.. -*- mode: rst; fill-column: 78; indent-tabs-mode: nil -*-
.. vi: set ft=rst sts=4 ts=4 sw=4 et tw=79:
  ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###
  #
  #   See COPYING file distributed along with the PyMVPA package for the
  #   copyright and license terms.
  #
  ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###


.. index:: Who is using it?, Publications
.. _chap_whoisusingit:

****************
Who Is Using It?
****************


.. only:: html

  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


Studies employing PyMVPA
========================

* :ref:`Hiroyuki et al., Frontiers in Neuroinformatics (2012) <HBL+12>`:
  Decoding Semantics across fMRI sessions with Different Stimulus Modalities:
  A practical MVPA Study.

* :ref:`Gorlin et al., PNAS (2012) <GMS+12>`: Imaging prior information in the
  brain.

* :ref:`Raizada and Connolly, Cognitive Neuroscience (In press) <RC12>`: What
  makes different people's representations alike: neural similarity-space
  solves the problem of across-subject fMRI decoding.
  `Preprint PDF and code <http://raizadalab.org/publications.html>`__ are available

* :ref:`Connolly et al., Journal of Neuroscience (2012) <CGG+12>`:
  Representation of Biological Classes in the Human Brain.

* :ref:`Haxby et al., Neuron (2011) <HGC+11>`: A common, high-dimensional model
  of the representational space in human ventral temporal cortex.

* :ref:`Jimura and Poldrack, Neuropsychologia (2011) <JP11>`: Analyses of
  regional-average activation and multivoxel pattern information tell
  complementary stories

* :ref:`Carlin et al., Current Biology (2011) <CCK+11>`: A head view-invariant
  representation of gaze direction in anterior superior temporal sulcus

* :ref:`Kaunitz et al., Frontiers in Perception Science (2011) <KKO+11>`:
  Intercepting the first pass: rapid categorization is suppressed for unseen stimuli.

* :ref:`Carlin et al., Cerebral Cortex (2011) <CRK+11>`:
  Direction-Sensitive Codes for Observed Head Turns in Human Superior Temporal
  Sulcus.

* :ref:`Kubilius et al., Psychological Science (2011) <KWO11>`:
  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) <https://bitbucket.org/qbilius/confsup>`__
  is available

* :ref:`Manelis et al., Cerebral Cortex (2011) <MRH11>`: Dynamic Changes In
  The Medial Temporal Lobe During Incidental Learning Of Object–Location
  Associations.

* :ref:`Meyer et al., Cerebral Cortex (2011) <MKE+11>`: Seeing Touch Is
  Correlated with Content-Specific Activity in Primary Somatosensory Cortex.

* :ref:`Woolgar et al., NeuroImage (2010) <WTB+10>`: Multi-voxel coding of
  stimuli, rules, and responses in human frontoparietal cortex.

* :ref:`Clithero et al., NeuroImage (2010) <CSM+10>`: Within- and
  cross-participant classifiers reveal different neural coding of information.

* :ref:`Gilliam et al., Proceedings of the International Conference on Pattern
  Recognition (2010) <GWC10>`: Scribe Identification in Medieval English
  Manuscripts.

* :ref:`Cohen at al., Frontiers in Human Neuroscience (2010) <CAS+10>`: Decoding
  Developmental Differences and Individual Variability in Response Inhibition
  Through Predictive Analyses Across Individuals.

* :ref:`Meyer et al., Nature Neuroscience (2010) <MKE10>`: Predicting visual
  stimuli based on activity in auditory cortices.

* :ref:`Manelis et al., Human Brain Mapping (2010) <MHH10>`: Implicit memory
  for object locations depends on reactivation of encoding-related brain
  regions.

* :ref:`Trautmann et al., IEEE/RSJ International Conference on Intelligent
  Robots and Systems (2009) <TRL09>`: Development of an autonomous robot for
  ground penetrating radar surveys of polar ice.

* :ref:`Sun et al., Biological Psychiatry (2009) <SET+09>`: Elucidating an
  MRI-Based Neuroanatomic Biomarker for Psychosis: Classification Analysis
  Using Probabilistic Brain Atlas and Machine Learning Algorithms.


Articles referring to PyMVPA
============================

* :ref:`Pernet et al., Front. Psychology (2011) <PSR11>`. Single-trial analyses: why bother?


* :ref:`Schackman et al., Nature Reviews Neuroscience (2011) <SSS+11>`: The
  integration of negative affect, pain and cognitive control in the cingulate
  cortex.

* :ref:`Margulies et al., Magnetic Resonance Materials in Physics, Biology and
  Medicine (2010) <MBL+10>`: Resting developments: a review of fMRI
  post-processing methodologies for spontaneous brain activity.

* :ref:`Shiffrin, Topics in Cognitive Science, (2010) <Shi10>`: Perspectives on
  Modeling in Cognitive Science.

* :ref:`LaConte, NeuroImage (2010) <LaC10>`: Decoding fMRI brain states in
  real-time.

* :ref:`Legge & Badii, Proceedings of the 2nd International Conference on
  Emerging Network Intelligence (2010) <LB10>`: An Application of Pattern
  Matching for the Adjustment of Quality of ServiceMetrics.

* :ref:`Spacek et al., The Neuromorphic Engineer (2009) <SS09>`: Python in
  Neuroscience.

* :ref:`Bandettini, Journal of Integrative Neuroscience (2009) <Ban09>`: Seven
  topics in functional magnetic reasonance imaging.

* :ref:`Garcia et al., Frontiers in Neuroinformatics (2009) <GF09>`:
  OpenElectrophy: An Electrophysiological Data- and Analysis-Sharing Framework.

* :ref:`Mur et al., Social Cognitive and Affective Neuroscience (2009)
  <MBK09>`: Revealing representational content with pattern-information fMRI –
  an introductory guide.

* :ref:`Pereira et al., NeuroImage (2009) <PMB09>`: Machine learning
  classifiers and fMRI: A tutorial overview.
