Sensorimotor neural dynamics during isochronous tapping in the medial premotor cortex of the macaque

Perception of temporal structure in speech is influenced by body movement and individual beat perception ability

The subjective experience of time flow in speech deviates from the sound acoustics in substantial ways. The present study focuses on the perceptual tendency to regularize time intervals found in speech but not in other types of sounds with a similar temporal structure. We investigate to what extent individual beat perception ability is responsible for perceptual regularization and if the effect can be eliminated through the involvement of body movement during listening. Participants performed a musical beat perception task and compared spoken sentences to their drumbeat-based versions either after passive listening or after listening and moving along with the beat of the sentences. The results show that the interval regularization prevails in listeners with a low beat perception ability performing a passive listening task and is eliminated in an active listening task involving body movement. Body movement also helped to promote a veridical percept of temporal structure in speech at the group level. We suggest that body movement engages an internal timekeeping mechanism, promoting the fidelity of auditory encoding even in sounds of high temporal complexity and irregularity such as natural speech.

Unified control of temporal and spatial scales of sensorimotor behavior through neuromodulation of short-term synaptic plasticity

Neuromodulators have been shown to alter the temporal profile of short-term synaptic plasticity (STP); however, the computational function of this neuromodulation remains unexplored. Here, we propose that the neuromodulation of STP provides a general mechanism to scale neural dynamics and motor outputs in time and space. We trained recurrent neural networks that incorporated STP to produce complex motor trajectories-handwritten digits-with different temporal (speed) and spatial (size) scales. Neuromodulation of STP produced temporal and spatial scaling of the learned dynamics and enhanced temporal or spatial generalization compared to standard training of the synaptic weights in the absence of STP. The model also accounted for the results of two experimental studies involving flexible sensorimotor timing. Neuromodulation of STP provides a unified and biologically plausible mechanism to control the temporal and spatial scales of neural dynamics and sensorimotor behaviors.

Common neural mechanisms supporting time judgements in humans and monkeys

There has been an increasing interest in identifying the biological underpinnings of human time perception, for which purpose research in non-human primates (NHP) is common. Although previous work, based on behaviour, suggests that similar mechanisms support time perception across species, the neural correlates of time estimation in humans and NHP have not been directly compared. In this study, we assess whether brain evoked responses during a time categorization task are similar across species. Specifically, we assess putative differences in post-interval evoked potentials as a function of perceived duration in human EEG (N = 24) and local field potential (LFP) and spike recordings in pre-supplementary motor area (pre-SMA) of one monkey. Event-related potentials (ERPs) differed significantly after the presentation of the temporal interval between "short" and "long" perceived durations in both species, even when the objective duration of the stimuli was the same. Interestingly, the polarity of the reported ERPs was reversed for incorrect trials (i.e., the ERP of a "long" stimulus looked like the ERP of a "short" stimulus when a time categorization error was made). Hence, our results show that post-interval potentials reflect the perceived (rather than the objective) duration of the presented time interval in both NHP and humans. In addition, firing rates in monkey's pre-SMA also differed significantly between short and long perceived durations and were reversed in incorrect trials. Together, our results show that common neural mechanisms support time categorization in NHP and humans, thereby suggesting that NHP are a good model for investigating human time perception.

thebeat: A Python package for working with rhythms and other temporal sequences

thebeat is a Python package for working with temporal sequences and rhythms in the behavioral and cognitive sciences, as well as in bioacoustics. It provides functionality for creating experimental stimuli, and for visualizing and analyzing temporal data. Sequences, sounds, and experimental trials can be generated using single lines of code. thebeat contains functions for calculating common rhythmic measures, such as interval ratios, and for producing plots, such as circular histograms. thebeat saves researchers time when creating experiments, and provides the first steps in collecting widely accepted methods for use in timing research. thebeat is an open-source, on-going, and collaborative project, and can be extended for use in specialized subfields. thebeat integrates easily with the existing Python ecosystem, allowing one to combine our tested code with custom-made scripts. The package was specifically designed to be useful for both skilled and novice programmers. thebeat provides a foundation for working with temporal sequences onto which additional functionality can be built. This combination of specificity and plasticity should facilitate research in multiple research contexts and fields of study.

A Second Introduction to the Neurobiology of Interval Timing

Time is a critical variable that organisms must be able to measure in order to survive in a constantly changing environment. Initially, this paper describes the myriad of contexts where time is estimated or predicted and suggests that timing is not a single process and probably depends on a set of different neural mechanisms. Consistent with this hypothesis, the explosion of neurophysiological and imaging studies in the last 10 years suggests that different brain circuits and neural mechanisms are involved in the ability to tell and use time to control behavior across contexts. Then, we develop a conceptual framework that defines time as a family of different phenomena and propose a taxonomy with sensory, perceptual, motor, and sensorimotor timing as the pillars of temporal processing in the range of hundreds of milliseconds.

Neural Sequences and the Encoding of Time

Converging experimental and computational evidence indicate that on the scale of seconds the brain encodes time through changing patterns of neural activity. Experimentally, two general forms of neural dynamic regimes that can encode time have been observed: neural population clocks and ramping activity. Neural population clocks provide a high-dimensional code to generate complex spatiotemporal output patterns, in which each neuron exhibits a nonlinear temporal profile. A prototypical example of neural population clocks are neural sequences, which have been observed across species, brain areas, and behavioral paradigms. Additionally, neural sequences emerge in artificial neural networks trained to solve time-dependent tasks. Here, we examine the role of neural sequences in the encoding of time, and how they may emerge in a biologically plausible manner. We conclude that neural sequences may represent a canonical computational regime to perform temporal computations.

