The HaxbyLab@Dartmouth

James V. Haxby

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James V. Haxby

Professor

Contact

Address:6207 Moore Hall, Rm447 Hanover, NH 03755
Email:james.v.haxby@dartmouth.edu

Research focus

My current research focuses on the development of computational methods for building models of representational spaces. We assume that distributed population responses encode information. Within a cortical field, a broad range of stimuli or cognitive states can be represented as different patterns of response. We use fMRI to measure these patterns of response and multivariate pattern (MVP) analysis to decode their meaning. We are currently developing methods that make it possible to decode an individual’s brain data using MVP classifiers that are based on other subjects’ data. We use a complex, natural stimulus to sample a broad range of brain representational states as a basis for building high-dimensional models of representational spaces within cortical fields. These models are based on response tuning functions that are common across subjects. Initially, we demonstrated the validity of such a model in ventral temporal cortex. We are working on building similar models in other visual areas and in auditory areas. We also plan to investigate representation of social cognition using this same conceptual framework.

Publications

Articles

[CSG+13]Conroy, B. R., Singer, B. D., Guntupalli, J. S. , Ramadge, P. J. and Haxby, J. V. (2013). Inter-subject alignment of human cortical anatomy using functional connectivity. NeuroImage, 81, 400-411. [PDF] [URL] DOI: 10.1016/j.neuroimage.2013.05.009
[KFR+13]Kohler, P. J., et al. (2013). Pattern classification precedes region-average hemodynamic response in early visual cortex.. Neuroimage, 78C, 249-260. [PDF] DOI: 10.1016/j.neuroimage.2013.04.019
[AWC+12]Abdi, H., Williams, L. J., Connolly, A. C. , Gobbini, M. I. , Dunlop, J. P. and Haxby, J. V. (2012). Multiple Subject Barycentric Discriminant Analysis (MUSUBADA): How to assign scans to categories without using spatial normalization. Computational and Mathematical Methods in Medicine, 2012, 1-15. [PDF] DOI: 10.1155/2012/634165, cited by: 4
[CGG+12]Connolly, A. C. , Guntupalli, J. S. , Gors, J. , Hanke, M. , Halchenko, Y. O., Wu, Y. , Abdi, H. and Haxby, J. V. (2012). Representation of biological classes in the human brain. Journal of Neuroscience, 32, 2608-2618. [PDF] DOI: 10.1523/JNEUROSCI.5547-11.2012, cited by: 16
[Hax12]Haxby, J. V. (2012). Multivariate pattern analysis of fMRI: The early beginnings. NeuroImage, In press. DOI: 10.1016/j.neuroimage.2012.03.016, cited by: 3
[WHH12]Wagner, D. D. , Haxby, J. V. and Heatherton, T. F. (2012). The Representation of Self and Person Knowledge in the Medial Prefrontal Cortex. Wiley Interdisciplinary Reviews:Cognitive Science, 3, 451-470. cited by: 3
[HGC+11]Haxby, J. V. , Guntupalli, J. S. , Connolly, A. C. , Halchenko, Y. O. , Conroy, B. R., Gobbini, M. I. , Hanke, M. and Ramadge, P. J. (2011). A Common, High-Dimensional Model of the Representational Space in Human Ventral Temporal Cortex. Neuron, 72, 404-416. [PDF] [PDF:Supp] DOI: 10.1016/j.neuron.2011.08.026, cited by: 21
[ENO+10]Engell, A. D., Nummenmaa, L., Oosterhof, N. N. , Henson, R. N., Haxby, J. V. and Calder, A. J. (2010). Differential activation of frontoparietal attention networks by social and symbolic spatial cues. Social cognitive and affective neuroscience, 5, 432-440. [PDF] DOI: 10.1093/scan/nsq008, cited by: 16
[SSC+10]Sabuncu, M. R., Singer, B. D., Conroy, B., Bryan, R. E., Ramadge, P. J. and Haxby, J. V. (2010). Function-based intersubject alignment of human cortical anatomy. Cereb Cortex, 20, 130-40. [PDF] DOI: 10.1093/cercor, cited by: 38
[SME+10]Said, C. P., Moore, C. D., Engell, A. D., Todorov, A. and Haxby, J. V. (2010). Distributed representations of dynamic facial expressions in the superior temporal sulcus. J Vis, 10. [PDF] DOI: 10.1167/10.5.11
[HHS+09a]Hanke, M. , Halchenko, Y. O. , Sederberg, P. B., Hanson, S. J., Haxby, J. V. and Pollmann, S. (2009). PyMVPA: A Python toolbox for multivariate pattern analysis of fMRI data. Neuroinformatics, 7, 37-53. [PDF] DOI: 10.1007/s12021-008-9041-y, cited by: 70
