Decoding the Brain: Neural Representation and the Limits of Multivariate Pattern Analysis in Cognitive Neuroscience
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[1] Russell A. Poldrack,et al. What do differences between multi-voxel and univariate analysis mean? How subject-, voxel-, and trial-level variance impact fMRI analysis , 2014, NeuroImage.
[2] H. P. Op de Beeck,et al. Dissociations and Associations between Shape and Category Representations in the Two Visual Pathways , 2015, The Journal of Neuroscience.
[3] Krish D. Singh,et al. Which “neural activity” do you mean? fMRI, MEG, oscillations and neurotransmitters , 2012, NeuroImage.
[4] Thomas A. Carlson,et al. Emerging Object Representations in the Visual System Predict Reaction Times for Categorization , 2015, PLoS Comput. Biol..
[5] Nikolaus Kriegeskorte,et al. Comparison of multivariate classifiers and response normalizations for pattern-information fMRI , 2010, NeuroImage.
[6] Peter Carruthers,et al. Opening Up Vision: The Case Against Encapsulation , 2016 .
[7] F. Tong,et al. Decoding reveals the contents of visual working memory in early visual areas , 2009, Nature.
[8] Fred I. Dretske,et al. Précis of Knowledge and the Flow of Information , 1983, Behavioral and Brain Sciences.
[9] R. Vogels,et al. Inferotemporal neurons represent low-dimensional configurations of parameterized shapes , 2001, Nature Neuroscience.
[10] Nikolaus Kriegeskorte,et al. Analyzing for information, not activation, to exploit high-resolution fMRI , 2007, NeuroImage.
[11] F. Tong,et al. Decoding the visual and subjective contents of the human brain , 2005, Nature Neuroscience.
[12] N. Kanwisher,et al. Only some spatial patterns of fMRI response are read out in task performance , 2007, Nature Neuroscience.
[13] F ATTNEAVE,et al. Dimensions of similarity. , 1950, The American journal of psychology.
[14] N. Logothetis. What we can do and what we cannot do with fMRI , 2008, Nature.
[15] S. Dehaene,et al. Characterizing the dynamics of mental representations: the temporal generalization method , 2014, Trends in Cognitive Sciences.
[16] J. Macke,et al. Neural population coding: combining insights from microscopic and mass signals , 2015, Trends in Cognitive Sciences.
[17] Nikolaus Kriegeskorte,et al. Reaction Time for Object Categorization Is Predicted by Representational Distance , 2014, Journal of Cognitive Neuroscience.
[18] Colin Klein,et al. Philosophical Issues in Neuroimaging , 2010 .
[19] P. Hanson. Information, language, and cognition , 1993 .
[20] R. Poldrack. Can cognitive processes be inferred from neuroimaging data? , 2006, Trends in Cognitive Sciences.
[21] P. Sajda,et al. Temporal characterization of the neural correlates of perceptual decision making in the human brain. , 2006, Cerebral cortex.
[22] Keiji Tanaka,et al. Matching Categorical Object Representations in Inferior Temporal Cortex of Man and Monkey , 2008, Neuron.
[23] Colin W. G. Clifford,et al. Discrimination of the local orientation structure of spiral Glass patterns early in human visual cortex , 2009, NeuroImage.
[24] Nicholas G Hatsopoulos,et al. The science of neural interface systems. , 2009, Annual review of neuroscience.
[25] Jeremy Freeman,et al. Orientation Decoding Depends on Maps, Not Columns , 2011, The Journal of Neuroscience.
[26] R. Dawes. Judgment under uncertainty: The robust beauty of improper linear models in decision making , 1979 .
[27] Omar H. Butt,et al. The Retinotopic Organization of Striate Cortex Is Well Predicted by Surface Topology , 2012, Current Biology.
[28] William Bechtel,et al. Representations and Cognitive Explanations: Assessing the Dynamicist's Challenge in Cognitive Science , 1998, Cogn. Sci..
[29] David Marr,et al. VISION A Computational Investigation into the Human Representation and Processing of Visual Information , 2009 .
[30] A. Ishai,et al. Distributed and Overlapping Representations of Faces and Objects in Ventral Temporal Cortex , 2001, Science.
[31] J. S. Guntupalli,et al. Decoding neural representational spaces using multivariate pattern analysis. , 2014, Annual review of neuroscience.
[32] David D. Cox,et al. Untangling invariant object recognition , 2007, Trends in Cognitive Sciences.
[33] Sean M. Polyn,et al. Beyond mind-reading: multi-voxel pattern analysis of fMRI data , 2006, Trends in Cognitive Sciences.
[34] W. T. Maddox,et al. A response time theory of separability and integrality in speeded classification , 1994 .
[35] Nicholas J. Priebe,et al. Mechanisms of Neuronal Computation in Mammalian Visual Cortex , 2012, Neuron.
[36] Janneke F. M. Jehee,et al. Attention Improves Encoding of Task-Relevant Features in the Human Visual Cortex , 2011, The Journal of Neuroscience.
