Neural responses to naturalistic clips of behaving animals in two different task contexts
暂无分享,去创建一个
[1] John-Dylan Haynes,et al. Valid population inference for information-based imaging: From the second-level t-test to prevalence inference , 2015, NeuroImage.
[2] Eric Jones,et al. SciPy: Open Source Scientific Tools for Python , 2001 .
[3] A. Dale,et al. High‐resolution intersubject averaging and a coordinate system for the cortical surface , 1999, Human brain mapping.
[4] William W. Graves,et al. Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. , 2009, Cerebral cortex.
[5] Michael Brady,et al. Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.
[6] Satrajit S. Ghosh,et al. The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments , 2016, Scientific Data.
[7] Bernhard E. Boser,et al. A training algorithm for optimal margin classifiers , 1992, COLT '92.
[8] Yi Chen,et al. Statistical inference and multiple testing correction in classification-based multi-voxel pattern analysis (MVPA): Random permutations and cluster size control , 2011, NeuroImage.
[9] Alexander Borst,et al. How does Nature Program Neuron Types? , 2008, Front. Neurosci..
[10] James L. McClelland,et al. The parallel distributed processing approach to semantic cognition , 2003, Nature Reviews Neuroscience.
[11] J. Gallant,et al. Reconstructing Visual Experiences from Brain Activity Evoked by Natural Movies , 2011, Current Biology.
[12] E. Rosch. Cognitive Representations of Semantic Categories. , 1975 .
[13] R W Cox,et al. AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. , 1996, Computers and biomedical research, an international journal.
[14] Jack L. Gallant,et al. A Continuous Semantic Space Describes the Representation of Thousands of Object and Action Categories across the Human Brain , 2012, Neuron.
[15] Abraham Z. Snyder,et al. Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion , 2012, NeuroImage.
[16] Bruce Fischl,et al. Accurate and robust brain image alignment using boundary-based registration , 2009, NeuroImage.
[17] Peter Gärdenfors,et al. Using Conceptual Spaces to Model Actions and Events , 2012, J. Semant..
[18] R. Shepard. Stimulus and response generalization: tests of a model relating generalization to distance in psychological space. , 1958, Journal of experimental psychology.
[19] Yaroslav O. Halchenko,et al. Neuroscience Runs on GNU/Linux , 2011, Front. Neuroinform..
[20] Thomas T. Liu,et al. A component based noise correction method (CompCor) for BOLD and perfusion based fMRI , 2007, NeuroImage.
[21] Alfonso Caramazza,et al. Action categories in lateral occipitotemporal cortex are organized along sociality and transitivity. , 2016, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[22] Samuel A. Nastase,et al. Attention Selectively Reshapes the Geometry of Distributed Semantic Representation , 2016, bioRxiv.
[23] W. R. Garner,et al. Integrality of stimulus dimensions in various types of information processing , 1970 .
[24] J. Kruschke,et al. ALCOVE: an exemplar-based connectionist model of category learning. , 1992, Psychological review.
[25] Thomas E. Nichols,et al. Thresholding of Statistical Maps in Functional Neuroimaging Using the False Discovery Rate , 2002, NeuroImage.
[26] Michael Hanke,et al. A studyforrest extension, retinotopic mapping and localization of higher visual areas , 2016, Scientific Data.
[27] Alexander G. Huth,et al. Attention During Natural Vision Warps Semantic Representation Across the Human Brain , 2013, Nature Neuroscience.
[28] R. Shepard,et al. Toward a universal law of generalization for psychological science. , 1987, Science.
[29] P. Boesiger,et al. SENSE: Sensitivity encoding for fast MRI , 1999, Magnetic resonance in medicine.
[30] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[31] T. Poggio,et al. Cognitive neuroscience: Neural mechanisms for the recognition of biological movements , 2003, Nature Reviews Neuroscience.
[32] Kingson Man,et al. Multivariate cross-classification: applying machine learning techniques to characterize abstraction in neural representations , 2015, Front. Hum. Neurosci..
[33] Satrajit S. Ghosh,et al. Nipype: A Flexible, Lightweight and Extensible Neuroimaging Data Processing Framework in Python , 2011, Front. Neuroinform..
[34] N. Kriegeskorte,et al. Author ' s personal copy Representational geometry : integrating cognition , computation , and the brain , 2013 .
[35] John D. Hunter,et al. Matplotlib: A 2D Graphics Environment , 2007, Computing in Science & Engineering.
[36] N. Logothetis,et al. Neurophysiological investigation of the basis of the fMRI signal , 2001, Nature.
[37] R. Shepard. Attention and the metric structure of the stimulus space. , 1964 .
[38] Christiane Fellbaum,et al. English Verbs as a Semantic Net , 1990 .
