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Rhesus monkeys performed two tasks, both requiring a choice between a red square and a blue circle. In the duration task, the two stimuli appeared sequentially on each trial, for varying durations, and, later, during the choice phase of the task, the monkeys needed to choose the one that had lasted longer. In the matching-to-sample task, one of the two stimuli appeared twice as a sample, with durations matching those in the duration task, and the monkey needed to choose that stimulus during the choice phase. Although stimulus duration was irrelevant in the matching-to-sample task, the monkeys made twice as many errors when the second stimulus was shorter. This across-task interference supports an order-dependent model of the monkeys' choice and reveals something about their strategy in the duration task. The monkeys tended to choose the second stimulus when its duration exceeded the first and to choose the alternative stimulus otherwise. For the duration task, this strategy obviated the need to store stimulus-duration conjunctions for both stimuli, but it generated errors on the matching-to-sample task. We examined duration coding in prefrontal neurons and confirmed that a population of cells encoded relative duration during the matching-to-sample task, as expected from the order-dependent errors.

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.

Neurophysiological and neuropsychological studies in monkeys sometimes require an automated food-pellet dispenser. Commercially available dispensers typically sequester the pellet until delivery and, once delivered, the pellet's availability cannot be controlled. The custom-designed dispenser described here overcomes those two limitations. The device is composed of two separate units: a feeder and an electronic controller. The feeder manipulates food pellets with actuators driven by air pressure and delivers them into a serving bowl. The controller's settings determine whether the monkey can retrieve a pellet from the bowl. If the experiment requires that the pellet be visible and within reach, but unavailable for retrieval, the controller enables a trap-door mechanism at the bottom of the bowl. Any motion near the serving bowl, such as that caused by the approach of a monkey's hand, will then trigger the opening of the trap door, which causes the pellet to fall into an enclosed pellet collector. This rapid pellet-removal mechanism can also be triggered by other computer-controlled contingencies. Two of these dispensers have been in operation in an applied laboratory setting for over 2 years.

When a small, focally attended visual stimulus and a larger background frame shift location at the same time, the frame's new location can affect spatial perception. For horizontal displacements on the order of 1–2°, when the frame moves more than the attended stimulus, human subjects may perceive that the attended stimulus has shifted to the right or left when it has not done so. However, that misapprehension does not disable accurate eye movements to the same stimulus. We trained a rhesus monkey to report the direction that an attended stimulus had shifted by making an eye movement to one of the two report targets. Then, using conditions that induce displacement illusions in human subjects, we tested the hypothesis that neuronal activity in the prefrontal cortex (PF) would reflect the displacement directions reported by the monkey, even when they conflicted with the actual displacement, if any, of the attended stimulus. We also predicted that these cells would have directional selectivity for movements used to make those reports, but not for similar eye movements made to fixate the attended stimulus. A population of PF neurons showed the predicted properties, which could not be accounted for on the basis of either eye-movement or frame-shift parameters. This activity, termed report-related, began approximately 150 ms before the onset of the reporting saccade. Another population of PF neurons showed greater directional selectivity for saccadic eye movements made to fixate the attended stimulus than for similar saccades made to report its displacement. In view of the evidence that PF functions to integrate inputs and actions occurring at different times and places, the present findings support the idea that such integration involves movements to acquire response targets, directly, as well as actions guided by less direct response rules, such as perceptual reports.

Neural network models were examined during delayed matching-to-sample tasks (DMS), and neurons in a monkey's prefrontal cortex were studied during the performance of comparable tasks. In DMS, various input stimuli follow a sample stimulus, and an output should occur whenever the sample reappears. Our previous models have been restricted to certain kinds of inputs, outputs, and temporal patterns. Here, we generalized the models by training them on both spatial and nonspatial inputs, spatial and nonspatial outputs, and both fixed and variable interstimulus intervals. Two versions of DMS were presented to both the model and the monkey, both involving nonspatial samples: (1) Two stimuli simultaneously appeared at a variable interval after the sample; and (2) A series of single stimuli appeared at fixed intervals after the sample. Both versions required identical spatial responses, reflecting the direction (left or right) of the matching stimulus relative to a central origin. Thus, these two versions of DMS involved the same samples, memory, and responses, but established different response contexts. Our analysis focused on unit activity prior to stimuli, as well as that prior to responses, termed anticipatory and response-related activity, respectively. In both the model and the monkey, anticipatory activity occurred only for fixed interstimulus intervals. In the model, we could determine that anticipatory activity acted either like a filter to suppress inappropriate responses or it served to enhance the network's general readiness to respond. As for response-related activity, units in both the model and the monkey showed directional selectivity and had a strong dependence on response context. In the model, we could show that this activity contributed both to the suppression of inappropriate responses and to the generation of correct ones. None of the model's hidden units contributed exclusively to computing the direction of match output. Instead, their response-related activity contributed to the computation of both the match decision and the correct response direction.

