Comparison of learning-related neuronal activity in the dorsal premotor cortex and striatum

Meta-learning of human motor adaptation via the dorsal premotor cortex

Meta-learning enables us to learn how to learn the same or similar tasks more efficiently. Decision-making literature theorizes that a prefrontal network, including the orbitofrontal and anterior cingulate cortices, underlies meta-learning of decision making by reinforcement learning. Recently, computationally similar meta-learning has been theorized and empirically demonstrated in motor adaptation. However, it remains unclear whether meta-learning of motor adaptation also relies on a prefrontal network. Considering hierarchical information flow from the prefrontal to motor cortices, this study explores whether meta-learning is processed in the dorsolateral prefrontal cortex (DLPFC) or in the dorsal premotor cortex (PMd), which is situated upstream of the primary motor cortex, but downstream of the DLPFC. Transcranial magnetic stimulation (TMS) was delivered to either PMd or DLPFC during a motor meta-learning task, in which human participants were trained to regulate the rate and retention of motor adaptation to maximize rewards. While motor adaptation itself was intact, TMS to PMd, but not DLPFC, attenuated meta-learning, impairing the ability to regulate motor adaptation to maximize rewards. Further analyses revealed that TMS to PMd attenuated meta-learning of memory retention. These results suggest that meta-learning of motor adaptation relies more on the premotor area than on a prefrontal network. Thus, while PMd is traditionally viewed as crucial for planning motor actions, this study suggests that PMd is also crucial for meta-learning of motor adaptation, processing goal-directed planning of how long motor memory should be retained to fit the long-term goal of motor adaptation.

Dynamics of directional motor tuning in the primate premotor and primary motor cortices during sensorimotor learning

Sensorimotor learning requires reorganization of neuronal activity in the premotor cortex (PM) and primary motor cortex (M1). To reveal PM- and M1-specific reorganization in a primate, we conducted calcium imaging in common marmosets while they learned a two-target reaching (pull/push) task after mastering a one-target reaching (pull) task. Throughout learning of the two-target reaching task, the dorsorostral PM (PMdr) showed peak activity earlier than the dorsocaudal PM (PMdc) and M1. During learning, the reaction time in pull trials increased and correlated strongly with the peak timing of PMdr activity. PMdr showed decreasing representation of newly introduced (push) movement, whereas PMdc and M1 maintained high representation of pull and push movements. Many task-related neurons in PMdc and M1 exhibited a strong preference to either movement direction. PMdc neurons dynamically switched their preferred direction depending on their performance in push trials in the early learning stage, whereas M1 neurons stably retained their preferred direction and high similarity of preferred direction between neighbors. These results suggest that in primate sensorimotor learning, dynamic directional motor tuning in PMdc converts the sensorimotor association formed in PMdr to the stable and specific motor representation of M1.

Decreasing mutant ATXN1 nuclear localization improves a spectrum of SCA1-like phenotypes and brain region transcriptomic profiles

Spinocerebellar ataxia type 1 (SCA1) is a dominant trinucleotide repeat neurodegenerative disease characterized by motor dysfunction, cognitive impairment, and premature death. Degeneration of cerebellar Purkinje cells is a frequent and prominent pathological feature of SCA1. We previously showed that transport of ATXN1 to Purkinje cell nuclei is required for pathology, where mutant ATXN1 alters transcription. To examine the role of ATXN1 nuclear localization broadly in SCA1-like disease pathogenesis, CRISPR-Cas9 was used to develop a mouse with an amino acid alteration (K772T) in the nuclear localization sequence of the expanded ATXN1 protein. Characterization of these mice indicates that proper nuclear localization of mutant ATXN1 contributes to many disease-like phenotypes including motor dysfunction, cognitive deficits, and premature lethality. RNA sequencing analysis of genes with expression corrected to WT levels in Atxn1175QK772T/2Q mice indicates that transcriptomic aspects of SCA1 pathogenesis differ between the cerebellum, brainstem, cerebral cortex, hippocampus, and striatum.

Instruction-based learning: A review

Humans are able to learn to implement novel rules from instructions rapidly, which is termed "instruction-based learning" (IBL). This remarkable ability is very important in our daily life in both learning individually or working as a team, and almost every psychology experiment starts with instructing participants. Many recent progresses have been made in IBL research both psychologically and neuroscientifically. In this review, we discuss the role of language in IBL, the importance of the first trial performance in IBL, why IBL should be considered as a goal-directed behavior, intelligence and IBL, cognitive flexibility and IBL, how behaviorally relevant information is processed in the lateral prefrontal cortex (LPFC), how the lateral frontal cortex (LFC) networks work as a functional hierarchy during IBL, and the cortical and subcortical contributions to IBL. Finally, we develop a neural working model for IBL and provide some sensible directions for future research.

Distinct Neural Circuits Underlie Prospective and Concurrent Memory-Guided Behavior

The past is the best predictor of the future. This simple postulate belies the complex neurobiological mechanisms that facilitate an individual's use of memory to guide decisions. Previous research has shown integration of memories bias decision-making. Alternatively, memories can prospectively guide our choices. Here, we elucidate the mechanisms and timing of hippocampal (HPC), medial prefrontal cortex (mPFC), and striatal contributions during prospective memory-guided decision-making. We develop an associative learning task in which the correct choice is conditional on the preceding stimulus. Two distinct networks emerge: (1) a prospective circuit consisting of the HPC, putamen, mPFC, and other cortical regions, which exhibit increased activation preceding successful conditional decisions and (2) a concurrent circuit comprising the caudate, dorsolateral prefrontal cortex (dlPFC), and additional cortical structures that engage during the execution of correct conditional choices. Our findings demonstrate distinct neurobiological circuits through which memory prospectively biases decisions and influences choice execution.