[HHS+09b]Hanke, M. , et al. (2009). PyMVPA: A Unifying Approach to the Analysis of Neuroscientific Data. Frontiers in Neuroinformatics, 3, 3. [PDF] DOI: 10.3389/neuro.11.003.2009, cited by: 36
[MSH09]Montgomery, K. J., Seeherman, K. R. and Haxby, J. V. (2009). The well-tempered social brain. Psychol Sci, 20, 1211-3. [PDF] DOI: 10.1111/j.1467-9280.2009.02428.x
[Hax06]Haxby, J. V. (2006). Fine structure in representations of faces and objects. Nature Neuroscience, 9, 1084-6.
[OJA+05]O, (2005). Partially Distributed Representations of Objects and Faces in Ventral Temporal Cortex. Journal of Cognitive Neuroscience, 17, 580-590. [PDF] DOI: 10.1162/0898929053467550, cited by: 178
[HMH04]Hanson, S. J., Matsuka, T. and Haxby, J. V. (2004). Combinatorial codes in ventral temporal lobe for object recognition: Haxby (2001) revisited: is there a “face’’ area?. NeuroImage, 23, 156-166. [PDF] DOI: 10.1016/j.neuroimage.2004.05.020, cited by: 173
[HHG02]Haxby, J. V. , Hoffman, E. A. and Gobbini, M. I. (2002). Human neural systems for face recognition and social communication. Biological psychiatry, 51, 59-67. [PDF], cited by: 631
[HGF+01]Haxby, J. V. , Gobbini, M. I. , Furey, M. L., Ishai, A., Schouten, J. L. and Pietrini, P. (2001). Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science, 293, 2425-2430. [PDF] [PDF:Supp] DOI: 10.1126/science.1063736, cited by: 1531
[HPU+00]Haxby, J. V. , Petit, L., Ungerleider, L. G. and Courtney, S. M. (2000). Distinguishing the functional roles of multiple regions in distributed neural systems for visual working memory.. Neuroimage, 11, 145-56. [PDF] DOI: 10.1006/nimg.1999.0527, cited by: 258
[IUH00]Ishai, A., Ungerleider, L. G. and Haxby, J. V. (2000). Distributed neural systems for the generation of visual images. Neuron, 28, 979-90. [PDF] DOI: 10.1016/S0896-6273(00)00168-9, cited by: 357
[CMH99]Chao, L. L., Martin, A. and Haxby, J. V. (1999). Are face-responsive regions selective only for faces?. Neuroreport, 10, 2945-50. cited by: 134
[HUC+99]Haxby, J. V. , Ungerleider, L. G., Clark, V. P., Schouten, J. L., Hoffman, E. A. and Martin, A. (1999). The effect of face inversion on activity in human neural systems for face and object perception.. Neuron, 22, 189-99. [PDF] DOI: 10.1016/S0896-6273(00)80690-X, cited by: 425
[CMH98]Clark, V. P., Maisog, J. M. and Haxby, J. V. (1998). fMRI study of face perception and memory using random stimulus sequences. J Neurophysiol, 79, 3257-65. [PDF] [URL], cited by: 132
[CPM+98]Courtney, S. M., Petit, L., Maisog, J. M., Ungerleider, L. G. and Haxby, J. V. (1998). An area specialized for spatial working memory in human frontal cortex. Science, 279, 1347-51. [PDF] DOI: 10.1126/science.279.5355.1347, cited by: 747
[CUK+97]Courtney, S. M., Ungerleider, L. G., Keil, K. and Haxby, J. V. (1997). Transient and sustained activity in a distributed neural system for human working memory. Nature, 386, 608-11. [PDF] DOI: 10.1038/386608a0, cited by: 754
[HUH+96]Haxby, J. V. , Ungerleider, L. G., Horwitz, B., Maisog, J. M., Rapoport, S. I. and Grady, C. L. (1996). Face encoding and recognition in the human brain.. Proc Natl Acad Sci U S A, 93, 922-7. [PDF] [URL], cited by: 431
[MBH+96]McIntosh, A. R., Bookstein, F. L., Haxby, J. V. and Grady, C. L. (1996). Spatial pattern analysis of functional brain images using partial least squares. Neuroimage, 3, 143-57. [PDF] [URL], cited by: 612
[HHU+94]Haxby, J. V. , Horwitz, B., Ungerleider, L. G., Maisog, J. M., Pietrini, P. and Grady, C. L. (1994). The functional organization of human extrastriate cortex: a PET-rCBF study of selective attention to faces and locations. J Neurosci, 14, 6336-53. [PDF] [URL], cited by: 971
[HPL+93]Haxby, J. V. , Parasuraman, R., Lalonde, F. and Abboud, H. (1993). SuperLab: General-purpose Macintosh software for human experimental psychology and psychological testing. Behavior Research Methods Instruments and Computers, 25, 400-400. [PDF]
[HGH+91]Haxby, J. V. , et al. (1991). Dissociation of object and spatial visual processing pathways in human extrastriate cortex.. Proc Natl Acad Sci U S A, 88, 1621-5. [PDF] [URL], cited by: 744

