MLC
Machine Learning Core
The Machine Learning Core supports NIMH investigators using statistics and machine learning for psychology, psychiatry, neuroscience, and imaging data.
The Machine Learning Core supports researchers in the NIMH intramural research program who want to address research problems in psychology, psychiatry, and neuroscience using statistics and machine learning approaches.
The core consults with individual researchers, helps select appropriate tools and methods, and can take on analysis work when that is the most efficient path. In parallel, it operates as a machine learning research group, developing new methods motivated by investigators' needs and by advances in the field.
Contact: francisco.pereira@nih.gov
Members
Francisco Pereira
group leader
Ka Chun Lam
research scientist
Gabriel Loewinger
research scientist
Juan Antonio Lossio-Ventura
research scientist
Anthony Matar
postbac IRTA
Dylan Nielson
research scientist
Aria Wang
research scientist
Yuan Zhao
research scientist
Charles Zheng
research scientist
Former Team Members
Sebastian Bruch
Sr. Research Scientist, Northeastern University
Yenho Chen
Machine Learning Ph.D. student at Georgia Tech
Nicole Kuznetsov
Data Science Researcher, NIA/CARD at NIH
Patrick McClure
Assistant Professor, Naval Postgraduate School
Al Xin
Statistics and Data Science Ph.D. student at CMU
Projects / Talks
Tools / Software
MLC
VICE
Toolbox for creating interpretable item embeddings from odd-one-out triplet task judgments.
MLC
Functional Linear Mixed Effects Models for Fiber Photometry
R and Python packages for fitting functional linear mixed effects models to fiber photometry data.
MLC
Interpretability-Constrained Questionnaire Factorization
Tools for generating interpretable factors and loadings from questionnaire data.
MLC
Fast Functional GEE
One-step functional GEE algorithm for longitudinal functional regression.
Publications
Preprints
Capturing instantaneous neural signal-behavior relationships with concurrent functional mixed models
Xin A.W., Cui E., Pereira F., Loewinger G.
Causal Inference in Studies with Functional Unmasking: Psychedelics and Beyond
Loewinger G., Stensrud M.J., Nayak S.M., Yaden D., Levis A
Fast Penalized Generalized Estimating Equations for Large Longitudinal Functional Datasets
Loewinger G., Levis A., Cui E., Pereira F.
In-Scanner Thoughts shape Resting-state Functional Connectivity: how participants "rest" matters
Gonzalez-Castillo J., Spurney M., Lam K.C., Gephart I. S., Pereira F., Handwerker D. A., Kam J. W. Y., Bandettini P.
Interpretable factorization of clinical questionnaires to identify latent factors of psychopathology
Lam K.C., Mahony B.W., Raznahan A., Pereira F.
Nonparametric causal inference for optogenetics: sequential excursion effects for dynamic regimes
Loewinger G., Levis A., Pereira F.
Prediction of mental well-being from individual characteristics and circumstances during the COVID-19 pandemic
Harris C., Farmer C., Gibbon A., Shaw J., Thomas A., Atlas L. Y., Chung J. Y., Pereira F.
