According to reinforcement learning theory of decision making, reward expectation is computed by integrating past rewards with a fixed timescale. By contrast, we found that a wide range of time constants is available across cortical neurons recorded from monkeys performing a competitive game task. By recognizing that reward modulates neural activity multiplicatively, we found that one or two time constants of reward memory can be extracted for each neuron in prefrontal, cingulate, and parietal cortex. These timescales ranged from hundreds of milliseconds to tens of seconds, according to a power-law distribution, which is consistent across areas and reproduced by a “reservoir” neural network model. These neuronal memory timescales were weakly but significantly correlated with those of monkey's decisions. Our findings suggest a flexible memory system, where neural subpopulations with distinct sets of long or short memory timescales may be selectively deployed according to the task demands.
Two general classes of models have been proposed to account for how people process temporal information in the milliseconds range. Dedicated models entail a mechanism in which time is explicitly encoded; examples include clock–counter models and functional delay lines. Intrinsic models, such as state-dependent networks (SDN), represent time as an emergent property of the dynamics of neural processing. An important property of SDN is that the encoding of duration is context dependent since the representation of an interval will vary as a function of the initial state of the network. Consistent with this assumption, duration discrimination thresholds for auditory intervals spanning 100 ms are elevated when an irrelevant tone is presented at varying times prior to the onset of the test interval. We revisit this effect in two experiments, considering attentional issues that may also produce such context effects. The disruptive effect of a variable context was eliminated or attenuated when the intervals between the irrelevant tone and test interval were made dissimilar or the duration of the test interval was increased to 300 ms. These results indicate how attentional processes can influence the perception of brief intervals, as well as point to important constraints for SDN models.
time perception; neural networks; dedicated timing; psychophysics
The current research was designed to establish whether individual differences in timing performance predict neural activation in the areas that subserve the perception of short durations ranging between 400 and 1600 milliseconds. Seventeen participants completed both a temporal bisection task and a control task, in a mixed fMRI design. In keeping with previous research, there was increased activation in a network of regions typically active during time perception including the right supplementary motor area (SMA) and right pre-SMA and basal ganglia (including the putamen and right pallidum). Furthermore, correlations between neural activity in the right inferior frontal gyrus and SMA and timing performance corroborate the results of a recent meta-analysis and are further evidence that the SMA forms part of a neural clock that is responsible for the accumulation of temporal information. Specifically, subjective lengthening of the perceived duration were associated with increased activation in both the right SMA (and right pre-SMA) and right inferior frontal gyrus.
The ability to probe defined neural circuits with both the spatial and temporal resolution imparted by optogenetics has transformed the field of neuroscience. Although much attention has been paid to the advantages of manipulating neural activity at millisecond timescales in order to elicit time-locked neural responses, little consideration has been given to the manipulation of circuit activity at physiologically relevant times of day, across multiple days. Nearly all biological events are governed by the circadian clock and exhibit 24 h rhythms in activity. Indeed, neural circuit activity itself exhibits a daily rhythm with distinct temporal peaks in activity occurring at specific times of the day. Therefore, experimentally probing circuit function within and across physiologically relevant time windows (minutes to hours) in behaving animals is fundamental to understanding the function of any one particular circuit within the intact brain. Furthermore, understanding how circuit function changes with repeated manipulation is important for modeling the circuit-wide disruptions that occur with chronic disease states. Here, we review recent advances in optogenetic technology that allow for chronic, temporally specific, control of circuit activity and provide examples of chronic optogenetic paradigms that have been utilized in the search for the neural circuit basis of behaviors relevant to human neuropsychiatric disease.
optogenetics; opsins; circadian rhythms; addiction; depression; bipolar disorder; obsessive-compulsive disorder; mouse models
A number of studies have examined the perception of time with durations ranging from milliseconds to a few seconds, however the neural basis of these processes are still poorly understood and the neural substrates underlying the perception of multiple-second intervals are unknown. Here we present evidence of neural systems activity in circumscribed areas of the human brain involved in the encoding of intervals with durations of 9 and 18 seconds in a temporal reproduction task using event-related functional magnetic resonance imaging (fMRI). During the encoding there was greater activation in more posterior parts of the medial frontal and insular cortex whereas the reproduction phase involved more anterior parts of these brain structures. Intriguingly, activation curves over time show an accumulating pattern of neural activity, which peaks at the end of the interval within bilateral posterior insula and superior temporal cortex when individuals are presented with 9- and 18-second tone intervals. This is consistent with an accumulator-type activity, which encodes duration in the multiple seconds range. Given the close connection between the dorsal posterior insula and ascending internal body signals, we suggest that the accumulation of physiological changes in body states constitutes our experience of time. This is the first time that an accumulation function in the posterior insula is detected that might be correlated with the encoding of time intervals.
