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Information-based functional brain mapping.
TLDR
The development of high-resolution neuroimaging and multielectrode electrophysiological recording provides neuroscientists with huge amounts of multivariate data, but the local averaging standardly applied to this end may obscure the effects of greatest neuroscientific interest.
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Analysis of functional image analysis contest (FIAC) data with brainvoyager QX: From single‐subject to cortically aligned group general linear model analysis and self‐organizing group independent…
TLDR
Using spatially and temporally unsmoothed data, this cortex‐based analysis revealed comparable results but with a set of spatially more confined group clusters and more differential group region of interest time courses.
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Mapping directed influence over the brain using Granger causality and fMRI
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Investigating directed cortical interactions in time-resolved fMRI data using vector autoregressive modeling and Granger causality mapping.
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Mirror-Symmetric Tonotopic Maps in Human Primary Auditory Cortex
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The constructive nature of vision: direct evidence from functional magnetic resonance imaging studies of apparent motion and motion imagery
TLDR
The comparison between the results obtained with objective motion, apparent motion and imagined motion provides further insights into a complex cortical network of motion‐sensitive areas driven by bottom‐up and top‐down neural processes.
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Combining multivariate voxel selection and support vector machines for mapping and classification of fMRI spatial patterns
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Integration of Letters and Speech Sounds in the Human Brain
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Individual faces elicit distinct response patterns in human anterior temporal cortex
TLDR
Responses elicited by the face images were distinct in aIT but not in the FFA, suggesting that individual-level face information is likely to be present in both regions, but the data suggest that it is more pronounced in a IT.
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"Who" Is Saying "What"? Brain-Based Decoding of Human Voice and Speech
TLDR
This work combines functional magnetic resonance imaging with a data-mining algorithm and retrieve what and whom a person is listening to from the neural fingerprints that speech and voice signals elicit in the listener's auditory cortex.
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