Timing Research Forum

The way we represent and perceive time has crucial implications for studying temporality in conscious experience. Contrasting positions posit that temporal information is separately abstracted out like any other perceptual property, or that time is represented through representations having temporal properties themselves. To add to this debate, we investigated alterations in felt time in conditions where only conscious visual experience is altered while a bistable figure remains physically unchanged. In this talk, I will discuss two studies that we have done in relation to answering this question. In study 1, we investigated whether perceptual switches in fixed intervals altered felt time. In three experiments we showed that a break in visual experience (via a perceptual switch) also leads to a break in felt time. In study 2, we are currently looking at figure-ground perception in ambigous displays. Here, in experiment 1 we show that differences in flicker frequencies on ambigous regions can induce figure-ground segregation. To see if a reverse complementarity exists for felt time, we ask participants to view ambigous regions as figure/ground and show that they have different temporal resolutions for the same region based on whether it is seen as figure or background. Overall, the two studies provide evidence for temporal mirroring and isomorphism in visual experience, arguing for a link between the timing of experience and time perception.

Quantifying the timing (duration and frequency) of brief visual events is vital to human perception, multisensory integration and action planning. For example, this allows us to follow and interact with the precise timing of speech and sports. Here we investigate how visual event timing is represented and transformed across the brain’s hierarchy: from sensory processing areas, through multisensory integration areas, to frontal action planning areas. We hypothesized that the dynamics of neural responses to sensory events in sensory processing areas allows derivation of event timing representations. This would allow higher-level processes such as multisensory integration and action planning to use sensory timing information, without the need for specialized central pacemakers or processes. Using 7T fMRI and neural model-based analyses, we found responses that monotonically increase in amplitude with visual event duration and frequency, becoming increasingly clear from primary visual cortex to lateral occipital visual field maps. Beginning in area MT/V5, we found a gradual transition from monotonic to tuned responses, with response amplitudes peaking at different event timings in different recording sites. While monotonic response components were limited to the retinotopic location of the visual stimulus, timing-tuned response components were independent of the recording sites' preferred visual field positions. These tuned responses formed a network of topographically organized timing maps in superior parietal, postcentral and frontal areas. From anterior to posterior timing maps, multiple events were increasingly integrated, response selectivity narrowed, and responses focused increasingly on the middle of the presented timing range. These results suggest that responses to event timing are transformed from the human brain’s sensory areas to the association cortices, with the event’s temporal properties being increasingly abstracted from the response dynamics and locations of early sensory processing. The resulting abstracted representation of event timing is then propagated through areas implicated in multisensory integration and action planning.

Neural representations of time are central to our understanding of the world around us. I review cognitive, neurophysiological and theoretical work that converges on three simple ideas. First, the time of past events is remembered via populations of neurons with a continuum of functional time constants. Second, these time constants evenly tile the log time axis. This results in a neural Weber-Fechner scale for time which can support behavioral Weber-Fechner laws and characteristic behavioral effects in memory experiments. Third, these populations appear as dual pairs---one type of population contains cells that change firing rate monotonically over time and a second type of population that has circumscribed temporal receptive fields. These ideas can be used to build artificial neural networks that have novel properties. Of particular interest, a convolutional neural network built using these principles can generalize to arbitrary rescaling of its inputs. That is, after learning to perform a classification task on a time series presented at one speed, it successfully classifies stimuli presented slowed down or sped up. This result illustrates the point that this confluence of ideas originating in cognitive psychology and measured in the mammalian brain could have wide-reaching impacts on AI research.

Playing action video games involves both explicit (conscious) and implicit (non-conscious) expectations of timed events, such as the appearance of foes. While studies revealed that explicit attention skills are improved in action video game players (VGPs), their implicit skills remained untested. To this end, we investigated explicit and implicit temporal processing in VGPs and non-VGPs (control participants). In our variable foreperiod task, participants were immersed in a virtual reality and instructed to respond to a visual target appearing at variable delays after a cue. I will present behavioral, oculomotor and EEG data and discuss possible markers of the implicit passage of time and explicit temporal attention processing. All evidence indicates that VGPs have enhanced implicit skills to track the passage of time, which does not require conscious attention. Thus, action video game play may improve a temporal processing found altered in psychopathologies, such as schizophrenia. Could digital (game-based) interventions help remediate temporal processing deficits in psychiatric populations?

