Time to imagine moving: Simulated motor activity affects time perception

Sensing the passage of time is important for countless daily tasks, yet time perception is easily influenced by perception, cognition, and emotion. Mechanistic accounts of time perception have traditionally regarded time perception as part of central cognition. Since proprioception, action execution, and sensorimotor contingencies also affect time perception, perception-action integration theories suggest motor processes are central to the experience of the passage of time. We investigated whether sensory information and motor activity may interactively affect the perception of the passage of time. Two prospective timing tasks involved timing a visual stimulus display conveying optical flow at increasing or decreasing velocity. While doing the timing tasks, participants were instructed to imagine themselves moving at increasing or decreasing speed, independently of the optical flow. In the direct-estimation task, the duration of the visual display was explicitly judged in seconds while in the motor-timing task, participants were asked to keep a constant pace of tapping. The direct-estimation task showed imagining accelerating movement resulted in relative overestimation of time, or time dilation, while decelerating movement elicited relative underestimation, or time compression. In the motor-timing task, imagined accelerating movement also accelerated tapping speed, replicating the time-dilation effect. The experiments show imagined movement affects time perception, suggesting a causal role of simulated motor activity. We argue that imagined movements and optical flow are integrated by temporal unfolding of sensorimotor contingencies. Consequently, as physical time is relative to spatial motion, so too is perception of time relative to imaginary motion.

Relationships between Freezing of Gait Severity and Cognitive Deficits in Parkinson’s Disease

Freezing of gait (FOG) is one of the most debilitating motor symptoms experienced by patients with Parkinson’s disease (PD), as it can lead to falls and a reduced quality of life. Evidence supports an association between FOG severity and cognitive functioning; however, results remain debatable. PD patients with (PDFOG+, n = 41) and without FOG (PDFOG–, n = 39) and control healthy subjects (n = 41) participated in this study. The NIH toolbox cognition battery, the Montreal Cognitive Assessment (MoCA), and the interval timing task were used to test cognitive domains. Measurements were compared between groups using multivariable models and adjusting for covariates. Correlation analyses, linear regression, and mediation models were applied to examine relationships among disease duration and severity, FOG severity, and cognitive functioning. Significant differences were observed between controls and PD patients for all cognitive domains. PDFOG+ and PDFOG– exhibited differences in Dimensional Change Card Sort (DCCS) test, interval timing task, and MoCA scores. After adjusting for covariates in two different models, PDFOG+ and PDFOG– differed in both MoCA and DCCS scores. In addition, significant relationships between FOG severity and cognitive function (MoCA, DCCS, and interval timing) were also found. Regression models suggest that FOG severity may be a predictor of cognitive impairment, and mediation models show the effects of cognitive impairment on the relationship between disease severity and FOG severity. Overall, this study provides insight into the relationship between cognitive and FOG severity in patients with PD, which could aid in the development of therapeutic interventions to manage both.

Design of distributed timing task scheduling system for smart grid

With the rapid development of information technology and the growing scale of enterprise development, more and more enterprise application systems appear due to business scenarios, requiring the system to execute the specified business operations at the planned time, which is the demand of “timed tasks”. The rapid growth of business volume makes the number of timed tasks also increase massively, and the importance of timed task application scenarios requires more and more strict guarantee of reliable triggering of tasks. In this paper, to address these problems, we design and implement a distributed system providing timed task scheduling service based on Quartz, an open source lightweight job scheduling framework, and realize business modules such as timed task control service, trigger execution, lock grabbing trigger, unified configuration management, task load balancing and log management. The system has been tested and put into operation, and has completed the requirements well and achieved the design goals.

