Francisco Pereira homepage (original) (raw)

Who

Francisco Pereira. If you would like to contact me, try the most obvious address at the most obvious commercial provider.
There are other places where you can find me online: LinkedIn, Twitter, Bluesky, Mastodon. I may not have much to say, though!

Where

I lead the Machine Learning Core at the National Institute of Mental Health (NIMH).

Prior to this, I was a researcher at Medical Imaging Technologies, Siemens Healthcare, where I managed the Computational Neuroscience program. I was also the PI of a team in the IARPA Knowledge Representation in Neural Systems program. I was a postdoc in the Botvinick Lab (and a frequent lurker in the Computational Memory Lab) at the Princeton Neuroscience Institute. I got my Ph.D. in theComputer Science Department at CMU, working with Tom Mitchell and Geoff Gordon. I was also a student in the graduate training program of theCenter for the Neural Basis of Cognition, working in collaboration with theCenter for Cognitive Brain Imaging. I got my undergraduate degree at the Computer Science Department of the University of Porto, in Portugal.

What

My primary role is leading the NIMH Machine Learning Core, a research group that I started in 2018. The mission of the Machine Learning Core is to support researchers in the NIMH and NIDA intramural research programs who want to address research problems in psychology, psychiatry, and neuroscience, using statistics and machine learning approaches. We do this by consulting with individual researchers and guiding them in the use of the appropriate tools and methods, or by taking on the analysis process ourselves, if this is more expedient. In parallel, we are a machine learning research group and, as such, develop new methods and analysis approaches, motivated by the needs of researchers or by the practical possibilities arising from advances in the field. In general, I am very interested in the use of artificial intelligence and machine learning to augment human capability, in domains such as scientific discovery or decision making.

My main interest within cognitive (neuro)science is in the question of how semantic knowledge is represented in the brain, and is evoked and transformed by language. I have worked on methods to extract semantic information from text corpora and combine it with structured knowledge databases, in order to build models of human performance on various semantic tasks. I also worked on methods to relate models of semantic mental processes to brain imaging data, validating those models through brain decoding tasks.

Publications, preprints, and software from our research group

(please see my Google Scholar for more citation details, or MLC for other publications by members of the group where I am not a co-author)

preprints under review software packages
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. 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. Nonparametric causal inference for optogenetics: sequential excursion effects for dynamic regimes Loewinger G., Levis A., Pereira F. 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. 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-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. 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. fastFMM: Fast Functional Mixed Models using Fast Univariate Inference (the primary developer is Gabe Loewinger, please see this paper for more details ) VICE: a toolbox for creating interpretable item embeddings from odd-one-out triplet task judgments (the primary developer is Lukas Muttenthaler, please see this paper for more details) ICQF: a factorization tool designed for questionnaire datasets, with constraints that promote interpretability (the primary developer is Ka Chun Lam, please see this preprint for more details)
papers about methods and tools papers about applications
More Experts Than Galaxies: Conditionally-overlapping Experts With Biologically-Inspired Fixed Routing Shaier S., Pereira F., von der Wense K., Hunter L. E., Jones M. in International Conference on Learning Representations, 2025 "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 "Causal inference in the closed-loop: marginal structural models for sequential excursion effects" Levis A., Loewinger G., Pereira F. to appear in Neural Information Processing Systems, 2024 "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 "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 "Manifold learning for fMRI time-varying functional connectivity" Gonzalez-Castillo J., Fernandez I., Lam K., Handwerker D., Pereira F., Bandettini P. Frontiers in Human Neuroscience, 2023; 17: 1134012 "VICE: Variational Interpretable Concept Embeddings" Muttenthaler L., Zheng C., McClure P., Vandermeulen R., Hebart M., Pereira F. in Proceedings of Neural Information Processing Systems, 2022 "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 "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 "Revealing interpretable object representations from human behavior" Zhen, C. Y., Pereira, F., Baker, C. I., Hebart, M. N. in Proceedings of the International Conference on Learning Representations, 2019 "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 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 "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. in Proceedings of Neural Information Processing Systems, 2018 "Distinct brain-wide presynaptic networks underlie the functional identity of individual cortical neurons" Inacio A. R., Lam K. C., Zhao Y., Pereira F., Gerfen C. R., Lee S. in press at Nature "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 press at Nature Mental Health "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 "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 "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. Journal of Medical Internet Research, Mental Health, 10 (1), 2023 "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 "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 "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 "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.s in Proceedings of the Cognitive Science Society Conference, 2021 [talk] 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 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 "Revealing the multidimensional mental representations of natural objects underlying human similarity judgments" Hebart, M., Zheng, C., Pereira, F., Baker, C. Nature Human Behaviour, 2020 "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 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 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

Prior publications

(from industry, postdoc, or graduate school)