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Research ArticleNew Research, Cognition and Behavior

Encoding of Spatial Attention by Primate Prefrontal Cortex Neuronal Ensembles

Theda Backen, Stefan Treue and Julio C. Martinez-Trujillo
eNeuro 8 January 2018, 5 (1) ENEURO.0372-16.2017; https://doi.org/10.1523/ENEURO.0372-16.2017
Theda Backen
1Department of Physiology, McGill University, Montreal, H3G 1Y6, Canada
2German Primate Center, Leibniz Institute for Primate Research, Goettingen, 37077, Germany
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Stefan Treue
2German Primate Center, Leibniz Institute for Primate Research, Goettingen, 37077, Germany
3Bernstein Center for Computational Neuroscience, Goettingen, 37073, Germany
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Julio C. Martinez-Trujillo
1Department of Physiology, McGill University, Montreal, H3G 1Y6, Canada
4Robarts Research Institute, University of Western Ontario, London, N6A 5B7, Canada
5Department of Physiology & Pharmacology, University of Western Ontario, London, N6A 5B7, Canada
6Brain and Mind Institute, University of Western Ontario, London, N6A 5B7, Canada
7Department of Psychiatry, University of Western Ontario, London, N6A 5B7, Canada
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  • Figure 1.
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    Figure 1.

    Behavioral task and performance. A, Example trial of color scale task and hierarchy of colors used (inset). The monkeys initiated a trial by fixating on the central point while pressing a button. After this initial fixation period, two white moving RDPs appeared peripherally of the fixation point and changed to two different colors after a random interval. The animals had to identify the higher-ranking color (the target) and allocate their attention to it before the color cue was extinguished and the RDPs returned to white. The monkeys had to maintain central fixation and covert attention until there was a brief motion direction change in the relevant stimulus. In 50% of the trials, the distractor changed before the target, in those cases, the monkeys had to keep pushing the button as only a release after the target change was rewarded with juice. B, Percentage of hits, errors, and mean response time for monkey R (black bars) and monkey S (white bars). Averaged across all color combinations. Error bars denote standard deviation across sessions.

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    Figure 2.

    Implantation sites of the arrays and single-unit activity. A, Schematic macaque brain with area 8 a highlighted according to Petrides (2005) and implantation sites. Photographs were taken during the implantation procedure. Principal and arcuate sulci are indicated. B, Single-cell examples obtained from monkey R illustrating mean normalized responses (ordinate) to different stimulus conditions as a function of time from stimulus onset (left abscissa) and color change onset (right abscissa). Schematic shows the position of the units on the array. Prominent landmarks are indicated. C, Single-cell examples obtained from monkey S for the same conditions. Shading represents SEM (±) at each time point.

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    Figure 3.

    Proportions of selective single units. A, Proportions of selective units were obtained using two-way ANOVA with the factors target location and motion direction in monkey R (right) and monkey S (right) during the postcue period. The markers represent the proportions of selective units found in the population (blue, location; yellow, direction; orange, selectivity for both); the error bars represent 95% confidence intervals. Shading indicates proportion found in data with shuffled trial labels. Asterisks mark significant differences in proportions compared to chance proportions (***, p < 0.001; **, p < 0.05, χ2-test). The majority of selective cells found in monkey R were location selective, and the majority of selective cells found in monkey S were direction selective. B, Timeline of the monkeys’ training. At the time of recording the task presented in this paper (ColorScale Task 2), monkey R had received exclusive training on a spatial attention task involving a color scale (Lennert and Martinez-Trujillo, 2011; 2013). Despite a 2.5-yr pause between the two tasks, monkey R performed the task very well. After its initial training, monkey S was extensively trained on delayed-match-to-sample tasks involving motion directions (for example, Mendoza-Halliday et al., 2014). Monkey S had a >4-yr break from a color scale task, during which it became an expert for motion direction tasks. C, We tracked the proportion of selective electrodes/channels per recording session in each animal to see whether the distributions were approximately stable over time. To test the spatial clustering hypothesis, each electrode’s categorical selectivity of on example session was mapped into the array for monkey R (D) and monkey S (E). Left panels: colors indicate whether units on an electrode were selective. White channels had no activity; black channels indicate unwired electrodes. Right panels: magnitude of spatial clustering of preferred stimuli in monkey R (D) and S (E). Black line depicts Moran’s I (metric of spatial autocorrelation) calculated over increasing spatial scales. Gray shaded area represents chance values.

