Neural correlates of mental rehearsal in dorsal premotor cortex

Behavioural and imaging studies suggest that when humans mentally rehearse a familiar action they execute some of the same neural operations used during overt motor performance. Similarly, neural activation is present during action observation in many of the same brain regions normally used for performance, including premotor cortex. Here we present behavioural evidence that monkeys also engage in mental rehearsal during the observation of sensory events associated with a well-learned motor task. Furthermore, most task-related neurons in dorsal premotor cortex exhibit the same activity patterns during observation as during performance, even during an instructed-delay period before any actual observed motion. This activity might be a single-neuron correlate of covert mental rehearsal.     

利用自举法与相干矢量虚部研究脑电信号的连通性

多导联脑电信号之间的连通性分析有助于了解脑的不同分区之间的信息交互。为了研究实验任务引起的脑区之间的连通性,提出了一种结合自举法与相干矢量虚部的统计分析方法,并用于研究左、右手运动想象任务中的信息交互。结果表明:在单侧的运动想象任务中,辅助运动皮层与对侧的运动前区及初级运动感觉皮层具有广泛的联结关系,同时提示受试是采用具有肌肉感觉的运动想象模式。该方法简洁、意义明确,可以进一步应用在脑-机接口及事件相关电位的研究中。     

Real-time prediction of hand trajectory by ensembles of cortical neurons in primates

Signals derived from the rat motor cortex can be used for controlling one-dimensional movements of a robot arm. It remains unknown, however, whether real-time processing of cortical signals can be employed to reproduce, in a robotic device, the kind of complex arm movements used by primates to reach objects in space. Here we recorded the simultaneous activity of large populations of neurons, distributed in the premotor, primary motor and posterior parietal cortical areas, as non-human primates performed two distinct motor tasks. Accurate real-time predictions of one- and three-dimensional arm movement trajectories were obtained by applying both linear and nonlinear algorithms to cortical neuronal ensemble activity recorded from each animal. In addition, cortically derived signals were successfully used for real-time control of robotic devices, both locally and through the Internet. These results suggest that long-term control of complex prosthetic robot arm movements can be achieved by simple real-time transformations of neuronal population signals derived from multiple cortical areas in primates.     

Involvement of secondary motor areas in externally-triggered single-finger movements of dominant and non-dominant hands

Abstract Whether the secondary motor areas are involved in simple voluntary movements remains controversial. Differences in the neural substrates of movements with the dominant and the non-dominant hands have not been well documented. In the present study, functional magnetic resonance imaging (fMRI) was used to investigate the hemodynamic response in the primary motor cortex (M1), supple-mentary motor area (SMA) and premotor cortex (PMC) in six healthy right-handed subjects while performing a visually-guided finger-tapping task with their dominant or non-dominant hands. Significant activation was observed in M1, SMA and PMC during this externally triggered simple voluntary movement task. While dominant hand movements only activated contralateral motor areas, non-domi-nant hand movements also activated ipsilateral SMA and PMC. The results provide strong evidence for the involvement of the secondary motor areas in simple voluntarymovements, and also suggest that movements of the dominant hand primarily engage the contralateral secondary motor areas, whereas movements of the non-dominant hand engage bilateral secondary motor areas.     

Relation of neurons in the nonprimary motor cortex to bilateral hand movement

In the primate cerebral cortex there are at least two somatotopically organized, nonprimary motor fields rostral to the primary motor area. To understand the functions of these multiple motor representations we have compared the neuronal activity in each of these fields while monkeys performed a trained motor task, using right, left or both hands. In the nonprimary motor cortex, activity in a number of neurons was related to the movement the animal chose and performed, whereas in the primary motor cortex, changes in the firing of most neurons were simply related to activity in the contralateral muscles. This result indicates that the nonprimary motor cortex is involved in higher-order coding of the laterality of the motor response, implying that it exerts its motor control function at a higher hierarchical level than its counterpart in the primary motor cortex.     

