scholarly journals GAMIT – A Fading-Gaussian Activation Model of Interval-Timing: Unifying Prospective and Retrospective Time Estimation

2014 ◽  
Vol 1 (1) ◽  
pp. 1-17 ◽  
Author(s):  
Robert M. French ◽  
Caspar Addyman ◽  
Denis Mareschal ◽  
Elizabeth Thomas
Keyword(s):  
Time Estimation ◽  
Interval Timing ◽  
Activation Model

Critical Analysis and Alternative Explanations for Effects of Apnea on the Timing of Motor Representations

2015 ◽  
Vol 3 (3-4) ◽  
pp. 307-316
Author(s):  
Neşe Alkan
Keyword(s):  
Clinical Studies ◽  
Critical Analysis ◽  
Water Immersion ◽  
Time Estimation ◽  
Interval Timing ◽  
Motor Representation ◽  
Unexpected Findings ◽  
Motor Representations ◽  
The Relationship

This commentary is designed to provide an analysis of issues pertinent to the investigation of the effects of the temporary cessation of breathing (apnea), particularly during water immersion or diving, and its effects on time estimation in general and the timing of motor representation in particular. In addition, this analysis provides alternative explanations of certain unexpected findings reported by Di Rienzo et al. (2014) pertaining to apnea and interval timing. The perspective and guidance that this commentary provides on the relationship between apnea and time estimation is especially relevant considering the scarcity of experimental and clinical studies examining these variables.

scholarly journals What is all the noise about in interval timing?

2014 ◽  
Vol 369 (1637) ◽  
pp. 20120459 ◽  
Author(s):  
Sorinel A. Oprisan ◽  
Catalin V. Buhusi
Keyword(s):  
Time Scale ◽  
Scale Invariance ◽  
Fundamental Property ◽  
Time Estimation ◽  
Interval Timing ◽  
Accurate Estimation ◽  
Scale Invariant ◽  
Estimation Errors ◽  
Neural Noise ◽  
Criterion Time

Cognitive processes such as decision-making, rate calculation and planning require an accurate estimation of durations in the supra-second range—interval timing. In addition to being accurate, interval timing is scale invariant: the time-estimation errors are proportional to the estimated duration. The origin and mechanisms of this fundamental property are unknown. We discuss the computational properties of a circuit consisting of a large number of (input) neural oscillators projecting on a small number of (output) coincidence detector neurons, which allows time to be coded by the pattern of coincidental activation of its inputs. We showed analytically and checked numerically that time-scale invariance emerges from the neural noise. In particular, we found that errors or noise during storing or retrieving information regarding the memorized criterion time produce symmetric, Gaussian-like output whose width increases linearly with the criterion time. In contrast, frequency variability produces an asymmetric, long-tailed Gaussian-like output, that also obeys scale invariant property. In this architecture, time-scale invariance depends neither on the details of the input population, nor on the distribution probability of noise.

scholarly journals Minutes, days and years: molecular interactions among different scales of biological timing

2014 ◽  
Vol 369 (1637) ◽  
pp. 20120465 ◽  
Author(s):  
Diego A. Golombek ◽  
Ivana L. Bussi ◽  
Patricia V. Agostino
Keyword(s):  
Biological Clock ◽  
Time Estimation ◽  
Interval Timing ◽  
Circadian System ◽  
Biological Clocks ◽  
Seasonal Rhythms ◽  
Everyday Activities ◽  
Multi Level ◽  
Timing Behaviour ◽  
Timing Structure

Biological clocks are genetically encoded oscillators that allow organisms to keep track of their environment. Among them, the circadian system is a highly conserved timing structure that regulates several physiological, metabolic and behavioural functions with periods close to 24 h. Time is also crucial for everyday activities that involve conscious time estimation. Timing behaviour in the second-to-minutes range, known as interval timing, involves the interaction of cortico-striatal circuits. In this review, we summarize current findings on the neurobiological basis of the circadian system, both at the genetic and behavioural level, and also focus on its interactions with interval timing and seasonal rhythms, in order to construct a multi-level biological clock.

