Motor cortical encoding of serial order in a context-recall task

Multiplicative joint coding in preparatory activity for reaching sequence in macaque motor cortex

Although the motor cortex has been found to be modulated by sensory or cognitive sequences, the linkage between multiple movement elements and sequence-related responses is not yet understood. Here, we recorded neuronal activity from the motor cortex with implanted micro-electrode arrays and single electrodes while monkeys performed a double-reach task that was instructed by simultaneously presented memorized cues. We found that there existed a substantial multiplicative component jointly tuned to impending and subsequent reaches during preparation, then the coding mechanism transferred to an additive manner during execution. This multiplicative joint coding, which also spontaneously emerged in recurrent neural networks trained for double reach, enriches neural patterns for sequential movement, and might explain the linear readout of elemental movements.

Temporal and Spatial Information Elicit Different Power and Connectivity Profiles during Working Memory Maintenance

Working memory (WM) is the cognitive ability to store and manipulate information necessary for ongoing tasks. Although frontoparietal areas are involved in the retention of visually presented information, oscillatory neural activity differs for temporal and spatial WM processing. In this study, we corroborated previous findings describing the modulation of neural oscillations and expanded our investigation to the network organization underlying the cognitive processing of temporal and spatial information. We utilized MEG recordings during a Sternberg visual WM task. The spectral oscillatory activity in the maintenance phase revealed increased frontal theta (4-8 Hz) and parietal beta (13-30 Hz) in the temporal condition. Source level coherence analysis delineated the prominent role of parietal areas in all frequency bands during the maintenance of temporal information, whereas frontal and central areas showed major contributions in theta and beta ranges during the maintenance of spatial information. Our study revealed distinct spectral profiles of neural oscillations for separate cognitive subdomains of WM processing. The delineation of specific functional networks might have important implications for clinical applications, enabling the development of stimulation protocols targeting cognitive disabilities associated with WM impairments.

Transcranial magnetic stimulation combined with endogenous human hippocampal and motor cortical activity enhances memory

The hippocampus is a fundamental cortical structure in the memory process of encoding, retaining, and recalling information. Transcranial Magnetic Stimulation (TMS) following a Paired Associative Stimulation (PAS) enhances nervous system excitability and promotes cortical plasticity mechanisms by synchronizing two stimuli in the same neural pathway. However, PAS has not been shown to improve memorization capacity yet. Here, we present an innovative protocol stemming from the PAS paradigm, which combines single-pulse TMS to the hippocampus with endogenous hippocampal activity during a working memory (WM) task. 96 volunteers were randomized across one experimental group and three parallel groups (motor cortex stimulation, sham stimulation, and no stimulation) in a single session. This combined-stimuli configuration resulted in an increased memorization capacity in the WM task, which was dependent on the stimulated brain location and subjects' basal memory performance. These results are potentially significant for clinical research on memory dysfunction and its related neurological disorders. Future research on paired associative or combined stimulation is required to unveil stimulation-derived neural mechanisms that enhance the ability to memorize.

Sequential order spatial memory in male rats: Characteristics and impact of medial prefrontal cortex and hippocampus disruption

Remembering an experience entails linking what happened, where the event transpired, and when it occurred. Most rodent hippocampal studies involve tests of spatial memory, but fewer investigate temporal and sequential order memory. Here we provide a demonstration of rats learning an aversive sequential order task using a radial arm water maze. Male rats learned a fixed sequence of up to seven spatial locations, with each decision session separated by a temporal delay. Rats relied on visuospatial cues and the number of times they had entered the maze for a given day in order to successfully perform the task. Behavioral patterns during asymptotic performance showed similarities to the serial-position effect, especially with regards to faster first choice latency. Rats at asymptotic performance were implanted with bilateral cannula in medial prefrontal cortex, dorsal, and ventral hippocampus. After re-training, we injected muscimol to temporarily disrupt targeted brain regions. While control rats made prospective errors, rats with mPFC muscimol exhibited more retrospective errors. Rats with hippocampal muscimol no longer exhibited a prospective bias and were at chance levels in their error choices. Taken together, our results suggest disruption of mPFC, but not the hippocampus, produced an error choice bias during an aversive sequential order spatial processing task.

Shared population-level dynamics in monkey premotor cortex during solo action, joint action and action observation

Studies of neural population dynamics of cell activity from monkey motor areas during reaching show that it mostly represents the generation and timing of motor behavior. We compared neural dynamics in dorsal premotor cortex (PMd) during the performance of a visuomotor task executed individually or cooperatively and during an observation task. In the visuomotor conditions, monkeys applied isometric forces on a joystick to guide a visual cursor in different directions, either alone or jointly with a conspecific. In the observation condition, they observed the cursor's motion guided by the partner. We found that in PMd neural dynamics were widely shared across action execution and observation, with cursor motion directions more accurately discriminated than task types. This suggests that PMd encodes spatial aspects irrespective of specific behavioral demands. Furthermore, our results suggest that largest components of premotor population dynamics, which have previously been suggested to reflect a transformation from planning to movement execution, may rather reflect higher cognitive-motor processes, such as the covert representation of actions and goals shared across tasks that require movement and those that do not.

Comparative Ultrastructural Analysis of Thalamocortical Innervation of the Primary Motor Cortex and Supplementary Motor Area in Control and MPTP-Treated Parkinsonian Monkeys

The synaptic organization of thalamic inputs to motor cortices remains poorly understood in primates. Thus, we compared the regional and synaptic connections of vGluT2-positive thalamocortical glutamatergic terminals in the supplementary motor area (SMA) and the primary motor cortex (M1) between control and MPTP-treated parkinsonian monkeys. In controls, vGluT2-containing fibers and terminal-like profiles invaded layer II-III and Vb of M1 and SMA. A significant reduction of vGluT2 labeling was found in layer Vb, but not in layer II-III, of parkinsonian animals, suggesting a potential thalamic denervation of deep cortical layers in parkinsonism. There was a significant difference in the pattern of synaptic connectivity in layers II-III, but not in layer Vb, between M1 and SMA of control monkeys. However, this difference was abolished in parkinsonian animals. No major difference was found in the proportion of perforated versus macular post-synaptic densities at thalamocortical synapses between control and parkinsonian monkeys in both cortical regions, except for a slight increase in the prevalence of perforated axo-dendritic synapses in the SMA of parkinsonian monkeys. Our findings suggest that disruption of the thalamic innervation of M1 and SMA may underlie pathophysiological changes of the motor thalamocortical loop in the state of parkinsonism.