Human cerebellar activity reflecting an acquired internal model of a new tool

Theories of motor control postulate that the brain uses internal models of the body to control movements accurately. Internal models are neural representations of how, for instance, the arm would respond to a neural command, given its current position and velocity. Previous studies have shown that the cerebellar cortex can acquire internal models through motor learning. Because the human cerebellum is involved in higher cognitive function as well as in motor control, we propose a coherent computational theory in which the phylogenetically newer part of the cerebellum similarly acquires internal models of objects in the external world. While human subjects learned to use a new tool (a computer mouse with a novel rotational transformation), cerebellar activity was measured by functional magnetic resonance imaging. As predicted by our theory, two types of activity were observed. One was spread over wide areas of the cerebellum and was precisely proportional to the error signal that guides the acquisition of internal models during learning. The other was confined to the area near the posterior superior fissure and remained even after learning, when the error levels had been equalized, thus probably reflecting an acquired internal model of the new tool.     

Active tactile exploration using a brain-machine-brain interface

Brain-machine interfaces use neuronal activity recorded from the brain to establish direct communication with external actuators, such as prosthetic arms. It is hoped that brain-machine interfaces can be used to restore the normal sensorimotor functions of the limbs, but so far they have lacked tactile sensation. Here we report the operation of a brain-machine-brain interface (BMBI) that both controls the exploratory reaching movements of an actuator and allows signalling of artificial tactile feedback through intracortical microstimulation (ICMS) of the primary somatosensory cortex. Monkeys performed an active exploration task in which an actuator (a computer cursor or a virtual-reality arm) was moved using a BMBI that derived motor commands from neuronal ensemble activity recorded in the primary motor cortex. ICMS feedback occurred whenever the actuator touched virtual objects. Temporal patterns of ICMS encoded the artificial tactile properties of each object. Neuronal recordings and ICMS epochs were temporally multiplexed to avoid interference. Two monkeys operated this BMBI to search for and distinguish one of three visually identical objects, using the virtual-reality arm to identify the unique artificial texture associated with each. These results suggest that clinical motor neuroprostheses might benefit from the addition of ICMS feedback to generate artificial somatic perceptions associated with mechanical, robotic or even virtual prostheses.     

Primate spinal interneurons show pre-movement instructed delay activity.

Preparatory changes in neural activity before the execution of a movement have been documented in tasks that involve an instructed delay period (an interval between a transient instruction cue and a subsequently triggered movement). Such preparatory activity occurs in many motor centres in the brain, including the primary motor cortex, premotor cortex, supplementary motor area and basal ganglia. Activity during the instructed delay period reflects movement planning, as it correlates with parameters of the cue and the subsequent movement (such as direction and extent), although it occurs well before muscle activity. How such delay-period activity shapes the ensuing motor action remains unknown. Here we show that spinal interneurons also exhibit early pre-movement delay activity that often differs from their responses during the subsequent muscle activity. This delay activity resembles the set-related activity found in various supraspinal areas, indicating that movement preparation may occur simultaneously over widely distributed regions, including spinal levels. Our results also suggest that two processes occur in the spinal circuitry during this delay period: the motor network is primed with rate changes in the same direction as subsequent movement-related activity; and a superimposed global inhibition suppresses the expression of this activity in muscles.     

