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Unlabelled: To expedite the selection of action under a structured behavioral context, we develop an expedient to promote its efficiency: tactics for action selection. Setting up a behavioral condition for subhuman primates (Macaca fuscata) that induced the development of a behavioral tactics, we explored neuronal representation of tactics in the medial frontal cortex. Here we show that neurons in the posterior medial prefrontal cortex, but not much in the medial premotor cortex, exhibit activity representing the behavioral tactics, in advance of action-selective activity. Such activity appeared during behavioral epochs of its retrieval from instruction cues, maintenance in short-term memory, and its implementation for the achievement of action selection. At a population level, posterior medial prefrontal cortex neurons take part in transforming the tactics information into the information representing action selection. The tactics representation revealed an aspect of neural mechanisms for an adaptive behavioral control, taking place in the medial prefrontal cortex., Significance Statement: We studied behavioral significance of neuronal activity in the posterior medial prefrontal cortex (pmPFC) and found the representation of behavioral tactics defined as specific and efficient ways to achieve objectives of actions. Neuronal activity appeared during behavioral epochs of its retrieval from instruction cues, maintenance in short-term memory, and its use preceding the achievement of action selection. We found further that pmPFC neurons take part in transforming the tactics information into the information representing action selection. A majority of individual neurons was recruited during a limited period in each behavioral epoch, constituting, as a whole, a temporal cascade of activity. Such dynamics found in behavioral-tactics specific activity characterize the participation of pmPFC neurons in executive control of purposeful behavior., (Copyright © 2016 the authors 0270-6474/16/365974-14$15.00/0.)

Visual search is coordinated adaptively by monitoring and predicting the environment. The supplementary eye field (SEF) plays a role in oculomotor control and outcome evaluation. However, it is not clear whether the SEF is involved in adjusting behavioral modes based on preceding feedback. We hypothesized that the SEF drives exploration-exploitation transitions by generating "surprise signals" or rectified prediction errors, which reflect differences between predicted and actual outcomes. To test this hypothesis, we introduced an oculomotor two-target search task in which monkeys were required to find two valid targets among four identical stimuli. After they detected the valid targets, they exploited their knowledge of target locations to obtain a reward by choosing the two valid targets alternately. Behavioral analysis revealed two distinct types of oculomotor search patterns: exploration and exploitation. We found that two types of SEF neurons represented the surprise signals. The error-surprise neurons showed enhanced activity when the monkey received the first error feedback after the target pair change, and this activity was followed by an exploratory oculomotor search pattern. The correct-surprise neurons showed enhanced activity when the monkey received the first correct feedback after an error trial, and this increased activity was followed by an exploitative, fixed-type search pattern. Our findings suggest that error-surprise neurons are involved in the transition from exploitation to exploration and that correct-surprise neurons are involved in the transition from exploration to exploitation., (Copyright © 2015 the American Physiological Society.)

The dorsal aspect of the globus pallidus (GP) communicates with the prefrontal cortex and higher-order motor areas, indicating that it plays a role in goal-directed behavior. We examined the involvement of dorsal GP neurons in behavioral goal monitoring and maintenance, essential components of executive function. We trained two macaque monkeys to choose a reach target based on relative target position in a spatial goal task or a target shape in an object-goal task. The monkeys were trained to continue to choose a certain behavioral goal when reward volume was constant and to switch the goals when the volume began to decrease. Because the judgment for the next goal was made in the absence of visual signals, the monkeys were required to monitor and maintain the chosen goals during the reaching movement. We obtained three major findings. (1) GP neurons reflected more of the relative spatial position than the shape of the reaching target during the spatial goal task. During the object-goal task, the shape of the reaching object was represented more than the relative position. (2) The selectivity of individual neurons for the relative position was enhanced during the spatial goal task, whereas the object-shape selectivity was enhanced during the object-goal task. (3) When the monkeys switched the goals, the selectivity for either the position or shape also switched. Together, these findings suggest that the dorsal GP is involved in behavioral goal monitoring and maintenance during execution of goal-oriented actions, presumably in collaboration with the prefrontal cortex.

