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Subdivisions of the prefrontal cortex (PFC) evolved at different times. Agranular parts of the PFC emerged in early mammals, and rodents, primates, and other modern mammals share them by inheritance. These are limbic areas and include the agranular orbital cortex and agranular medial frontal cortex (areas 24, 32, and 25). Rodent research provides valuable insights into the structure, functions, and development of these shared areas, but it contributes less to parts of the PFC that are specific to primates, namely, the granular, isocortical PFC that dominates the frontal lobe in humans. The first granular PFC areas evolved either in early primates or in the last common ancestor of primates and tree shrews. Additional granular PFC areas emerged in the primate stem lineage, as represented by modern strepsirrhines. Other granular PFC areas evolved in simians, the group that includes apes, humans, and monkeys. In general, PFC accreted new areas along a roughly posterior to anterior trajectory during primate evolution. A major expansion of the granular PFC occurred in humans in concert with other association areas, with modifications of corticocortical connectivity and gene expression, although current evidence does not support the addition of a large number of new, human-specific PFC areas.

In the epilogue, a couple of kids befriend a shy stegosaurus; a different stegosaurus worries about the rise of mammals; and a tyrannosaurus presents a situation report. But mainly we consider reptilian brains, the relationship of brain size to intelligence, and the evolutionary success of mammals. Contrary to an internet meme, no one has a “reptilian” or “lizard” brain lurking within. Our entire brain is human. Regarding intelligence, brain organization matters as much as brain size and maybe more. Once dinosaurs became extinct, the mammals that supplanted them had much smaller brains than large dinosaurs had. Instead, the success of mammals depended on the emergence of the neocortex, a new part of the brain. Eventually, this evolutionary innovation came to dominate both the brain and the memories that it contains.

Comparative neuroanatomy shows that new prefrontal areas emerged during the evolution of anthropoid primates to augment prefrontal, parietal, and temporal areas that had evolved in earlier primates. We recently proposed that the new anthropoid areas reduce foraging errors by generating goals from current contexts and learning to do so rapidly, sometimes based on single events. Among the contexts used to generate these goals, the posterior parietal cortex provides the new prefrontal areas with information about relational metrics such as order, number, duration, length, distance and proportion, which play a crucial role in foraging choices. Here we propose that this specialized network later became adapted to support the human capacity for reasoning and general problem-solving.

Recent research indicates that the orbital prefrontal cortex (PFo) represents stimulus valuations and that the amygdala updates these valuations. An exploration of how PFo and the amygdala interact could improve the understanding of both. PFo and the amygdala function cooperatively when monkeys choose objects associated with recently revalued foods. In other tasks, they function in opposition. PFo uses positive feedback to promote learning in object-reward reversal tasks, and PFo also promotes extinction learning. Amygdala function interferes with both kinds of learning. The amygdala underlies fearful responses to a rubber snake from the first exposure on, but PFo is necessary only after the initial exposure. The amygdala mediates an arousal response in anticipation of rewards, whereas PFo sometimes suppresses such arousal. A role for PFo in advanced cognition, for the amygdala in instinctive behavior, and for cortex-subcortex interactions in prioritizing behaviors provides one account for these findings.

The primate prefrontal cortex contributes to stimulus-guided behavior, but the functional specializations among its areas remain uncertain. To better understand such specializations, we contrasted neuronal activity in the dorsolateral prefrontal cortex (PFdl) and the orbital prefrontal cortex (PFo). The task required rhesus monkeys to use a visual cue to choose a saccade target. Some cues instructed the monkeys to repeat their most recent response; others instructed them to change it. Responses were followed by feedback: fluid reward if correct, visual feedback if incorrect. Previous studies, using different tasks, have reported that PFo neurons did not encode responses. We found PFo did encode responses in this task, but only near feedback time, after the response had been completed. PFdl differed from PFo in several respects. As reported previously, some PFdl neurons encoded responses from the previous trial and others encoded planned responses. PFo neurons did not have these properties. After feedback, PFdl encoded rewarded responses better than unrewarded ones and thus combined response and outcome information. PFo, in contrast, encoded the responses chosen, rewarded or not. These findings suggest that PFdl and PFo contribute differently to response knowledge, with PFo using an outcome-independent signal to monitor current responses at feedback time.

The largest part of the primate prefrontal cortex has no homolog in other mammals. Accordingly, it probably confers some advantage that other mammals either lack or attain through the function of other structures. Yet, this advantage remains enigmatic. This is not so for other parts of the cortex. For example, certain visual areas encode, represent and store knowledge about objects. By analogy, perhaps the primate prefrontal cortex encodes, represents and stores knowledge about behaviors, including the consequences of doing (or not doing) something in complex and challenging situations. The long list of functions often attributed to the prefrontal cortex could contribute to knowing what to do and what will happen when rare risks arise or outstanding opportunities knock.

The activity of some prefrontal (PF) cortex neurons distinguishes short from long time intervals. Here, we examined whether this property reflected a general timing mechanism or one dependent on behavioral context. In one task, monkeys discriminated the relative duration of 2 stimuli; in the other, they discriminated the relative distance of 2 stimuli from a fixed reference point. Both tasks had a pre-cue period (interval 1) and a delay period (interval 2) with no discriminant stimulus. Interval 1 elapsed before the presentation of the first discriminant stimulus, and interval 2 began after that stimulus. Both intervals had durations of either 400 or 800 ms. Most PF neurons distinguished short from long durations in one task or interval, but not in the others. When neurons did signal something about duration for both intervals, they did so in an uncorrelated or weakly correlated manner. These results demonstrate a high degree of context dependency in PF time processing. The PF, therefore, does not appear to signal durations abstractedly, as would be expected of a general temporal encoder, but instead does so in a highly context-dependent manner, both within and between tasks.

In healthy humans, the two cerebral hemispheres show functional specialization to a degree unmatched in other animals, and such strong hemispheric specialization contributes to unimanual skill acquisition [1, 2]. When most humans learn a new motor skill with one hand, this process results in performance improvements in the opposite hand as well [3-6]. Despite the obvious adaptive advantage of such intermanual transfer, there is no direct evidence identifying the neural substrates of this form of skill acquisition [7-9]. Here, we used functional magnetic resonance imaging (fMRI) to study brain regions activated during intermanual transfer of a learned sequence of finger movements. First, we found that the supplementary motor area (SMA) has more activity when a skill has transferred well than when it has transferred poorly. Second, we found that fMRI activity in the ventrolateral posterior thalamic nucleus correlated with successful future intermanual transfer, whereas activity in the ventrolateral anterior thalamic nucleus correlated with past intermanual transfer. Third, we found that repetitive transcranial magnetic stimulation applied over the SMA blocked intermanual transfer without affecting skill acquisition. These findings provide direct evidence for an SMA-based mechanism that supports intermanual transfer of motor-skill learning.