time perception; duration reproduction; insular cortex; fMRI
Temporal judgment in the milliseconds-to-seconds range depends on consistent attention to time and robust working memory representation. Individual differences in working memory capacity (WMC) predict a wide range of higher-order and lower-order cognitive abilities. In the present work we examined whether WMC would predict temporal discrimination. High-WMC individuals were more sensitive than low-WMC at discriminating the longer of two temporal intervals across a range of temporal differences. WMC-related individual differences in temporal discrimination were not eliminated by including a measure of fluid intelligence as a covariate. Results are discussed in terms of attention, working memory and other psychological constructs.
Stimulant-dependent individuals (SDI) have abnormal brain metabolism and structural changes involving dopaminergic target areas important for the processing of time. These individuals are also more impulsive and impaired in working memory and attention. The current study tested whether SDI show altered temporal processing in relation to impulsivity or impaired prefrontal cortex functioning. We employed a series of timing tasks aimed to examine time processing from the milliseconds to multiple seconds range and assessed cognitive function in 15 male SDI and 15 stimulant-naïve individuals. A mediation analysis determined the degree to which impulsivity or executive dysfunctions contributed to group differences in time processing. SDI showed several abnormal time processing characteristics. SDI needed larger time differences for effective duration discrimination, particularly for intervals of around 1 sec. SDI also accelerated finger tapping during a continuation period after a 1 Hz pacing stimulus was removed. In addition, SDI overestimated the duration of a relatively long time interval, an effect which was attributable to higher impulsivity. Taken together, these data show for the first time that SDI exhibit altered time processing in several domains, one which can be explained by increased impulsivity. Altered time processing in SDI could explain why SDI have difficulty delaying gratification.
Methamphetamine; Cocaine; Dopamine; Temporal processing; Working memory; Impulsivity
Proteins are dynamic molecules with motions ranging from picoseconds to longer than seconds. Many protein functions, however, appear to occur on the micro to millisecond timescale and therefore there has been intense research of the importance of these motions in catalysis and molecular interactions. Nuclear Magnetic Resonance (NMR) relaxation dispersion experiments are used to measure motion of discrete nuclei within the micro to millisecond timescale. Information about conformational/chemical exchange, populations of exchanging states and chemical shift differences are extracted from these experiments. To ensure these parameters are correctly extracted, accurate and careful analysis of these experiments is necessary.
The software introduced in this article is designed for the automatic analysis of relaxation dispersion data and the extraction of the parameters mentioned above. It is written in Python for multi platform use and highest performance. Experimental data can be fitted to different models using the Levenberg-Marquardt minimization algorithm and different statistical tests can be used to select the best model. To demonstrate the functionality of this program, synthetic data as well as NMR data were analyzed. Analysis of these data including the generation of plots and color coded structures can be performed with minimal user intervention and using standard procedures that are included in the program.
NESSY is easy to use open source software to analyze NMR relaxation data. The robustness and standard procedures are demonstrated in this article.
Protein dynamics; software; cpmg; conformational/chemical exchange; μs-ms motion; van't Hoff; transition state theory
Spike timing is thought to be an important mechanism for transmitting information in the CNS. Recent studies have emphasized millisecond precision in spike timing, to allow temporal summation of rapid synaptic signals. However, spike timing over slower timescales could also be important, through mechanisms including activity-dependent synaptic plasticity, or temporal summation of slow PSPs such as those mediated by kainate receptors. To determine the extent to which these slower mechanisms contribute to information processing, it is first necessary to understand the properties of behaviorally relevant spike timing over this slow timescale. In this study, we examine the activity of CA3 pyramidal cells during the performance of a complex behavioral task in rats. Sustained firing rates vary over a wide range, and the firing rate of a cell is poorly correlated with the behavioral cues to which the cell responds. Non-random interactions between successive spikes can last for several seconds, but the non-random distribution of interspike intervals (ISIs) can account for the majority of nonrandom multi-spike patterns. During a stimulus, cellular responses are temporally complex, causing a shift in spike timing that favors intermediate ISIs over short and long ISIs. Response discrimination between related stimuli occurs through changes in both response time-course and response intensity. Precise synchrony between cells is limited, but loosely correlated firing between cells is common. This study indicates that spike timing is regulated over long timescales, and suggests that slow synaptic mechanisms could play a substantial role in information processing in the CNS.