Motivation and information in motor performance: modelling of self-efficacy and knowledge of results interaction in a timing task

BACKGROUND: Despite the literature positing a strong relation between motor performance and self-efficacy, few studies address the phenomenon formally. In this sense, how self-efficacy modulates corrections in a trial-to-trial basis and how the performance that individuals consider to be satisfactory modulate both corrections and self-efficacy are not well understood. AIM: The aim of this study is to develop and evaluate a model that relates self-efficacy and performance through a system of difference equations. METHOD: First, we demonstrate the model’s capabilities through constrained simulations. The, to evaluate the model’s grasp of empirical data, we parameterized the model to capture the constant, variable error, self-efficacy and believed satisfactory performance for each individual. RESULTS: The model demonstrates capacity to reproduce these summary results when initial conditions are fed to the system of difference equations. However, we observe features that must be improved and qualitative deviations when individuals demonstrate highly variable behavior. CONCLUSION: The initial results support the current assumptions and included variables in this model.

Central stress allostasis among deprived and continuing marijuana users and non-users

Objective: We examined central nervous system stress allostasis (i.e., stress responses) among deprived and continuing heavy marijuana users and non-users. Method: Participants (N=210; 46.7% female; mean age=21.99; 91.4% White, 94.3% Non-Hispanic) were heavy marijuana users (N=134) and non-users (N=76). Heavy users were randomly assigned to a 3-day marijuana deprivation condition (N=68) or to continue using regularly (N=66). Participants completed 2 threat-of-shock stressor tasks that manipulated stressor predictability by varying shock probability or timing. We measured central stress allostasis via startle potentiation (stressor conditions minus matched no-stressor condition). We examined two group contrasts (heavy use: all heavy users vs. non-users; deprivation: deprived vs. continuing heavy users) on startle potentiation overall and moderated by stressor predictability (unpredictable vs. predictable). Results: Deprivation did not affect startle potentiation overall (timing task: p=0.184; probability task: p=0.328) or by stressor predictability (timing task: p=0.340; probability task: p=0.488). Heavy use did not affect startle potentiation overall (timing task: p=0.213; probability task: p=0.843) or by stressor predictability (timing task: p=0.683; probability task: p=0.348). Post-hoc analyses showed a general startle reactivity X deprivation interaction on startle potentiation overall (timing task: p=0.019; probability task: p=0.056) and by stressor predictability in the probability task (p=0.022) but not in the timing task (p=0.374). Conclusions: A history of marijuana use or acute deprivation did not alter central stress allostasis despite prominent theoretical expectations. This study adds to growing research on central stress allostasis in individuals with a history of drug use and begins to parse moderating roles of individual differences and stressor characteristics.

Single-trial modeling separates multiple overlapping prediction errors during reward processing in human EEG

Learning signals during reinforcement learning and cognitive control rely on valenced reward prediction errors (RPEs) and non-valenced salience prediction errors (PEs) driven by surprise magnitude. A core debate in reward learning focuses on whether valenced and non-valenced PEs can be isolated in the human electroencephalogram (EEG). We combine behavioral modeling and single-trial EEG regression to disentangle sequential PEs in an interval timing task dissociating outcome valence, magnitude, and probability. Multiple regression across temporal, spatial, and frequency dimensions characterized a spatio-tempo-spectral cascade from early valenced RPE value to non-valenced RPE magnitude, followed by outcome probability indexed by a late frontal positivity. Separating negative and positive outcomes revealed the valenced RPE value effect is an artifact of overlap between two non-valenced RPE magnitude responses: frontal theta feedback-related negativity on losses and posterior delta reward positivity on wins. These results reconcile longstanding debates on the sequence of components representing reward and salience PEs in the human EEG.

Validating model-based Bayesian integration using prior–cost metamers

There are two competing views on how humans make decisions under uncertainty. Bayesian decision theory posits that humans optimize their behavior by establishing and integrating internal models of past sensory experiences (priors) and decision outcomes (cost functions). An alternative hypothesis posits that decisions are optimized through trial and error without explicit internal models for priors and cost functions. To distinguish between these possibilities, we introduce a paradigm that probes the sensitivity of humans to transitions between prior–cost pairs that demand the same optimal policy (metamers) but distinct internal models. We demonstrate the utility of our approach in two experiments that were classically explained by Bayesian theory. Our approach validates the Bayesian learning strategy in an interval timing task but not in a visuomotor rotation task. More generally, our work provides a domain-general approach for testing the circumstances under which humans explicitly implement model-based Bayesian computations.