In addition to its projection to the brainstem, the ventral premotor cortex (PMv) sends axons directly to the upper cervical spinal cord in primates, with few terminations more caudally in either the cervical enlargement or in the lumbosacral spinal segments. This finding suggests that PMv plays a role in the control of head movements. Furthermore, comparative neuroanatomical studies indicate that PMv's corticospinal projection was a primate innovation. If the first primates adapted to an arboreal life that involved unimanual feeding, as some experts believe, then perhaps PMv's corticospinal projection evolved to coordinate head movements with this kind of feeding behavior. The computations underlying such control could later be adapted to control head orientation during social signaling.

A previous study found that as monkeys learned novel mappings between visual cues and responses, neuronal activity patterns evolved at approximately the same time in both the dorsal premotor cortex (PMd) and the putamen. Here we report that, in both regions, the population activity for novel mappings came to resemble that for familiar ones as learning progressed. Both regions showed activity differences on trials with correct responses versus those with incorrect ones. In addition to these common features, we observed two noteworthy differences between PMd and putamen activity during learning. After a response choice had been made, but prior to feedback about the correctness of that choice (reward or nonreward), the putamen showed a sustained activity increase in activity, whereas PMd did not. Also in the putamen, this prereward activity was highly selective for the specific visuomotor mapping that had just been performed, and this selectivity was maintained until the time of the reward. After performance reached an asymptote, the degree of this selectivity decreased markedly to the level typical for familiar visuomotor mappings. These findings support the hypothesis that neurons in the striatum play a pivotal role in associative learning.

Historically, different groups of researchers have investigated the mechanisms of perceptual learning and motor learning. For sensory cortex, neurophysiological and psychophysical findings have linked changes in perception with altered neuronal tuning properties. However, less information has been forthcoming from motor cortex. This review compares recent findings on perceptual and motor learning, and suggests that similar mechanisms govern both. These mechanisms involve changes in both the center of neuronal tuning functions and their width or slope. The former reflects the values of the sensory or motor parameters that a neuron encodes, and the latter adjusts the encoding sensitivity. These similarities suggest that specific unifying principles for neural coding and computation exist across sensory and motor domains.

Five rhesus monkeys (Macaca mulatta) were trained to learn novel conditional visuomotor associations, to perform this task with familiar stimuli, and to perform a visual matching-to-sample task with the same familiar stimuli. Removal of the orbital and ventral prefrontal cortex (PFv+o) in 1 hemisphere and inferotemporal cortex (IT) in the other, thus completing a surgical disconnection of these 2 regions, yielded an impairment on all 3 tasks. Addition of a premotor cortex lesion to the hemisphere containing the PFv+o lesion did not worsen the impairments. The results indicate that PFv+o interacts with IT in both the learning and retention of conditional visuomotor associations. In addition to those associations, which might be considered lower order rules for choosing a response, frontotemporal interaction also appears to be important for higher order rules, such as those involved in the matching task.

Practicing movements results in improvement in performance and in plasticity of the motor cortex. To identify the underlying mechanisms, we studied use-dependent plasticity in human subjects premedicated with drugs that influence synaptic plasticity. Use-dependent plasticity was reduced substantially by dextromethorphan (an N- methyl- d -aspartate receptor blocker) and by lorazepam [a γ-aminobutyric acid (GABA) type A receptor-positive allosteric modulator]. These results identify N -methyl- d -aspartate receptor activation and GABAergic inhibition as mechanisms operating in use-dependent plasticity in intact human motor cortex and point to similarities in the mechanisms underlying this form of plasticity and long-term potentiation.

We examined single-unit activity in the dorsal premotor cortex for evidence of fast neuronal oscillations. Four rhesus monkeys performed a task in which visuospatial instruction stimuli indicated the direction of forelimb movement to be executed on each trial. After an instructed delay period of 1.5-3 s, movements to either the right or left of a central origin were triggered by a second visuospatial stimulus. From a database of 579 single units, 78 units (13%) contained periodic peaks in their autocorrelation histograms (ACHs), with oscillation frequencies typically 20-30 Hz (mean 27 Hz). An additional 26 units (5%) had oscillatory features that were identified in joint interspike-interval (ISI) plots. Three observations, taken together, suggest entrainment by rhythmic drive extrinsic to these neurons: shuffling ISIs attenuated ACH peaks, indicating a dependency on serial-order effects; oscillation frequency did not change during either increases or decreases in firing rate; and joint ISI plots contained features consistent with a rhythmicity interrupted by intervening discharges. In some cells, oscillations occurred for only one of the two directions of movement. During the delay period, such directional selectivity was observed in 37 units (60% of delay-period oscillators). For at least 17 of these units, we could exclude the possibility that oscillatory directional selectivity resulted from the difficulty in detecting oscillations due to low discharge rates (for one of the two movement directions). Directional selectivity in fast oscillations shows that they can reflect specific aspects of an intended action.

Macaque monkeys can learn arbitrary mappings between stimuli and spatially directed actions (often termed conditional motor learning), and, after the development of a strong learning set, can do so in just a few trials. Ablation studies have shown that the hippocampus plus subjacent cortex is necessary for this rapid and highly flexible type of learning. We consider evidence that the arbitrary mapping function of the hippocampal system may be more general and fundamental than currently accepted and what limitations there may be, if any, on the information that it can map. Removal of the hippocampal system yields a pattern of deficits and preserved abilities that correlates remarkably closely with that found in human global amnesics, such as patient H.M., on a variety of declarative memory tasks. Thus, the rapid acquisition of arbitrary visuomotor mappings may represent an example of declarative memory in nonhuman primates.