Diverse Time Encoding Strategies Within the Medial Premotor Areas of the Primate

The measurement of time in the subsecond scale is critical for many sophisticated behaviors, yet its neural underpinnings are largely unknown. Recent neurophysiological experiments from our laboratory have shown that the neural activity in the medial premotor areas (MPC) of macaques can represent different aspects of temporal processing. During single interval categorization, we found that preSMA encodes a subjective category limit by reaching a peak of activity at a time that divides the set of test intervals into short and long. We also observed neural signals associated with the category selected by the subjects and the reward outcomes of the perceptual decision. On the other hand, we have studied the behavioral and neurophysiological basis of rhythmic timing. First, we have shown in different tapping tasks that macaques are able to produce predictively and accurately intervals that are cued by auditory or visual metronomes or when intervals are produced internally without sensory guidance. In addition, we found that the rhythmic timing mechanism in MPC is governed by different layers of neural clocks. Next, the instantaneous activity of single cells shows ramping activity that encodes the elapsed or remaining time for a tapping movement. In addition, we found MPC neurons that build neural sequences, forming dynamic patterns of activation that flexibly cover all the produced interval depending on the tapping tempo. This rhythmic neural clock resets on every interval providing an internal representation of pulse. Furthermore, the MPC cells show mixed selectivity, encoding not only elapsed time, but also the tempo of the tapping and the serial order element in the rhythmic sequence. Hence, MPC can map different task parameters, including the passage of time, using different cell populations. Finally, the projection of the time varying activity of MPC hundreds of cells into a low dimensional state space showed circular neural trajectories whose geometry represented the internal pulse and the tapping tempo. Overall, these findings support the notion that MPC is part of the core timing mechanism for both single interval and rhythmic timing, using neural clocks with different encoding principles, probably to flexibly encode and mix the timing representation with other task parameters.

Cortico-spinal modularity in the parieto-frontal system: A new perspective on action control

Classical neurophysiology suggests that the motor cortex (MI) has a unique role in action control. In contrast, this review presents evidence for multiple parieto-frontal spinal command modules that can bypass MI. Five observations support this modular perspective: (i) the statistics of cortical connectivity demonstrate functionally-related clusters of cortical areas, defining functional modules in the premotor, cingulate, and parietal cortices; (ii) different corticospinal pathways originate from the above areas, each with a distinct range of conduction velocities; (iii) the activation time of each module varies depending on task, and different modules can be activated simultaneously; (iv) a modular architecture with direct motor output is faster and less metabolically expensive than an architecture that relies on MI, given the slow connections between MI and other cortical areas; (v) lesions of the areas composing parieto-frontal modules have different effects from lesions of MI. Here we provide examples of six cortico-spinal modules and functions they subserve: module 1) arm reaching, tool use and object construction; module 2) spatial navigation and locomotion; module 3) grasping and observation of hand and mouth actions; module 4) action initiation, motor sequences, time encoding; module 5) conditional motor association and learning, action plan switching and action inhibition; module 6) planning defensive actions. These modules can serve as a library of tools to be recombined when faced with novel tasks, and MI might serve as a recombinatory hub. In conclusion, the availability of locally-stored information and multiple outflow paths supports the physiological plausibility of the proposed modular perspective.

Amodal population clock in the primate medial premotor system for rhythmic tapping

The neural substrate for beat extraction and response entrainment to rhythms is not fully understood. Here we analyze the activity of medial premotor neurons in monkeys performing isochronous tapping guided by brief flashing stimuli or auditory tones. The population dynamics shared the following properties across modalities: the circular dynamics of the neural trajectories form a regenerating loop for every produced interval; the trajectories converge in similar state space at tapping times resetting the clock; and the tempo of the synchronized tapping is encoded in the trajectories by a combination of amplitude modulation and temporal scaling. Notably, the modality induces displacement in the neural trajectories in the auditory and visual subspaces without greatly altering the time-keeping mechanism. These results suggest that the interaction between the medial premotor cortex's amodal internal representation of pulse and a modality-specific external input generates a neural rhythmic clock whose dynamics govern rhythmic tapping execution across senses.

Rhythmic tapping to a moving beat motion kinematics overrules natural gravity

Beat induction is the cognitive ability that allows humans to listen to a regular pulse in music and move in synchrony with it. Although auditory rhythmic cues induce more consistent synchronization than flashing visual metronomes, this auditory-visual asymmetry can be canceled by visual moving stimuli. Here, we investigated whether the naturalness of visual motion or its kinematics could provide a synchronization advantage over flashing metronomes. Subjects were asked to tap in sync with visual metronomes defined by vertically accelerating/decelerating motion, either congruent or not with natural gravity; horizontally accelerating/decelerating motion; or flashing stimuli. We found that motion kinematics was the predominant factor determining rhythm synchronization, as accelerating moving metronomes in any cardinal direction produced more precise and predictive tapping than decelerating or flashing conditions. Our results support the notion that accelerating visual metronomes convey a strong sense of beat, as seen in the cueing movements of an orchestra director.

Sex differences in vocal learning ability in songbirds are linked with differences in flexible rhythm pattern perception

Humans readily recognize familiar rhythmic patterns, such as isochrony (equal timing between events) across a wide range of rates. This reflects a facility with perceiving the relative timing of events, not just absolute interval durations. Several lines of evidence suggest this ability is supported by precise temporal predictions arising from forebrain auditory-motor interactions. We have shown previously that male zebra finches, Taeniopygia guttata, which possess specialized auditory-motor networks and communicate with rhythmically patterned sequences, share our ability to flexibly recognize isochrony across rates. To test the hypothesis that flexible rhythm pattern perception is linked to vocal learning, we ask whether female zebra finches, which do not learn to sing, can also recognize global temporal patterns. We find that females can flexibly recognize isochrony across a wide range of rates but perform slightly worse than males on average. These findings are consistent with recent work showing that while females have reduced forebrain song regions, the overall network connectivity of vocal premotor regions is similar to males and may support predictions of upcoming events. Comparative studies of male and female songbirds thus offer an opportunity to study how individual differences in auditory-motor connectivity influence perception of relative timing, a hallmark of human music perception.