Cortical control of a prosthetic arm for self-feeding

Arm movement is well represented in populations of neurons recorded from the motor cortex. Cortical activity patterns have been used in the new field of brain-machine interfaces to show how cursors on computer displays can be moved in two- and three-dimensional space. Although the ability to move a cursor can be useful in its own right, this technology could be applied to restore arm and hand function for amputees and paralysed persons. However, the use of cortical signals to control a multi-jointed prosthetic device for direct real-time interaction with the physical environment ('embodiment') has not been demonstrated. Here we describe a system that permits embodied prosthetic control; we show how monkeys (Macaca mulatta) use their motor cortical activity to control a mechanized arm replica in a self-feeding task. In addition to the three dimensions of movement, the subjects' cortical signals also proportionally controlled a gripper on the end of the arm. Owing to the physical interaction between the monkey, the robotic arm and objects in the workspace, this new task presented a higher level of difficulty than previous virtual (cursor-control) experiments. Apart from an example of simple one-dimensional control, previous experiments have lacked physical interaction even in cases where a robotic arm or hand was included in the control loop, because the subjects did not use it to interact with physical objects-an interaction that cannot be fully simulated. This demonstration of multi-degree-of-freedom embodied prosthetic control paves the way towards the development of dexterous prosthetic devices that could ultimately achieve arm and hand function at a near-natural level.     

基于增量PCA的目标跟踪算法

在空间遥操作系统中为了获取良好的视觉信息使操作员有种身临其境的感觉，在基于奇异值分解的PCA算法上采用增量PCA跟踪算法，避免了提取大量图片的问题；将该算法与PTZ摄像机相结合，设计了一套基于主动视觉的目标跟踪系统。为机械臂提供灵敏的感知系统，在不接触目标的情况下将相关信息及时传递给地面操作员，便于操作员自然、有效地解决问题。在机械臂动作之前执行规划，在动作过程中不断地反馈信息，适合于对环境变化有适应性要求的作业。     

Free choice activates a decision circuit between frontal and parietal cortex

We often face alternatives that we are free to choose between. Planning movements to select an alternative involves several areas in frontal and parietal cortex that are anatomically connected into long-range circuits. These areas must coordinate their activity to select a common movement goal, but how neural circuits make decisions remains poorly understood. Here we simultaneously record from the dorsal premotor area (PMd) in frontal cortex and the parietal reach region (PRR) in parietal cortex to investigate neural circuit mechanisms for decision making. We find that correlations in spike and local field potential (LFP) activity between these areas are greater when monkeys are freely making choices than when they are following instructions. We propose that a decision circuit featuring a sub-population of cells in frontal and parietal cortex may exchange information to coordinate activity between these areas. Cells participating in this decision circuit may influence movement choices by providing a common bias to the selection of movement goals.     

Numerical representation for action in the parietal cortex of the monkey

The anterior part of the parietal association area in the cerebral cortex of primates has been implicated in the integration of somatosensory signals, which generate neural images of body parts and apposed objects and provide signals for sensorial guidance of movements. Here we show that this area is active in primates performing numerically based behavioural tasks. We required monkeys to select and perform movement A five times, switch to movement B for five repetitions, and return to movement A, in a cyclical fashion. Cellular activity in the superior parietal lobule reflected the number of self-movement executions. For the most part, the number-selective activity was also specific for the type of movement. This type of numerical representation of self-action was seen less often in the inferior parietal lobule, and rarely in the primary somatosensory cortex. Such activity in the superior parietal lobule is useful for processing numerical information, which is necessary to provide a foundation for the forthcoming motor selection.     

Bayesian integration in sensorimotor learning

When we learn a new motor skill, such as playing an approaching tennis ball, both our sensors and the task possess variability. Our sensors provide imperfect information about the ball's velocity, so we can only estimate it. Combining information from multiple modalities can reduce the error in this estimate. On a longer time scale, not all velocities are a priori equally probable, and over the course of a match there will be a probability distribution of velocities. According to bayesian theory, an optimal estimate results from combining information about the distribution of velocities-the prior-with evidence from sensory feedback. As uncertainty increases, when playing in fog or at dusk, the system should increasingly rely on prior knowledge. To use a bayesian strategy, the brain would need to represent the prior distribution and the level of uncertainty in the sensory feedback. Here we control the statistical variations of a new sensorimotor task and manipulate the uncertainty of the sensory feedback. We show that subjects internally represent both the statistical distribution of the task and their sensory uncertainty, combining them in a manner consistent with a performance-optimizing bayesian process. The central nervous system therefore employs probabilistic models during sensorimotor learning.     