The phenomenon of object-centred unilateral neglect suggests that some neural networks process spatial information relative to reference objects. To examine object-centred information processing, we measured regional cerebral blood flow in 11 normal subjects with PET. During each PET scan, a subject viewed a sample stimulus followed by a cue on a video screen. The sample consisted of two polygons, termed 'objects', each located in a corner of the screen. A small target spot appeared in a corner of each polygon. There were two tasks: the visuomotor task and the matching-to-sample task. In the visuomotor task, the subject moved a joystick in a direction indicated by either the location of the target spot inside the object (if object-centred coordinates were operative) or the location of the object relative to the video screen (if screen-centred coordinates were operative). In the matching-to-sample task, the subject moved the joystick to report whether the relevant spatial information (object- or screen-centred) in the cue matched the sample. In both the visuomotor and the matching-to-sample task, use of object-centred (versus screen- or viewer-centred) information caused augmented activation in the inferior occipitotemporal cortex, bilaterally, in the left superior occipital gyrus, and in both the thalamus and the brainstem. In addition, in the visuomotor task such activation occurred in the right posterior parietal cortex and in the left ventral premotor, dorsolateral prefrontal and anterior supplementary motor areas. These findings suggest the involvement of the occipitotemporal cortex and a broad frontoparietal network when, as in the visuomotor task, object-centred information guides movement. When the same data underlie declarative reports, as in the matching-to-sample task, the occipitotemporal cortex remains engaged but the frontoparietal network diminishes in importance.

We examined neuronal activity in three motor cortical areas while a rhesus monkey adapted to novel visuomotor transforms. The monkey moved a joystick that controlled a cursor on a video screen. Each trial began with the joystick centered. Next, the cursor appeared in one of eight positions, arranged in a circle around a target stimulus at the center of the screen. To receive reinforcement, the monkey moved the joystick so that the cursor contacted the target continuously for Is. The video monitor provided continuous visual feedback of both cursor and target position. With those elements of the task constant, we modified the transform between joystick movement and that of the cursor at the beginning of a block of trials. Neuronal activity was studied as the monkey adapted to these novel joystick-cursor transforms. Some novel tasks included spatial transforms such as single-axis inversions, asymmetric double-axis inversions and angular deviations (also known as rotations). Other tasks involved changes in the spatiotemporal pattern and magnitude of joystick movement. As the monkey adapted to various visuomotor tasks, 209 task-related neurons (selected for stable background activity) showed significant changes in their task-related activity: 88 neurons in the primary motor cortex (M1), 32 in the supplementary motor cortex (M2), and 89 in the caudal part of the dorsal premotor cortex (PMdc). Slightly more than half of the sample in each area showed significant changes in the magnitude of activity modulation during adaptation, with the number of increases approximately equaling the number of decreases. These data support the prediction that changes in task-related neuronal activity can be observed in M1 during motor adaptation, but fail to support the hypothesis that M1 and PMdc differ in this regard. When viewed in population averages, motor cortex continued to change its activity for at least dozens of trials after performance reached a plateau. This slow, apparently continuing change in the pattern and magnitude of task-related activity may reflect the initial phases of consolidating the motor memory for preparing and executing visuomotor skills.

A fully recurrent neural network model was optimized to perform a spatial delayed matching-to-sample task (DMS). In DMS, a stimulus is presented at a sample location, and a match is reported when a subsequent stimulus appears at that location. Stimuli elsewhere are ignored. Computationally, a DMS system could consist of memory and comparison components. The model, although not constrained to do so, worked by using two corresponding classes of neurons in the hidden layer: storage and comparator units. Storage units form a dynamical system with one fixed point attractor for each sample location. Comparator units constitute a system receiving input from these storage units as well as from current input stimuli. Both unit types were tuned directionally. These two sources of information combine to create unique patterns of activity that determine whether a match has occurred. In networks with abundant hidden units, the storage and comparator functions were distributed so that individual units took part in both. We compared the model with single-neuron recordings from premotor (PM) and prefrontal (PF) cortex. As shown previously, many PM and PF neurons behaved like storage units. In addition, both regions contain neurons that behave like the comparator units of the model and appear to have dual functionality similar to that observed in the model units. No neuron in either area had properties identical to those of the match output neuron of the model. However, four PF neurons and one PM neuron resembled the output signal more closely than any of the hidden units of the model.

We assessed the preferred directions (PDs) of supplementary eye field (SEF) neurons during conditional visuomotor learning. Monkeys learned to select one of four saccadic eye movements in response to a foveal instruction stimulus (IS). ISs were either familiar or novel. Each familiar IS reliably evoked one saccade: 7° left, right, up, or down from the central fixation point. Novel ISs initially triggered virtually random responses among those four possibilities, but the monkeys ultimately learned to select the instructed saccade. As reported previously, activity rates on novel IS trials significantly changed during learning. Some of these cells (learning-dependent) also have significant modulation on familiar IS trials, but others (learning-selective) lack such activity. Of the former, the familiar IS activity can be either directionally selective or omnidirectional. For most neurons, PDs were apparent during all phases of learning, but they were rarely constant. Only infrequently did a neuron’s PD for novel ISs closely match that for familiar ISs throughout the learning process. In directional learning-dependent cells, the PD usually reoriented near the end of learning to resemble that for familiar IS trials. In omnidirectional cells, initially evident PDs dissipated with learning, even as the cell became more strongly modulated. Learning-selective cells typically began with significant PDs, but became unmodulated as learning progressed. Our findings show a pervasive lability in SEF PDs that may reflect a flexible and rapid remapping between inputs and responses within the premotor cortical network.

The motor system includes structures distributed widely through the CNS, and in this feature article we present a scheme for how they might cooperate in the control of action. Distributed modules, which constitute the basic building blocks of our model, include recurrent loops connecting distant brain structures, as well as local circuitry that modulates loop activity. We consider interconnections among the basal ganglia, cerebellum, and cerebral cortex and the specialized properties of certain cell types within each of those structures, namely, striatal spiny neurons, cerebellar Purkinje cells, and neocortical pyramidal cells. In our model, striatal spiny neurons of the basal ganglia function in contextual pattern recognition under the training influence of reinforcement signals transmitted in dopamine fibers. Cerebellar Purkinje cells also function in pattern recognition, in their case to select and execute actions through training supervised by climbing fibers, which signal discoordination. Neocortical pyramidal cells perform collective computations learned through a local training mechanism and also function as information stores for other modular operations. We discuss how distributed modules might function in a parallel, cooperative manner to plan, modulate, and execute action.