Turning Touch into Perception

Many brain areas modulate their activity during vibrotactile tasks. The activity from these areas may code the stimulus parameters, stimulus perception, or perceptual reports. Here, we discuss findings obtained in behaving monkeys aimed to understand these processes. In brief, neurons from the somatosensory thalamus and primary somatosensory cortex (S1) only code the stimulus parameters during the stimulation periods. In contrast, areas downstream of S1 code the stimulus parameters during not only the task components but also perception. Surprisingly, the midbrain dopamine system is an actor not considered before in perception. We discuss the evidence that it codes the subjective magnitude of a sensory percept. The findings reviewed here may help us to understand where and how sensation transforms into perception in the brain.

Inhibition of protein synthesis in M1 of monkeys disrupts performance of sequential movements guided by memory

The production of action sequences is a fundamental aspect of motor skills. To examine whether primary motor cortex (M1) is involved in maintenance of sequential movements, we trained two monkeys (Cebus apella) to perform two sequential reaching tasks. In one task, sequential movements were instructed by visual cues, whereas in the other task, movements were generated from memory after extended practice. After the monkey became proficient with performing the tasks, we injected an inhibitor of protein synthesis, anisomycin, into M1 to disrupt information storage in this area. Injection of anisomycin in M1 had a marked effect on the performance of sequential movements that were guided by memory. In contrast, the anisomycin injection did not have a significant effect on the performance of movements guided by vision. These results suggest that M1 of non-human primates is involved in the maintenance of skilled sequential movements.

Action perception and motor imagery: Mental practice of action

Motor cognition is related to the planning and generation of actions as well as to the recognition and imagination of motor acts. Recently, there is evidence that the motor system participates not only in overt actions but also in mental processes supporting covert actions. Within this framework, we have investigated the cortical areas engaged in execution, observation, and imagination of the same action, by the use of the high resolution quantitative ¹⁴C-deoxyglucose method in monkeys and by fMRI in humans, throughout the entire primate brain. Our data demonstrated that observing or imagining an action excites virtually the same sensory-motor cortical network which supports execution of that same action. In general agreement with the results of five relevant meta-analyses that we discuss extensively, our results imply mental practice, i.e. internal rehearsal of the action including movements and their sensory effects. We suggest that we actively perceive and imagine actions by selecting and running off-line restored sensory-motor memories, by mentally simulating the actions. We provide empirical evidence that mental simulation of actions underlies motor cognition, and conceptual representations are grounded in sensory-motor codes. Motor cognition may, therefore, be embodied and modal. Finally, we consider questions regarding agency attribution and the possible causal or epiphenomenal role the involved sensory-motor network could play in motor cognition.

Cortical neural modulation by previous trial outcome differentiates fast- from slow-learning rats on a visuomotor directional choice task

To better understand the neural cortical underpinnings that explain behavioral differences in learning rate, we recorded single-unit activity in primary motor (M1) and secondary motor (M2) areas while rats learned to perform a directional (left or right) operant visuomotor association task. Analysis of neural activity during the early portion of the cue period showed that neural modulation in the motor cortex was most strongly associated with two task factors: the previous trial outcome (success or error) and the current trial's directional choice (left or right). Furthermore, the fast learners, defined as those who had steeper learning curves and required fewer learning sessions to reach criterion performance, encoded the previous trial outcome factor more strongly than the directional choice factor. Conversely, the slow learners encoded directional choice more strongly than previous trial outcome. These differences in task factor encoding were observed in both the percentage of neurons and the neural modulation depth. These results suggest that fast learning is accompanied by a stronger component of previous trial outcome in the modulation representation present in motor cortex, which therefore may be a contributing factor to behavioral differences in learning rate. NEW & NOTEWORTHY We chronically recorded neural activity as rats learned a visuomotor directional choice task from a naive state. Learning rates varied. Single-unit neural modulation of two motor areas revealed that the fast learners encoded previous trial outcome more strongly than directional choice, whereas the reverse was true for slow learners. This finding provides novel evidence that rat learning rate is strongly correlated with the strength of neural modulation by previous trial outcome in motor cortex.

Organizing Sequential Memory in a Neuromorphic Device Using Dynamic Neural Fields

Neuromorphic Very Large Scale Integration (VLSI) devices emulate the activation dynamics of biological neuronal networks using either mixed-signal analog/digital or purely digital electronic circuits. Using analog circuits in silicon to physically emulate the functionality of biological neurons and synapses enables faithful modeling of neural and synaptic dynamics at ultra low power consumption in real-time, and thus may serve as computational substrate for a new generation of efficient neural controllers for artificial intelligent systems. Although one of the main advantages of neural networks is their ability to perform on-line learning, only a small number of neuromorphic hardware devices implement this feature on-chip. In this work, we use a reconfigurable on-line learning spiking (ROLLS) neuromorphic processor chip to build a neuronal architecture for sequence learning. The proposed neuronal architecture uses the attractor properties of winner-takes-all (WTA) dynamics to cope with mismatch and noise in the ROLLS analog computing elements, and it uses its on-chip plasticity features to store sequences of states. We demonstrate, with a proof-of-concept feasibility study how this architecture can store, replay, and update sequences of states, induced by external inputs. Controlled by the attractor dynamics and an explicit destabilizing signal, the items in a sequence can last for varying amounts of time and thus reliable sequence learning and replay can be robustly implemented in a real sensorimotor system.