Anticipation occurs on timescales ranging from milliseconds to hours to days. This paper relates the theoretical and methodological developments in the study of interval timing in the seconds, minutes and hours range to research on the anticipatory activity induced by regularly timed daily meals. Daily food anticipatory activity (FAA) is entrained by procedures which are formally identical to procedures studied in Pavlovian and Operant conditioning except for the long duration of the interval between feeding opportunities. As in FAA, the conditioning procedures induce orderly anticipatory activity in advance of food presentation. During the interval between foods the behaviors that express anticipation change as the interval progresses. Consequently, no single response represents a pure measure of anticipation. The ability to distinguish between properties of general anticipatory timing mechanisms such as the scalar property (Gibbon, 1977) and dynamic properties of specific response output systems has been facilitated by teaching animals to use arbitrary anticipatory responses like bar pressing to obtain food. Interval timing research highlights the importance of identifying the mechanisms of perception, memory, decision making and motivation that all contribute to food anticipation. We suggest that future work focused on the similarities and differences in the neural bases of FAA and interval timing may be useful in unravelling the mechanisms mediating timing behavior.
food anticipatory activity; interval timing; Pavlovian conditioning; scalar property
When two tasks are presented within a short interval, a delay in the execution of the second task has been systematically observed. Psychological theorizing has argued that while sensory and motor operations can proceed in parallel, the coordination between these modules establishes a processing bottleneck. This model predicts that the timing but not the characteristics (duration, precision, variability…) of each processing stage are affected by interference. Thus, a critical test to this hypothesis is to explore whether the qualitiy of the decision is unaffected by a concurrent task.
In number comparison–as in most decision comparison tasks with a scalar measure of the evidence–the extent to which two stimuli can be discriminated is determined by their ratio, referred as the Weber fraction. We investigated performance in a rapid succession of two non-symbolic comparison tasks (number comparison and tone discrimination) in which error rates in both tasks could be manipulated parametrically from chance to almost perfect. We observed that dual-task interference has a massive effect on RT but does not affect the error rates, or the distribution of errors as a function of the evidence.
Our results imply that while the decision process itself is delayed during multiple task execution, its workings are unaffected by task interference, providing strong evidence in favor of a sequential model of task execution.
In most species, the capability of perceiving and using the passage of time in the seconds-to-minutes range (interval timing) is not only accurate but also scalar: errors in time estimation are linearly related to the estimated duration. The ubiquity of scalar timing extends over behavioral, lesion, and pharmacological manipulations. For example, in mammals, dopaminergic drugs induce an immediate, scalar change in the perceived time (clock pattern), whereas cholinergic drugs induce a gradual, scalar change in perceived time (memory pattern). How do these properties emerge from unreliable, noisy neurons firing in the milliseconds range? Neurobiological information relative to the brain circuits involved in interval timing provide support for an striatal beat frequency (SBF) model, in which time is coded by the coincidental activation of striatal spiny neurons by cortical neural oscillators. While biologically plausible, the impracticality of perfect oscillators, or their lack thereof, questions this mechanism in a brain with noisy neurons. We explored the computational mechanisms required for the clock and memory patterns in an SBF model with biophysically realistic and noisy Morris–Lecar neurons (SBF–ML). Under the assumption that dopaminergic drugs modulate the firing frequency of cortical oscillators, and that cholinergic drugs modulate the memory representation of the criterion time, we show that our SBF–ML model can reproduce the pharmacological clock and memory patterns observed in the literature. Numerical results also indicate that parameter variability (noise) – which is ubiquitous in the form of small fluctuations in the intrinsic frequencies of neural oscillators within and between trials, and in the errors in recording/retrieving stored information related to criterion time – seems to be critical for the time-scale invariance of the clock and memory patterns.
