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Highlights • Data sharing of primate neuroimaging offers new opportunities. • The potential of metadata to enrich primate neuroimaging is described. • Illustration of how meta-data can be shared in the BIDS format is provided., Sharing and pooling large amounts of non-human primate neuroimaging data offer new exciting opportunities to understand the primate brain. The potential of big data in non-human primate neuroimaging could however be tremendously enhanced by combining such neuroimaging data with other types of information. Here we describe metadata that have been identified as particularly valuable by the non-human primate neuroimaging community, including behavioural, genetic, physiological and phylogenetic data.

Accurate extraction of the cortical brain surface is critical for cortical thickness estimation and a key element to perform multimodal imaging analysis, where different metrics are integrated and compared in a common space. While brain surface extraction has become widespread practice in human studies, several challenges unique to neuroimaging of non-human primates (NHP) have hindered its adoption for the study of macaques. Although, some of these difficulties can be addressed at the acquisition stage, several common artifacts can be minimized through image preprocessing. Likewise, there are several image analysis pipelines for human MRIs, but very few automated methods for extraction of cortical surfaces have been reported for NHPs and none have been tested on data from diverse sources. We present PREEMACS, a pipeline that standardizes the preprocessing of structural MRI images (T1- and T2-weighted) and carries out an automatic surface extraction of the macaque brain. Building upon and extending pre-existing tools, the first module performs volume orientation, image cropping, intensity non-uniformity correction, and volume averaging, before skull-stripping through a convolutional neural network. The second module performs quality control using an adaptation of MRIqc method to extract objective quality metrics that are then used to determine the likelihood of accurate brain surface estimation. The third and final module estimates the white matter (wm) and pial surfaces from the T1-weighted volume (T1w) using an NHP customized version of FreeSurfer aided by the T2-weighted volumes (T2w). To evaluate the generalizability of PREEMACS, we tested the pipeline using 57 T1w/T2w NHP volumes acquired at 11 different sites from the PRIME-DE public dataset. Results showed an accurate and robust automatic brain surface extraction from images that passed the quality control segment of our pipeline. This work offers a robust, efficient and generalizable pipeline for the automatic standardization of MRI surface analysis on NHP.

Perceptual categorization depends on the assignment of different stimuli to specific groups based, in principle, on the notion of flexible categorical boundaries. To determine the neural basis of categorical boundaries, we record the activity of pre-SMA neurons of monkeys executing an interval categorization task in which the limit between short and long categories changes between blocks of trials within a session. A large population of cells encodes this boundary by reaching a constant peak of activity close to the corresponding subjective limit. Notably, the time at which this peak is reached changes according to the categorical boundary of the current block, predicting the monkeys’ categorical decision on a trial-by-trial basis. In addition, pre-SMA cells also represent the category selected by the monkeys and the outcome of the decision. These results suggest that the pre-SMA adaptively encodes subjective duration boundaries between short and long durations and contains crucial neural information to categorize intervals and evaluate the outcome of such perceptual decisions., Grouping stimuli into categories often depends on a subjective determination of category boundaries. Here the authors report a neuronal population in pre-supplementary motor area whose peak activity predicts the categorical decision boundary between long and short time intervals on a trial-by-trial basis.

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 STATEMENTThe 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.

The proper response to an ever-changing environment depends on the ability to quantify elapsed time, memorize short intervals and forecast when an upcoming experience may occur. A recent study describes the encoding principles of these three types of time using computational modelling.

Several lines of evidence suggest that motoric brain structures may form the core amodal component of a neural network supporting a wide range of timed behaviours. Here, we review recent findings which elucidate the neural computations that occur within motor regions, and in particular the supplementary motor area, in order to support precisely timed actions. Although motor activity may help us represent time, it is also clear that action both enriches and complicates the interpretation of sensory inputs. Hence, in the second half of this review, we consider the latest findings regarding the perceptual distortions that our actions can impose upon our subjective perception of time.

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.

