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.
Spike timing-dependent plasticity (STDP) has been shown to enable single neurons to detect repeatedly presented spatiotemporal spike patterns. This holds even when such patterns are embedded in equally dense random spiking activity, that is, in the absence of external reference times such as a stimulus onset. Here we demonstrate, both analytically and numerically, that STDP can also learn repeating rate-modulated patterns, which have received more experimental evidence, for example, through post-stimulus time histograms (PSTHs). Each input spike train is generated from a rate function using a stochastic sampling mechanism, chosen to be an inhomogeneous Poisson process here. Learning is feasible provided significant covarying rate modulations occur within the typical timescale of STDP (∼10–20 ms) for sufficiently many inputs (∼100 among 1000 in our simulations), a condition that is met by many experimental PSTHs. Repeated pattern presentations induce spike-time correlations that are captured by STDP. Despite imprecise input spike times and even variable spike counts, a single trained neuron robustly detects the pattern just a few milliseconds after its presentation. Therefore, temporal imprecision and Poisson-like firing variability are not an obstacle to fast temporal coding. STDP provides an appealing mechanism to learn such rate patterns, which, beyond sensory processing, may also be involved in many cognitive tasks.
In vivo neural responses to stimuli are known to have a lot of variability across trials. If the same number of spikes is emitted from trial to trial, the neuron is said to be reliable. If the timing of such spikes is roughly preserved across trials, the neuron is said to be precise. Here we demonstrate both analytically and numerically that the well-established Hebbian learning rule of spike-timing-dependent plasticity (STDP) can learn response patterns despite relatively low reliability (Poisson-like variability) and low temporal precision (10–20 ms). These features are in line with many experimental observations, in which a poststimulus time histogram (PSTH) is evaluated over multiple trials. In our model, however, information is extracted from the relative spike times between afferents without the need of an absolute reference time, such as a stimulus onset. Relevantly, recent experiments show that relative timing is often more informative than the absolute timing. Furthermore, the scope of application for our study is not restricted to sensory systems. Taken together, our results suggest a fine temporal resolution for the neural code, and that STDP is an appropriate candidate for encoding and decoding such activity.
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.
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 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.
A biophysical mechanism acting in auditory neurons allows the brain to process the high variability of speaking rates in natural speech in a time-warp-invariant manner.
Fluctuations in the temporal durations of sensory signals constitute a major source of variability within natural stimulus ensembles. The neuronal mechanisms through which sensory systems can stabilize perception against such fluctuations are largely unknown. An intriguing instantiation of such robustness occurs in human speech perception, which relies critically on temporal acoustic cues that are embedded in signals with highly variable duration. Across different instances of natural speech, auditory cues can undergo temporal warping that ranges from 2-fold compression to 2-fold dilation without significant perceptual impairment. Here, we report that time-warp–invariant neuronal processing can be subserved by the shunting action of synaptic conductances that automatically rescales the effective integration time of postsynaptic neurons. We propose a novel spike-based learning rule for synaptic conductances that adjusts the degree of synaptic shunting to the temporal processing requirements of a given task. Applying this general biophysical mechanism to the example of speech processing, we propose a neuronal network model for time-warp–invariant word discrimination and demonstrate its excellent performance on a standard benchmark speech-recognition task. Our results demonstrate the important functional role of synaptic conductances in spike-based neuronal information processing and learning. The biophysics of temporal integration at neuronal membranes can endow sensory pathways with powerful time-warp–invariant computational capabilities.
The brain has a robust ability to process sensory stimuli, even when those stimuli are warped in time. The most prominent example of such perceptual robustness occurs in speech communication. Rates of speech can be highly variable both within and across speakers, yet our perceptions of words remain stable. The neuronal mechanisms that subserve invariance to time warping without compromising our ability to discriminate between fine temporal cues have puzzled neuroscientists for several decades. Here, we describe a cellular process whereby auditory neurons recalibrate, on the fly, their perceptual clocks and allows them effectively to correct for temporal fluctuations in the rate of incoming sensory events. We demonstrate that this basic biophysical mechanism allows simple neural architectures to solve a standard benchmark speech-recognition task with near perfect performance. This proposed mechanism for time-warp–invariant neural processing leads to novel hypotheses about the origin of speech perception pathologies.