Memory loss resulting from damage to the medial temporal lobes (MTL) is traditionally considered to reflect damage to a dedicated, exclusive memory system. Recent work, however, has suggested that damage to one MTL structure, the perirhinal cortex (PRC), compromises complex object representations that are necessary for both memory and perception. These representations are thought to be critical in shielding against the interference caused by a stream of visually similar input. In this study, we administered a complex object discrimination task to two memory-impaired populations thought to have brain damage that includes the PRC [patients diagnosed with amnestic mild cognitive impairment (MCI), and older adults at risk for MCI], as well as age-matched controls. Importantly, we carefully manipulated the level of interference: in the High Interference condition, participants completed a block of consecutive perceptually similar complex object discriminations, whereas in the Low Interference condition, we interspersed perceptually dissimilar objects such that there was less buildup of visual interference. We found that both memory-impaired populations were impaired on the High Interference condition compared with controls, but critically, by reducing the degree of perceptual interference, we were largely able to improve their performance. These findings, when taken together with convergent evidence from animals with selective PRC lesions and amnesic patients with focal damage to the PRC, provide support for a representational-hierarchical model of PRC function and suggest that memory loss following PRC damage may reflect a heightened vulnerability to perceptual interference.

behavior-guiding rules and strategies allow monkeys to avoid errors in rarely encountered situations. In the present study, we contrasted strategy-related neuronal activity in the dorsolateral prefrontal cortex (PFdl) and the orbital prefrontal cortex (PFo) of rhesus monkeys. On each trial of their behavioral task, the monkeys responded to a foveal visual cue by making a saccade to one of two spatial targets. One response required a leftward saccade, the other required a saccade of equal magnitude to the right. The cues instructed the monkeys to follow one of two response strategies: to stay with their most recent successful response or to shift to the alternative response. Neurons in both areas encoded the stay and shift strategies after the cue appeared, but there were three major differences between the PFo and the PFdl: (1) many strategy-encoding cells in PFdl also encoded the response (left or right), but few, if any, PFo cells did so; (2) strategy selectivity appeared earlier in PFo than in PFdl; and (3) on error trials, PFo neurons encoded the correct strategy—the one that had been cued but not implemented—whereas in PFdl the strategy signals were weak or absent on error trials. These findings indicate that PFo and PFdl both contribute to behaviors guided by abstract response strategies, but do so differently, with PFo encoding a strategy and PFdl encoding a response based on a strategy.

To compare with our previous findings on relative-duration discrimination, we studied prefrontal cortex activity as monkeys performed a relative-distance discrimination task. We wanted to know whether the same parts of the prefrontal cortex compare durations and distances and, if so, whether they use similar mechanisms. Two stimuli appeared sequentially on a video screen, one above a fixed reference point, the other below it by a different distance. After a delay period, the same two stimuli reappeared (as choice stimuli), and the monkeys' task was to choose the one that had appeared farther from the reference point during its initial presentation. We recorded from neurons in the dorsolateral prefrontal cortex (area 46) and the caudal prefrontal cortex (area 8). Although some prefrontal neurons encoded the absolute distance of a stimulus from the reference point, many more encoded relative distance. Categorical representations (“farther”) predominated over parametric ones (“how much farther”). Relative-distance coding was most often abstract, coding the farther or closer stimulus to the same degree, independent of its position on the screen. During the delay period before the choice stimuli appeared, feature-based coding supplanted order-based coding, and position-based coding—always rare—decreased to chance levels. The present results closely resembled those for a duration-discrimination task in the same cortical areas. We conclude, therefore, that these areas contribute to decisions based on both spatial and temporal information.

Considerable neuroimaging research in humans indicates that the frontal pole cortex (FPC), also known as Brodmann area 10, contributes to many aspects of cognition. Despite these findings, however, its fundamental function and mechanism remain unclear. Recent neurophysiological results from the FPC of monkeys have implications about both. Neurons in the FPC seem to encode chosen goals at feedback time and nothing else. Goals, the places and objects that serve as targets for action, come in many forms and arise from many cognitive processes. The FPC's signal, although surprisingly simple for neurons at the apex of a prefrontal hierarchy, could promote learning about which kinds of goals and goal-generating processes produce particular costs and benefits, thereby improving future choices.

When visuospatial stimuli instruct a limb movement, the stimulus can be said to have both sensory and sensorimotor aspects. We studied the premotor and prefrontal areas of a rhesus monkey in order to identify neuronal activity related to the motor (or instructional) aspects of such stimuli. A rhesus monkey chose limb-movement targets according to one of two rules: (1) visuospatial stimuli instructed and triggered a limb movement toward their locations or (2) identical stimuli triggered a movement toward a predetermined target regardless of their location. Gaze and head fixation assured that each stimulus appeared at a constant location in both retinocentric and craniocentric coordinates, as well as in allocentric space. The task required that the spatial location cued by certain stimuli had to be either remembered or attended after stimulus presentation and before movement. Thus, the visuospatial information presented under one rule differed from that presented under the other only in its motor (instructional) significance and not in its attentional, spatial, mnemonic, or strictly sensory aspects. We could thereby test and confirm the hypothesis that the motor significance of visuospatial cues should commonly affect neuronal activity in the premotor cortex, but less commonly do so in the prefrontal cortex.

We examined neuronal activity in the primate premotor (PM) and prefrontal (PF) areas during a demanding spatial matching task. On each behavioral trial, a rhesus monkey moved its forelimb when a visual stimulus, called the "prime stimulus," reappeared at a previously cued location. Because it triggered a movement, the part of space cued by the prime stimulus had to be either remembered or attended during the time between prime stimulus presentations. Between the first and second appearances of the prime stimulus, behaviorally irrelevant visual stimuli could appear at one or several locations other than that of the prime stimulus. We could thereby examine the activity that followed a stimulus when it was attended versus when it was irrelevant and presumably unattended. We found that visuospatial attention affected neuronal activity in both the motor and "nonmotor" parts of the frontal cortex. The magnitude of attention effects exceeded that previously reported--a finding that probably resulted from the intensive attentional demands of the present task.

Despite considerable effort, the localization of dysfunction in major depressive disorder (MDD) remains poorly understood. We present a hypothesis about its localization that builds on recent findings from primate neuropsychology. The hypothesis has four key components: a deficit in the valuation of "self" underlies the core disorder in MDD; the medial frontal cortex represents "self"; interactions between the amygdala and cortical representations update their valuation; and inefficiency in using positive feedback by orbital prefrontal cortex contributes to MDD.

Neurophysiological research has explored most of the prefrontal cortex of macaque monkeys, but the relatively inaccessible frontal-pole cortex remains unexamined. Here we describe a method for gaining access to the frontal-pole cortex with moveable microelectrodes. The key innovation is a direct approach through the frontal air sinus. In addition, the small size of the frontal-pole cortex in macaques led to the design of a smaller recording chamber than typically used in behavioral neurophysiology. The method has proven successful in two subjects, with no adverse health consequences.