Relationships between freezing of gait severity and cognitive deficits in Parkinson's disease

Introduction: Freezing of gait (FOG) is one of the most debilitating motor symptoms experienced by patients with Parkinson's disease (PD), as it can lead to falls and reduced quality of life. Evidence supports an association between FOG severity and cognitive functioning; however, results are varied. Methods: PD patients with (PDFOG+, n=41) and without FOG (PDFOG-, n=39) and control healthy subjects (n=41) participated in the study. The NIH toolbox cognition battery, Montreal cognitive assessment (MoCA), and interval timing task were used to test cognitive domains. Measurements were compared between groups using multivariable models and adjusting for covariates. Correlation analyses, linear regression, and mediation models were applied to examine relationships among disease duration and severity, FOG severity, and cognitive functioning. Results: Significant differences were observed between controls and PD patients for all cognitive domains. PDFOG+ and PDFOG- exhibited differences in the dimensional change card sort (DCCS) test, interval timing task, and MoCA scores. After adjusting for covariates in two different models, PDFOG+ and PDFOG- differed in both MoCA and DCCS scores. In addition, significant relationships between FOG severity and cognitive function (MoCA, DCCS, and interval timing) were also found. Regression models suggest that FOG severity may be a predictor of cognitive impairment, and mediation models show the effects of cognitive impairment on the relationship between disease severity and FOG severity. Conclusions: Overall, this study provides insight into the relationship between cognitive and gait impairments in patients with PD, which could aid in the development of therapeutic interventions to manage both.

Premovement inhibition protects motor actions from interference

Shortly before movement initiation, the corticospinal system undergoes a transient suppression. This phenomenon has been observed across a range of motor tasks, suggesting that it may be a obligatory component of movement preparation. We probed whether this was also the case when the urgency to perform a motor action was high, in a situation where little time was available to engage in preparatory processes. We controlled the urgency of an impending motor action by increasing or decreasing the foreperiod duration in an anticipatory timing task. Transcranial magnetic stimulation (TMS; experiment one) or a loud acoustic stimulus (LAS; experiment two) were used to examine how corticospinal and subcortical excitability were modulated during motor preparation. Preparatory inhibition of the corticospinal tract was absent when movement urgency was high, though motor actions were initiated on time. In contrast, subcortical circuits were progressively inhibited as the time to prepare increased. Interestingly, movement force and vigour were reduced by both TMS and the LAS when movement urgency was high, and enhanced when movement urgency was low. Our findings indicate that preparatory inhibition may not be a obligatory component of motor preparation. The behavioural effects we observed in the absence of preparatory inhibition were induced by both TMS and the LAS, suggesting that accessory sensory stimulation may disrupt motor output when such stimulation is presented in the absence of preparatory inhibition. We conclude that preparatory inhibition may be an adaptive strategy which can serve to protect the prepared motor action from external interference.

Experience-related remapping of temporal encoding by striatal ensembles

Temporal control of action is key for a broad range of behaviors and is disrupted in human diseases such as Parkinson’s disease and schizophrenia. A brain structure that is critical for temporal control is the dorsal striatum. Experience and learning can influence dorsal striatal neuronal activity, but it is unknown how these neurons change with experience in contexts which require precise temporal control of movement. We investigated this question by recording from medium-spiny neurons (MSNs) in the dorsal striatum of mice as they gained experience controlling their actions in time. We leveraged an interval timing task optimized for mice which required them to “switch” response ports after enough time had passed without receiving a reward. We report three main results. First, we found that time-related ramping activity and response-related activity increased with more experience. Second, temporal decoding by MSN ensembles improved with experience and was predominantly driven by time-related ramping activity. Finally, we found that some MSNs had differential modulation on error trials. These findings enhance our understanding of dorsal striatal temporal processing by demonstrating how MSN ensembles can evolve with experience. Our results can be linked to temporal habituation and illuminate striatal flexibility during interval timing, which may be relevant for human disease.