The medial frontal cortex has been thought to be crucially involved in temporal structuring of behavior in monkeys and humans. We examined neuronal activity in the supplementary and presupplementary motor areas of monkeys to investigate how the nervous system deals with the coding of 16 motor sequences resulting from multiple actions involving bilateral use of the arms. We first found in both areas that this behavioral demand resulted in attribute-based representation of individual motor acts, reflecting functional (action) or anatomical (right/left arm) attributes. Actions were frequently represented according to a body-axis-centered reference frame (supination or pronation) regardless of the arm to be used. Moreover, behavioral sequences were primarily represented with respect to the action- or arm-use sequence rather than the sequence of individual movements. We propose that the two-dimensional attribute-based sequence representation provides a robust and efficient means of processing multiple behavioral sequences.

Volitional selection of action is subject to continuous adjustment under the influence of information obtained by monitoring behavioral consequences and by exploiting behavioral context based on prior knowledge about the environment. The rostral cingulate motor area (CMAr) is thought to be responsible for adjusting behavior by monitoring its consequences. To investigate whether the CMAr also plays a role in exploitation of behavioral context in action selection, we recorded neuronal activities from the CMAr while monkeys performed a reward-based motor selection task that required them to switch from one action to the other based on the amount of reward. We examined both the behavior of monkeys and the activity of CMA neurons quantitatively by constructing a hybrid reinforcement learning model incorporating context-based and outcome-based action values into a new action value. We found that CMAr neurons encoded the context-based action value by increasing or decreasing their firing rates gradually with the number of repetitions of the same movement (i.e., behavioral context). We also found that CMAr neurons encoded the context-based and outcome-based action values in two distinct time windows at single neuron and population levels. Our findings indicate that the CMAr is involved in behavioral adjustment of action selection by exploiting the behavioral context and not merely by monitoring reward outcome.

Multiple loop circuits interconnect the basal ganglia and the frontal cortex, and each part of the cortico-basal ganglia loops plays an essential role in neuronal computational processes underlying motor behavior. To gain deeper insight into specific functions played by each component of the loops, we compared response properties of neurons in the globus pallidus (GP) with those in the dorsal premotor cortex (PMd) and the ventrolateral and dorsolateral prefrontal cortex (vlPFC and dlPFC) while monkeys performed a behavioral task designed to include separate processes for behavioral goal determination and action selection. Initially, visual signals instructed an abstract behavioral goal, and seconds later, a choice cue to select an action was presented. When the instruction cue appeared, GP neurons started to reflect visual features as early as vlPFC neurons. Subsequently, GP neurons began to reflect goals informed by the visual signals no later than neurons in the PMd, vlPFC, and dlPFC, indicating that the GP is involved in the early determination of behavioral goals. In contrast, action specification occurred later in the GP than in the cortical areas, and the GP was not as involved in the process by which a behavioral goal was transformed into an action. Furthermore, the length of time representing behavioral goal and action was shorter in the GP than in the PMd and dlPFC, indicating that the GP may play an important role in detecting individual behavioral events. These observations elucidate the involvement of the GP in goal-directed behavior.

Previous studies have shown that elementary aspects of numerical abilities have developed in non-human primates. In the present study, we explored the potential for the development of a novel ability in the use of numerical operations by macaque monkeys (Macaca fuscata): adequate selection of a series of numerical actions toward achieving a behavioral goal. We trained monkeys to use a pair of devices to selectively add or subtract items to/from a digital array in order to match a previously viewed sample array. The monkeys determined whether to add or subtract on the basis of the feedback about numerosity given to the monkeys, which was displayed as an outcome of each step of the numerical operation. We also found that monkeys adapted flexibly to changes in the numerical rule that determined the relationship between device use and numerical operation. Our model analysis found that the numerosity-based model was a better fit for the monkeys' performance than was the reward-expectation-based model. Such a capacity for goal-oriented selection of numerical operations suggests a mechanism by which monkeys use numerical representations for purposeful behaviors.

