Monkey Prefrontal Single-Unit Activity Reflecting Category-Based Logical Thinking Process and Its Neural Network Model.

Category-based thinking is a fundamental form of logical thinking. Here, we aimed to investigate its neural process at the local circuit level in the prefrontal cortex (PFC). We recorded single-unit PFC activity while male monkeys (Macaca fuscata) performed a task in which the category and rule were prerequisites of logical thinking and the outcome contingency was its consequence. Different groups of neurons coded a single type of information discretely or multiple types in a transitional form. Results of time-by-time analysis of neuronal activity suggest an information flow from category-coding and rule-coding neurons to transitional intermediate neurons, and then to contingency-coding neurons. Category-coding, rule-coding, and contingency-coding neurons showed stable coding of information, whereas intermediate neurons showed dynamic coding, as if it integrated category and rule to derive contingency. A similar process was confirmed by using a spiking neural network model that consisted of subnetworks coding category and rule on the input layer and those coding contingency on the output layer, with a subnetwork for integration in the intermediate layer. These results suggest that category-based logical thinking is realized in the PFC by separated neural populations organized for working in a feedforward manner.SIGNIFICANCE STATEMENT To elucidate the neural process for logical thinking, we combined an in-depth analysis of single-unit activity data with a biologically plausible computational model. Results of time-by-time analysis of prefrontal neuronal activity suggest an information flow from category-coding and rule-coding neurons to transitional intermediate neurons, and then to contingency-coding neurons. Category-coding, rule-coding, and contingency-coding neurons showed stable coding, whereas intermediate neurons showed dynamic coding, as if they integrated category and rule to derive contingency. A spiking neural network model reproduced similar temporal changes of information as the recorded neuronal data. Our results suggest that the prefrontal cortex (PFC) is critically involved in category-based thought process, and this process may be produced by separated neural populations organized for working in a feedforward manner.

Mechanisms of adjustments to different types of uncertainty in the reward environment across mice and monkeys.

Despite being unpredictable and uncertain, reward environments often exhibit certain regularities, and animals navigating these environments try to detect and utilize such regularities to adapt their behavior. However, successful learning requires that animals also adjust to uncertainty associated with those regularities. Here, we analyzed choice data from two comparable dynamic foraging tasks in mice and monkeys to investigate mechanisms underlying adjustments to different types of uncertainty. In these tasks, animals selected between two choice options that delivered reward probabilistically, while baseline reward probabilities changed after a variable number (block) of trials without any cues to the animals. To measure adjustments in behavior, we applied multiple metrics based on information theory that quantify consistency in behavior, and fit choice data using reinforcement learning models. We found that in both species, learning and choice were affected by uncertainty about reward outcomes (in terms of determining the better option) and by expectation about when the environment may change. However, these effects were mediated through different mechanisms. First, more uncertainty about the better option resulted in slower learning and forgetting in mice, whereas it had no significant effect in monkeys. Second, expectation of block switches accompanied slower learning, faster forgetting, and increased stochasticity in choice in mice, whereas it only reduced learning rates in monkeys. Overall, while demonstrating the usefulness of metrics based on information theory in examining adaptive behavior, our study provides evidence for multiple types of adjustments in learning and choice behavior according to uncertainty in the reward environment.

Oral Administration of Methylphenidate (Ritalin) Affects Dopamine Release Differentially Between the Prefrontal Cortex and Striatum: A Microdialysis Study in the Monkey.

Methylphenidate (MPH; trade name Ritalin) is a widely used drug for the treatment of attention deficit hyperactivity disorder (ADHD) and is often used as a cognitive enhancer. Because MPH increases dopamine (DA) release by blocking the DA transporter in the human striatum, MPH is supposed to work on attention and cognition through a DA increase in the striatum. However, ADHD patients show impaired prefrontal cortex (PFC) function and MPH administration is associated with increased neural activity in the PFC. Although MPH is indicated to increase DA release in the rat PFC, there has been no study to examine MPH-induced DA changes in the human PFC because of technical difficulties associated with the low level of PFC DA receptors. Using the microdialysis technique, we examined the effects of oral administration of MPH on DA release in both the PFC and striatum in the monkey. We also tested the effect of MPH on cognitive task performance. As in human studies, in the striatum, both high and low doses of MPH induced consistent increases in DA release ∼30 min after their administrations. In the PFC, a consistent increase in DA release was observed 1 h after a high dose, but not low doses, of MPH. Low doses of MPH improved cognitive task performance, but a high dose of MPH made the monkey drowsy. Therefore, low-dose MPH-induced cognitive enhancement is supported by striatum DA increase.SIGNIFICANCE STATEMENT Methylphenidate (MPH) is a widely used drug for the treatment of attention deficit hyperactivity disorder and is often used as a cognitive enhancer. Although human positron emission tomography studies suggest that MPH works on attention and cognition through dopamine (DA) changes in the striatum, there has been no study to examine MPH-induced DA changes in the human prefrontal cortex (PFC). Using the microdialysis technique in monkeys, we found, for the first time, that low doses of MPH consistently increased DA release in the striatum but did not in the PFC. Cognitive enhancement effects of low doses of MPH are supposed to be supported by the striatum DA increase.

