Article Figures & Data
Figures
- Figure 1.
Schematic illustration of the experimental design during the detection and discrimination tasks. The first two rows portray examples of visual cues displayed to participants during detection and discrimination trials. During each trial, a liquid tastant (black) was embedded in a sequence of water pulses. Participants were to speededly respond by button press during both tasks.
- Figure 2.
A, Signal strength quantified as the average GFP computed within-subjects as the standard deviation of the event-related potentials over 64 electrodes for each of the tastants and water over detection trials (left) and discrimination trials (right). Salty and sour tastants show a stronger signal than sweet and bitter tastants, but less strongly so for discrimination trials. Note that the onset of the liquid stimulation (for all tastes and for water) coincided with the presentation of the fixation cross, resulting in a clear GFP response for water as well. B, Topographical voltage maps for each taste and task represent the grand-averaged mean over a 50-ms time window, early during processing (upper row) and surrounding the decoding onset (lower row) shown in Table 2 and Figure 3C relative to water. Intensity (0–100; C) and pleasantness ratings (-50–50; D) for the two tastant pairs, salty-sour and sweet-bitter. The colored squares show individual participant ratings, the gray lines between two squares indicate that these ratings were given by the same participant. Semitransparent and colored boxplots entail the ratings of all participants (N = 19); the horizontal dashed line within each box represents the median, the bottom and top of the box represent the first and third quartiles, respectively; whiskers show 1.5 times the interquartile range. The colors represent the taste. Significance is indicated above the plot area: ns p > 0.05; *p < 0.05; ***p < 0.001.
- Figure 3.
A, Average within-subject decoding generalization across time for each of the four tastes by task. Detection performance is obtained for the classification of a tastant against water (detection task trials); discrimination performance is obtained for the classification between two tastants (discrimination task trials). The diagonals of the matrices (identical training and testing time) correspond to the common decoding approach. The x-axis displays training times which represents the stability of an average taste pattern. The y-axis displays generalization or testing times which represents the emergence of the average pattern (x-axis) within individual trials. Warm colors reflect average performance increases as compared to chance level (50%), cold colors reflect decreases; black contour lines indicate statistical significance of the grand average as assessed via one-sided cluster-adjusted binomial tests (p < 0.05). Salty and sour show earlier and better detection performance than sweet and bitter, whereas discrimination performance is less pronounced than detection performance in either case. B, Behavioral data of the button press RTs of correct responses and accuracy (average per participant, N = 20) color-coded for tasks (blue indicating detection trials, gray discrimination trials). The horizontal line in each boxplot represents the median, the bottom and top of the box represent the first and third quartiles, respectively; whiskers show 1.5 times the interquartile range, dots indicate outliers. Participants are faster and more accurate at detecting salty and sour than they are at discriminating the two tastants. Sweet and bitter show no difference in RTs but higher accuracy at discriminating the two as opposed to detection from water. C, Neural data of onset times of above-chance performance (determined at the single-trial level; averaged per participant; N = 20 for sweet and bitter tastes, and N = 18 for salty and sour tastes) and of the accuracy indicating the percentage of trials for which such an onset was determinable (boxplot parameters as in B). The neural findings correspond closely to the behavioral data in that salty and sour are classified faster and more accurately in detection trials. Sweet and bitter show no significant difference between the two tasks. D, Correlations of the difference values between the average discrimination and detection neural onset times and button press RTs (each point in a graph represents one participant). Color-coded dashed lines represent linear regression models; horizontal and vertical gray dashed lines indicate the points of no difference between discrimination and detection latencies on the respective axis. The observed effects were significantly positively correlated for three of four tastes, such that an early neural difference (or lack thereof) corresponded to the same behavioral effect.
Tables
Detection Discrimination RT (ms) Accuracy (%) RT (ms) Accuracy (%) Taste M SEM M SEM M SEM M SEM Salty 609 24 96.1 1.1 1029 39 67.6 4.3 Sour 642 24 95.9 0.8 964 38 80.6 4.3 Bitter 905 51 81.9 3.2 938 45 93.3 1.7 Sweet 835 37 91.1 1.8 881 36 92.0 2.0 Water 906 38 95.6 1.0 - - - - RT = reaction time.
Detection Discrimination Onset (ms) Accuracy (%) Onset (ms) Accuracy (%) M SEM M SEM M SEM M SEM Salty 136 12 92.2 1.2 304 18 66.8 5.1 Sour 147 11 95.4 1.1 285 25 61.7 4.7 Bitter 250 22 80.6 3.0 242 12 79.5 4.6 Sweet 245 17 80.8 3.1 242 15 80.0 4.7
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