Motor activity improves temporal expectancy

The Motor of Time: Coupling Action to Temporally Predictable Events Heightens Perception

Timing and motor function share neural circuits and dynamics, which underpin their close and synergistic relationship. For instance, the temporal predictability of a sensory event optimizes motor responses to that event. Knowing when an event is likely to occur lowers response thresholds, leading to faster and more efficient motor behavior though in situations of response conflict can induce impulsive and inappropriate responding. In turn, through a process of active sensing, coupling action to temporally predictable sensory input enhances perceptual processing. Action not only hones perception of the event's onset or duration, but also boosts sensory processing of its non-temporal features such as pitch or shape. The effects of temporal predictability on motor behavior and sensory processing involve motor and left parietal cortices and are mediated by changes in delta and beta oscillations in motor areas of the brain.

How movements shape the perception of time

In order to keep up with a changing environment, mobile organisms must be capable of deciding both where and when to move. This precision necessitates a strong sense of time, as otherwise we would fail in many of our movement goals. Yet, despite this intrinsic link, only recently have researchers begun to understand how these two features interact. Primarily, two effects have been observed: movements can bias time estimates, but they can also make them more precise. Here we review this literature and propose that both effects can be explained by a Bayesian cue combination framework, in which movement itself affords the most precise representation of time, which can influence perception in either feedforward or active sensing modes.

The internal representation of temporal orienting: A temporal pulse-accumulation and attentional-gating-based account

Timing can be processed explicitly or implicitly. Temporal orienting is a typical implicit timing through which we can anticipate and prepare an optimized response to forthcoming events. It is, however, not yet clear whether mechanisms such as temporal-pulse accumulation and attentional gating (more attention, more accumulated temporal pulses) underly the internal representations of temporal orienting, as in explicit timing. To clarify this, a dual-task paradigm, consisting of a temporal orienting and an interference task, was adopted. Consistent with the temporal-pulse-accumulation and attentional-gating model, reaction times to the target detection of temporal orienting increased as the interference stimuli were temporally closer to the target, i.e., a location effect for temporal orienting. This effect is likely due to attention being diverted away from temporal orienting to monitor the occurrence of the interference stimuli for a longer time, resulting in greater temporal pulse loss and less accurate temporal orienting for conditions with later interference stimuli. The temporal-pulse-accumulation aspect in temporal orienting received further support by taking an explicit duration reproduction (containing a second temporal-pulse accumulation) as the interference task. On the one hand, temporal orienting became less accurate with increased temporal-pulse-accumulation overlaps between the dual tasks; on the other hand, two-way (one for temporal orienting and the other for duration reproduction), rather than one-way, location effects were observed, implying processing conflicts between the two temporal-pulse accumulations. Taken together, these results suggest that implicit and explicit timing may share common mechanisms upon internal temporal representations.

Having your cake and eating it: Faster responses with reduced muscular activation while learning a temporal interval

We examined how motor responses to a stimulus evolve as individuals learn to predict when a stimulus will appear, by comparing responses to a regular versus irregular stimulus train. The study was conducted with two groups of adults - one responded to the regular appearance of a visual stimulus every 3 s (R group) and the second responded to the irregular presentation of the same stimulus (IR group) at intervals varying between 2 and 4 s. Participants responded to the appearance of the stimulus by bending over to press a button that was slightly out of reach. This whole body reach requires muscular activation at the ankles. Over the course of 50 consecutive responses, the response times in the R group were found to decrease more than those for participants in the IR group. The electromyographs (EMGs) of two ankle antagonist muscles, the anterior tibialis and soleus were also modified as participants progressively learnt the temporal regularity of a sequence. Tibialis onset times for the R group were found to decrease faster. A less predictable observation was the faster reduction in post stimulus activation of the tibialis muscle for the R group. Soleus muscle deactivation is an indicator of movement preparation. EMG integrals for this muscle a little before stimulus onset showed a trend for greater decrease in the R group. In summary, our study shows that temporal expectations over repeated stimulus presentation permit the dynamic optimization of motor activity with progressively faster response times, muscle activation onset times and lower muscle activation amplitudes.

The beneficial effect of synchronized action on motor and perceptual timing in children

We examined the role of action in motor and perceptual timing across development. Adults and children aged 5 or 8 years old learned the duration of a rhythmic interval with or without concurrent action. We compared the effects of sensorimotor versus visual learning on subsequent timing behaviour in three different tasks: rhythm reproduction (Experiment 1), rhythm discrimination (Experiment 2) and interval discrimination (Experiment 3). Sensorimotor learning consisted of sensorimotor synchronization (tapping) to an isochronous visual rhythmic stimulus (ISI = 800 ms), whereas visual learning consisted of simply observing this rhythmic stimulus. Results confirmed our hypothesis that synchronized action during learning systematically benefitted subsequent timing performance, particularly for younger children. Action-related improvements in accuracy were observed for both motor and perceptual timing in 5 years olds and for perceptual timing in the two older age groups. Benefits on perceptual timing tasks indicate that action shapes the cognitive representation of interval duration. Moreover, correlations with neuropsychological scores indicated that while timing performance in the visual learning condition depended on motor and memory capacity, sensorimotor learning facilitated an accurate representation of time independently of individual differences in motor and memory skill. Overall, our findings support the idea that action helps children to construct an independent and flexible representation of time, which leads to coupled sensorimotor coding for action and time.

Embodiment and the origin of interval timing: kinematic and electromyographic data

Recent evidence suggests that interval timing (the judgment of durations lasting from approximately 500 ms. to a few minutes) is closely coupled to the action control system. We used surface electromyography (EMG) and motion capture technology to explore the emergence of this coupling in 4-, 6-, and 8-month-olds. We engaged infants in an active and socially relevant arm-raising task with seven cycles and response period. In one condition, cycles were slow (every 4 s); in another, they were fast (every 2 s). In the slow condition, we found evidence of time-locked sub-threshold EMG activity even in the absence of any observed overt motor responses at all three ages. This study shows that EMGs can be a more sensitive measure of interval timing in early development than overt behavior.

Neural Microstates Govern Perception of Auditory Input without Rhythmic Structure

Human perception fluctuates with the phase of neural oscillations in the presence of environmental rhythmic structure by which neural oscillations become entrained. However, in the absence of predictability afforded by rhythmic structure, we hypothesize that the neural dynamical states associated with optimal psychophysical performance are more complex than what has been described previously for rhythmic stimuli. The current electroencephalography study characterized the brain dynamics associated with optimal detection of gaps embedded in narrow-band acoustic noise stimuli lacking low-frequency rhythmic structure. Optimal gap detection was associated with three spectrotemporally distinct delta-governed neural microstates. Individual microstates were characterized by unique instantaneous combinations of neural phase in the delta, theta, and alpha frequency bands. Critically, gap detection was not predictable from local fluctuations in stimulus acoustics. The current results suggest that, in the absence of rhythmic structure to entrain neural oscillations, good performance hinges on complex neural states that vary from moment to moment. Significance statement: Our ability to hear faint sounds fluctuates together with slow brain activity that synchronizes with environmental rhythms. However, it is so far not known how brain activity at different time scales might interact to influence perception when there is no rhythm with which brain activity can synchronize. Here, we used electroencephalography to measure brain activity while participants listened for short silences that interrupted ongoing noise. We examined brain activity in three different frequency bands: delta, theta, and alpha. Participants' ability to detect gaps depended on different numbers of frequency bands--sometimes one, sometimes two, and sometimes three--at different times. Changes in the number of frequency bands that predict perception are a hallmark of a complex neural system.