Timing is a fundamental variable for behavior. However, the mechanisms allowing human and non-human primates to synchronize their actions with periodic events are not yet completely understood. Here we characterize the ability of rhesus monkeys and humans to perceive and maintain rhythms of different paces in the absence of sensory cues or motor actions. In our rhythm task subjects had to observe and then internally follow a visual stimulus that periodically changed its location along a circular perimeter. Crucially, they had to maintain this visuospatial tempo in the absence of movements. Our results show that the probability of remaining in synchrony with the rhythm decreased, and the variability in the timing estimates increased, as a function of elapsed time, and these trends were well described by the generalized law of Weber. Additionally, the pattern of errors shows that human subjects tended to lag behind fast rhythms and to get ahead of slow ones, suggesting that a mean tempo might be incorporated as prior information. Overall, our results demonstrate that rhythm perception and maintenance are cognitive abilities that we share with rhesus monkeys, and these abilities do not depend on overt motor commands.

The precise quantification of time during motor performance is critical for many complex behaviors, including musical execution, speech articulation, and sports; however, its neural mechanisms are primarily unknown. We found that neurons in the medial premotor cortex (MPC) of behaving monkeys are tuned to the duration of produced intervals during rhythmic tapping tasks. Interval-tuned neurons showed similar preferred intervals across tapping behaviors that varied in the number of produced intervals and the modality used to drive temporal processing. In addition, we found that the same population of neurons is able to multiplex the ordinal structure of a sequence of rhythmic movements and a wide range of durations in the range of hundreds of milliseconds. Our results also revealed a possible gain mechanism for encoding the total number of intervals in a sequence of temporalized movements, where interval-tuned cells show a multiplicative effect of their activity for longer sequences of intervals. These data suggest that MPC is part of a core timing network that uses interval tuning as a signal to represent temporal processing in a variety of behavioral contexts where time is explicitly quantified.

β oscillations in the basal ganglia have been associated with interval timing. We recorded the putaminal local field potentials (LFPs) from monkeys performing a synchronization-continuation task (SCT) and a serial reaction-time task (RTT), where the animals produced regularly and irregularly paced tapping sequences, respectively. We compared the activation profile of β oscillations between tasks and found transient bursts of β activity in both the RTT and SCT. During the RTT, β power was higher at the beginning of the task, especially when LFPs were aligned to the stimuli. During the SCT, β was higher during the internally driven continuation phase, especially for tap-aligned LFPs. Interestingly, a set of LFPs showed an initial burst of β at the beginning of the SCT, similar to the RTT, followed by a decrease in β oscillations during the synchronization phase, to finally rebound during the continuation phase. The rebound during the continuation phase of the SCT suggests that the corticostriatal circuit is involved in the control of internally driven motor sequences. In turn, the transient bursts of β activity at the beginning of both tasks suggest that the basal ganglia produce a general initiation signal that engages the motor system in different sequential behaviors.

The interception of moving targets is a complex activity that involves a dynamic interplay of several perceptual and motor processes and therefore involves a rich interaction among several brain areas. Although the behavioral aspects of interception have been studied for the past three decades, it is only during the past decade that neural studies have been focused on this problem. In addition to the interception itself, several neural studies have explored, within that context, the underlying mechanisms concerning perceptual aspects of moving stimuli, such as optic flow and apparent motion. In this review, we discuss the wealth of knowledge that has accumulated on this topic with an emphasis on the results of neural studies in behaving monkeys.

Adult human subjects can classify the height of an object as belonging to either of the "high" or "low" categories by utilizing an abstract concept of midline that divides the vertical dimension into two halves. Children lack this abstract concept of midline, do not have a sense that these categories are directional opposites, and their categorical and comparative usages of high(er) or low(er) are restricted to the corresponding poles. We investigated the abilities of a rhesus monkey to perform categorical judgments in space. We were also interested in the presence of the congruity effect (a decrease in response time when the objects compared are closer to the category pole) in the monkey. The presence of this phenomenon in the monkey would allow us to relate the behavior of the animal to the two major competing hypotheses that have been suggested to explain the congruity effect in humans: the analog and semantic models. The monkey was trained in delayed match-to-sample tasks in which it had to categorize objects as belonging to either a high or low category. The monkey was able to generate an abstract notion of midline in a fashion similar to that of adult human subjects. The congruity effect was also present in the monkey. These findings, taken together with the notion that monkeys are not considered to think in propositional terms, may favor an analog comparison model in the monkey.

