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Dynamic representation of time in brain states

View Article: PubMed Central - PubMed

ABSTRACT

The ability to process time on the scale of milliseconds and seconds is essential for behaviour. A growing number of studies have started to focus on brain dynamics as a mechanism for temporal encoding. Although there is growing evidence in favour of this view from computational and in vitro studies, there is still a lack of results from experiments in humans. We show that high-dimensional brain states revealed by multivariate pattern analysis of human EEG are correlated to temporal judgements. First, we show that, as participants estimate temporal intervals, the spatiotemporal dynamics of their brain activity are consistent across trials. Second, we present evidence that these dynamics exhibit properties of temporal perception, such as scale invariance. Lastly, we show that it is possible to predict temporal judgements based on brain states. These results show how scalp recordings can reveal the spatiotemporal dynamics of human brain activity related to temporal processing.

No MeSH data available.


Experimental task and results.(a) The task consisted of a computerised shoot the target task. In regular trials a bulls-eye moved towards the centre of the screen reaching it in 1.50 seconds. Participants were instructed to produce a “shot” when the target passed trough the “aiming sight” in the centre of the screen. In Test trials, target trajectory was masked and automatic shots were given at seven different intervals (0.80, 0.98, 1.22, 1.50, 1.85, 2.27 and 2.80 seconds). Participants had to judge whether the shot occurred after an interval “shorter”, “equal”, or “longer” than the time the target normally took to reach screen centre. (b) Psychometric functions describing performance on Test trials. Right panel shows estimated parameters from the psychometric functions: Points of Subjective Equality (PSE), Just Noticeable Difference (JND) and Weber ratio. Plots show mean and standard error of the mean (s.e.m.) across participants. (c) Contingent Negative Variation (CNV, mean ± s.e.m.) for central-parietal electrodes for Test trials longer or equal to 2.27 seconds (dashed lines indicates intervals where the shot could have been presented). The CNV peaks at the memorised interval. Right panel shows the topographies for the intervals close to possible moments of shot presentation.
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f1: Experimental task and results.(a) The task consisted of a computerised shoot the target task. In regular trials a bulls-eye moved towards the centre of the screen reaching it in 1.50 seconds. Participants were instructed to produce a “shot” when the target passed trough the “aiming sight” in the centre of the screen. In Test trials, target trajectory was masked and automatic shots were given at seven different intervals (0.80, 0.98, 1.22, 1.50, 1.85, 2.27 and 2.80 seconds). Participants had to judge whether the shot occurred after an interval “shorter”, “equal”, or “longer” than the time the target normally took to reach screen centre. (b) Psychometric functions describing performance on Test trials. Right panel shows estimated parameters from the psychometric functions: Points of Subjective Equality (PSE), Just Noticeable Difference (JND) and Weber ratio. Plots show mean and standard error of the mean (s.e.m.) across participants. (c) Contingent Negative Variation (CNV, mean ± s.e.m.) for central-parietal electrodes for Test trials longer or equal to 2.27 seconds (dashed lines indicates intervals where the shot could have been presented). The CNV peaks at the memorised interval. Right panel shows the topographies for the intervals close to possible moments of shot presentation.

Mentions: Human participants (n = 14) performed a temporal categorisation task. The experiment was based on a “shoot the target” task that has been previously used to study temporal perception2021. The task consisted of two types of trials. In Regular trials, a visual target transited from the left periphery of the screen towards a central target zone taking 1.5 seconds to reach screen centre, where there was an “aiming sight” (Fig. 1a). In these trials, participants were instructed to press a button in order to produce a “shot” (an audiovisual stimulus) when the target passed the aiming sight. In Test trials, the trajectory of the target was masked by an occluder and only the aiming sight remained visible throughout the entire trial. In these trials, participants did not see the movement of the target, but only heard the start of its movement by a characteristic sound that targets made when they started moving (both in Regular and in Test trials). One automatic shot was given in each Test trial in one of seven different intervals (0.8, 0.98, 1.22, 1.5, 1.85, 2.27 or 2.8 s) after the sound indicated that the target started moving. Participants had to judge whether the shot occurred at an interval “shorter”, “equal”, or “longer” than the time the target normally took to reach screen centre. Test and Regular trials were presented in a pseudo randomised order during the experimental session in which more than three consecutive Test trials were not allowed.