interval timing; striatal beat frequency; computer simulations; dopamine; acetylcholine; neural noise; noise
It is not yet known whether the scalar properties of explicit timing are also displayed by more implicit, predictive forms of timing. We investigated whether performance in both explicit and predictive timing tasks conformed to the two psychophysical properties of scalar timing: the Psychophysical law and Weber's law. Our explicit temporal generalization task required overt estimation of the duration of an empty interval bounded by visual markers, whereas our temporal expectancy task presented visual stimuli at temporally predictable intervals, which facilitated motor preparation thus speeding target detection. The Psychophysical Law and Weber's Law were modeled, respectively, by (1) the functional dependence between mean subjective time and real time (2) the linearity of the relationship between timing variability and duration. Results showed that performance for predictive, as well as explicit, timing conformed to both psychophysical properties of interval timing. Both tasks showed the same linear relationship between subjective and real time, demonstrating that the same representational mechanism is engaged whether it is transferred into an overt estimate of duration or used to optimise sensorimotor behavior. Moreover, variability increased with increasing duration during both tasks, consistent with a scalar representation of time in both predictive and explicit timing. However, timing variability was greater during predictive timing, at least for durations greater than 200 msec, and ascribable to temporal, rather than non-temporal, mechanisms engaged by the task. These results suggest that although the same internal representation of time was used in both tasks, its external manifestation varied as a function of temporal task goals.
Neurons show diverse timescales, so that different parts of a network respond with disparate temporal dynamics. Such diversity is observed both when comparing timescales across brain areas and among cells within local populations; the underlying circuit mechanism remains unknown. We examine conditions under which spatially local connectivity can produce such diverse temporal behavior.
In a linear network, timescales are segregated if the eigenvectors of the connectivity matrix are localized to different parts of the network. We develop a framework to predict the shapes of localized eigenvectors. Notably, local connectivity alone is insufficient for separate timescales. However, localization of timescales can be realized by heterogeneity in the connectivity profile, and we demonstrate two classes of network architecture that allow such localization. Our results suggest a framework to relate structural heterogeneity to functional diversity and, beyond neural dynamics, are generally applicable to the relationship between structure and dynamics in biological networks.
Many biological systems can be thought of as networks in which a large number of elements, called ‘nodes’, are connected to each other. The brain, for example, is a network of interconnected neurons, and the changing activity patterns of this network underlie our experience of the world around us. Within the brain, different parts can process information at different speeds: sensory areas of the brain respond rapidly to the current environment, while the cognitive areas of the brain, involved in complex thought processes, are able to gather information over longer periods of time. However, it has been largely unknown what properties of a network allow different regions to process information over different timescales, and how variations in structural properties translate into differences in the timescales over which parts of a network can operate.
Now Chaudhuri et al. have addressed these issues using a simple but ubiquitous class of networks called linear networks. The activity of a linear network can be broken down into simpler patterns called eigenvectors that can be combined to predict the responses of the whole network. If these eigenvectors ‘map’ to different parts of the network, this could explain how distinct regions process information on different timescales.
Chaudhuri et al. developed a mathematical theory to predict what properties would cause such eigenvectors to be separated from each other and applied it to networks with architectures that resemble the wiring of the brain. This revealed that gradients in the connectivity across the network, such that nodes share more properties with neighboring nodes than distant nodes, combined with random differences in the strength of inter-node connections, are general motifs that give rise to such separated activity patterns. Intriguingly, such gradients and randomness are both common features of biological systems.
timescales; network dynamics; neural networks; None
The notion of the temporal window of integration, when applied in a multisensory context, refers to the breadth of the interval across which the brain perceives two stimuli from different sensory modalities as synchronous. It maintains a unitary perception of multisensory events despite physical and biophysical timing differences between the senses. The boundaries of the window can be influenced by attention and past sensory experience. Here we examined whether task demands could also influence the multisensory temporal window of integration. We varied the stimulus onset asynchrony between simple, short-lasting auditory and visual stimuli while participants performed two tasks in separate blocks: a temporal order judgment task that required the discrimination of subtle auditory-visual asynchronies, and a reaction time task to the first incoming stimulus irrespective of its sensory modality. We defined the temporal window of integration as the range of stimulus onset asynchronies where performance was below 75% in the temporal order judgment task, as well as the range of stimulus onset asynchronies where responses showed multisensory facilitation (race model violation) in the reaction time task. In 5 of 11 participants, we observed audio-visual stimulus onset asynchronies where reaction time was significantly accelerated (indicating successful integration in this task) while performance was accurate in the temporal order judgment task (indicating successful segregation in that task). This dissociation suggests that in some participants, the boundaries of the temporal window of integration can adaptively recalibrate in order to optimize performance according to specific task demands.