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.

We studied single-neuron activity in the prefrontal cortex (PF) while a monkey performed a task according to two different rules, termed conditional and spatial. The monkey viewed a video screen, and its task required a hand movement in response to the dimming of a light spot. There were four light spots on the screen: right, left, up, and down from the center. Only one of the four spots dimmed, and the degree of dimming was slight. Accordingly, the monkey needed to foveate the "correct" light spot to detect the dimming. A visual cue indicated which of the four light spots would be deemed correct and, thus, would dim on each trial. The sequence of events was as follows: a fixation spot appeared at the center of the screen; then, a cue appeared twice at one of the four potential target locations; then, the four target spots appeared; and, finally, one of them dimmed. Except for the color of an initial fixation point, the cues, their locations, and other events were identical for the conditional and spatial rules. The rules differed in one essential way. For the conditional rule, nonspatial attributes of the visual cue indicated which of the four light spots would dim, and the cue's location was irrelevant. For the spatial rule, the cue's location determined the correct target on that trial. The light spot at the location of the cue always dimmed, regardless of which cue appeared there. Our sample included 221 PF neurons showing significant task-related activity modulation, distributed among dorsal, dorsolateral, and ventral PF regions. Between one-third and one-half of the sample in each of those regions showed statistically significant activity differences that could be attributed to the rule. Selectivity for cues and/or their locations was common. However, there was no significant regional segregation of such selectivity. These data support the hypothesis that PF plays a role in the guidance of behavior according to previously learned rules.

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.

Classen, Joseph, Joachim Liepert, Steven P. Wise, Mark Hallett, and Leonardo G. Cohen. Rapid plasticity of human cortical movement representation induced by practice. J. Neurophysiol. 79: 1117–1123, 1998. The process of acquiring motor skills through the sustained performance of complex movements is associated with neural plasticity. However, it is unknown whether even simple movements, repeated over a short period of time, are effective in inducing cortical representational changes. Whether the motor cortex can retain specific kinematic aspects of a recently practiced movement is also unknown. We used focal transcranial magnetic stimulation (TMS) of the motor cortex to evoke isolated and directionally consistent thumb movements. Thumb movements then were practiced in a different direction. Subsequently, TMS came to evoke movements in or near the recently practiced direction for several minutes before returning to the original direction. To initiate a change of the TMS-evoked movement direction, 15 or 30 min of continuous training were required in most of the subjects and, on two occasions, as little as 5 or 10 min. Substantially smaller effects followed more direct stimulation of corticofugal axons with transcranial electrical stimulation, pointing to cortex as the site of plasticity. These findings suggest that the training rapidly, and transiently, established a change in the cortical network representing the thumb, which encoded kinematic details of the practiced movement. This phenomenon may be regarded as a short-term memory for movement and be the first step of skill acquisition.

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.

Two rhesus monkeys performed a distance discrimination task in which they reported whether a red square or a blue circle had appeared farther from a fixed reference point. Because a new pair of distances was chosen randomly on each trial, and because the monkeys had no opportunity to correct errors, no information from the previous trial was relevant to a current one. Nevertheless, many prefrontal cortex neurons encoded the outcome of the previous trial on current trials. A smaller, intermingled population of cells encoded the spatial goal on the previous trial or the features of the chosen stimuli, such as color or shape. The coding of previous outcomes and goals began at various times during a current trial, and it was selective in that prefrontal cells did not encode other information from the previous trial. The monitoring of previous goals and outcomes often contributes to problem solving, and it can support exploratory behavior. The present results show that such monitoring occurs autonomously and selectively, even when irrelevant to the task at hand.