Human movement disorders and pharmacological studies have long suggested molecular dopamine modulates the pace of the internal clock. But how does the endogenous dopaminergic system influence the timing of our movements? We examined the relationship between dopaminergic signaling and the timing of reward-related, self-timed movements in mice. Animals were trained to initiate licking after a self-timed interval following a start cue; reward was delivered if the animal’s first lick fell within a rewarded window (3.3-7 s). The first-lick timing distributions exhibited the scalar property, and we leveraged the considerable variability in these distributions to determine how the activity of the dopaminergic system related to the animals’ timing. Surprisingly, dopaminergic signals ramped-up over seconds between the start-timing cue and the self-timed movement, with variable dynamics that predicted the movement/reward time, even on single trials. Steeply rising signals preceded early initiation, whereas slowly rising signals preceded later initiation. Higher baseline signals also predicted earlier self-timed movement. Optogenetic activation of dopamine neurons during self-timing did not trigger immediate movements, but rather caused systematic early-shifting of the timing distribution, whereas inhibition caused late-shifting, as if dopaminergic manipulation modulated the moment-to-moment probability of unleashing the planned movement. Consistent with this view, the dynamics of the endogenous dopaminergic signals quantitatively predicted the moment-by-moment probability of movement initiation. We conclude that ramping dopaminergic signals, potentially encoding dynamic reward expectation, probabilistically modulate the moment-by-moment decision of when to move. (Based on work from Hamilos et al., eLife, 2021).

Estimating intervals is essential for adaptive behavior and decision-making. Although several theoretical models have been proposed to explain how the brain keeps track of time, there is still no evidence toward a single one. It is often hard to compare different models due to their overlap in behavioral predictions. For this reason, several studies have looked for neural signatures of temporal processing using methods such as electrophysiological recordings (EEG). However, for this strategy to work, it is essential to have consistent EEG markers of temporal processing. In this talk, I'll present results from several studies investigating how temporal information is encoded in the EEG signal. Specifically, across different experiments, we have investigated whether different neural signatures of temporal processing (such as the CNV, the LPC, and early ERPs): 1. Depend on the task to be executed (whether or not it is a temporal task or different types of temporal tasks); 2. Are encoding the physical duration of an interval or how much longer/shorter an interval is relative to a reference. Lastly, I will discuss how these results are consistent with recent proposals that approximate temporal processing with decisional models.

The theory of predictive processing posits that the brain computes expectations to process information predictively. Empirical evidence in support of this theory, however, is scarce and largely limited to sensory areas. Here, we report a precise and adaptive mechanism in the frontal cortex of non-human primates consistent with predictive processing of temporal events. We found that the speed of neural dynamics is precisely adjusted according to the average time of an expected stimulus. This speed adjustment, in turn, enables neurons to encode stimuli in terms of deviations from expectation. This lawful relationship was evident across multiple experiments and held true during learning: when temporal statistics underwent covert changes, neural responses underwent predictable changes that reflected the new mean. Together, these results highlight a precise mathematical relationship between temporal statistics in the environment and neural activity in the frontal cortex that may serve as a mechanism for predictive temporal processing.

Cognitive models of timing often include a pacemaker analogue whose ticks are accumulated to form an internal representation of time, and a threshold that determines when a target duration has elapsed. However, clear EEG manifestations of these abstract components have not yet been identified. We measured the EEG of subjects while they performed a temporal bisection task in which they were requested to categorize visual stimuli as short or long in duration. We report an ERP component whose amplitude depends monotonically on the stimulus duration. The relation of the ERP amplitude and stimulus duration can be captured by a simple model, adapted from a known drift-diffusion model for time perception. It includes a noisy accumulator that starts with the stimulus onset and a threshold. If the threshold is reached during stimulus presentation, the stimulus is categorized as "long", otherwise the stimulus is categorized as "short". At the stimulus offset, a response proportional to the distance to the threshold is emitted. This simple model has two parameters that fit both the behavior and ERP amplitudes recorded in the task. Two subsequent experiments replicate and extend this finding to another modality (touch) as well as to different time ranges (subsecond and suprasecond), establishing the described ERP component as a useful handle on the cognitive processes involved in temporal decisions.

