Ka Chun Lam
Recent Publications
Characterizing Universal Object Representations Across Vision Models
Mahner F. P., Roth J., Lam K. C., Bonner M. F., Pereira F., Hebart M. N.
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. - in press at Nature Communications, 2026
Interpretable factorization of clinical questionnaires to identify latent factors of psychopathology
Lam K.C., Pereira F., Mahony B.W., Raznahan A. Transactions on Machine Learning Research 2026
Similarity-based representation factorization for revealing interpretable dimensions in representational data
Mahner F. P., Lam K. C., Pereira F., Hebart M. N.
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
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
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]
Software
MLC
Interpretability-Constrained Questionnaire Factorization
Tools for generating interpretable factors and loadings from questionnaire data.