Methods
A Deep Neural Network Tool for Automatic Segmentation of Human Body Parts in Natural Scenes
McClure P. , Reimann G., Ramot M., Pereira F. arXiv preprint
Validating the Representational Space of Deep Reinforcement Learning Models of Behavior with Neural Data
"Validating the Representational Space of Deep Reinforcement Learning Models of Behavior with Neural Data" Bruch S. N. , McClure P., Zhou J., Schoenbaum G., Pereira F. bioRxiv preprint
A Statistical Framework for Analysis of Trial-Level Temporal Dynamics in Fiber Photometry Experiments
Loewinger G., Cui E., Lovinger D., Pereira F. in press at eLife, 2025
More Experts Than Galaxies: Conditionally-overlapping Experts With Biologically-Inspired Fixed Routing
Shaier S., Pereira F., K von der Wense, LE Hunter, M Jones in International Conference on Learning Representations, 2025
A Comparison of ChatGPT and Fine-Tuned Open Pre-Trained Transformers (OPT) Against Widely Used Sentiment Analysis Tools: Sentiment Analysis of COVID-19 Survey Data
Lossio-Ventura J. A., Weger R., Lee A., Guinee E., Chung J. Y., Atlas L. Y., Linos E., Pereira F. JMIR Mental Health Vol 11, 2024
Causal Inference in the Closed-Loop: Marginal Structural Models for Sequential Excursion Effects
"Causal Inference in the Closed-Loop: Marginal Structural Models for Sequential Excursion Effects" Levis A., Loewinger G., Pereira in Neural Information Processing Systems, 2024
Improving the Interpretability of fMRI Decoding using Deep Neural Networks and Adversarial Robustness
"Improving the Interpretability of fMRI Decoding using Deep Neural Networks and Adversarial Robustness" McClure P., Moraczewski D., Lam K. C., Thomas A., Pereira F. Aperture Neuro, 2023
Linear time GPs for inferring latent trajectories from neural spike trains
Linear time GPs for inferring latent trajectories from neural spike trains" Matthew Dowling, Yuan Zhao, Il Memming Park in International Conference on Machine Learning, 2023
Real-time variational method for learning neural trajectory and its dynamics
"Real-time variational method for learning neural trajectory and its dynamics" Matthew Dowling, Yuan Zhao, Il Memming Park in International Conference on Learning Representations, 2023
Semantic Projection: Recovering Human Knowledge of Multiple, Distinct, Object Features from Word Embeddings
Grand G., Blank I., Pereira F., Fedorenko E. Nature Human Behaviour, 2022
VICE: Variational Interpretable Concept Embeddings
"VICE: Variational Interpretable Concept Embeddings" Muttenthaler L., Zheng C., McClure P., Vandermeulen R., Hebart M., Pereira F. in Neural Information Processing Systems, 2022
Deep Neural Networks in Computational Neuroscience
"Deep Neural Networks in Computational Neuroscience" Kietzmann, T., McClure, P., Kriegeskorte, N. Oxford Research Encyclopedia of Neuroscience, 2019
Knowing What You Know in Brain Segmentation Using Bayesian Deep Neural Networks
"Knowing What You Know in Brain Segmentation Using Bayesian Deep Neural Networks" McClure, P., Rho, N., Lee, J., Kaczmarzyk, J., Zheng, C., Ghosh, S., Nielson, D., Thomas, A., Bandettini, P., Pereira, F. Frontiers in Neuroinformatics, 2019
Revealing interpretable object representations from human behavior
"Revealing interpretable object representations from human behavior" Zheng, C., Pereira, F., Baker, C., Hebart, M. International Conference on Learning Representations, 2019
Distributed Weight Consolidation: A Brain Segmentation Case Study
"Distributed Weight Consolidation: A Brain Segmentation Case Study" McClure P., Zheng C., Kaczmarzyk J., Rogers-Lee J., Ghosh S., Nielson D., Bandettini P., Pereira F. Neural Information Processing Systems, 2018
Extrapolating Expected Accuracies for Large Multi-Class Problems
"Extrapolating Expected Accuracies for Large Multi-Class Problems" Zheng, C., Achanta R., Benjamini. Y. Journal of Machine Learning Research vol. 19. 2018.