Error monitoring refers to the ability to monitor one's own task performance without explicit feedback. This ability is studied typically in two-alternative forced-choice (2AFC) paradigms. Recent research showed that humans can also keep track of the magnitude and direction of errors in different magnitude domains (e.g., numerosity, duration, length). Based on the evidence that suggests a shared mechanism for magnitude representations, we aimed to investigate whether metric error monitoring ability is commonly governed across different magnitude domains. Participants reproduced/estimated temporal, numerical, and spatial magnitudes after which they rated their confidence regarding first order task performance and judged the direction of their reproduction/estimation errors. Participants were also tested in a 2AFC perceptual decision task and provided confidence ratings regarding their decisions. Results showed that variability in reproductions/estimations and metric error monitoring ability, as measured by combining confidence and error direction judgements, were positively related across temporal, spatial, and numerical domains. Metacognitive sensitivity in these metric domains was also positively associated with each other but not with metacognitive sensitivity in the 2AFC perceptual decision task. In conclusion, the current findings point at a general metric error monitoring ability that is shared across different metric domains with limited generalizability to perceptual decision-making.

Interpretation of interval timing data generated from animal models is complicated by ostensible motivational effects which arise from the delay-to-reward imposed by interval timing tasks, as well as overlap between timed and non-timed responses. These factors become increasingly prevalent at longer intervals. To address these concerns, two adjustments to long interval timing tasks are proposed. First, subjects should be afforded with reinforced non-timing behaviors concurrent with timing. Second, subjects should initiate the onset of timed stimuli. Under these conditions, interference by extraneous behavior would be detected in the rate of concurrent non- timing behaviors, and changes in motivation would be detected in the rate at which timed stimuli are initiated. In a task with these characteristics, rats initiated a concurrent fixed-interval (FI) random-ratio (RR) schedule of reinforcement. This design facilitated response-initiated timing behavior, even at increasingly long delays. Pre-feeding manipulations revealed an effect on the number of initiated trials, but not on the timing peak function.

The subdivision benefit refers to the positive effect of subdividing a beat on sensorimotor synchronization. We recorded electroencephalograms of musicians and non-musicians to study how they listened or finger-tapped to a beat, subdivided into four distinct subdivisions. Musicians showed more consistent tapping responses than non-musicians, and enhanced neural entrainment during the tapping task than in the listening task. In both groups, there was a neural enhancement of the beat frequency and its first harmonic (related to duplets) after listening to the four subdivisions. Furthermore, non-musicians tapped more consistently to the beat of duplets than other subdivisions. Altogether, this suggests a neural and behavioral advantage for binary subdivisions, that can be modulated with formal training in music.

Over 60 years of research has established that medial temporal lobe structures, including the hippocampus and entorhinal cortex, are necessary for the formation of episodic memories (i.e. memories of specific personal events that occur in spatial and temporal context). While prior work to establish the neural mechanisms underlying episodic memory has largely focused on questions related spatial context, recently we have begun to investigate how these brain structures could be involved in encoding aspects of temporal context. In particular, we have focused on how medial entorhinal cortex, a structure well known for its role in spatial memory, may also be involved in encoding interval time. To answer this question we have developed an instrumental paradigm for head-fixed mice that requires both immobile interval timing and locomotion-dependent navigation behavior. By combining this behavioral paradigm with large-scale cellular resolution functional imaging and optogenetic-mediated inactivation, our results suggest that MEC is required for learning of interval timing behavior and that interval timing could be mediated through regular, sequential neural activity of a distinct subpopulation of neurons in MEC that encode elapsed time during periods of immobility (Heys and Dombeck, 2018; Heys et al, 2020; Issa et al., 2020). In this talk, I will discuss these findings and discuss our on-going work to investigate the principles underlying the role of medial temporal lobe structures in timing behavior and episodic memory.