Task Errors Drive Memories That Improve Sensorimotor Adaptation

Traditional views of sensorimotor adaptation (i.e., adaptation of movements to perturbed sensory feedback) emphasize the role of automatic, implicit correction of sensory prediction errors. However, latent memories formed during sensorimotor adaptation, manifest as improved relearning (e.g., savings), have recently been attributed to strategic corrections of task errors (failures to achieve task goals). To dissociate contributions of task errors and sensory prediction errors to latent sensorimotor memories, we perturbed target locations to remove or enforce task errors during learning and/or test, with male/female human participants. Adaptation improved after learning in all conditions where participants were permitted to correct task errors, and did not improve whenever we prevented correction of task errors. Thus, previous correction of task errors was both necessary and sufficient to improve adaptation. In contrast, a history of sensory prediction errors was neither sufficient nor obligatory for improved adaptation. Limiting movement preparation time showed that the latent memories driven by learning to correct task errors take at least two forms: a time-consuming but flexible component, and a rapidly expressible, inflexible component. The results provide strong support for the idea that movement corrections driven by a failure to successfully achieve movement goals underpin motor memories that manifest as savings. Such persistent memories are not exclusively mediated by time-consuming strategic processes but also comprise a rapidly expressible but inflexible component. The distinct characteristics of these putative processes suggest dissociable underlying mechanisms, and imply that identification of the neural basis for adaptation and savings will require methods that allow such dissociations.SIGNIFICANCE STATEMENT Latent motor memories formed during sensorimotor adaptation manifest as improved adaptation when sensorimotor perturbations are reencountered. Conflicting theories suggest that this "savings" is underpinned by different mechanisms, including a memory of successful actions, a memory of errors, or an aiming strategy to correct task errors. Here we show that learning to correct task errors is sufficient to show improved subsequent adaptation with respect to naive performance, even when tested in the absence of task errors. In contrast, a history of sensory prediction errors is neither sufficient nor obligatory for improved adaptation. Finally, we show that latent sensorimotor memories driven by task errors comprise at least two distinct components: a time-consuming, flexible component, and a rapidly expressible, inflexible component.

An Integrated Model of Action Selection: Distinct Modes of Cortical Control of Striatal Decision Making

Making decisions in environments with few choice options is easy. We select the action that results in the most valued outcome. Making decisions in more complex environments, where the same action can produce different outcomes in different conditions, is much harder. In such circumstances, we propose that accurate action selection relies on top-down control from the prelimbic and orbitofrontal cortices over striatal activity through distinct thalamostriatal circuits. We suggest that the prelimbic cortex exerts direct influence over medium spiny neurons in the dorsomedial striatum to represent the state space relevant to the current environment. Conversely, the orbitofrontal cortex is argued to track a subject's position within that state space, likely through modulation of cholinergic interneurons.

Non-motor Characterization of the Basal Ganglia: Evidence From Human and Non-human Primate Electrophysiology

Although the basal ganglia have been implicated in a growing list of human behaviors, they include some of the least understood nuclei in the brain. For several decades studies have employed numerous methodologies to uncover evidence pointing to the basal ganglia as a hub of both motor and non-motor function. Recently, new electrophysiological characterization of the basal ganglia in humans has become possible through direct access to these deep structures as part of routine neurosurgery. Electrophysiological approaches for identifying non-motor function have the potential to unlock a deeper understanding of pathways that may inform clinical interventions and particularly neuromodulation. Various electrophysiological modalities can also be combined to reveal functional connections between the basal ganglia and traditional structures throughout the neocortex that have been linked to non-motor behavior. Several reviews have previously summarized evidence for non-motor function in the basal ganglia stemming from behavioral, clinical, computational, imaging, and non-primate animal studies; in this review, instead we turn to electrophysiological studies of non-human primates and humans. We begin by introducing common electrophysiological methodologies for basal ganglia investigation, and then we discuss studies across numerous non-motor domains–emotion, response inhibition, conflict, decision-making, error-detection and surprise, reward processing, language, and time processing. We discuss the limitations of current approaches and highlight the current state of the information.

Neural representations of time-linked memory

Many cognitive processes, such as episodic memory and decision making, rely on the ability to form associations between two events that occur separately in time. The formation of such temporal associations depends on neural representations of three types of information: what has been presented (trace holding), what will follow (temporal expectation), and when the following event will occur (explicit timing). The present review seeks to link these representations with firing patterns of single neurons recorded while rodents and non-human primates associate stimuli, outcomes, and motor responses over time intervals. Across these studies, two distinct firing patterns were observed in the hippocampus, neocortex, and striatum: some neurons change firing rates during or shortly after the stimulus presentation and sustain the firing rate stably or sidlingly during the subsequent intervals (tonic firings). Other neurons transiently change firing rates during a specific moment within the time intervals (phasic firings), and as a group, they form a sequential firing pattern that covers the entire interval. Clever task designs used in some of these studies collectively provide evidence that both tonic and phasic firing responses represent trace holding, temporal expectation, and explicit timing. Subsequently, we applied machine-learning based classification approaches to the two firing patterns within the same dataset collected from rat medial prefrontal cortex during trace eyeblink conditioning. This quantitative analysis revealed that phasic-firing patterns showed greater selectivity for stimulus identity and temporal position than tonic-firing patterns. Our summary illuminates distributed neural representations of temporal association in the forebrain and generates several ideas for future investigations.

Neural oscillations during conditional associative learning

Associative learning requires mapping between complex stimuli and behavioural responses. When multiple stimuli are involved, conditional associative learning is a gradual process with learning based on trial and error. It is established that a distributed network of regions track associative learning, however the role of neural oscillations in human learning remains less clear. Here we used scalp EEG to test how neural oscillations change during learning of arbitrary visuo-motor associations. Participants learned to associative 48 different abstract shapes to one of four button responses through trial and error over repetitions of the shapes. To quantify how well the associations were learned for each trial, we used a state-space computational model of learning that provided a probability of each trial being correct given past performance for that stimulus, that we take as a measure of the strength of the association. We used linear modelling to relate single-trial neural oscillations to single-trial measures of association strength. We found frontal midline theta oscillations during the delay period tracked learning, where theta activity was strongest during the early stages of learning and declined as the associations were formed. Further, posterior alpha and low-beta oscillations in the cue period showed strong desynchronised activity early in learning, while stronger alpha activity during the delay period was seen as associations became well learned. Moreover, the magnitude of these effects during early learning, before the associations were learned, related to improvements in memory seen on the next presentation of the stimulus. The current study provides clear evidence that frontal theta and posterior alpha/beta oscillations play a key role during associative memory formation.

