Who Is Using It?¶

If you are using PyMVPA or have published a study employing it, please leave a comment at the bottom of this page, if you want to be listed here as well.

Institutions Where PyMVPA Is Known To Be Used¶

Center for Mind/Brain Sciences, University of Trento, Italy
Department of Psychological and Brain Sciences, Dartmouth College, USA
Thayer School of Engineering, Dartmouth College, USA
Department of Psychology & Neuroscience, Duke University, USA
Fondazione Bruno Kessler, Italy
Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, USA
Department of Neurology, Max Planck Insititute for Neurological Research, Cologne, Germany
MRC Cognition and Brain Sciences Unit, Cambridge, UK
Department of Experimental Psychology, Otto-von-Guericke-University Magdeburg, Germany
Donders Center for Cognition, Radboud University Nijmegen, Netherlands
Department of Psychology, University of California at Los Angeles, USA
Center for Functional Neuroimaging, University of Pennsylvania, USA
Brain & Creativity Institute, University of Southern California, USA
Imaging Research Center, University of Texas at Austin, USA
Department of Psychiatry, University of Wisconsin, Madison, USA
Department of Psychology, Yale University, USA

...and many more (stopped extending this list in 2012).

Studies employing PyMVPA¶

2016¶

Guntupalli et al., Cerebral Cortex (2016). A Model of Representational Spaces in Human Cortex
Watson et al., NeuroImage (2016). Spatial properties of objects predict patterns of neural response in the ventral visual pathway
Watson et al., NeuroImage (2016). Patterns of neural response in scene-selective regions of the human brain are affected by low-level manipulations of spatial frequency

2015¶

Floren et al., Frontiers in Human Neuroscience (2015). Accurately decoding visual information from fMRI data obtained in a realistic virtual environment
Merkel et al, NeuroImage (2015). Neural correlates of multiple object tracking strategies
Pogoda, et al., Brain and Cognition (2015). Multivariate representation of food preferences in the human brain
Emmerling et al., NeuroImage (2015). Decoding the direction of imagined visual motion using 7 T ultra-high field fMRI
Danelli et al., Frontiers in Psychology (2015). Framing effects reveal discrete lexical-semantic and sublexical procedures in reading: an fMRI study
Schlegel et al., NeuroImage (2015). The artist emerges: Visual art learning alters neural structure and function
Maass et al., ELife (2015). Functional subregions of the human entorhinal cortex
Sha et al., Journal of Cognitive Neuroscience (2015). The Animacy Continuum in the Human Ventral Vision Pathway
Greisel et al., arXiv (2015). Photometric redshifts and model spectral energy distributions of galaxies from the SDSS-III BOSS DR10 data
McNamee et al., Journal of Neuroscience (2015). Characterizing the associative content of brain structures involved in habitual and goal-directed actions in humans: a multivariate fMRI study
Cole et al., Cerebral Cortex (2015). The behavioral relevance of task information in human prefrontal cortex
Guo and Meng, NeuroImage (2015). The encoding of category-specific versus nonspecific information in human inferior temporal cortex

2014¶

Rueschemeyer et al., Journal of Cognitive Neuroscience (2014). Observing, performing, and understanding actions: Revisiting the role of cortical motor areas in processing of action words.
Hanke et al., Scientific Data (2014). A high-resolution 7-Tesla fMRI dataset from complex natural stimulation with an audio movie.
Helfinstein et al., PNAS (2014). Predicting risky choices from brain activity patterns.
Sha et al., Journal of Cognitive Neuroscience (2014). The animacy continuum in the human ventral vision pathway
Schönwiesner et al., Cerebral Cortex (2014). Parcellation of Human and Monkey core auditory cortex with fMRI pattern classification and objective detection of tonotopic gradient reversals
Klein and Zatorre, Cerebral Cortex (2014). Representations of invariant musical categories are decodable by pattern analysis of locally distributed BOLD responses in superior temporal and intraparietal sulci
Huffman and Start, Hippocampus (2014). Multivariate pattern analysis of the human medial temporal lobe revealed representationally categorical cortex and representationally agnostic hippocampus
Schlegel et al., NeuroImage (2014). The artist emerges: Visual art learning alters neural structure and function
Jimura et al, Frontiers in Human Neuroscience (2014). The neural basis of task switching changes with skill acquisition
Lee and McCarthy, Cerebral Cortex (2014). Functional Heterogeneity and Convergence in the Right Temporoparietal Junction
Watson et al., NeuroImage (2014). Patterns of response to visual scenes are linked to the low-level properties of the image
Schlichting and Preston, PNAS (2014). Memory reactivation during rest supports upcoming learning of related content
Mittner et al., Journal of Neuroscience (2014). When the brain takes a break: A model-based analysis of mind wandering
Wang et al., Journal of Neuroscience (2014). Distributed Value Representation in the Medial Prefrontal Cortex during Intertemporal Choices
Parkinson et al., Journal of Neuroscience (2014). A common cortical metric for spatial, temporal, and social distance
Kim et al., Frontiers in Human Neuroscience (2014). Discriminable spatial patterns of activation for faces and bodies in the fusiform gyrus
Pollmann et al., NeuroImage (2014). The right temporo-parietal junction contributes to visual feature binding
Fogelson et al., Frontiers in Psychology (2014). Unconscious neural processing differs with method used to render stimuli invisible
Plitt et al., Social Neuroscience (2014). Are corporations people too? The neural correlates of moral judgments about companies and individuals
Kubilius et al., Journal of Vision (2014). Encoding of configural regularity in the human visual system
Heitmeyer et al., Automated Software Engineering (2014). Building high assurance human-centric decision systems

