Neurophysiology of timing in the hundreds of milliseconds: multiple layers of neuronal clocks in the medial premotor areas

Measuring self-similarity in empirical signals to understand musical beat perception

Experiencing music often entails the perception of a periodic beat. Despite being a widespread phenomenon across cultures, the nature and neural underpinnings of beat perception remain largely unknown. In the last decade, there has been a growing interest in developing methods to probe these processes, particularly to measure the extent to which beat-related information is contained in behavioral and neural responses. Here, we propose a theoretical framework and practical implementation of an analytic approach to capture beat-related periodicity in empirical signals using frequency-tagging. We highlight its sensitivity in measuring the extent to which the periodicity of a perceived beat is represented in a range of continuous time-varying signals with minimal assumptions. We also discuss a limitation of this approach with respect to its specificity when restricted to measuring beat-related periodicity only from the magnitude spectrum of a signal and introduce a novel extension of the approach based on autocorrelation to overcome this issue. We test the new autocorrelation-based method using simulated signals and by re-analyzing previously published data and show how it can be used to process measurements of brain activity as captured with surface EEG in adults and infants in response to rhythmic inputs. Taken together, the theoretical framework and related methodological advances confirm and elaborate the frequency-tagging approach as a promising window into the processes underlying beat perception and, more generally, temporally coordinated behaviors.

White matter structural bases for phase accuracy during tapping synchronization

We determined the intersubject association between the rhythmic entrainment abilities of human subjects during a synchronization-continuation tapping task (SCT) and the macro- and microstructural properties of their superficial (SWM) and deep (DWM) white matter. Diffusion-weighted images were obtained from 32 subjects who performed the SCT with auditory or visual metronomes and five tempos ranging from 550 to 950 ms. We developed a method to determine the density of short-range fibers that run underneath the cortical mantle, interconnecting nearby cortical regions (U-fibers). Notably, individual differences in the density of U-fibers in the right audiomotor system were correlated with the degree of phase accuracy between the stimuli and taps across subjects. These correlations were specific to the synchronization epoch with auditory metronomes and tempos around 1.5 Hz. In addition, a significant association was found between phase accuracy and the density and bundle diameter of the corpus callosum (CC), forming an interval-selective map where short and long intervals were behaviorally correlated with the anterior and posterior portions of the CC. These findings suggest that the structural properties of the SWM and DWM in the audiomotor system support the tapping synchronization abilities of subjects, as cortical U-fiber density is linked to the preferred tapping tempo and the bundle properties of the CC define an interval-selective topography.

Aperiodic activity differences in individuals with high and low temporal processing efficiency

It is known that Temporal Information Processing (TIP) underpins our cognitive functioning. Previous research has focused on the relationship between TIP efficiency and oscillatory brain activity, especially the gamma rhythm; however, non-oscillatory (aperiodic or 1/f) brain activity has often been missed. Recent studies have identified the 1/f component as being important for the functioning of the brain. Therefore, the current study aimed to verify whether TIP efficiency is associated with specific EEG resting state cortical activity patterns, including oscillatory and non-oscillatory (aperiodic) brain activities. To measure individual TIP efficiency, we used two behavioral tasks in which the participant judges the order of two sounds separated by millisecond intervals. Based on the above procedure, participants were classified into two groups with high and low TIP efficiency. Using cluster-based permutation analyses, we examined between-group differences in oscillatory and non-oscillatory (aperiodic) components across the 1-90 Hz range. The results revealed that the groups differed in the aperiodic component across the 30-80 Hz range in fronto-central topography. In other words, participants with low TIP efficiency exhibited higher levels of aperiodic activity, and thus a flatter frequency spectrum compared to those with high TIP efficiency. We conclude that participants with low TIP efficiency display higher levels of 'neural noise', which is associated with poorer quality and speed of neural processing.

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.

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.

A common timing mechanism across different millisecond domains: evidence from perceptual and motor tasks

Temporal information processing (TIP) constitutes a complex construct that underlies many cognitive functions and operates in a few hierarchically ordered time domains. This study aimed to verify the relationship between the tens of milliseconds and hundreds of milliseconds domains, referring to perceptual and motor timing, respectively. Sixty four young healthy individuals participated in this study. They underwent two auditory temporal order judgement tasks to assess their performance in the tens of milliseconds domain; on this basis, groups of high-level performers (HLP) and low-level performers (LLP) were identified. Then, a maximum tapping task was used to evaluate performance in the hundreds of milliseconds domain. The most remarkable result was that HLP achieved a faster tapping rate and synchronised quicker with their "internal clock" during the tapping task than did LLP. This result shows that there is a relationship between accuracy in judging temporally asynchronous stimuli and ability to achieve and maintain the pace of a movement adequate to one's internal pacemaker. This could indicate the strong contribution of a common timing mechanism, responsible for temporal organisation and coordination of behaviours across different millisecond domains.