Latencies of click-evoked auditory responses in a harbor porpoise exceed the time interval between subsequent echolocation clicks

Most auditory evoked potential (AEP) studies in echolocating toothed whales measure neural responses to outgoing clicks and returning echoes using short-latency auditory brainstem responses (ABRs) arising a few ms after acoustic stimuli. However, little is known about longer-latency cortical AEPs despite their relevance for understanding echo processing and auditory stream segregation. Here, we used a non-invasive AEP setup with low click repetition rates on a trained harbor porpoise to test the long-standing hypothesis that echo information from distant targets is completely processed before the next click is emitted. We reject this hypothesis by finding reliable click-related AEP peaks with latencies of 90 and 160 ms, which are longer than 99% of click intervals used by echolocating porpoises, demonstrating that some higher-order echo processing continues well after the next click emission even during slow clicking. We propose that some of the echo information, such as range to evasive prey, is used to guide vocal-motor responses within 50-100 ms, but that information used for discrimination and auditory scene analysis is processed more slowly, integrating information over many click-echo pairs. We conclude by showing theoretically that the identified long-latency AEPs may enable hearing sensitivity measurements at frequencies ten times lower than current ABR methods.

The neural bases for timing of durations

Durations are defined by a beginning and an end, and a major distinction is drawn between durations that start in the present and end in the future ('prospective timing') and durations that start in the past and end either in the past or the present ('retrospective timing'). Different psychological processes are thought to be engaged in each of these cases. The former is thought to engage a clock-like mechanism that accurately tracks the continuing passage of time, whereas the latter is thought to engage a reconstructive process that utilizes both temporal and non-temporal information from the memory of past events. We propose that, from a biological perspective, these two forms of duration 'estimation' are supported by computational processes that are both reliant on population state dynamics but are nevertheless distinct. Prospective timing is effectively carried out in a single step where the ongoing dynamics of population activity directly serve as the computation of duration, whereas retrospective timing is carried out in two steps: the initial generation of population state dynamics through the process of event segmentation and the subsequent computation of duration utilizing the memory of those dynamics.

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

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

Encoding time in neural dynamic regimes with distinct computational tradeoffs

Converging evidence suggests the brain encodes time in dynamic patterns of neural activity, including neural sequences, ramping activity, and complex dynamics. Most temporal tasks, however, require more than just encoding time, and can have distinct computational requirements including the need to exhibit temporal scaling, generalize to novel contexts, or robustness to noise. It is not known how neural circuits can encode time and satisfy distinct computational requirements, nor is it known whether similar patterns of neural activity at the population level can exhibit dramatically different computational or generalization properties. To begin to answer these questions, we trained RNNs on two timing tasks based on behavioral studies. The tasks had different input structures but required producing identically timed output patterns. Using a novel framework we quantified whether RNNs encoded two intervals using either of three different timing strategies: scaling, absolute, or stimulus-specific dynamics. We found that similar neural dynamic patterns at the level of single intervals, could exhibit fundamentally different properties, including, generalization, the connectivity structure of the trained networks, and the contribution of excitatory and inhibitory neurons. Critically, depending on the task structure RNNs were better suited for generalization or robustness to noise. Further analysis revealed different connection patterns underlying the different regimes. Our results predict that apparently similar neural dynamic patterns at the population level (e.g., neural sequences) can exhibit fundamentally different computational properties in regards to their ability to generalize to novel stimuli and their robustness to noise—and that these differences are associated with differences in network connectivity and distinct contributions of excitatory and inhibitory neurons. We also predict that the task structure used in different experimental studies accounts for some of the experimentally observed variability in how networks encode time.

The ability to tell time and anticipate when external events will occur are among the most fundamental computations the brain performs. Converging evidence suggests the brain encodes time through changing patterns of neural activity. Different temporal tasks, however, have distinct computational requirements, such as the need to flexibly scale temporal patterns or generalize to novel inputs. To understand how networks can encode time and satisfy different computational requirements we trained recurrent neural networks (RNNs) on two timing tasks that have previously been used in behavioral studies. Both tasks required producing identically timed output patterns. Using a novel framework to quantify how networks encode different intervals, we found that similar patterns of neural activity—neural sequences—were associated with fundamentally different underlying mechanisms, including the connectivity patterns of the RNNs. Critically, depending on the task the RNNs were trained on, they were better suited for generalization or robustness to noise. Our results predict that similar patterns of neural activity can be produced by distinct RNN configurations, which in turn have fundamentally different computational tradeoffs. Our results also predict that differences in task structure account for some of the experimentally observed variability in how networks encode time.

Mapping between sound, brain and behaviour: four-level framework for understanding rhythm processing in humans and non-human primates

Humans perceive and spontaneously move to one or several levels of periodic pulses (a meter, for short) when listening to musical rhythm, even when the sensory input does not provide prominent periodic cues to their temporal location. Here, we review a multi-levelled framework to understanding how external rhythmic inputs are mapped onto internally represented metric pulses. This mapping is studied using an approach to quantify and directly compare representations of metric pulses in signals corresponding to sensory inputs, neural activity and behaviour (typically body movement). Based on this approach, recent empirical evidence can be drawn together into a conceptual framework that unpacks the phenomenon of meter into four levels. Each level highlights specific functional processes that critically enable and shape the mapping from sensory input to internal meter. We discuss the nature, constraints and neural substrates of these processes, starting with fundamental mechanisms investigated in macaque monkeys that enable basic forms of mapping between simple rhythmic stimuli and internally represented metric pulse. We propose that human evolution has gradually built a robust and flexible system upon these fundamental processes, allowing more complex levels of mapping to emerge in musical behaviours. This approach opens promising avenues to understand the many facets of rhythmic behaviours across individuals and species. This article is part of the theme issue 'Synchrony and rhythm interaction: from the brain to behavioural ecology'.