The functional roles of the primate posterior medial prefrontal cortex have remained largely unknown. Here, we show that this region participates in the regulation of actions in the presence of multiple response tactics. Monkeys performed a forelimb task in which a visual cue required prompt decision of reaching to a left or a right target. The location of the cue was either ipsilateral (concordant) or contralateral (discordant) to the target. As a result of extensive training, the reaction times for the concordant and discordant trials were indistinguishable, indicating that the monkeys developed tactics to overcome the cue-response conflict. Prefrontal neurons exhibited prominent activity when the concordant and discordant trials were randomly presented, requiring rapid selection of a response tactic (reach toward or away from the cue). The following findings indicate that these neurons are involved in the selection of tactics, rather than the selection of action or monitoring of response conflict: (i) The response period activity of neurons in this region disappeared when the monkeys performed the task under the behavioral condition that required a single tactic alone, whereas the action varied across trials. (ii) The neuronal activity was found in the dorsomedial prefrontal cortex but not in the anterior cingulate cortex that has been implicated for the response conflict monitoring. These results suggest that the medial prefrontal cortex participates in the selection of a response tactic that determines an appropriate action. Furthermore, the observation of dynamic, task-dependent neuronal activity necessitates reconsideration of the conventional concept of cortical motor representation.

The prefrontal cortex (PFC) plays a crucial role in flexible cognitive behavior by representing task relevant information with its working memory. The working memory with sustained neural activity is described as a neural dynamical system composed of multiple attractors, each attractor of which corresponds to an active state of a cell assembly, representing a fragment of information. Recent studies have revealed that the PFC not only represents multiple sets of information but also switches multiple representations and transforms a set of information to another set depending on a given task context. This representational switching between different sets of information is possibly generated endogenously by flexible network dynamics but details of underlying mechanisms are unclear. Here we propose a dynamically reorganizable attractor network model based on certain internal changes in synaptic connectivity, or short-term plasticity. We construct a network model based on a spiking neuron model with dynamical synapses, which can qualitatively reproduce experimentally demonstrated representational switching in the PFC when a monkey was performing a goal-oriented action-planning task. The model holds multiple sets of information that are required for action planning before and after representational switching by reconfiguration of functional cell assemblies. Furthermore, we analyzed population dynamics of this model with a mean field model and show that the changes in cell assemblies' configuration correspond to those in attractor structure that can be viewed as a bifurcation process of the dynamical system. This dynamical reorganization of a neural network could be a key to uncovering the mechanism of flexible information processing in the PFC.

The proper timing of actions is necessary for the survival of animals, whether in hunting prey or escaping predators. Researchers in the field of neuroscience have begun to explore neuronal signals correlated to behavioral interval timing. Here, we attempt to decode the lapse of time from neuronal population signals recorded from the frontal cortex of monkeys performing a multiple-interval timing task. We designed a Bayesian algorithm that deciphers temporal information hidden in noisy signals dispersed within the activity of individual neurons recorded from monkeys trained to determine the passage of time before initiating an action. With this decoder, we succeeded in estimating the elapsed time with a precision of approximately 1 s throughout the relevant behavioral period from firing rates of 25 neurons in the pre-supplementary motor area. Further, an extended algorithm makes it possible to determine the total length of the time-interval required to wait in each trial. This enables observers to predict the moment at which the subject will take action from the neuronal activity in the brain. A separate population analysis reveals that the neuronal ensemble represents the lapse of time in a manner scaled relative to the scheduled interval, rather than representing it as the real physical time.