scholarly journals 001 Altered interval timing as a novel marker of cognitive fluctuations in lewy body dementia

2019 ◽  
Vol 90 (e7) ◽  
pp. A1.1-A1 ◽  
Author(s):  
Elie Matar ◽  
Kaylena Ehgoetz Martens ◽  
Joseph Phillips ◽  
Glenda Halliday ◽  
Simon Lewis
Keyword(s):  
Cognitive Abilities ◽  
Lewy Body Dementia ◽  
Time Estimation ◽  
Interval Timing ◽  
Interval Length ◽  
Clinical Feature ◽  
Good Test ◽  
Time Production ◽  
Objective Evidence ◽  
Cognitive Fluctuations

IntroductionCognitive fluctuations are a core clinical feature of Dementia with Lewy Bodies(DLB), characterized by marked spontaneous variations in cognitive abilities and alertness. There is a paucity of objective measurements of fluctuations in the clinical setting. Altered time awareness represents a potential clinical marker of fluctuations and/or their severity. In this study we aimed to investigate qualities of interval timing in patients with DLB.Methods25 patients with probable DLB and 14 older controls underwent testing using a simple time perception paradigm testing probing different aspects of interval timing including time estimation(retrospective estimation of interval length),time production(prospective determination of an interval) and time pacing(explicit timing of an interval).Intervals of 10 to 90s were randomized between trials.Self/carer-reporting of fluctuations were measured using the clinician assessment of fluctuation(CAF) and one-day fluctuation(OFS) scales.ResultsWe found significant differences in interval timing between controls and DLB for time estimation and time production. Overall, DLB patients estimated less time which was significant at 90 seconds(proportion of interval=0.92 vs 0.69; p=0.03). DLB produced less time(proportion of 90s interval 0.58 vs 1.0; p<0.001). Errors in time estimation at 90 seconds correlated with fluctuation presence according to the CAF(r­=0.47;p=0.009) whilst errors in time pacing at 90s correlated strongest with fluctuation severity according to the OFS(r=0.65,p<0.001). ROC analysis identified time production(90s) as a good test to distinguish DLB from controls (AUC=0.8;95%CI:0.75–0.98).ConclusionWe demonstrate objective evidence for altered temporal processing in DLB and suggest abnormal interval timing as a novel and clinically useful bedside marker of cognitive fluctuations.

scholarly journals Unifying Prospective and Retrospective Interval-time Estimation: A Fading-gaussian Activation-based Model of Interval-timing

2014 ◽  
Vol 126 ◽  
pp. 141-150 ◽  
Author(s):  
Robert M. French ◽  
Caspar Addyman ◽  
Denis Mareschal ◽  
Elizabeth Thomas
Keyword(s):  
Time Estimation ◽  
Interval Timing ◽  
Interval Time

scholarly journals Timing variability and midfrontal ~4 Hz rhythms correlate with cognition in Parkinson’s disease

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Arun Singh ◽  
Rachel C. Cole ◽  
Arturo I. Espinoza ◽  
Aron Evans ◽  
Scarlett Cao ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Dysfunction ◽  
Cognitive Impairments ◽  
Time Estimation ◽  
Interval Timing ◽  
Oscillatory Activity ◽  
Mixed Effects Modeling ◽  
Timing Variability ◽  
Temporal Intervals