Human Genomics and the Biocultural Origin of Music

Music is an exclusive feature of humankind. It can be considered as a form of universal communication, only partly comparable to the vocalizations of songbirds. Many trends of research in this field try to address music origins, as well as the genetic bases of musicality. On one hand, several hypotheses have been made on the evolution of music and its role, but there is still debate, and comparative studies suggest a gradual evolution of some abilities underlying musicality in primates. On the other hand, genome-wide studies highlight several genes associated with musical aptitude, confirming a genetic basis for different musical skills which humans show. Moreover, some genes associated with musicality are involved also in singing and song learning in songbirds, suggesting a likely evolutionary convergence between humans and songbirds. This comprehensive review aims at presenting the concept of music as a sociocultural manifestation within the current debate about its biocultural origin and evolutionary function, in the context of the most recent discoveries related to the cross-species genetics of musical production and perception.

Spontaneous grouping of saccade timing in the presence of task-irrelevant objects

Sequential movements are often grouped into several chunks, as evidenced by the modulation of the timing of each elemental movement. Even during synchronized tapping with a metronome, we sometimes feel subjective accent for every few taps. To examine whether motor segmentation emerges during synchronized movements, we trained monkeys to generate a series of predictive saccades synchronized with visual stimuli which sequentially appeared for a fixed interval (400 or 600 ms) at six circularly arranged landmark locations. We found two types of motor segmentations that featured periodic modulation of saccade timing. First, the intersaccadic interval (ISI) depended on the target location and saccade direction, indicating that particular combinations of saccades were integrated into motor chunks. Second, when a task-irrelevant rectangular contour surrounding three landmarks ("inducer") was presented, the ISI significantly modulated depending on the relative target location to the inducer. All patterns of individual differences seen in monkeys were also observed in humans. Importantly, the effects of the inducer greatly decreased or disappeared when the animals were trained to generate only reactive saccades (latency >100 ms), indicating that the motor segmentation may depend on the internal rhythms. Thus, our results demonstrate two types of motor segmentation during synchronized movements: one is related to the hierarchical organization of sequential movements and the other is related to the spontaneous grouping of rhythmic events. This experimental paradigm can be used to investigate the underlying neural mechanism of temporal grouping during rhythm production.

Neural Encoding and Representation of Time for Sensorimotor Control and Learning

The ability to perceive and produce movements in the real world with precise timing is critical for survival in animals, including humans. However, research on sensorimotor timing has rarely considered the tight interrelation between perception, action, and cognition. In this review, we present new evidence from behavioral, computational, and neural studies in humans and nonhuman primates, suggesting a pivotal link between sensorimotor control and temporal processing, as well as describing new theoretical frameworks regarding timing in perception and action. We first discuss the link between movement coordination and interval-based timing by addressing how motor training develops accurate spatiotemporal patterns in behavior and influences the perception of temporal intervals. We then discuss how motor expertise results from establishing task-relevant neural manifolds in sensorimotor cortical areas and how the geometry and dynamics of these manifolds help reduce timing variability. We also highlight how neural dynamics in sensorimotor areas are involved in beat-based timing. These lines of research aim to extend our understanding of how timing arises from and contributes to perceptual-motor behaviors in complex environments to seamlessly interact with other cognitive processes.

How Beat Perception Co-opts Motor Neurophysiology

Beat perception offers cognitive scientists an exciting opportunity to explore how cognition and action are intertwined in the brain even in the absence of movement. Many believe the motor system predicts the timing of beats, yet current models of beat perception do not specify how this is neurally implemented. Drawing on recent insights into the neurocomputational properties of the motor system, we propose that beat anticipation relies on action-like processes consisting of precisely patterned neural time-keeping activity in the supplementary motor area (SMA), orchestrated and sequenced by activity in the dorsal striatum. In addition to synthesizing recent advances in cognitive science and motor neuroscience, our framework provides testable predictions to guide future work.

A spike analysis method for characterizing neurons based on phase locking and scaling to the interval between two behavioral events

Standard analysis of neuronal functions assesses the temporal correlation between animal behaviors and neuronal activity by aligning spike trains with the timing of a specific behavioral event, e.g., visual cue. However, spike activity is often involved in information processing dependent on a relative phase between two consecutive events rather than a single event. Nevertheless, less attention has so far been paid to such temporal features of spike activity in relation to two behavioral events. Here, we propose "Phase-Scaling analysis" to simultaneously evaluate the phase locking and scaling to the interval between two events in task-related spike activity of individual neurons. This analysis method can discriminate conceptual "scaled"-type neurons from "nonscaled"-type neurons using an activity variation map that combines phase locking with scaling to the interval. Its robustness was validated by spike simulation using different spike properties. Furthermore, we applied it to analyzing actual spike data from task-related neurons in the primary visual cortex (V1), posterior parietal cortex (PPC), primary motor cortex (M1), and secondary motor cortex (M2) of behaving rats. After hierarchical clustering of all neurons using their activity variation maps, we divided them objectively into four clusters corresponding to nonscaled-type sensory and motor neurons and scaled-type neurons including sustained and ramping activities, etc. Cluster/subcluster compositions for V1 differed from those of PPC, M1, and M2. The V1 neurons showed the fastest functional activities among those areas. Our method was also applicable to determine temporal "forms" and the latency of spike activity changes. These findings demonstrate its utility for characterizing neurons.NEW & NOTEWORTHY Phase-Scaling analysis is a novel technique to unbiasedly characterize the temporal dependency of functional neuron activity on two behavioral events and objectively determine the latency and form of the activity change. This powerful analysis can uncover several classes of latently functioning neurons that have thus far been overlooked, which may participate differently in intermediate processes of a brain function. The Phase-Scaling analysis will yield profound insights into neural mechanisms for processing internal information.