The hallmark of higher-order brain functions is the ability to integrate and associate diverse sets of information in a flexible manner. Thus, fundamental knowledge about the mechanisms underlying of information in the brain can be obtained by examining the neural mechanisms involved in the generation of an appropriate motor command based on perceived sensory signals. In this review article, we have focused on the involvement of the neuronal networks centered at the lateral aspect of the frontal cortex in the process of motor selection and motor planning based on visual signals. We have initially discussed the role of the lateral prefrontal cortex in integrating multiple sets of visual signals to select a reach target and the participation of the premotor cortex in retrieving and integrating diverse sets of motor information, such as where should one reach out or which arm is to be used. Next, based on the results of the studies on ideomotor apraxia, we have hypothesized that there are at least 2 distinct levels of neural representation (virtual level and physical level). We have reviewed the evidence supporting the operation of 2 distinct classes of neuronal activities corresponding to these 2 levels. In conclusion, we propose that the frontal cortex initially processes information across sensory and motor domains at the virtual level to generate information about a forthcoming motor action (virtual action plan) and that this information is subsequently transformed into a motor command, such as muscle activity or movement direction, for an actual body movement at the physical level (physical motor plan). This proposed framework may be useful for explaining the diverse clinical conditions caused by brain lesions as well as for clarifying the neural mechanisms underlying the integration of perception and action.

We examined the organization of multisynaptic projections from the basal ganglia (BG) to the dorsal premotor area in macaques. After injection of the rabies virus into the rostral sector of the caudal aspect of the dorsal premotor area (F2r) and the caudal sector of the caudal aspect of the dorsal premotor area (F2c), second-order neuron labeling occurred in the internal segment of the globus pallidus (GPi) and the substantia nigra pars reticulata (SNr). Labeled GPi neurons were found in the caudoventral portion after F2c injection, and in the dorsal portion at the rostrocaudal middle level after F2r injection. In the SNr, F2c and F2r injections led to labeling in the caudal or rostral part, respectively. Subsequently, third-order neuron labeling was observed in the external segment of the globus pallidus (GPe), the subthalamic nucleus (STN), and the striatum. After F2c injection, labeled neurons were observed over a broad territory in the GPe, whereas after F2r injection, labeled neurons tended to be restricted to the rostral and dorsal portions. In the STN, F2c injection resulted in extensive labeling over the nucleus, whereas F2r injection resulted in labeling in the ventral portion only. After both F2r and F2c injections, labeled neurons in the striatum were widely observed in the striatal cell bridge region and neighboring areas, as well as in the ventral striatum. The present results revealed that the origins of multisynaptic projections to F2c and F2r in the BG are segregated in the output stations of the BG, whereas intermingling rather than segregation is evident with respect to their input station., (© 2010 The Authors. European Journal of Neuroscience © 2010 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.)

A previous study identified neuronal activity in area 5 of the monkey posterior parietal cortex that reflects the numerosity of a series of self-performed actions. It is not known, however, whether area 5 is crucially involved in the selection of an action based on numerical information or, instead, merely reflects numerosity-related signals that originate in other brain regions. We transiently and focally inactivated area 5 to test its functional contributions to numerosity-based action selection. Two monkeys were trained to either push or turn a handle in response to a visual trigger signal. The selection of the action was solely based on numerical information from a series of actions performed by the monkey: select A five times, select B five times, and then return to A in a cyclical fashion. When muscimol was applied to a portion of area 5 in which the activity in the numerosity-selective cells was recorded, the error rate in the selection task increased significantly. This transient neural inactivation also caused omission errors that were not observed before the muscimol injection. A control task showed that the errors were not caused by motor deficits or impaired ability to select between two possible actions. Our results indicate that area 5 is crucial for selecting actions on the basis of numerical information about a series of actions performed by the tested individual.