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    Figure 4.

    Population selectivities. Mean normalized population responses (ordinate) as a function of time from trial event onsets (abscissas) in monkey R (A) and monkey S (B). Left: the population of location-selective cells (n = 167 and n = 32) shows an increased response when the target is in the preferred location (red) after color cue onset (left dashed line) compared with trials in which the target is in the nonpreferred location (blue). Right: the population of direction selective cells (n = 80 and n = 147) shows an increased response in trials with the preferred motion direction (orange) compared with the response in trials with the nonpreferred direction (green). Shading represents SEM (±) at each time point. Arrows indicate the onset of separability between the two curves, determined as the time point when the data in at least five consecutive bins of 20 ms were significantly different from each other (paired t test, p < 0.05).

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    Figure 5.

    Ensemble building procedure. A, We ranked individual units based on their information content, as assessed by SVM and then, starting with the most informative unit, either iteratively added the next best unit to the ensemble (BSU procedure) or looped through the remaining units to identify which pair yielded the highest performance, then looped through the remaining units to identify the best trio, etc. (BE procedure). B, Example session from monkey R when decoding target location. The decoding accuracy in percentage is shown as a function of ensemble size for both building procedures (green, BE; magenta, BSU). Decoding accuracy expected by chance is shown in gray for BSU and in black for BE. Circular markers indicate the individual units’ decoding accuracy and the order in which they get added to the ensemble. Colored markers mark selectivity for the decoded feature. The red line connects the markers that make up the BSU ensemble, and the green line connects those that make up the BE ensemble. C, Example session from monkey S when decoding motion direction.

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    Figure 6.

    Decoding from neuronal ensembles using SVM. We decoded target location (A, B) and motion direction (C, D) during the postcue epoch from monkey R and S, respectively. The SVM’s performance (left ordinate) is shown as a function of ensemble size (abscissa). We truncated the plots to show only the performance for the minimum number of units across sessions. Green lines indicate decoding from BE ensembles, and magenta indicates BSU ensembles. Average decoding performance from ensembles built out of shuffled data are shown in black (BE) and gray (BSU). Dashed lines represent decoding from BE and BSE ensembles when noise correlations had been removed by shuffling trials within the same condition. Shading over the lines indicates SEM (±) for each ensemble size. The lines in the table on top indicate which ensemble sizes were significantly different from each other (p < 0.05) for the indicated comparisons. Circular markers indicate the individual units’ decoding performance once they got added to the ensembles. The right ordinate indicates decoding performance for the maximum ensemble sizes averaged across sessions. We compared median SVM performance of the ensembles that had produced the highest decoding accuracy for each stimulus class independently in monkey R (E) and monkey S (F). Error bars represent standard deviations across recording sessions.

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    Figure 7.

    Relationship between decoding accuracy and monkeys’ behavior. We used the BE ensemble with the highest decoding accuracy to decode target location from the neuronal activity during different trial outcomes (black, averaged across all trials; white, correct trials only; dark gray, error trials; light gray, false positives only) independently for monkey R (A) and monkey S (B). Error bars represent standard deviations across recording sessions. Asterisks mark significant differences in mean accuracy compared to chance decoding accuracy (***, p < 0.001, *, p < 0.05; exact test). We repeated this analysis for motion direction in monkey R (C) and monkey S (D).

Tables

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    Table 1.

