Who

Where

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 the Computer Science Department at CMU, working with Tom Mitchell and Geoff Gordon. I was also a student in the graduate training program of the Center for the Neural Basis of Cognition, working in collaboration with the Center for Cognitive Brain Imaging. I got my undergraduate degree at the Computer Science Department of the University of Porto, in Portugal.

What

My personal scientific interest 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 from our research group

preprints under review
"Causal inference in the closed-loop: marginal structural models for sequential excursion effects" Levis A., Loewinger G., Pereira F. "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. "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. "A Statistical Framework for Analysis of Trial-Level Temporal Dynamics in Fiber Photometry Experiments" Loewinger G., Cui E., Lovinger D., 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. “Interpretable factorization of clinical questionnaires to identify latent factors of psychopathology” Lam K. C., Mahony B. W., Raznahan A., Pereira F.
methods and tools	applications
"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 "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	"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 "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 "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

software from our research group

• fastFMM: Fast Functional Mixed Models using Fast Univariate Inference
  (the primary developer is Gabe Loewinger)
• VICE toolbox for creating interpretable item embeddings from odd-one-out triplet task judgments
  (the primary developer is Lukas Muttenthaler, please see VICE paper for the method we developed jointly with him)

past publications

• "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
• "A comparative evaluation of off-the-shelf distributed semantic representations for modelling behavioural data"
  
  Pereira F., Gershman S., Ritter S., Botvinick M.
  Cognitive Neuropsychology 33.3-4: 175-190, 2016
• "Simitar: simplified searching of statistically significant similarity structure"
  
  Pereira F., Botvinick M.
  in Proceedings of Pattern Recognition in Neuroimaging, 2013
• "Creating group-level functionally-defined atlases for diagnostic classification"
  
  Pereira F., Walz J. M., Cetingul H. E., Sudarsky S., Nadar M., Prakash R.
  in Proceedings of Pattern Recognition in Neuroimaging, 2013
• "A systematic approach to extracting semantic information from functional MRI data"
  
  Pereira F., Botvinick M.
  in Proceedings of the Neural Information Processing Systems conference, 2012
• "Distinguishing grammatical constructions with fMRI pattern analysis"
  
  Allen K., Pereira F., Botvinick M, Goldberg A.
  Brain and Language 123.3: 174-182 (2012)
• "Using Wikipedia to produce semantic feature representations of concrete concepts in neuroimaging experiments"
  
  Pereira F., Detre G., Botvinick M.
  Artificial Intelligence Journal, 194: 240-252 (2013)
• "Network, anatomical, and non-imaging measures for the prediction of ADHD diagnosis in individual subjects"
  
  Bohland F., Saperstein S. Pereira F., Rapin J., Grady L.
  Frontiers in Systems Neuroscience 6:78 (2012)
• "Generating text from functional brain images"
  
  Pereira F., Detre G., Botvinick M.
  Frontiers in Human Neuroscience 5:72
  

  Supplementary material (visualizations of the topic model used in the paper)

  Morgan Kelly wrote a nice article describing the research and it was mentioned in a few media outlets and sites: Economist, MSNBC, Fox, Popular Science, Engadget, Slashdot

• "Classification of functional magnetic resonance imaging data using informative pattern features"
  
  Pereira F., Botvinick M.
  Proceedings of the 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2011
• "A topographic latent source model for fMRI data"
  
  Gershman, S.J., Blei, D.M., Pereira, F., & Norman, K.A.
  NeuroImage, 57, 89-100, 2011
• "Information mapping with pattern classifiers: a comparative study"
  
  Pereira F., Botvinick M.
  NeuroImage, Volume 56, Issue 2, Pages 385-850, May 2011
  
• "Reproducibility Distinguishes Conscious from Nonconscious Neural Representations"
  
  Schurger A., Pereira F., Treisman A., Cohen J.D.
  Science, 1 January 2010 327: 97-99
• "Machine learning classifiers and fMRI: a tutorial overview"
  
  Pereira F., Mitchell T., Botvinick M..
  NeuroImage, Volume 45, Issue 1, Supplement 1, March 2009, Pages S199-S209
  
• "Beyond Brain Blobs:
  Machine Learning Classifiers as Instruments for Analyzing Functional Magnetic Resonance Imaging Data"
  
  Pereira F.
  Ph.D. thesis, CMU-CS-07-175
  Computer Science Department and Center for the Neural Basis of Cognition, Carnegie Mellon University, December 2007
  [divided by chapters]

  Coming soon...
• "Closed-form supervised dimensionality reduction with generalized linear models"
  
  Rish I., Grabarnik G., Cecchi G., Pereira F., Gordon G.
  International Conference on Machine Learning, 2007
  
• "The Support Vector Decomposition Machine"
  
  Pereira F., Gordon G.
  International Conference on Machine Learning, 2006
  
• "Exploring predictive and reproducible modeling with the single-subject FIAC data set"
  
  Chen X., Pereira F., Lee W., Strother S., Mitchell T.
  Human Brain Mapping
  
• "Learning to Decode Cognitive States from Brain Images"
  
  Mitchell T., Hutchinson R., Niculescu S., Pereira F., Wang X., Just M., Newman S.
  Machine Learning Journal, Vol. 57, Issue 1-2, pp. 145-175, 2004
  
• "Detecting Significant Multidimensional Spatial Clusters"
  
  Neill D., Moore A.,Pereira F., Mitchell T.
  Proceedings of Neural Information Processing Systems 2004
  
• "Classifying Instantaneous Cognitive States from fMRI Data"
  
  Mitchell T., Hutchinson R., Niculescu S., Pereira F., Wang X., Just M., Newman S.
  Proceedings of AMIA 2003 (Best Foundational Paper Award)
  
• "Concise, Intelligible, and Approximate Profiling of Multiple Classes"
  
  Valdes-Perez R., Pericliev V. and Pereira F.
  International Journal of Human Computer Systems, 53(3):411-436, 2000