Mapping and characterization of positive and negative BOLD responses to visual stimulation in multiple brain regions at 7T

External stimuli and tasks often elicit negative BOLD responses in various brain regions, and growing experimental evidence supports that these phenomena are functionally meaningful. In this work, the high sensitivity available at 7T was explored to map and characterize both positive (PBRs) and negative BOLD responses (NBRs) to visual checkerboard stimulation, occurring in various brain regions within and beyond the visual cortex. Recently-proposed accelerated fMRI techniques were employed for data acquisition, and procedures for exclusion of large draining vein contributions, together with ICA-assisted denoising, were included in the analysis to improve response estimation. Besides the visual cortex, significant PBRs were found in the lateral geniculate nucleus and superior colliculus, as well as the pre-central sulcus; in these regions, response durations increased monotonically with stimulus duration, in tight covariation with the visual PBR duration. Significant NBRs were found in the visual cortex, auditory cortex, default-mode network (DMN) and superior parietal lobule; NBR durations also tended to increase with stimulus duration, but were significantly less sustained than the visual PBR, especially for the DMN and superior parietal lobule. Responses in visual and auditory cortex were further studied for checkerboard contrast dependence, and their amplitudes were found to increase monotonically with contrast, linearly correlated with the visual PBR amplitude. Overall, these findings suggest the presence of dynamic neuronal interactions across multiple brain regions, sensitive to stimulus intensity and duration, and demonstrate the richness of information obtainable when jointly mapping positive and negative BOLD responses at a whole-brain scale, with ultra-high field fMRI.

Maintained avalanche dynamics during task-induced changes of neuronal activity in nonhuman primates

Sensory events, cognitive processing and motor actions correlate with transient changes in neuronal activity. In cortex, these transients form widespread spatiotemporal patterns with largely unknown statistical regularities. Here, we show that activity associated with behavioral events carry the signature of scale-invariant spatiotemporal clusters, neuronal avalanches. Using high-density microelectrode arrays in nonhuman primates, we recorded extracellular unit activity and the local field potential (LFP) in premotor and prefrontal cortex during motor and cognitive tasks. Unit activity and negative LFP deflections (nLFP) consistently changed in rate at single electrodes during tasks. Accordingly, nLFP clusters on the array deviated from scale-invariance compared to ongoing activity. Scale-invariance was recovered using ‘adaptive binning’, that is identifying clusters at temporal resolution given by task-induced changes in nLFP rate. Measures of LFP synchronization confirmed and computer simulations detailed our findings. We suggest optimization principles identified for avalanches during ongoing activity to apply to cortical information processing during behavior.

Distinct Neural Activities in Premotor Cortex during Natural Vocal Behaviors in a New World Primate, the Common Marmoset (Callithrix jacchus)

Although evidence from human studies has long indicated the crucial role of the frontal cortex in speech production, it has remained uncertain whether the frontal cortex in nonhuman primates plays a similar role in vocal communication. Previous studies of prefrontal and premotor cortices of macaque monkeys have found neural signals associated with cue- and reward-conditioned vocal production, but not with self-initiated or spontaneous vocalizations (Coudé et al., 2011; Hage and Nieder, 2013), which casts doubt on the role of the frontal cortex of the Old World monkeys in vocal communication. A recent study of marmoset frontal cortex observed modulated neural activities associated with self-initiated vocal production (Miller et al., 2015), but it did not delineate whether these neural activities were specifically attributed to vocal production or if they may result from other nonvocal motor activity such as orofacial motor movement. In the present study, we attempted to resolve these issues and examined single neuron activities in premotor cortex during natural vocal exchanges in the common marmoset (Callithrix jacchus), a highly vocal New World primate. Neural activation and suppression were observed both before and during self-initiated vocal production. Furthermore, by comparing neural activities between self-initiated vocal production and nonvocal orofacial motor movement, we identified a subpopulation of neurons in marmoset premotor cortex that was activated or suppressed by vocal production, but not by orofacial movement. These findings provide clear evidence of the premotor cortex's involvement in self-initiated vocal production in natural vocal behaviors of a New World primate.

SIGNIFICANCE STATEMENT

Human frontal cortex plays a crucial role in speech production. However, it has remained unclear whether the frontal cortex of nonhuman primates is involved in the production of self-initiated vocalizations during natural vocal communication. Using a wireless multichannel neural recording technique, we observed in the premotor cortex neural activation and suppression both before and during self-initiated vocalizations when marmosets, a highly vocal New World primate species, engaged in vocal exchanges with conspecifics. A novel finding of the present study is the discovery of a subpopulation of premotor cortex neurons that was activated by vocal production, but not by orofacial movement. These observations provide clear evidence of the premotor cortex's involvement in vocal production in a New World primate species.

Parsing Heterogeneous Striatal Activity

The striatum is an input channel of the basal ganglia and is well known to be involved in reward-based decision making and learning. At the macroscopic level, the striatum has been postulated to contain parallel functional modules, each of which includes neurons that perform similar computations to support selection of appropriate actions for different task contexts. At the single-neuron level, however, recent studies in monkeys and rodents have revealed heterogeneity in neuronal activity even within restricted modules of the striatum. Looking for generality in the complex striatal activity patterns, here we briefly survey several types of striatal activity, focusing on their usefulness for mediating behaviors. In particular, we focus on two types of behavioral tasks: reward-based tasks that use salient sensory cues and manipulate outcomes associated with the cues; and perceptual decision tasks that manipulate the quality of noisy sensory cues and associate all correct decisions with the same outcome. Guided by previous insights on the modular organization and general selection-related functions of the basal ganglia, we relate striatal activity patterns on these tasks to two types of computations: implementation of selection and evaluation. We suggest that a parsing with the selection/evaluation categories encourages a focus on the functional commonalities revealed by studies with different animal models and behavioral tasks, instead of a focus on aspects of striatal activity that may be specific to a particular task setting. We then highlight several questions in the selection-evaluation framework for future explorations.

Role of human premotor dorsal region in learning a conditional visuomotor task

Conditional learning is an important component of our everyday activities (e.g., handling a phone or sorting work files) and requires identification of the arbitrary stimulus, accurate selection of the motor response, monitoring of the response, and storing in memory of the stimulus-response association for future recall. Learning this type of conditional visuomotor task appears to engage the premotor dorsal region (PMd). However, the extent to which PMd might be involved in specific or all processes of conditional learning is not well understood. Using transcranial magnetic stimulation (TMS), we demonstrate the role of human PMd in specific stages of learning of a novel conditional visuomotor task that required subjects to identify object center of mass using a color cue and to apply appropriate torque on the object at lift onset to minimize tilt. TMS over PMd, but not vertex, increased error in torque exerted on the object during the learning trials. Analyses of digit position and forces further revealed that the slowing in conditional visuomotor learning resulted from impaired monitoring of the object orientation during lift, rather than stimulus identification, thus compromising the ability to accurately reduce performance error across trials. Importantly, TMS over PMd did not alter production of torque based on the recall of learned color-torque associations. We conclude that the role of PMd for conditional learning is highly sensitive to the stage of learning visuomotor associations.