Cerebral Substrates for Controlling Rhythmic Movements

Our daily lives are filled with rhythmic movements, such as walking, sports, and dancing, but the mechanisms by which the brain controls rhythmic movements are poorly understood. In this review, we examine the literature on neuropsychological studies of patients with focal brain lesions, and functional brain imaging studies primarily using finger-tapping tasks. These studies suggest a close connection between sensory and motor processing of rhythm, with no apparent distinction between the two functions. Thus, we conducted two functional brain imaging studies to survey the rhythm representations relatively independent of sensory and motor functions. First, we determined brain activations related to rhythm processing in a sensory modality-independent manner. Second, we examined body part-independent brain activation related to rhythm reproduction. Based on previous literature, we discuss how brain areas contribute rhythmic motor control. Furthermore, we also discuss the mechanisms by which the brain controls rhythmic movements.

Differential contributions of the two human cerebral hemispheres to action timing

Rhythmic actions benefit from synchronization with external events. Auditory-paced finger tapping studies indicate the two cerebral hemispheres preferentially control different rhythms. It is unclear whether left-lateralized processing of faster rhythms and right-lateralized processing of slower rhythms bases upon hemispheric timing differences that arise in the motor or sensory system or whether asymmetry results from lateralized sensorimotor interactions. We measured fMRI and MEG during symmetric finger tapping, in which fast tapping was defined as auditory-motor synchronization at 2.5 Hz. Slow tapping corresponded to tapping to every fourth auditory beat (0.625 Hz). We demonstrate that the left auditory cortex preferentially represents the relative fast rhythm in an amplitude modulation of low beta oscillations while the right auditory cortex additionally represents the internally generated slower rhythm. We show coupling of auditory-motor beta oscillations supports building a metric structure. Our findings reveal a strong contribution of sensory cortices to hemispheric specialization in action control.

Modulation of Beta Oscillations for Implicit Motor Timing in Primate Sensorimotor Cortex during Movement Preparation

Motor timing is an important part of sensorimotor control. Previous studies have shown that beta oscillations embody the process of temporal perception in explicit timing tasks. In contrast, studies focusing on beta oscillations in implicit timing tasks are lacking. In this study, we set up an implicit motor timing task and found a modulation pattern of beta oscillations with temporal perception during movement preparation. We trained two macaques in a repetitive visually-guided reach-to-grasp task with different holding intervals. Spikes and local field potentials were recorded from microelectrode arrays in the primary motor cortex, primary somatosensory cortex, and posterior parietal cortex. We analyzed the association between beta oscillations and temporal interval in fixed-duration experiments (500 ms as the Short Group and 1500 ms as the Long Group) and random-duration experiments (500 ms to 1500 ms). The results showed that the peak beta frequencies in both experiments ranged from 15 Hz to 25 Hz. The beta power was higher during the hold period than the movement (reach and grasp) period. Further, in the fixed-duration experiments, the mean power as well as the maximum rate of change of beta power in the first 300 ms were higher in the Short Group than in the Long Group when aligned with the Center Hit event. In contrast, in the random-duration experiments, the corresponding values showed no statistical differences among groups. The peak latency of beta power was shorter in the Short Group than in the Long Group in the fixed-duration experiments, while no consistent modulation pattern was found in the random-duration experiments. These results indicate that beta oscillations can modulate with temporal interval in their power mode. The synchronization period of beta power could reflect the cognitive set maintaining working memory of the temporal structure and attention.

The amplitude in periodic neural state trajectories underlies the tempo of rhythmic tapping

Our motor commands can be exquisitely timed according to the demands of the environment, and the ability to generate rhythms of different tempos is a hallmark of musical cognition. Yet, the neuronal underpinnings behind rhythmic tapping remain elusive. Here, we found that the activity of hundreds of primate medial premotor cortices (MPCs; pre-supplementary motor area [preSMA] and supplementary motor area [SMA]) neurons show a strong periodic pattern that becomes evident when their responses are projected into a state space using dimensionality reduction analysis. We show that different tapping tempos are encoded by circular trajectories that travelled at a constant speed but with different radii, and that this neuronal code is highly resilient to the number of participating neurons. Crucially, the changes in the amplitude of the oscillatory dynamics in neuronal state space are a signature of duration encoding during rhythmic timing, regardless of whether it is guided by an external metronome or is internally controlled and is not the result of repetitive motor commands. This dynamic state signal predicted the duration of the rhythmically produced intervals on a trial-by-trial basis. Furthermore, the increase in variability of the neural trajectories accounted for the scalar property, a hallmark feature of temporal processing across tasks and species. Finally, we found that the interval-dependent increments in the radius of periodic neural trajectories are the result of a larger number of neurons engaged in the production of longer intervals. Our results support the notion that rhythmic timing during tapping behaviors is encoded in the radial curvature of periodic MPC neural population trajectories.

Rhesus Monkeys (Macaca mulatta) Sense Isochrony in Rhythm, but Not the Beat: Additional Support for the Gradual Audiomotor Evolution Hypothesis

Charles Darwin suggested the perception of rhythm to be common to all animals. While only recently experimental research is finding some support for this claim, there are also aspects of rhythm cognition that appear to be species-specific, such as the capability to perceive a regular pulse (or beat) in a varying rhythm. In the current study, using EEG, we adapted an auditory oddball paradigm that allows for disentangling the contributions of beat perception and isochrony to the temporal predictability of the stimulus. We presented two rhesus monkeys (Macaca mulatta) with a rhythmic sequence in two versions: an isochronous version, that was acoustically accented such that it could induce a duple meter (like a march), and a jittered version using the same acoustically accented sequence but that was presented in a randomly timed fashion, as such disabling beat induction. The results reveal that monkeys are sensitive to the isochrony of the stimulus, but not its metrical structure. The MMN was influenced by the isochrony of the stimulus, resulting in a larger MMN in the isochronous as opposed to the jittered condition. However, the MMN for both monkeys showed no interaction between metrical position and isochrony. So, while the monkey brain appears to be sensitive to the isochrony of the stimulus, we find no evidence in support of beat perception. We discuss these results in the context of the gradual audiomotor evolution (GAE) hypothesis (Merchant and Honing, 2014) that suggests beat-based timing to be omnipresent in humans but only weakly so or absent in non-human primates.