The discrimination and production of temporal patterns on the scale of hundreds of milliseconds are critical to sensory and motor processing. Indeed, most complex behaviours, such as speech comprehension and production, would be impossible in the absence of sophisticated timing mechanisms. Despite the importance of timing to human learning and cognition, little is known about the underlying mechanisms, in particular whether timing relies on specialized dedicated circuits and mechanisms or on general and intrinsic properties of neurons and neural circuits. Here, we review experimental data describing timing and interval-selective neurons in vivo and in vitro. We also review theoretical models of timing, focusing primarily on the state-dependent network model, which proposes that timing in the subsecond range relies on the inherent time-dependent properties of neurons and the active neural dynamics within recurrent circuits. Within this framework, time is naturally encoded in populations of neurons whose pattern of activity is dynamically changing in time. Together, we argue that current experimental and theoretical studies provide sufficient evidence to conclude that at least some forms of temporal processing reflect intrinsic computations based on local neural network dynamics.
neural dynamics; temporally selective neurons; state-dependent network model; short-term plasticity
The ability to process temporal information is fundamental to sensory perception, cognitive processing and motor behaviour of all living organisms, from amoebae to humans1–4. Neural circuit mechanisms based on neuronal and synaptic properties have been shown to process temporal information over the range of tens of microseconds to hundreds of milliseconds5–7. How neural circuits process temporal information in the range of seconds to minutes is much less understood. Studies of working memory in monkeys and rats have shown that neurons in the prefrontal cortex8–10, the parietal cortex9,11 and the thalamus12 exhibit ramping activities that linearly correlate with the lapse of time until the end of a specific time interval of several seconds that the animal is trained to memorize. Many organisms can also memorize the time interval of rhythmic sensory stimuli in the timescale of seconds and can coordinate motor behaviour accordingly, for example, by keeping the rhythm after exposure to the beat of music. Here we report a form of rhythmic activity among specific neuronal ensembles in the zebrafish optic tectum, which retains the memory of the time interval (in the order of seconds) of repetitive sensory stimuli for a duration of up to ~20 s. After repetitive visual conditioning stimulation (CS) of zebrafish larvae, we observed rhythmic post-CS activities among specific tectal neuronal ensembles, with a regular interval that closely matched the CS. Visuomotor behaviour of the zebrafish larvae also showed regular post-CS repetitions at the entrained time interval that correlated with rhythmic neuronal ensemble activities in the tectum. Thus, rhythmic activities among specific neuronal ensembles may act as an adjustable ‘metronome’ for time intervals in the order of seconds, and serve as a mechanism for the short-term perceptual memory of rhythmic sensory experience.
Pigeons were trained on two temporal bisection tasks, which alternated every two sessions. In the first task, they learned to choose a red key after a 1-s signal and a green key after a 4-s signal; in the second task, they learned to choose a blue key after a 4-s signal and a yellow key after a 16-s signal. Then the pigeons were exposed to a series of test trials in order to contrast two timing models, Learning-to-Time (LeT) and Scalar Expectancy Theory (SET). The models made substantially different predictions particularly for the test trials in which the sample duration ranged from 1 s to 16 s and the choice keys were Green and Blue, the keys associated with the same 4-s samples: LeT predicted that preference for Green should increase with sample duration, a context effect, but SET predicted that preference for Green should not vary with sample duration. The results were consistent with LeT. The present study adds to the literature the finding that the context effect occurs even when the two basic discriminations are never combined in the same session.