Encoding of Serial Order in Working Memory: Neuronal Activity in Motor, Premotor, and Prefrontal Cortex during a Memory Scanning Task

We have adapted Sternberg's context-recall task to investigate the neural mechanisms of encoding serial order information in working memory, in 2 male rhesus monkeys. We recorded from primary motor, premotor, and dorsolateral prefrontal cortex while the monkeys performed the task. In each cortical area, most neurons displayed marked modulation of activity during the list presentation period of the task, whereas the serial order of the stimuli needed to be encoded in working memory. The activity of many neurons changed in a consistent manner over the course of the list presentation period, without regard to the location of the stimuli presented. Remarkably, these neurons encoded serial position information in a relative (rather than absolute) manner across different list lengths. In addition, many neurons showed activity related to both location and serial position, in the form of an interaction effect. Surprisingly, the activity of these neurons was often modulated by the location of stimuli presented before the epoch in which the activity changes occurred. In motor and premotor areas, a large proportion of neurons with list presentation activity also showed direction-related activity during the response phase, whereas in prefrontal cortex most cells showed only list presentation effects. These results show that many neurons had a heterogeneous functionality by representing distinct task variables at different periods of the task. Finally, potential confounds could not account for the effects observed. For these reasons, we conclude that these neurons were indeed participating in sequence encoding in working memory.SIGNIFICANCE STATEMENT Traditionally, primary motor, premotor, and prefrontal areas have been considered to be mainly engaged in motor output, visuomotor transformation, and higher cognitive functions, respectively. Here we show that neurons in all three cortical regions participate in the encoding of a sequence of spatial stimuli in working memory. Furthermore, a central question in cognitive neuroscience has been the manner in which the position of an item within a sequence is encoded in the brain. Our findings provide direct neurophysiological support for a specific hypothesis from cognitive psychology: that of relative coding of serial order.

Object-based processes in the planning of goal-directed hand movements

Theories in motor control suggest that the parameters specified during the planning of goal-directed hand movements to a visual target are defined in spatial parameters like direction and amplitude. Recent findings in the visual attention literature, however, argue widely for early object-based selection processes. The present experiments were designed to examine the contributions of object-based and space-based selection processes to the preparation time of goal-directed pointing movements. Therefore, a cue was presented at a specific location. The question addressed was whether the initiation of responses to uncued target stimuli could benefit from being either within the same object (object based) or presented at the same direction (space based). Experiment 1 replicated earlier findings of object-based benefits for non-goal-directed responses. Experiment 2 confirmed earlier findings of space-based benefits for goal-directed hand pointing movements. In Experiments 3 and 4, space-based and object-based manipulations were combined while requiring goal-directed hand pointing movements. The results clearly favour the notion that the selection processes for goal-directed pointing movements are primarily object based. Implications for theories on selective attention and action planning are discussed.

Population-Level Representation of a Temporal Sequence Underlying Song Production in the Zebra Finch

The zebra finch brain features a set of clearly defined and hierarchically arranged motor nuclei that are selectively responsible for producing singing behavior. One of these regions, a critical forebrain structure called HVC, contains premotor neurons that are active at precise time points during song production. However, the neural representation of this behavior at a population level remains elusive. We used two-photon microscopy to monitor ensemble activity during singing, integrating across multiple trials by adopting a Bayesian inference approach to more precisely estimate burst timing. Additionally, we examined spiking and motor-related synaptic inputs using intracellular recordings during singing. With both experimental approaches, we find that premotor events do not occur preferentially at the onsets or offsets of song syllables or at specific subsyllabic motor landmarks. These results strongly support the notion that HVC projection neurons collectively exhibit a temporal sequence during singing that is uncoupled from ongoing movements.

From the motor cortex to the movement and back again

The motor cortex controls motor behaviors by generating movement-specific signals and transmitting them through spinal cord circuits and motoneurons to the muscles. Precise and well-coordinated muscle activation patterns are necessary for accurate movement execution. Therefore, the activity of cortical neurons should correlate with movement parameters. To investigate the specifics of such correlations among activities of the motor cortex, spinal cord network and muscles, we developed a model for neural control of goal-directed reaching movements that simulates the entire pathway from the motor cortex through spinal cord circuits to the muscles controlling arm movements. In this model, the arm consists of two joints (shoulder and elbow), whose movements are actuated by six muscles (4 single-joint and 2 double-joint flexors and extensors). The muscles provide afferent feedback to the spinal cord circuits. Cortical neurons are defined as cortical "controllers" that solve an inverse problem based on a proposed straight-line trajectory to a target position and a predefined bell-shaped velocity profile. Thus, the controller generates a motor program that produces a task-specific activation of low-level spinal circuits that in turn induce the muscle activation realizing the intended reaching movement. Using the model, we describe the mechanisms of correlation between cortical and motoneuronal activities and movement direction and other movement parameters. We show that the directional modulation of neuronal activity in the motor cortex and the spinal cord may result from direction-specific dynamics of muscle lengths. Our model suggests that directional modulation first emerges at the level of muscle forces, augments at the motoneuron level, and further increases at the level of the motor cortex due to the dependence of frictional forces in the joints, contractility of the muscles and afferent feedback on muscle lengths and/or velocities.

Reading positional codes with fMRI: Problems and solutions

Neural mechanisms which bind items into sequences have been investigated in a large body of research in animal neurophysiology and human neuroimaging. However, a major problem in interpreting this data arises from a fact that several unrelated processes, such as memory load, sensory adaptation, and reward expectation, also change in a consistent manner as the sequence unfolds. In this paper we use computational simulations and data from two fMRI experiments to show that a host of unrelated neural processes can masquerade as sequence representations. We show that dissociating such unrelated processes from a dedicated sequence representation is an especially difficult problem for fMRI data, which is almost exclusively the modality used in human experiments. We suggest that such fMRI results must be treated with caution and in many cases the assumed neural representation might actually reflect unrelated processes.