[37] Chris Eliasmith,et al. Neural Engineering: Computation, Representation, and Dynamics in Neurobiological Systems , 2004, IEEE Transactions on Neural Networks.
[38] David D. Cox,et al. Functional magnetic resonance imaging (fMRI) “brain reading”: detecting and classifying distributed patterns of fMRI activity in human visual cortex , 2003, NeuroImage.
[39] Doris Y. Tsao,et al. Single-Unit Recordings in the Macaque Face Patch System Reveal Limitations of fMRI MVPA , 2015, The Journal of Neuroscience.
[40] D. Heeger,et al. BOLD and spiking activity , 2008, Nature Neuroscience.
[41] N. Kriegeskorte,et al. Author ' s personal copy Representational geometry : integrating cognition , computation , and the brain , 2013 .
[42] Keiji Tanaka,et al. Object category structure in response patterns of neuronal population in monkey inferior temporal cortex. , 2007, Journal of neurophysiology.
[43] N. Kriegeskorte,et al. Revealing representational content with pattern-information fMRI--an introductory guide. , 2009, Social cognitive and affective neuroscience.
[44] Andreas Bartels,et al. The Coding of Color, Motion, and Their Conjunction in the Human Visual Cortex , 2009, Current Biology.
[45] Janneke F. M. Jehee,et al. Less Is More: Expectation Sharpens Representations in the Primary Visual Cortex , 2012, Neuron.
[46] Jack L. Gallant,et al. Encoding and decoding in fMRI , 2011, NeuroImage.
[47] James V. Haxby,et al. Multivariate pattern analysis of fMRI: The early beginnings , 2012, NeuroImage.
[48] R. Shepard. Attention and the metric structure of the stimulus space. , 1964 .
[49] G. Rees,et al. Neuroimaging: Decoding mental states from brain activity in humans , 2006, Nature Reviews Neuroscience.
[50] Yevgeniy B. Sirotin,et al. Anticipatory haemodynamic signals in sensory cortex not predicted by local neuronal activity. , 2009, Nature.
[51] David D. Cox,et al. Do we understand high-level vision? , 2014, Current Opinion in Neurobiology.
[52] N. Logothetis,et al. Neurophysiological investigation of the basis of the fMRI signal , 2001, Nature.
[53] R. Poldrack,et al. Measuring neural representations with fMRI: practices and pitfalls , 2013, Annals of the New York Academy of Sciences.
[54] Nikolaus Kriegeskorte,et al. Perceptual similarity of visual patterns predicts dynamic neural activation patterns measured with MEG , 2016, NeuroImage.
[55] Takeshi Norimatsu,et al. Encoding and Decoding , 2016 .
[56] G. Rees,et al. Predicting the orientation of invisible stimuli from activity in human primary visual cortex , 2005, Nature Neuroscience.
[57] R. Goebel,et al. Human Object-Similarity Judgments Reflect and Transcend the Primate-IT Object Representation , 2013, Front. Psychol..
[58] John Duncan,et al. Multi-voxel coding of stimuli, rules, and responses in human frontoparietal cortex , 2011, NeuroImage.
[59] Stefania Bracci,et al. Dissociations and associations between shape and category representations in the two visual pathways. , 2015, Journal of vision.
[60] R. Poldrack,et al. Quantifying the internal structure of categories using a neural typicality measure. , 2014, Cerebral cortex.
[61] F. Tong,et al. Decoding Seen and Attended Motion Directions from Activity in the Human Visual Cortex , 2006, Current Biology.
[62] N. Kanwisher,et al. The Fusiform Face Area: A Module in Human Extrastriate Cortex Specialized for Face Perception , 1997, The Journal of Neuroscience.
[63] Thomas A. Carlson,et al. Neural Decoding and “Inner” Psychophysics: A Distance-to-Bound Approach for Linking Mind, Brain, and Behavior , 2016, Front. Neurosci..
[64] G. Piccinini,et al. Information without Truth , 2010 .
[65] David Kirsh,et al. When is Information Explicitly Represented , 1990 .
[66] S. Edelman,et al. Toward direct visualization of the internal shape representation space by fMRI , 1998, Psychobiology.
[67] A. Zador,et al. Neural representation and the cortical code. , 2000, Annual review of neuroscience.
[68] Tomaso Poggio,et al. Fast Readout of Object Identity from Macaque Inferior Temporal Cortex , 2005, Science.
[69] D. M. Green,et al. Signal detection theory and psychophysics , 1966 .
[70] Michael S. Pratte,et al. Decoding patterns of human brain activity. , 2012, Annual review of psychology.
[71] N. Kanwisher,et al. Feedback of pVisual Object Information to Foveal Retinotopic Cortex , 2008, Nature Neuroscience.
[72] Yaroslav O. Halchenko,et al. The Animacy Continuum in the Human Ventral Vision Pathway , 2015, Journal of Cognitive Neuroscience.
[73] Dae-Shik Kim,et al. Global and local fMRI signals driven by neurons defined optogenetically by type and wiring , 2010, Nature.
[74] Nikolaus Kriegeskorte,et al. Frontiers in Systems Neuroscience Systems Neuroscience , 2022 .