We analyzed the dissimilarity matrix of neuronal responses to moving visual stimuli using tree clustering and multidimensional scaling (MDS). Single-cell activity was recorded in area 7a while random dots moving coherently in eight different kinds of motion (right-, left-, up-, and downward, clockwise, counterclockwise, expansion, contraction) were presented to behaving monkeys with eyes fixated. Tree clustering analyses showed that the {rightward, leftward}, {upward, downward}, and {clockwise, counterclockwise]} motions were clustered in three separate branches (i.e., horizontal, vertical, and rotatory motion, respectively). In contrast, expansion was in a lone branch, whereas contraction was also separate but within a larger cluster. The distances among these clusters were then subjected to an MDS analysis to identify the dimensions underlying the tree clustering observed. This analysis revealed two major factors in operation. The first factor separated expansion from all other stimulus motions, which seems to reflect the prominence of expansion during the common activity of locomotion. In contrast, the second factor separated planar motions from motion in depth, which suggests that the latter may hold a special place in visual motion processing.

We determined the encoding properties of single cells and the decoding accuracy of cell populations in the medial premotor cortex (MPC) of Rhesus monkeys to represent in a time-varying fashion the duration and serial order of six intervals produced rhythmically during a synchronization-continuation tapping task. We found that MPC represented the temporal and sequential structure of rhythmic movements by activating small ensembles of neurons that encoded the duration or the serial order in rapid succession, so that the pattern of active neurons changed dramatically within each interval. Interestingly, the width of the encoding or decoding function for serial order increased as a function of duration. Finally, we found that the strength of correlation in spontaneous activity of the individual cells varied as a function of the timing of their recruitment. These results demonstrate the existence of dynamic representations in MPC for the duration and serial order of intervals produced rhythmically and suggest that this dynamic code depends on ensembles of interconnected neurons that provide a strong synaptic drive to the next ensemble in a consecutive chain of neural events.

Gamma (γ) and beta (β) oscillations seem to play complementary functions in the cortico-basal ganglia-thalamo-cortical circuit (CBGT) during motor behavior. We investigated the time-varying changes of the putaminal spiking activity and the spectral power of local field potentials (LFPs) during a task where the rhythmic tapping of monkeys was guided by isochronous stimuli separated by a fixed duration (synchronization phase), followed by a period of internally timed movements (continuation phase). We found that the power of both bands and the discharge rate of cells showed an orderly change in magnitude as a function of the duration and/or the serial order of the intervals executed rhythmically. More LFPs were tuned to duration and/or serial order in the β- than the γ-band, although different values of preferred features were represented by single cells and by both bands. Importantly, in the LFPs tuned to serial order, there was a strong bias toward the continuation phase for the β-band when aligned to movements, and a bias toward the synchronization phase for the γ-band when aligned to the stimuli. Our results suggest that γ-oscillations reflect local computations associated with stimulus processing, whereas β-activity involves the entrainment of large putaminal circuits, probably in conjunction with other elements of CBGT, during internally driven rhythmic tapping.

A critical question in tapping behavior is to understand whether the temporal control is exerted on the duration and trajectory of the downward-upward hand movement or on the pause between hand movements. In the present study, we determined the duration of both the movement execution and pauses of monkeys performing a synchronization-continuation task (SCT), using the speed profile of their tapping behavior. We found a linear increase in the variance of pause-duration as a function of interval, while the variance of the motor implementation was relatively constant across intervals. In fact, 96% of the variability of the duration of a complete tapping cycle (pause + movement) was due to the variability of the pause duration. In addition, we performed a Bayesian model selection to determine the effect of interval duration (450–1,000 ms), serial-order (1–6 produced intervals), task phase (sensory cued or internally driven), and marker modality (auditory or visual) on the duration of the movement-pause and tapping movement. The results showed that the most important parameter used to successfully perform the SCT was the control of the pause duration. We also found that the kinematics of the tapping movements was concordant with a stereotyped ballistic control of the hand pressing the push-button. The present findings support the idea that monkeys used an explicit timing strategy to perform the SCT, where a dedicated timing mechanism controlled the duration of the pauses of movement, while also triggered the execution of fixed movements across each interval of the rhythmic sequence.