Dynamic representation of time in brain states
Experimental task and results.(a) The task consisted of a computerised shoot the target task. In regular trials a bulls-eye moved towards the centre of the screen reaching it in 1.50 seconds. Participants were instructed to produce a “shot” when the target passed trough the “aiming sight” in the centre of the screen. In Test trials, target trajectory was masked and automatic shots were given at seven different intervals (0.80, 0.98, 1.22, 1.50, 1.85, 2.27 and 2.80 seconds). Participants had to judge whether the shot occurred after an interval “shorter”, “equal”, or “longer” than the time the target normally took to reach screen centre. (b) Psychometric functions describing performance on Test trials. Right panel shows estimated parameters from the psychometric functions: Points of Subjective Equality (PSE), Just Noticeable Difference (JND) and Weber ratio. Plots show mean and standard error of the mean (s.e.m.) across participants. (c) Contingent Negative Variation (CNV, mean ± s.e.m.) for central-parietal electrodes for Test trials longer or equal to 2.27 seconds (dashed lines indicates intervals where the shot could have been presented). The CNV peaks at the memorised interval. Right panel shows the topographies for the intervals close to possible moments of shot presentation.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5385543&req=5

f1: Experimental task and results.(a) The task consisted of a computerised shoot the target task. In regular trials a bulls-eye moved towards the centre of the screen reaching it in 1.50 seconds. Participants were instructed to produce a “shot” when the target passed trough the “aiming sight” in the centre of the screen. In Test trials, target trajectory was masked and automatic shots were given at seven different intervals (0.80, 0.98, 1.22, 1.50, 1.85, 2.27 and 2.80 seconds). Participants had to judge whether the shot occurred after an interval “shorter”, “equal”, or “longer” than the time the target normally took to reach screen centre. (b) Psychometric functions describing performance on Test trials. Right panel shows estimated parameters from the psychometric functions: Points of Subjective Equality (PSE), Just Noticeable Difference (JND) and Weber ratio. Plots show mean and standard error of the mean (s.e.m.) across participants. (c) Contingent Negative Variation (CNV, mean ± s.e.m.) for central-parietal electrodes for Test trials longer or equal to 2.27 seconds (dashed lines indicates intervals where the shot could have been presented). The CNV peaks at the memorised interval. Right panel shows the topographies for the intervals close to possible moments of shot presentation.
Mentions: Human participants (n = 14) performed a temporal categorisation task. The experiment was based on a “shoot the target” task that has been previously used to study temporal perception2021. The task consisted of two types of trials. In Regular trials, a visual target transited from the left periphery of the screen towards a central target zone taking 1.5 seconds to reach screen centre, where there was an “aiming sight” (Fig. 1a). In these trials, participants were instructed to press a button in order to produce a “shot” (an audiovisual stimulus) when the target passed the aiming sight. In Test trials, the trajectory of the target was masked by an occluder and only the aiming sight remained visible throughout the entire trial. In these trials, participants did not see the movement of the target, but only heard the start of its movement by a characteristic sound that targets made when they started moving (both in Regular and in Test trials). One automatic shot was given in each Test trial in one of seven different intervals (0.8, 0.98, 1.22, 1.5, 1.85, 2.27 or 2.8 s) after the sound indicated that the target started moving. Participants had to judge whether the shot occurred at an interval “shorter”, “equal”, or “longer” than the time the target normally took to reach screen centre. Test and Regular trials were presented in a pseudo randomised order during the experimental session in which more than three consecutive Test trials were not allowed.

View Article: PubMed Central - PubMed

ABSTRACT

The ability to process time on the scale of milliseconds and seconds is essential for behaviour. A growing number of studies have started to focus on brain dynamics as a mechanism for temporal encoding. Although there is growing evidence in favour of this view from computational and in vitro studies, there is still a lack of results from experiments in humans. We show that high-dimensional brain states revealed by multivariate pattern analysis of human EEG are correlated to temporal judgements. First, we show that, as participants estimate temporal intervals, the spatiotemporal dynamics of their brain activity are consistent across trials. Second, we present evidence that these dynamics exhibit properties of temporal perception, such as scale invariance. Lastly, we show that it is possible to predict temporal judgements based on brain states. These results show how scalp recordings can reveal the spatiotemporal dynamics of human brain activity related to temporal processing.

No MeSH data available.