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
Theoretical and empirical evidence suggests that impaired time perception and the neural circuitry underlying internal timing mechanisms may contribute to severe psychiatric disorders, including psychotic and mood disorders. The degree to which alterations in temporal perceptions reflect deficits that exist across psychosis-related phenotypes and the extent to which mood symptoms contribute to these deficits is currently unknown. In addition, compared to schizophrenia, where timing deficits have been more extensively investigated, sub-second timing has been studied relatively infrequently in bipolar disorder. The present study compared sub-second duration estimates of schizophrenia (SZ), schizoaffective disorder (SA), non-psychotic bipolar disorder (BDNP), bipolar disorder with psychotic features (BDP), and healthy non-psychiatric controls (HC) on a well-established time perception task using sub-second durations. Participants included 66 SZ, 37 BDNP, 34 BDP, 31 SA, and 73 HC who participated in a temporal bisection task that required temporal judgements about auditory durations ranging from 300 to 600 milliseconds. Timing variability was significantly higher in SZ, BDP, and BDNP groups compared to healthy controls. The bisection point did not differ across groups. These findings suggest that both psychotic and mood symptoms may be associated with disruptions in internal timing mechanisms. Yet unexpected findings emerged. Specifically, the BDNP group had significantly increased variability compared to controls, but the SA group did not. In addition, these deficits appeared to exist independent of current symptom status. The absence of between group differences in bisection point suggests that increased variability in the SZ and bipolar disorder groups are due to alterations in perceptual timing in the sub-second range, possibly mediated by the cerebellum, rather than cognitive deficits.
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.
Spontaneous retinal activity (known as “waves”) remodels synaptic connectivity to the lateral geniculate nucleus (LGN) during development. Analysis of retinal waves recorded with multielectrode arrays in mouse suggested that a cue for the segregation of functionally distinct (ON and OFF) retinal ganglion cells (RGCs) in the LGN may be a desynchronization in their firing, where ON cells precede OFF cells by one second. Using the recorded retinal waves as input, with two different modeling approaches we explore timing-based plasticity rules for the evolution of synaptic weights to identify key features underlying ON/OFF segregation. First, we analytically derive a linear model for the evolution of ON and OFF weights, to understand how synaptic plasticity rules extract input firing properties to guide segregation. Second, we simulate postsynaptic activity with a nonlinear integrate-and-fire model to compare findings with the linear model. We find that spike-time-dependent plasticity, which modifies synaptic weights based on millisecond-long timing and order of pre- and postsynaptic spikes, fails to segregate ON and OFF retinal inputs in the absence of normalization. Implementing homeostatic mechanisms results in segregation, but only with carefully-tuned parameters. Furthermore, extending spike integration timescales to match the second-long input correlation timescales always leads to ON segregation because ON cells fire before OFF cells. We show that burst-time-dependent plasticity can robustly guide ON/OFF segregation in the LGN without normalization, by integrating pre- and postsynaptic bursts irrespective of their firing order and over second-long timescales. We predict that an LGN neuron will become ON- or OFF-responsive based on a local competition of the firing patterns of neighboring RGCs connecting to it. Finally, we demonstrate consistency with ON/OFF segregation in ferret, despite differences in the firing properties of retinal waves. Our model suggests that diverse input statistics of retinal waves can be robustly interpreted by a burst-based rule, which underlies retinogeniculate plasticity across different species.
