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Within- and cross-participant classifiers reveal different neural coding of information.

Publication ,  Journal Article
Clithero, JA; Smith, DV; Carter, RM; Huettel, SA
Published in: NeuroImage
May 2011

Analyzing distributed patterns of brain activation using multivariate pattern analysis (MVPA) has become a popular approach for using functional magnetic resonance imaging (fMRI) data to predict mental states. While the majority of studies currently build separate classifiers for each participant in the sample, in principle a single classifier can be derived from and tested on data from all participants. These two approaches, within- and cross-participant classification, rely on potentially different sources of variability and thus may provide distinct information about brain function. Here, we used both approaches to identify brain regions that contain information about passively received monetary rewards (i.e., images of currency that influenced participant payment) and social rewards (i.e., images of human faces). Our within-participant analyses implicated regions in the ventral visual processing stream-including fusiform gyrus and primary visual cortex-and ventromedial prefrontal cortex (VMPFC). Two key results indicate these regions may contain statistically discriminable patterns that contain different informational representations. First, cross-participant analyses implicated additional brain regions, including striatum and anterior insula. The cross-participant analyses also revealed systematic changes in predictive power across brain regions, with the pattern of change consistent with the functional properties of regions. Second, individual differences in classifier performance in VMPFC were related to individual differences in preferences between our two reward modalities. We interpret these results as reflecting a distinction between patterns showing participant-specific functional organization and those indicating aspects of brain organization that generalize across individuals.

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Published In

NeuroImage

DOI

EISSN

1095-9572

ISSN

1053-8119

Publication Date

May 2011

Volume

56

Issue

2

Start / End Page

699 / 708

Related Subject Headings

  • Young Adult
  • Reward
  • Photic Stimulation
  • Pattern Recognition, Visual
  • Pattern Recognition, Automated
  • Neurology & Neurosurgery
  • Magnetic Resonance Imaging
  • Image Processing, Computer-Assisted
  • Humans
  • Face
 

Citation

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Clithero, J. A., Smith, D. V., Carter, R. M., & Huettel, S. A. (2011). Within- and cross-participant classifiers reveal different neural coding of information. NeuroImage, 56(2), 699–708. https://doi.org/10.1016/j.neuroimage.2010.03.057
Clithero, John A., David V. Smith, R McKell Carter, and Scott A. Huettel. “Within- and cross-participant classifiers reveal different neural coding of information.NeuroImage 56, no. 2 (May 2011): 699–708. https://doi.org/10.1016/j.neuroimage.2010.03.057.
Clithero JA, Smith DV, Carter RM, Huettel SA. Within- and cross-participant classifiers reveal different neural coding of information. NeuroImage. 2011 May;56(2):699–708.
Clithero, John A., et al. “Within- and cross-participant classifiers reveal different neural coding of information.NeuroImage, vol. 56, no. 2, May 2011, pp. 699–708. Epmc, doi:10.1016/j.neuroimage.2010.03.057.
Clithero JA, Smith DV, Carter RM, Huettel SA. Within- and cross-participant classifiers reveal different neural coding of information. NeuroImage. 2011 May;56(2):699–708.
Journal cover image

Published In

NeuroImage

DOI

EISSN

1095-9572

ISSN

1053-8119

Publication Date

May 2011

Volume

56

Issue

2

Start / End Page

699 / 708

Related Subject Headings

  • Young Adult
  • Reward
  • Photic Stimulation
  • Pattern Recognition, Visual
  • Pattern Recognition, Automated
  • Neurology & Neurosurgery
  • Magnetic Resonance Imaging
  • Image Processing, Computer-Assisted
  • Humans
  • Face