NEW & NOTEWORTHY

Conditional learning involves stimulus identification, motor response selection, response monitoring, memory encoding, and recall of the learned association. Premotor dorsal (PMd) has been implicated for conditional learning. However, the extent to which PMd might be involved in specific or all stages of conditional learning is not well understood. The novel finding of our study is that PMd appears to be involved with monitoring motor responses, a sensorimotor integration stage essential for conditional learning.

Fast and slow transitions in frontal ensemble activity during flexible sensorimotor behavior

The ability to shift between repetitive and goal-directed actions is a hallmark of cognitive control. Previous studies have reported that adaptive shifts in behavior are accompanied by changes of neural activity in frontal cortex. However, neural and behavioral adaptations can occur at multiple time scales, and their relationship remains poorly defined. Here we developed an adaptive sensorimotor decision-making task for head-fixed mice, requiring them to shift flexibly between multiple auditory-motor mappings. Two-photon calcium imaging of secondary motor cortex (M2) revealed different ensemble activity states for each mapping. When adapting to a conditional mapping, transitions in ensemble activity were abrupt and occurred before the recovery of behavioral performance. By contrast, gradual and delayed transitions accompanied shifts toward repetitive responding. These results demonstrate distinct ensemble signatures associated with the start versus end of sensory-guided behavior and suggest that M2 leads in engaging goal-directed response strategies that require sensorimotor associations.

Hierarchical effects on target detection and conflict monitoring

Previous neuroimaging studies have demonstrated a hierarchical functional structure of the frontal cortices of the human brain, but the temporal course and the electrophysiological signature of the hierarchical representation remains unaddressed. In the present study, twenty-one volunteers were asked to perform a nested cue-target task, while their scalp potentials were recorded. The results showed that: (1) in comparison with the lower-level hierarchical targets, the higher-level targets elicited a larger N2 component (220-350 ms) at the frontal sites, and a smaller P3 component (350-500 ms) across the frontal and parietal sites; (2) conflict-related negativity (non-target minus target) was greater for the lower-level hierarchy than the higher-level, reflecting a more intensive process of conflict monitoring at the final step of target detection. These results imply that decision making, context updating, and conflict monitoring differ among different hierarchical levels of abstraction.

Learning a New Selection Rule in Visual and Frontal Cortex

How do you make a decision if you do not know the rules of the game? Models of sensory decision-making suggest that choices are slow if evidence is weak, but they may only apply if the subject knows the task rules. Here, we asked how the learning of a new rule influences neuronal activity in the visual (area V1) and frontal cortex (area FEF) of monkeys. We devised a new icon-selection task. On each day, the monkeys saw 2 new icons (small pictures) and learned which one was relevant. We rewarded eye movements to a saccade target connected to the relevant icon with a curve. Neurons in visual and frontal cortex coded the monkey's choice, because the representation of the selected curve was enhanced. Learning delayed the neuronal selection signals and we uncovered the cause of this delay in V1, where learning to select the relevant icon caused an early suppression of surrounding image elements. These results demonstrate that the learning of a new rule causes a transition from fast and random decisions to a more considerate strategy that takes additional time and they reveal the contribution of visual and frontal cortex to the learning process.

Improved discriminability of spatiotemporal neural patterns in rat motor cortical areas as directional choice learning progresses

Animals learn to choose a proper action among alternatives to improve their odds of success in food foraging and other activities critical for survival. Through trial-and-error, they learn correct associations between their choices and external stimuli. While a neural network that underlies such learning process has been identified at a high level, it is still unclear how individual neurons and a neural ensemble adapt as learning progresses. In this study, we monitored the activity of single units in the rat medial and lateral agranular (AGm and AGl, respectively) areas as rats learned to make a left or right side lever press in response to a left or right side light cue. We noticed that rat movement parameters during the performance of the directional choice task quickly became stereotyped during the first 2–3 days or sessions. But learning the directional choice problem took weeks to occur. Accompanying rats' behavioral performance adaptation, we observed neural modulation by directional choice in recorded single units. Our analysis shows that ensemble mean firing rates in the cue-on period did not change significantly as learning progressed, and the ensemble mean rate difference between left and right side choices did not show a clear trend of change either. However, the spatiotemporal firing patterns of the neural ensemble exhibited improved discriminability between the two directional choices through learning. These results suggest a spatiotemporal neural coding scheme in a motor cortical neural ensemble that may be responsible for and contributing to learning the directional choice task.

Dorsal premotor cortex: neural correlates of reach target decisions based on a color-location matching rule and conflicting sensory evidence

We recorded single-neuron activity in dorsal premotor (PMd) and primary motor cortex (M1) of two monkeys in a reach-target selection task. The monkeys chose between two color-coded potential targets by determining which target's color matched the predominant color of a multicolored checkerboard-like Decision Cue (DC). Different DCs contained differing numbers of colored squares matching each target. The DCs provided evidence about the correct target ranging from unambiguous (one color only) to very ambiguous and conflicting (nearly equal number of squares of each color). Differences in choice behavior (reach response times and success rates as a function of DC ambiguity) of the monkeys suggested that each applied a different strategy for using the target-choice evidence in the DCs. Nevertheless, the appearance of the DCs evoked a transient coactivation of PMd neurons preferring both potential targets in both monkeys. Reach response time depended both on how long it took activity to increase in neurons that preferred the chosen target and on how long it took to suppress the activity of neurons that preferred the rejected target, in both correct-choice and error-choice trials. These results indicate that PMd neurons in this task are not activated exclusively by a signal proportional to the net color bias of the DCs. They are instead initially modulated by the conflicting evidence supporting both response choices; final target selection may result from a competition between representations of the alternative choices. The results also indicate a temporal overlap between action selection and action initiation processes in PMd and M1.

Practice structure improves unconscious transitional memories by increasing synchrony in a premotor network

Sequence learning relies on formation of unconscious transitional and conscious ordinal memories. The influence of practice type on formation of these memories that compose skill and systems level neural substrates is not known. Here, we studied learning of transitional and ordinal memories in participants trained on motor sequences while scanned using fMRI. Practice structure was varied or grouped (mixing or grouping sequences during training, respectively). Memory was assessed 30 min and 1 week later. Varied practice improved transitional memory and enhanced coupling of the dorsal premotor cortex with thalamus, cerebellum, and lingual and cingulate regions and greater transitional memory correlated with this coupling. Thus, varied practice improves unconscious transitional memories in proportion to coupling within a cortico-subcortical network linked to premotor cortex. This result indicates that practice structure influences unconscious transitional memory formation and identifies underlying systems level mechanisms.