Ventrolateral Prefrontal Cortex Updates Chosen Value According to Choice Set Size.

Having chosen an item typically increases the subjective value of the chosen item, and people generally enjoy making choices from larger choice sets. However, having too many items to choose from can reduce the value of chosen items-for example, because of conflict or choice difficulty. In this study, we investigated the effects of choice set size on behavioral and neural value updating (revaluation) of the chosen item. In the scanner, participants selected items from choice sets of various sizes (one, two, four, or eight items). After they chose an item, participants rerated the chosen item, and we quantified revaluation by taking the difference of postchoice minus prechoice ratings. Revaluation of chosen items increased up to choice sets of four alternatives but then decreased again for items chosen from choice sets of eight alternatives, revealing both a linear and a quadratic effect of choice set size. At the time of postchoice rating, activation of the ventrolateral pFC (VLPFC) reflected the influence of choice set size on parametric revaluation, without significant relation to either prechoice or postchoice ratings tested separately. Additional analyses revealed relations of choice set size to anterior cingulate and insula activity during actual choice and increased coupling of both regions to revaluation-related VLPFC during postchoice rating. These data suggest that the VLPFC plays a central role in a network that relates choice set size to updating the value of chosen items and integrates choice overload with value-enhancing effects of larger choice sets.

Representation of Functional Category in the Monkey Prefrontal Cortex and Its Rule-Dependent Use for Behavioral Selection.

Humans, monkeys, and other animals are considered to have the cognitive ability to use functional categories--that is, stimulus groups based on functional equivalence independent of physical properties. To investigate the underlying neural mechanisms of the use of functional categories, we recorded single-unit activity in the prefrontal cortex of monkeys performing a behavioral task in which the rule-dependent usage of functional category was needed to select an appropriate response. We found a neural correlate of functional categories on the single-neuron level and found that category information is coded independently of other task-relevant information such as rule and contingency information. Analysis of the time course of the information activation suggested that contingency information used for action selection is derived by integrating incoming category information with rule information maintained throughout a session. Such neural computation can be considered as the neural background of flexible behavioral control based on category and rule.

Similarity in Neuronal Firing Regimes across Mammalian Species.

UNLABELLED: The architectonic subdivisions of the brain are believed to be functional modules, each processing parts of global functions. Previously, we showed that neurons in different regions operate in different firing regimes in monkeys. It is possible that firing regimes reflect differences in underlying information processing, and consequently the firing regimes in homologous regions across animal species might be similar. We analyzed neuronal spike trains recorded from behaving mice, rats, cats, and monkeys. The firing regularity differed systematically, with differences across regions in one species being greater than the differences in similar areas across species. Neuronal firing was consistently most regular in motor areas, nearly random in visual and prefrontal/medial prefrontal cortical areas, and bursting in the hippocampus in all animals examined. This suggests that firing regularity (or irregularity) plays a key role in neural computation in each functional subdivision, depending on the types of information being carried. SIGNIFICANCE STATEMENT: By analyzing neuronal spike trains recorded from mice, rats, cats, and monkeys, we found that different brain regions have intrinsically different firing regimes that are more similar in homologous areas across species than across areas in one species. Because different regions in the brain are specialized for different functions, the present finding suggests that the different activity regimes of neurons are important for supporting different functions, so that appropriate neuronal codes can be used for different modalities.

Discrete coding of stimulus value, reward expectation, and reward prediction error in the dorsal striatum.

