Modeling pharmacological clock and memory patterns of interval timing in a striatal beat-frequency model with realistic, noisy neurons

Cholinergic interneurons in the dorsal striatum play an important role in the acquisition of duration memory

The present study aimed to examine the effect of cholinergic interneuron lesions in the dorsal striatum on duration-memory formation. Cholinergic interneurons in the dorsal striatum may be involved in the formation of duration memory since they are among the main inputs to the dorsal striatal muscarinic acetylcholine-1 receptors, which play a role in the consolidation of duration memory. Rats were sufficiently trained using a peak-interval 20 s procedure and then infused with anti-choline acetyltransferase-saporin into the dorsal striatum to cause selective ablation of cholinergic interneurons. To make the rats acquire new duration-memories, we trained them with a peak interval 40 s after lesion. Before lesion, the peak times (an index of duration memory) for sham-lesioned and lesioned groups were similar at approximately 20 s. In the peak interval 40 s session, the peak times for the sham-lesioned and lesioned groups were approximately 30 and 20 s, respectively. After additional peak interval 40 s sessions, the peak times of both groups were shifted to approximately 40 s. Those results suggest that the cholinergic interneuron lesion delayed new duration-memory acquisition. Subsequent experiments showed that cholinergic interneuron lesions did not retard the shift of peak time to the original target time (20 s). Following experiment without changing the target time after lesion showed that cholinergic interneuron lesions did not change their peak times. Our findings suggest that cholinergic interneurons in the dorsal striatum are involved in new duration-memory acquisition but not in the utilization of already acquired duration memory and interval timing.

Cognitive and plastic recurrent neural network clock model for the judgment of time and its variations

The aim of this study in the field of computational neurosciences was to simulate and predict inter-individual variability in time judgements with different neuropsychological properties. We propose and test a Simple Recurrent Neural Network-based clock model that is able to account for inter-individual variability in time judgment by adding four new components into the clock system: the first relates to the plasticity of the neural system, the second to the attention allocated to time, the third to the memory of duration, and the fourth to the learning of duration by iteration. A simulation with this model explored its fit with participants' time estimates in a temporal reproduction task undertaken by both children and adults, whose varied cognitive abilities were assessed with neuropsychological tests. The simulation successfully predicted 90% of temporal errors. Our Cognitive and Plastic RNN-Clock model (CP-RNN-Clock), that takes into account the interference arising from a clock system grounded in cognition, was thus validated.

Anaesthetics and time perception: A review

Consciousness requires subjective experience in the "now." Establishing "now," however, necessitates temporal processing. In the current article, we review one method of altering consciousness, anaesthetic drug administration, and its effects on perceived duration. We searched PubMed, PsycInfo, and ScienceDirect databases, and article reference sections, for combinations of anaesthetic drugs and time perception tasks, finding a total of 36 articles which met our inclusion criteria. We categorised these articles with regard to whether they altered the felt passage of time, short or long interval timing, or were motor timing tasks. We found that various drugs alter the perceived passage of time; ketamine makes time subjectively slow down while GABAergic drugs make time subjectively speed up. At a short interval there is little established evidence of a shift in time perception, though temporal estimates appear more variable. Similarly, when asked to use time to optimise responses (i.e., in motor timing tasks), various anaesthetic agents make timing more variable. Longer durations are estimated as lasting longer than their objective duration, though there is some variation across articles in this regard. We conclude by proposing further experiments to examine time perception under altered states of consciousness and ask whether it is possible to perceive the passage of time of events which do not necessarily reach the level of conscious perception. The variety of methods used raises the need for more systematic investigations of time perception under anaesthesia. We encourage future investigations into the overlap of consciousness and time perception to advance both fields.

mPFC catecholamines modulate attentional capture by appetitive distracters and attention to time in a peak-interval procedure in rats

The behavioral and neural mechanisms by which distracters delay interval timing behavior are currently unclear. Distracters delay timing in a considerable dynamic range: Some distracters have no effect on timing ("run"), whereas others seem to "stop" timing; some distracters restart ("reset") the entire timing mechanisms at their offset, whereas others seem to capture attentional resources long after their termination ("over-reset"). While the run-reset range of delays is accounted for by the Time-Sharing Hypothesis (Buhusi, 2003, 2012), the behavioral and neural mechanisms of "over-resetting" are currently uncertain. We investigated the role of novelty (novel/familiar) and significance (consequential/inconsequential) in the time-delaying effect of distracters and the role of medial prefrontal cortex (mPFC) catecholamines by local infusion of norepinephrine-dopamine reuptake inhibitor (NDRI) nomifensine in a peak-interval (PI) procedure in rats. Results indicate differences in time delay between groups, suggesting a role for both novelty and significance: inconsequential, familiar distracters "stopped" timing, novel distracters "reset" timing, whereas appetitively conditioned distracters "over-reset" timing. mPFC infusion of nomifensine modulated attentional capture by appetitive distracters in a "U"-shaped fashion, reduced the delay after novel distracters, but had no effects after inconsequential, familiar distracters. These results were not due to nomifensine affecting either timing accuracy, precision, or peak response rate. Results may help elucidate the behavioral and physiological mechanisms underlying interval timing and attention to time and may contribute to developing new treatment strategies for disorders of attention. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Beyond Scalar Timing Theory: Integrating Neural Oscillators with Computational Accessibility in Memory

One of the major challenges for computational models of timing and time perception is to identify a neurobiological plausible implementation that predicts various behavioral properties, including the scalar property and retrospective timing. The available timing models primarily focus on the scalar property and prospective timing, while virtually ignoring the computational accessibility. Here, we first selectively review timing models based on ramping activity, oscillatory pattern, and time cells, and discuss potential challenges for the existing models. We then propose a multifrequency oscillatory model that offers computational accessibility, which could account for a much broader range of timing features, including both retrospective and prospective timing.