Many central targets in the brain are involved in the processing of information from the outside world. Before information about the visual scene reaches the visual cortex, it is preprocessed in the retina and the lateral geniculate nucleus. Connections which relay this information between the different brain targets are not determined at birth, but undergo a developmental period during which they are guided by molecular cues to the correct locations, and refined by activity to the appropriate numbers and strengths. Before the onset of vision, spontaneous activity generated within the retina plays an important role in the remodeling of these connections. In a computational and theoretical model, we used recorded spontaneous retinal activity patterns with several plasticity rules at the retinogeniculate synapse to identify the key properties underlying the selective refinement of connections. Our model shows robust behavior when applied to both mouse and ferret data, demonstrating that a common plasticity rule across species may underlie synaptic refinements in the visual system driven by spontaneous retinal activity.
Developmental dyslexia is associated with rhythmic difficulties, including impaired perception of beat patterns in music and prosodic stress patterns in speech. Spoken prosodic rhythm is cued by slow (<10 Hz) fluctuations in speech signal amplitude. Impaired neural oscillatory tracking of these slow amplitude modulation (AM) patterns is one plausible source of impaired rhythm tracking in dyslexia. Here, we characterise the temporal profile of the dyslexic rhythm deficit by examining rhythmic entrainment at multiple speech timescales. Adult dyslexic participants completed two experiments aimed at testing the perception and production of speech rhythm. In the perception task, participants tapped along to the beat of 4 metrically-regular nursery rhyme sentences. In the production task, participants produced the same 4 sentences in time to a metronome beat. Rhythmic entrainment was assessed using both traditional rhythmic indices and a novel AM-based measure, which utilised 3 dominant AM timescales in the speech signal each associated with a different phonological grain-sized unit (0.9–2.5 Hz, prosodic stress; 2.5–12 Hz, syllables; 12–40 Hz, phonemes). The AM-based measure revealed atypical rhythmic entrainment by dyslexic participants to syllable patterns in speech, in perception and production. In the perception task, both groups showed equally strong phase-locking to Syllable AM patterns, but dyslexic responses were entrained to a significantly earlier oscillatory phase angle than controls. In the production task, dyslexic utterances showed shorter syllable intervals, and differences in Syllable:Phoneme AM cross-frequency synchronisation. Our data support the view that rhythmic entrainment at slow (∼5 Hz, Syllable) rates is atypical in dyslexia, suggesting that neural mechanisms for syllable perception and production may also be atypical. These syllable timing deficits could contribute to the atypical development of phonological representations for spoken words, the central cognitive characteristic of developmental dyslexia across languages.
This article is part of a Special Issue entitled .
•Rhythmic entrainment at the syllable timescale is disrupted in dyslexia.•Both syllable perception and production are atypical.•Syllable timing deficits could contribute to dyslexics' atypical phonology.•New AM-based methodology for measuring rhythmic entrainment is introduced.
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
Emotions change our perception of time. In the past, this has been attributed primarily to emotions speeding up an “internal clock” thereby increasing subjective time estimates. Here we probed this account using an S1/S2 temporal discrimination paradigm. Participants were presented with a stimulus (S1) followed by a brief delay and then a second stimulus (S2) and indicated whether S2 was shorter or longer in duration than S1. We manipulated participants' emotions by presenting a task-irrelevant picture following S1 and preceding S2. Participants were more likely to judge S2 as shorter than S1 when the intervening picture was emotional as compared to neutral. This effect held independent of S1 and S2 modality (Visual: Exps. 1, 2, & 3; Auditory: Exp. 4) and intervening picture valence (Negative: Exps. 1, 2 & 4; Positive: Exp. 3). Moreover, it was replicated in a temporal reproduction paradigm (Exp. 5) where a timing stimulus was preceded by an emotional or neutral picture and participants were asked to reproduce the duration of the timing stimulus. Taken together, these findings indicate that emotional experiences may decrease temporal estimates and thus raise questions about the suitability of internal clock speed explanations of emotion effects on timing. Moreover, they highlight attentional mechanisms as a viable alternative.
