A full list of publications can be found here on Google Scholar.
| Cognition | We use fMRI to explain and predict individual differences in behavior.
Finn, E.S., Shen, X., Scheinost, D., Rosenberg, M.D., Chun, M.M., Papademetris, X., & Constable, R.T. (2015). Functional connectome fingerprinting: Identification of individuals using patterns of brain connectivity. Nature Neuroscience, 18, 1664-1671. Rosenberg, M. D., Finn, E. S., Scheinost, D., Constable, R. T., & Chun, M. M. (2017). Characterizing attention with predictive network models. Trends in Cognitive Sciences, 21, 290-302. Yoo, K., Rosenberg, M.D., Hsu, W.-T, Zhang, S., Li, C.-S.R., Scheinost, D., Constable, R.T., & Chun, M.M. (2018). Connectome-based predictive modeling of attention: Comparing different functional connectivity features and prediction methods across datasets. Neuroimage, 167, 11-22. |
| Attention | We are developing methods to quantify attentional performance based on whole brain functional connectivity and multivoxel pattern analysis. Our models can even predict ADHD symptoms from resting state scans.
Rosenberg, M.D., Finn, E.S., Scheinost, D., & Papademetris, X., Shen, X., Constable, R.T., & Chun, M.M. (2015). A neuromarker of sustained attention from whole-brain functional connectivity. Nature Neuroscience, 19, 165-171. Rosenberg, M.D., Scheinost, D., Greene, A.S., Avery, E.W., Kwon, Y.H., Finn, E.S., Ramani, R., Qiu, M., Constable, R.T., & Chun, M.M. (2020). Functional connectivity predicts change in attention observed across minutes, days, and months. PNAS, 117, 3797-3807. Chun, M.M., Golomb, J.D., Turk-Browne, N.B. (2011). A Taxonomy of External and Internal Attention. Annual Review of Psychology, 62, 73-101. [pdf] |
| Memory | We view memory as enduring traces of attentional processing, such that the study of attention and memory are tightly related.
Lin, Q., Yoo, K., Shen, X., Constable, T.R., Chun, M.M. (2021). Functional connectivity during encoding predicts individual differences in long-term memory. Journal of Cognitive Neuroscience. Chun, M.M., & Johnson, M.K. (2011). Memory: Enduring traces of perceptual and reflective attention. Neuron, 72, 520-35. PMID: 22099456. [pdf] |
| Perception | We’re interested in the nature of perceptual representations to decode the mind and to predict behavior.
Cowen, A.S., Chun, M.M., & Kuhl, B.A. (2014). Neural portraits of perception: Reconstructing face images from evoked brain activity. Neuroimage. [pdf] [press] Mocz, V., Vaziri-Passhkam, M., Chun, M.M., & Xu, Y. (2021). Predicting identity-preserving object transformations across the human ventral visual stream, Journal of Neuroscience, 41, 7403-7419. O’Connell, T., & Chun, M.M. (2018). Predicting eye movement patterns from fMRI responses to natural scenes. Nature Communications, 9, 5159. |
| Funding | The lab is grateful to have been supported by the NIH, NSF, and Yale. |