Predictive rhythmic tapping to isochronous and tempo changing metronomes in the nonhuman primate

Beat entrainment is the ability to entrain one's movements to a perceived periodic stimulus, such as a metronome or a pulse in music. Humans have a capacity to predictively respond to a periodic pulse and to dynamically adjust their movement timing to match the varying music tempos. Previous studies have shown that monkeys share some of the human capabilities for rhythmic entrainment, such as tapping regularly at the period of isochronous stimuli. However, it is still unknown whether monkeys can predictively entrain to dynamic tempo changes like humans. To address this question, we trained monkeys in three tapping tasks and compared their rhythmic entrainment abilities with those of humans. We found that, when immediate feedback about the timing of each movement is provided, monkeys can predictively entrain to an isochronous beat, generating tapping movements in anticipation of the metronome pulse. This ability also generalized to a novel untrained tempo. Notably, macaques can modify their tapping tempo by predicting the beat changes of accelerating and decelerating visual metronomes in a manner similar to humans. Our findings support the notion that nonhuman primates share with humans the ability of temporal anticipation during tapping to isochronous and smoothly changing sequences of stimuli.

The Synaptic Properties of Cells Define the Hallmarks of Interval Timing in a Recurrent Neural Network

Extensive research has described two key features of interval timing. The bias property is associated with accuracy and implies that time is overestimated for short intervals and underestimated for long intervals. The scalar property is linked to precision and states that the variability of interval estimates increases as a function of interval duration. The neural mechanisms behind these properties are not well understood. Here we implemented a recurrent neural network that mimics a cortical ensemble and includes cells that show paired-pulse facilitation and slow inhibitory synaptic currents. The network produces interval selective responses and reproduces both bias and scalar properties when a Bayesian decoder reads its activity. Notably, the interval-selectivity, timing accuracy, and precision of the network showed complex changes as a function of the decay time constants of the modeled synaptic properties and the level of background activity of the cells. These findings suggest that physiological values of the time constants for paired-pulse facilitation and GABAb, as well as the internal state of the network, determine the bias and scalar properties of interval timing.SIGNIFICANCE STATEMENT Timing is a fundamental element of complex behavior, including music and language. Temporal processing in a wide variety of contexts shows two primary features: time estimates exhibit a shift toward the mean (the bias property) and are more variable for longer intervals (the scalar property). We implemented a recurrent neural network that includes long-lasting synaptic currents, which cannot only produce interval-selective responses but also follow the bias and scalar properties. Interestingly, only physiological values of the time constants for paired-pulse facilitation and GABAb, as well as intermediate background activity within the network can reproduce the two key features of interval timing.

On the biological basis of musicality

In recent years, music and musicality have been the focus of an increasing amount of research effort. This has led to a growing role and visibility of the contribution of (bio)musicology to the field of neuroscience and cognitive sciences at large. While it has been widely acknowledged that there are commonalities between speech, language, and musicality, several researchers explain this by considering musicality as an epiphenomenon of language. However, an alternative hypothesis is that musicality is an innate and widely shared capacity for music that can be seen as a natural, spontaneously developing set of traits based on and constrained by our cognitive abilities and their underlying biology. A comparative study of musicality in humans and well-known animal models (monkeys, birds, pinnipeds) will further our insights on which features of musicality are exclusive to humans and which are shared between humans and nonhuman animals, contribute to an understanding of the musical phenotype, and further constrain existing evolutionary theories of music and musicality.

Rhythmic entrainment: Why humans want to, fireflies can't help it, pet birds try, and sea lions have to be bribed

Until recently, the literature on rhythmic ability took for granted that only humans are able to synchronize body movements to an external beat-to entrain. This assumption has been undercut by findings of beat-matching in various species of parrots and, more recently, in a sea lion, several species of primates, and possibly horses. This throws open the question of how widespread beat-matching ability is in the animal kingdom. Here we reassess the arguments and evidence for an absence of beat-matching in animals, and conclude that in fact no convincing case against beat-matching in animals has been made. Instead, such evidence as there is suggests that this capacity could be quite widespread. Furthermore, mutual entrainment of oscillations is a general principle of physical systems, both biological and nonbiological, suggesting that entrainment of motor systems by sensory systems may be a default rather than an oddity. The question then becomes, not why a few privileged species are able to beat-match, but why species do not always do so-why they vary in both spontaneous and learned beat-matching. We propose that when entrainment is not driven by fixed, mandatory connections between input and output (as in the case of, e.g., fireflies entraining to each others' flashes), it depends on voluntary control over, and voluntary or learned coupling of, sensory and motor systems, which can paradoxically lead to apparent failures of entrainment. Among the factors that affect whether an animal will entrain are sufficient control over the motor behavior to be entrained, sufficient perceptual sophistication to extract the entraining beat from the overall sensory environment, and the current cognitive state of the animal, including attention and motivation. The extent of entrainment in the animal kingdom potentially has widespread implications, not only for understanding the roots of human dance, but also for understanding the neural and cognitive architectures of animals.

Monkeys share the neurophysiological basis for encoding sound periodicities captured by the frequency-following response with humans

The extraction and encoding of acoustical temporal regularities are fundamental for human cognitive auditory abilities such as speech or beat entrainment. Because the comparison of the neural sensitivity to temporal regularities between human and animals is fundamental to relate non-invasive measures of auditory processing to their neuronal basis, here we compared the neural representation of auditory periodicities between human and non-human primates by measuring scalp-recorded frequency-following response (FFR). We found that rhesus monkeys can resolve the spectrotemporal structure of periodic stimuli to a similar extent as humans by exhibiting a homologous FFR potential to the speech syllable /da/. The FFR in both species is robust and phase-locked to the fundamental frequency of the sound, reflecting an effective neural processing of the fast-periodic information of subsyllabic cues. Our results thus reveal a conserved neural ability to track acoustical regularities within the primate order. These findings open the possibility to study the neurophysiology of complex sound temporal processing in the macaque subcortical and cortical areas, as well as the associated experience-dependent plasticity across the auditory pathway in behaving monkeys.