In the caudal part of the dorsal premotor cortex of macaques (area F2), both anatomical and physiological studies have identified two rostrocaudally separate sectors. The rostral sector (F2r) is located medial to the genu of the arcuate sulcus, and the caudal sector (F2c) is located lateral to the superior precentral dimple. Here we examined the sites of origin of projections from the cerebellum to F2r and F2c. We applied retrograde transsynaptic transport of a neurotropic virus, CVS-11 of rabies virus, in macaque monkeys. Three days after rabies injections into F2r or F2c, neuronal labeling was found in the deep cerebellar nuclei mainly of the contralateral hemisphere. After the F2r injection, labeled cells were distributed primarily in the caudoventral portion of the dentate nucleus, whereas cells labeled after the F2c injection were distributed in the rostrodorsal portion of the dentate nucleus, and in the interpositus and fastigial nuclei. Four days after rabies injections, Purkinje cells were densely labeled in the lateral part of the cerebellar cortex. After the F2r injection, Purkinje cell labeling was confined to Crus I and II, whereas the labeling seen after the F2c injection was located broadly from lobules III to VIII, including Crus I and II. These results have revealed that F2c receives inputs from broader areas of the cerebellum than F2r, and that distinct portions of the deep cerebellar nuclei and the cerebellar cortex send major projections to F2r and F2c, suggesting that F2c and F2r may be under specific influences of the cerebellum.

Early studies on cortical motor areas have been centered on their somatotopical organization: a reasonable direction of research from the standpoint of skeletomotor control of limb and body movements. On the primary motor cortex, anatomical and physiological studies revealed aspects of somatotopical organization in progressively finer scales. Earlier studies were directed at elucidating the fine-grain modular organization of the primary motor cortex. Later studies, however, emphasized the diversity of output organization in individual part of the cortex, even at a single-cell level. At present, there is no convincing evidence for the existence of microstructures representing any form of unitary function. As for nonprimary motor areas, the existence of somatotopical organization has been inferred based on anatomical studies and on studies utilizing microstimulation. In the supplementary motor area, the body-part representation is broadly organized rostrocaudally in the order of face, forelimb and hindlimb areas, although with an extensive overlap of each area. In contrast, somatotopy is not apparent in the presupplemenetary motor area; effector-independent control of motor behavior seems to be dominant in this area. In the premotor cortex, motor acts involving the hindlimb appears to be much less represented than actions involving hand-arm and face. Overall, in considering the workings of nonprimary areas, aspects of motor behavior involving sensorial guidance, action-selection, or visuomotor association appear to be of primary importance rather than the determination of body parts to be used.

Previous reports have indicated that the premotor cortex (PM) uses visual information for either direct guidance of limb movements or indirect specification of action targets at a conceptual level. We explored how visual inputs signaling these two different categories of information are processed by PM neurons. Monkeys performed a delayed reaching task after receiving two different sets of visual instructions, one directly specifying the spatial location of a motor target (a direct spatial-target cue) and the other providing abstract information about the spatial location of a motor target by indicating whether to select the right or left target at a conceptual level (a symbolic action-selection cue). By comparing visual responses of PM neurons to the two sets of visual cues, we found that the conceptual action plan indicated by the symbolic action-selection cue was represented predominantly in dorsal PM (PMd) neurons with a longer latency (150 ms), whereas both PMd and ventral PM (PMv) neurons responded with a shorter latency (90 ms) when the motor target was directly specified with the direct spatial-target cue. We also found that excited, but not inhibited, responses of PM neurons to the direct spatial-target cue were biased toward contralateral preference. In contrast, responses to the symbolic action-selection cue were either excited or inhibited without laterality preference. Taken together, these results suggest that the PM constitutes a pair of distinct circuits for visually guided motor act; one circuit, linked more strongly with PMd, carries information for retrieving action instruction associated with a symbolic cue, and the other circuit, linked with PMd and PMv, carries information for directly specifying a visuospatial position of a reach target.

To select an appropriate action, we conform to a behavioral rule determined uniquely in each behavioral context. If the rule is not predetermined and must be discovered, we often test hypotheses concerning rules by applying one candidate rule after another. The neural mechanisms underlying such rule identification are still unknown. To explore which brain areas are involved in the process of logical rule identification and to determine whether such areas differ from those taking part in implementing the rule to find a suitable action, we measured brain activation using functional magnetic resonance imaging while subjects performed a rule-identification task. The subjects were required to select a red or blue square on a screen based on either a "sequence rule" or a "probability rule." Positive or negative feedback to the subject's choice led the subject to identify the correct rule. We found that the posterior medial frontal cortex (pMFC), caudate nucleus, fusiform gyrus, and middle temporal cortex exhibited significant activation during the period when subjects underwent the hypothesis testing. Among these brain areas, the pMFC and caudate nucleus were also activated in response to the critical feedback signals selectively during the trials when the subjects identified a rule. Furthermore, we found a significant enhancement in effective connectivity between the active regions in the pMFC and caudate regions.