Resource Allocation in the Noise-Free Striatal Beat Frequency Model of Interval Timing

The Striatal Beat Frequency (SBF) model of interval timing uses many neural oscillators, presumably located in the frontal cortex (FC), to produce beats at a specific criterion time Tc. The coincidence detection produces the beats in the basal ganglia spiny neurons by comparing the current state of the FC neural oscillators against the long-term memory values stored at reinforcement time Tc. The neurobiologically realistic SBF model has been previously used for producing precise and scalar timing in the presence of noise. Here we simplified the SBF model to gain insight into the resource allocation problem in interval timing networks. Specifically, we used a noise-free SBF model to explore the lower limits of the number of neural oscillators required for producing accurate timing. Using abstract sine-wave neural oscillators in the SBF-sin model, we found that the lower limit of the number of oscillators needed is proportional to the criterion time Tc and the frequency span (fmax − fmin) of the FC neural oscillators. Using biophysically realistic Morris–Lecar model neurons in the SBF-ML model, the lower bound increased by one to two orders of magnitude compared to the SBF-sin model.

Oscillation/Coincidence-Detection Models of Reward-Related Timing in Corticostriatal Circuits

The major tenets of beat-frequency/coincidence-detection models of reward-related timing are reviewed in light of recent behavioral and neurobiological findings. This includes the emphasis on a core timing network embedded in the motor system that is comprised of a corticothalamic-basal ganglia circuit. Therein, a central hub provides timing pulses (i.e., predictive signals) to the entire brain, including a set of distributed satellite regions in the cerebellum, cortex, amygdala, and hippocampus that are selectively engaged in timing in a manner that is more dependent upon the specific sensory, behavioral, and contextual requirements of the task. Oscillation/coincidence-detection models also emphasize the importance of a tuned ‘perception’ learning and memory system whereby target durations are detected by striatal networks of medium spiny neurons (MSNs) through the coincidental activation of different neural populations, typically utilizing patterns of oscillatory input from the cortex and thalamus or derivations thereof (e.g., population coding) as a time base. The measure of success of beat-frequency/coincidence-detection accounts, such as the Striatal Beat-Frequency model of reward-related timing (SBF), is their ability to accommodate new experimental findings while maintaining their original framework, thereby making testable experimental predictions concerning diagnosis and treatment of issues related to a variety of dopamine-dependent basal ganglia disorders, including Huntington’s and Parkinson’s disease.

Speed and Consolidation: Warren Meck’s Early Ideas about Temporal Reference Memory and some Later Developments

This article is initially focussed on Warren Meck’s early work on temporal reference memory, in particular the idea that some drug manipulations affect ‘memory storage speed’. Meck’s original notion had links to an earlier literature, not usually related to timing, the study of memory consolidation. We present some examples of the use of the idea of memory storage speed from Meck’s early work, and show how it was abandoned in favour of a ‘memory constant’, K*, not related to storage speed per se. Some arguments against the idea of memory storage speed are presented, as well as discussion of a small amount of research on consolidation of memories for time. Later work on temporal reference memory, including rapid acquisition and interference effects, is also discussed.

Time is body: Multimodal evidence of crosstalk between interoception and time estimation

Theoretical approaches propose a blending between interoception and time estimation. Interoception might constitute a neurophysiological mechanism for encoding duration. However, no study has assessed the convergence between interoception and time estimation using behavioral, neurophysiological, and functional anatomy signatures. We examined the multimodal convergence between interoception and time estimation using a two-fold approach. In study 1, we developed a dual design combining interoception (measuring heartbeat detection - HBD, and heartbeat evoked potential - HEP) with a time estimation paradigm (TEP, estimation of duration of a 120 s interval). In study 2, we performed a conjoint metanalysis (Multi-level Kernel Density Analysis, MKDA) of neuroimaging, including reports of interoception and time estimation. Both studies provide convergent evidence of time estimation's significant involvement in behavioral, electrophysiological (enhanced HEP), and neuroimaging (overlapping cluster in the right insula and operculum) signatures of interoception. Convergent results from both studies offer direct support for a shared mechanism of interoception and time estimation.

Is the scalar property of interval timing preserved after hippocampus lesions?

Time perception is fundamental for decision-making, adaptation, and survival. In the peak-interval (PI) paradigm, one of the critical features of time perception is its scale invariance, i.e., the error in time estimation increases linearly with the to-be-timed interval. Brain lesions can profoundly alter time perception, but do they also change its scalar property? In particular, hippocampus (HPC) lesions affect the memory of the reinforced durations. Experiments found that ventral hippocampus (vHPC) lesions shift the perceived durations to longer values while dorsal hippocampus (dHPC) lesions produce opposite effects. Here we used our implementation of the Striatal Beat Frequency (SBFML) model with biophysically realistic Morris-Lecar (ML) model neurons and a topological map of HPC memory to predict analytically and verify numerically the effect of HPC lesions on scalar property. We found that scalar property still holds after both vHPC and dHPC lesions in our SBFML-HPC network simulation. Our numerical results show that PI durations are shifted in the correct direction and match the experimental results. In our simulations, the relative peak shift of the behavioral response curve is controlled by two factors: (1) the lesion size, and (2) the cellular-level memory variance of the temporal durations stored in the HPC. The coefficient of variance (CV) of the behavioral response curve remained constant over the tested durations of PI procedure, which suggests that scalar property is not affected by HPC lesions.