The effects of short-term and long-term learning on the responses of lateral intraparietal neurons to visually presented objects

The lateral intraparietal area (LIP) is thought to play an important role in the guidance of where to look and pay attention. LIP can also respond selectively to differently shaped objects. We sought to understand to what extent short-term and long-term experience with visual orienting determines the responses of LIP to objects of different shapes. We taught monkeys to arbitrarily associate centrally presented objects of various shapes with orienting either toward or away from a preferred spatial location of a neuron. The training could last for less than a single day or for several months. We found that neural responses to objects are affected by such experience, but that the length of the learning period determines how this neural plasticity manifests. Short-term learning affects neural responses to objects, but these effects are only seen relatively late after visual onset; at this time, the responses to newly learned objects resemble those of familiar objects that share their meaning or arbitrary association. Long-term learning affects the earliest bottom-up responses to visual objects. These responses tend to be greater for objects that have been associated with looking toward, rather than away from, LIP neurons' preferred spatial locations. Responses to objects can nonetheless be distinct, although they have been similarly acted on in the past and will lead to the same orienting behavior in the future. Our results therefore indicate that a complete experience-driven override of LIP object responses may be difficult or impossible. We relate these results to behavioral work on visual attention.

Reach target selection in humans using ambiguous decision cues containing variable amounts of conflicting sensory evidence supporting each target choice

Human subjects chose between two color-coded reach targets using multicolored checkerboard-like decision cues (DCs) that presented variable amounts of conflicting sensory evidence supporting both target choices. Different DCs contained different numbers of small squares of the two target colors. The most ambiguous DCs contained nearly equal numbers of squares of both target colors. The subjects reached as soon as they selected a target after the appearance of the DC (“choose-and-go” task). The choice behavior of the subjects showed many similarities to prior studies using other stimulus properties (e.g., visual motion coherence, brightness), including progressively longer response times and higher target-choice error rates for more ambiguous DCs. However, certain trends in their choice behavior could not be fully captured by simple drift-diffusion models. Allowing the subjects to view the DCs for a period of time before presenting the targets (“match-to-sample” task) resulted in much shorter response times overall, but also revealed a reluctance of subjects to commit to a decision about the predominant color of the more ambiguous DCs during the initial extended observation period. Model processing and simulation analyses suggest that the subjects might adjust the dynamics of their decision-making process on a trial-to-trial basis in response to the variable level of ambiguous and conflicting evidence in different DCs between trials.

Auditory observation of infant-directed speech by mothers: experience-dependent interaction between language and emotion in the basal ganglia

Adults address infants with a special speech register known as infant-directed speech (IDS), which conveys both linguistic and emotional information through its characteristic lexicon and exaggerated prosody (e.g., higher pitched, slower, and hyperarticulated). Although caregivers are known to regulate the usage of IDS (linguistic and emotional components) depending on their child's development, the underlying neural substrates of this flexible modification are largely unknown. Here, using an auditory observation method and functional magnetic resonance imaging (fMRI) of four different groups of females, we revealed the experience-dependent influence of the emotional component on linguistic processing in the right caudate nucleus when mothers process IDS: (1) non-mothers, who do not use IDS regularly, showed no significant difference between IDS and adult-directed speech (ADS); (2) mothers with preverbal infants, who primarily use the emotional component of IDS, showed the main effect of the emotional component of IDS; (3) mothers with toddlers at the two-word stage, who use both linguistic and emotional components of IDS, showed an interaction between the linguistic and emotional components of IDS; and (4) mothers with school-age children, who use ADS rather than IDS toward their children, showed a tendency toward the main effect of ADS. The task that was most comparable to the naturalistic categories of IDS (i.e., explicit-language and implicit-emotion processing) recruited the right caudate nucleus, but it was not recruited in the control, less naturalistic condition (explicit-emotion and implicit-language processing). Our results indicate that the right caudate nucleus processes experience-and task-dependent interactions between language and emotion in mothers' IDS.

Extrasynaptic glutamate NMDA receptors: key players in striatal function

N-methyl-D-aspartate receptors (NMDAR) are crucial for the function of excitatory neurotransmission and are present at the synapse and on the extrasynaptic membrane. The major nucleus of the basal ganglia, striatum, receives a large glutamatergic excitatory input carrying information about movements and associated sensory stimulation for its proper function. Such bombardment of glutamate synaptic release results in a large extracellular concentration of glutamate that can overcome the neuronal and glial uptake homeostatic systems therefore allowing the stimulation of extrasynaptic glutamate receptors. Here we have studied the participation of their extrasynaptic type in cortically evoked responses or in the presence of NMDARs stimulation. We report that extrasynaptic NMDAR blocker memantine, reduced in a dose-dependent manner cortically induced NMDA excitatory currents in striatal neurons (recorded in zero-Mg(++) plus DNQX 10 μM). Moreover, memantine (2-4 μM) significantly reduced the NMDAR-dependent membrane potential oscillations called up and down states. Recordings of neuronal striatal networks with a fluorescent calcium indicator or with multielectrode arrays (MEA) also showed that memantine reduced in a dose-dependent manner, NMDA-induced excitatory currents and network behavior. We used multielectrode arrays (MEA) to grow segregated cortical and striatal neurons. Once synaptic contacts were developed (>21DIV) recordings of extracellular activity confirmed the cortical drive of spontaneous synchronous discharges in both compartments. After severing connections between compartments, active striatal neurons in the presence of memantine (1 μM) and CNQX (10 μM) were predominantly fast spiking interneurons (FSI). The significance of extrasynaptic receptors in the regulation of striatal function and neuronal network activity is evident.