In this issue of Neuron, Genovesio et al. report that neurons in the frontal cortex encode the relative duration of appearance of two sensory signals, together with the features of each signal. Such representations could provide a neural basis for episodic memory.

It has been empirically established that the cerebral cortical areas defined by Brodmann one hundred years ago solely on the basis of cellular organization are closely correlated to their function, such as sensation, association, and motion. Cytoarchitectonically distinct cortical areas have different densities and types of neurons. Thus, signaling patterns may also vary among cytoarchitectonically unique cortical areas. To examine how neuronal signaling patterns are related to innate cortical functions, we detected intrinsic features of cortical firing by devising a metric that efficiently isolates non-Poisson irregular characteristics, independent of spike rate fluctuations that are caused extrinsically by ever-changing behavioral conditions. Using the new metric, we analyzed spike trains from over 1,000 neurons in 15 cortical areas sampled by eight independent neurophysiological laboratories. Analysis of firing-pattern dissimilarities across cortical areas revealed a gradient of firing regularity that corresponded closely to the functional category of the cortical area; neuronal spiking patterns are regular in motor areas, random in the visual areas, and bursty in the prefrontal area. Thus, signaling patterns may play an important role in function-specific cerebral cortical computation.

Interval timing is an essential guiding force of behavior. Previous reports have implicated the prefrontal and parietal cortex as being involved in time perception and in temporal decision making. We found that neurons in the medial motor areas, in particular the presupplementary motor area, participate in interval timing in the range of seconds. Monkeys were trained to perform an interval-generation task that required them to determine waiting periods of three different durations. Neuronal activity contributed to the process of retrieving time instructions from visual cues, signaled the initiation of action in a time-selective manner, and developed activity to represent the passage of time. These results specify how medial motor areas take part in initiating actions on the basis of self-generated time estimates.

We attempted to analyze the nature of premovement activity of neurons in medial motor areas [supplementary motor area (SMA) and pre-SMA] from a perspective of coding multiple movements. Monkeys were trained to perform a series of two movements with an intervening delay: supination or pronation with either forearm. Movements were initially instructed with visual signals but had to be remembered thereafter. Although a well-known type of premovement activity representing the forthcoming movements was found in the two areas, we found an unexpected type of activity that represented a second-next movement before initiating the first of the two movements. Typically in the pre-SMA, such activity selective for the second-next movement peaked before the initiation of the first movement, decayed thereafter, and remained low in magnitude while initiating the second movement. This type of activity may tentatively hold information for the second movement while initiating the first. That information may be fed into another group of neurons that themselves build a preparatory activity required to plan the second movements. Alternatively, the activity could serve as a signal to inhibit a premature exertion of the motor command for the second movement.

To achieve a behavioral goal in a complex environment, such as problem-solving situations, we must plan multiple steps of action. On planning a series of actions, we anticipate future events that will occur as a result of each action, and mentally organize the temporal sequence of events. To investigate the involvement of the lateral prefrontal cortex (PFC) in such multistep planning, we examined neuronal activity in the PFC while monkeys performed a maze path-finding task. In this task, we set monkeys the job of capturing a goal in the maze by moving a cursor on the screen. Cursor movement was linked to movements of each wrist. To dissociate the outcomes of the intended action from the motor commands, we trained the monkeys to use three different hand-cursor assignments. We found that monkeys were able to perform this task in a flexible manner. This report first introduces a problem-solving framework for studying the function of the PFC, from the view point of cognitive science. Then, this chapter will cover the neuronal representation of a series of actions, goal subgoal transformation, and synchrony of PFC neurons. We reported PFC neurons reflected final goals and immediate goals during the preparatory period. We also found some PFC neurons reflected each of all forthcoming steps of actions during the preparatory period and increased their activity step by step during the execution period. Recently, we found that the transient increase in synchronous activity of PFC neurons was involved in goal subgoal transformations. Our data suggest that the PFC is involved primarily in the dynamic representation of multiple future events that occur as a consequence of behavioral actions in problem-solving situations.