AbstractPatients with Parkinson’s disease (PD) can have significant cognitive dysfunction; however, the mechanisms for these cognitive symptoms are unknown. Here, we used scalp electroencephalography (EEG) to investigate the cortical basis for PD-related cognitive impairments during interval timing, which requires participants to estimate temporal intervals of several seconds. Time estimation is an ideal task demand for investigating cognition in PD because it is simple, requires medial frontal cortical areas, and recruits basic executive processes such as working memory and attention. However, interval timing has never been systematically studied in PD patients with cognitive impairments. We report three main findings. First, 71 PD patients had increased temporal variability compared to 37 demographically matched controls, and this variability correlated with cognitive dysfunction as measured by the Montreal Cognitive Assessment (MOCA). Second, PD patients had attenuated ~4 Hz EEG oscillatory activity at midfrontal electrodes in response to the interval-onset cue, which was also predictive of MOCA. Finally, trial-by-trial linear mixed-effects modeling demonstrated that cue-triggered ~4 Hz power predicted subsequent temporal estimates as a function of PD and MOCA. Our data suggest that impaired cue-evoked midfrontal ~4 Hz activity predicts increased timing variability that is indicative of cognitive dysfunction in PD. These findings link PD-related cognitive dysfunction with cortical mechanisms of cognitive control, which could advance novel biomarkers and neuromodulation for PD.

scholarly journals Timing variability and midfrontal ~4 Hz rhythms correlate with cognition in Parkinson’s disease

2020 ◽  
Author(s):  
Arun Singh ◽  
Rachel C. Cole ◽  
Arturo I. Espinoza ◽  
Aron Evans ◽  
Scarlett Cao ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Dysfunction ◽  
Cognitive Impairments ◽  
Time Estimation ◽  
Interval Timing ◽  
Oscillatory Activity ◽  
Mixed Effects Modeling ◽  
Timing Variability ◽  
Temporal Intervals

ABSTRACTPatients with Parkinson’s disease (PD) can have significant cognitive dysfunction; however, the mechanisms for these cognitive symptoms are unknown. Here, we used scalp electroencephalography (EEG) to investigate the cortical basis for PD-related cognitive impairments during interval timing, which requires participants to estimate temporal intervals of several seconds. Time estimation is an ideal task demand for investigating cognition in PD because it is simple, requires medial frontal cortical areas, and recruits basic executive processes such as working memory and attention.However, interval timing has never been systematically studied in PD patients with cognitive impairments. We report three main findings. First, 71 PD patients had increased temporal variability compared to 37 demographically-matched controls, and this variability correlated with cognitive dysfunction as measured by the Montreal Cognitive Assessment (MOCA). Second, PD patients had attenuated ~4 Hz EEG oscillatory activity at midfrontal electrodes in response to the interval-onset cue, which was also predictive of MOCA. Finally, trial-by-trial linear mixed-effects modeling demonstrated that cue-triggered ~4 Hz power predicted subsequent temporal estimates as a function of PD and MOCA. Our data suggest that impaired cue-evoked midfrontal ~4 Hz activity predicts increased timing variability that is indicative of cognitive dysfunction in PD. These findings link PD-related cognitive dysfunction with cortical mechanisms of cognitive control, which could advance novel biomarkers and neuromodulation for PD.

Temporal Prediction Errors Affect Short-Term Memory Scanning Response Time

2016 ◽  
Vol 63 (6) ◽  
pp. 333-342
Author(s):  
Roberto Limongi ◽  
Angélica M. Silva
Keyword(s):  
Response Time ◽  
Short Term Memory ◽  
Estimation Error ◽  
Predictive Coding ◽  
Time Estimation ◽  
Prediction Errors ◽  
Memory Scanning ◽  
Short Term ◽  
Term Memory ◽  
Temporal Prediction

Abstract. The Sternberg short-term memory scanning task has been used to unveil cognitive operations involved in time perception. Participants produce time intervals during the task, and the researcher explores how task performance affects interval production – where time estimation error is the dependent variable of interest. The perspective of predictive behavior regards time estimation error as a temporal prediction error (PE), an independent variable that controls cognition, behavior, and learning. Based on this perspective, we investigated whether temporal PEs affect short-term memory scanning. Participants performed temporal predictions while they maintained information in memory. Model inference revealed that PEs affected memory scanning response time independently of the memory-set size effect. We discuss the results within the context of formal and mechanistic models of short-term memory scanning and predictive coding, a Bayes-based theory of brain function. We state the hypothesis that our finding could be associated with weak frontostriatal connections and weak striatal activity.

Sign in / Sign up

Export Citation Format

Share Document