Striatal dopamine D1 receptors control motivation to respond, but not interval timing, during the timing task

Dopamine plays a critical role in behavioral tasks requiring interval timing (time perception in a seconds-to-minutes range). Although some studies demonstrate the role of dopamine receptors as a controller of the speed of the internal clock, other studies demonstrate their role as a controller of motivation. Both D1 dopamine receptors (D1DRs) and D2 dopamine receptors (D2DRs) within the dorsal striatum may play a role in interval timing because the dorsal striatum contains rich D1DRs and D2DRs. However, relative to D2DRs, the precise role of D1DRs within the dorsal striatum in interval timing is unclear. To address this issue, rats were trained on the peak-interval 20-sec procedure, and D1DR antagonist SCH23390 was infused into the bilateral dorsocentral striatum before behavioral sessions. Our results showed that the D1DR blockade drastically reduced the maximum response rate and increased the time to start responses with no effects on the time to terminate responses. These findings suggest that the D1DRs within the dorsal striatum are required for motivation to respond, but not for modulation of the internal clock speed.

Blockade of Catecholamine Reuptake in the Prelimbic Cortex Decreases Top-down Attentional Control in Response to Novel, but Not Familiar Appetitive Distracters, within a Timing Paradigm

Emotionally charged distracters delay timing behavior. Increasing catecholamine levels within the prelimbic cortex has beneficial effects on timing by decreasing the delay after aversive distracters. We examined whether increasing catecholamine levels within the prelimbic cortex also protects against the deleterious timing delays caused by novel distracters or by familiar appetitive distracters. Rats were trained in a peak-interval procedure and tested in trials with either a novel (unreinforced) distracter, a familiar appetitive (food-reinforced) distracter, or no distracter after being locally infused within the prelimbic cortex with catecholamine reuptake blocker nomifensine. Prelimbic infusion of nomifensine did not alter timing accuracy and precision. However, it increased the delay caused by novel distracters in an inverted-U dose-dependent manner, while being ineffective for appetitive distracters. Together with previous data, these results suggest that catecholaminergic modulation of prelimbic top-down attentional control of interval timing varies with distracter’s valence: prelimbic catecholamines increase attentional control when presented with familiar aversive distracters, have no effect on familiar neutral or familiar appetitive distracters, and decrease it when presented with novel distracters. These findings detail complex interactions between catecholaminergic modulation of attention to timing and nontemporal properties of stimuli, which should be considered when developing therapeutic methods for attentional or affective disorders.

Logarithmic encoding of ensemble time intervals

Although time perception is based on the internal representation of time, whether the subjective timeline is scaled linearly or logarithmically remains an open issue. Evidence from previous research is mixed: while the classical internal-clock model assumes a linear scale with scalar variability, there is evidence that logarithmic timing provides a better fit to behavioral data. A major challenge for investigating the nature of the internal scale is that the retrieval process required for time judgments may involve a remapping of the subjective time back to the objective scale, complicating any direct interpretation of behavioral findings. Here, we used a novel approach, requiring rapid intuitive ‘ensemble’ averaging of a whole set of time intervals, to probe the subjective timeline. Specifically, observers’ task was to average a series of successively presented, auditory or visual, intervals in the time range 300–1300 ms. Importantly, the intervals were taken from three sets of durations, which were distributed such that the arithmetic mean (from the linear scale) and the geometric mean (from the logarithmic scale) were clearly distinguishable. Consistently across the three sets and the two presentation modalities, our results revealed subjective averaging to be close to the geometric mean, indicative of a logarithmic timeline underlying time perception.

Interval timing deficits and their neurobiological correlates in aging mice

Age-related neurobiological and cognitive alterations suggest that interval timing (as a related function) is also altered in aging, which can, in turn, disrupt timing-dependent functions. We investigated alterations in interval timing with aging and accompanying neurobiological changes. We tested 4-6, 10-12, and 18-20 month-old mice on the dual peak interval procedure. Results revealed a specific deficit in the termination of timed responses (stop-times). The decision processes contributed more to timing variability (vs. clock/memory process) in the aged mice. We observed age-dependent reductions in the number of dopaminergic neurons in the VTA and SNc, cholinergic neurons in the medial septum/diagonal band (MS/DB) complex, and density of dopaminergic axon terminals in the DLS/DMS. Negative correlations were found between the number of dopaminergic neurons in the VTA and stop times, and the number of cholinergic neurons in MS/DB complex and the acquisition of stop times. Our results point at age-dependent changes in the decisional components of interval timing and the role of dopaminergic and cholinergic functions in these behavioral alterations.