Brain-Machine Interfaces: From Basic Science to Neuroprostheses and Neurorehabilitation

Brain-machine interfaces (BMIs) combine methods, approaches, and concepts derived from neurophysiology, computer science, and engineering in an effort to establish real-time bidirectional links between living brains and artificial actuators. Although theoretical propositions and some proof of concept experiments on directly linking the brains with machines date back to the early 1960s, BMI research only took off in earnest at the end of the 1990s, when this approach became intimately linked to new neurophysiological methods for sampling large-scale brain activity. The classic goals of BMIs are 1) to unveil and utilize principles of operation and plastic properties of the distributed and dynamic circuits of the brain and 2) to create new therapies to restore mobility and sensations to severely disabled patients. Over the past decade, a wide range of BMI applications have emerged, which considerably expanded these original goals. BMI studies have shown neural control over the movements of robotic and virtual actuators that enact both upper and lower limb functions. Furthermore, BMIs have also incorporated ways to deliver sensory feedback, generated from external actuators, back to the brain. BMI research has been at the forefront of many neurophysiological discoveries, including the demonstration that, through continuous use, artificial tools can be assimilated by the primate brain's body schema. Work on BMIs has also led to the introduction of novel neurorehabilitation strategies. As a result of these efforts, long-term continuous BMI use has been recently implicated with the induction of partial neurological recovery in spinal cord injury patients.

Computational Architecture of the Parieto-Frontal Network Underlying Cognitive-Motor Control in Monkeys

The statistical structure of intrinsic parietal and parieto-frontal connectivity in monkeys was studied through hierarchical cluster analysis. Based on their inputs, parietal and frontal areas were grouped into different clusters, including a variable number of areas that in most instances occupied contiguous architectonic fields. Connectivity tended to be stronger locally: that is, within areas of the same cluster. Distant frontal and parietal areas were targeted through connections that in most instances were reciprocal and often of different strength. These connections linked parietal and frontal clusters formed by areas sharing basic functional properties. This led to five different medio-laterally oriented pillar domains spanning the entire extent of the parieto-frontal system, in the posterior parietal, anterior parietal, cingulate, frontal, and prefrontal cortex. Different information processing streams could be identified thanks to inter-domain connectivity. These streams encode fast hand reaching and its control, complex visuomotor action spaces, hand grasping, action/intention recognition, oculomotor intention and visual attention, behavioral goals and strategies, and reward and decision value outcome. Most of these streams converge on the cingulate domain, the main hub of the system. All of them are embedded within a larger eye–hand coordination network, from which they can be selectively set in motion by task demands.

Primary Motor Area Activation during Precision-Demanding versus Simple Finger Movement

The authors used functional magnetic resonance imaging to explore whether the primary motor area (M1) serves a processing role in a finger-movement tracking task, emphasizing attention to accuracy, beyond its execution role of simple movements, with no attention to accuracy. Twenty healthy subjects performed alternating conditions: Rest, involving no finger movement; Track, involving careful control of a cursor along a target pathway with finger extension/flexion movements; and Move, involving finger extension/flexion movements without careful control. The authors compared volume of activated voxels in the M1, blood-oxygen-level-dependent (BOLD) signal intensity of activated voxels in the M1, and BOLD signal intensity of all voxels in the M1 between the Track and Move conditions. The results showed greater volume and signal intensity in both the contralateral and ipsilateral M1 during Track than during Move. Overall, the results suggest that the M1 is engaged not only in the execution of movements but also in spatial and temporal processing to produce accurately controlled movements. These findings invite further work exploring whether precision-demanding movements, such as tracking, form a more potent stimulus for promoting helpful brain reorganization in the M1 during the recovery from stroke than simple repetitive movements.

New Views of the Primary Motor Cortex

For 100 years, from the 1870s to the 1970s, somatotopic organization was considered the hallmark of the primary motor cortex (M1). M1 neurons were viewed as upper motor neurons, implying that their organization and function were upstream versions of the spinal motoneurons to which they project. Taken together, the notions of somatotopic organization and upper motor neurons established a view of M1 as a sheet of somatotopically arrayed neurons that controlled either the muscles or the movements of different body parts. Evidence accumulating since the 1970s, however, has generated new views of M1 at an accelerating pace. Here, I briefly review evidence leading to three new views of M1. First, whereas the gross somatotopic organization of M1—with the head represented laterally, the lower extremity medially, and the upper extremity in between—is unquestioned, we now view representation within the upper extremity region (from which the most evidence is available) as widely distributed. Second, rather than a fixed array of representation, we now view M1 as capable of considerable, and surprisingly rapid, reorganization. And third, rather than simply controlling the parameters of movement execution, we now view M1 as participating in aspects of sensorimotor transformation that include some representation of the sensory cues leading to voluntary movement. Although these new views account for a good deal of recent experimental evidence, they also open many new questions about the primary motor cortex.

The Cognitive Side of M1

The primary motor cortex (M1) is traditionally implicated in voluntary movement control. In order to test the hypothesis that there is a functional topography of M1 activation in studies where it has been implicated in higher cognitive tasks we performed activation-likelihood-estimation (ALE) meta-analyses of functional neuroimaging experiments reporting M1 activation in relation to six cognitive functional categories for which there was a sufficient number of studies to include, namely motor imagery, working memory, mental rotation, social/emotion/empathy, language, and auditory processing. The six categories activated different sub-sectors of M1, either bilaterally or lateralized to one hemisphere. Notably, the activations found in the M1 of the left or right hemisphere detected in our study were unlikely due to button presses. In fact, all contrasts were selected in order to eliminate M1 activation due to activity related to the finger button press. In addition, we identified the M1 sub-region of Area 4a commonly activated by 4/6 categories, namely motor imagery and working memory, emotion/empathy, and language. Overall, our findings lend support to the idea that there is a functional topography of M1 activation in studies where it has been found activated in higher cognitive tasks and that the left Area 4a can be involved in a number of cognitive processes, likely as a product of implicit mental simulation processing.

Insights into Seeing and Grasping: Distinguishing the Neural Correlates of Perception and Action

Vision contributes to both perception and visuomotor control, and it has been suggested that many higher brain structures specialize in one or the other function. An alternative view, presented here, is that most higher brain areas participate in both visuomotor and perceptual functions. In the anterior frontal cortex, for example, the activity of one population of neurons reflects perceptual reports about a visual stimulus, whereas the activity of an intermingled population reflects movements aimed at the same stimulus. Similarly, posterior parietal and inferior temporal areas appear to function in both visual perception and visuomotor control. Visuomotor signals in higher order cortical areas could contribute to the perception of one’s own action. They also might reflect the existence of two systems for visual information processing: one stressing accuracy for the control of movement and the other generating hypotheses about the world.

