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Articles, Systems/Circuits

Feature-Specific Information Processing Precedes Concerted Activation in Human Visual Cortex

Pavan Ramkumar, Mainak Jas, Sebastian Pannasch, Riitta Hari and Lauri Parkkonen
Journal of Neuroscience 1 May 2013, 33 (18) 7691-7699; DOI: https://doi.org/10.1523/JNEUROSCI.3905-12.2013
Pavan Ramkumar
1Brain Research Unit and MEG Core, O.V. Lounasmaa Laboratory, School of Science,
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Mainak Jas
1Brain Research Unit and MEG Core, O.V. Lounasmaa Laboratory, School of Science,
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Sebastian Pannasch
1Brain Research Unit and MEG Core, O.V. Lounasmaa Laboratory, School of Science,
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Riitta Hari
1Brain Research Unit and MEG Core, O.V. Lounasmaa Laboratory, School of Science,
2Advanced Magnetic Imaging Centre, School of Science, and
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Lauri Parkkonen
1Brain Research Unit and MEG Core, O.V. Lounasmaa Laboratory, School of Science,
2Advanced Magnetic Imaging Centre, School of Science, and
3Department of Biomedical Engineering and Computational Sciences, School of Science, Aalto University, FI-00076 Aalto, Espoo, Finland
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  • Figure 1.
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    Figure 1.

    All stimuli used in the study were sinusoidal gratings within annuli spanning the full visual field at eccentricities between 2° and 10°. A, In the static-grating experiment, stimuli were of two distinct SFs (left, 0.33 c/deg; right, 1.33 c/deg) and two distinct ORs (top, 45°; bottom, 135°). B, In the rotating-grating experiment, gratings with an SF of 1.33 c/deg rotated either clockwise or anticlockwise in the range of 0–180°. C, In the cross-contrast decoding experiment, static gratings oriented at 135° were presented at full, half, and one-fourth contrasts. D, In the cross-phase decoding experiment, static gratings, oriented at 135°, were presented at zero, quarter-cycle, and half-cycle phase shifts.

  • Figure 2.
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    Figure 2.

    A, The average photodiode responses to 100 trials each of black (black trace) and white (gray trace) stimulus patches were averaged with respect to the stimulus trigger (gray vertical dashed line). The photodiode signal begins to change 36 ms after the stimulus trigger, as indicated by the arrow on the top left. The dotted lines indicate the region near the photodiode signal onset, from which the signal in the inset is displayed. The inset shows the 2 ms rise time to maximum luminance. B, Time-resolved decoding of the stimulus patch color from the single-trial photodiode responses. C, Time-resolved decoding of SF from a single subject's single-trial filtered (gray) and unfiltered (black) MEG responses.

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    Figure 3.

    Evoked responses to static gratings. Responses averaged across 100 trials for a representative subject's parieto-occipital planar gradiometer. A, Low (0.33 c/deg; red) and high (1.33 c/deg; blue) spatial frequencies for gratings oriented at 135°. B, Gratings oriented at 45° (red) and 135° (blue), both at 1.33 c/deg. Shaded boundaries show SEMs. Arrows show the median onset of above-chance decoding accuracy (see Results, Time-resolved decoding of visual features and Fig. 5).

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    Figure 4.

    Time-insensitive decoding. A, Subjectwise classification accuracies for the four-class decoding problem: identification of both SF and OR from a closed set. The chance level (25%) is given as a dashed line. Error bars indicate bootstrapped 95% CIs. B, Decoding accuracies for the two-class problem: OR (x-axis) versus SF (y-axis). Each circle represents one subject; error bars indicate bootstrapped 95% CIs. C, Confusion matrix for the four-class decoding problem, viz. prediction of OR and SF. Individual confusion matrices estimated from each subject and cross-validation fold were averaged. Entries in each row show percentage of trials predicted as the category corresponding to the respective column. Chance level is 25%. The categories—indicated by schematics depicting the stimulus features—correspond to left-oriented (135°) high SF, left-oriented low SF, right-oriented (45°) high SF, and right-oriented low SF.

  • Figure 5.
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    Figure 5.

