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PyMVPA: a unifying approach to the analysis of neuroscientific data

Michael Hanke
2009 Frontiers in Neuroinformatics  
In this article we show how PyMVPA, a specialized Python framework for machine learning based data analysis, can help to facilitate this inter-disciplinary technology transfer by providing a single interface  ...  We demonstrate the general applicability and power of PyMVPA via analyses of a number of neural data modalities, including fMRI, EEG, MEG, and extracellular recordings. applicability to humans, and the  ...  ACKNOWLEDGMENTS We are thankful to Dr. Artur Luczak and Dr. Kenneth D. Harris (CMBN, Rutgers University, Newark, NJ, USA) for providing the extracellular recordings dataset for the paper.  ... 
doi:10.3389/neuro.11.003.2009 pmid:19212459 pmcid:PMC2638552 fatcat:6dfxvlmjsbgcfflpmul5puuqce

Statistical learning analysis in neuroscience: aiming for transparency

Michael Hanke
2010 Frontiers in Neuroscience  
for the analysis of neural data.  ...  In order to facilitate a wider adoption of these methods, neuroscientific research needs to ensure a maximum of transparency to allow for comprehensive evaluation of the employed procedures.  ...  Halchenko was supported by the National Science Foundation (grant: SBE 0751008) and the James McDonnell Foundation (grant: 220020127).  ... 
doi:10.3389/neuro.01.007.2010 pmid:20582270 pmcid:PMC2891484 fatcat:6tncphwbtnbyjcewxj6nlkuv2q

Deep-Learning-Based Multivariate Pattern Analysis (dMVPA): A Tutorial and a Toolbox

Karl M Kuntzelman, Jacob M Williams, Phui Cheng Lim, Ashok Samal, Prahalada K Rao, Matthew R Johnson
2021 Frontiers in Human Neuroscience  
In this paper, we provide a brief introduction to deep learning for those new to the technique, explore the logistical pros and cons of using deep learning to analyze neuroimaging data - which we term  ...  data, but we believe that those have barely scratched the surface of the potential deep learning holds for the field.  ...  SUPPLEMENTARY MATERIAL The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnhum. 2021.638052/full#supplementary-material  ... 
doi:10.3389/fnhum.2021.638052 pmid:33737872 pmcid:PMC7960649 fatcat:h5jyzefvvvfghhhpec3wrmzjee

The Behavioral Relevance of Task Information in Human Prefrontal Cortex

Michael W. Cole, Takuya Ito, Todd S. Braver
2015 Cerebral Cortex  
Human lateral prefrontal cortex (LPFC) is thought to play a critical role in enabling cognitive flexibility, particularly when performing novel tasks.  ...  This suggests that left anterior LPFC may be particularly important for representing task information that contributes to the cognitive flexibility needed to perform successfully in novel task situations  ...  Notes We thank Joset Etzel, Mattia Rigotti, Kevin Oksanen, and Maria Chushak for their help with data collection, analysis, and helpful discussions. Conflict of Interest: None declared.  ... 
doi:10.1093/cercor/bhv072 pmid:25870233 pmcid:PMC4869805 fatcat:szacdtmbsnbqjn6vquy57casfe

Nipype: A Flexible, Lightweight and Extensible Neuroimaging Data Processing Framework in Python

Krzysztof Gorgolewski, Christopher D. Burns, Cindee Madison, Dav Clark, Yaroslav O. Halchenko, Michael L. Waskom, Satrajit S. Ghosh
2011 Frontiers in Neuroinformatics  
A list of people who have contributed code to the project is available at http://github.com/nipy/nipype/contributors.  ...  We would also like to thank the developers of FreeSurfer, FSL, and SPM for being supportive of the project and providing valuable feedback on technical issues.  ...  Iterables -parameter spaCe exploratIon Nipype provides a flexible approach to prototype and experiment with different processing strategies, through the unified and uniform access to a variety of software  ... 
doi:10.3389/fninf.2011.00013 pmid:21897815 pmcid:PMC3159964 fatcat:vzgm5hzdu5dwxor7fhtehusb3m

Linking signal detection theory and encoding models to reveal independent neural representations from neuroimaging data

Fabian A Soto, Lauren E Vucovich, F Gregory Ashby
2018 PLoS Computational Biology  
The framework formally specifies the relation between these different levels of perceptual and brain representation, providing the tools for a truly integrative research approach.  ...  The new theory allowed us, for the first time, to precisely define separability of neural representations and to theoretically link behavioral and brain measures of separability.  ...  Author Contributions Conceptualization: Fabian A. Soto. Data curation: Fabian A. Soto. Formal analysis: Fabian A. Soto.  ... 
doi:10.1371/journal.pcbi.1006470 pmid:30273337 pmcid:PMC6181430 fatcat:croyw4oyy5f4tgcpnuwjx6b35u

Linking signal detection theory and encoding models to reveal independent neural representations from neuroimaging data [article]

Fabian A. Soto, Lauren E. Vucovich, F. Gregory Ashby
2018 bioRxiv   pre-print
The framework formally specifies the relation between these different levels of perceptual and brain representation, providing the tools for a truly integrative research approach.  ...  The new theory allowed us, for the first time, to precisely define separability of neural representations and to theoretically link behavioral and brain measures of separability.  ...  in pyMVPA) to decode the target dimension using all the available data.  ... 
doi:10.1101/254995 fatcat:ht3hdqthuraodg6mpi47igwkqm

Generalizing, Decoding, and Optimizing Support Vector Machine Classification [article]

Mario Michael Krell
2018 arXiv   pre-print
The classification of complex data usually requires the composition of processing steps.  ...  Namely, we take a theoretical view on classical classifiers, provide an approach to interpret the classifier together with the preprocessing, and integrate both into one framework which enables a semiautomatic  ...  discuss typical data analysis problems illustrated by examples from neuroscientific and robotic data.Motivation Most data in neuroscience and robotics are not feature vector data but time series data  ... 
arXiv:1801.04929v1 fatcat:hs7r6m7qojcrniu2v7np6745ru

The integration of negative affect, pain and cognitive control in the cingulate cortex

Alexander J. Shackman, Tim V. Salomons, Heleen A. Slagter, Andrew S. Fox, Jameel J. Winter, Richard J. Davidson
2011 Nature Reviews Neuroscience  
These observations compel a reconsideration of the dorsal cingulate's contribution to negative affect and pain.  ...  Anatomical studies reveal that the aMCC constitutes a hub where information about reinforcers can be linked to motor centres responsible for expressing affect and executing goal-directed behaviour.  ...  Acknowledgements We thank the Laboratory for Affective Neuroscience and Waisman Laboratory for Brain Imaging and Behavior staff A.  ... 
doi:10.1038/nrn2994 pmid:21331082 pmcid:PMC3044650 fatcat:mcvztpcmtbgcdk45gcgrqmp4vu

Functional networks in absolute pitch and auditory-visual synesthesia

Christian Brauchli
2019
of the unsmoothed data to a MVPA of smoothed data.  ...  It thus constituted a unifying tool to designate synesthetes for neuroscientific studies of the last decade (Jäncke & Langer, 2011; Jäncke, Rogenmoser, Meyer, & Elmer, 2012; Zamm, Schlaug, Eagleman, &  ...  mass-univariate statistics of local connectivity calculated from smoothed (A) and unsmoothed (B) fMRI data.  ... 
doi:10.5167/uzh-170788 fatcat:4t5uaymc45hidfckxnb6blulla