The supplementary motor area (SMA) makes a crucial contribution to intermanual transfer: the ability to use one hand to perform a skill practiced and learned with the other hand. However, the timing of this contribution relative to movement remains unknown. Here, 33 healthy volunteers performed a 12 item sequence in the serial reaction time task. During training, each participant responded to a sequence of visual cues presented at 1 Hz by pressing one of four keys with their right hand. The measure of intermanual transfer was response time (RT) during repetition of the trained sequence with the left hand, which was at rest during learning. Participants were divided into three groups, which did not differ in their learning rates or amounts. In two groups, 1 Hz repetitive transcranial magnetic stimulation induced transient virtual lesions of the SMA during training, either 100 ms before each cue (the premovement group) or during each key press (the movement group). The third group received sham stimulation (the sham group). After training with the right hand, RTs for performance with the left (transfer) hand were longer for the premovement group than for the movement or sham groups. Thus, the most crucial contribution of SMA to intermanual transfer occurs in the interval between movements, when the memory of a previous movement plays a role in encoding specific sequences. These results provide insight into frontal lobe contributions to procedural knowledge.

Several lines of evidence suggest that the role of the basal ganglia in motor control is of a higher order than control of movements per se. First the striatum receives inputs from cortical areas that subserve mnemonic and other cognitive processes. Furthermore, the supplementary motor area (a zone that receives outputs from the globus pallidus via thalamus) exhibits changes in neuronal discharge and metabolic activity during movement planning as well as during movement. It is possible that this activity reflects its pallidal inputs. In addition, cells in another part of the basal ganglia, the pars reticulata of the substantia nigra, exhibit activity that reflects mnemonic as well as oculomotor and visual processes. Finally, there are striatal neurons that respond to stimuli when these stimuli trigger movement but not when responses to the stimuli are extinguished. Taken collectively, these observations are consistent with the view that the basal ganglia may provide an interface between motor centres and cortical areas for higher brain function.

Learning to perform a motor task with one hand results in performance improvements in the other hand, a process called intermanual transfer. To gain information on its neural mechanisms, we studied this phenomenon using the serial reaction-time task (SRTT). Sixteen, right-handed volunteers trained a 12-item sequence of key presses repeated without the subjects' knowledge. Blocks with no repeating sequence, called random blocks, were interspersed with sequence-training blocks. Response times improved in random and training blocks in both hands. The former result reflects nonspecific improvement in performance, and the latter represents a sequence-specific improvement. To evaluate changes in the primary motor cortex (M1), we tested resting motor thresholds (RMT), recruitments curves to transcranial magnetic stimulation (RC), short intracortical inhibition (SICI), and interhemispheric inhibition (IHI) from the dominant left (learning) to the nondominant right (transfer) hemisphere, before and after SRTT training. Training resulted in (1) increased RC and decreased SICI but no changes in RMT in the learning hemisphere, (2) decreased SICI and no changes in RC or RMT in the transfer hemisphere, and (3) decreased IHI. The amount in IHI after training correlated with nonspecific performance improvements in the transfer hand but not with sequence-specific performance improvements. Our results indicate that modulation of interhemispheric inhibition between the M1 areas may, as a result of the learning that has occurred in one hemisphere after practice with one hand, contribute to faster, more skilled performance of the opposite hand.

Should the medial temporal lobe (MTL) of primates--which includes allocortical structures such as the hippocampus, neocortical structures such as the parahippocampal cortex, and nuclear structures such as the basolateral amygdala--be considered a single "thing"? According to the prevailing view, here termed the reification theory, the answer is yes. According to this theory, the MTL functions as an amalgamated entity that provides the neuronal mechanisms for declarative memory; the greater the damage to the MTL or any of its components, the greater the deleterious effects on declarative memory. A countervailing view, here called the balkanization theory, holds that the various components of the MTL process and store different kinds of information. According to this theory, damage to each part of the MTL causes a unique set of behavioral deficits-some involving memory, others involving perception, and yet others involving response selection. The empirical neuropsychological evidence favors the balkanization theory, as do some new concepts in theoretical neuroanatomy.

Previous studies have reported learning‐related changes in neuronal activity during conditional visuomotor learning, also known as arbitrary sensorimotor mapping, conditional visual discrimination, and symbolic or endogenous mapping. Qualitatively similar observations have been reported for the dorsal premotor cortex, the supplementary eye field, the prefrontal cortex, the hippocampus, the striatum and the globus pallidus. The fact that cells in both the dorsal premotor cortex (PMd) and the basal ganglia show changes in activity during associative learning enables a test of the hypothesis that cortex and basal ganglia function in distributed architectures known as cortical–basal ganglionic modules or 'loops'. We reasoned that if these loops represent functional entities, as proposed, then learning‐related changes in activity should occur simultaneously in both the cortical and striatal nodes of a loop. The present results confirmed this prediction; as monkeys learned conditional visuomotor associations, neurons in the premotor cortex and associated parts of the putamen changed their rates at approximately the same time. For the largest number of neurons, the evolution in neural activity occurred in close correspondence to the monkeys' learning curves. As a population, however, learning‐related changes in activity continued after the monkeys reached an asymptote in performance.

A paradigm is described for recording the activity of single cortical neurons from awake, behaving macaque monkeys. Its unique features include high-density microwire arrays and multichannel instrumentation. Three adult rhesus monkeys received microwire array implants, totaling 96–704 microwires per subject, in up to five cortical areas, sometimes bilaterally. Recordings 3–4 weeks after implantation yielded 421 single neurons with a mean peak-to-peak voltage of 115 ± 3 μV and a signal-to-noise ratio of better than 5:1. As many as 247 cortical neurons were recorded in one session, and at least 58 neurons were isolated from one subject 18 months after implantation. This method should benefit neurophysiological investigation of learning, perception, and sensorimotor integration in primates and the development of neuroprosthetic devices.

The selection and preparation of movement, as well as the decision to act, depend on the accumulation and maintenance of information within distributed neural networks. These networks perform several related functions, including: (1) identifying sensory inputs that might be targets of movement; (2) evaluating the biological impact of moving to those potential targets; (3) selecting the targets of action from among these possibilities, along with the movements needed to achieve those goals; (4) maintaining those intentions when action must be deferred; and (5) determining when to act. Neurons in the cerebral cortex of monkeys contribute to these networks, and some have discharge patterns resembling the late phase of the Bereitschaftspotential (BP) or the analogous phase of the Contingent Negative Variation (CNV). Many neurons show a steady build-up in activity over a few hundred milliseconds prior to movement, a property I will call ramp-to-threshold activity when it contributes to the selection of movement, or anticipatory activity when it contributes to motor readiness, an increased but nonspecific tendency to act. Perhaps this latter function comes closest to a correlate of the late BP at the single-cell level. Other cortical neurons have sustained changes in discharge rate that resemble the earlier phases of the CNV, termed delay period- or set-related activity, which can persist for several seconds. Set-related neurons participate in movement preparation, especially during intervals between movement selection and the decision to act.

