About

Aron Keith Barbey is a Professor of Psychology at the University of Illinois Urbana-Champaign, where he also holds a position in the Department of Bioengineering. He began his academic career at Illinois in 2011 and was promoted to Full Professor in 2019. During his tenure at Illinois, he held several leadership roles, including Director of the Center for Brain Plasticity, Director of the Intelligence, Learning, and Plasticity Initiative, and Chair of the Intelligent Systems Research Theme at the Beckman Institute for Advanced Science and Technology. He later served as the Mildred Francis Thompson Professor and Director of the Center for Brain, Biology and Behavior at the University of Nebraska-Lincoln. Dr. Barbey's research investigates how intelligence emerges from the network organization and dynamics of the human connectome, utilizing methods from network neuroscience, cognitive psychology, and computer science. His work aims to deepen the understanding of the neural foundations of intelligence and to foster innovations in cognitive enhancement, neurorehabilitation, and biologically inspired artificial intelligence. His research group has secured over $26 million in funding from various organizations, including the Office of the Director of National Intelligence, the Department of Defense, the White House BRAIN Initiative, NIH, NSF, and private industry sponsors. Dr. Barbey has received numerous honors, including the Mensa Foundation Prize for his work on the neuroscience of intelligence. He is a co-editor of key handbooks in the field and serves as editor of the forthcoming Oxford Handbook of Cognitive Enhancement and Brain Plasticity. He earned his Ph.D. in Psychology from Emory University and completed postdoctoral training at the National Institutes of Health.

Research topics

• Computer Science
• Neuroscience
• Cognitive science
• Psychology
• Artificial Intelligence
• Biology
• Cognitive psychology
• Medicine
• Radiology
• Physics
• Internal medicine
• Emergency medicine
• Biomedical engineering
• Intensive care medicine
• Bioinformatics
• Anatomy
• Pharmacology
• Physical medicine and rehabilitation
• Developmental psychology
• Psychiatry

Selected publications

• Nutrition for Older Adults: Perspectives on Dietary Guidance for Healthy Aging

  Current Developments in Nutrition · 2026-02-21

  articleOpen access

  <h2>Abstract</h2> The world is rapidly aging. It is projected that "young old" (i.e., 60+ y) will double by 2050 and "older old" (i.e., 80+ y) will nearly triple. Greater life expectancy has been accompanied by more chronic health conditions and disabilities, especially those that are related to diet and lifestyle. Although people are living longer, their healthy life expectancy has not kept pace, meaning that more years are spent in poorer health—thus, the need to identify targets to increase "health span." Nutrition plays a critical role in aging healthfully. However, the aging process is accompanied by unique physiological, social, and contextual factors that impact the nutritional needs of the aging population—requiring more specific and tailored dietary recommendations. To examine the complexity of diet within the aging population, the <i>Nutrition and Wellness Science Forum: Exploring the Journey to Healthy Aging</i> was held in Washington, D.C. to focus on scientific evidence and research gaps surrounding dietary intakes and nutrient adequacy among older adults, as well as the role of nutrition in musculoskeletal, cardiometabolic, and cognitive health. Discussions also addressed the need for culturally appropriate dietary assessment methods and interventions that reflect the heterogeneity and diversity of older adults, as well as the importance of the food system. This review summarizes the forum's key themes, discussions, and identified research gaps.

  PublisherOA PDFDOI

• The network architecture of general intelligence in the human connectome

  Nature Communications · 2026-01-26 · 2 citations

  articleOpen accessSenior author

  Advances in network neuroscience challenge the view that general intelligence (g) emerges from a primary brain region or network. Network Neuroscience Theory (NNT) proposes that g arises from coordinated activity across the brain’s global network architecture. We tested predictions from NNT in 831 healthy young adults from the Human Connectome Project. We jointly modeled the brain’s structural topology and intrinsic functional covariation patterns to capture its global topological organization. Our investigation provided evidence that g (1) engages multiple networks, supporting the principle of distributed processing; (2) relies on weak, long-range connections, emphasizing an efficient and globally coordinated network; (3) recruits regions that orchestrate network interactions, supporting the role of modal control in driving global activity; and (4) depends on a small-world architecture for system-wide communication. These results support a shift in perspective from prevailing localist models to a theory that grounds intelligence in the global topology of the human connectome. General intelligence (g) emerges from the global topology of the human connectome. Modeling structure and function in 831 adults reveals g engages distributed networks, weak long-range connections, modal control regions, and a small-world topology.