The gradual audiomotor evolution hypothesis is proposed as an alternative interpretation to the auditory timing mechanisms discussed in Ackermann et al.'s article. This hypothesis accommodates the fact that the performance of nonhuman primates is comparable to humans in single-interval tasks (such as interval reproduction, categorization, and interception), but shows differences in multiple-interval tasks (such as entrainment, synchronization, and continuation).

In tasks where different sensory, cognitive, and motor events are mixed in a sequence it is difficult to determine whether neural activity is related to any behavioral parameter. Here, we consider the case in which two alternative trial-alignment schemes correspond to two different neural representations, one stimulus-related and the other movement-related, using both simulations of neural activity and real recordings in the medial premotor areas during a multiple-interval tapping task called synchronization-continuation task (SCT). To discover whether neural responses are better aligned to sensory or motor events we introduce a family of trial-alignment time-warping functions indexed by a single parameter such that when the parameter takes the value 0 the trials are aligned to the stimulus and when the parameter takes the value 1 they are aligned to the movement. We then characterize neurons by the best-fitting alignment scheme (in the sense of maximum likelihood) under the assumption that the correct alignment would produce homogeneous trials without excess trial-to-trial variation. We use Bayes factors to determine the evidence in favor of sensory or motor neural alignments. The simulations revealed that the variability in neural responses and sequential motor outputs are key parameters to obtain appropriate warping results. In addition, the analysis on the activity of 500 neurons in the medial premotor areas of monkeys executing the SCT showed that most of the neural responses (54.2%) were aligned to the tapping movements instead of the stimuli used to drive the temporal behavior.

It has been proposed that a functional overlap exists in the brain for temporal and spatial information processing. To test this, we designed two relative categorization tasks in which human subjects and a Rhesus monkey had to assign time intervals or distances to a “short” or “long” category according to varying prototypes. The performance of both species was analyzed using psychometric techniques that showed that they may have similar perceptual, memory, and/or decision mechanisms, specially for the estimation of time intervals. We also did a correlation analysis with human subjects’ psychometric thresholds and the results imply that indeed, temporal and spatial information categorization share neural substrates. However, not all of the tested distances and intervals correlated with each other, suggesting the existence of sub-circuits that process restricted ranges of distances and intervals. A different analysis was done on the monkey data, in which the influence of the previous categorical prototypes was measured on the task currently being performed. Again, we found a significant interaction between previous and current interval and distance categorization. Overall, the present paper points toward common or at least partially overlapped neural circuits for temporal and spatial categorization in primates.

We used different tools from experimental psychology to obtain a broad picture of the possible neural underpinnings of temporal processing in the range of milliseconds. The temporal variability of human subjects was measured in timing tasks that differed in terms of: explicit-implicit timing, perception-production, single-multiple intervals, and auditory-visual interval markers. The results showed a dissociation between implicit and explicit timing. Inside explicit timing, we found a complex interaction in the temporal variability between tasks. These findings do not support neither a unique nor a ubiquitous mechanism for explicit timing, but support the notion of a partially distributed timing mechanism, integrated by main core structures such as the cortico-thalamic-basal ganglia circuit, and areas that are selectively engaged depending on the specific behavioral requirement of a task. A learning-generalization study of motor timing also supports this hypothesis and suggests that neurons of the timing circuit should be tuned to interval durations.

This article investigated both the ability of naive human subjects to learn interval production, as well as the properties of learning generalization across modalities and interval durations that varied systematically from the over-trained interval. Human subjects trained on a 450-, 650-, or 850-ms single-interval production task, using auditory stimuli to define the intervals, showed a significant decrease in performance variability with intensive training. This learning generalized to the visual modality and to non-trained durations following a Gaussian transfer pattern. However, the learning carryover followed different rules, depending on the duration of the trained interval as follows: (1) the dispersion of the generalization curve increased as a function of the trained interval, (2) the generalization pattern was tilted to the right in the visual condition, and (3) the transfer magnitude for 650 ms was less prominent than for the other two intervals. These findings suggest the existence of neural circuits that are tuned to specific time lengths and that show different temporal processing properties depending on their preferred interval duration.