To investigate the temporal relationship between synchrony in the discharge of neuron pairs and modulation of the discharge rate, we recorded the neuronal activity of the lateral prefrontal cortex of monkeys performing a behavioral task that required them to plan an immediate goal of action to attain a final goal. Information about the final goal was retrieved via visual instruction signals, whereas information about the immediate goal was generated internally. The synchrony of neuron pair discharges was analyzed separately from changes in the firing rate of individual neurons during a preparatory period. We focused on neuron pairs that exhibited a representation of the final goal followed by a representation of the immediate goal at a later stage. We found that changes in synchrony and discharge rates appeared to be complementary at different phases of the behavioral task. Synchrony was maximized during a specific phase in the preparatory period corresponding to a transitional stage when the neuronal activity representing the final goal was replaced with that representing the immediate goal. We hypothesize that the transient increase in discharge synchrony is an indication of a process that facilitates dynamic changes in the prefrontal neural circuits in order to undergo profound state changes.

The lateral prefrontal cortex is critically involved in broad aspects of executive behavioral control. Early studies emphasized its role in the short-term retention of information retrieved from cortical association areas and in the inhibition of prepotent responses. Recent studies of subhuman primates and humans have revealed the role of this area in more general aspects of behavioral planning. Novel findings of neuronal activity have specified how neurons in this area take part in selective attention for action and in selecting an intended action. Furthermore, the involvement of the lateral prefrontal cortex in the implementation of behavioral rules and in setting multiple behavioral goals has been discovered. Recent studies have begun to reveal neuronal mechanisms for strategic behavioral planning and for the development of knowledge that enables the planning of macrostructures of event-action sequences at the conceptual level.

Many lines of evidence implicate the lateral prefrontal cortex (LPFC) in the executive control of behavior. In early studies, neuronal activity in this area was thought to retain information about forthcoming movements for a short period until they were executed. However, later studies have stressed its role in the cognitive aspects of behavioral planning, such as behavioral significance, behavioral rules and behavioral goals. The consequence of the intended action (i.e. a change in the state of the target object), rather than the intended movement, is primarily represented in the LPFC during planning. Recent studies show that the LPFC is involved in more abstract aspects of conceptual processes, such as in representing categories of multiple actions at the stage of behavioral planning.

The dorsal and ventral premotor areas, together with the primary motor cortex, are believed to have major roles in preparing and executing limb movements. Recent studies have expanded our knowledge of the dorsal and ventral premotor areas, which occupy the lateral part of area 6 in the frontal cortex. It is becoming clear that these two premotor areas, through involvement in distinct cortical networks, take part in unique aspects of motor planning and decision making. New lines of evidence also implicate the lateral premotor areas in planning motor behavior and selecting actions.

Although it has long been thought that the prefrontal cortex of primates is involved in the integrative regulation of behaviours, the neural architecture underlying specific aspects of cognitive behavioural planning has yet to be clarified. If subjects are required to remember a large number of complex motor sequences and plan to execute each of them individually, categorization of the sequences according to the specific temporal structure inherent in each subset of sequences serves to facilitate higher-order planning based on memory. Here we show, using these requirements, that cells in the lateral prefrontal cortex selectively exhibit activity for a specific category of behavioural sequences, and that categories of behaviours, embodied by different types of movement sequences, are represented in prefrontal cells during the process of planning. This cellular activity implies the generation of neural representations capable of storing structured event complexes at an abstract level, exemplifying the development of macro-structured action knowledge in the lateral prefrontal cortex.