Patterns of cortical input to the primary motor area in the marmoset monkey

In primates the primary motor cortex (M1) forms a topographic map of the body, whereby neurons in the medial part of this area control movements involving trunk and hindlimb muscles, those in the intermediate part control movements involving forelimb muscles, and those in the lateral part control movements of facial and other head muscles. This topography is accompanied by changes in cytoarchitectural characteristics, raising the question of whether the anatomical connections also vary between different parts of M1. To address this issue, we compared the patterns of cortical afferents revealed by retrograde tracer injections in different locations within M1 of marmoset monkeys. We found that the entire extent of this area is unified by projections from the dorsocaudal and medial subdivisions of premotor cortex (areas 6DC and 6M), from somatosensory areas 3a, 3b, 1/2, and S2, and from posterior parietal area PE. While cingulate areas projected to all subdivisions, they preferentially targeted the medial part of M1. Conversely, the ventral premotor areas were preferentially connected with the lateral part of M1. Smaller but consistent inputs originated in frontal area 6DR, ventral posterior parietal cortex, the retroinsular cortex, and area TPt. Connections with intraparietal, prefrontal, and temporal areas were very sparse, and variable. Our results demonstrate that M1 is unified by a consistent pattern of major connections, but also shows regional variations in terms of minor inputs. These differences likely reflect requirements for control of voluntary movement involving different body parts.

Inter-synaptic learning of combination rules in a cortical network model

Selecting responses in working memory while processing combinations of stimuli depends strongly on their relations stored in long-term memory. However, the learning of XOR-like combinations of stimuli and responses according to complex rules raises the issue of the non-linear separability of the responses within the space of stimuli. One proposed solution is to add neurons that perform a stage of non-linear processing between the stimuli and responses, at the cost of increasing the network size. Based on the non-linear integration of synaptic inputs within dendritic compartments, we propose here an inter-synaptic (IS) learning algorithm that determines the probability of potentiating/depressing each synapse as a function of the co-activity of the other synapses within the same dendrite. The IS learning is effective with random connectivity and without either a priori wiring or additional neurons. Our results show that IS learning generates efficacy values that are sufficient for the processing of XOR-like combinations, on the basis of the sole correlational structure of the stimuli and responses. We analyze the types of dendrites involved in terms of the number of synapses from pre-synaptic neurons coding for the stimuli and responses. The synaptic efficacy values obtained show that different dendrites specialize in the detection of different combinations of stimuli. The resulting behavior of the cortical network model is analyzed as a function of inter-synaptic vs. Hebbian learning. Combinatorial priming effects show that the retrospective activity of neurons coding for the stimuli trigger XOR-like combination-selective prospective activity of neurons coding for the expected response. The synergistic effects of inter-synaptic learning and of mixed-coding neurons are simulated. The results show that, although each mechanism is sufficient by itself, their combined effects improve the performance of the network.

Patterns of afferent input to the caudal and rostral areas of the dorsal premotor cortex (6DC and 6DR) in the marmoset monkey

Corticocortical projections to the caudal and rostral areas of dorsal premotor cortex (6DC and 6DR, also known as F2 and F7) were studied in the marmoset monkey. Both areas received their main thalamic inputs from the ventral anterior and ventral lateral complexes, and received dense projections from the medial premotor cortex. However, there were marked differences in their connections with other cortical areas. While 6DR received consistent inputs from prefrontal cortex, area 6DC received few such connections. Conversely, 6DC, but not 6DR, received major projections from the primary motor and somatosensory areas. Projections from the anterior cingulate cortex preferentially targeted 6DC, while the posterior cingulate and adjacent medial wall areas preferentially targeted 6DR. Projections from the medial parietal area PE to 6DC were particularly dense, while intraparietal areas (especially the putative homolog of LIP) were more strongly labeled after 6DR injections. Finally, 6DC and 6DR were distinct in terms of inputs from the ventral parietal cortex: projections to 6DR originated preferentially from caudal areas (PG and OPt), while 6DC received input primarily from rostral areas (PF and PFG). Differences in connections suggest that area 6DR includes rostral and caudal subdivisions, with the former also involved in oculomotor control. These results suggest that area 6DC is more directly involved in the preparation and execution of motor acts, while area 6DR integrates sensory and internally driven inputs for the planning of goal-directed actions. They also provide strong evidence of a homologous organization of the dorsal premotor cortex in New and Old World monkeys.

Passive reading and motor imagery about hand actions and tool-use actions: an fMRI study

Recent studies have shown that motor activations in action verb comprehension can be modulated by task demands (e.g., motor imagery vs. passive reading) and the specificity of action verb meaning. However, how the two factors work together to influence the involvement of the motor system during action verb comprehension is still unclear. To address the issue, the current study investigated the brain activations in motor imagery and passive reading of verbs about hand actions and tool-use actions. Three types of Chinese verbs were used, including hand-action verbs and two types of tool-use verbs emphasizing either the hand or tools information. Results indicated that all three types of verbs elicited common activations in hand motor areas during passive reading and motor imagery. Contrast analyses showed that in the hand verbs and the tool verbs where the hand information was emphasized, motor imagery elicited stronger effects than passive reading in the superior frontal gyrus, supplemental motor area and cingulate cortex that are related to motor control and regulation. For tool-use verbs emphasizing tools information, the motor imagery task elicited stronger activity than passive reading in occipital regions related to visual imagery. These results suggest that motor activations during action verb comprehension can be modulated by task demands and semantic features of action verbs. The sensorimotor simulation during language comprehension is flexible and determined by the interactions between linguistic and extralinguistic contexts.

Cortico-basal ganglia networks subserving goal-directed behavior mediated by conditional visuo-goal association

Action is often executed according to information provided by a visual signal. As this type of behavior integrates two distinct neural representations, perception and action, it has been thought that identification of the neural mechanisms underlying this process will yield deeper insights into the principles underpinning goal-directed behavior. Based on a framework derived from conditional visuomotor association, prior studies have identified neural mechanisms in the dorsal premotor cortex (PMd), dorsolateral prefrontal cortex (dlPFC), ventrolateral prefrontal cortex (vlPFC), and basal ganglia (BG). However, applications resting solely on this conceptualization encounter problems related to generalization and flexibility, essential processes in executive function, because the association mode involves a direct one-to-one mapping of each visual signal onto a particular action. To overcome this problem, we extend this conceptualization and postulate a more general framework, conditional visuo-goal association. According to this new framework, the visual signal identifies an abstract behavioral goal, and an action is subsequently selected and executed to meet this goal. Neuronal activity recorded from the four key areas of the brains of monkeys performing a task involving conditional visuo-goal association revealed three major mechanisms underlying this process. First, visual-object signals are represented primarily in the vlPFC and BG. Second, all four areas are involved in initially determining the goals based on the visual signals, with the PMd and dlPFC playing major roles in maintaining the salience of the goals. Third, the cortical areas play major roles in specifying action, whereas the role of the BG in this process is restrictive. These new lines of evidence reveal that the four areas involved in conditional visuomotor association contribute to goal-directed behavior mediated by conditional visuo-goal association in an area-dependent manner.

