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decoding

Known as: decoded 
 
National Institutes of Health

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2015
Highly Cited
2015
The Decoding Toolbox (TDT): a versatile software package for multivariate analyses of functional imaging data
The multivariate analysis of brain signals has recently sparked a great amount of interest, yet accessible and versatile tools to… Expand
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Highly Cited
2015
Highly Cited
2015
A voxel-wise encoding model for early visual areas decodes mental images of remembered scenes
Recent multi-voxel pattern classification (MVPC) studies have shown that in early visual cortex patterns of brain activity… Expand
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Highly Cited
2015
Highly Cited
2015
Decoding a Wide Range of Hand Configurations from Macaque Motor, Premotor, and Parietal Cortices
Despite recent advances in decoding cortical activity for motor control, the development of hand prosthetics remains a major… Expand
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2015
2015
Decoding Internally and Externally Driven Movement Plans
During movement planning, brain activity within parietofrontal networks encodes information about upcoming actions that can be… Expand
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Highly Cited
2014
Highly Cited
2014
Measurement of average decoding rates of the 61 sense codons in vivo
Most amino acids can be encoded by several synonymous codons, which are used at unequal frequencies. The significance of unequal… Expand
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Highly Cited
2014
Highly Cited
2014
Prioritizing spatial accuracy in high-resolution fMRI data using multivariate feature weight mapping
Although ultra-high-field fMRI at field strengths of 7T or above provides substantial gains in BOLD contrast-to-noise ratio, when… Expand
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Highly Cited
2014
Highly Cited
2014
Capturing the musical brain with Lasso: Dynamic decoding of musical features from fMRI data
We investigated neural correlates of musical feature processing with a decoding approach. To this end, we used a method that… Expand
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2014
2014
Decoding individual natural scene representations during perception and imagery
We used a multi-voxel classification analysis of functional magnetic resonance imaging (fMRI) data to determine to what extent… Expand
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Highly Cited
2014
Highly Cited
2014
Bayesian multi-task learning for decoding multi-subject neuroimaging data
Decoding models based on pattern recognition (PR) are becoming increasingly important tools for neuroimaging data analysis. In… Expand
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Highly Cited
2013
Highly Cited
2013
fMRI orientation decoding in V1 does not require global maps or globally coherent orientation stimuli
The orientation of a large grating can be decoded from V1 functional magnetic resonance imaging (fMRI) data, even at low… Expand
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