2013¶

Anderson et al., Clinical Neuropsychology (2013). 7T fMRI reveals feasibility of covert visual attention-based brain–computer interfacing with signals obtained solely from cortical grey matter accessible by subdural surface electrodes
Manelis and Reder, Cerebral Cortex (2013). he who is well prepared has half won the battle: an fMRI study of task preparation
Kohler et al., NeuroImage (2013). Pattern classification precedes region-average hemodynamic response in early visual cortex.
Hassabis et al., Cerebral Cortex (2013). Imagine all the people: How the brain creates and uses personality models to predict behavior.
Smith et al., PNAS (2013). Decoding the anatomical network of spatial attention.
Lescroart and Biederman, Cerebral Cortex (2013). Cortical representation of medial axis structure.
Strnad et al., PloS one (2013). Multivoxel Pattern Analysis Reveals Auditory Motion Information in MT+ of Both Congenitally Blind and Sighted Individuals.
Baumgartner et al., NeuroImage (2013). Evidence for feature binding in the superior parietal lobule.
McNamee et al., Nature Neuroscience (2013). Category-dependent and category-independent goal-value codes in human ventromedial prefrontal cortex.
Liang, et al., Nature Communications (2013). Primary sensory cortices contain distinguishable spatial patterns of activity for each sense.

2012¶

Viswanathan et al., arXiv preprint (2012). On the geometric structure of fMRI searchlight-based information maps.
Farrell et al., Biochemistry (2012). Toward Fast Determination of Protein Stability Maps: Experimental and Theoretical Analysis of Mutants of a Nocardiopsis prasina Serine Protease.
Sobhani et al., PloS one (2012). Interpersonal liking modulates motor-related neural regions.
Kingson et al., Journal of Neuroscience (2012). Sight and Sound Converge to Form Modality-Invariant Representations in Temporoparietal Cortex.
Kaplan and Meyer, NeuroImage (2012). Multivariate pattern analysis reveals common neural patterns across individuals during touch observation.
Carter et al., Science (2012). A distinct role of the temporal-parietal junction in predicting socially guided decisions.
van der Laan, PloS one (2012). Appearance matters: neural correlates of food choice and packaging aesthetics.
Merrill et al., Frontiers in Psychology (2012). Perception of words and pitch patterns in song and speech.
Ekman et al., PNAS (2012). Predicting errors from reconfiguration patterns in human brain networks.
Hiroyuki et al., Frontiers in Neuroinformatics (2012): Decoding Semantics across fMRI sessions with Different Stimulus Modalities: A practical MVPA Study.
Gorlin et al., PNAS (2012): Imaging prior information in the brain.
Raizada and Connolly, Cognitive Neuroscience (2012): What makes different people’s representations alike: neural similarity-space solves the problem of across-subject fMRI decoding. Preprint PDF and code are available
Connolly et al., Journal of Neuroscience (2012): Representation of Biological Classes in the Human Brain.

2011¶

Cole et al, Frontiers in Human Neuroscience (2011). Rapid Transfer of Abstract Rules to Novel Contexts in Human Lateral Prefrontal Cortex.
Vickery et al, Neuron (2011). Ubiquity and Specificity of Reinforcement Signals throughout the Human Brain.
Duff et al., NeuroImage (2011): Task-driven ICA feature generation for accurate and interpretable prediction using fMRI.
Haxby et al., Neuron (2011): A common, high-dimensional model of the representational space in human ventral temporal cortex.
Jimura and Poldrack, Neuropsychologia (2011): Analyses of regional-average activation and multivoxel pattern information tell complementary stories
Carlin et al., Current Biology (2011): A head view-invariant representation of gaze direction in anterior superior temporal sulcus
Kaunitz et al., Frontiers in Perception Science (2011): Intercepting the first pass: rapid categorization is suppressed for unseen stimuli.
Carlin et al., Cerebral Cortex (2011): Direction-Sensitive Codes for Observed Head Turns in Human Superior Temporal Sulcus.
Kubilius et al., Psychological Science (2011): Emergence of perceptual gestalts in the human visual cortex: The case of the configural superiority effect. Complete suite of sources from stimuli delivery (PsychoPy) to data analysis (PyMVPA) is available
Manelis et al., Cerebral Cortex (2011): Dynamic Changes In The Medial Temporal Lobe During Incidental Learning Of Object–Location Associations.
Meyer et al., Cerebral Cortex (2011): Seeing Touch Is Correlated with Content-Specific Activity in Primary Somatosensory Cortex.

2010¶

Woolgar et al., NeuroImage (2010): Multi-voxel coding of stimuli, rules, and responses in human frontoparietal cortex.
Clithero et al., NeuroImage (2010): Within- and cross-participant classifiers reveal different neural coding of information.
Gilliam et al., Proceedings of the International Conference on Pattern Recognition (2010): Scribe Identification in Medieval English Manuscripts.
Cohen at al., Frontiers in Human Neuroscience (2010): Decoding Developmental Differences and Individual Variability in Response Inhibition Through Predictive Analyses Across Individuals.
Meyer et al., Nature Neuroscience (2010): Predicting visual stimuli based on activity in auditory cortices.
Manelis et al., Human Brain Mapping (2010): Implicit memory for object locations depends on reactivation of encoding-related brain regions.

2009¶

Trautmann et al., IEEE/RSJ International Conference on Intelligent Robots and Systems (2009): Development of an autonomous robot for ground penetrating radar surveys of polar ice.
Sun et al., Biological Psychiatry (2009): Elucidating an MRI-Based Neuroanatomic Biomarker for Psychosis: Classification Analysis Using Probabilistic Brain Atlas and Machine Learning Algorithms.

Articles referring to PyMVPA¶