Timing deficiencies in amnestic Mild Cognitive Impairment: Disentangling clock and memory processes

Maaß, Sarah; Riemer, Martin; Wolbers, Thomas; Rijn, Hedderik van

doi:10.1016/j.bbr.2019.112110

Cited by 23 publications

(55 citation statements)

References 53 publications

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“…The crossing point between the plotted function and the line of unison took place at around 2-3 s. Taking the slope of linear correlation between the presented and reproduced duration as an index of the migration effect, the MMSE score showed a significant correlation with the slope in our PD patients, suggesting an association with short-term or working memory. A similar correlation between the degree of migration effect and cognitive dysfunction has been reported in patients with mild cognitive impairment (Dušek et al, 2012;Maaß et al, 2019).…”

Section: Time Reproduction Tasksupporting

confidence: 81%

Time Distortion in Parkinsonism

et al. 2021

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Although animal studies and studies on Parkinson’s disease (PD) suggest that dopamine deficiency slows the pace of the internal clock, which is corrected by dopaminergic medication, timing deficits in parkinsonism remain to be characterized with diverse findings. Here we studied patients with PD and progressive supranuclear palsy (PSP), 3–4 h after drug intake, and normal age-matched subjects. We contrasted perceptual (temporal bisection, duration comparison) and motor timing tasks (time production/reproduction) in supra- and sub-second time domains, and automatic versus cognitive/short-term memory–related tasks. Subjects were allowed to count during supra-second production and reproduction tasks. In the time production task, linearly correlating the produced time with the instructed time showed that the “subjective sense” of 1 s is slightly longer in PD and shorter in PSP than in normals. This was superposed on a prominent trend of underestimation of longer (supra-second) durations, common to all groups, suggesting that the pace of the internal clock changed from fast to slow as time went by. In the time reproduction task, PD and, more prominently, PSP patients over-reproduced shorter durations and under-reproduced longer durations at extremes of the time range studied, with intermediate durations reproduced veridically, with a shallower slope of linear correlation between the presented and produced time. In the duration comparison task, PD patients overestimated the second presented duration relative to the first with shorter but not longer standard durations. In the bisection task, PD and PSP patients estimated the bisection point (BP50) between the two supra-second but not sub-second standards to be longer than normal subjects. Thus, perceptual timing tasks showed changes in opposite directions to motor timing tasks: underestimating shorter durations and overestimating longer durations. In PD, correlation of the mini-mental state examination score with supra-second BP50 and the slope of linear correlation in the reproduction task suggested involvement of short-term memory in these tasks. Dopamine deficiency didn’t correlate significantly with timing performances, suggesting that the slowed clock hypothesis cannot explain the entire results. Timing performance in PD may be determined by complex interactions among time scales on the motor and sensory sides, and by their distortion in memory.

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Section: Time Reproduction Tasksupporting

confidence: 81%

Time Distortion in Parkinsonism

et al. 2021

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“…Second, it should generalize across tasks : once a parameter has been estimated by fitting a model to an individual, the same parameter’s value should predict that individual’s performance in other tasks. For example, Maaß and colleagues (2019) were able to estimate the variability of the internal clock using a simple time production task (Maaß & van Rijn, 2018), and use it to predict performance in a more elaborated temporal reproduction task in a pre-clinical population.…”

Section: Introductionmentioning

confidence: 99%

Reflections of Idiographic Long-Term Memory Characteristics In Resting-State Neuroimaging Data

Zhou

Sense

Rijn

et al. 2020

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Translational applications of cognitive science depend on having predictive models at the individual, or idiographic, level. However, idiographic model parameters, such as working memory capacity, often need to be estimated from specific tasks, making them dependent on task-specific assumptions. Here, we explore the possibility that idiographic parameters reflect an individual's biology and can be identified from task-free neuroimaging measures. To test this hypothesis, we correlated a reliable behavioral trait, the individual rate of forgetting in long-term memory, with a readily available task-free neuroimaging measure, the resting-state EEG spectrum. Using an established, adaptive fact-learning procedure, the rate of forgetting for verbal and visual materials was measured in a sample of 50 undergraduates from whom we also collected eyes-closed resting state EEG data. A statistical analysis revealed that the individual rates of forgetting were significantly correlated across verbal and visual materials, in agreement previous results. Importantly, both rates correlated with power levels in the alpha (8-13 Hz) and low beta (13-15 Hz) frequency bands, with the correlation between verbal rate of forgetting and low beta power over the right parietal site being significant even when accounting for multiple comparisons. The results suggest that computational models could be individually tailored for prediction using idiographic parameter values derived from inexpensive, task-free imaging recordings.

