About

Michael L. Platt is a James S. Riepe University Professor whose research focuses on the biological mechanisms underlying decision-making and social interaction. His work studies brain circuits and behavior, neurological and neuropsychiatric disorders, and individual differences in behavior and genetics. His lab applies insights and technology from brain science to areas such as branding, marketing, management, finance, innovation, and elite performance, with sports serving as a key context for validating these applications. He has held prominent academic positions, including former Director of the Duke Institute for Brain Sciences and the Center for Cognitive Neuroscience at Duke, as well as the founding Co-Director of the Duke Center for Neuroeconomic Studies. Platt has authored over 170 peer-reviewed papers and more than 60 review and opinion papers, and he is the author of 'The Leader’s Brain.' His research has been supported by major institutions such as the NIH, the McDonnell Foundation, and the Department of Defense, among others. He has created and directs executive education courses on neuroscience and business for Wharton and works closely with companies, professional sports teams, and organizations. His work has been featured in numerous major media outlets, and he serves on various scientific advisory boards, including the Yang-Tan Autism Centers at MIT and Harvard, and the National Primate Research Centers at Emory and UC Davis. Platt has served as President of the Society for Neuroeconomics and has been involved in various initiatives related to brain science and neurotechnology.

Research topics

• Biology
• Psychology
• Evolutionary biology
• Neuroscience
• Medicine
• Genetics
• Computer Science
• Psychiatry
• Business
• Computational biology
• Physiology
• Zoology
• Medical physics
• Ecology
• Developmental psychology
• Internal medicine
• Cognitive science
• Social psychology
• Immunology
• Cognitive psychology
• Pathology

Selected publications

• Interpretable Visual Complexity and Neural Transfer Functions for Understanding Consumer Value

  SSRN Electronic Journal · 2026-01-01

  preprintOpen accessSenior author
  PublisherDOI

• Interpretable Modeling Reveals Population-Level Representation Differences in P300 Brain Computer Interfaces Across Neurodivergent and Neurotypical Cohorts

  2026-04-27

  articleOpen access

  P300-based brain-computer interfaces (BCIs) are widely used for communication, but population heterogeneity may alter the neural patterns available for decoding. Prior work has mainly examined such differences at the signal or performance level, while the representation structure learned by the decoder remains underexplored. In this study, we propose an interpretable fuzzy spatiotemporal framework for P300 classification and use it to analyze population-level differences across amyotrophic lateral sclerosis (ALS), autism (AUT), and neurotypical (NT) cohorts. The model employs spatial and temporal fuzzy filters with learnable prototypes, enabling both classification and reconstruction of cohort-specific fuzzy centers. Experiments were conducted on ALS and NT subsets from bigP3BCI and on the BCIAUT-P300 benchmark in a within-subject setting. The proposed model achieved competitive performance against multiple deep learning baselines. More importantly, the reconstructed fuzzy centers revealed systematic cohort-dependent differences in waveform morphology and representation geometry. Point-wise statistical analysis identified significant temporal differences between cohorts, including intervals overlapping with the canonical P300 window, and low-dimensional embeddings showed partially separated cohort-specific prototype organizations. These results suggest that population heterogeneity in P300-BCI is reflected not only in decoding performance but also in the discriminative structure learned by the model. The proposed framework provides an interpretable route toward population-aware P300-BCI analysis and design.

  PublisherDOI

• Interpretable Modeling Reveals Population-Level Representation Differences in P300 Brain Computer Interfaces Across Neurodivergent and Neurotypical Cohorts

  2026-04-13

  articleOpen access

  P300-based brain-computer interfaces (BCIs) are widely used for communication, but population heterogeneity may alter the neural patterns available for decoding. Prior work has mainly examined such differences at the signal or performance level, while the representation structure learned by the decoder remains underexplored. In this study, we propose an interpretable fuzzy spatiotemporal framework for P300 classification and use it to analyze population-level differences across amyotrophic lateral sclerosis (ALS), autism (AUT), and neurotypical (NT) cohorts. The model employs spatial and temporal fuzzy filters with learnable prototypes, enabling both classification and reconstruction of cohort-specific fuzzy centers. Experiments were conducted on ALS and NT subsets from bigP3BCI and on the BCIAUT-P300 benchmark in a within-subject setting. The proposed model achieved competitive performance against multiple deep learning baselines. More importantly, the reconstructed fuzzy centers revealed systematic cohort-dependent differences in waveform morphology and representation geometry. Point-wise statistical analysis identified significant temporal differences between cohorts, including intervals overlapping with the canonical P300 window, and low-dimensional embeddings showed partially separated cohort-specific prototype organizations. These results suggest that population heterogeneity in P300-BCI is reflected not only in decoding performance but also in the discriminative structure learned by the model. The proposed framework provides an interpretable route toward population-aware P300-BCI analysis and design.