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.

Efficient Temporal Coding in the Early Visual System: Existing Evidence and Future Directions

While it is universally accepted that the brain makes predictions, there is little agreement about how this is accomplished and under which conditions. Accurate prediction requires neural circuits to learn and store spatiotemporal patterns observed in the natural environment, but it is not obvious how such information should be stored, or encoded. Information theory provides a mathematical formalism that can be used to measure the efficiency and utility of different coding schemes for data transfer and storage. This theory shows that codes become efficient when they remove predictable, redundant spatial and temporal information. Efficient coding has been used to understand retinal computations and may also be relevant to understanding more complicated temporal processing in visual cortex. However, the literature on efficient coding in cortex is varied and can be confusing since the same terms are used to mean different things in different experimental and theoretical contexts. In this work, we attempt to provide a clear summary of the theoretical relationship between efficient coding and temporal prediction, and review evidence that efficient coding principles explain computations in the retina. We then apply the same framework to computations occurring in early visuocortical areas, arguing that data from rodents is largely consistent with the predictions of this model. Finally, we review and respond to criticisms of efficient coding and suggest ways that this theory might be used to design future experiments, with particular focus on understanding the extent to which neural circuits make predictions from efficient representations of environmental statistics.

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'.

Stimulation of Different Sectors of the Human Dorsal Premotor Cortex Induces a Shift from Reactive to Predictive Action Strategies and Changes in Motor Inhibition: A Dense Transcranial Magnetic Stimulation (TMS) Mapping Study

Delayed motor tasks require timely interaction between immobility and action. The neural substrates of these processes probably reside in the premotor and motor circuits; however, fine-grained anatomical/functional information is still lacking. Participants performed a delayed simple reaction task, structured as a ready-set-go sequence, with a fixed, predictable, SET-period. Responses were given with lip movements. During the SET-period, we performed a systematic dense-mapping of the bilateral dorsal premotor region (dPM) by means of single transcranial magnetic stimulation (TMS) pulses on an 18-spot mapping grid, interleaved with sham TMS which served as a baseline. Reaction times (RTs) in TMS trials over each grid spot were compared to RTs in sham trials to build a statistical parametric z-map. The results reveal a rostro-caudal functional gradient in the dPM. TMS of the rostral dPM induced a shift from reactive towards predictive response strategies. TMS of the caudal dPM interfered with the SET-period duration. By means of dense TMS mapping, we have drawn a putative functional map of the role of the dPM during the SET-period. A higher-order rostral component is involved in setting action strategies and a caudal, lower-order, part is probably involved in the inhibitory control of motor output.

Motor and Predictive Processes in Auditory Beat and Rhythm Perception

In this article, we review recent advances in research on rhythm and musical beat perception, focusing on the role of predictive processes in auditory motor interactions. We suggest that experimental evidence of the motor system's role in beat perception, including in passive listening, may be explained by the generation and maintenance of internal predictive models, concordant with the Active Inference framework of sensory processing. We highlight two complementary hypotheses for the neural underpinnings of rhythm perception: The Action Simulation for Auditory Prediction hypothesis (Patel and Iversen, 2014) and the Gradual Audiomotor Evolution hypothesis (Merchant and Honing, 2014) and review recent experimental progress supporting each of these hypotheses. While initial formulations of ASAP and GAE explain different aspects of beat-based timing-the involvement of motor structures in the absence of movement, and physical entrainment to an auditory beat respectively-we suggest that work under both hypotheses provide converging evidence toward understanding the predictive role of the motor system in the perception of rhythm, and the specific neural mechanisms involved. We discuss future experimental work necessary to further evaluate the causal neural mechanisms underlying beat and rhythm perception.