Internal Clocks, mGluR7 and Microtubules: A Primer for the Molecular Encoding of Target Durations in Cerebellar Purkinje Cells and Striatal Medium Spiny Neurons

The majority of studies in the field of timing and time perception have generally focused on sub- and supra-second time scales, specific behavioral processes, and/or discrete neuronal circuits. In an attempt to find common elements of interval timing from a broader perspective, we review the literature and highlight the need for cell and molecular studies that can delineate the neural mechanisms underlying temporal processing. Moreover, given the recent attention to the function of microtubule proteins and their potential contributions to learning and memory consolidation/re-consolidation, we propose that these proteins play key roles in coding temporal information in cerebellar Purkinje cells (PCs) and striatal medium spiny neurons (MSNs). The presence of microtubules at relevant neuronal sites, as well as their adaptability, dynamic structure, and longevity, makes them a suitable candidate for neural plasticity at both intra- and inter-cellular levels. As a consequence, microtubules appear capable of maintaining a temporal code or engram and thereby regulate the firing patterns of PCs and MSNs known to be involved in interval timing. This proposed mechanism would control the storage of temporal information triggered by postsynaptic activation of mGluR7. This, in turn, leads to alterations in microtubule dynamics through a "read-write" memory process involving alterations in microtubule dynamics and their hexagonal lattice structures involved in the molecular basis of temporal memory.

Modeling Interval Timing by Recurrent Neural Nets

The purpose of this study was to take a new approach in showing how the central nervous system might encode time at the supra-second level using recurrent neural nets (RNNs). This approach utilizes units with a delayed feedback, whose feedback weight determines the temporal properties of specific neurons in the network architecture. When these feedback neurons are coupled, they form a multilayered dynamical system that can be used to model temporal responses to steps of input in multidimensional systems. The timing network was implemented using separate recurrent “Go” and “No-Go” neural processing units to process an individual stimulus indicating the time of reward availability. Outputs from these distinct units on each time step are converted to a pulse reflecting a weighted sum of the separate Go and No-Go signals. This output pulse then drives an integrator unit, whose feedback weight and input weights shape the pulse distribution. This system was used to model empirical data from rodents performing in an instrumental “peak interval timing” task for two stimuli, Tone and Flash. For each of these stimuli, reward availability was signaled after different times from stimulus onset during training. Rodent performance was assessed on non-rewarded trials, following training, with each stimulus tested individually and simultaneously in a stimulus compound. The associated weights in the Go/No-Go network were trained using experimental data showing the mean distribution of bar press rates across an 80 s period in which a tone stimulus signaled reward after 5 s and a flash stimulus after 30 s from stimulus onset. Different Go/No-Go systems were used for each stimulus, but the weighted output of each fed into a final recurrent integrator unit, whose weights were unmodifiable. The recurrent neural net (RNN) model was implemented using Matlab and Matlab’s machine learning tools were utilized to train the network using the data from non-rewarded trials. The neural net output accurately fit the temporal distribution of tone and flash-initiated bar press data. Furthermore, a “Temporal Averaging” effect was also obtained when the flash and tone stimuli were combined. These results indicated that the system combining tone and flash responses were not superposed as in a linear system, but that there was a non-linearity, which interacted between tone and flash. In order to achieve an accurate fit to the empirical averaging data it was necessary to implement non-linear “saliency functions” that limited the output signal of each stimulus to the final integrator when the other was co-present. The model suggests that the central nervous system encodes timing generation as a dynamical system whose timing properties are embedded in the connection weights of the system. In this way, event timing is coded similar to the way other sensory-motor systems, such as the vestibulo-ocular and optokinetic systems, which combine sensory inputs from the vestibular and visual systems to generate the temporal aspects of compensatory eye movements.

A model for the peak-interval task based on neural oscillation-delimited states

Specific mechanisms underlying how the brain keeps track of time are largely unknown. Several existing computational models of timing reproduce behavioral results obtained with experimental psychophysical tasks, but only a few tackle the underlying biological mechanisms, such as the synchronized neural activity that occurs throughout brain areas. In this paper, we introduce a model for the peak-interval task based on neuronal network properties. We consider that Local Field Potential (LFP) oscillation cycles specify a sequence of states, represented as neuronal ensembles. Repeated presentation of time intervals during training reinforces the connections of specific ensembles to downstream networks - sets of neurons connected to the sequence of states. Later, during the peak-interval procedure, these downstream networks are reactivated by previously experienced neuronal ensembles, triggering behavioral responses at the learned time intervals. The model reproduces experimental response patterns from individual rats in the peak-interval procedure, satisfying relevant properties such as the Weber law. Finally, we provide a biological interpretation of the parameters of the model.

Neural Correlates of Interval Timing Deficits in Schizophrenia

Previous research has shown that schizophrenia (SZ) patients exhibit impairments in interval timing. The cause of timing impairments in SZ remains unknown but may be explained by a dysfunction in the fronto-striatal circuits. Although the current literature includes extensive behavioral data on timing impairments, there is limited focus on the neural correlates of timing in SZ. The neuroimaging literature included in the current review reports hypoactivation in the dorsal-lateral prefrontal cortex (DLPFC), supplementary motor area (SMA) and the basal ganglia (BG). Timing deficits and deficits in attention and working memory (WM) in SZ are likely due to a dysfunction of dopamine (DA) and gamma-aminobutyric acid (GABA) neurotransmission in the cortico-striatal-thalamo-cortical circuits, which are highly implicated in executive functioning and motor preparation.

