Dale Zhou
Hewitt Postdoctoral Research Fellow
University of California, Irvine
I am a cognitive neuroscientist working with Aaron Bornstein and Mike Yassa. My PhD at the University of Pennsylvania, supervised by Dani Bassett and Ted Satterthwaite, focused on network models of brain and behavior dynamics.
We constantly search for what matters and rediscover what is possible. Exactly what to aim for is rarely a clear target projected in high-definition within our minds, but more often a soupy mixture of values, gists, and mental models shaped by our interactions with the world. With the pursuit of multi-dimensional goals comes a blurry mishmash of experiences. We sometimes turn to a magnifying lens, inevitably revealing hidden patterns and unexpectedly sprawling cracks beneath the surface. Other times we drift aimlessly, open to raw, random, and rival discoveries along the way which expand our world, illuminating invisible tapestries resistant to easy categorization. How do we distill a mishmash of experiences back into a beautiful soup of what matters?
To address this question, I develop models of compression, curiosity, and cognitive control, by applying methods from network science, dynamical systems theory, and artificial intelligence to behavioral experiments, naturalistic behavior in everyday contexts, and neuroimaging tasks. I am particularly interested in problems at the intersection of cognition, philosophy, and mental health.
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University of Maryland, College Park
National Institute of Mental Health
Too much
Dale moved from Atlanta, GA to Bethesda, MD as a child, blowing his chance at becoming a true southern gentleman. As consolation, he was awarded dual degrees and 3rd place in a campus-wide table tennis tournament by the University of Maryland. Weighing his prospects as a professional athlete, he decided to train at the National Institute of Mental Health in neuroscience. On occasion, Dale tried to escape his ever-northward destiny. One summer, he reportedly biked west across the U.S., pedaling from Maryland to Oregon to help fight cancer. But his efforts proved fruitless; Dale moved north again to Philadelphia and joined Penn's Neuroscience Graduate Group. He yearns to one day search for research positions in all cardinal directions. Outside of lab, Dale enjoys reading, music, art, gaming, hiking, and maintaining lists of exciting future hobbies.
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Information compression, relevance, and novelty detection
How do we distill raw information into what is most relevant for current goals? Attentional templates and memory schemas are thought to filter relevant from irrelevant information, but it is unclear what computations support their form and function. I argue that lossy compression is an optimization process that determines what is relevant by constructing compact representations which strategically discard redundant details while retaining essential properties for a given task. For example, a field mushroom and a destroying angel both look pale and unassuming, with domed caps and slender stalks, but one feeds while the other poisons. Many exploration and decision models assume a perfect ability to pattern separate novel and familiar encounters with a field mushroom or a destroying angel. However, I hypothesize that imperfect memory is not only more realistic but is a function of a lossy compression process that discards less relevant information. Lossy compression is not merely a strategy for energy efficiency or minimizing resource costs; it also implements a computation for relevance, selectively preserving information that is most useful for downstream goals.
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A compressed code for memory discrimination
(Submitted)
Dale Zhou,
Sharon Mina Noh,
Nora Harhen,
Nidhi Banavar,
Brock Kirwan,
Michael Yassa,
Aaron Bornstein,
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This work presents a novel computational framework and supporting human empirical evidence (behavioral and neural) that the brain discriminates memories not by expanding representational space, as long assumed, but by compressing it. The ability to tell whether an experience is new or familiar lies at the core of perception and memory. For decades, theories of memory discrimination have rested on the Marr-Albus principle of dimensionality expansion, instantiated by an expanded encoding ensemble (i.e. expanded dimensionality) and a sparse firing code. Our work provides behavioral, computational, and neural evidence that dimensionality reduction, not expansion, underlies the capacity to tell similar experiences apart. We show that neural activity in the hippocampus and neocortex reflects this compaction of representational space. Beyond resolving a long-standing paradox in memory theory, our results have broad implications. They link efficient coding in the brain to modern machine learning and computer vision architectures, connect compression to changes in memory systems with development and aging, and provide a computational link between perceptual categorization, novelty detection, and one-shot episodic encoding. The concept that selective information loss can improve memory discrimination reframes how we understand the adaptive nature of memory, and opens a path towards unified theories of biological and artificial intelligence.