The primary motor cortex is involved in the control of a non-motor cognitive action

OBJECTIVE

Adaptive interactions with the outer world necessitate effective connections between cognitive and executive functions. The primary motor cortex (M1) with its control of the spinal cord motor apparatus and its involvement in the processing of cognitive information related to motor functions is one of the best suited structures of this cognition-action connection. The question arose whether M1 might be involved also in situations where no overt or covered motor action is present.

METHODS

The EEG data analyzed were recorded during an oddball task in one epileptic patient (19 years) with depth multilead electrodes implanted for diagnostic reasons into the M1 and several prefrontal areas.

RESULTS

The main result was the finding of an evoked response to non-target stimuli with a pronounced late component in all frontal areas explored, including three loci of the M1. The late component was implicated in the evaluation of predicted and actual action and was synchronized in all three precentral loci and in the majority of prefrontal loci.

CONCLUSION

The finding is considered as direct evidence of functional involvement of the M1 in cognitive activity not related to motor function.

SIGNIFICANCE

Our results contribute to better understanding of neural mechanisms underlying cognition.

Dynamic reorganization of neural activity in motor cortex during new sequence production

Although previous studies have shown that primary motor cortex (M1) neurons are modulated during the performance of a sequence of movements, it is not known how this neural activity in the M1 reorganizes during new learning of sequence-dependent motor skills. Here we trained monkeys to move to each of four spatial targets to produce multiple distinct sequences of movements in which the spatial organization of the targets determined uniquely the serial order of the movements. After the monkeys memorized the sequences, we changed one element of these over-practised sequences and the subjects were required to learn the new sequence through trial and error. When one element in an over-learned four-element sequence was changed, the sequence-specific neural activity was totally disrupted, but relatively minor changes in the direction-specific activity were observed. The data suggest that sequential motor skills are represented within M1 in the context of the complete sequential behavior rather than as a series of single consecutive movements; and sequence-specific neurons in the M1 are involved in new learning of sequence by using memorized knowledge to acquire complex motor skill efficiently.

Organization and evolution of parieto-frontal processing streams in macaque monkeys and humans

The functional organization of the parieto-frontal system is crucial for understanding cognitive-motor behavior and provides the basis for interpreting the consequences of parietal lesions in humans from a neurobiological perspective. The parieto-frontal connectivity defines some main information streams that, rather than being devoted to restricted functions, underlie a rich behavioral repertoire. Surprisingly, from macaque to humans, evolution has added only a few, new functional streams, increasing however their complexity and encoding power. In fact, the characterization of the conduction times of parietal and frontal areas to different target structures has recently opened a new window on cortical dynamics, suggesting that evolution has amplified the probability of dynamic interactions between the nodes of the network, thanks to communication patterns based on temporally-dispersed conduction delays. This might allow the representation of sensory-motor signals within multiple neural assemblies and reference frames, as to optimize sensory-motor remapping within an action space characterized by different and more complex demands across evolution.

Improved discriminability of spatiotemporal neural patterns in rat motor cortical areas as directional choice learning progresses

Animals learn to choose a proper action among alternatives to improve their odds of success in food foraging and other activities critical for survival. Through trial-and-error, they learn correct associations between their choices and external stimuli. While a neural network that underlies such learning process has been identified at a high level, it is still unclear how individual neurons and a neural ensemble adapt as learning progresses. In this study, we monitored the activity of single units in the rat medial and lateral agranular (AGm and AGl, respectively) areas as rats learned to make a left or right side lever press in response to a left or right side light cue. We noticed that rat movement parameters during the performance of the directional choice task quickly became stereotyped during the first 2–3 days or sessions. But learning the directional choice problem took weeks to occur. Accompanying rats' behavioral performance adaptation, we observed neural modulation by directional choice in recorded single units. Our analysis shows that ensemble mean firing rates in the cue-on period did not change significantly as learning progressed, and the ensemble mean rate difference between left and right side choices did not show a clear trend of change either. However, the spatiotemporal firing patterns of the neural ensemble exhibited improved discriminability between the two directional choices through learning. These results suggest a spatiotemporal neural coding scheme in a motor cortical neural ensemble that may be responsible for and contributing to learning the directional choice task.

Cortical neural responses to previous trial outcome during learning of a directional choice task

The outcomes that result from previous behavior affect future choices in several ways, but the neural mechanisms underlying these effects remain to be determined. Previous studies have shown that the lateral (AGl) and medial (AGm) agranular areas of the rat frontal cortex are involved in the learning and selection of action. Here we describe the activity of single neurons in AGl and AGm as rats learned to perform a directional choice task. Our analysis shows that single-cell activity in AGl and AGm was modulated by the outcome of the previous trial. A larger proportion of neurons encoded the previous trial's outcome shortly after cue onset than during other time periods of a trial. Most of these neurons had greater activity after correct trials than after error trials, a difference that increased as behavioral performance improved. The number of neurons encoding the previous trial's outcome correlated positively with performance accuracy. In summary, we found that neurons in both AGl and AGm encode the outcome of the immediately preceding trial, information that might play a role in the successful selection of action based on past experience.

Bottlenecks to clinical translation of direct brain-computer interfaces

Despite several decades of research into novel brain-implantable devices to treat a range of diseases, only two—cochlear implants for sensorineural hearing loss and deep brain stimulation for movement disorders—have yielded any appreciable clinical benefit. Obstacles to translation include technical factors (e.g., signal loss due to gliosis or micromotion), lack of awareness of current clinical options for patients that the new therapy must outperform, traversing between federal and corporate funding needed to support clinical trials, and insufficient management expertise. This commentary reviews these obstacles preventing the translation of promising new neurotechnologies into clinical application and suggests some principles that interdisciplinary teams in academia and industry could adopt to enhance their chances of success.