bisection procedure; context effect; temporal discrimination; timing models; key peck; pigeon
Previous research suggests that the frontal lobes are essential for temporal processing. We report a patient, MN, with probable Frontotemporal Dementia (FTD) who was tested on a battery of timing tasks with stimuli in the sub- and supra-second range. MN demonstrated a substantial over-estimation and under-production of target intervals on estimation and production tasks respectively but was as accurate as controls on a reproduction task. Furthermore, this deficit was markedly different for auditory and visual stimuli on production and estimation tasks; estimates of the duration of auditory stimuli were 3-4 times longer than for comparable visual stimuli. She performed normally on a task requiring her to judge whether a stimulus was longer or shorter than a standard duration with both sub- and supra-second stimuli. She performed well on control tasks involving estimation, production and reproduction of line lengths suggesting that her deficits were not attributable to a generalized cognitive impairment or an inability to make magnitude judgments. These data suggest that bifrontal pathology disrupts the “clock” or memory for time.
Temporal processing; interval timing; Frontotemporal dementia; 0THERS?
Compared to our understanding of the functional maturation of executive functions, little is known about the neurofunctional development of perceptive functions. Time perception develops during late adolescence, underpinning many functions including motor and verbal processing, as well as late maturing higher order cognitive skills such as forward planning and future-related decision making. Nothing, however, is known about the neurofunctional changes associated with time perception from childhood to adulthood. Using functional magnetic resonance imaging we explored the effects of age on the brain activation and functional connectivity of 32 male participants from 10 to 53 years of age during a time discrimination task that required the discrimination of temporal intervals of seconds differing by several hundred milliseconds. Increasing development was associated with progressive activation increases within left lateralized dorsolateral and inferior fronto-parieto-striato-thalamic brain regions. Furthermore, despite comparable task performance, adults showed increased functional connectivity between inferior/dorsolateral interhemispheric fronto-frontal activation as well as between inferior fronto-parietal regions compared with adolescents. Activation in caudate, specifically, was associated with both increasing age and better temporal discrimination. Progressive decreases in activation with age were observed in ventromedial prefrontal cortex, limbic regions, and cerebellum. The findings demonstrate age-dependent developmentally dissociated neural networks for time discrimination. With increasing age there is progressive recruitment of later maturing left hemispheric and lateralized fronto-parieto-striato-thalamic networks, known to mediate time discrimination in adults, while earlier developing brain regions such as ventromedial prefrontal cortex, limbic and paralimbic areas, and cerebellum subserve fine-temporal processing functions in children and adolescents.
development; time discrimination; functional magnetic resonance imaging
It has been suggested that perception and action can be understood as evolving in temporal epochs or sequential processing units. Successive events are fused into units forming a unitary experience or “psychological present.” Studies have identified several temporal integration levels on different time scales which are fundamental for our understanding of behavior and subjective experience. In recent literature concerning the philosophy and neuroscience of consciousness these separate temporal processing levels are not always precisely distinguished. Therefore, empirical evidence from psychophysics and neuropsychology on these distinct temporal processing levels is presented and discussed within philosophical conceptualizations of time experience. On an elementary level, one can identify a functional moment, a basic temporal building block of perception in the range of milliseconds that defines simultaneity and succession. Below a certain threshold temporal order is not perceived, individual events are processed as co-temporal. On a second level, an experienced moment, which is based on temporal integration of up to a few seconds, has been reported in many qualitatively different experiments in perception and action. It has been suggested that this segmental processing mechanism creates temporal windows that provide a logistical basis for conscious representation and the experience of nowness. On a third level of integration, continuity of experience is enabled by working memory in the range of multiple seconds allowing the maintenance of cognitive operations and emotional feelings, leading to mental presence, a temporal window of an individual’s experienced presence.
temporal integration; time perception; the present; psychophysics
Motor variability often reflects a mixture of different neural and peripheral sources operating over a range of timescales. We present a statistical model of sequence timing that can be used to measure three distinct components of timing variability: global tempo changes that are spread across the sequence, such as might stem from neuromodulatory sources with widespread influence; fast, uncorrelated timing noise, stemming from noisy components within the neural system; and timing jitter that does not alter the timing of subsequent elements, such as might be caused by variation in the motor periphery or by measurement error. In addition to quantifying the variability contributed by each of these latent factors in the data, the approach assigns maximum likelihood estimates of each factor on a trial-to-trial basis. We applied the model to adult zebra finch song, a temporally complex behavior with rich structure on multiple timescales. We find that individual song vocalizations (syllables) contain roughly equal amounts of variability in each of the three components while overall song length is dominated by global tempo changes. Across our sample of syllables, both global and independent variability scale with average length while timing jitter does not, a pattern consistent with the Wing and Kristofferson (1973) model of sequence timing. We also find significant day-to-day drift in all three timing sources, but a circadian pattern in tempo only. In tests using artificially generated data, the model successfully separates out the different components with small error. The approach provides a general framework for extracting distinct sources of timing variability within action sequences, and can be applied to neural and behavioral data from a wide array of systems.