Perception routinely integrates inputs from different senses. Stimulus temporal proximity critically determines whether or not these inputs are bound together. Despite the temporal window of integration being a widely accepted notion, its neurophysiological substrate remains unclear. Many types of common audio-visual interactions occur within a time window of ∼100 ms [1–5]. For example, in the sound-induced double-flash illusion, when two beeps are presented within ∼100 ms together with one flash, a second illusory flash is often perceived . Due to their intrinsic rhythmic nature, brain oscillations are one candidate mechanism for gating the temporal window of integration. Interestingly, occipital alpha band oscillations cycle on average every ∼100 ms, with peak frequencies ranging between 8 and 14 Hz (i.e., 120–60 ms cycle). Moreover, presenting a brief tone can phase-reset such oscillations in visual cortex [6, 7]. Based on these observations, we hypothesized that the duration of each alpha cycle might provide the temporal unit to bind audio-visual events. Here, we first recorded EEG while participants performed the sound-induced double-flash illusion task  and found positive correlation between individual alpha frequency (IAF) peak and the size of the temporal window of the illusion. Participants then performed the same task while receiving occipital transcranial alternating current stimulation (tACS), to modulate oscillatory activity  either at their IAF or at off-peak alpha frequencies (IAF±2 Hz). Compared to IAF tACS, IAF−2 Hz and IAF+2 Hz tACS, respectively, enlarged and shrunk the temporal window of illusion, suggesting that alpha oscillations might represent the temporal unit of visual processing that cyclically gates perception and the neurophysiological substrate promoting audio-visual interactions.
•Peak α frequency predicts temporal windows of the double-flash illusion•tACS tuned around α frequency causally modulates this illusory temporal window•Slower versus faster tACS α frequencies enlarged versus shrunk the illusory temporal window•α peak is the “fingerprint” driving crossmodal impact upon visual processing
Multisensory integration occurs within a critical temporal window. Cecere et al. discover the neurophysiological correlates of this phenomenon. Individual oscillatory frequency within the occipital α band causally determines the individual temporal profile of cross-sensory integration, setting the sensory pace of conscious perceptual experience.
Eight pigeons responded in a concurrent-chains procedure in which terminal-link schedules changed pseudorandomly across sessions. Pairs of terminal-link delays either summed to 15 s or to 45 s. Across sessions, the location of the shorter terminal link changed according to a pseudorandom binary sequence. On some terminal links, food was withheld to obtain start and stop times, measures of temporal control. Log initial-link response ratios stabilized within the first half of each session. Log response ratio was a monotonically-increasing but nonlinear function of programmed log terminal-link immediacy ratio. There was an effect of absolute terminal-link duration on log response ratio: For most subjects, preference for the relatively shorter terminal-link delay was stronger when absolute delays were long than when absolute delays were short. Polynomial regressions and model comparison showed that differences in degree of nonlinearity, not in sensitivity to log immediacy ratio, produced this effect. Temporal control of stop times was timescale invariant with scalar variability, but temporal control of start times was not consistent across subjects or terminal-link durations.