Patterns of modulation in the activity and connectivity of motor cortex during the repeated generation of movement sequences

It is not clear how the engagement of motor mnemonic processes is expressed in online brain activity. We scanned participants, using fMRI, during the paced performance of a finger-to-thumb opposition sequence (FOS), intensively trained a day earlier (T-FOS), and a similarly constructed, but novel, untrained FOS (U-FOS). Both movement sequences were performed in pairs of blocks separated by a brief rest interval (30 sec). We have recently shown that in the primary motor cortex (M1) motor memory was not expressed in the average signal intensity but rather in the across-block signal modulations, that is, when comparing the first to the second performance block across the brief rest interval. Here, using an M1 seed, we show that for the T-FOS, the M1-striatum functional connectivity decreased across blocks; however, for the U-FOS, connectivity within the M1 and between M1 and striatum increased. In addition, in M1, the pattern of within-block signal change, but not signal variability per se, reliably differentiated the two sequences. Only for the U-FOS and only within the first blocks in each pair, the signal significantly decreased. No such modulation was found within the second corresponding blocks following the brief rest interval in either FOS. We propose that a network including M1 and striatum underlies online motor working memory. This network may promote a transient integrated representation of a new movement sequence and readily retrieves a previously established movement sequence representation. Averaging over single events or blocks may not capture the dynamics of motor representations that occur over multiple timescales.

Acupuncture on GB34 activates the precentral gyrus and prefrontal cortex in Parkinson's disease

BACKGROUND

Acupuncture is increasingly used as an additional treatment for patients with Parkinson's disease (PD).

METHODS

In this functional magnetic resonance imaging study, brain activation in response to acupuncture in a group of 12 patients with PD was compared with a group of 12 healthy participants. Acupuncture was conducted on a specific acupoint, the right GB 34 (Yanglingquan), which is a frequently used acupoint for motor function treatment in the oriental medical field.

RESULTS

Acupuncture stimulation on this acupoint activates the prefrontal cortex, precentral gyrus, and putamen in patients with PD; areas that are known to be impaired in patients with PD. Compared with healthy participants, patients with PD showed significantly higher brain activity in the prefrontal cortex and precentral gyrus, especially visible in the left hemisphere.

CONCLUSIONS

The neuroimaging results of our study suggest that in future acupuncture research; the prefrontal cortex as well as the precentral gyrus should be treated for symptoms of Parkinson's disease and that GB 34 seems to be a suitable acupoint. Moreover, acupuncture evoked different brain activations in patients with Parkinson's disease than in healthy participants in our study, stressing the importance of conducting acupuncture studies on both healthy participants as well as patients within the same study, in order to detect acupuncture efficacy.

TRIAL REGISTRATION

KCT0001122 at cris.nih.go.kr (registration date: 20140530).

Cognitive-motor interactions of the basal ganglia in development

Neural circuits linking activity in anatomically segregated populations of neurons in subcortical structures and the neocortex throughout the human brain regulate complex behaviors such as walking, talking, language comprehension, and other cognitive functions associated with frontal lobes. The basal ganglia, which regulate motor control, are also crucial elements in the circuits that confer human reasoning and adaptive function. The basal ganglia are key elements in the control of reward-based learning, sequencing, discrete elements that constitute a complete motor act, and cognitive function. Imaging studies of intact human subjects and electrophysiologic and tracer studies of the brains and behavior of other species confirm these findings. We know that the relation between the basal ganglia and the cerebral cortical region allows for connections organized into discrete circuits. Rather than serving as a means for widespread cortical areas to gain access to the motor system, these loops reciprocally interconnect a large and diverse set of cerebral cortical areas with the basal ganglia. Neuronal activity within the basal ganglia associated with motor areas of the cerebral cortex is highly correlated with parameters of movement. Neuronal activity within the basal ganglia and cerebellar loops associated with the prefrontal cortex is related to the aspects of cognitive function. Thus, individual loops appear to be involved in distinct behavioral functions. Damage to the basal ganglia of circuits with motor areas of the cortex leads to motor symptoms, whereas damage to the subcortical components of circuits with non-motor areas of the cortex causes higher-order deficits. In this report, we review some of the anatomic, physiologic, and behavioral findings that have contributed to a reappraisal of function concerning the basal ganglia and cerebellar loops with the cerebral cortex and apply it in clinical applications to attention deficit/hyperactivity disorder (ADHD) with biomechanics and a discussion of retention of primitive reflexes being highly associated with the condition.

Dorsal parietal area 5 encodes immediate reach in sequential arm movements

To generate a coherent action sequence, it is essential to integrate all component movements beforehand, and such sequence-related information has been observed in numerous brain regions. However, this high-level sequential plan encompassing multiple motor elements in parallel ultimately must be decomposed into serial motor commands to be executed by the musculoskeletal system. In the present study, we recorded single-neuron activity from dorsal parietal area 5 (area 5d) while monkeys performed a double-reach task, and found that area 5d conveys the immediate upcoming reach, but not the subsequent movement, as opposed to the entire movement sequence being encoded as in other cortical sensorimotor areas. The elementary movement coded in area 5d suggests that unfolding of the motor sequence begins in the parietal-frontal cortex, instead of being exclusively implemented by downstream subcortical and spinal circuits.

Compositionality in neural control: an interdisciplinary study of scribbling movements in primates

This article discusses the compositional structure of hand movements by analyzing and modeling neural and behavioral data obtained from experiments where a monkey (Macaca fascicularis) performed scribbling movements induced by a search task. Using geometrically based approaches to movement segmentation, it is shown that the hand trajectories are composed of elementary segments that are primarily parabolic in shape. The segments could be categorized into a small number of classes on the basis of decreasing intra-class variance over the course of training. A separate classification of the neural data employing a hidden Markov model showed a coincidence of the neural states with the behavioral categories. An additional analysis of both types of data by a data mining method provided evidence that the neural activity patterns underlying the behavioral primitives were formed by sets of specific and precise spike patterns. A geometric description of the movement trajectories, together with precise neural timing data indicates a compositional variant of a realistic synfire chain model. This model reproduces the typical shapes and temporal properties of the trajectories; hence the structure and composition of the primitives may reflect meaningful behavior.