Publisher Summary This chapter discusses population coding in the motor cortex. Single unit activity, accounted for input-output transforms in distributed neural networks. Serial recording during a stereotyped task has no demerits in understanding population coding, assuming a reasonable neuronal sample, and a hypothesis related to relatively stereotyped input-output mappings. Complex, emergent features of neuronal ensembles is not needed for an understanding of input-output mappings, but may play a role in more fundamental information-processing functions, such as learning, coordination among parallel networks, and attention to action. The population vector is computed from the activity of hidden units, but its accuracy does not depend on direct influences of hidden units on output elements. Cosine-like tuning and population vector coding emerged from a minimal-assumption network. The population vector rotated when the input output function is changed from the standard mapping to a nonstandard one. Population-vector rotation is accounted by a transition between two inputs, one representing the visual signal and reflecting standard visuomotor mapping, and the target signal into which it is transformed, and reflecting nonstandard mapping. The changes of hidden-unit tuning properties that occurred while the network learned a nonstandard transform corresponded to those observed in the motor cortex of a monkey that learned analogous transforms. The tuning properties of individual cells changed during the learning of both transformational and arbitrary mappings. During learning, the population vector became more accurate in both model and biological networks, for both standard and nonstandard mappings, and for both transformational and arbitrary nonstandard mappings.

▪ Abstract The dorsal premotor cortex is a functionally distinct cortical field or group of fields in the primate frontal cortex. Anatomical studies have confirmed that most parietal input to the dorsal premotor cortex originates from the superior parietal lobule. However, these projections arise not only from the dorsal aspect of area 5, as has long been known, but also from newly defined areas of posterior parietal cortex, which are directly connected with the extrastriate visual cortex. Thus, the dorsal premotor cortex receives much more direct visual input than previously accepted. It appears that this fronto-parietal network functions as a visuomotor controller—one that makes computations based on proprioceptive, visual, gaze, attentional, and other information to produce an output that reflects the selection, preparation, and execution of movements.

Il nous arrive souvent d'observer attentivement l'objet que nous nous preparons a saisir, et ceci jusqu'a ce que notre but soit atteint. Un mecanisme elabore, se situant principalement dans le tronc cerebral et dans la moelle epiniere, est dote de systemes de controle assurant le guidage spatial coherent des yeux, des membres et du corps vers des cibles de l'espace visuel. Nous utiliserons l'expression schema sensori-moteur standard pour designer les transformations sensori-motrices qui sous-tendent un tel comportement. Associees au schema sensori-moteur, les tâches de fixation, de poursuite et de prehension peuvent neanmoins etre dissociees les unes des autres. Ainsi, notre attention peut etre dirigee par des stimuli situes hors du champ de la cible d'action. Nous pouvons fixer notre regard dans une direction et saisir un objet situe dans une autre. Et nous pouvons guider une action spatiale au moyen de stimuli non spatiaux, comme lorsque, dans des tâches motrices conditionnelles, la couleur d'un objet ordonne l'execution d'un mouvement ailleurs dans l'espace. Toutes ces situations, et de nombreuses autres, font appel a un processus, que nous nommons schema non standard, ou le systeme nerveux central doit rejeter les correspondances habituelles entre les stimuli visuo-spatiaux, la fixation, le mouvement des yeux et les mouvements de prehension. Nous soulignons la possibilite que le cortex premoteur sous-tende le schema non standard et, par consequent, la flexibilite comportementale qui lui est associee.

In the typical course of daily events, we often gaze at an object, attend to its features and its place, reach toward it and grasp it, all with an awareness of what we are doing at the time. But behavior is not always thus. Gaze, attention, limb movement direction and awareness can be behaviorally dissociated from each other, and this review focuses on one such dissociation: that between the perception of an object and the use of that object's inherent spatial and nonspatial information for mediating visuomotor control. We review evidence that partially different neuronal systems underlie these two aspects of visual information processing. In neurophysiological studies of the primate frontal lobe, it has been possible to demonstrate that neural signals appearing to be visual responses reflect, at least in part, the motor significance of a stimulus. This finding has been confirmed, in separate studies, for both spatial and nonspatial visual information and supports the hypothesis that some frontal cortex activity reflects the selection and guidance of action rather than the properties of visual stimuli, per se. These findings are discussed in the context of neuropsychological studies indicating that accurate and appropriate movements are possible without perceptual awareness of the information guiding those movements.

We compared neuronal activity in the dorsal premotor cortex (PMd), ventral premotor cortex (PMv), and prefrontal (PF) cortex of two rhesus monkeys. The behavioral design was a variant of the instructed delay task which established that: (1) a given visual stimulus could, on different trials, instruct different limb movements and (2) several different visual stimuli could instruct the same movement. Neurons in all frontal areas displayed the often replicated activity patterns that occur during instructed delay tasks, including phasic increases after instruction stimuli (signal-related activity), tonic discharge during an instructed delay period (set-related activity), and phasic premovement discharge (movement-related activity). For signal-, set-, and movement-related activity, the majority of neurons in PMd (51-64%), but only a minority in PF (16-18%) and PMv (32-40%), showed activity levels that significantly depended on the action instructed by that stimulus rather than simply the characteristics of the stimulus per se. Thus, most PMd activity, including the aspects that most resembled a sensory response, reflected factors in addition to the signal. Taken together with the results of related studies, it seems most likely that these other factors are dominated by the motor instructional significance of the stimulus. In addition, many neurons (17-37%) in all examined areas showed activity that significantly depended on which of various stimuli guided the same movement. This finding shows that, in those frontal areas, neuronal activity can be affected by both the action to be taken and the events guiding that action.