[39] S Edelman,et al. Representation is representation of similarities , 1996, Behavioral and Brain Sciences.
[40] Paul E. Downing,et al. Crossmodal and action-specific: neuroimaging the human mirror neuron system , 2013, Trends in Cognitive Sciences.
[41] J. I. The Design of Experiments , 1936, Nature.
[42] Satrajit S. Ghosh,et al. BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods , 2016, bioRxiv.
[43] Jonathan W. Peirce,et al. PsychoPy—Psychophysics software in Python , 2007, Journal of Neuroscience Methods.
[44] Brian E. Granger,et al. IPython: A System for Interactive Scientific Computing , 2007, Computing in Science & Engineering.
[45] Nikolaus Kriegeskorte,et al. Frontiers in Systems Neuroscience Systems Neuroscience , 2022 .
[46] Russell A. Poldrack,et al. OpenfMRI: Open sharing of task fMRI data , 2017, NeuroImage.
[47] Anders M. Dale,et al. Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction , 1999, NeuroImage.
[48] Joset A. Etzel. MVPA significance testing when just above chance, and related properties of permutation tests , 2017, 2017 International Workshop on Pattern Recognition in Neuroimaging (PRNI).
[49] Paul E. Downing,et al. A comparison of volume-based and surface-based multi-voxel pattern analysis , 2011, NeuroImage.
[50] Geoffrey Karl Aguirre,et al. Continuous carry-over designs for fMRI , 2007, NeuroImage.
[51] Keiji Tanaka,et al. Matching Categorical Object Representations in Inferior Temporal Cortex of Man and Monkey , 2008, Neuron.
[52] D. Heeger,et al. Reliability of cortical activity during natural stimulation , 2010, Trends in Cognitive Sciences.
[53] R. Nosofsky. Attention, similarity, and the identification-categorization relationship. , 1986, Journal of experimental psychology. General.
[54] Stephen M. Smith,et al. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm , 2001, IEEE Transactions on Medical Imaging.
[55] Lawrence L. Wald,et al. Comparison of physiological noise at 1.5 T, 3 T and 7 T and optimization of fMRI acquisition parameters , 2005, NeuroImage.
[56] J. S. Guntupalli,et al. The Representation of Biological Classes in the Human Brain , 2012, The Journal of Neuroscience.
[57] Krzysztof J. Gorgolewski,et al. MRIQC: Advancing the automatic prediction of image quality in MRI from unseen sites , 2016, bioRxiv.
[58] Y. Benjamini,et al. Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .
[59] Stefan Pollmann,et al. PyMVPA: a Python Toolbox for Multivariate Pattern Analysis of fMRI Data , 2009, Neuroinformatics.
[60] Gidon Felsen,et al. A natural approach to studying vision , 2005, Nature Neuroscience.
[61] A. Tversky. Features of Similarity , 1977 .
[62] F ATTNEAVE,et al. Dimensions of similarity. , 1950, The American journal of psychology.
[63] S. Zeki,et al. Functional brain mapping during free viewing of natural scenes , 2004, Human brain mapping.
[64] A. Ishai,et al. Distributed and Overlapping Representations of Faces and Objects in Ventral Temporal Cortex , 2001, Science.
[65] Yaroslav O. Halchenko,et al. Cross-modal searchlight classification: methodological challenges and recommended solutions , 2016, 2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI).
[66] J. S. Guntupalli,et al. Decoding neural representational spaces using multivariate pattern analysis. , 2014, Annual review of neuroscience.
[67] Thomas E. Nichols,et al. Fixing the stimulus-as-fixed-effect fallacy in task fMRI , 2016, bioRxiv.
[68] Brenna Argall,et al. SUMA: an interface for surface-based intra- and inter-subject analysis with AFNI , 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).
[69] Yaroslav O. Halchenko,et al. The Animacy Continuum in the Human Ventral Vision Pathway , 2015, Journal of Cognitive Neuroscience.
[70] Mark S. Cohen,et al. Parametric Analysis of fMRI Data Using Linear Systems Methods , 1997, NeuroImage.
[71] Gaël Varoquaux,et al. The NumPy Array: A Structure for Efficient Numerical Computation , 2011, Computing in Science & Engineering.
[72] Rainer Goebel,et al. Information-based functional brain mapping. , 2006, Proceedings of the National Academy of Sciences of the United States of America.
[73] Bryan R. Conroy,et al. A Common, High-Dimensional Model of the Representational Space in Human Ventral Temporal Cortex , 2011, Neuron.
[74] Thomas E. Nichols,et al. Fixing the stimulus-as-fixed-effect fallacy in task fMRI , 2016 .
[75] Oliver Speck,et al. A high-resolution 7-Tesla fMRI dataset from complex natural stimulation with an audio movie , 2014, Scientific Data.