Posters

[GH11]Guntupalli, J. S. and Haxby, J. (2011). Deriving a neural basis for ventral temporal cortex. Journal of Vision, 11, 880-880. [PDF] [URL] DOI: 10.1167/11.11.880
[GH10]Guntupalli, J. S. , Connolly, A. C. and Haxby, J. V. (2010). In search of functional brain atlases: Deriving common categorical representational patterns across individuals in ventral visual pathway. Journal of Vision, 10, 978. [PDF] [URL] DOI: 10.1167/10.7.978

Review Articles

[HHH+10]Hanke, M. , Halchenko, Y. O. , Haxby, J. V. and Pollmann, S. (2010). Statistical learning analysis in neuroscience: aiming for transparency. Frontiers in Neuroscience, 4, 38-43. [PDF] DOI: 10.3389/neuro.01.007.2010
[NPD+06]Norman, K. A., Polyn, S. M., Detre, G. J. and Haxby, J. V. (2006). Beyond mind-reading: multi-voxel pattern analysis of fMRI data. Trends in Cognitive Science, 10, 424-430. [PDF] DOI: 10.1016/j.tics.2006.07.005, cited by: 650
[HHG00]Haxby, J. V. , Hoffman, E. A. and Gobbini, M. I. (2000). The distributed human neural system for face perception. Trends Cogn Sci, 4, 223-233. [PDF] DOI: 10.1016/S1364-6613(00)01482-0, cited by: 1972

Book Chapters

[CGH12]Connolly, A. C. , Gobbini, M. I. and Haxby, J. V. (2012). Understanding visual population codes: Toward a common multivariate framework for cell recording and functional imaging. In Kriegeskorte, N. and Kreiman, G. (Eds.) (pp. ): MIT Press. cited by: 3
[HG11]Haxby, J. V. and Gobbini, M. I. (2011). Oxford Handbook of Face Perception. In Rhodes, Gillian and Calder, Andy and Johnson, Mark and Haxby, James V. (Eds.) (pp. ): Oxford University Press. [PDF], cited by: 6

Collection Chapters

[CSH+09]Conroy, B., Singer, B. D., Haxby, J. V. and Ramadge, P. J. (2009). fMRI-Based Inter-Subject Cortical Alignment Using Functional Connectivity. In Bengio, Y. and Schuurmans, D. and Lafferty, J. and Williams, C. K. I. and Culotta, A. (Eds.) Advances in Neural Information Processing Systems 22 (pp. 378-386). [PDF]