Deiber, M.-P., S. P. Wise, M. Honda, M. J. Catalan, J. Grafman, and M. Hallett. Frontal and parietal networks for conditional motor learning: a positron emission tomography study. J. Neurophysiol. 78: 977–991, 1997. Studies on nonhuman primates show that the premotor (PM) and prefrontal (PF) areas are necessary for the arbitrary mapping of a set of stimuli onto a set of responses. However, positron emission tomography (PET) measurements of regional cerebral blood flow (rCBF) in human subjects have failed to reveal the predicted rCBF changes during such behavior. We therefore studied rCBF while subjects learned two arbitrary mapping tasks. In the conditional motor task, visual stimuli instructed which of four directions to move a joystick (with the right, dominant hand). In the evaluation task, subjects moved the joystick in a predetermined direction to report whether an arrow pointed in the direction associated with a given stimulus. For both tasks there were three rules: for the nonspatial rule, the pattern within each stimulus determined the correct direction; for the spatial rule, the location of the stimulus did so; and for the fixed-response rule, movement direction was constant regardless of the pattern or its location. For the nonspatial rule, performance of the evaluation task led to a learning-related increase in rCBF in a caudal and ventral part of the premotor cortex (PMvc, area 6), bilaterally, as well as in the putamen and a cingulate motor area (CM, area 24) of the left hemisphere. Decreases in rCBF were observed in several areas: the left ventro-orbital prefrontal cortex (PFv, area 47/12), the left lateral cerebellar hemisphere, and, in the right hemisphere, a dorsal and rostral aspect of PM (PMdr, area 6), dorsal PF (PFd, area 9), and the posterior parietal cortex (area 39/40). During performance of the conditional motor task, there was only a decrease in the parietal area. For the spatial rule, no rCBF change reached significance for the evaluation task, but in the conditional motor task, a ventral and rostral premotor region (PMvr, area 6), the dorsolateral prefrontal cortex (PFdl, area 46), and the posterior parietal cortex (area 39/40) showed decreasing rCBF during learning, all in the right hemisphere. These data confirm the predicted rCBF changes in premotor and prefrontal areas during arbitrary mapping tasks and suggest that a broad frontoparietal network may show decreased synaptic activity as arbitrary rules become more familiar.

Chen, Longtang L. and Steven P. Wise. Conditional oculomotor learning: population vectors in the supplementary eye field. J. Neurophysiol. 78: 1160–1163, 1997. We have shown previously that the activity levels and preferred directions of supplementary eye field neurons change as monkeys learn to associate nonspatial visual information with a saccade (or the spatial target of that saccade). The present report describes changes in neuronal population vectors (PV) during such learning. PVs based on neuronal activity shortly before and after saccades predicted movement direction poorly in the earliest stage of learning, but as monkeys mastered novel stimulus-response mappings, PV accuracy and magnitude increased significantly.

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.

A common conjecture about the basal ganglia holds that these nuclei and their cortical inputs subserve relatively automatic stimulus–response behavior (habits) and other procedural memories. This speculative hypothesis warrants critical reassessment. No unequivocal evidence supports the assignment of this information-processing specialization to the basal ganglia or its cortical afferents.

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.

We compared neuronal activity in the dorsolateral (PFdl), orbital (PFo), and polar (PFp) prefrontal cortex as monkeys performed three tasks. In two tasks, a cue instructed one of two strategies: stay with the previous response or shift to the alternative. Visual stimuli served as cues in one of these tasks; in the other, fluid rewards did so. In the third task, visuospatial cues instructed each response. A delay period followed each cue. As reported previously, PFdl encoded strategies (stay or shift) and responses (left or right) during the cue and delay periods, while PFo encoded strategies and PFp encoded neither strategies nor responses; during the feedback period, all three areas encoded responses, but not strategies. Four novel findings emerged from the present analysis. (1) The strategy encoded by PFdl and PFo cells during the cue and delay periods was modality specific. (2) The response encoded by PFdl cells was task and modality specific during the cue period, but during the delay and feedback periods it became task and modality general. (3) Although some PFdl and PFo cells responded to or anticipated rewards, we could rule out reward effects for most strategy- and response-related activity. (4) Immediately before feedback, only PFp signaled responses that were correct according to the cued strategy; after feedback, only PFo signaled the response that had been made, whether correct or incorrect. These signals support a role in generating responses by PFdl, assigning outcomes to choices by PFo, and assigning outcomes to cognitive processes by PFp.

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.