  PublisherOA PDFDOI

• Nutrition and Mental Health: Advances in Nutritional Cognitive Neuroscience

  Annual Review of Food Science and Technology · 2026-02-21 · 1 citations

  articleSenior author

  Accumulating evidence indicates that diet and nutrition are important modifiable risk factors for the prevention and treatment of mental health disorders. However, the neural mechanisms underlying nutrition's effects on mental health remain to be well established. The interdisciplinary field of nutritional cognitive neuroscience integrates methods across the nutritional, cognitive, and brain sciences to understand nutrition's impact on brain health across the lifespan, with recent applications to the study of mood and anxiety-related disorders. In this focused review, we begin by investigating the neural mechanisms underlying mood and anxiety-related disorders, surveying evidence of alterations within specific structural and functional networks. We then review emerging evidence to suggest that the structure and function of these networks are influenced by specific nutrients that may confer beneficial effects, including B-vitamins, omega-3 polyunsaturated fatty acids, polyphenols, and carotenoids. In this effort, we highlight plausible biological pathways through which diet may influence mood and anxiety-related disorders. We conclude by presenting directions for future research, emphasizing the need for dietary interventions that incorporate contemporary methods from cognitive neuroscience and nutritional epidemiology to promote brain health and reduce the risk of mental illness.

  PublisherDOI

• The moderating effects of PUFA-MUFA status on brain network organization and cognitive function in older adults

  Global Perspectives on Nutrition · 2026-01-01

  articleOpen accessSenior author

  Abstract Objectives This study investigates the interplay between dietary fatty acid composition (poly- and mono-unsaturated fatty acids, PUFAs and MUFAs), functional brain network organization, and attention and visuomotor processing speed among older adults. Background Dietary intake is one of several modifiable lifestyle behaviors that can have a significant impact on both cognitive function and brain health. Diets emphasizing the intake of polyunsaturated and monounsaturated fatty acids have been shown to support cognitive aging and reduce age-related cognitive decline. Methods Cross-sectional data from 92 participants with a mean age of 68.8 were examined using a moderation model. PUFA + MUFA nutrient pattern served as the moderator (w). The predictor (x) was the small world propensity of the dorsal attention network (DAN), and the outcome (y) was the D-KEFS Trail composite score. Results The moderation model yielded significance (F (9, 82) = 2.18, P = .047, R2 = 0.19, P = .032). Notably, an interaction (t = 2.74, P = .008, CI [1.71, 10.83]) emerged between PUFA + MUFA nutrient pattern and functional organization. Conclusions Expanding upon prior research, these findings reveal that individuals with higher long-term dietary PUFA and MUFA intake from food sources, as assessed via a diet history questionnaire, are inclined to exhibit small-world DAN organization. Furthermore, these individuals demonstrate superior attention and visuomotor processing speed compared to peers with lower dietary intake. This study underscores the impact of diet on brain network properties and cognitive function and offers actionable insights for nutritional interventions targeting enhanced brain health during aging.

  PublisherDOI

• Statistical Machine-Learning Methods to Model Brain Plasticity

  Oxford University Press eBooks · 2025-03-20 · 1 citations

  book-chapter

  Abstract This chapter discusses statistical machine-learning (ML) approaches to model brain plasticity, which involves complex changes in the brain due to natural or induced causes. The chapter highlights various advantages that ML models have compared with traditional models of brain plasticity. Since brain plasticity can be analyzed at various levels of granularity, this chapter discusses several approaches to model brain plasticity, starting with some examples of the most traditionally studied, that is, the plasticity of the visual and motor control systems and synaptic plasticity for memory throughout the mammalian neocortex. Then brain plasticity models are discussed in various contexts and scales, including the main aspects to be considered in multiscale plasticity modeling, with specific information about models at the neuron level, the cortical column, and plasticity changes as a result of natural development. Following this, the chapter discusses modeling of plasticity’s effect on higher-level cognitive functions, specifically those related to behavior, cognition, learning, decision making, intelligence, and memory. Plasticity when it results from trauma or brain damage is then reviewed. The chapter concludes by reviewing open research questions and future research directions for machine-learning modeling of brain plasticity.

