Brain Image Analysis Research Group


"A Compositional and Interpretable Semantic Space", Alona Fyshe, Leila Wehbe, Partha P. Talukdar, Brian Murphy, and Tom Mitchell. The 2015 Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies, Denver, CO, (NAACL 2015, long paper). Supporting Website

"Simultaneously uncovering the patterns of brain regions involved in different story reading subprocesses", Leila Wehbe, Brian Murphy, Partha Talukdar, Alona Fyshe, Aaditya Ramdas and Tom Mitchell. PLOS ONE, 2014. Supplementary Material, Supporting Website

"Aligning context-based statistical models of language with brain activity during reading", Leila Wehbe, Ashish Vaswani, Kevin Knight and Tom Mitchell. Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP 2014, long paper). Supporting Website

"Interpretable Semantic Vectors from a Joint Model of Brain- and Text-Based Meaning", Alona Fyshe, Partha P. Talukdar, Brian Murphy and Tom Mitchell. Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL 2014, long paper). Supporting Website

"Documents and Dependencies: an Exploration of Vector Space Models for Semantic Composition", Alona Fyshe, Partha Talukdar, Brian Murphy and Tom Mitchell. International Conference on Computational Natural Language Learning (CoNLL 2013), Sofia, Bulgaria. Supplementary Material

"Learning Effective and Interpretable Semantic Models using Non-Negative Sparse Embedding", Brian Murphy, Partha Talukdar, Tom Mitchell. International Conference on Computational Linguistics (COLING 2012), Mumbai, India. [ Slides ] Supplementary Material

"Machine Learning and Interpretation in Neuroimaging", Georg Langs, Irina Rish, Mortiz Grosse-Wentrup and Brian Murphy, 2012 (eds): Machine Learning and Interpretation in Neuroimaging, Lecture Notes in Computer Science, Vol. 7263, Springer Verlag.

"Tracking Neural Coding of Perceptual and Semantic Features of Concrete Nouns", Gustavo Sudre, Dean Pomerleau, Mark Palatucci, Leila Wehbe, Alona Fyshe, Riitta Salmelin and Tom Mitchell, NeuroImage, 2012 Aug 1;62(1):451-63.

"Selecting Corpus-Semantic Models for Neurolinguistic Decoding", Brian Murphy, Partha Talukdar and Tom Mitchell, Proceedings of the First Joint Conference on Lexical and Computational Semantics (*SEM), Pages 114-123, June 2012.

"Hierarchical Latent Dictionaries for Models of Brain Activation" Alona Fyshe, Emily Fox, David Dunson and Tom Mitchell, International Conference on Artificial Intelligence and Statistics, 2012.

"Decoding Semantics across fMRI sessions with with Different Stimulus Modalities - A practical MVPA Study", Hiroyuki Akama, Brian Murphy, Li Na, Yumiko Shimizu, and Massimo Poesio, Frontiers in Neuroinformatics, 6:24, 24 August 2012. doi: 10.3389/fninf.2012.00024.

"A Neurosemantic Theory of Concrete Noun Representation Based on the Underlying Brain Codes", Marcel A. Just, Vladimir L. Cherkassky, Sandesh Aryal, Tom M. Mitchell, PLoS ONE 5(1): e8622 DOI: 10.1371/journal.pone.0008622,  January 13, 2010.

"Zero-Shot Learning with Semantic Output Codes", M. Palatucci, D. Pomerleau, G. Hinton, T. Mitchell Neural Information Processing Systems (NIPS),2009.

"Integrating Multiple-Study Multiple-Subject fMRI Datasets Using Canonical Correlation Analysis", I. Rustandi, M.A. Just, T.M. Mitchell. Proceedings of the MICCAI 2009 Workshop: Statistical modeling and detection issues in intra- and inter-subject functional MRI data analysis. September 2009.

"Blockwise Coordinate Descent Procedures for the Multi-task Lasso, with Applications to Neural Semantic Basis Discovery", H. Liu, M. Palatucci, and J. Zhang International Conference on Machine Learning (ICML),2009. received Best Student Paper Award and Best Overall Paper Honorable Mention

"Modeling fMRI data generated by overlapping cognitive processes with unknown onsets using Hidden Process Models", R.A. Hutchinson, R.S. Niculescu, T.A. Keller, I. Rustandi, T.M. Mitchell, NeuroImage (2009), doi: 10.1016/j.neuroimage.2009.01.025.

