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
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.
Articles referring to PyMVPA