Stephen José Hanson, SJ Hanson, Stephen J. Hanson
Stephen José Hanson, SJ Hanson, Stephen J. Hanson
Director RUBIC (Rutgers Brain Imaging Center), Professor of Psychology, Cognitive Science Center
Verified email at - Homepage
Cited by
Cited by
Comparing biases for minimal network construction with back-propagation
S Hanson, L Pratt
Advances in neural information processing systems 1, 1988
PyMVPA: A python toolbox for multivariate pattern analysis of fMRI data
M Hanke, YO Halchenko, PB Sederberg, SJ Hanson, JV Haxby, ...
Neuroinformatics 7 (1), 37-53, 2009
Discriminability-based transfer between neural networks
Pratt, Lorien Y and Hanson, SJ
Advances in Neural Information Processing Systems 5, 1993
Six problems for causal inference from fMRI
JD Ramsey, SJ Hanson, C Hanson, YO Halchenko, RA Poldrack, ...
neuroimage 49 (2), 1545-1558, 2010
Combinatorial codes in ventral temporal lobe for object recognition: Haxby (2001) revisited: is there a “face” area?
SJ Hanson, T Matsuka, JV Haxby
Neuroimage 23 (1), 156-166, 2004
Decoding the large-scale structure of brain function by classifying mental states across individuals
RA Poldrack, YO Halchenko, SJ Hanson
Psychological science 20 (11), 1364-1372, 2009
Arousal: its genesis and manifestation as response rate.
PR Killeen, SJ Hanson, SR Osborne
Psychological review 85 (6), 571, 1978
What connectionist models learn: Learning and representation in connectionist networks
SJ Hanson, DJ Burr
Behavioral and Brain Sciences 13 (3), 471-489, 1990
Nonlinear autoassociation is not equivalent to PCA
N Japkowicz, SJ Hanson, MA Gluck
Neural computation 12 (3), 531-545, 2000
PARSNIP: A connectionist network that learns natural language grammar from exposure to natural language sentences
SJ Hanson, J Kegl
Proceedings of the Eight Annual Meeting of the Cognitive Science Society …, 1987
Advancing functional connectivity research from association to causation
AT Reid, DB Headley, RD Mill, R Sanchez-Romero, LQ Uddin, ...
Nature neuroscience 22 (11), 1751-1760, 2019
Conceptual clustering, categorization, and polymorphy
SJ Hanson, M Bauer
Machine Learning 3 (4), 343-372, 1989
Brain reading using full brain support vector machines for object recognition: there is no “face” identification area
SJ Hanson, YO Halchenko
Neural Computation 20 (2), 486-503, 2008
Regulation during challenge: A general model of learned performance under schedule constraint.
SJ Hanson, W Timberlake
Psychological Review 90 (3), 261, 1983
Multi-subject search correctly identifies causal connections and most causal directions in the DCM models of the Smith et al. simulation study
JD Ramsey, SJ Hanson, C Glymour
NeuroImage 58 (3), 838-848, 2011
Central place foraging in Rattus norvegicus
PR Killeen, JP Smith, SJ Hanson
Animal Behaviour 29 (1), 64-70, 1981
Interface design and multivariate analysis of UNIX command use
SJ Hanson, RE Kraut, JM Farber
ACM Transactions on Information Systems (TOIS) 2 (1), 42-57, 1984
PyMVPA: a unifying approach to the analysis of neuroscientific data
M Hanke, YO Halchenko, PB Sederberg, E Olivetti, I Fründ, JW Rieger, ...
Frontiers in neuroinformatics 3, 3, 2009
Multivariate analysis of Drosophila courtship
TA Markow, SJ Hanson
Proceedings of the National Academy of Sciences 78 (1), 430-434, 1981
Minkowski-r back-propagation: Learning in connectionist models with non-euclidian error signals
S Hanson, D Burr
Neural information processing systems, 1987
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