Electrical stimulation-evoked dopamine release in the primate striatum

BACKGROUND

Primate studies demonstrate that high-frequency electrical stimulation (HFS) of the caudate can enhance learning. Importantly, in these studies, stimulation was applied following the execution of behavior and the effect persisted into subsequent trials, suggesting a change in plasticity rather than a momentary facilitation of behavior.

OBJECTIVES/METHODS

Although the mechanism of HFS-enhanced learning is not understood, evidence suggests that dopamine plays a critical role. Therefore, we used in vivo amperometry to evaluate the effects of HFS on striatal dopamine release in the anesthetized primate. While this does not directly examine dopamine during learning, it provides insight with relation to dopamine dynamics during electrical stimulation and specifically between different stimulation parameters and striatal compartments.

RESULTS

We demonstrate that HFS results in significantly more dopamine release in the striatum compared to low-frequency stimulation. In addition, electrical stimulation operates differentially on specific neuronal elements, as the parameters for dopamine release are different for the caudate, putamen and medial forebrain bundle.

CONCLUSIONS

While not direct evidence, these data suggest that HFS evokes significant dopamine release which may play a role in stimulation-enhanced learning. Moreover, these data suggest a means to modulate extracellular dopamine with a high degree of temporal and spatial precision for either research or clinical applications.

Many hats: intratrial and reward level-dependent BOLD activity in the striatum and premotor cortex

Human functional magnetic resonance imaging (fMRI) studies, as well as lesion, drug, and single-cell recording studies in animals, suggest that the striatum plays a key role in associating sensory events with rewarding actions, both by facilitating reward processing and prediction (i.e., reinforcement learning) and by biasing and later updating action selection. Previous human neuroimaging research has failed to dissociate striatal activity associated with reward, stimulus, and response processing, and previous electrophysiological research in nonhuman animals has typically only examined single striatal subregions. Overcoming both these limitations, we isolated blood oxygen level-dependent (BOLD) signal associated with four intratrial processes (stimulus, preparation of response, response, and feedback) in a visuomotor learning task and examined activity associated with each within four striatal subregions (ventral striatum, putamen, head of the caudate nucleus, and body of the caudate) and the lateral premotor cortex. Overall, the striatum and lateral premotor cortex were recruited during all trial components, confirming their importance in all aspects of visuomotor learning. However, the caudate was most active at stimulus and feedback, whereas the putamen peaked in activity at response. Activation in the lateral premotor cortex was, surprisingly, strongest during stimulus and following response as feedback approached. Activity was additionally examined at three reward magnitudes. Reward magnitude affected neural activity only during stimulus in the caudate, putamen, and premotor cortex, whereas the ventral striatum showed reward sensitivity during both stimulus and feedback. Collectively, these results indicate that each striatal region makes a unique contribution to visuomotor learning through functions performed at different points within single trials.

Task-related "cortical" bursting depends critically on basal ganglia input and is linked to vocal plasticity

Basal ganglia-thalamocortical circuits are critical for motor control and motor learning. Classically, basal ganglia nuclei are thought to regulate motor behavior by increasing or decreasing cortical firing rates, and basal ganglia diseases are assumed to reflect abnormal overall activity levels. More recent studies suggest instead that motor disorders derive from abnormal firing patterns, and have led to the hypothesis that surgical treatments, such as pallidotomy, act primarily by eliminating pathological firing patterns. Surprisingly little is known, however, about how the basal ganglia normally influence task-related cortical activity to regulate motor behavior, and how lesions of the basal ganglia influence cortical firing properties. Here, we investigated these questions in a songbird circuit that has striking homologies to mammalian basal ganglia-thalamocortical circuits but is specialized for singing. The "cortical" outflow nucleus of this circuit is required for song plasticity and normally exhibits increased firing during singing and song-locked burst firing. We found that lesions of the striato-pallidal nucleus in this circuit prevented hearing-dependent song changes. These basal ganglia lesions also stripped the cortical outflow neurons of their patterned burst firing during singing, without changing their spontaneous or singing-related firing rates. Taken together, these results suggest that the basal ganglia are essential not for normal cortical firing rates but for driving task-specific cortical firing patterns, including bursts. Moreover, such patterned bursting appears critical for motor plasticity. Our findings thus provide support for therapies that aim to treat basal ganglia movement disorders by normalizing firing patterns.

Advanced Parkinson's disease effect on goal-directed and habitual processes involved in visuomotor associative learning

The present behavioral study re-addresses the question of habit learning in Parkinson's disease (PD). Patients were early onset, non-demented, dopa-responsive, candidates for surgical treatment, similar to those we found earlier as suffering greater dopamine depletion in the putamen than in the caudate nucleus. The task was the same conditional associative learning task as that used previously in monkeys and healthy humans to unveil the striatum involvement in habit learning. Sixteen patients and 20 age- and education-matched healthy control subjects learned sets of 3 visuo-motor associations between complex patterns and joystick displacements during two testing sessions separated by a few hours. We distinguished errors preceding vs. following the first correct response to compare patients' performance during the earliest phase of learning dominated by goal-directed actions with that observed later on, when responses start to become habitual. The disease significantly retarded both learning phases, especially in patients under 60 years of age. However, only the late phase deficit was disease severity-dependent and persisted on the second testing session. These findings provide the first corroboration in Parkinson patients of two ideas well-established in the animal literature. The first is the idea that associating visual stimuli to motor acts is a form of habit learning that engages the striatum. It is confirmed here by the global impairment in visuo-motor learning induced by PD. The second idea is that goal-directed behaviors are predominantly caudate-dependent whereas habitual responses are primarily putamen-dependent. At the advanced PD stages tested here, dopamine depletion is greater in the putamen than in the caudate nucleus. Accordingly, the late phase of learning corresponding to the emergence of habitual responses was more vulnerable to the disease than the early phase dominated by goal-directed actions.