Miscelaneous

Posters

[CSG+HBM13]Connolly, A. C. , Sha, L., Gobbini, M. I. and Haxby, J. V. (2013). Decoding representations of actions of other species using multivariate pattern analysis. . [PDF] [URL]
[CSG+VSS13]Connolly, A. C. , Sha, L., Gobbini, M. I. and Haxby, J. V. (2013). Representations of action categories generalize across the phylum, genus, and species of the actor. . [PDF] [URL]
[GH_OHBM13]Guntupalli, J. S. and Haxby, J. V. (2013). Facilitating functional brain atlases using searchlight-based inter-subject hyperalignment.. . [PDF] [URL]
[CGG+SFN12]Connolly, A. C. , Guntupalli, J. S. , Gors, J. and Haxby, J. V. (2012). Decoding categorical representations of human actions from brain activity associated with viewing point-light movies. . [PDF] [URL]
[SHC_SFN12]Sha, L., Haxby, J. V. and Connolly, A. C. (2012). The representation of object categories along an animacy continuum in the human visual system. . [PNG] [URL]
[CGH+11]Connolly, A. C. , Guntupalli, J. S. , Hanke, M. , Gobbini, M. I. and Haxby, J. V. (2011). More or less human: The animate-inanimate distinction in visual cortex may be more continuum than distinction. . [PNG] [URL]
[CWH+11]Connolly, A. C. , Wu, Y. , Halchenko, Y. O. , Guntupalli, J. S. and Haxby, J. V. (2011). Scanning parameters for optimal decoding using a 32-channel head coil for fMRI. . [PNG] [URL]
[CH10a]Connolly, A. C. and Haxby, J. V. (2010). Similarity-based pattern analysis reveals an emergent taxonomy of animal species along the object vision pathway. . [URL]
[CH10b]Connolly, A. C. and Haxby, J. V. (2010). Neural similarity reveals taxonomic organization for animate categories in object-vision pathway. . [URL]
[CH10c]Connolly, A. C. and Haxby, J. V. (2010). Similarity-based multi-voxel pattern analysis reveals an emergent taxonomy of animal species along the object vision pathway. . [URL]
[GCH10a]Guntupalli, J. S. , Connolly, A. C. and Haxby, J. V. (2010). Deriving universal neural representational space of objects. . [PDF] [URL]
[GCH10b]Guntupalli, J. S. , Connolly, A. C. and Haxby, J. V. (2010). Inter-subject hyperalignment of neural representational spaces to derive common categorical patterns. . [PDF] [URL]
[GCH10c]Guntupalli, J. S. , Connolly, A. C. and Haxby, J. V. (2010). In search of functional brain atlases: Deriving common categorical representational patterns across individuals in ventral visual pathway. . [PDF] [URL]
[GH_CNS10]Guntupalli, J. S. and Haxby, J. V. (2010). In search of a common representational space for decoding: comparing anatomical alignment, functional voxel matching, and hyperalignment.. . [PDF] [URL]
[HHH10]Hanke, M. , Halchenko, Y. O. , Haxby, J. V. and Pollmann, S. (2010). Improving efficiency in cognitive neuroscience research with NeuroDebian. . [PDF] `[URL] <Poster presented at the annual meeting of the Cognitive Neuroscience Society, Montr{\’{e}}al, Canada>`__
[GH_CAOS10]J Swaroop Guntupalli, A. C. C. and Haxby, J. V. (2010). Deriving universal neural representational space of objects. . [PDF] [URL]
[GH_SFN09]Guntupalli, J. S. and Haxby, J. V. (2009). Inter-subject hyperalignment of neurl representational space.. . [PDF] [URL]
[DPM+06]Detre, G., Polyn, S. M., Moore, C. D., Natu, V. S., Singer, B. D., Cohen, J. D., Haxby, J. V. and Norman, K. A. (2006). The Multi-Voxel Pattern Analysis (MVPA) toolbox. . [URL]

Talks

[Gun13]Guntupalli, J. S. , Connolly, A. C. and Haxby, J. (2013). Exploring the scale of common dimensions of information decoding in human ventral temporal cortex. . [PDF] [URL]
[Gun11]Guntupalli, J. S. and Haxby, J. (2011). Inter-subject hyperalignment of neural representational spaces in the auditory cortex. . [PNG] [URL]
[Gun10a]Guntupalli, J. S. , Connolly, A. C. and Haxby, J. (2010). Inter-subject hyperalignment of neural representational spaces to derive common categorical patterns. . [PDF] [URL]
[Gun10b]Guntupalli, J. S. and Haxby, J. (2010). Deriving universal neural representational spaces for decoding brain states. . [PDF] [URL]

References

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