Despite a half century of development, the orthodox monkey model of human amnesia needs improvement, in part because of two problems inherent in animal models of advanced human cognition. First, animal models are perforce comparative, but the principles of comparative and evolutionary biology have not featured prominently in developing the orthodox model. Second, no one understands the relationship between human consciousness and cognition in other animals, but the orthodox model implicitly assumes a close correspondence. If we treat these two difficulties with the deference they deserve, monkeys can tell us a lot about human amnesia and memory. Three future contributions seem most likely: (1) an improved monkey model, one refocused on the hippocampus rather than on the medial temporal lobe as a whole; (2) a better understanding of cortical areas unique to primates, especially the granular prefrontal cortex; and (3), taking the two together, insight into prefrontal-hippocampal interactions. We propose that interactions among the granular prefrontal areas create the kind of cross-domain, analogical and self-referential knowledge that underlies advanced cognition in modern humans. When these products of frontal-lobe function interact with the hippocampus, and its ancestral function in navigation, what emerges is the human ability to embed ourselves in scenarios — real and imagined, self-generated and received — thereby creating a coherent, conscious life experience.

In motor and sensory areas of cortex, neuronal activity often depends on the location of a movement target or a sensory stimulus, with each neuron tuned to a single part of space called a preferred direction (when motor) or a receptive field (when sensory). As we previously reported, some neurons in the monkey prefrontal cortex are tuned to two parts of space, which we interpreted as reflecting attention and working memory, respectively. Monkeys performed a behavioral task in which they attended to a visual stimulus at one location while remembering a second place, and these locations were varied from trial to trial to assess spatial tuning. Most spatially tuned neurons specialized in either attentional or mnemonic processing, but about one-third of the cells showed tuning for both. Here, we show that the latter population, called multitasking neurons, improves the encoding of both the attended and remembered locations. These neurons do so for three reasons: (1) the preferred directions for attention and for working memory usually differ (and often diametrically oppose one another), (2) they have stronger tuning than specialized cells, and (3) pairs of multitasking neurons represent these cognitive parameters more efficiently than pairs that include even a single specialized cell. These findings suggest that multitasking neurons provide a computational advantage for behaviors that place simultaneous demands on two or more cognitive processes.

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.

We reported previously that as monkeys used abstract response strategies to choose spatial goals, 1 population of prefrontal cortex neurons encoded future goals (F cells), whereas a largely separate population encoded previous goals (P cells). Here, to better understand the mechanisms of goal selection and maintenance, we studied correlated activity among pairs of these neurons. Among the 3 possible types of pairs, F-F and F-P pairs often exhibited significant correlations when and after monkeys selected future goals but P-P pairs rarely did. These correlations were stronger when monkeys shifted from a previous goal than when they stayed with that goal. In addition, members of F-F pairs usually preferred the same goal and thus shared both prospective coding and spatial tuning properties. In contrast, cells composing F-P pairs usually had different spatial preferences and thus shared neither coding nor spatial tuning properties. On the assumption that the neurons composing a pair send convergent outputs to target neurons, their correlated activity could enhance their efficacy in context-dependent goal selection, goal maintenance, and the transformation of goal choices into action.

The primate prefrontal cortex (PF) plays a central role in choosing goals and strategies. To better understand its mechanisms, we recorded from PF neurons as monkeys used abstract response strategies to select a spatial goal. A visual cue, selected randomly from a set of three cues, appeared on each trial. All three cues were novel when neuronal recording commenced. From trial to trial, the cue could have either been repeated or changed from the previous trial; these were called repeat trials and change trials, respectively. On repeat trials, the monkeys used a Repeat-stay strategy to gain a reward by choosing the same spatial goal as on the previous trial; on change trials, they used a Change-shift strategy to reject the previous goal in favour of an alternative. We reported previously that when monkeys performed the task correctly, many PF neurons had activity encoding one of these two strategies. The monkeys sometimes chose the incorrect strategy, however. Strategy coding was weak or absent during the cue period of error trials which was, for correct trials, the time when the monkeys used a strategy to choose a future goal. By contrast, later in the trial, after the chosen goal had been attained and the monkeys awaited feedback, strategy coding was present and it reflected the strategy used, whether correct or incorrect. The weak cue-period strategy signal could, whatever its cause, have contributed to the errors made, whereas the activity prior to feedback suggests a role in monitoring task performance.