    Statistical analyses

    LocationComparisonData StructureType of TestObserved Power
    aTask-relatedness in monkey R and SNormally distributedWilcoxon rank-sumR: 2.89 × 10−206 – 0.0481; S: 3.79 × 10−102 – 0.0498
    bSingle-unit selectivity in monkey RNormally distributed2-factor ANOVALocation: 2.08 × 10−58 – 0.0486; Direction: 1.16 × 10−12 – 0.0496
    Single-unit selectivity in monkey SNormally distributed2-factor ANOVALocation: 3.13 × 10−5 – 0.0496; Direction: 7.54 × 10−38 – 0.0445
    c, fLocation selectivity vs. chance in monkey R (c) and S (f)Normally distributedχ2 testR: 8.29 × 10−10; S: 0.6972
    d, gDirection selectivity vs. chance in monkey R (d) and S (g)Normally distributedχ2 testR: 0.0019; S: 4.13 × 10−10
    e, hOverlapping selectivity vs. chance in monkey R (e) and S (h)Normally distributedχ2 testR: 0.0040; S: 0.1016
    iLatency of significant difference in responses to preferred and nonpreferred location in monkey R and SNormally distributedStudent’s t testR: T = 12.36 ± 5.09; p = 2.46 × 10−45 – 0.0235; S: T = 4.15 ± 1.61; p = 2.98 × 10−8 – 0.0486
    jLatency of difference in responses to directions in monkey R and SNormally distributedStudent’s t testR: T = 7.14 ± 2.98; p = 4.63 × 10−21 – 0.0461; S: T = 11.41 ± 3.57; p = 4.79 × 10−37 – 0.0253
    k, oDecoding attended location using BSU approach vs. chance in monkey R (k) and S (o)Normally distributedExact testR: <0.01; S: >0.2400
    l, pDecoding attended location using BE approach vs. chance in monkey R (l) and S (p)Normally distributedExact testR: <0.01; S: >0.08
    m, nDecoding location from decorrelated BE (m) and BSU (n) ensembles in monkey RNormally distributedPaired t testBE: p = 0.0091 – 0.0489; BSU: p = 0.2074
    q, rDecoding direction from decorrelated BE (q) and BSU (r) ensembles in monkey SNormally distributedPaired t testBE: p = 1.59 × 10−4 – 0.0495; BSU: p = 0.0373 – 0.0499
    sComparing BE Nmax decoding performance in monkey S to chanceNormally distributedExact test0.8000
    t, uDecoding motion direction using BSU approach vs. chance in monkey R (t) and S (u)Normally distributedExact testR: <0.01; S: <0.01
    v, wDecoding motion direction using BE approach vs. chance in monkey R (v) and S (w)Normally distributedExact testR: <0.01; S: <0.01
    x, yDecoding location from decorrelated BE ensembles in monkey R (x) and S (y)Normally distributedPaired t testR: p = 1.43x10−4 – 0.0469S: p = 6.19x10−5 – 0.0458
    z, aaComparing location decoding between animals using BE (z) and BSU (aa)Normally distributedUnpaired t testBE: 5.69 × 10−7 – 2.99 × 10−4; BSU: 1.05 × 10−5 – 4.02 × 10−4
    bb, ccComparing motion direction decoding between animals using BE (bb) and BSU (cc)Normally distributedUnpaired t testBE: 2.74 × 10−6 – 0.0080; BSU: 1.46 × 10−5 – 0.0191
    dd, eeComparing max. location decoding performance between ensemble types in monkey R (dd) and S (ee)Normally distributedWilcoxon signed-rankR: 0.1250; S: 0.0625
    ff, ggComparing max. direction decoding performance between ensemble types in monkey R (ff) and S (gg)Normally distributedWilcoxon rank-sumR: 0.1250; S: 0.0625
    hhComparing maximum location decoding performance between ensemble types for each recording sessionNormally distributedWilcoxon signed-rank0.0039
    iiComparing maximum direction decoding performance between ensemble types for each recording sessionNormally distributedWilcoxon signed-rank0.0039
    jjComparing ensemble sizes with maximum decoding performance across stimulus featuresNormally distributedWilcoxon signed-rank0.0198
    kkComparing ensemble sizes with 90% of maximum decoding performance across stimulus featuresNormally distributedWilcoxon signed-rank0.0293
    ll, mmDecoding attended location across all trial outcomes vs. chance in monkey R (ll) and S (mm)Normally distributedExact testR: <0.01; S: 0.2840
    nn, ooDecoding location across all hit trials vs. chance in monkey R (nn) and S (oo)Normally distributedExact testR: <0.01; S: 0.0160
    pp, qqDecoding location across all error trials vs. chance in monkey R (pp) and S (qq)Normally distributedExact testR: 0.4300; S: 0.3760
    rr, ssDecoding location across all false positive trials vs. chance in monkey R (rr) and S (ss)Normally distributedExact testR: 0.4600; S: 0.6600
    tt, uuDecoding motion direction in across all outcomes vs. chance in monkey R (tt) and S (uu)Normally distributedExact testR: <0.01; S: <0.01
    vv
    ww
    Decoding motion direction across all hit trials vs. chance in monkey R (vv) and S (ww)Normally distributedExact testR: <0.01; S: <0.01
    xx, yyDecoding motion direction across all error trials vs. chance in monkey R (xx) and S (yy)Normally distributedExact testR: 0.5500; S: <0.01
    zz, aaaDecoding motion direction in false positive trials vs. chance in monkey R (zz) and S (aaa)Normally distributedExact testR: 0.3850; S: <0.01
    • Superscript letters refer to the statistical tests in figures, Results, and Tables 2 and 3.