To investigate how the striatum integrates sensory information with reward information for behavioral guidance, we recorded single-unit activity in the dorsal striatum of head-fixed rats participating in a probabilistic Pavlovian conditioning task with auditory conditioned stimuli (CSs) in which reward probability was fixed for each CS but parametrically varied across CSs. We found that the activity of many neurons was linearly correlated with the reward probability indicated by the CSs. The recorded neurons could be classified according to their firing patterns into functional subtypes coding reward probability in different forms such as stimulus value, reward expectation, and reward prediction error. These results suggest that several functional subgroups of dorsal striatal neurons represent different kinds of information formed through extensive prior exposure to CS-reward contingencies.

Inactivating anterior insular cortex reduces risk taking.

We often have to make risky decisions between alternatives with outcomes that can be better or worse than the outcomes of safer alternatives. Although previous studies have implicated various brain regions in risky decision making, it remains unknown which regions are crucial for balancing whether to take a risk or play it safe. Here, we focused on the anterior insular cortex (AIC), the causal involvement of which in risky decision making is still unclear, although human imaging studies have reported AIC activation in various gambling tasks. We investigated the effects of temporarily inactivating the AIC on rats' risk preference in two types of gambling tasks, one in which risk arose in reward amount and one in which it arose in reward delay. As a control within the same subjects, we inactivated the adjacent orbitofrontal cortex (OFC), which is well known to affect risk preference. In both gambling tasks, AIC inactivation decreased risk preference whereas OFC inactivation increased it. In risk-free control situations, AIC and OFC inactivations did not affect decision making. These results suggest that the AIC is causally involved in risky decision making and promotes risk taking. The AIC and OFC may be crucial for the opposing motives of whether to take a risk or avoid it.

Value of freedom to choose encoded by the human brain.

Humans and animals value the opportunity to choose by preferring alternatives that offer more rather than fewer choices. This preference for choice may arise not only from an increased probability of obtaining preferred outcomes but also from the freedom it provides. We used human neuroimaging to investigate the neural basis of the preference for choice as well as for the items that could be chosen. In each trial, participants chose between two options, a monetary amount option and a "choice option." The latter consisted of a number that corresponded to the number of everyday items participants would subsequently be able to choose from. We found that the opportunity to choose from a larger number of items was equivalent to greater amounts of money, indicating that participants valued having more choice; moreover, participants varied in the degree to which they valued having the opportunity to choose, with some valuing it more than the increased probability of obtaining preferred items. Neural activations in the mid striatum increased with the value of the opportunity to choose. The same region also coded the value of the items. Conversely, activation in the dorsolateral striatum was not related to the value of the items but was elevated when participants were offered more choices, particularly in those participants who overvalued the opportunity to choose. These data suggest a functional dissociation of value representations within the striatum, with general representations in mid striatum and specific representations of the value of freedom provided by the opportunity to choose in dorsolateral striatum.

Hippocampal-medial entorhinal circuit is differently organized along the dorsoventral axis in rodents.

The general understanding of hippocampal circuits is that the hippocampus and the entorhinal cortex (EC) are topographically connected through parallel identical circuits along the dorsoventral axis. Our anterograde tracing and in vitro electrophysiology data, however, show a markedly different dorsoventral organization of the hippocampal projection to the medial EC (MEC). While dorsal hippocampal projections are confined to the dorsal MEC, ventral hippocampal projections innervate both dorsal and ventral MEC. Further, whereas the dorsal hippocampus preferentially targets layer Vb (LVb) neurons, the ventral hippocampus mainly targets cells in layer Va (LVa). This connectivity scheme differs from hippocampal projections to the lateral EC, which are topographically organized along the dorsoventral axis. As LVa neurons project to telencephalic structures, our findings indicate that the ventral hippocampus regulates LVa-mediated entorhinal-neocortical output from both dorsal and ventral MEC. Overall, the marked dorsoventral differences in hippocampal-entorhinal connectivity impose important constraints on signal flow in hippocampal-neocortical circuits.

Rat hippocampal CA1 region represents learning-related action and reward events with shorter latency than the lateral entorhinal cortex.