This chapter describes the encoding and decoding properties of target parameters in the primate parietofrontal system during an interception task of stimuli in real and apparent motion. The stimulus moved along a circular path with one of 5 speeds (180–540 degrees/s), and was intercepted at 6 o’clock by exerting a force pulse on a joystick that controlled a cursor on the screen. The real stimuli moved smoothly along the circular path, whereas in the apparent motion situation five stimuli were flashed successively at the vertices of a regular pentagon. First, we include a description of the neural responses associated with temporal and spatial aspects of the targets with real and apparent motion. Then, using a selected population of cells that encoded the target’s angular position or time-to-contact, we tested the decoding power of the motor cortex and area 7a to reconstruct these variables in the real and apparent motion conditions. On the basis of these results, we suggest a possible neurophysiological mechanism involved in the integration of target information to trigger an interception movement.

We present a method for estimating the locations of sites visited by an array of microelectrodes. The method relies on visualization of tracks made by electrodes coated in a fluorescent dye. These tracks are used to estimate the parameters of a simple geometrical model that generates coordinates for each recording site. We describe several ways to measure the error of this procedure and present experimental results from recordings in the motor cortex of macaque monkeys that suggest that errors are of the order of 230 μm. We also introduce a coordinate transformation that takes into account the convoluted structure of the cortex near sulci to conveniently visualize recording site locations in a rectilinear representation. This method greatly extends the capabilities of microelectrodes for studying the three-dimensional structure of topographic maps in the cortex.

We compared quantitatively the psychometric capacity of human subjects to detect path-guided apparent motion (PAM) and the accuracy of cell ensembles in area 7a to code the same type of stimuli. Nine human subjects performed a detection task of PAM. They were instructed to indicate with a key-press whether they perceived a circularly moving object when five stimuli were flashed successively at the vertices of a regular pentagon. The stimuli were presented along a low contrast circular path with one of 33 speeds (150-600 degrees /s). The average psychometric curve revealed that the threshold for PAM detection was 314 degrees /s. The minimum and maximum thresholds for individual subjects were 277 degrees and 378 degrees /s, respectively. In addition, the activity of cells in area 7a that were modulated by the stimulus position in real or apparent motion was used in a multivariate linear regression analysis to recover the stimulus position over time. Real stimulus motion was decoded successfully from neural ensemble activity at all speeds. In contrast, the decoding of PAM was poor at low stimulus speeds but improved markedly above 300 degrees /s: in fact, this was very close to the threshold above for human subjects to perceive continuous stimulus motion in this condition. These results suggest that the posterior parietal cortex is part of a high-level system that is directly involved in the dynamic representation of complex motion.

Human subjects represent the location of a point in 2D space using two independent dimensions (x-y in Euclidean or radius-angle in polar space), and encode location in memory along these dimensions using two levels of representation: a fine-grain value and a category. Here we determined whether monkeys possessed the ability to represent location with these two levels of coding. A rhesus monkey was trained to reproduce the location of a dot in a circle by pointing, after a delay period, on the location where a dot was presented. Five different delay periods (0.5-5 s) were used. The results showed that the monkey used a polar coordinate system to represent the fine-grain spatial coding, where the radius and angle of the dots were encoded independently. The variability of the spatial response and reaction time increased with longer delays. Furthermore, the animal was able to form a categorical representation of space that was delay-dependent. The responses avoided the circumference and the center of the circle, defining a categorical radial prototype around one third of the total radial length. This radial category was observed only at delay durations of 3-5 s. Finally, the monkey also formed angular categories with prototypes at the obliques of the quadrants of the circle, avoiding the horizontal and vertical axes. However, these prototypes were only observed at the 5-s delay and on dots lying on the circumference. These results indicate that monkeys may possess spatial cognitive abilities similar to humans.