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“…Although there is abundant behavioral evidence for Bayesian integration in human time perception (Acerbi, Wolpert, & Vijayakumar, 2012;Cicchini, Arrighi, Cecchetti, Giusti, & Burr, 2012;Gu, Jurkowski, Lake, Malapani, & Meck, 2015;Hallez, Damsma, Rhodes, van Rijn, & Droit-Volet, 2019;Jazayeri & Shadlen, 2010;Maaß, Riemer, Wolbers, & van Rijn, 2019;Maaß, Schlichting, & van Rijn, 2019;Roach, McGraw, Whitaker, & Heron, 2017;Schlichting et al, 2018;Shi, Church, & Meck, 2013), its temporal locus and neural underpinnings are not yet understood.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, the prior distribution has been shown to be dynamically updated, such that more recent intervals have a greater influence on the current estimate (Dyjas, Bausenhart, & Ulrich, 2012; Taatgen & van Rijn, 2011; Wiener, Thompson, & Branch Coslett, 2014). Although there is abundant behavioral evidence for Bayesian integration in human time perception (Acerbi, Wolpert, & Vijayakumar, 2012; Cicchini, Arrighi, Cecchetti, Giusti, & Burr, 2012; Gu, Jurkowski, Lake, Malapani, & Meck, 2015; Hallez, Damsma, Rhodes, van Rijn, & Droit-Volet, 2019; Jazayeri & Shadlen, 2010; Maaß, Riemer, Wolbers, & van Rijn, 2019; Maaß, Schlichting, & van Rijn, 2019; Roach, McGraw, Whitaker, & Heron, 2017; Schlichting et al, 2018; Shi, Church, & Meck, 2013), its temporal locus and neural underpinnings are not yet understood.…”

Section: Introductionmentioning

confidence: 99%

Temporal context actively shapes EEG signatures of time perception

Damsma

Schlichting

Rijn

2020

Preprint

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Our subjective perception of time is optimized to temporal regularities in the environment. This is illustrated by the central tendency effect: when estimating a range of intervals, short intervals are overestimated whereas long intervals are underestimated to reduce the overall estimation error. Most models of interval timing ascribe this effect to the weighting of the current interval with previous memory traces after the interval has been perceived. Alternatively, the perception of the duration could already be flexibly tuned to its temporal context. We investigated this hypothesis using an interval reproduction task with a shorter and longer interval range. As expected, reproductions were biased towards the subjective mean of each presented range. EEG analysis showed that temporal context affected neural dynamics during the perception phase. Specifically, longer previous durations decreased CNV and P2 amplitude and increased beta power. In addition, multivariate pattern analysis showed that it is possible to decode context from the transient EEG signal quickly after the onset and offset of the perception phase. Together, these results suggest that temporal context creates dynamic expectations which actively affect the perception of duration.The subjective sense of duration does not arise in isolation, but is informed by previous experiences. This is demonstrated by abundant evidence showing that duration estimates are biased towards previously perceived time intervals. However, it is yet unknown whether this temporal context actively affects perception or asserts its influence in later, post-perceptual stages as proposed by most current formal models of this task. Using an interval reproduction task, we here show that EEG signatures flexibly adapt to the temporal context during perceptual encoding. Furthermore, interval history could be decoded from the transient EEG signal even when the current duration was identical.All in all, our results suggest that context actively influences perception.

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Timing deficiencies in amnestic Mild Cognitive Impairment: Disentangling clock and memory processes

Cited by 23 publications

References 53 publications

Time Distortion in Parkinsonism

Time Distortion in Parkinsonism

Reflections of Idiographic Long-Term Memory Characteristics In Resting-State Neuroimaging Data

Temporal context actively shapes EEG signatures of time perception

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