  PublisherDOI

• Age and early life adversity shape heterogeneity of the epigenome across tissues in macaques

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-07-18 · 1 citations

  preprintOpen access

  Age and early life adversity (ELA) are both key determinants of health, but whether they target similar physiological mechanisms across the body is unknown due to limited multi-tissue datasets from well-characterized cohorts. We generated DNA methylation (DNAm) profiles across 14 tissues in 237 semi-free ranging rhesus macaques, with records of naturally occurring ELA. We show that age-associated DNAm variation is predominantly tissue-dependent, yet tissue-specific epigenetic clocks reveal that the pace of epigenetic aging is relatively consistent within individuals. ELA effects on loci are adversity-dependent, but a given ELA has a coordinated impact across tissues. Finally, ELA targeted many of the same loci as age, but the direction of these effects varied, indicating that ELA does not uniformly contribute to accelerated age in the epigenome. ELA thus imprints a coordinated, tissue-spanning epigenetic signature that is both distinct from and intertwined with age-related change, advancing our understanding of how early environments sculpt the molecular foundations of aging and disease.

  PublisherOA PDFDOI

• Data for Siracusa et al. 2023 Phil Trans - "Ageing in a collective: The impact of ageing individuals on social network structure"

  Figshare · 2025-01-01 · 1 citations

  datasetOpen access

  Data to recreate analyses found in Siracusa et al. 2023 Phil. Trans - "Ageing in a collective: The impact of ageing individuals on social network structure".<br>Data updated on 29-Aug-25 due to previous error in how individual IDs were scrambled.

  PublisherDOI

• Author response: Multi-dimensional social relationships shape social attention in monkeys

  2025-02-26

  peer-reviewOpen access

  Social relationships guide individual behavior and ultimately shape the fabric of society. Primates exhibit particularly complex, differentiated, and multidimensional social relationships, which form interwoven social networks, reflecting both individual social tendencies and specific dyadic interactions. How the patterns of behavior that underlie these social relationships emerge from moment-to-moment patterns of social information processing remains unclear. Here, we assess social relationships among a group of four monkeys, focusing on aggression, grooming, and proximity. We show that individual differences in social attention vary with individual differences in patterns of general social tendencies and patterns of individual engagement with specific partners. Oxytocin administration altered social attention and its relationship to both social tendencies and dyadic relationships, particularly grooming and aggression. Our findings link the dynamics of visual information sampling to the dynamics of primate social networks.

  PublisherDOI

• Prefrontal Cortical Synchronization Underlies Emotional State Transmission via Perceived Arousal

  2025-10-30

  articleOpen access

  Touch is one of the most fundamental and evolutionarily conserved channels of social communication, yet it remains unclear whether and how touch alone can transmit affective states between individuals. Existing studies often conflate tactile contact with visual or auditory cues, obscuring the neural mechanisms and temporal dynamics of emotional state transmission. Here we isolated tactile channel in pairs of participants who engaged in handholding while one partner (Sender) viewed emotional videos and the other (Receiver) was visually and acoustically isolated. Functional near-infrared spectroscopy (fNIRS) hyperscanning revealed that touch aligned partners’ arousal states, enhanced receivers’ sensitivity to emotional cues, and strengthened prefrontal inter-brain synchrony (IBS). Crucially, mediation analyses showed that under the touch level, prefrontal IBS predicted receivers’ arousal estimates, which in turn predicted their emotional sensitivity (d'), indicating a touch-specific indirect pathway through arousal alignment. Time-resolved analyses further revealed that neural activity in the Sender's prefrontal cortex, particularly inferior frontal gyrus, preceded Receiver neural responses by approximately 16 s. These findings reveal a neural mechanism by which embodied contact sequentially aligns emotional states through prefrontal coupling. By elucidating how touch embeds emotional meaning within a shared neural space, our findings advance an embodied account of human communication and provide a biological foundation for developing emotionally attuned, socially embedded artificial intelligence.

