Article Figures & Data
Figures
- Figure 1.
Experimental setup and behavioral effects of pharmacological and pupil-linked elevations of neuromodulatory activity. A, Schematic overview of experimental sessions. Participants came to the lab on four occasions: one intake session and three experimental sessions. On the experimental sessions, participants received either placebo (PLC, data in orange), donepezil (DNP, 5 mg, data in green), or atomoxetine (ATX, 40 mg, data in blue). Drug order was counterbalanced across participants. To account for differences in pharmacokinetics (ATX takes ∼2 h to reach peak plasma level, DNP ∼4 h), while keeping participants blind for the drug conditions, we administered two pills at two fixed times on every session. The first pill (administered at the beginning of the session) contained either PLC (for PLC and ATX session) or DNP (DNP session), and the second pill (administered 2 h later) was either a PLC (for PLC and DNP session) or ATX (ATX session). Behavioral testing started 4 h after administration of the first pill. B, Schematic representation of the behavioral task. Participants reported the orientation of a centrally presented Gabor patch as clockwise (CW) versus counterclockwise (CCW). At the same time, participants provided a binary report on how confident they were in their perceptual judgment (high confidence or low confidence). C, Perceptual sensitivity (d’) for all drug conditions and confidence levels. ATX, but not DNP, significantly increased d’ compared with PLC. D, The proportion of high confident answers was not modulated by drug condition. E, Metacognitive sensitivity (meta-d’) was not modulated by drug condition. F, Metacognitive efficiency (M-diff, meta-d’ − d’) was lower under ATX as compared with PLC. G, Hierarchical Bayesian estimation of M-ratio (meta-d’ / d’). Density plots show posterior distributions for drug effects (drug—PLC) on log-transformed M-ratio scores. Log-transformed values below zero are indicative of a reduction in M-ratio. Horizontal bars indicate the 95% credibility intervals for the ATX effect (blue) and DNP effect (green). The reported p value (note: capital letter) is the probability that the true drug effect is greater than zero. H, Same as C–F, but for prestimulus pupil size bins, ranging from relatively small (light blue) to relatively large (dark blue). Linear (indicated with /) and quadratic (indicated with ∩) regression fits are plotted when significant. Note that the x-axis depicts the average pupil diameter of each bin (in % of block mean), but that the regression analyses were performed on bin number (1–5). I, Same as G, but here the density plot indicates the posterior distribution for beta weights describing a linear relation between prestimulus pupil size bin and M-ratio. Error bars indicate standard error of the mean (SEM).
- Figure 2.
Multivariate decoding of Gabor orientation. A, During the localizer task (illustration shown), participants reported a slight tilt offset of ±2° from diagonal, by pressing a button with their left hand (for horizontally tilted Gabors: −47° and +47°) or right hand (for vertically tilted Gabors: −43° and +43°). Gabor orientation and behavioral responses were therefore independent (see Materials and Methods for details). B, Temporal generalization of stimulus orientation decoding in the localizer task (AUC). Training time is shown on the y-axis, testing time on the x-axis. Black demarked areas represent clusters that survived cluster-based permutation testing at p ≤ 0.05. C, Topographic maps showing the activity patterns (from transformed classifier weights) in two separate time windows. D, Tenfold within-localizer decoding AUC taken from the cluster of panel B, separated by drug. E, Schematic of cross-task decoding setup. A linear discriminant was trained to distinguish CCW (red dots, example data) from CW (blue dots) during the localizer task (top panel). This linear discriminant was then presented with data from the main task, after which it classified trials as containing CCW or CW information (bottom panel). F, Temporal generalization of stimulus orientation cross-decoding (AUC) when training on the (localizer task, y-axis) and testing on the main task (discrimination task, on the x-axis). Black demarked areas represent clusters that survived cluster-based permutation testing at p ≤ 0.05. G, Cross-decoding AUC taken from the cluster of panel E, separated by drug, accuracy, and confidence. Note that conf. demarks the factor decision confidence and acc. demarks the factor decision accuracy. All error bars indicate SEM.
- Figure 3.
Response-locked ERPs over centroparietal and frontal cortical regions. A, Topographic maps of response-locked activity, in steps of 100 ms. The bottom topographic map shows spatial ROIs for the CPP (three electrodes at over centroparietal areas: CP1, CP2, CPz) and the FP (three electrodes over frontal areas: F1, F2, Fz) analyses as white markers. B, Response-locked CPP shown for the ATX, DNP, and PLC condition, split up for high confident (solid lines) versus low confident (dotted lines) and correct (opaque lines) versus incorrect (transparent lines) trials. The horizontally plotted black dots indicate effects that survived across time cluster-correction. *The effects of ATX were tested with a cluster-corrected one-sided t test (ATX > PLC, see Materials and Methods). C, Average CPP amplitudes from the cluster in which ATX modulated CPP amplitude. The three drug conditions are plotted on the x-axis, separated for high and low confidence decisions. Correct trials are plotted in opaque lines and incorrect trials in transparent lines. The inset bar plot on the right shows the overall CPP amplitude (averaged across confidence and accuracy) for each drug. D, Same as B, but for FP ERP component. E, Average FP amplitudes within the cluster where the three-way interaction (drug × accuracy × confidence) was significant. The three drug conditions are plotted on the x-axis, separated for high and low confidence decisions. Correct trials are plotted in opaque lines and incorrect trials in transparent lines. The inset bar plot on the right shows the FP amplitude interaction effect (accuracy × confidence) for each drug, defined as [(Chi − Clo) + (Ilo − Ihi)], with Chi, correct decision, high confidence; Clo, correct decision, low confidence; Ilo, incorrect decision, low confidence; and Ihi, incorrect decision, high confidence. All error bars indicate SEM.
- Figure 4.
Relation between pupil size and the CPP and FP. Same as Figure 3, but now using five prestimulus pupil size bins as variables instead of the pharmacological manipulation. A, Response-locked CPP shown for each pupil size bin, split up for high confident (solid lines) versus low confident (dotted lines) and correct (opaque lines) versus incorrect (transparent lines) trials. B, CPP amplitudes extracted from the temporal cluster in A (statistics and cluster from Fig. 3B), shown for each condition as a factor of pupil size. The right panel shows the CPP amplitude per pupil bin and the regression results. C, Response-locked FP (accuracy × confidence), as a factor of pupil size bin. D, FP amplitudes extracted from cluster in C (same as in Fig. 3D), shown for each condition. The inset bar plot on the right shows the FP amplitude interaction effect (accuracy × confidence) for each drug, defined as [(Chi − Clo) + (Ilo − Ihi)], with Chi, correct decision, high confidence; Clo, correct decision, low confidence, high confidence; Ilo, incorrect decision, low confidence; and Ihi, incorrect decision. Note that the regression analyses of the utmost right panels were performed with bin number as independent variable, but the x-axis shows the mean pupil size (in % of block mean) for each bin. All error bars indicate SEM.
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