Differential Encoding of Time by Prefrontal and Striatal Network Dynamics

Telling time is fundamental to many forms of learning and behavior, including the anticipation of rewarding events. Although the neural mechanisms underlying timing remain unknown, computational models have proposed that the brain represents time in the dynamics of neural networks. Consistent with this hypothesis, changing patterns of neural activity dynamically in a number of brain areas-including the striatum and cortex-has been shown to encode elapsed time. To date, however, no studies have explicitly quantified and contrasted how well different areas encode time by recording large numbers of units simultaneously from more than one area. Here, we performed large-scale extracellular recordings in the striatum and orbitofrontal cortex of mice that learned the temporal relationship between a stimulus and a reward and reported their response with anticipatory licking. We used a machine-learning algorithm to quantify how well populations of neurons encoded elapsed time from stimulus onset. Both the striatal and cortical networks encoded time, but the striatal network outperformed the orbitofrontal cortex, a finding replicated both in simultaneously and nonsimultaneously recorded corticostriatal datasets. The striatal network was also more reliable in predicting when the animals would lick up to ∼1 s before the actual lick occurred. Our results are consistent with the hypothesis that temporal information is encoded in a widely distributed manner throughout multiple brain areas, but that the striatum may have a privileged role in timing because it has a more accurate "clock" as it integrates information across multiple cortical areas.

SIGNIFICANCE STATEMENT

The neural representation of time is thought to be distributed across multiple functionally specialized brain structures, including the striatum and cortex. However, until now, the neural code for time has not been compared quantitatively between these areas. Here, we performed large-scale recordings in the striatum and orbitofrontal cortex of mice trained on a stimulus-reward association task involving a delay period and used a machine-learning algorithm to quantify how well populations of simultaneously recorded neurons encoded elapsed time from stimulus onset. We found that, although both areas encoded time, the striatum consistently outperformed the orbitofrontal cortex. These results suggest that the striatum may refine the code for time by integrating information from multiple inputs.

Predictive and tempo-flexible synchronization to a visual metronome in monkeys

Predictive and tempo-flexible synchronization to an auditory beat is a fundamental component of human music. To date, only certain vocal learning species show this behaviour spontaneously. Prior research training macaques (vocal non-learners) to tap to an auditory or visual metronome found their movements to be largely reactive, not predictive. Does this reflect the lack of capacity for predictive synchronization in monkeys, or lack of motivation to exhibit this behaviour? To discriminate these possibilities, we trained monkeys to make synchronized eye movements to a visual metronome. We found that monkeys could generate predictive saccades synchronized to periodic visual stimuli when an immediate reward was given for every predictive movement. This behaviour generalized to novel tempi, and the monkeys could maintain the tempo internally. Furthermore, monkeys could flexibly switch from predictive to reactive saccades when a reward was given for each reactive response. In contrast, when humans were asked to make a sequence of reactive saccades to a visual metronome, they often unintentionally generated predictive movements. These results suggest that even vocal non-learners may have the capacity for predictive and tempo-flexible synchronization to a beat, but that only certain vocal learning species are intrinsically motivated to do it.

Representation of Behavioral Tactics and Tactics-Action Transformation in the Primate Medial Prefrontal Cortex

To expedite the selection of action under a structured behavioral context, we develop an expedient to promote its efficiency: tactics for action selection. Setting up a behavioral condition for subhuman primates (Macaca fuscata) that induced the development of a behavioral tactics, we explored neuronal representation of tactics in the medial frontal cortex. Here we show that neurons in the posterior medial prefrontal cortex, but not much in the medial premotor cortex, exhibit activity representing the behavioral tactics, in advance of action-selective activity. Such activity appeared during behavioral epochs of its retrieval from instruction cues, maintenance in short-term memory, and its implementation for the achievement of action selection. At a population level, posterior medial prefrontal cortex neurons take part in transforming the tactics information into the information representing action selection. The tactics representation revealed an aspect of neural mechanisms for an adaptive behavioral control, taking place in the medial prefrontal cortex.

SIGNIFICANCE STATEMENT

We studied behavioral significance of neuronal activity in the posterior medial prefrontal cortex (pmPFC) and found the representation of behavioral tactics defined as specific and efficient ways to achieve objectives of actions. Neuronal activity appeared during behavioral epochs of its retrieval from instruction cues, maintenance in short-term memory, and its use preceding the achievement of action selection. We found further that pmPFC neurons take part in transforming the tactics information into the information representing action selection. A majority of individual neurons was recruited during a limited period in each behavioral epoch, constituting, as a whole, a temporal cascade of activity. Such dynamics found in behavioral-tactics specific activity characterize the participation of pmPFC neurons in executive control of purposeful behavior.

Probing the timing network: A continuous theta burst stimulation study of temporal categorization

Time perception in the millisecond and second ranges is thought to be processed by different neural mechanisms. However, whether there is a sharp boundary between these ranges and whether they are implemented in the same, overlapped or separate brain areas is still not certain. To probe the role of the right dorsolateral prefrontal cortex (dlPFC), the right supplementary motor area (SMA), and the cerebellum on time perception, we temporarily altered their activity on healthy volunteers on separate sessions using transcranial magnetic stimulation with the continuous Theta Burst Stimulation (cTBS) protocol. A control session was reserved for the stimulation of the primary somatosensory cortex (S1). Before and after stimulation, participants were tested on a temporal categorization task using intervals in the hundreds and thousands of milliseconds ranges, as well as on a pitch categorization task which was used as a further control. We then looked for changes in the Relative Threshold and the Constant Error, which, respectively, reflect participants' sensitivity to interval duration and their accuracy at setting an interval that acts as a boundary between categories. We found that after cTBS in all of the studied regions, the Relative Threshold, but not the Constant Error, was affected and only when hundreds of milliseconds intervals were being categorized. Categorization of thousands of milliseconds intervals and of pitch was not affected. These results suggest that the fronto-cerebellar circuit is particularly involved in the estimation of intervals in the hundreds of milliseconds range.

