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Brief Communications

Decoding the Contents of Visual Short-Term Memory from Human Visual and Parietal Cortex

Thomas B. Christophel, Martin N. Hebart and John-Dylan Haynes
Journal of Neuroscience 19 September 2012, 32 (38) 12983-12989; https://doi.org/10.1523/JNEUROSCI.0184-12.2012
Thomas B. Christophel
1Bernstein Center for Computational Neuroscience, Charité Universitätsmedizin, 10115 Berlin, Germany,
2Berlin Center for Advanced Neuroimaging, and
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Martin N. Hebart
1Bernstein Center for Computational Neuroscience, Charité Universitätsmedizin, 10115 Berlin, Germany,
2Berlin Center for Advanced Neuroimaging, and
4Berlin School of Mind and Brain, Humboldt Universität, 10099 Berlin, Germany, and
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John-Dylan Haynes
1Bernstein Center for Computational Neuroscience, Charité Universitätsmedizin, 10115 Berlin, Germany,
2Berlin Center for Advanced Neuroimaging, and
3Cluster of Excellence NeuroCure, Charité Universitätsmedizin, 10117 Berlin, Germany,
4Berlin School of Mind and Brain, Humboldt Universität, 10099 Berlin, Germany, and
5Max Planck Institute for Human Cognitive and Brain Sciences, 04303 Leipzig, Germany
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    Figure 1.

    Delayed similarity detection task using complex artificial stimuli. A, In each trial, subjects were presented with two sample stimuli followed by a retro-cue. This cue indicated which of the two samples was supposed to be remembered. It was surrounded by a mask. After an extended delay, two test stimuli were shown. Subjects were asked to indicate which of the two test stimuli was more similar to the memorized sample. B, All subjects remembered a unique set of four randomly generated samples. C, Stimuli from an example trial. Arrows indicates which test item is more similar to a given sample. For presentation purposes, the correlation between remembered sample and target shown here is higher than in the actual experiment. D, Behavioral performance across subjects. Red squares indicate mean accuracy per subject (N = 17) and red circles show the performance in each of the four runs.

  • Figure 2.
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    Figure 2.

    Brain regions encoding the content of visual working memory. A, B, Localization of working memory content-related information shown in a 3D rendering and in sagittal, coronal, and axial slices. Green areas indicate brain regions that carry significant information (N = 17, pFWE < 0.05, k = 20) about the stimulus encoded in a given trial. Colored crosses in A indicate the positioning of the slices shown in B. These MNI coordinates are reported in the respective colors in B.

  • Figure 3.
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    Figure 3.

    Distribution of decoding accuracy across pairwise comparisons between memorized samples. The three displays correspond to the three peak voxels reported in the text. Top, Distributions of decoding accuracy across all 102 pairwise comparisons (17 subjects × 6 pairwise comparisons per subject) at the peaks of the respective time series. Bottom, The same data for each subject separately as open circles and the subject-mean as filled squares.

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    Figure 4.

    Time courses of working memory content-related information. Decoding accuracy (in percentages) is plotted against time (seconds) locked to the beginning of the delay phase. Data are shown for the statistical peaks in the three clusters shown in Figure 2A. The delay phase is represented by a blue overlay. Error bars indicate the SEM across subjects. The time series data are shown at the exact time points of data acquisition of the respective slices. The slice acquisition offsets relative to image acquisition onsets was 1.462 s (SEM: 18 ms) in left PPC, 1.58 s (SEM: 16 ms) in right PPC, and 0.620 s (SEM: 22 ms) in right visual cortex.

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The Journal of Neuroscience: 32 (38)
Journal of Neuroscience
Vol. 32, Issue 38
19 Sep 2012
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Decoding the Contents of Visual Short-Term Memory from Human Visual and Parietal Cortex
Thomas B. Christophel, Martin N. Hebart, John-Dylan Haynes
Journal of Neuroscience 19 September 2012, 32 (38) 12983-12989; DOI: 10.1523/JNEUROSCI.0184-12.2012

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Decoding the Contents of Visual Short-Term Memory from Human Visual and Parietal Cortex
Thomas B. Christophel, Martin N. Hebart, John-Dylan Haynes
Journal of Neuroscience 19 September 2012, 32 (38) 12983-12989; DOI: 10.1523/JNEUROSCI.0184-12.2012
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