Applications
Neuroscience
Brain-wide presynaptic networks of functionally distinct cortical neurons
Inacio A. R., Lam K. C., Zhao Y., Pereira F., Gerfen C. R., Lee S. in Nature 1-11, 2025
Distinct prelimbic cortex ensembles encode response execution and inhibition
Madangopal R., Zhao Y., Heins C., Zhou U., Liang B., Barbera G., Lam K.C., Komer L.E., Weber S.J., Thompson D. J., Gera Y., Pham D.Q., Savell K.E., Warren B.L., Caprioli D., Venniro M., Bossert J.M., Ramsey L.A., Jedema H.P., Schoenbaum G., Lin D.T., Shaham Y., Pereira F., Hope B.T. in Proceedings of the National Academy of Sciences 122 (37), 2025
Persistent representation of a prior schema in the orbitofrontal cortex facilitates learning of a conflicting schema
Maor I., Atwell J., Ascher I., Zhao Y., Takahashi Y.K., Hart E., Pereira F., Schoenbaum G. in press at Nature Communications, 2025
The encoding of interoceptive-based predictions by the paraventricular nucleus of the thalamus D2+ neurons
Machen B., Miller S., Xin A., Lampert C., Assaf L., Tucker J., Pereira F., Loewinger G., Beas S. in press at iScience, 2025
Dissociable encoding of motivated behavior by parallel thalamo-striatal projections
Beas S., Khan I., Gao C., Loewinger G., Macdonald E., Bashford A., Rodriguez-Gonzalez S., Pereira F., Penzo M.A. in Current Biology, 2024
Sensory and Choice Responses in MT Distinct from Motion Encoding
"Sensory and Choice Responses in MT Distinct from Motion Encoding" Aaron J. Levi, Yuan Zhao, Il Memming Park and Alexander C. Huk Journal of Neuroscience 22 March 2023, 43 (12) 2090-2103
Working memory and reward increase the accuracy of animal location encoding in the medial prefrontal cortex
"Working memory and reward increase the accuracy of animal location encoding in the medial prefrontal cortex" Ma X., Zheng C., Chen Y., Pereira F., Zheng L. Cerebral Cortex, 2022, 1-15
Cell-type-specific recruitment of GABAergic interneurons in the primary somatosensory cortex by long-range inputs
Naskar S., Qi J., Pereira F., Gerfen, C., Lee, S. Cell Reports 34, 108774, 2021
Psychiatry
Mood and Behaviors of Adolescents With Depression in a Longitudinal Study Before and During the COVID-19 Pandemic
"Mood and Behaviors of Adolescents With Depression in a Longitudinal Study Before and During the COVID-19 Pandemic" Sadeghi N., Fors P.Q., Eisner L., Taigman J., Qi K., Gorham L.S., Camp C.C., O'Callaghan G., Rodriguez D., McGuire J., Garth E.M., Engel C., Davis M., Towbin K.E., Stringaris A., Nielson D.M.
Origins of Anhedonia in Childhood and Adolescence
"Origins of Anhedonia in Childhood and Adolescence" Prabhakar J., Nielson D.M., Stringaris A.
Automated classification of exposure and encourage events in speech data from pediatric OCD treatment
Lossio-Ventura J.A., Frank S., Ringlein G., Bonson K., Olszko A., Knobel A., Pine D.S., Freeman J., Benito K., Jangraw D.C, in JAMIA Open 8 (6), 2025
Detecting Cry in Daylong Audio Recordings using Machine Learning: The Development and Evaluation of Binary Classifiers
Henry L.M., Lee K., Hansen E., Tandilashvili E., Rozsypal J., Erjo T., Raven J. G., Reynolds H. M., Curtis P., Haller S.,Pine D., Norton E., Wakschlag K.S., Pereira F., Brotman M.A. in press at Assessment, 2025
Multivariate prediction of temper outbursts in a sample of youth enriched for irritability using ecological momentary assessment data: A registered report
Saha D., Naim R., Pereira F., Brotman M.A., Zheng C.Y. in PLoS one, vol. 30 (3), 2025
Dynamic effects of psychiatric vulnerability, loneliness, and social distancing on distress during the first year of the COVID-19 pandemic: Insights from a large-scale longitudinal study
Atlas L. Y., Farmer C., Shaw J., Gibbon A., Guinee E.P., Lossio-Ventura J. A., Ballard E., Ernst M., Japee S., Pereira F., Chung J. Y. in Nature Mental Health, 2024
Outcomes that matter to depressed adolescents can be identified with large language models
Xin A., Lossio-Ventura J. A., Krause, K. R., Fiorini, G., Midgley N., Pereira F., and Nielson D. M. in Journal of the American Medical Informatics Association, 2024
Subjective Affective Experience under threat is shaped by environmental affordances
Qi S., Nielson D.M., Marcotulli D., Pine D.S., Stringaris A. in Public Library of Science One, 2024
Test-retest reliability of functional connectivity in adolescents with depression
Camp C., Noble S., Scheinost D., Stringaris A., Nielson D.M. in Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 2024
A Highly Replicable Decline in Mood During Rest and Simple Tasks
"A Highly Replicable Decline in Mood During Rest and Simple Tasks" Jangraw D., Keren H., Sun H., Bedder R., Rutledge R., Pereira F., Thomas A., Pine D., Zheng C., Nielson D., Stringaris A. Nature Human Behaviour 7 (4), 596-610, 2023
Trends in Language Use During the COVID-19 Pandemic and Relationship Between Language Use and Mental Health: Text Analysis Based on Free Responses From a Longitudinal Study
Weger R., Lossio-Ventura J. A., Rose-McCandlish M., Shaw J., Sinclair S., Pereira F., Chung J., Atlas L. JMIR Mental Health 10 (1), e40899, 2023
Validation of CBCL depression scores of adolescents in three independent datasets
Zelenina M., Pine D.S., Stringaris A., Nielson D.M. JCPP Advances, 2023
Gauging facial feature viewing preference as a stable individual trait in autism spectrum disorder.