The Computational and Neural Basis of Rhythmic Timing in Medial Premotor Cortex

The neural underpinnings of rhythmic behavior, including music and dance, have been studied using the synchronization-continuation task (SCT), where subjects initially tap in synchrony with an isochronous metronome and then keep tapping at a similar rate via an internal beat mechanism. Here, we provide behavioral and neural evidence that supports a resetting drift-diffusion model (DDM) during SCT. Behaviorally, we show the model replicates the linear relation between the mean and standard-deviation of the intervals produced by monkeys in SCT. We then show that neural populations in the medial premotor cortex (MPC) contain an accurate trial-by-trial representation of elapsed-time between taps. Interestingly, the autocorrelation structure of the elapsed-time representation is consistent with a DDM. These results indicate that MPC has an orderly representation of time with features characteristic of concatenated DDMs and that this population signal can be used to orchestrate the rhythmic structure of the internally timed elements of SCT.SIGNIFICANCE STATEMENT The present study used behavioral data, ensemble recordings from medial premotor cortex (MPC) in macaque monkeys, and computational modeling, to establish evidence in favor of a class of drift-diffusion models of rhythmic timing during a synchronization-continuation tapping task (SCT). The linear relation between the mean and standard-deviation of the intervals produced by monkeys in SCT is replicated by the model. Populations of MPC cells faithfully represent the elapsed time between taps, and there is significant trial-by-trial relation between decoded times and the timing behavior of the monkeys. Notably, the neural decoding properties, including its autocorrelation structure are consistent with a set of drift-diffusion models that are arranged sequentially and that are resetting in each SCT tap.

Time to Move Again: Does the Bereitschaftspotential Covary with Demands on Internal Timing?

When Bereitschaftspotentials (BPs) are measured, participants are required to voluntarily perform a predefined number of identical movements, with varying intervals between movements, exceeding some obligatory minimum interval. Participants might cope with these demands on timing by installing a slow, broadly tuned rhythm of activation, serving as an internal trigger for executing movements in time. The BP might reflect the rising phase of this activation, culminating at the movement. If so (i) not only should BP amplitudes become larger, but BPs should also have their onsets earlier before movements when longer minimum intervals are required between movements (Experiment 1). Further, (ii) BP amplitudes should covary with demands on internal timing: decrease when internal timing is less necessary and increase in the other case. Variation of timing demands was realized by requiring participants to count vs. not to count the seconds between movements (Experiment 1) and by regular vs. irregular vs. no ticking of a clock (Experiment 2). Prediction (i) was confirmed while prediction (ii) was not. Thus, BP onsets did vary in accordance with the temporal constraints about when the movements should be performed, suggesting some relation to timing mechanisms, but we could not provide evidence for the notion that the process reflected by BPs is this timing mechanism.

Temporal Processing by Intrinsic Neural Network Dynamics

It is becoming more apparent that there are rich contributions to temporal processing across the brain. Temporal dynamics have been found from lower brain structures all the way to cortical regions. Specifically,in vitrocortical preparations have been extremely useful in understanding how local circuits can time. While many of these results depict vastly different processing than a traditional central clock metaphor they still leave questions as to how this information is integrated. We therefore review evidence to place the results pertaining to local circuit timers into the larger context of temporal perception and generalization.

Recording extracellular neural activity in the behaving monkey using a semichronic and high-density electrode system

We describe a technique to semichronically record the cortical extracellular neural activity in the behaving monkey employing commercial high-density electrodes. After the design and construction of low cost microdrives that allow varying the depth of the recording locations after the implantation surgery, we recorded the extracellular unit activity from pools of neurons at different depths in the presupplementary motor cortex (pre-SMA) of a rhesus monkey trained in a tapping task. The collected data were processed to classify cells as putative pyramidal cells or interneurons on the basis of their waveform features. We also demonstrate that short time cross-correlogram occasionally yields unit pairs with high short latency (<5 ms), narrow bin (<3 ms) peaks, indicative of monosynaptic spike transmission from pre- to postsynaptic neurons. These methods have been verified extensively in rodents. Finally, we observed that the pattern of population activity was repetitive over distinct trials of the tapping task. These results show that the semichronic technique is a viable option for the large-scale parallel recording of local circuit activity at different depths in the cortex of the macaque monkey and other large species.

Enhanced brainstem and cortical encoding of sound during synchronized movement

Movement to a steady beat has been widely studied as a model of alignment of motor outputs on sensory inputs. However, how the encoding of sensory inputs is shaped during synchronized movements along the sensory pathway remains unknown. To investigate this, we simultaneously recorded brainstem and cortical electro-encephalographic activity while participants listened to periodic amplitude-modulated tones. Participants listened either without moving or while tapping in sync on every second beat. Cortical responses were identified at the envelope modulation rate (beat frequency), whereas brainstem responses were identified at the partials frequencies of the chord and at their modulation by the beat frequency (sidebands). During sensorimotor synchronization, cortical responses at beat frequency were larger than during passive listening. Importantly, brainstem responses were also enhanced, with a selective amplification of the sidebands, in particular at the lower-pitched tone of the chord, and no significant correlation with electromyographic measures at tapping frequency. These findings provide first evidence for an online gain in the cortical and subcortical encoding of sounds during synchronized movement, selective to behavior-relevant sound features. Moreover, the frequency-tagging method to isolate concurrent brainstem and cortical activities even during actual movements appears promising to reveal coordinated processes along the human auditory pathway.