concurrent chains; terminal-link effect; rapid acquisition procedure; conditioned reinforcing value; temporal control; key peck; pigeons
The nature of the auditory processing deficit of disabled readers is still an unresolved issue. The quest for a fundamental, nonlinguistic, perceptual impairment has been dominated by the hypothesis that the difficulty lies in processing sequences of stimuli at presentation rates of tens of milliseconds. The present study examined this hypothesis using tasks that require processing of a wide range of stimulus time constants. About a third of the sampled population of disabled readers (classified as "poor auditory processors") had difficulties in most of the tasks tested: detection of frequency differences, detection of tones in narrowband noise, detection of amplitude modulation, detection of the direction of sound sources moving in virtual space, and perception of the lateralized position of tones based on their interaural phase differences. Nevertheless, across-channel integration was intact in these poor auditory processors since comodulation masking release was not reduced. Furthermore, phase locking was presumably intact since binaural masking level differences were normal. In a further examination of temporal processing, participants were asked to discriminate two tones at various intervals where the frequency difference was ten times each individual's frequency just noticeable difference (JND). Under these conditions, poor auditory processors showed no specific difficulty at brief intervals, contrary to predictions under a fast temporal processing deficit assumption. The complementary subgroup of disabled readers who were not poor auditory processors showed some difficulty in this condition when compared with their direct controls. However, they had no difficulty on auditory tasks such as amplitude modulation detection, which presumably taps processing of similar time scales. These two subgroups of disabled readers had similar reading performance but those with a generally poor auditory performance scored lower on some cognitive tests. Taken together, these results suggest that a large portion of disabled readers suffer from diverse difficulties in auditory processing. No parsimonious explanation based on current models of low-level auditory processing can account simultaneously for all these results, though increased within-channel noise is consistent with the majority of the deficits found in the subgroup of poorer auditory processors.
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.
The ability to determine the interval and duration of sensory events is fundamental to most forms of sensory processing, including speech and music perception. Recent experimental data support the notion that different mechanisms underlie temporal processing in the subsecond and suprasecond range. Here, we examine the predictions of one class of subsecond timing models: state-dependent networks. We establish that the interval between the comparison and the test interval, interstimulus interval (ISI), in a two-interval forced-choice discrimination task, alters the accuracy of interval discrimination but not the point of subjective equality—i.e. while timing was impaired, subjective time contraction or expansion was not observed. We also examined whether the deficit in temporal processing produced by short ISIs can be reduced by learning, and determined the generalization patterns. These results show that training subjects on a task using a short or long ISI produces dramatically different generalization patterns, suggesting different forms of perceptual learning are being engaged. Together, our results are consistent with the notion that timing in the range of hundreds of milliseconds is local as opposed to centralized, and that rapid stimulus presentation rates impair temporal discrimination. This interference is, however, decreased if the stimuli are presented to different sensory channels.
timing; interval discrimination; perceptual learning; temporal processing; generalization
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
To test whether atypical number development may affect other types of quantity processing, we investigated temporal discrimination in adults with developmental dyscalculia (DD). This also allowed us to test whether number and time may be sub-served by a common quantity system or decision mechanisms: if they do, both should be impaired in dyscalculia, but if number and time are distinct they should dissociate. Participants judged which of two successively presented horizontal lines was longer in duration, the first line being preceded by either a small or a large number prime (“1” or “9”) or by a neutral symbol (“#”), or in a third task participants decided which of two Arabic numbers (either “1,” “5,” “9”) lasted longer. Results showed that (i) DD’s temporal discriminability was normal as long as numbers were not part of the experimental design, even as task-irrelevant stimuli; however (ii) task-irrelevant numbers dramatically disrupted DD’s temporal discriminability the more their salience increased, though the actual magnitude of the numbers had no effect; in contrast (iii) controls’ time perception was robust to the presence of numbers but modulated by numerical quantity: therefore small number primes or numerical stimuli seemed to make durations appear shorter than veridical, but longer for larger numerical prime or numerical stimuli. This study is the first to show spared temporal discrimination – a dimension of continuous quantity – in a population with a congenital number impairment. Our data reinforce the idea of a partially shared quantity system across numerical and temporal dimensions, which supports both dissociations and interactions among dimensions; however, they suggest that impaired number in DD is unlikely to originate from systems initially dedicated to continuous quantity processing like time.
