How noise contributes to time-scale invariance of interval timing

Oprisan, Sorinel A.; Buhusi, Catalin V.

doi:10.1103/physreve.87.052717

Cited by 24 publications

(25 citation statements)

References 88 publications

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“…For example, a description of the neurobiological mechanisms involved in interval timing is currently provided by the Striatal Beat-Frequency (SBF) model, which ascribes a role for detecting event durations to medium spiny neurons within the dorsal striatum (Matell and Meck, 2004 ; Buhusi and Meck, 2005 ), which become entrained to fire in response to oscillating, coincident cortical inputs that become active at previously trained event durations. An interesting feature of this model is that scalar property emerges in the model due to neural noise (Buhusi and Oprisan, 2013 ; Oprisan and Buhusi, 2013a , b , 2014 ). In regard to the current experiment, reversible mPFC inactivation resulted in a decrease in timing precision, which could be interpreted as reflecting an increase in neural noise.…”

Section: Discussionmentioning

confidence: 99%

Inactivation of the Medial-Prefrontal Cortex Impairs Interval Timing Precision, but Not Timing Accuracy or Scalar Timing in a Peak-Interval Procedure in Rats

Buhusi

Reyes

Gathers

et al. 2018

Front. Integr. Neurosci.

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Motor sequence learning, planning and execution of goal-directed behaviors, and decision making rely on accurate time estimation and production of durations in the seconds-to-minutes range. The pathways involved in planning and execution of goal-directed behaviors include cortico-striato-thalamo-cortical circuitry modulated by dopaminergic inputs. A critical feature of interval timing is its scalar property, by which the precision of timing is proportional to the timed duration. We examined the role of medial prefrontal cortex (mPFC) in timing by evaluating the effect of its reversible inactivation on timing accuracy, timing precision and scalar timing. Rats were trained to time two durations in a peak-interval (PI) procedure. Reversible mPFC inactivation using GABA agonist muscimol resulted in decreased timing precision, with no effect on timing accuracy and scalar timing. These results are partly at odds with studies suggesting that ramping prefrontal activity is crucial to timing but closely match simulations with the Striatal Beat Frequency (SBF) model proposing that timing is coded by the coincidental activation of striatal neurons by cortical inputs. Computer simulations indicate that in SBF, gradual inactivation of cortical inputs results in a gradual decrease in timing precision with preservation of timing accuracy and scalar timing. Further studies are needed to differentiate between timing models based on coincidence detection and timing models based on ramping mPFC activity, and clarify whether mPFC is specifically involved in timing, or more generally involved in attention, working memory, or response selection/inhibition.

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Section: Discussionmentioning

confidence: 99%

Inactivation of the Medial-Prefrontal Cortex Impairs Interval Timing Precision, but Not Timing Accuracy or Scalar Timing in a Peak-Interval Procedure in Rats

Buhusi

Reyes

Gathers

et al. 2018

Front. Integr. Neurosci.

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“…The striatal beat frequency (SBF) model of interval timing accounts well for much of the pharmacological, neurophysiological, and psychological data on timing and time perception (e.g., Matell and Meck, 2000 , 2004 ; Coull et al, 2011 ; Oprisan and Buhusi, 2011 , 2013 , 2014 ; van Rijn et al, 2011 ; Allman and Meck, 2012 ; Buhusi and Oprisan, 2013 ; Oprisan et al, 2014 ; Kononowicz, 2015 ; Kononowicz and van Wassenhove, 2016 ). The SBF model proposes that time perception is largely subserved by connections between the striatum, cortex, and thalamus, with the dorsal striatum being specifically crucial for proper timing abilities (Meck, 2006a , b ).…”

Section: Striatal Beat-frequency (Sbf) Model: Neurobiological Basis Fmentioning

confidence: 99%

Cognitive Aging and Time Perception: Roles of Bayesian Optimization and Degeneracy

Turgeon

Lustig

Meck

2016

Front. Aging Neurosci.

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This review outlines the basic psychological and neurobiological processes associated with age-related distortions in timing and time perception in the hundredths of milliseconds-to-minutes range. The difficulty in separating indirect effects of impairments in attention and memory from direct effects on timing mechanisms is addressed. The main premise is that normal aging is commonly associated with increased noise and temporal uncertainty as a result of impairments in attention and memory as well as the possible reduction in the accuracy and precision of a central timing mechanism supported by dopamine-glutamate interactions in cortico-striatal circuits. Pertinent to these findings, potential interventions that may reduce the likelihood of observing age-related declines in timing are discussed. Bayesian optimization models are able to account for the adaptive changes observed in time perception by assuming that older adults are more likely to base their temporal judgments on statistical inferences derived from multiple trials than on a single trial’s clock reading, which is more susceptible to distortion. We propose that the timing functions assigned to the age-sensitive fronto-striatal network can be subserved by other neural networks typically associated with finely-tuned perceptuo-motor adjustments, through degeneracy principles (different structures serving a common function).

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“…A similar strong coherence in gamma band was found between frontal and parietal cortex during successful recollection (Burgess and Ali, 2002 ). Cross-frequency coupling between brain rhythms is essential in organization and consolidation of working memory (Oprisan and Buhusi, 2013 ). Such a cross-frequency coupling between gamma and theta oscillations is believed to code multiple items in an ordered way in hippocampus where spatial information is represented in different gamma subcycles of a theta cycle (Kirihara et al, 2012 ; Lisman and Jensen, 2013 ).…”

Section: Introductionmentioning

confidence: 99%

Low-dimensional attractor for neural activity from local field potentials in optogenetic mice

Oprisan¹,

Lynn²,

Tompa³

et al. 2015

Front. Comput. Neurosci.

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We used optogenetic mice to investigate possible nonlinear responses of the medial prefrontal cortex (mPFC) local network to light stimuli delivered by a 473 nm laser through a fiber optics. Every 2 s, a brief 10 ms light pulse was applied and the local field potentials (LFPs) were recorded with a 10 kHz sampling rate. The experiment was repeated 100 times and we only retained and analyzed data from six animals that showed stable and repeatable response to optical stimulations. The presence of nonlinearity in our data was checked using the null hypothesis that the data were linearly correlated in the temporal domain, but were random otherwise. For each trail, 100 surrogate data sets were generated and both time reversal asymmetry and false nearest neighbor (FNN) were used as discriminating statistics for the null hypothesis. We found that nonlinearity is present in all LFP data. The first 0.5 s of each 2 s LFP recording were dominated by the transient response of the networks. For each trial, we used the last 1.5 s of steady activity to measure the phase resetting induced by the brief 10 ms light stimulus. After correcting the LFPs for the effect of phase resetting, additional preprocessing was carried out using dendrograms to identify “similar” groups among LFP trials. We found that the steady dynamics of mPFC in response to light stimuli could be reconstructed in a three-dimensional phase space with topologically similar “8”-shaped attractors across different animals. Our results also open the possibility of designing a low-dimensional model for optical stimulation of the mPFC local network.

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How noise contributes to time-scale invariance of interval timing

Cited by 24 publications

References 88 publications

Inactivation of the Medial-Prefrontal Cortex Impairs Interval Timing Precision, but Not Timing Accuracy or Scalar Timing in a Peak-Interval Procedure in Rats

Inactivation of the Medial-Prefrontal Cortex Impairs Interval Timing Precision, but Not Timing Accuracy or Scalar Timing in a Peak-Interval Procedure in Rats

Cognitive Aging and Time Perception: Roles of Bayesian Optimization and Degeneracy

Low-dimensional attractor for neural activity from local field potentials in optogenetic mice

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