We examined neuronal activity in three parts of the primate frontal cortex: the dorsal (PMd) and ventral (PMv) premotor cortex and a ventrolateral part of the dorsolateral prefrontal (PF) cortex. Two monkeys fixated a 0.2° white square in the center of a video display while depressing a switch located between two touch pads. On each trial, a spatial-attentional/mnemonic (SAM) cue was presented first. The SAM cue consisted of one 2° × 2° square, usually red or green, and its location indicated where a conditional motor instruction would appear after a delay period. The stimulus event containing the motor instruction, termed the motor instructional/conditional (MIC) cue, could be of two general types. It might consist of a single 2° × 2° square stimulus identical to one of the SAM cues presented at the same location as the SAM cue on that trial. When the MIC cue was a single square, it instructed the monkey to move its forelimb to one of the two touch pads according to the following conditional rule: a green MIC cue meant that contact with the right touch pad would be rewarded on that trial and a red MIC cue instructed a movement to the left touch pad. Alternatively, the MIC cue might consist of two 2° × 2° squares, only one of which was at the SAM-cue location: in those cases, one square was red and the other was green. The colored square at the SAM cue location for that trial was the instructing stimulus, and the other part of the MIC cue was irrelevant. When, after a variable delay period, the MIC cue disappeared, the monkey had to touch the appropriate target within 1 s to receive a reward and could break visual fixation. The experimental design allowed comparison of frontal cortical activity when one stimulus, identical in retinocentric, craniocentric, and allocentric spatial location as well as all other stimulus parameters, had two different meanings for the animal's behavior. When a stimulus was the SAM cue, it led to either a reorientation of spatial attention to its location, or the storage of its location in spatial memory. By contrast, when it was the MIC cue, the same stimulus instructed a motor act to be executed after a delay period. For the majority of PMd neurons (55%), post-MIC cue activity exceeded post-SAM cue activity. In many instances, no activity followed the SAM cue, although the identical stimulus caused profound modulation when it served as the MIC cue. In PF, by contrast, significantly fewer cells (30%) showed such a property, and PMv was intermediate in this respect (36%). The results support the hypothesis that many PMd cells reflect the motor significance of stimuli, and that a significantly smaller proportion of cells in PF do so.

Previous reports have argued that single neurons in the ventral premotor cortex of rhesus monkeys (PMv, the ventrolateral part of Brodmann's area 6) typically show spatial response fields that are independent of gaze angle. We reinvestigated this issue for PMv and also explored the adjacent prearcuate cortex (PAv, areas 12 and 45). Two rhesus monkeys were operantly conditioned to press a switch and maintain fixation on a small visual stimulus (0.2 degree x 0.2 degree) while a second visual stimulus (1 degree x 1 degree or 2 degrees x 2 degrees) appeared at one of several possible locations on a video screen. When the second stimulus dimmed, after an unpredictable period of 0.4-1.2 s, the monkey had to quickly release the switch to receive liquid reinforcement. By presenting stimuli at fixed screen locations and varying the location of the fixation point, we could determine whether single neurons encode stimulus location in "absolute space" or any other coordinate system independent of gaze. For the vast majority of neurons in both PMv (90%) and PAv (94%), the apparent response to a stimulus at a given screen location varied significantly and dramatically with gaze angle. Thus, we found little evidence for gaze-independent activity in either PMv or PAv neurons. The present result in frontal cortex resembles that in posterior parietal cortex, where both retinal image location and eye position affect responsiveness to visual stimuli.

Cerebellum means little brain. Cerebrum, of course, also means brain, but has come to refer primarily to the cerebral cortex and basal ganglia. One of the most vexing problems in brain physiology remains identifying the roles of these three structures in the selection and control of behavior. Unfortunately, researchers often study the cerebellum, cerebral cortex and basal ganglia independently. Indeed, many motor systems specialists often use the term “cortex” without modification despite the fact that both the forebrain and cerebellum have a cortex important in the control of movement. We set in this chapter, therefore, the objective of collective consideration of these three parts of the brain and their cooperative control functions. Our outline sketches one speculative view of how the cerebellum, basal ganglia and cerebral cortex might process information in a cooperative manner to establish goals, plan strategies and then program and implement a complex motor behavior.