developmental dyscalculia; time; magnitude; numerosity; number cognition
Behavioural and neurophysiological studies in primates have increasingly shown the involvement of urgency signals during the temporal integration of sensory evidence in perceptual decision-making. Neuronal correlates of such signals have been found in the parietal cortex, and in separate studies, demonstrated attention-induced gain modulation of both excitatory and inhibitory neurons. Although previous computational models of decision-making have incorporated gain modulation, their abstract forms do not permit an understanding of the contribution of inhibitory gain modulation. Thus, the effects of co-modulating both excitatory and inhibitory neuronal gains on decision-making dynamics and behavioural performance remain unclear. In this work, we incorporate time-dependent co-modulation of the gains of both excitatory and inhibitory neurons into our previous biologically based decision circuit model. We base our computational study in the context of two classic motion-discrimination tasks performed in animals. Our model shows that by simultaneously increasing the gains of both excitatory and inhibitory neurons, a variety of the observed dynamic neuronal firing activities can be replicated. In particular, the model can exhibit winner-take-all decision-making behaviour with higher firing rates and within a significantly more robust model parameter range. It also exhibits short-tailed reaction time distributions even when operating near a dynamical bifurcation point. The model further shows that neuronal gain modulation can compensate for weaker recurrent excitation in a decision neural circuit, and support decision formation and storage. Higher neuronal gain is also suggested in the more cognitively demanding reaction time than in the fixed delay version of the task. Using the exact temporal delays from the animal experiments, fast recruitment of gain co-modulation is shown to maximize reward rate, with a timescale that is surprisingly near the experimentally fitted value. Our work provides insights into the simultaneous and rapid modulation of excitatory and inhibitory neuronal gains, which enables flexible, robust, and optimal decision-making.
Perceptual decision-making involves not only simple transformation of sensory information to a motor decision, but can also be modulated by high-level cognition. For example, the latter may include strategic allocation of limited attentional resources over time in a decision task to improve performance. At the neurophysiological level, there is evidence supporting attention-induced neuronal gain modulation of both excitatory and inhibitory cortical neurons. In the context of perceptual discrimination tasks performed by animals, we make use of a biologically inspired computational model of decision-making to understand the computational capabilities of such co-modulation of neuronal gains. We find that dynamic co-modulation of both excitatory and inhibitory neurons is important for flexible, and cognitively demanding decision-making while also enhancing robustness in the decision circuit's functions. Our model captures the neuronal activity and behavioural data in the animal experiments remarkably well. Decision performance in a reaction time task can be optimized, maximizing the rate of receiving reward by using fast gain recruitment. Our experimentally fitted timescale is near the optimal one, suggesting that the animals performed almost optimally. By providing both computational simulations and theoretical analyses, our computational model sheds light into the multiple functions of rapid co-modulation of neuronal gains during decision-making.
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.
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.
Experienced meditators typically report that they experience time slowing down in meditation practice as well as in everyday life. Conceptually this phenomenon may be understood through functional states of mindfulness, i.e., by attention regulation, body awareness, emotion regulation, and enhanced memory. However, hardly any systematic empirical work exists regarding the experience of time in meditators. In the current cross-sectional study, we investigated whether 42 experienced mindfulness meditation practitioners (with on average 10 years of experience) showed differences in the experience of time as compared to 42 controls without any meditation experience matched for age, sex, and education. The perception of time was assessed with a battery of psychophysical tasks assessing the accuracy of prospective time judgments in duration discrimination, duration reproduction, and time estimation in the milliseconds to minutes range as well with several psychometric instruments related to subjective time such as the Zimbardo Time Perspective Inventory, the Barratt Impulsivity Scale and the Freiburg Mindfulness Inventory. In addition, subjective time judgments on the current passage of time and retrospective time ranges were assessed. While subjective judgements of time were found to be significantly different between the two groups on several scales, no differences in duration estimates in the psychophysical tasks were detected. Regarding subjective time, mindfulness meditators experienced less time pressure, more time dilation, and a general slower passage of time. Moreover, they felt that the last week and the last month passed more slowly. Overall, although no intergroup differences in psychophysical tasks were detected, the reported findings demonstrate a close association between mindfulness meditation and the subjective feeling of the passage of time captured by psychometric instruments.
mindfulness meditation; time perception; passage of time; time perspective; impulsiveness