The hippocampus and entorhinal cortex are deeply involved in learning and memory. However, little is known how ongoing events are processed in the hippocampal-entorhinal circuit. By recording from head-fixed rats during action-reward learning, here we show that the action and reward events are represented differently in the hippocampal CA1 region and lateral entorhinal cortex (LEC). Although diverse task-related activities developed after learning in both CA1 and LEC, phasic activities related to action and reward events differed in the timing of behavioral event representation. CA1 represented action and reward events almost instantaneously, whereas the superficial and deep layers of the LEC showed a delayed representation of the same events. Interestingly, we also found that ramping activity towards spontaneous action was correlated with waiting time in both regions and exceeded that in the motor cortex. Such functional activities observed in the entorhinal-hippocampal circuits may play a crucial role for animals in utilizing ongoing information to dynamically optimize their behaviors.

Depression induced by low-frequency repetitive transcranial magnetic stimulation to ventral medial frontal cortex in monkeys.

The medial frontal cortex (MFC), especially its ventral part, has long been of great interest with respect to the pathology of mood disorders. A number of human brain imaging studies have demonstrated the abnormalities of this brain region in patients with mood disorders, however, whether it is critically and causally involved in the pathogenesis of such disorders remains to be fully elucidated. In this study, we examined how the suppression of neural activity in the ventral region of the MFC (vMFC) affects the behavioral and physiological states of monkeys by using repetitive transcranial magnetic stimulation (rTMS). By using low-frequency rTMS (LF-rTMS) as an inhibitory intervention, we found that LF-rTMS targeting the vMFC temporarily induced a depression-like state in monkeys, which was characterized by a reduced movement activity level, impaired sociability, and decreased motivation level, as well as increased plasma cortisol level. On the other hand, no such significant changes in behavioral and physiological states were observed when targeting the other MFC regions, dorsal or posterior. We further found that the administration of an antidepressant agent, ketamine, ameliorated the abnormal behavioral and physiological states induced by the LF-rTMS intervention. These findings causally indicate the involvement of the vMFC in the regulation of mood and the validity of the LF-rTMS-induced dysfunction of the vMFC as a nonhuman primate model of depression.

Reward prediction error coding in dorsal striatal neurons.

In the current theory of learning, the reward prediction error (RPE), the difference between expected and received reward, is thought to be a key factor in reward-based learning, working as a teaching signal. The activity of dopamine neurons is known to code RPE, and the release of dopamine is known to modify the strength of synaptic connectivity in the target neurons. A fundamental interest in current neuroscience concerns the origin of RPE signals in the brain. Here, we show that a group of rat striatal neurons show a clear parametric RPE coding similar to that of dopamine neurons when tested under probabilistic pavlovian conditioning. Together with the fact that striatum and dopamine neurons have strong direct and indirect fiber connections, the result suggests that the striatum plays an important role in coding RPE signal by cooperating with dopamine neurons.

Changes in beta and high-gamma power in resting-state electrocorticogram induced by repetitive transcranial magnetic stimulation of primary motor cortex in unanesthetized macaque monkeys.

Repetitive transcranial magnetic stimulation (rTMS) is now widely used as a means of neuromodulation, but the details of the mechanisms by which rTMS works remain unclarified. As a step forward to unveiling the neural phenomena occurring underneath the TMS coil, we conducted an electrophysiological study using awake and unanesthetized monkeys with subdural electrocorticogram (ECoG) electrodes implanted over the primary motor cortex (MI). We evaluated the effects of low-frequency (1 Hz) and high-frequency (10 Hz) rTMS on the resting-state ECoG signals in the stimulated MI, as well as the motor evoked potentials (MEPs) in the contralateral hand. Following the 1-Hz rTMS application, the ECoG beta band power and the MEP amplitude were significantly decreased. Following the 10-Hz rTMS application, the ECoG high-gamma power and the MEP amplitude significantly increased. Given that beta and high-gamma activities in the ECoG reflect the synchronous firing and the firing frequency of cell assemblies, respectively, in local neural circuits, these results suggest that low-frequency rTMS inhibits neural activity by desynchronizing the firing activity of local circuits, whereas high-frequency rTMS facilitates neural activity by increasing the firing rate of cell assemblies in the local circuits.

Laminar Organization of the Entorhinal Cortex in Macaque Monkeys Based on Cell-Type-Specific Markers and Connectivity.

