Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
Parallel Models of Associative Memory
Parallel Models of Associative Memory
The Representation of Objects in the Human Occipital and Temporal Cortex
Journal of Cognitive Neuroscience
Partially Distributed Representations of Objects and Faces in Ventral Temporal Cortex
Journal of Cognitive Neuroscience
Using Image Stimuli to Drive fMRI Analysis
Neural Information Processing
GLM and SVM analyses of neural response to tonal and atonal stimuli: new techniques and a comparison
Connection Science - Music, Brain, Cognition
Bayesian Reconstruction of Perceptual Experiences from Human Brain Activity
FAC '09 Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009
Generalized sparse classifiers for decoding cognitive states in fMRI
MLMI'10 Proceedings of the First international conference on Machine learning in medical imaging
Towards one-class pattern recognition in brain activity via neural networks
MICAI'10 Proceedings of the 9th Mexican international conference on Artificial intelligence conference on Advances in soft computing: Part II
Reaction time for object categorization is predicted by representational distance
Journal of Cognitive Neuroscience
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Object perception has been a subject of extensive fMRI studies in recent years. Yet the nature of the cortical representation of objects in the human brain remains controversial. Analyses of fMRI data have traditionally focused on the activation of individual voxels associated with presentation of various stimuli. The current analysis approaches functional imaging data as collective information about the stimulus. Linking activity in the brain to a stimulus is treated as a pattern-classification problem. Linear discriminant analysis was used to reanalyze a set of data originally published by Ishai et al. (2000), available from the fMRIDC (accession no. 2-2000-1113D). Results of the new analysis reveal that patterns of activity that distinguish one category of objects from other categories are largely independent of one another, both in terms of the activity and spatial overlap. The information used to detect objects from phase-scrambled control stimuli is not essential in distinguishing one object category from another. Furthermore, performing an object-matching task during the scan significantly improved the ability to predict objects from controls, but had minimal effect on object classification, suggesting that the task-based attentional benefit was non-specific to object categories.