  PublisherDOI

• Cost-effective solutions for high-throughput enzymatic DNA methylation sequencing

  PLoS Genetics · 2025-05-22 · 8 citations

  articleOpen accessCorresponding

  Characterizing DNA methylation patterns is important for addressing key questions in evolutionary biology, development, geroscience, and medical genomics. While costs are decreasing, whole-genome DNA methylation profiling remains prohibitively expensive for most population-scale studies, creating a need for cost-effective, reduced representation approaches (i.e., assays that rely on microarrays, enzyme digests, or sequence capture to target a subset of the genome). Most common whole genome and reduced representation techniques rely on bisulfite conversion, which can damage DNA resulting in DNA loss and sequencing biases. Enzymatic methyl sequencing (EM-seq) was recently proposed to overcome these issues, but thorough benchmarking of EM-seq combined with cost-effective, reduced representation strategies is currently lacking. To address this gap, we optimized the Targeted Methylation Sequencing protocol (TMS)-which profiles ~4 million CpG sites-for miniaturization, flexibility, and multispecies use. First, we tested modifications to increase throughput and reduce cost, including increasing multiplexing, decreasing DNA input, and using enzymatic rather than mechanical fragmentation to prepare DNA. Second, we compared our optimized TMS protocol to commonly used techniques, specifically the Infinium MethylationEPIC BeadChip (n = 55 paired samples) and whole genome bisulfite sequencing (n = 6 paired samples). In both cases, we found strong agreement between technologies (R2 = 0.97 and 0.99, respectively). Third, we tested the optimized TMS protocol in three non-human primate species (rhesus macaques, geladas, and capuchins). We captured a high percentage (mean = 77.1%) of targeted CpG sites and produced methylation level estimates that agreed with those generated from reduced representation bisulfite sequencing (R2 = 0.98). Finally, we confirmed that estimates of 1) epigenetic age and 2) tissue-specific DNA methylation patterns are strongly recapitulated using data generated from TMS versus other technologies. Altogether, our optimized TMS protocol will enable cost-effective, population-scale studies of genome-wide DNA methylation levels across human and non-human primate species.

  PublisherDOI

• The Effects of Neurodiversity in Human-Computer Trading Environments

  SSRN Electronic Journal · 2025-01-01

  preprintOpen accessSenior author
  PublisherDOI

• Author response: Multi-dimensional social relationships shape social attention in monkeys

  2025-03-07

  peer-reviewOpen access

  Multi-dimensional social relationships dynamically shape attentional biases toward in-group and out-group conspecifics in monkeys, with oxytocin modulating these interactions to reveal neurobiological links between social networks and visual information processing.

  PublisherDOI

Recent grants

• Single cell transcriptional and epigenomic atlas of the macaque brain across the lifespan

  NIH · $4.8M · 2019–2023

• NIH Grant R03MH066259

  NIH · $154k · 2005

• Mechanisms Regulating Complex Social Behavior

  NIH · $7.1M · 2016–2027

• Neurogenomics of Vulnerability and Resilience to Mental Health Syndromes in Response to Extreme Life Events

  NIH · $1.9M · 2019–2025

• NIH Grant R01EY013496

  NIH · $2.6M · 2011

Frequent coauthors

• Julie E. Horvath

  North Carolina Museum of Natural Sciences

  83 shared

• Lauren J. N. Brent

  University of Exeter

  76 shared

• Noah Snyder‐Mackler

  Arizona State University

  70 shared

• Karli Watson

  University of Colorado Boulder

  70 shared

• John Pearson

  66 shared

• James P. Higham

  New York University

  65 shared

• Benjamin Y. Hayden

  Baylor College of Medicine

  57 shared

• Michael J. Montague

  University of Pennsylvania

  45 shared

Awards & honors

• MERIT award from the National Institute of Mental Health
• Alfred P. Sloan Foundation Fellow
• Master Teacher/Clinician Award from the Duke University Scho…
• Teaching Commitment and Curricular Innovation Award from the…