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. 2022 Jun 6;12(6):745.
doi: 10.3390/brainsci12060745.

Time Perception in Cocaine-Dependent Patients

Affiliations

Time Perception in Cocaine-Dependent Patients

Giovanna Mioni et al. Brain Sci. .

Abstract

The involvement of the dopamine system in modulating time perception has been widely reported. Clinical conditions (e.g., Parkinson's disease, addictions) that alter dopaminergic signaling have been shown to affect motor timing and perceived duration. The present study aimed at investigating whether the effects of chronic stimulant use on temporal processing are time-interval dependent. All participants performed two different time bisection tasks (480/1920 ms and 1200/2640 ms) in which we analysed the proportion of long responses for each stimulus duration as well as an index of perceived duration and one of sensitivity. Regarding the proportion of long responses, we found no differences between groups in either time bisection task but patients had more variable results than controls did in both tasks. This study provides new insight into temporal processing in stimulant-dependent patients. Regardless of the time interval tested, the results showed comparable temporal ability in patients and controls, but higher temporal variability in patients. This finding is consistent with impairment of frontally-mediated cognitive functions involved in time perception rather than impairment in time processing per se.

Keywords: stimulant dependent; time bisection task; time perception.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Proportion of “long” responses as a function of temporal intervals for (A) Short (480/1920 ms) and (B) Long (1200/2640 ms) anchors. Error bars indicate 95% confidence interval.
Figure 2
Figure 2
(A,C) Bisection Point (PSE) and (B,D) Weber ratio (WR) for stimulant dependent and controls. Each dot represents a participant. The thicker line represents the median and the box represents the interquartile range. The grey area represents the kernel density estimation to show the distribution shape of the data. Wider sections of the violin plot represent a higher probability that members of the population will take on the given value; the skinnier sections represent a lower probability.

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