A comparison of lateral and medial intraparietal areas during a visual categorization task

Categorization is essential for interpreting sensory stimuli and guiding our actions. Recent studies have revealed robust neuronal category representations in the lateral intraparietal area (LIP). Here, we examine the specialization of LIP for categorization and the roles of other parietal areas by comparing LIP and the medial intraparietal area (MIP) during a visual categorization task. MIP is involved in goal-directed arm movements and visuomotor coordination but has not been implicated in non-motor cognitive functions, such as categorization. As expected, we found strong category encoding in LIP. Interestingly, we also observed category signals in MIP. However, category signals were stronger and appeared with a shorter latency in LIP than MIP. In this task, monkeys indicated whether a test stimulus was a category match to a previous sample with a manual response. Test-period activity in LIP showed category encoding and distinguished between matches and non-matches. In contrast, MIP primarily reflected the match/non-match status of test stimuli, with a strong preference for matches (which required a motor response). This suggests that, although category representations are distributed across parietal cortex, LIP and MIP play distinct roles: LIP appears more involved in the categorization process itself, whereas MIP is more closely tied to decision-related motor actions.

Computing reaching dynamics in motor cortex with Cartesian spatial coordinates

How neurons in the primary motor cortex control arm movements is not yet understood. Here we show that the equations of motion governing reaching simplify when expressed in spatial coordinates. In this fixed reference frame, joint torques are the sums of vector cross products between the spatial positions of limb segments and their spatial accelerations and velocities. The consequences that follow from this model explain many properties of neurons in the motor cortex, including directional broad, cosinelike tuning, nonuniformly distributed preferred directions dependent on the workspace, and the rotation of the population vector during arm movements. Remarkably, the torques can be directly computed as a linearly weighted sum of responses from cortical motoneurons, and the muscle tensions can be obtained as rectified linear sums of the joint torques. This allows the required muscle tensions to be computed rapidly from a trajectory in space with a feedforward network model.

Midbrain contributions to sensorimotor decision making

Making decisions about future actions is a fundamental function of the nervous system. Classical theories hold that separate sets of brain regions are responsible for selecting and implementing an action. Traditionally, action selection has been considered the domain of high-level regions, such as the prefrontal cortex, whereas action generation is thought to be carried out by dedicated cortical and subcortical motor regions. However, increasing evidence suggests that the activity of individual neurons in cortical motor structures reflects abstract properties of "decision variables" rather than conveying simple motor commands. Less is known, though, about the role of subcortical structures in decision making. In particular, the superior colliculus (SC) is critical for planning and initiating visually guided, gaze-displacing movements and selecting visual targets, but whether and how it contributes more generally to sensorimotor decisions are unclear. Here, we show that the SC is intimately involved in orienting decisions based on odor cues, even though the SC does not explicitly process olfactory stimuli. Neurons were recorded from the intermediate and deep SC layers in rats trained to perform a delayed-response, odor-cued spatial choice task. SC neurons commonly fired well in advance of movement initiation, predicting the chosen direction nearly 1 s before movement. Moreover, under conditions of sensory uncertainty, SC activity varied with task difficulty and reward outcome, reflecting the influence of decision variables on the intercollicular competition thought to underlie orienting movements. These results indicate that the SC plays a more general role in decisions than previously appreciated, extending beyond visuomotor functions.

Conversion of sensory signals into perceptual decisions

A fundamental problem in neurobiology is to understand how brain circuits represent sensory information and how such representations give rise to perception, memory and decision-making. We demonstrate that a sensory stimulus engages multiple areas of the cerebral cortex, including primary sensory, prefrontal, premotor and motor cortices. As information transverses the cortical circuits it shows progressively more relation to perception, memory and decision reports. In particular, we show how somatosensory areas on the parietal lobe generate a parameterized representation of a tactile stimulus. This representation is maintained in working memory by prefrontal and premotor areas of the frontal lobe. The presentation of a second stimulus, that monkeys are trained to compare with the first, generates decision-related activity reflecting which stimulus had the higher frequency. Importantly, decision-related activity is observed across several cortical circuits including prefrontal, premotor and parietal cortices. Sensory information is encoded by neuronal populations with opposite tuning, and suggests that a simple subtraction operation could be the underlying mechanism by which past and present sensory information is compared to generate perceptual decisions.

Parallel contributions of cerebellar, striatal and M1 mechanisms to motor sequence learning

When learning a new motor sequence, we must execute the correct order of movements while simultaneously optimizing sensorimotor parameters such as trajectory, timing, velocity and force. Neurophysiological studies in animals and humans have identified the major brain regions involved in sequence learning, including the motor cortex (M1), basal ganglia (BG) and cerebellum. Current models link these regions to different stages of learning (early vs. late) or different components of performance (spatial vs. sensorimotor). At the same time, research in motor control has given rise to the concept that internal models at different levels of the motor system may contribute to learning. The goal of this review is to develop a new framework for motor sequence learning that combines stage and component models within the context of internal models. To do this, we review behavioral and neuroimaging studies in humans and neurophysiological studies in animals. Based on this evidence, we present a model proposing that sequence learning is underwritten by parallel, interacting processes, including internal model formation and sequence representation, that are instantiated in specific cerebellar, BG or M1 mechanisms depending on task demands and the stage of learning. The striatal system learns predictive stimulus-response associations and is critical for motor chunking. The role of the cerebellum is to acquire the optimal internal model for sequence performance in a particular context, and to contribute to error correction and control of on-going movement. M1 acts to store the representation of a learned sequence, likely as part of a distributed network including the parietal lobe and premotor cortex.

Neuroplasticity of the sensorimotor cortex during learning

We will discuss some of the current issues in understanding plasticity in the sensorimotor (SM) cortices on the behavioral, neurophysiological, and synaptic levels. We will focus our paper on reaching and grasping movements in the rat. In addition, we will discuss our preliminary work utilizing inhibition of protein kinase Mζ (PKMζ), which has recently been shown necessary and sufficient for the maintenance of long-term potentiation (LTP) (Ling et al., 2002). With this new knowledge and inhibitors to this system, as well as the ability to overexpress this system, we can start to directly modulate LTP and determine its influence on behavior as well as network level processing dependent at least in part due to this form of LTP. We will also briefly introduce the use of brain machine interface (BMI) paradigms to ask questions about sensorimotor plasticity and discuss current analysis techniques that may help in our understanding of neuroplasticity.