"Predicting Human Brain Activity Associated with the Meanings of Nouns", T. M. Mitchell, S. V. Shinkareva, A. Carlson, K.M. Chang, V. L. Malave, R. A. Mason, and M. A. Just, Science, 320, 1191, May 30, 2008. DOI: 10.1126/science.1152876. Supporting Online Material, Supporting website.

"Computational Models of Neural Representations in the Human Brain", (extended abstract) T.M. Mitchell,  DS 2008, Lecture Notes in Artificial Intelligence 5255, J.-F. Boulicaut, M.R. Berthold, and T. Horvarth (Eds.), Springer-Verlag Berlin Heidelberg, pp. 26–27, 2008.

Discovering a Semantic Basis of Neural Activity Using Simultaneous Sparse Approximation", M. Palatucci, T.M. Mitchell, and H. Liu International Conference on Machine Learning (ICML)-Sparse Optimization and Variable Selection Workshop,2008.

On the Chance Accuracies of Large Collections of Classifiers", Mark Palatucci and Andrew Carlson International Conference on Machine Learning (ICML),2008.

"Using fMRI Brain Activation to Identify Cognitive States Associated with Perception of Tools and Dwellings",  S.V. Shinkareva, R.A. Mason, V.L. Malave, W. Wang, T. M. Mitchell, and M. A. Just, PLoS ONE 3(1): e1394. doi:10.1371/journal.pone.0001394, January 2, 2008.

"Classification in Very High Dimensional Problems with Handfuls of Examples", Mark Palatucci and Tom Mitchell, Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD). September 2007.

"Classifying Multiple-Subject fMRI Data Using the Hierarchical Gaussian Naïve Bayes Classifier", Indrayana Rustandi, 13th Conference on Human Brain Mapping. June 2007.

"Hidden Process Models", Rebecca Hutchinson, Tom M. Mitchell, Indrayana Rustandi, 23rd International Conference on Machine Learning. June 2006.

"The Support Vector Decomposition Machine" , F. Pereira, G. Gordon, 23rd International Conference on Machine Learning. June 2006.

"Decoding of semantic category information from single trial fMRI activation in response to word stimuli, using searchlight voxel selection" , F. Pereira, R. Mason, M. Just, T. Mitchell, N. Kriegeskorte, 12th Conference on Human Brain Mapping. June 2006.

"Hidden Process Models", Tom M. Mitchell, Rebecca Hutchinson, Indrayana Rustandi, CMU Technical Report CS-CALD-05-116. February 17, 2006.

"Learning to Identify Overlapping and Hidden Cognitive Processes from fMRI Data", R. Hutchinson, T.M. Mitchell, I. Rustandi, 11th Conference on Human Brain Mapping. June 2005.

"Learning to Decode Cognitive States from Brain Images", T.M. Mitchell, R. Hutchinson, R.S. Niculescu, F.Pereira, X. Wang, M. Just, and S. Newman, Machine Learning, Vol. 57, Issue 1-2, pp. 145-175. October 2004.

"Training fMRI Classifiers to Discriminate Cognitive States across Multiple Subjects", X. Wang, R. Hutchinson, and T. M. Mitchell, Neural Information Processing Systems 2003. December 2003.

"Classifying Instantaneous Cognitive States from fMRI Data", T. Mitchell, R. Hutchinson, M. Just, R.S. Niculescu, F. Pereira, X. Wang, American Medical Informatics Association Symposium, October 2003. (received Best Foundational Paper Award)

"Distinguishing natural language processes on the basis of fMRI-measured brain activation", F. Pereira, M. Just, T. Mitchell, PKDD 2001, Freiburg, Germany, 2001.

Working Papers:

Learning to Identify Part of Speech from Brain Image Data, (studies feasibility of detecting part of speech of individual words in sentences, from MEG neural activity), Arshit Gupta, Masters student Independent Study project, May 2015.

Using Machine Learning to Predict Human Brain Activity, (compares learned models across studies, and across subjects), Mahtiyar Bonakdarpour, Undergraduate Senior Thesis, May 2009.

Temporal Feature Selection for fMRI Analysis, Mark Palatucci, Working Paper, February 2007.

Understanding Feature Selection in Functional Magnetic Resonance Imaging, J. Pujara, Master's thesis, Computer Science Dept., Carnegie Mellon University, May 2005.

Learning Common Features from fMRI Data of Multiple Subjects, J. Ramish, Summer Undergraduate Project Report, August 2004.

Using machine learning to detect cognitive states across multiple subjects, X. Wang, CALD KDD Project report, May, 2003.