The influence of visual motion on fast reaching movements to a stationary object

One of the most important functions of vision is to direct actions to objects. However, every time that vision is used to guide an action, retinal motion signals are produced by the movement of the eye and head as the person looks at the object or by the motion of other objects in the scene. To reach for the object accurately, the visuomotor system must separate information about the position of the stationary target from background retinal motion signals-a long-standing problem that is poorly understood. Here we show that the visuomotor system does not distinguish between these two information sources: when observers made fast reaching movements to a briefly presented stationary target, their hand shifted in a direction consistent with the motion of a distant and unrelated stimulus, a result contrary to most other findings. This can be seen early in the hand's trajectory (approximately 120 ms) and occurs continuously from programming of the movement through to its execution. The visuomotor system might make use of the motion signals arising from eye and head movements to update the positions of targets rapidly and redirect the hand to compensate for body movements.     

Temporal dissociation of parallel processing in the human subcortical outputs.

Many tasks require rapid and fine-tuned adjustment of motor performance based on incoming sensory information. This process of sensorimotor adaptation engages two parallel subcorticocortical neural circuits, involving the cerebellum and basal ganglia, respectively. How these distributed circuits are functionally coordinated has not been shown in humans. The cerebellum and basal ganglia show very similar convergence of input-output organization, which presents an ideal neuroimaging model for the study of parallel processing at a systems level. Here we used functional magnetic resonance imaging to measure the temporal coherence of brain activity during a tactile discrimination task. We found that, whereas the prefrontal cortex maintained a high level of activation, output activities in the cerebellum and basal ganglia showed different phasic patterns. Moreover, cerebellar activity significantly correlated with the activity of the supplementary motor area but not with that of the primary motor cortex; in contrast, basal ganglia activity was more strongly associated with the activity of the primary motor cortex than with that of the supplementary motor area. These results demonstrate temporally partitioned activity in the cerebellum and basal ganglia, implicating functional independence in the parallel subcortical outputs. This further supports the idea of task-related dynamic reconfiguration of large-scale neural networks.     

Motor antagonism exposed by spatial segregation and timing of neurogenesis

Walking is a key motor behaviour of limbed animals, executed by contraction of functionally antagonistic muscle groups during swing and stance phases. Nevertheless, neuronal circuits regulating the activation of antagonistic extensor-flexor muscles remain poorly understood. Here we use monosynaptically restricted trans-synaptic viruses to elucidate premotor anatomical substrates for extensor-flexor control in mice. We observe a medio-lateral spatial segregation between extensor and flexor premotor interneurons in the dorsal spinal cord. These premotor interneuron populations are derived from common progenitor domains, but segregate by timing of neurogenesis. We find that proprioceptive sensory feedback from the periphery is targeted to medial extensor premotor populations and is required for extensor-specific connectivity profiles during development. Our findings provide evidence for a discriminating anatomical basis of antagonistic circuits at the level of premotor interneurons, and point to synaptic input and developmental ontogeny as key factors in the establishment of circuits regulating motor behavioural dichotomy.     

Corticostriatal plasticity is necessary for learning intentional neuroprosthetic skills

The ability to learn new skills and perfect them with practice applies not only to physical skills but also to abstract skills, like motor planning or neuroprosthetic actions. Although plasticity in corticostriatal circuits has been implicated in learning physical skills, it remains unclear if similar circuits or processes are required for abstract skill learning. Here we use a novel behavioural task in rodents to investigate the role of corticostriatal plasticity in abstract skill learning. Rodents learned to control the pitch of an auditory cursor to reach one of two targets by modulating activity in primary motor cortex irrespective of physical movement. Degradation of the relation between action and outcome, as well as sensory-specific devaluation and omission tests, demonstrate that these learned neuroprosthetic actions are intentional and goal-directed, rather than habitual. Striatal neurons change their activity with learning, with more neurons modulating their activity in relation to target-reaching as learning progresses. Concomitantly, strong relations between the activity of neurons in motor cortex and the striatum emerge. Specific deletion of striatal NMDA receptors impairs the development of this corticostriatal plasticity, and disrupts the ability to learn neuroprosthetic skills. These results suggest that corticostriatal plasticity is necessary for abstract skill learning, and that neuroprosthetic movements capitalize on the neural circuitry involved in natural motor learning.     