  PublisherDOI

• Microstructural Plasticity

  Oxford University Press eBooks · 2025-07-22

  book-chapter

  Abstract This chapter explores the study of plasticity of white matter microstructural and structural connectivity of the brain. Diffusion-weighted magnetic resonance imaging provides an in vivo method for modeling changes to the white matter that affect critical communication between brain regions. As described here, the diffusion tensor imaging model provided useful insights into this plasticity and built the foundation for tractography and structural connectivity. However, the limitations of this model are now well known, and new methods seek to provide better approximations of underlying tissue microstructure and more complete representations of white matter connections in the brain. Critically for cognitive research, these methods have shown promising improvements in prediction of brain function. The chapter describes more recent models of diffusion, tractography, and structural connectivity generation that address limitations of the diffusion tensor imaging approach and provide greater potential for cutting-edge biomarker research. The text also presents recent applications of these techniques in cognitive neuroscience research.

  PublisherDOI

• Investigating the Impact of Nuts and Seeds on Cognitive Functions in Healthy Adults While Accounting for Dietary Interactions

  Current Developments in Nutrition · 2025-05-01

  articleOpen accessSenior author

  Objectives: Cognitive performance is influenced by lifestyle choices, including dietary intake, which plays a key role in brain health and functioning. Prior research indicates that (1) nuts and seeds are a type of nutrient-dense food that contains various neuroprotective components including MUFAs and PUFAs, and (2) increased consumption of foods rich in these nutrients may be associated with better executive function and fluid intelligence. However, much of this evidence stemmed from investigation of nuts and seeds in isolation, without considering their interactions with other dietary components.

  PublisherOA PDFDOI

• Nutritional Cognitive Neuroscience: The Science of Mind, Brain, and Nutrition

  Journal of Nutrition · 2025-12-02 · 1 citations

  article1st authorCorresponding
  PublisherDOI

• The Utilitarian Brain: Going Beyond the Free Energy Principle

  2024-01-09

  preprintOpen accessSenior author

  The Free Energy Principle (FEP) is a normative computational framework for iterativereduction of prediction error and uncertainty through perceptioneintervention cycles thathas been presented as a potential unifying theory of all brain functions (Friston, 2006). Anytheory hoping to unify the brain sciences must be able to explain the mechanisms ofdecision-making, an important cognitive faculty, without the addition of independent,irreducible notions. This challenge has been accepted by several proponents of the FEP(Friston, 2010; Gershman, 2019). We evaluate attempts to reduce decision-making to theFEP, using Lucas' (2005) meta-theory of the brain's contextual constraints as a guidepost.We find reductive variants of the FEP for decision-making unable to explain behavior incertain types of diagnostic, predictive, and multi-armed bandit tasks. We trace the shortcomings to the core theory's lack of an adequate notion of subjective preference or “utility”, a concept central to decision-making and grounded in the brain's biological reality. We argue that any attempts to fully reduce utility to the FEP would require unrealistic assumptions, making the principle an unlikely candidate for unifying brain science. Wesuggest that researchers instead attempt to identify contexts in which either informationalor independent reward constraints predominate, delimiting the FEP's area of applicability.To encourage this type of research, we propose a two-factor formal framework that cansubsume any FEP model and allows experimenters to compare the contributions ofinformational versus reward constraints to behavior.

  PublisherDOI

• Cognitive Neuroscience: Basic Principles, Systems, and Methods

  2024-01-01

  book-chapter
  PublisherDOI

Frequent coauthors

• Jordan Grafman

  108 shared

• Frank Krueger

  George Mason University

  63 shared

• Roberto Colom

  42 shared

• Christopher E. Zwilling

  University of Illinois Urbana-Champaign

  34 shared

• Arthur F. Kramer

  29 shared

• Neal J. Cohen

  Icahn School of Medicine at Mount Sinai

  26 shared

• Marta K. Zamroziewicz

  26 shared

• Erick J. Paul

  Microsoft (United States)

  23 shared

Education

• Ph.D., Bioengineering

  University of Illinois Urbana-Champaign

  2004

• M.S., Bioengineering

  University of Illinois Urbana-Champaign

  2001

• B.S., Bioengineering

  University of Illinois Urbana-Champaign

  1998

Awards & honors

• Mensa Foundation Prize