To investigate the involvement of primate non-primary motor cortices in bimanual sequential movements, we recorded neuronal activity in the supplementary motor area (SMA) and presupplementary motor area (pre-SMA) while an animal was performing bimanual motor tasks that required two sequential arm movements consisting of either pronation or supination of the right or left arms with delay periods. We also recorded electromyograms (EMGs) from the arm while the animal performed the bimanual task to compare muscle and neuronal activity. This paper focuses on the neuronal activity before the onset of sequential movements. We found that the prime-mover forelimb muscles were selectively active when an impending arm movement involved recorded muscles, but was not dependent on whether the arm movements were bimanual or unimanual. In contrast, we found that neurons in the non-primary motor cortices showed different activity depending on whether the forthcoming sequential arm movements were unimanual or bimanual. Our results suggest that neuronal activity in the SMA and pre-SMA reflects higher-order information about arm use before motor execution. By extracting this type of information, we can use it to control prosthetic arms in a more intelligent manner through a brain-machine interface.

We examined neuronal activity in the lateral prefrontal cortex of monkeys performing a path-planning task in a maze that required the planning of actions in multiple steps. The animals received an instruction that prompted them to prepare to move a cursor in the maze stepwise from a starting position to a goal position by operating manipulanda with either arm. During a delay period in which the animal prepared to start the first of three cursor movements to approach the pre-instructed goal, we identified two types of neuronal activity: the first type reflected the position within the maze to which the animal intended to move the cursor as an initial step (an immediate goal) and the second type reflected the position within the maze that was to be captured as a final goal. Neither type reflected motor responses. We propose that these two types of neuronal activity are neuronal correlates that represent immediate and ultimate behavioral goals. This finding implicates the prefrontal cortex in governing goal-oriented sequential behavior rather than sensorimotor transformation.

The ventral premotor cortex (PMv) has been implicated in the visual guidance of movement. To examine whether neuronal activity in the PMv is involved in controlling the direction of motion of a visual image of the hand or the actual movement of the hand, we trained a monkey to capture a target that was presented on a video display using the same side of its hand as was displayed on the video display. We found that PMv neurons predominantly exhibited premovement activity that reflected the image motion to be controlled, rather than the physical motion of the hand. We also found that the activity of half of such direction-selective PMv neurons depended on which side (left versus right) of the video image of the hand was used to capture the target. Furthermore, this selectivity for a portion of the hand was not affected by changing the starting position of the hand movement. These findings suggest that PMv neurons play a crucial role in determining which part of the body moves in which direction, at least under conditions in which a visual image of a limb is used to guide limb movements.

The premotor cortex (PM) in the bilateral lateral hemisphere of nonhuman primates and the human has been implicated in the sensorial guidance of movements. This is in contrast to more medial motor areas that are involved more in the temporal structuring of movements based on memorized information. The PM is further subdivided into dorsal (PMd) and ventral (PMv) parts. In this chapter, we describe our attempts to find differences in the use of these two areas in a nonhuman primate for programming future motor actions based on visual signals. We show that neurons in the PMv are involved primarily in receiving visuospatial signals and in specifying the spatial location of the target to be reached. In contrast, neurons in the PMd are involved more in integrating information about which arm to use and the target to be reached. Thus, PMd neurons are more implicated than those of the PMv in the preparation for a future motor action.

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

The cingulate motor areas, located in the banks of the cingulate sulcus, constitute a portion of the cingulate cortex of primates. We here present experimental evidence showing that the rostral cingulate motor area (CMAr), but not the caudal one (CMAc) is crucial for the selection of future movements based on reward information. After muscimol injection into the CMAr, monkeys were impaired in selecting movements appropriately on the basis of the amount of reward obtained by performing correct movements. Furthermore, four types of cells in the CMAr were found to reflect a process intervening between detection of reward alteration and selection of a future movement. Each type of cell seems to be involved in responding to the quality of the reward, and to relay that information to change planned movements, and prepare a new movement.