hypothesized flow signatures show up in behavior and brain connectivity.

Together, this network integrates theory, imaging, computation, and real-world measurement into a single pipeline.

RECENT WORK
RECENT WORK
RECENT WORK
RECENT WORK
RECENT WORK
RECENT WORK
RECENT WORK
RECENT WORK
PUBLISHED

A comprehensive proposal of the neurobiology and neurodynamics of state onset

With Center for Edge at Deloitte we worked to quantify the relationship between flow and Deloitte’s metrics for employee engagement.

The Flow Research Collective taught 17 adults aged 30-68 how to perform park skiing/snowboarding tricks over 4 days. Participants made significant progress learning the tricks, experienced increased flow states, and had more positive attitudes about learning new skills later in life.

IN PRESS / IN PREP

An interdisciplinary book defining the new field of performance neuroscience—linking psychophysiology, cognitive control, brain dynamics, flow, recovery, sports, arts, meditation, and future AI applications—with chapters from leading researchers. A Complexity-Science Framework for Studying Flow: Using Media to Probe Brain–Phenomenology Dynamics Introduces a complexity-science model and experimental paradigm for studying how media stimuli drive shifts in attention, absorption, and subjective flow-like states.

Argues against the popular “stored trauma in the body” metaphor and reframes PTSD as a collapse of neural metastability—over-precision of threat priors—and suggests restoration through adaptive prediction and flow-rich interventions.

Studies whether spirituality, belief in a higher power, and religious rituals predict performance and flow across different levels of athletic risk and gender.

Proposes that consciousness isn’t a fundamental property of matter but an emergent informational phenomenon that arises when neural dynamics cross a metastable coordination threshold.

Presents a unified dynamical model showing that purpose, synchronicity, and flow are temporal expressions of the same metastable attractor dynamics, linking meaning to predictive processing and active inference.

Develops a mathematical framework for modeling moral reasoning as metastable attractor dynamics and proposes a JEPA-based architecture for AI systems that minimize “moral free-energy” in real-time decisions.

Shows how Zen koans deliberately overload predictive processing, triggering cognitive collapse into awe and then reorganizing into effortless flow as the brain resets its generative model.

Argues that between-set smartphone checking satisfies short-term prediction-error relief but collapses the metastable brain dynamics needed for flow, conditioning intolerance of uncertainty and undermining both physical adaptation and mental health benefits of exercise.

Discover more about peak performance.

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Flow research collective
Flow research collective
Flow research collective
Flow research collective
Flow research collective
Flow research collective
Flow research collective
Flow research collective

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