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Efficient coding in the economics of human brain connectomics
Network Neuroscience
Dale Zhou,
Christopher Lynn,
Zaixu Cui,
Rastko Ciric,
Graham Baum,
Tyler Moore,
David Roalf,
John Detre,
Ruben Gur,
Raquel Gur,
Theodore Satterthwaite,
Dani Bassett
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How do we distill a "blooming, buzzing confusion" into what matters? Information compression is an optimization process that determines what is relevant by constructing compact representations which strategically discard redundant details while retaining essential properties for a given task. For example, image compression optimizes for efficient storage by removing visual details imperceptible to humans. Compression has been hypothesized across perception, memory, learning, attention, decision-making, social cognition, and emotion, but its neural bases are not understood. I developed a dynamical systems theory explaining that brain regions better compress inputs when embedded in highly connected, recurrent anatomical networks, letting signals circulate more efficiently so fewer signals are needed. Our framework adapts the mathematics of information theory to understand the limits of sending and receiving packets of information with individually varying speed and reliability across white matter pathways of differing integrity. Longer pathways distort information flow, so brain regions with higher transmission fidelity send and receive packets with greater rate and reliability as a function of network topology prioritizing shortest paths. Our model parsimoniously explains communication as a function of network complexity, how highly connected hub regions integrate information, and the speed and accuracy of behavior.
Conference abstract at Organization of Human Brain Mapping 2020
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Cognitive control, executive function, and psychopathology
There is an enormous gulf between the instrumental goals we typically study and the hopes, dreams, and wishes that we seek to give life meaning. Even the worries and doubts we may naturally wish to avoid can be guides, signaling where attention, control, and reflection are most needed. What are goals, how are they represented, and how do they come into conflict? I puzzle over the form and function of goals using control theory at the behavioral and neural levels. At the neural unit, I am interested in how the explicit mathematical framework of dynamic and distributed signal propagation lays bare the strangeness of pairing a biological control function with beliefs about willpower, societal power structures, and the "right" kinds of goals. At the computational unit, I use reinforcement learning in complex environments to model pursuit of dynamic constellations of goals and motivations. These approaches can improve the coherence between biological models of psychiatric disease and the experience of mental illness.
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Neural dynamics underlying the persistence of perseverative thought in depression and anxiety
(Submitted)
Dale Zhou,
Jeesung Ahn,
David Lydon-Staley,
Emily Falk,
Dani Bassett,
Ayelet Meron Ruscio
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"Being stuck in a hole" is a clinical metaphor that is used to convey the pull of perseverative thought in depression and anxiety. The current paper makes this clinical metaphor for uncontrollable negative thinking more concrete through the mathematical frameworks of dynamical systems and control theory. The persistent, "sticky" quality of perseverative thought may emerge from brain activity that evolves in a low-energy attractor basin that is easy to enter and stay within, but difficult to leave. In perseverative thought, especially rumination, deepened attractors are associated with persistent neural activity and heightened symptom severity. The pull of these attractors could help explain why depressed and anxious individuals must exert so much effort to disengage from negative thoughts.
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Mindful attention promotes control of brain network dynamics for self-regulation and discontinues the past from the present
Proceedings of the National Academy of Sciences
Dale Zhou,
Yoona Kang,
Danielle Cosme,
Mia Jovanova,
Xiaosong He,
Arun Mahadevan,
Jeesung Ahn,
Ovidia Stanoi,
Julia Brynildsen,
Nicole Cooper,
Eli Cornblath,
Linden Parkes,
Peter Mucha,
Kevin Ochsner,
David Lydon-Staley,
Emily Falk,
Dani Bassett
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Practitioners of mindfulness effortfully de-automatize habitual reactions and center the present moment. We investigated how to understand these defining components of mindful experience using formal theory and associated computational metrics of brain network structure and function. In an experiment, we instructed college students to mindfully regulate their responses to alcohol in an fMRI scanner. Analyzing their neural activity, we identified changes in brain function during mindfulness. These changes in brain function characterize how individuals exert effort to de-automatize natural reactions to alcohol. We found associated brain metrics that predicted how likely college students were to drink alcohol in the future. Analyzing how their brain activity naturally changes over time, we found that brain regions that used more effort tended to renew activity more quickly. Since renewing activity is updating the present, the brain may center the present moment when it uses more effort. Our findings advance our understanding of brain network processes that characterize elusive subjective experiences during mindfulness. The general framework can be applied to study other forms of meditation and attention, and when processes of attention go awry in psychiatric disorders involving worry, anxiety, and rumination.
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Curiosity, open-ended search, and information foraging
Curiosity is an intrinsic motivation to seek information that can kindle creativity, magnify attention, continue learning, and maximize reward. However, in addition to these welcome ends, curiosity also blooms endlessly. Unpredictable changes in individuals and environments motivate a more random curiosity that can be as peculiar, patient, and playful as it is sensible, urgent, and rational. I treat curiosity as an open-ended search and discovery process that is rooted in foraging patterns and the need to detect and remember novel finds. This complex systems approach embraces vastness, randomness, and change.