    Time-resolved decoding. Performance of time-resolved classifiers using windows moving or growing in 1 ms time steps is shown. The moving and growing window traces for SF (A, B), OR (C, D), and RD (E, F) are shown, along with chance-level threshold as solid lines and overall accuracies from time-insensitive classifiers as dotted lines. The bounds on each trace indicate bootstrapped 95% CIs across eight subjects. Subjectwise accuracy traces were themselves obtained by averaging across five cross-validation folds. Black bars at the bottom of each trace show the duration in which above-chance decoding (p < 0.00005) was obtained. Insets in A, C, and E show the accuracy traces around the stimulus or rotation onset. Arrows within the insets indicate the leading edge of the windows at which chance level was first exceeded. The gray patches in A–D show the stimulus time course. The light gray patches for E and F between 0–200 ms and 800–1000 ms indicate the periods of contrast fade-in and fade-out of the grating, and the dark gray patches indicate the duration of rotation. The arrows in E and F show the onset of stimulus rotation.

  • Figure 6.
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    Figure 6.

    Robustness analysis. Classification performance for the static and dynamic gratings as a function of the percentage of samples in the training set are shown. Accuracies are shown as a function of the number of training samples used to train the classifier. The proportion of samples in the training set was varied from 5 to 80%, and the remaining trials were used for testing. Accuracies are shown for (A) SFs, (B) ORs, and (C) RDs. Error bars indicate SD of the mean classification accuracies across the eight subjects.

Tables

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    Table 1.

    Periods of successful decoding

    Stimulus featureStimulus onset at 0 msStimulus offset at 1000 ms
    Decoding onsetDecoding offsetDecoding onsetDecoding offset
    SF51 (50–53)262 (247–287)1060 (1057–1067)1219 (1202–1239)
    OR65 (58–72)193 (174–261)1098 (1090–1106)1123 (1115–1179)
    RD298 (284–313)841 (772–863)
    • The numbers refer to latencies (in milliseconds) at which decoding emerged above (decoding onset) and returned back to (decoding offset) chance level at stimulus onset and offset. The values were obtained using a one-tailed t test against an empirical baseline estimated from the [−300 ms, 0] interval (see Material and Methods). Each entry gives the median and the 95% CI from the bootstrap distribution.

    • View popup
    Table 2.

    Classification accuracies for intersubject analysis

    SubjectSpatial frequencyOrientationRotation direction
    135°45°1.33°0.33°
    170.57453.553.5—
    27570.5545356.5
    366.5736458.561
    4756845.55556
    575.57853.55049
    66964595356.5
    774.769.553.755.854
    882.57955.55753
    9————58
    Mean ± SD73.6 ± 4.972.0 ± 5.154.2 ± 5.054.5 ± 2.755.5 ± 3.6
    • Each row corresponds to the decoding accuracies on one subject's data obtained with a classifier trained on data from all other subjects. The columns give the classification accuracies (percentage of trials correctly classified) for each stimulus feature (two-class problem). Chance level is 50%.

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    Table 3.

    Classification accuracies for cross-contrast and cross-phase decoding

    Target contrastAccuracyTarget phaseAccuracy
    175081
    Half79¼73
    One-fourth78½71
    • A spatial frequency decoder was trained on responses to gratings with contrasts (phase) other than the target contrast (phase) and tested on responses to gratings with the target contrast (phase).

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The Journal of Neuroscience: 33 (18)
Journal of Neuroscience
Vol. 33, Issue 18
1 May 2013
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Feature-Specific Information Processing Precedes Concerted Activation in Human Visual Cortex
Pavan Ramkumar, Mainak Jas, Sebastian Pannasch, Riitta Hari, Lauri Parkkonen
Journal of Neuroscience 1 May 2013, 33 (18) 7691-7699; DOI: 10.1523/JNEUROSCI.3905-12.2013

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Feature-Specific Information Processing Precedes Concerted Activation in Human Visual Cortex
Pavan Ramkumar, Mainak Jas, Sebastian Pannasch, Riitta Hari, Lauri Parkkonen
Journal of Neuroscience 1 May 2013, 33 (18) 7691-7699; DOI: 10.1523/JNEUROSCI.3905-12.2013
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