In the last decades, researchers have proposed a large number of theoretical models of timing. These models make different assumptions concerning how animals learn to time events and how such learning is represented in memory. However, few studies have examined these different assumptions either empirically or conceptually. For knowledge to accumulate, variation in theoretical models must be accompanied by selection of models and model ideas. To that end, we review two timing models, Scalar Expectancy Theory (SET), the dominant model in the field, and the Learning-to-Time (LeT) model, one of the few models dealing explicitly with learning. In the first part of this article, we describe how each model works in prototypical concurrent and retrospective timing tasks, identify their structural similarities, and classify their differences concerning temporal learning and memory. In the second part, we review a series of studies that examined these differences and conclude that both the memory structure postulated by SET and the state dynamics postulated by LeT are probably incorrect. In the third part, we propose a hybrid model that may improve on its parents. The hybrid model accounts for the typical findings in fixed-interval schedules, the peak procedure, mixed fixed interval schedules, simple and double temporal bisection, and temporal generalization tasks. In the fourth and last part, we identify seven challenges that any timing model must meet.
Learning-to-Time (LeT) model; Scalar Expectancy Theory (SET); mathematical models; temporal discrimination; timing
Time information processing relies on memory, which greatly supports the operations of hypothetical internal timekeepers. Scalar Expectancy Theory (SET) postulates the existence of a memory component that is functionally separated from an internal clock and other processing stages. SET has devised several experimental procedures to map these cognitive stages onto cerebral regions and neurotransmitter systems. One of these, the time bisection procedure, has provided support for a dissociation between the clock stage, controlled by dopaminergic systems, and the memory stage, mainly supported by cholinergic neuronal networks. This study aimed at linking the specific memory processes predicted by SET to brain mechanisms, by submitting time bisection tasks to patients with probable Alzheimer's disease (AD), that are known to present substantial degeneration of the fronto-temporal regions underpinning memory.
Twelve mild AD patients were required to make temporal judgments about intervals either ranging from 100 to 600 ms (short time bisection task) or from 1000 to 3000 ms (long time bisection task). Their performance was compared with that of a group of aged-matched control participants and a group of young control subjects.
Long time bisection scores of AD patients were not significantly different from those of the two control groups. In contrast, AD patients showed increased variability (as indexed by increased WR values) in timing millisecond durations and a generalized inconsistency of responses over the same interval in both the short and long bisection tasks. A similar, though milder, decreased millisecond interval sensitivity was found for elderly subjects.
The present results, that are consistent with those of previous timing studies in AD, are interpreted within the SET framework as not selectively dependent on working or reference memory disruptions but as possibly due to distortions in different components of the internal clock model. Moreover, the similarity between the timing patterns of elderly and AD participants raises the important issue of whether AD may be considered as part of the normal aging process, rather than a proper disease.
The developmental trajectory of nervous system dynamics shows hierarchical structure on time scales spanning ten orders of magnitude from milliseconds to years. Analyzing and characterizing this structure poses significant signal processing challenges. In the context of birdsong development, we have previously proposed that an effective way to do this is to use the dynamic spectrum or spectrogram, a classical signal processing tool, computed at multiple time scales in a nested fashion. Temporal structure on the millisecond timescale is normally captured using a short time Fourier analysis, and structure on the second timescale using song spectrograms. Here we use the dynamic spectrum on time series of song features to study the development of rhythm in juvenile zebra finch. The method is able to detect rhythmic structure in juvenile song in contrast to previous characterizations of such song as unstructured. We show that the method can be used to examine song development, the accuracy with which rhythm is imitated, and the variability of rhythms across different renditions of a song. We hope that this technique will provide a standard, automated method for measuring and characterizing song rhythm.