Oxford University Press, 1998. £22.99 (pbk) (viii + 248 pages)ISBN 0 198 52441 2In the Hitchhiker's Guide to the Galaxy1xThe More than Complete Hitchhiker's Guide. Adams, D. See all References1, a computer named Deep Thought churns for 7.5 million years to answer the Great Question of Life, the Universe and Everything. The answer turns out to be forty-two, and as Deep Thought surmises, the people do not like it. The Prefrontal Cortex: Executive and Cognitive Functions attempts to answer a less universal question: What are the functions of the primate prefrontal cortex? Are its answers any more satisfying than Deep Thought's?If not, no fault lies with the editors of the present volume. They assembled a stellar cast and prepared an effective, concise volume based on a meeting of the Royal Society in 1996. In just 15 chapters, many current ideas about the functions of prefrontal cortex appear, including planning action, devising strategies, making decisions, selecting goals, using feedback, monitoring and ordering events, suppressing routine behavior, and subserving working memory, to recount a partial list that excludes language. However, because such a long list of functions remains fundamentally dissatisfying, it seems that every publishing house from Oxford University Press to Megadodo Publications would like to redress that discontent by launching a volume on prefrontal cortex. Some of these publications strive to synthesize an astronomical quantity of literature into a guide to the frontal lobe, such as the Passingham2xThe Frontal Lobes in Voluntary Action. Passingham, R.E. See all References2 and Fuster3xThe Prefrontal Cortex: Anatomy, Physiology, and Neuropsychology of the Frontal Lobe. Fuster, J.M. See all References3 monographs. Others, like the present anthology, offer readers a galaxy of authoritative progress reports from the authors' clinics and laboratories.This volume's most noteworthy contributions focus on memory (Baddeley and Della Sala; Shallice and Burgess; Petrides), strategies and response selection (Robbins; Passingham), the role of dopamine in development (Diamond), and the potential contribution of prefrontal dysfunction to schizophrenia (Weinberger and Berman; Frith; Cohen, Braver and O'Reilly). Damasio's chapter explains his somatic marker hypothesis, which holds that a central representation of body state (gut feeling) plays an essential role in decisions concerning oneself and others. Certain patients have a normal repertoire of social knowledge, but nevertheless make socially inappropriate decisions. The finding that damage to the ventromedial prefrontal cortex disrupts gut feelings and causes disadvantageous, inappropriate judgments represents an important advance. However, as Rolls points out in his chapter, the somatic marker hypothesis brings to mind older ideas. Like others before him, Teuber4xNeurophysiology, effects of focal brain lesions. Teuber, H-L. Neurosci. Res. Prog. Bull. 1972; 10: 381–384PubMedSee all References4 emphasized that ‘patients with frontal lobe disease… seem to perceive the mistakes they make, but are unable to use the information to guide their behavior’. Likewise, one patient's statement during psychological testing exemplifies the distinction between judgments and actions:if I put this card down, it will be wrong. You see – I am right – this one is wrong! And this one – wrong! and wrong again!’ He then proceeds in this fashion by contradicting in his actions what he can announce verbally as the correct procedure, evidently aware of the contradiction but incapable of avoiding it5xUnity and diversity of frontal lobe function. Teuber, H-L. Acta Neurobiol. Exp. 1972; 32: 615–656PubMedSee all References5.The somatic marker hypothesis helps to explain such machine-like behavior.This likable book does have its defects, however. Certain chapters contain material omissions, and only a minority of the authors address each others' views. Among this minority, Rolls, Robbins, Petrides, and Diamond contribute particularly useful discussions. In other chapters, the neglect of their many mutual contradictions creates some doubt about whether their authors attended the meeting that brought this book into being. Discordance among chapters is probably inevitable, but some contributions even lack internal consistency. For example, one author laments the confusion caused by the “ill-defined terms of ‘executive processing’ and ‘higher-order cognitive processing’” but later considers the ‘cognitive mechanisms that contribute to higher-order executive processing’ with little elucidation of those terms. However, these are relatively minor quibbles. If this book fails to dispel discontentment over our level of understanding the prefrontal cortex, they are not the reasons.Perhaps we find the current state of the art so unsatisfying because most of the prevailing ideas leave the impression of timelessness. As Fulton6xPhysiology of the Nervous System. Fulton, J.F. See all References6 commented a half century ago:The earliest experiments on the frontal areas were those of the French neurologist Flourens (1824), who, on the basis of ablation studies, cast to the four winds the then current phrenological doctrines… He attributed to the frontal lobes, acting in harmony with the rest of the brain, the higher perceptual, associative, and executive functions of the mind.Have ideas about the prefrontal cortex changed fundamentally in our time? Inferences first drawn at the dawn of neuroscience appear in new guises to undergo relentless promotion as the key advance. The quest for synthesis encourages the neglect of sound evidence. And the unearthing of the global function of prefrontal cortex – announced every few years – yields a remarkably familiar account. By now, virtually every possibility has been suggested, so future theories of the prefrontal cortex, too, will probably echo much from the past. As those new or resurrected concepts evolve, will any time-honored ideas become extinct? As Fulton pointed out in the quotation above, the field had already cast aside one view of prefrontal function by 1824, but that feat has seldom been replicated in the intervening 175 years. The habit of recycling and rarely rejecting a limited constellation of ideas suggests that we already know the most likely functions of the primate prefrontal cortex. Perhaps our dissatisfaction results not from failing to have the answers, but from not liking the answers that we do have. Twenty-first century authorities may conclude that our contemporaries rejected so few conceptions concerning prefrontal cortex because, as a group, the ideas of our time suffered from the twin nuisances of untestability and validity. As Gaffan7xInteraction of temporal lobe and frontal lobe in memory. Gaffan, D. : 129–138CrossrefSee all References7 has advised, ‘let us accept at the outset that the prefrontal cortex is involved in all types of memory’, to which one might add all other aspects of information processing important to the life history of primates. Like forty-two, some answers are simply unsatisfying.

We examined whether reported physiological distinctions between prefrontal (PF) and premotor (PM) areas reflect true dissimilarity or instead result from technical considerations such as differences among species, individuals, or behavioural, physiological and anatomical techniques. A Rhesus monkey performed a task involving 2 stimulus events on each trial: the first stimulus appeared briefly, then after a delay period, 2 peripheral stimuli appeared simultaneously. The monkey had to delay responding for an additional, self-timed instructed delay period, then contact a touch pad beneath the peripheral stimulus of the colour matching the first stimulus. PM and PF cortex differ in several respects. More PF than PM neurons discharge during the presentation of the first stimulus, and only PF neurons show phasic bursts of activity shortly after that stimulus disappears. During the instructed delay period, cells in PF begin activity earlier than PM neurons, whereas PM neurons continue their activity longer. Similarly, PF cells show greater discharge modulation early in the instructed delay period compared with PM cells, which discharge more intensely later. Cells with apparent selectivity for stimulus characteristics appear only in PF. Thus our results support the view that PM and PF have distinctive physiological properties that cannot be accounted for by technical considerations alone. In addition, we describe the activity cells in a cortical region, here termed the dorsomedial frontal cortex, which has a distinctive dysgranular cytoarchitecture and has physiological properties that ally it with PF.

Neurons in the premotor cortex of rhesus monkeys were studied under two conditions: (1) visuospatial cues were given to guide the amplitude, direction, and onset time of forearm movements or (2) physically identical visual cues were given when reward was contingent on withholding movement. Neurons with sustained activity following the cues were preferentially active when the cues triggered a movement. Thus, activity of certain neurons in this cortical field is linked to motor set, i.e. intention to make a movement in response to the cue, rather than the visual cue per se.

Fifty years ago, F.M.R. Walshe launched his famous diatribe against J.F. Fulton and his thesis that a premotor area with specialized functions exists within the agranular frontal cortex of primates. Now there is general agreement that the agranular frontal cortex contains at least 3 cortical fields: the primary motor cortex, the supplementary motor cortex, and the premotor cortex. This paper summarizes some of the evidence that the premotor cortex plays a role in the preparation for limb movements and presents speculation concerning the aspects of motor preparation in which the premotor cortex might be involved.

Pre-cue activity, the neuronal modulation that precedes a predictable stimulus, was studied in the premotor cortex of three rhesus monkeys. In one condition, a directional cue dictated the timing and target of a forelimb movement. In another condition, a nondirectional cue provided identical timing information but did not indicate the target. Of 501 task-related neurons recorded in premotor cortex, 168 showed pre-cue activity. The onset time of pre-cue activity varied markedly from trial to trial and cell to cell, ranging from trial initiation to 4.8 sec later. No pre-cue activity reflected the direction of limb movement; thus, the data argue against the hypothesis that pre-cue activity reflects preparation for specific limb movements. A small number of cells showed greater pre-cue activity before directional than before nondirectional cues, and this difference may reflect anticipation of the cue's directional information. However, the vast majority (84%) of neurons lacked such differences. We therefore hypothesize that most pre-cue activity reflects or contributes to a facet of behavior common to the two conditions: anticipation of the time and/or nature of events.

The importance of the mammalian cerebral cortex in the control of movement has been accepted for a century. Recent studies indicate that the number of cortical fields involved in motor control is much greater than previously believed. This article summarizes neuroanatomical and neurophysiological investigations which suggest that each of these cortical fields has a specialized role in the control of movement.