The entorhinal cortex (EC) is a major gateway between the hippocampus and telencephalic structures, and plays a critical role in memory and navigation. Through the use of various molecular markers and genetic tools, neuron types constituting EC are well studied in rodents, and their layer-dependent distributions, connections, and functions have also been characterized. In primates, however, such cell-type-specific understandings are lagging. To bridge the gap between rodents and primates, here we provide the first cell-type-based global map of EC in macaque monkeys. The laminar organization of the monkey EC was systematically examined and compared with that of the rodent EC by using immunohistochemistry for molecular markers which have been well characterized in the rodent EC: reelin, calbindin, and Purkinje cell protein 4 (PCP4). We further employed retrograde neuron labeling from the nucleus accumbens and amygdala to identify the EC output layer. This cell-type-based approach enabled us to apply the latest laminar definition of rodent EC to monkeys. Based on the similarity of the laminar organization, the monkey EC can be divided into two subdivisions: rostral and caudal EC. These subdivisions likely correspond to the lateral and medial EC in rodents, respectively. In addition, we found an overall absence of a clear laminar arrangement of layer V neurons in the rostral EC, unlike rodents. The cell-type-based architectural map provided in this study will accelerate the application of genetic tools in monkeys for better understanding of the role of EC in memory and navigation.

Default mode of brain activity demonstrated by positron emission tomography imaging in awake monkeys: higher rest-related than working memory-related activity in medial cortical areas.

Human neuroimaging studies have demonstrated the presence of a "default system" in the brain, which shows a "default mode of brain activity," i.e., greater activity during the resting state than during an attention-demanding cognitive task. The default system mainly involves the medial prefrontal and medial parietal areas, including the anterior and posterior cingulate cortex. It has been proposed that this default activity is concerned with internal thought processes. Recently, it has been indicated that chimpanzees show high metabolic levels in these medial brain areas during rest. Correlated low-frequency spontaneous activity as measured by functional magnetic resonance imaging was observed between the medial parietal and medial prefrontal areas in the anesthetized monkey. However, there have been few attempts to demonstrate a default system that shows task-induced deactivation in nonhuman primates. We conducted a positron emission tomography study with [(15)O]H(2)O to demonstrate a default mode of brain activity in the awake monkey sitting on a primate chair. Macaque monkeys showed higher level of regional blood flow in these medial brain areas as well as lateral and orbital prefrontal areas during rest compared with that under a working memory task, suggesting the existence of internal thought processes in the monkey. However, during rest in the monkey, the highest level of blood flow relative to that in other brain regions was observed not in the default system but in the dorsal striatum, suggesting that regions with the highest cerebral blood flow during rest may differ depending on the resting condition and/or species.

Relating neuronal firing patterns to functional differentiation of cerebral cortex.

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.

A parametric relief signal in human ventrolateral prefrontal cortex.

People experience relief whenever outcomes are better than they would have been, had an alternative course of action been chosen. Here we investigated the neuronal basis of relief with functional resonance imaging in a choice task in which the outcome of the chosen option and that of the unchosen option were revealed sequentially. We found parametric activation increases in anterior ventrolateral prefrontal cortex with increasing relief (chosen outcomes better than unchosen outcomes). Conversely, anterior ventrolateral prefrontal activation was unrelated to the opposite of relief, increasing regret (chosen outcomes worse than unchosen outcomes). Furthermore, the anterior ventrolateral prefrontal activation was unrelated to primary gains and increased with relief irrespective of whether the chosen outcome was a loss or a gain. These results suggest that the anterior ventrolateral prefrontal cortex encodes a higher-order reward signal that lies at the core of current theories of emotion.

Primate prefrontal neurons signal economic risk derived from the statistics of recent reward experience.

Risk derives from the variation of rewards and governs economic decisions, yet how the brain calculates risk from the frequency of experienced events, rather than from explicit risk-descriptive cues, remains unclear. Here, we investigated whether neurons in dorsolateral prefrontal cortex process risk derived from reward experience. Monkeys performed in a probabilistic choice task in which the statistical variance of experienced rewards evolved continually. During these choices, prefrontal neurons signaled the reward-variance associated with specific objects ('object risk') or actions ('action risk'). Crucially, risk was not derived from explicit, risk-descriptive cues but calculated internally from the variance of recently experienced rewards. Support-vector-machine decoding demonstrated accurate neuronal risk discrimination. Within trials, neuronal signals transitioned from experienced reward to risk (risk updating) and from risk to upcoming choice (choice computation). Thus, prefrontal neurons encode the statistical variance of recently experienced rewards, complying with formal decision variables of object risk and action risk.