Human subjects and monkeys intercepted real (RM) and apparent (AM) moving targets that traveled through a low contrast circular path. The subjects intercepted the targets at 6 o'clock by applying a net force pulse on a semi-isometric joystick which controlled a cursor on the screen. Eight target speeds (180-560 degrees/s) were used. The starting points of the moving target were systematically placed around the circle in order to determine the effect of the target travel time and velocity on the decision to initiate the interception movement and on the interception accuracy. It was found that the probability of interception in the first revolution varied as a function of the target travel time, which followed an S-shaped psychometric curve. The minimum processing time (MPT) was defined as the target travel that corresponded to a 75% probability of interception in the first revolution on the psychometric curve. The MPT decreased slightly as a function of target speed and was larger in AM than RM. In addition, the interception accuracy increased when the target travel time was above the MPT, and the angular error was smaller in RM than in AM. Finally, the interception movement was initiated at different target locations and time-to-contacts, depending on the target speed and the motion condition. Interestingly, similar findings were observed in human subjects and monkeys. These results suggest that the neural mechanisms engaged in extracting the visual motion information and in the implementation of the response are more efficient during RM than AM, and that such mechanisms need less processing time when the target is moving faster.

In this paper we describe a type of neuron of the medial premotor cortex (MPC) that discharged differentially during a categorization task and reflected in their activity whether the speed of a tactile stimulus was low or high. The activity of these neurons was recorded in the MPC contralateral (right MPC, n = 88) and ipsilateral (left MPC, n = 103) to the stimulated hand of four monkeys performing this somesthetic task. Animals performed the task by pressing with the right hand one of two target switches to indicate whether the speed of probe movement across the skin of the left hand was low or high. Differential responses of MPC neurons occurred during the stimulus and reaction time period. We used an analysis based on signal detection theory to determine whether these differential responses were associated with the animal's decision. According to this analysis, 104 of the 191 neurons (right MPC, n = 48; left MPC, n = 56) coded the categorization of the stimulus speeds (categorical neurons). In a light instruction task, we tested the possibility that the categorical neurons (n = 71) were associated with the intention to press, or with the trajectory of the hand to one of the two target switches used to indicate categorization. In this situation, each trial began as in the somesthetic categorization task, but one of the two target switches was illuminated beginning with the skin indentation, continued during the delay period and turned off when the probe was lifted off from the skin. This condition instructed the animal which target switch was required to be pressed for reward. Very few neurons (14 of 71) maintained their differential responses observed in the categorization task. Some categorical neurons (n = 5) were also studied; the animal categorized the tactile stimulus speeds, but knew in advance whether the stimulus speed was low or high (categorization + light instruction). This was made by illuminating one of the two target switches which was associated with the stimulus speed. The categorical response was considerably attenuated in this condition. Interestingly, during the delay period, these neurons reflected in their activity whether the stimulus was low or high. A number of the categorical MPC neurons (n = 30) were studied when the same set of stimuli, used in the categorization, were delivered passively. None of these neurons responded in this condition. These results suggest that the MPC, apart from its well-known role in motor behavior, is also involved in the animal's decision during the execution of this learned somesthetic task.

In the present study we determined the performance interrelations of ten different tasks that involved the processing of temporal intervals in the subsecond range, using multidimensional analyses. Twenty human subjects executed the following explicit timing tasks: interval categorization and discrimination (perceptual tasks), and single and multiple interval tapping (production tasks). In addition, the subjects performed a continuous circle-drawing task that has been considered an implicit timing paradigm, since time is an emergent property of the produced spatial trajectory. All tasks could be also classified as single or multiple interval paradigms. Auditory or visual markers were used to define the intervals. Performance variability, a measure that reflects the temporal and non-temporal processes for each task, was used to construct a dissimilarity matrix that quantifies the distances between pairs of tasks. Hierarchical clustering and multidimensional scaling were carried out on the dissimilarity matrix, and the results showed a prominent segregation of explicit and implicit timing tasks, and a clear grouping between single and multiple interval paradigms. In contrast, other variables such as the marker modality were not as crucial to explain the performance between tasks. Thus, using this methodology we revealed a probable functional arrangement of neural systems engaged during different timing behaviors.

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’.