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    Table 2.

    Ensemble decoding performance and ensemble size when decoding target location for each recording session in both animals

    Recording sessionMaximum BE performance (%)BE size at maximum performanceBE size at 90% of maximum performanceMaximum BSU performance (%)BSU size at maximum performanceBSU size at 90% of maximum performanceTotal n
    Monkey R
        Day 186.6755880.001033116
        Day 287.5552686.12271194
        Day 390.8398389.88527116
        Day 493.3469492.011228136
    Monkey S
        Day 160.6911155.653047112
        Day 260.9345959.4856173
        Day 363.4112159.30703177
        Day 461.57154857.32115761
        Day 557.73156154.3015568
    • Detailed list of what the maximum decoding accuracy was and at which ensemble size it was achieved, measured separately for the BE and BSU methods. Because the estimates are noisy and the decoding performance saturates, the ensemble sizes at which 90% of the maximum performance were achieved are also listed. The data are divided up into the individual sessions recorded from each animal. Decoding performances between ensemble types as well as ensemble sizes were compared across the nine sessions using Wilcoxon signed-rank tests (p < 0.05).

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    Table 3.

    Ensemble decoding performance and ensemble size when decoding motion direction for each recording session in both animals

    Recording sessionMaximum BE performance (%)BE size at maximum performanceBE size at 90% of maximum performanceMaximum BSU performance (%)BSU size at maximum performanceBSU size at 90% of maximum performanceTotal n
    Monkey R
        Day 175.3318273.67986116
        Day 267.31309262.80792794
        Day 371.8788669.959317116
        Day 473.3698770.2613423136
    Monkey S
        Day 191.2933390.11955112
        Day 289.3841387.10321873
        Day 389.51481486.61764977
        Day 487.1034383.8949261
        Day 587.6442587.33663568
    • Same as Table 2 but for the feature motion direction.

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Encoding of Spatial Attention by Primate Prefrontal Cortex Neuronal Ensembles
Theda Backen, Stefan Treue, Julio C. Martinez-Trujillo
eNeuro 8 January 2018, 5 (1) ENEURO.0372-16.2017; DOI: 10.1523/ENEURO.0372-16.2017

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Encoding of Spatial Attention by Primate Prefrontal Cortex Neuronal Ensembles
Theda Backen, Stefan Treue, Julio C. Martinez-Trujillo
eNeuro 8 January 2018, 5 (1) ENEURO.0372-16.2017; DOI: 10.1523/ENEURO.0372-16.2017
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