A Temporal Signal-Processing Circuit Based on Spiking Neuron and Synaptic Learning

Time is a continuous, homogeneous, one-way, and independent signal that cannot be modified by human will. The mechanism of how the brain processes temporal information remains elusive. According to previous work, time-keeping in medial premotor cortex (MPC) is governed by four kinds of ramp cell populations (Merchant et al., 2011). We believe that these cell populations participate in temporal information processing in MPC. Hence, in this the present study, we present a model that uses spiking neuron, including these cell populations, to construct a complete circuit for temporal processing. By combining the time-adaptive drift-diffusion model (TDDM) with the transmission of impulse information between neurons, this new model is able to successfully reproduce the result of synchronization-continuation tapping task (SCT). We also discovered that the neurons that we used exhibited some of the firing properties of time-related neurons detected by electrophysiological experiments in other studies. Therefore, we believe that our model reflects many of the physiological of neural circuits in the biological brain and can explain some of the phenomena in the temporal-perception process.

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.

Activity in perceptual classification networks as a basis for human subjective time perception

Despite being a fundamental dimension of experience, how the human brain generates the perception of time remains unknown. Here, we provide a novel explanation for how human time perception might be accomplished, based on non-temporal perceptual classification processes. To demonstrate this proposal, we build an artificial neural system centred on a feed-forward image classification network, functionally similar to human visual processing. In this system, input videos of natural scenes drive changes in network activation, and accumulation of salient changes in activation are used to estimate duration. Estimates produced by this system match human reports made about the same videos, replicating key qualitative biases, including differentiating between scenes of walking around a busy city or sitting in a cafe or office. Our approach provides a working model of duration perception from stimulus to estimation and presents a new direction for examining the foundations of this central aspect of human experience.

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.

Neurochemical changes in basal ganglia affect time perception in parkinsonians

BACKGROUND

Parkinson's disease is described as resulting from dopaminergic cells progressive degeneration, specifically in the substantia nigra pars compacta that influence the voluntary movements control, decision making and time perception.

AIM

This review had a goal to update the relation between time perception and Parkinson's Disease.

METHODOLOGY

We used the PRISMA methodology for this investigation built guided for subjects dopaminergic dysfunction in the time judgment, pharmacological models with levodopa and new studies on the time perception in Parkinson's Disease. We researched on databases Scielo, Pubmed / Medline and ISI Web of Knowledge on August 2017 and repeated in September 2017 and February 2018 using terms and associations relevant for obtaining articles in English about the aspects neurobiology incorporated in time perception. No publication status or restriction of publication date was imposed, but we used as exclusion criteria: dissertations, book reviews, conferences or editorial work.

RESULTS/DISCUSSION

We have demonstrated that the time cognitive processes are underlying to performance in cognitive tasks and that many are the brain areas and functions involved and the modulators in the time perception performance.

CONCLUSIONS

The influence of dopaminergic on Parkinson's Disease is an important research tool in Neuroscience while allowing for the search for clarifications regarding behavioral phenotypes of Parkinson's disease patients and to study the areas of the brain that are involved in the dopaminergic circuit and their integration with the time perception mechanisms.

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.

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.

Finding the beat: a neural perspective across humans and non-human primates

Humans possess an ability to perceive and synchronize movements to the beat in music ('beat perception and synchronization'), and recent neuroscientific data have offered new insights into this beat-finding capacity at multiple neural levels. Here, we review and compare behavioural and neural data on temporal and sequential processing during beat perception and entrainment tasks in macaques (including direct neural recording and local field potential (LFP)) and humans (including fMRI, EEG and MEG). These abilities rest upon a distributed set of circuits that include the motor cortico-basal-ganglia-thalamo-cortical (mCBGT) circuit, where the supplementary motor cortex (SMA) and the putamen are critical cortical and subcortical nodes, respectively. In addition, a cortical loop between motor and auditory areas, connected through delta and beta oscillatory activity, is deeply involved in these behaviours, with motor regions providing the predictive timing needed for the perception of, and entrainment to, musical rhythms. The neural discharge rate and the LFP oscillatory activity in the gamma- and beta-bands in the putamen and SMA of monkeys are tuned to the duration of intervals produced during a beat synchronization-continuation task (SCT). Hence, the tempo during beat synchronization is represented by different interval-tuned cells that are activated depending on the produced interval. In addition, cells in these areas are tuned to the serial-order elements of the SCT. Thus, the underpinnings of beat synchronization are intrinsically linked to the dynamics of cell populations tuned for duration and serial order throughout the mCBGT. We suggest that a cross-species comparison of behaviours and the neural circuits supporting them sets the stage for a new generation of neurally grounded computational models for beat perception and synchronization.