A Population-Based Model of the Temporal Memory in the Hippocampus

Spatial and temporal dimensions are fundamental for orientation, adaptation, and survival of organisms. Hippocampus has been identified as the main neuroanatomical structure involved both in space and time perception and their internal representation. Dorsal hippocampus lesions showed a leftward shift (toward shorter durations) in peak-interval procedures, whereas ventral lesions shifted the peak time toward longer durations. We previously explained hippocampus lesion experimental findings by assuming a topological map model of the hippocampus with shorter durations memorized ventrally and longer durations more dorsal. Here we suggested a possible connection between the abstract topological maps model of the hippocampus that stored reinforcement times in a spatially ordered memory register and the "time cells" of the hippocampus. In this new model, the time cells provide a uniformly distributed time basis that covers the entire to-be-learned temporal duration. We hypothesized that the topological map of the hippocampus stores the weights that reflect the contribution of each time cell to the average temporal field that determines the behavioral response. The temporal distance between the to-be-learned criterion time and the time of the peak activity of each time cell provides the error signal that determines the corresponding weight correction. Long-term potentiation/depression could enhance/weaken the weights associated to the time cells that peak closer/farther to the criterion time. A coincidence detector mechanism, possibly under the control of the dopaminergic system, could be involved in our suggested error minimization and learning algorithm.

Interval timing under a behavioral microscope: Dissociating motivational and timing processes in fixed-interval performance

The distribution of latencies and interresponse times (IRTs) of rats was compared between two fixed-interval (FI) schedules of food reinforcement (FI 30 s and FI 90 s), and between two levels of food deprivation. Computational modeling revealed that latencies and IRTs were well described by mixture probability distributions embodying two-state Markov chains. Analysis of these models revealed that only a subset of latencies is sensitive to the periodicity of reinforcement, and prefeeding only reduces the size of this subset. The distribution of IRTs suggests that behavior in FI schedules is organized in bouts that lengthen and ramp up in frequency with proximity to reinforcement. Prefeeding slowed down the lengthening of bouts and increased the time between bouts. When concatenated, latency and IRT models adequately reproduced sigmoidal FI response functions. These findings suggest that behavior in FI schedules fluctuates in and out of schedule control; an account of such fluctuation suggests that timing and motivation are dissociable components of FI performance. These mixture-distribution models also provide novel insights on the motivational, associative, and timing processes expressed in FI performance. These processes may be obscured, however, when performance in timing tasks is analyzed in terms of mean response rates.

Scalar timing in memory: A temporal map in the hippocampus

Many essential tasks, such as decision making, rate calculation and planning, require accurate timing in the second to minute range. This process, known as interval timing, involves many cortical areas such as the prefrontal cortex, the striatum, and the hippocampus. Although the neurobiological origin and the mechanisms of interval timing are largely unknown, we have developed increasingly accurate mathematical and computational models that can mimic some properties of time perception. The accepted paradigm of temporal durations storage is that the objective elapsed time from the short-term memory is transferred to the reference memory using a multiplicative "memory translation constant" K*. It is believed that K* has a Gaussian distribution due to trial-related variabilities. To understand K* genesis, we hypothesized that the storage of temporal memories follows a topological map in the hippocampus, with longer durations stored towards dorsal hippocampus and shorter durations stored toward ventral hippocampus. We found that selective removal of memory cells in this topological map model shifts the peak-response time in a manner consistent with the current experimental data on the effect of hippocampal lesions on time perception. This opens new avenues for experimental testing of our topological map hypothesis. We found numerically that the relative shift is determined both by the lesion size and its location and we suggested a theoretical estimate for the memory translation constant K*.

Functional coding variation in the presynaptic dopamine transporter associated with neuropsychiatric disorders drives enhanced motivation and context-dependent impulsivity in mice

Recent genetic analyses have provided evidence that clinical commonalities associated with different psychiatric diagnoses often have shared mechanistic underpinnings. The development of animal models expressing functional genetic variation attributed to multiple disorders offers a salient opportunity to capture molecular, circuit and behavioral alterations underlying this hypothesis. In keeping with studies suggesting dopaminergic contributions to attention-deficit hyperactivity disorder (ADHD), bipolar disorder (BPD) and autism spectrum disorder (ASD), subjects with these diagnoses have been found to express a rare, functional coding substitution in the dopamine (DA) transporter (DAT), Ala559Val. We developed DAT Val559 knock-in mice as a construct valid model of dopaminergic alterations that drive multiple clinical phenotypes, and here evaluate the impact of lifelong expression of the variant on impulsivity and motivation utilizing the 5- choice serial reaction time task (5-CSRTT) and Go/NoGo as well as tests of time estimation (peak interval analysis), reward salience (sucrose preference), and motivation (progressive ratio test). Our findings indicate that the DAT Val559 variant induces impulsivity behaviors that are dependent upon the reward context, with increased impulsive action observed when mice are required to delay responding for a reward, whereas mice are able to withhold responding if there is a probability of reward for a correct rejection. Utilizing peak interval and progressive ratio tests, we provide evidence that impulsivity is likely driven by an enhanced motivational phenotype that also may drive faster task acquisition in operant tasks. These data provide critical validation that DAT, and more generally, DA signaling perturbations can drive impulsivity that can manifest in specific contexts and not others, and may rely on motivational alterations, which may also drive increased maladaptive reward seeking.