Reimann G., Walsh C., Csumitta K., McClure P., Pereira F., Martin A., Ramot M. Autism Research 14:1670–1683, 2021
Magnetoencephalographic Correlates of Mood and Reward Dynamics in Human Adolescents
"Magnetoencephalographic Correlates of Mood and Reward Dynamics in Human Adolescents" Liuzzi, L., Chang, K.K., Zheng, C., Keren, H., Saha, D., Nielson, D.M. and Stringaris, A. Cerebral Cortex, 2021
The temporal representation of experience in subjective mood
"The temporal representation of experience in subjective mood" Keren H., Zheng C., Jangraw D. C., Chang K., Vitale A., Nielson D., Rutledge R. B., Pereira F., Stringaris A. eLife 2021
Data-driven identification of subtypes of executive function across typical development, attention deficit hyperactivity disorder, and autism spectrum disorders
Vaidya C., You X., Mostofsky S., Pereira F., Berl M., Kenworthy L. J Child Psychol Psychiatry 61(1): 51–61. 2019
Cognitive Psychology/Neuroscience
Neural and behavioral reinstatement jointly reflect retrieval of narrative events
Nau M., Greene A., Tarder-Stoll H., Lossio-Ventura J.A., Pereira F., Chen J., Baldassano C., Baker C.I. in press at Nature Communications, 2025
Manifold learning for fMRI time-varying functional connectivity
"Manifold learning for fMRI time-varying functional connectivity" Gonzalez-Castillo J., Fernandez I., Lam K., Handwerker D., Pereira F., Bandettini P. Front Hum Neurosci. 2023; 17: 1134012
Mental representations of objects reflect the ways in which we interact with them
"Mental representations of objects reflect the ways in which we interact with them" Lam K. C., Pereira F., Vaziri-Pashkam M., Woodard K., McMahon E. Proceedings of the Cognitive Science Society Conference, 2021 [selected for oral presentation]
The temporal representation of experience in subjective mood
"The temporal representation of experience in subjective mood" Keren H., Zheng C., Jangraw D. C., Chang K., Vitale A., Nielson D., Rutledge R. B., Pereira F., Stringaris A. eLife 2021
Revealing the multidimensional mental representations of natural objects underlying human similarity judgments
"Revealing the multidimensional mental representations of natural objects underlying human similarity judgments" Hebart, M., Zheng, C., Pereira, F., Baker, C. Nature Human Behaviour, 2020
Imaging the spontaneous flow of thought: Distinct periods of cognition contribute to dynamic functional connectivity during rest
Gonzalez-Castillo J., Caballero-Gaudes C., Topolski N., Handwerker D., Pereira F. , Bandettini P. Neuroimage 15; 202: 116129. 2019
Subtle predictive movements reveal actions regardless of social context
"Subtle predictive movements reveal actions regardless of social context" McMahon, E.G., Zheng, C.Y., Pereira, F., Gonzalez, R., Ungerleider, L.G. and Vaziri-Pashkam, M. Journal of vision 19 (7), 16-16, 2019
Toward a universal decoder of linguistic meaning from brain activation
"Toward a universal decoder of linguistic meaning from brain activation" Pereira F., Lou B., Pritchett B., Ritter S., Gershman S., Kanwisher N., Botvinick M., Fedorenko E. Nature Communications 9 (963), 2018