Demographical data
The ADHD and control groups did not differ in age (t(38)=0.035, p= 0.97, d=0.011, LBF= –0.52) and male/female ratio (X2=0.93, p=0.33). Non-verbal reasoning skills were slightly lower in the group with ADHD (t(32)=1.8, p= 0.083, d=0.6, LBF= 0).
Groups difference on time perception
All participants were well able to perform the psychophysical timing task (depicted in Figure 1A) producing ordered psychometric functions. Figure 1 (panels B-C) shows psychometric functions obtained aggregating all the data together across participants. It is evident, even by inspection, that for the task measuring time perception in the subsecond range (B), the psychometric function of the control participants (black) was steeper than that produced by the sample with ADHD (red). This difference indicates less precision (higher thresholds, Weber Fractions) in individuals with ADHD. Regarding the suprasecond stimuli (C) the psychometric functions have similar slopes between groups, indicating similar sensory precision levels.
The fitting procedure was applied to the data provided by each participant. Figure 2 reports between participants average thresholds (Weber Fractions, Wf) separately for the two perceptual tasks, while single subject data are reported in figure 2 B&C. From visual inspection, it is evident that only the time perceptual thresholds measured for short (subsecond) auditory stimuli were impaired in participants with ADHD, with a clear interaction between tasks and groups.
A RM ANOVA with task (2 levels: Wf subsecond, Wf suprasecond) as repeated measures factor and group (2 levels: ADHD, controls) as between participants factor, revealed a significant effect of task (F(1,36)= 7.38, p= 0.01, η2= 0.12, LBFincl= 2.31), suggesting different thresholds across tasks. Crucially the task*group interaction was highly statistically significant (F(1,36)= 18.04, p< 0.001, η2= 0.29, LBFincl = 2.59) indicating that the groups performed differently across the tasks. Post-hoc analyses confirmed that time thresholds for subsecond stimuli were higher in the ADHD group compared to controls (t(38)=3.98, p<0.001, d= 1.26, LBF= 1.9). On this task, ADHD thresholds were, on average, almost double compared to controls (Wf= 0.23 and 0.12 for ADHD and controls respectively), indicating a severe impairment. Time thresholds for suprasecond stimuli (t(36)=0.26, p=0.79, d= 0.08, LBF= –0.5) were statistically indistinguishable between the groups.
To explore the specificity of the impairment found for the time perception task in the subsecond range, we ran a separate ANCOVA with time thresholds as the dependent variable, groups (ADHD, controls) as the fixed factor and age, non-verbal reasoning, and sex as covariates. Even when partialling out the effect of these covariates, the result remained unchanged with a significant effect on the group (F(1,29)=20.11, p<0.001, η2= 0.33, LBFincl = 2.78).
Table 2
Descriptive Statistics on time thresholds (Weber Fraction)
|
Tasks
|
Groups
|
N
|
Mean (SD)
|
p-value
|
Cohen's d
|
LBF
|
Time subsecond
(0.5s)
|
ADHD
|
20
|
0.23 (0.1)
|
< 0.001***
|
1.26
|
1.9
|
Controls
|
20
|
0.12 (0.05)
|
Time suprasecond
(1.5s)
|
ADHD
|
19
|
0.15 (0.07)
|
0.79
|
0.08
|
–0.5
|
Controls
|
19
|
0.14 (0.06)
|
Two tailed t-tests, α Bonferroni corrected 0.05/2= 0.025
|
To check the discriminant power of the subsecond auditory time thresholds, we ran a linear discriminant analysis with the group as the dependent variable and time thresholds (Wf) as independent variable. The results revealed 72.5% of cases correctly classified. The sensitivity was 60% while specificity was 85%. As a sanity check, the same analysis on suprasecond thresholds (Wf) provides a near to chance level (53%) classification.
Developmental trajectories
To investigate whether the deficit was stable across the age range, we studied the developmental trajectories. Time thresholds for suprasecond stimuli had a similar and not significant dependency with age across both groups (ADHD: r= –0.43, p= 0.062, LBF= 0.15, Controls: r= –0.42, p=0.068, LBF= 0.12), suggesting that both were near to a developmental plateau. The developmental trajectories of time thresholds in the subsecond range were, in contrast, different between the groups. While controls had reached an almost full developmental stage (r= –0.34, p=0.14, LBF= –0.11), the age dependence for participants with ADHD was steeper (r= –0.62 , p=0.003, LBF= 1.2), suggesting a different developmental trend (Figure 3). Confirming partially independent mechanisms, regressing out age, thresholds for subsescond and suprasecond stimuli were not correlated with each other (ADHD: rpartial=0.367, p=0.134, LBF=0.09 ; Controls: rpartial=0.287, p=0.25, LBF= –0.07).
Correlations with clinical symptoms
Within the sample with ADHD, we run correlations and between time thresholds (subsecond and suprasecond) and both general (CGI, CGAS, see Table 1) and specific clinical symptoms (the four parents Conners indexes, see Table 1 for details). For the CGAS test, which provides range scores, we transformed the ranges into categorical values reflecting the symptoms severity (following the test manual: from 1 to 10 with one indicating no symptoms and 10 indicating very severe symptoms). The analyses revealed no meaningful correlations (all p>0.05, min LBF= –0.55, max LBF=0.3).
Perceptual task reliability
It is theoretically possible that the different pattern of results provided by the two time tasks results from different reliability levels. To test this possibility, we measured and compared the reliability of the two psychophysical tasks. Following previous studies [20], we used a “sample-with-replacement” bootstrap technique [21]. For each participant, we calculated two separate thresholds in each task (0.5 or 1.5s), using a random sample of the data (44 trials, sampled with replacement), and then computed the correlation between those two measures, across participants. The process was reiterated 1,000 times. We found that mean correlations for subsecond (0.5s) and suprasecond (1.5s) stimuli were very similar (Pearson’s r= 0.68, r= 0.64, respectively) and not statistically different (bootstrap sign-test p= 0.4). This last control rules out the possibility that the different pattern of results was generated by different reliability levels.
Contextual effects
The paradigm used to measure time thresholds requires the ability to perceive both the stimuli mean and range extremes of the set. The group with ADHD could had excessive contextual effects, which would have inflated thresholds. To check for this possibility, we measured (on aggregate data) the PSEs and thresholds as a function of the magnitude of the preceding stimulus (N-1). To this aim, separately for the two groups and the two tasks, we sorted the aggregated data into two categories in which the preceding stimulus (N-1) was shorter or longer than the stimulus tested in the current trial. The data were then fitted by psychometric functions providing PSEs and thresholds (Weber fraction). The analyses releveled very small effects on PSEs for both groups (ADHD 1.5s= shorter 1.4s, longer 1.5s ; ADHD 0.5s= shorter 0.56s, longer 0.61s ; Controls 1.5s= shorter 1.6s, longer 1.6s ; Controls 0.5s= shorter 0.55s, longer 0.56s), suggesting similar contextual effects. More importantly, for both subdivisions (shorter, longer), the difference between groups on subsecond thresholds remained evident and constant (Figure 4) confirming similar contextual effects.