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Architectural styles of curiosity in global Wikipedia mobile app readership
Science Advances
Dale Zhou,
Shubhankar Patankar,
David Lydon-Staley,
Perry Zurn,
Martin Gerlach,
Dani Bassett
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Curiosity is a fundamental aspect of human nature, yet most studies rely on small, Western samples. Analyzing 482,760 Wikipedia readers across 50 countries, this study replicates two known curiosity styles—"busybody" and "hunter"—and reveals a third, the "dancer," characterized by creative exploration. By linking these styles to global indicators like education and well-being, the findings shed light on how digital knowledge-seeking behaviors are shaped by cultural and geographical factors.
Coverage in Nature briefing, Science podcast, and Penn Today article.
Builds from our work in Hunters, busybodies, and the knowledge network building associated with curiosity (Nature Human Behavior)
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The growth and form of knowledge networks by kinesthetic curiosity
Current Opinion in Behavioral Sciences
Dale Zhou,
David Lydon-Staley,
Perry Zurn,
Dani Bassett
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Throughout life, we might seek a calling, companions, skills, entertainment, truth, self-knowledge, beauty, and edification. In this review, we describe how the practice of curiosity can be viewed as an extended and open-ended search for valuable information with hidden identity and location in a complex space of interconnected information. We propose how a computational model of efficient search can be used to bridge curiosity, cognitive maps, and model-based reinforcement learning.
Builds from our work in Hunters, busybodies, and the knowledge network building associated with curiosity (Nature Human Behavior)
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Advocacy & Outreach
I organize and have have been involved in outreach and mentoring across several programs:
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Kamen's Lens
Exhibited at Dyslexic Dictionary
Organized and curated by Gershoni Creative Arion Press Gallery, The Presidio, San Francisco, CA
Collaboration with Rebecca Kamen and SJ Fowler
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Description from the gallery: '"Dyslexic Dictionary" is a provocation — an invitation to explore and redefine. Nine dyslexic artists have been commissioned to produce a creative response to words, books, poems and even the alphabet itself, highlighting how their minds experience language. Participating artists include Governor Gavin Newsom, Gil Gershoni, Adeniyi Akingbade, Christian Boer, Adam Eli Feibelman, Sally Gardner, Martin Grasser, Rebecca Kamen and Kelsey Ann Kasom.'
Video description: Dyslexia highlights thoughts that are often more perceptual than verbal, shaping a uniquely visuospatial imagination. To depict Rebecca Kamen's visuospatial imagination, we used artificial intelligence (diffusion models) to translate verbal transcripts from Rebecca's interviews and presentations into animated images. Animations visualize the dynamic, fluid, and spontaneous forces underlying Rebecca's connective imagination—her curiosity.
This video spotlights one of Rebecca's artworks, Corona 3, and animates it into slightly different images according to guided prompts from transcripts describing the art. These verbal prompts include: “Vehicles of discovery, the dance of creation and destruction, an energy dance; a pulsating process of creation and destruction. The style of German zoologist Ernst Haeckel." By having artificial intelligence translate words into images, we appreciate a visual reimagining of the unique stories and neurodiverse artists behind how art takes shape.
Below, we took this approach a step further. British poet, SJ Fowler and Rebecca Kamen created an illustrated poem, Kamen's Lens, following years of communication about art, dyslexia, and inspirations. Here SJ Fowler performs a reading of Kamen's Lens. Six illustrations are each paired to their corresponding section of poetry and were animated using the text of the poetry itself.
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Sparking Curiosity
Exhibited at Reveal: The Art of Reimagining Scientific Discovery
Organized and curated by Rebecca Kamen and Sarah Tanguy
Museum at the Katzen Arts Center, American University, Washington, D.C.
Collaboration with
David Lydon-Staley,
Perry Zurn,
Dani Bassett
Code
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Sparking Curiosity depicts the network dynamics of Rebecca Kamen's art process. This network was created from transcribed interviews, where each circle represents a word describing an idea that shaped her artistic journey; and each line indicates how similar those words are to each other. The colors represent communities of ideas that are more alike. Every frame of the video summarizes the spark of hundreds of ideas and their immediate neighbors in the same order as spoken during the interview.
Builds from our work in Hunters, busybodies, and the knowledge network building associated with curiosity (Nature Human Behavior) and in The growth and form of knowledge networks by kinesthetic curiosity (Current Opinion in Behavioral Sciences)
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