Theoretical implications of quantitative properties of interval timing and probability estimation in mouse and rat

In three experiments with mice ( Mus musculus ) and rats (Rattus norvigicus), we used a switch paradigm to measure quantitative properties of the interval-timing mechanism. We found that: 1) Rodents adjusted the precision of their timed switches in response to changes in the interval between the short and long feed latencies (the temporal goalposts). 2) The variability in the timing of the switch response was reduced or unchanged in the face of large trial-to-trial random variability in the short and long feed latencies. 3) The adjustment in the distribution of switch latencies in response to changes in the relative frequency of short and long trials was sensitive to the asymmetry in the Kullback-Leibler divergence. The three results suggest that durations are represented with adjustable precision, that they are timed by multiple timers, and that there is a trial-by-trial (episodic) record of feed latencies in memory.

The brain and the subjective experience of time. A voxel based symptom-lesion mapping study

The aim of the study was to identify the anatomical bases involved in the subjective experience of time, by means of a voxel based symptom-lesion mapping (VLSM) study on patients with focal brain damage. Thirty-three patients (nineteen with right-hemisphere lesions -RBD, and fourteen with left lesion- LBD) and twenty-eight non-neurological controls (NNC) underwent the semi-structured QUEstionnaire for the Subjective experience of Time (QUEST) requiring retrospective and prospective judgements on self-relevant time intervals. All participants also completed tests to assess general cognitive functioning and two questionnaires to evaluate their emotional state. Both groups of brain-damaged patients achieved significantly different scores from NNC on the time performance, without differences between RBD and LBD. VLSM showed a cluster of voxels located in the right inferior parietal lobule significantly related to errors in the prospective items. The lesion subtraction analysis revealed two different patterns possibly associated with errors in the prospective items (the right inferior parietal cortex, rolandic operculum and posterior middle temporal gyrus) and in the retrospective items (superior middle temporal gyrus, white matter posterior to the insula).

Timing Intervals Using Population Synchrony and Spike Timing Dependent Plasticity

We present a computational model by which ensembles of regularly spiking neurons can encode different time intervals through synchronous firing. We show that a neuron responding to a large population of convergent inputs has the potential to learn to produce an appropriately-timed output via spike-time dependent plasticity. We explain why temporal variability of this population synchrony increases with increasing time intervals. We also show that the scalar property of timing and its violation at short intervals can be explained by the spike-wise accumulation of jitter in the inter-spike intervals of timing neurons. We explore how the challenge of encoding longer time intervals can be overcome and conclude that this may involve a switch to a different population of neurons with lower firing rate, with the added effect of producing an earlier bias in response. Experimental data on human timing performance show features in agreement with the model's output.

A Brief History of “The Psychology of Time Perception”

Basic mechanisms of interval timing and associative learning are shared by many animal species, and develop quickly in early life, particularly across infancy, and childhood. Indeed, John Wearden in his book “The Psychology of Time Perception”, which is based on decades of his own research with colleagues, and which our commentary serves to primarily review, has been instrumental in implementing animal models and methods in children and adults, and has revealed important similarities (and differences) between human timing (and that of animals) when considered within the context of scalar timing theory. These seminal studies provide a firm foundation upon which the contemporary multifaceted field of timing and time perception has since advanced. The contents of the book are arguably one piece of a larger puzzle, and as Wearden cautions, “The reader is warned that my own contribution to the field has been exaggerated here, but if you are not interested in your own work, why would anyone else be?” Surely there will be many interested readers, however the book is noticeably lacking in it neurobiological perspective. The mind (however it is conceived) needs a brain (even if behaviorists tend to say “the brain behaves”, and most neuroscientists currently have a tenuous grasp on the neural mechanisms of temporal cognition), and to truly understand the psychology of time, brain and behavior must go hand in hand regardless of the twists, turns, and detours along the way.

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

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).

Emotional modulation of interval timing and time perception

Like other senses, our perception of time is not veridical, but rather, is modulated by changes in environmental context. Anecdotal experiences suggest that emotions can be powerful modulators of time perception; nevertheless, the functional and neural mechanisms underlying emotion-induced temporal distortions remain unclear. Widely accepted pacemaker-accumulator models of time perception suggest that changes in arousal and attention have unique influences on temporal judgments and contribute to emotional distortions of time perception. However, such models conflict with current views of arousal and attention suggesting that current models of time perception do not adequately explain the variability in emotion-induced temporal distortions. Instead, findings provide support for a new perspective of emotion-induced temporal distortions that emphasizes both the unique and interactive influences of arousal and attention on time perception over time. Using this framework, we discuss plausible functional and neural mechanisms of emotion-induced temporal distortions and how these temporal distortions may have important implications for our understanding of how emotions modulate our perceptual experiences in service of adaptive responding to biologically relevant stimuli.

Corticostriatal Field Potentials Are Modulated at Delta and Theta Frequencies during Interval-Timing Task in Rodents

Organizing movements in time is a critical and highly conserved feature of mammalian behavior. Temporal control of action requires corticostriatal networks. We investigate these networks in rodents using a two-interval timing task while recording LFPs in medial frontal cortex (MFC) or dorsomedial striatum. Consistent with prior work, we found cue-triggered delta (1–4 Hz) and theta activity (4–8 Hz) primarily in rodent MFC. We observed delta activity across temporal intervals in MFC and dorsomedial striatum. Rewarded responses were associated with increased delta activity in MFC. Activity in theta bands in MFC and delta bands in the striatum was linked with the timing of responses. These data suggest both delta and theta activity in frontostriatal networks are modulated during interval timing and that activity in these bands may be involved in the temporal control of action.