Compositionality of arm movements can be realized by propagating synchrony

We present a biologically plausible spiking neuronal network model of free monkey scribbling that reproduces experimental findings on cortical activity and the properties of the scribbling trajectory. The model is based on the idea that synfire chains can encode movement primitives. Here, we map the propagation of activity in a chain to a linearly evolving preferred velocity, which results in parabolic segments that fulfill the two-thirds power law. Connections between chains that match the final velocity of one encoded primitive to the initial velocity of the next allow the composition of random sequences of primitives with smooth transitions. The model provides an explanation for the segmentation of the trajectory and the experimentally observed deviations of the trajectory from the parabolic shape at primitive transition sites. Furthermore, the model predicts low frequency oscillations (<10 Hz) of the motor cortex local field potential during ongoing movements and increasing firing rates of non-specific motor cortex neurons before movement onset.

Decoding a perceptual decision process across cortex

Perceptual decisions arise from the activity of neurons distributed across brain circuits. But, decoding the mechanisms behind this cognitive operation across brain circuits has long posed a difficult problem. We recorded the neuronal activity of diverse cortical areas, while monkeys performed a vibrotactile discrimination task. We find that the encoding of the stimuli during the stimulus periods, working memory, and comparison periods is widely distributed across cortical areas. Notably, during the comparison and postponed decision report periods the activity of frontal brain circuits encode both the result of the sensory evaluation that corresponds to the monkey's possible choices and past information on which the decision is based. These results suggest that frontal lobe circuits are more engaged in the readout of sensory information from working memory, when it is required to be compared with other sensory inputs, than simply engaged in motor responses during this task.

Rhythmic muscular activation pattern for fast figure-eight movement

OBJECTIVE

To address the question of how the CNS generates muscle activation patterns for complex gestures, we have chosen to study a figure-eight movement. We hypothesized that the well defined rhythmic aspect of this figure will provide further insights into the temporal features of multi-muscular commands.

METHODS

Subjects performed, as fast as possible, figure-eights initiated in the center of the figure with 4 different initial directions and 2 positions of the shoulder. We extracted the temporal modulation of the EMG patterns by calculating conjugate cross-correlation functions.

RESULTS

(1) The muscular command was tuned with respect to the rotational direction of the figure-eight, (2) two sets of synergistic muscles acted in a reciprocal mode, and (3) these reciprocal commands presented an invariant temporal correlation with the spatial component of the velocity having the highest frequency.

CONCLUSION

Our results suggest that the rhythmic features of certain drawing movements favor the partitioning of the muscles into synergistic groups acting in a reciprocal mode. The inclusion of an individual muscle in one group or the other takes into account the expected number of changes of direction in the movement as a whole.

SIGNIFICANCE

Muscular temporal synergies may depend on the rhythmic features of the trajectory.

Response-dependent contributions of human primary motor cortex and angular gyrus to manual and perceptual sequence learning

Motor sequence learning on the serial reaction time task involves the integration of response-, stimulus-, and effector-based information. Human primary motor cortex (M1) and the inferior parietal lobule (IPL) have been identified with supporting the learning of effector-dependent and -independent information, respectively. Current neurocognitive data are, however, exclusively based on learning complex sequence information via perceptual-motor responses. Here, we investigated the effects of continuous theta-burst transcranial magnetic stimulation (cTBS)-induced disruption of M1 and the angular gyrus (AG) of the IPL on learning a probabilistic sequence via sequential perceptual-motor responses (experiment 1) or covert orienting of visuospatial attention (experiment 2). Functional effects on manual sequence learning were evident during 75% of training trials in the cTBS M1 condition, whereas cTBS over the AG resulted in interference confined to a midpoint during the training phase. Posttraining direct (declarative) tests of sequence knowledge revealed that cTBS over M1 modulated the availability of newly acquired sequence knowledge, whereby sequence knowledge was implicit in the cTBS M1 condition but was available to conscious awareness in the cTBS AG and control conditions. In contrast, perceptual sequence learning was abolished in the perceptual cTBS AG condition, whereas learning was intact and available to conscious awareness in the cTBS M1 and control conditions. These results show that the right AG had a critical role in perceptual sequence learning, whereas M1 had a causal role in developing experience-dependent functional attributes relevant to conscious knowledge on manual but not perceptual sequence learning.

Dynamic encoding of movement direction in motor cortical neurons

When we perform a skilled movement such as reaching for an object, we can make use of prior information, for example about the location of the object in space. This helps us to prepare the movement, and we gain improved accuracy and speed during movement execution. Here, we investigate how prior information affects the motor cortical representation of movements during preparation and execution. We trained two monkeys in a delayed reaching task and provided a varying degree of prior information about the final target location. We decoded movement direction from multiple single-unit activity recorded from M1 (primary motor cortex) in one monkey and from PMd (dorsal premotor cortex) in a second monkey. Our results demonstrate that motor cortical cells in both areas exhibit individual encoding characteristics that change dynamically in time and dependent on prior information. On the population level, the information about movement direction is at any point in time accurately represented in a neuronal ensemble of time-varying composition. We conclude that movement representation in the motor cortex is not a static one, but one in which neurons dynamically allocate their computational resources to meet the demands defined by the movement task and the context of the movement. Consequently, we find that the decoding accuracy decreases if the precise task time, or the previous information that was available to the monkey, were disregarded in the decoding process. An optimal strategy for the readout of movement parameters from motor cortex should therefore take into account time and contextual parameters.

Representation of number in the brain

Number symbols have allowed humans to develop superior mathematical skills that are a hallmark of technologically advanced cultures. Findings in animal cognition, developmental psychology, and anthropology indicate that these numerical skills are rooted in nonlinguistic biological primitives. Recent studies in human and nonhuman primates using a broad range of methodologies provide evidence that numerical information is represented and processed by regions of the prefrontal and posterior parietal lobes, with the intraparietal sulcus as a key node for the representation of the semantic aspect of numerical quantity.