fMRI results have shown that the supplementary motor area (SMA) and the basal ganglia, most often discussed in their roles in generating action, are engaged by beat-based timing even in the absence of movement. Some have argued that the motor system is “recruited” by beat-based timing tasks due to the presence of motor-like timescales, but a deeper understanding of the roles of these motor structures is lacking. Reviewing a body of motor neurophysiology literature and drawing on the “active inference” framework, I argue that we can see the motor and timing functions of these brain areas as examples of dynamic sub-second prediction informed by sensory event timing. I hypothesize that in both cases, sub-second dynamics in SMA predict the progress of a temporal process outside the brain, and direct pathway activation in basal ganglia selects temporal and sensory predictions for the upcoming interval -- the only difference is that in motor processes, these predictions are made manifest through motor effectors. If we can unify our understanding of beat-based timing and motor control, we can draw on the substantial motor neuroscience literature to make conceptual leaps forward in the study of predictive timing and musical rhythm.

Medium-spiny neurons (MSNs) in the striatum are required for interval timing, or the estimation of the time over several seconds via a motor response. We and others have shown that striatal MSNs can encode the duration of temporal intervals via time-dependent ramping activity, progressive monotonic changes in firing rate preceding behaviorally salient points in time. Here, we investigated how timing-related activity within striatal ensembles changes with experience. We leveraged a rodent-optimized interval timing task in which mice ‘switch’ response ports after an amount of time has passed without reward. We report three main results. First, we found that the proportion of MSNs exhibiting time-dependent modulations of firing rate increased after 10 days of task overtraining. Second, temporal decoding by MSN ensembles increased with experience and was largely driven by time-related ramping activity. Finally, we found that time-related ramping activity generalized across both correct and error trials. These results enhance our understanding of striatal temporal processing by demonstrating that time-dependent activity within MSN ensembles evolves with experience and is dissociable from motor- and reward-related processes.

My talk will discuss the use of some of these four, simple Matlab functions to simulate models of timing, and to fit models to empirical data. Feel free to examine the code and the relatively brief book chapter that explains the code before the talk if you would like to learn more about computational/mathematical modeling.

Interval timing is a fundamental component action, and is susceptible to motor-related temporal distortions. Previous studies have shown that movement biases temporal estimates, but have primarily considered self-modulated movement only. However, real-world encounters often include situations in which movement is restricted or perturbed by environmental factors. In the following experiments, we introduced viscous movement environments to externally modulate movement and investigated the resulting effects on temporal perception. In two separate tasks, participants timed auditory intervals while moving a robotic arm that randomly applied four levels of viscosity. Results demonstrated that higher viscosity led to shorter perceived durations. Using a drift-diffusion model and a Bayesian observer model, we confirmed these biasing effects arose from perceptual mechanisms, instead of biases in decision making. These findings suggest that environmental perturbations are an important factor in movement-related temporal distortions, and enhance the current understanding of the interactions of motor activity and cognitive processes. https://www.biorxiv.org/content/10.1101/2020.10.26.355396v1

In daily life, we consistently make decisions in pursuit of some goal. Many decisions are informed by multiple sources of information. Unfortunately, these sources often provide ambiguous information about what course of action to take. Therefore, determining how the brain integrates information to resolve this ambiguity is key to understanding the neural mechanisms of decision-making. In the domain of time, this topic can be studied by training subjects to predict when a future event will occur based on distinct cues (e.g., tone, light, etc.). If multiple cues are presented simultaneously and their cue-to-event intervals differ (e.g., tone-10s + light-30s), subjects will often expect the event to occur at the average of their intervals. This ‘temporal averaging’ effect is presumably how the timing system resolves ambiguous time-information. The neural mechanisms of temporal averaging are currently unclear. Here, we will propose how temporal averaging could emerge in cortical circuits using a simple modification of a ‘drift-diffusion’ model of timing.

Global responses to the Covid-19 pandemic have resulted in various forms of “lockdown” being imposed on citizens. These lockdown measures have resulted in significant changes to all aspects of daily life for all those who live under them. Lockdowns have however, also provided a unique opportunity for psychologists to examine how changes in the structure of daily life influence our experience of time. This talk will review recent research examining the impact on covid-19 on real-world time experience. It will look to discuss whether the factors which influence “normal” time experience also influenced time experience during lockdown. Finally, it will try to highlight some potential future directions for enhancing our understanding of real-life time distortion.