Clocks within Clocks: Timing by Coincidence Detection

The many existent models of timing rely on vastly different mechanisms to track temporal information. Here we examine these differences, and identify coincidence detection in its most general form as a common mechanism that many apparently different timing models share, as well as a common mechanism of biological circadian, millisecond and interval timing. This view predicts that timing by coincidence detection is a ubiquitous phenomenon at many biological levels, explains the reports of biological timing in many brain areas, explains the role of neural noise at different time scales at both biological and theoretical levels, and provides cohesion within the timing field.

Dissecting Neural Responses to Temporal Prediction, Attention, and Memory: Effects of Reward Learning and Interoception on Time Perception

Temporal prediction (TP) is needed to anticipate future events and is essential for survival. Our sense of time is modulated by emotional and interoceptive (corporal) states that are hypothesized to rely on a dopamine (DA)-modulated "internal clock" in the basal ganglia. However, the neurobiological substrates for TP in the human brain have not been identified. We tested the hypothesis that TP involves DA striato-cortical pathways, and that accurate responses are reinforcing in themselves and activate the nucleus accumbens (NAc). Functional magnetic resonance imaging revealed the involvement of the NAc and anterior insula in the temporal precision of the responses, and of the ventral tegmental area in error processing. Moreover, NAc showed higher activation for successful than for unsuccessful trials, indicating that accurate TP per se is rewarding. Inasmuch as activation of the NAc is associated with drug-induced addictive behaviors, its activation by accurate TP could help explain why video games that rely on TP can trigger compulsive behaviors.

Oscillatory multiplexing of neural population codes for interval timing and working memory

Interval timing and working memory are critical components of cognition that are supported by neural oscillations in prefrontal-striatal-hippocampal circuits. In this review, the properties of interval timing and working memory are explored in terms of behavioral, anatomical, pharmacological, and neurophysiological findings. We then describe the various neurobiological theories that have been developed to explain these cognitive processes - largely independent of each other. Following this, a coupled excitatory - inhibitory oscillation (EIO) model of temporal processing is proposed to address the shared oscillatory properties of interval timing and working memory. Using this integrative approach, we describe a hybrid model explaining how interval timing and working memory can originate from the same oscillatory processes, but differ in terms of which dimension of the neural oscillation is utilized for the extraction of item, temporal order, and duration information. This extension of the striatal beat-frequency (SBF) model of interval timing (Matell and Meck, 2000, 2004) is based on prefrontal-striatal-hippocampal circuit dynamics and has direct relevance to the pathophysiological distortions observed in time perception and working memory in a variety of psychiatric and neurological conditions.

What does scalar timing tell us about neural dynamics?

The “Scalar Timing Law,” which is a temporal domain generalization of the well known Weber Law, states that the errors estimating temporal intervals scale linearly with the durations of the intervals. Linear scaling has been studied extensively in human and animal models and holds over several orders of magnitude, though to date there is no agreed upon explanation for its physiological basis. Starting from the assumption that behavioral variability stems from neural variability, this work shows how to derive firing rate functions that are consistent with scalar timing. We show that firing rate functions with a log-power form, and a set of parameters that depend on spike count statistics, can account for scalar timing. Our derivation depends on a linear approximation, but we use simulations to validate the theory and show that log-power firing rate functions result in scalar timing over a large range of times and parameters. Simulation results match the predictions of our model, though our initial formulation results in a slight bias toward overestimation that can be corrected using a simple iterative approach to learn a decision threshold.

What is all the noise about in interval timing?

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.

Subthalamic deep brain stimulation in Parkinson׳s disease has no significant effect on perceptual timing in the hundreds of milliseconds range

Bilateral, high-frequency stimulation of the basal ganglia (STN-DBS) is in widespread use for the treatment of the motor symptoms of Parkinson׳s disease (PD). We present here the first psychophysical investigation of the effect of STN-DBS upon perceptual timing in the hundreds of milliseconds range, with both duration-based (absolute) and beat-based (relative) tasks; 13 patients with PD were assessed with their STN-DBS ‘on’, ‘off’, and then ‘on’ again.

Paired parametric analyses revealed no statistically significant differences for any task according to DBS status. We demonstrate, from the examination of confidence intervals, that any functionally relevant effect of STN-DBS on relative perceptual timing is statistically unlikely. For absolute, duration-based timing, we demonstrate that the activation of STN-DBS may either worsen performance or have no effect, but that it is unlikely to lead to significant improvement.

Although these results are negative they have important implications for our understanding of perceptual timing and its relationship to motor functions within the timing network of the brain. They imply that the mechanisms involved in the perceptual processing of temporal information are likely to be functionally independent from those that underpin movement. Further, they suggest that the connections between STN and the subtantia nigra and globus pallidus are unlikely to be critical to beat-based perceptual timing.

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We assessed the effect of STN-DBS on both duration- and beat-based perceptual timing.

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DBS activation did not profoundly affect beat-based perceptual timing.

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An effect of DBS on duration-based timing was not demonstrated but cannot be excluded.

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Connections between STN and cerebellum are unlikely to be critical to perceptual timing.