Reach and grasp by people with tetraplegia using a neurally controlled robotic arm

Paralysis following spinal cord injury, brainstem stroke, amyotrophic lateral sclerosis and other disorders can disconnect the brain from the body, eliminating the ability to perform volitional movements. A neural interface system could restore mobility and independence for people with paralysis by translating neuronal activity directly into control signals for assistive devices. We have previously shown that people with long-standing tetraplegia can use a neural interface system to move and click a computer cursor and to control physical devices. Able-bodied monkeys have used a neural interface system to control a robotic arm, but it is unknown whether people with profound upper extremity paralysis or limb loss could use cortical neuronal ensemble signals to direct useful arm actions. Here we demonstrate the ability of two people with long-standing tetraplegia to use neural interface system-based control of a robotic arm to perform three-dimensional reach and grasp movements. Participants controlled the arm and hand over a broad space without explicit training, using signals decoded from a small, local population of motor cortex (MI) neurons recorded from a 96-channel microelectrode array. One of the study participants, implanted with the sensor 5?years earlier, also used a robotic arm to drink coffee from a bottle. Although robotic reach and grasp actions were not as fast or accurate as those of an able-bodied person, our results demonstrate the feasibility for people with tetraplegia, years after injury to the central nervous system, to recreate useful multidimensional control of complex devices directly from a small sample of neural signals.     

Relative reward preference in primate orbitofrontal cortex

The orbital part of prefrontal cortex appears to be crucially involved in the motivational control of goal-directed behaviour. Patients with lesions of orbitofrontal cortex show impairments in making decisions about the expected outcome of actions. Monkeys with orbitofrontal lesions respond abnormally to changes in reward expectations and show altered reward preferences. As rewards constitute basic goals of behaviour, we investigated here how neurons in the orbitofrontal cortex of monkeys process information about liquid and food rewards in a typical frontal task, spatial delayed responding. The activity of orbitofrontal neurons increases in response to reward-predicting signals, during the expectation of rewards, and after the receipt of rewards. Neurons discriminate between different rewards, mainly irrespective of the spatial and visual features of reward-predicting stimuli and behavioural reactions. Most reward discriminations reflect the animals' relative preference among the available rewards, as expressed by their choice behaviour, rather than physical reward properties. Thus, neurons in the orbitofrontal cortex appear to process the motivational value of rewarding outcomes of voluntary action.     

Cross-modal and cross-temporal association in neurons of frontal cortex

The prefrontal cortex is essential for the temporal integration of sensory information in behavioural and linguistic sequences. Such information is commonly encoded in more than one sense modality, notably sight and sound. Connections from sensory cortices to the prefrontal cortex support its integrative function. Here we present the first evidence that prefrontal cortex cells associate visual and auditory stimuli across time. We gave monkeys the task of remembering a tone of a certain pitch for 10 s and then choosing the colour associated with it. In this task, prefrontal cortex cells responded selectively to tones, and most of them also responded to colours according to the task rule. Thus, their reaction to a tone was correlated with their subsequent reaction to the associated colour. This correlation faltered in trials ending in behavioural error. We conclude that prefrontal cortex neurons are part of integrative networks that represent behaviourally meaningful cross-modal associations. The orderly and timely activation of neurons in such networks is crucial for the temporal transfer of information in the structuring of behaviour, reasoning and language.