Timing and expectation of reward: a neuro-computational model of the afferents to the ventral tegmental area

Neural activity in dopaminergic areas such as the ventral tegmental area is influenced by timing processes, in particular by the temporal expectation of rewards during Pavlovian conditioning. Receipt of a reward at the expected time allows to compute reward-prediction errors which can drive learning in motor or cognitive structures. Reciprocally, dopamine plays an important role in the timing of external events. Several models of the dopaminergic system exist, but the substrate of temporal learning is rather unclear. In this article, we propose a neuro-computational model of the afferent network to the ventral tegmental area, including the lateral hypothalamus, the pedunculopontine nucleus, the amygdala, the ventromedial prefrontal cortex, the ventral basal ganglia (including the nucleus accumbens and the ventral pallidum), as well as the lateral habenula and the rostromedial tegmental nucleus. Based on a plausible connectivity and realistic learning rules, this neuro-computational model reproduces several experimental observations, such as the progressive cancelation of dopaminergic bursts at reward delivery, the appearance of bursts at the onset of reward-predicting cues or the influence of reward magnitude on activity in the amygdala and ventral tegmental area. While associative learning occurs primarily in the amygdala, learning of the temporal relationship between the cue and the associated reward is implemented as a dopamine-modulated coincidence detection mechanism in the nucleus accumbens.

Comparison of interval timing behaviour in mice following dorsal or ventral hippocampal lesions with mice having δ-opioid receptor gene deletion

Mice with cytotoxic lesions of the dorsal hippocampus (DH) underestimated 15 s and 45 s target durations in a bi-peak procedure as evidenced by proportional leftward shifts of the peak functions that emerged during training as a result of decreases in both 'start' and 'stop' times. In contrast, mice with lesions of the ventral hippocampus (VH) displayed rightward shifts that were immediately present and were largely limited to increases in the 'stop' time for the 45 s target duration. Moreover, the effects of the DH lesions were congruent with the scalar property of interval timing in that the 15 s and 45 s functions superimposed when plotted on a relative timescale, whereas the effects of the VH lesions violated the scalar property. Mice with DH lesions also showed enhanced reversal learning in comparison to control and VH lesioned mice. These results are compared with the timing distortions observed in mice lacking δ-opioid receptors (Oprd1(-/-)) which were similar to mice with DH lesions. Taken together, these results suggest a balance between hippocampal-striatal interactions for interval timing and demonstrate possible functional dissociations along the septotemporal axis of the hippocampus in terms of motivation, timed response thresholds and encoding in temporal memory.

Phase resetting and its implications for interval timing with intruders

Time perception in the second-to-minutes range is crucial for fundamental cognitive processes like decision making, rate calculation, and planning. We used a striatal beat frequency (SBF) computational model to predict the response of an interval timing network to intruders, such as gaps in conditioning stimulus (CS), or distracters presented during the uninterrupted CS. We found that, depending on the strength of the input provided to neural oscillators by the intruder, the SBF model can either ignore it or reset timing. The significant delays in timing produced by emotionally charged distracters were numerically simulated by a strong phase resetting of all neural oscillators involved in the SBF network for the entire duration of the evoked response. The combined effect of emotional distracter and pharmacological manipulations was modeled in our SBF model by modulating the firing frequencies of neural oscillators after they are released from inhibition due to emotional distracters. This article is part of a Special Issue entitled: SI: Associative and Temporal Learning.

Associative and temporal processes: a dual process approach

Approaches to the study of associative learning and interval timing have traditionally diverged on methodological and theoretical levels of analysis. However, more recent attempts have been made to explain one class of phenomena in terms of the other using various single-process approaches. In this paper we suggest that an interactive dual-process approach might more accurately reflect underlying behavioral and neural processes. We will argue that timing in Pavlovian conditioning is best understood in terms of an abstract temporal code that is not a feature of the predictive stimulus (i.e., the conditioned stimulus, CS), per se. Rather, we assume that the time between the CS and the unconditioned stimulus (US) is encoded in the form of an abstract representation of this temporal interval produced as an output of a central multiple-oscillator interval timing system. As such, associations can then develop between the CS and this abstract temporal code in much the same way that the CS develops associations with different features of the US. To support the dual-process approach, we first show that exposure to a Pavlovian zero contingency procedure results in a failure to acquire new associations, not a failure to express learning due to some temporally defined performance mask. We also consider evidence that supports the abstract temporal coding idea in a US preexposure task, and, finally, present some evidence to encourage the dissociation between basic associative and temporal learning processes by exploring reward devaluation effects in a peak timing task.

Dedicated clock/timing-circuit theories of time perception and timed performance

Scalar Timing Theory (an information-processing version of Scalar Expectancy Theory) and its evolution into the neurobiologically plausible Striatal Beat-Frequency (SBF) theory of interval timing are reviewed. These pacemaker/accumulator or oscillation/coincidence detection models are then integrated with the Adaptive Control of Thought-Rational (ACT-R) cognitive architecture as dedicated timing modules that are able to make use of the memory and decision-making mechanisms contained in ACT-R. The different predictions made by the incorporation of these timing modules into ACT-R are discussed as well as the potential limitations. Novel implementations of the original SBF model that allow it to be incorporated into ACT-R in a more fundamental fashion than the earlier simulations of Scalar Timing Theory are also considered in conjunction with the proposed properties and neural correlates of the "internal clock".