Distinct information representation and processing for goal-directed behavior in the dorsolateral and ventrolateral prefrontal cortex and the dorsal premotor cortex

Although the lateral prefrontal cortex (lPFC) and dorsal premotor cortex (PMd) are thought to be involved in goal-directed behavior, the specific roles of each area still remain elusive. To characterize and compare neuronal activity in two sectors of the lPFC [dorsal (dlPFC) and ventral (vlPFC)] and the PMd, we designed a behavioral task for monkeys to explore the differences in their participation in four aspects of information processing: encoding of visual signals, behavioral goal retrieval, action specification, and maintenance of relevant information. We initially presented a visual object (an instruction cue) to instruct a behavioral goal (reaching to the right or left of potential targets). After a subsequent delay, a choice cue appeared at various locations on a screen, and the animals could specify an action to achieve the behavioral goal. We found that vlPFC neurons amply encoded object features of the instruction cues for behavioral goal retrieval and, subsequently, spatial locations of the choice cues for specifying the actions. By contrast, dlPFC and PMd neurons rarely encoded the object features, although they reflected the behavioral goals throughout the delay period. After the appearance of the choice cues, the PMd held information for action throughout the specification and preparation of reaching movements. Remarkably, lPFC neurons represented information for the behavioral goal continuously, even after the action specification as well as during its execution. These results indicate that area-specific representation and information processing at progressive stages of the perception-action transformation in these areas underlie goal-directed behavior.

Sensorimotor learning biases choice behavior: a learning neural field model for decision making

According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making) should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject's learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action selection required for decision making in ambiguous choice situations.

Decision making requires the selection between alternative actions. It has been suggested that action selection is not separate from motor preparation of the according actions, but rather that the selection emerges from the competition between different movement plans. We expand on this idea, and ask how action selection mechanisms interact with the learning of new action choices. We present a neurodynamic model that provides an integrated account of action selection and the learning of sensorimotor associations. The model explains recent electrophysiological findings from monkeys' sensorimotor cortex, and correctly predicted a newly described characteristic pattern of their choice errors. Based on the model, we present a theory of how geometrical sensorimotor mapping rules can be learned by association without the need for an explicit representation of the transformation rule, and how the learning history of these associations can have a direct influence on later decision making.

An investigation of implicit memory through left temporal lobectomy for epilepsy

Temporal lobe epilepsy patients have demonstrated a relative preservation in the integrity of implicit memory procedures. We examined performance in a verbal implicit and explicit memory task in left anterior temporal lobectomy patients (LATL) and healthy normal controls (NCs) while undergoing fMRI. We hypothesized that despite the relative integrity of implicit memory in both the LATL patients and normal controls, the two groups would show distinct functional neuroanatomic profiles during implicit memory. LATLs and NCs performed Jacoby's Process Dissociation Process (PDP) procedure during fMRI, requiring completion of word stems based on the previously studied words or new/unseen words. Measures of automaticity and recollection provided uncontaminated indices of implicit and explicit memory, respectively. The behavioral data showed that in the face of temporal lobe pathology implicit memory can be carried out, suggesting implicit verbal memory retrieval is non-mesial temporal in nature. Compared to NCs, the LATL patients showed reliable activation, not deactivation, during implicit (automatic) responding. The regions mediating this response were cortical (left medial frontal and precuneus) and striatal. The active regions in LATL patients have the capacity to implement associative, conditioned responses that might otherwise be carried out by a healthy temporal lobe, suggesting this represented a compensatory activity. Because the precuneus has also been implicated in explicit memory, the data suggests this structure may have a highly flexible functionality, capable of supporting implementation of either explicit memory, or automatic processes such as implicit memory retrieval. Our data suggest that a healthy mesial/anterior temporal lobe may be needed for generating the posterior deactivation perceptual priming response seen in normals.

Multisynaptic projections from the ventrolateral prefrontal cortex to the dorsal premotor cortex in macaques - anatomical substrate for conditional visuomotor behavior

Lines of evidence indicate that both the ventrolateral prefrontal cortex (vlPFC) (areas 45/12) and dorsal premotor cortex (PMd) (rostral F2 in area 6) are crucially involved in conditional visuomotor behavior, in which it is required to determine an action based on an associated visual object. However, virtually no direct projections appear to exist between the vlPFC and PMd. In the present study, to elucidate possible multisynaptic networks linking the vlPFC to the PMd, we performed a series of neuroanatomical tract-tracing experiments in macaque monkeys. First, we identified cortical areas that send projection fibers directly to the PMd by injecting Fast Blue into the PMd. Considerable retrograde labeling occurred in the dorsal prefrontal cortex (dPFC) (areas 46d/9/8B/8Ad), dorsomedial motor cortex (dmMC) (F7 and presupplementary motor area), rostral cingulate motor area, and ventral premotor cortex (F5 and area 44), whereas the vlPFC was virtually devoid of neuronal labeling. Second, we injected the rabies virus, a retrograde transneuronal tracer, into the PMd. At 3 days after the rabies injections, second-order neurons were labeled in the vlPFC (mainly area 45), indicating that the vlPFC disynaptically projects to the PMd. Finally, to determine areas that connect the vlPFC to the PMd indirectly, we carried out an anterograde/retrograde dual-labeling experiment in single monkeys. By examining the distribution of axon terminals labeled from the vlPFC and cell bodies labeled from the PMd, we found overlapping labels in the dPFC and dmMC. These results indicate that the vlPFC outflow is directed toward the PMd in a multisynaptic fashion through the dPFC and/or dmMC.

The influence of movement initiation deficits on the quantification of retention in Parkinson's disease

In patients with an impaired motor system, like Parkinson’s disease (PD), deficits in motor learning are expected and results of various studies seem to confirm these expectations. However, most studies in this regard are behaviorally based and quantify learning by performance changes between at least two points in time, e.g., baseline and retention. But, performance in a retention test is also dependent on other factors than learning. Especially in patients, the functional capacity of the control system might be altered unspecific to a certain task and learning episode. The aim of the study is to test whether characteristic temporal deficits exist in PD patients that affect retention performance. We tested the confounding effects of typical PD motor control deficits, here movement initiation deficits, on retention performance in the motor learning process. 12 PD patients and 16 healthy control participants practiced a virtual throwing task over 3 days with 24 h rest between sessions. Retention was tested comparing performance before rest with performance after rest. Movement initiation deficits were quantified by the timing of throwing release that should be affected by impairments in movement initiation. To scrutinize the influence of the initiation deficits on retention performance we gave participants a specific initiation intervention prior to practice on one of the three practice days. We found that only for the PD patients, post-rest performance as well as release timing was better with intervention as compared to without intervention. Their performance could be enhanced through a tuning of release initiation. Thus, we suggest that in PD patients, performance decline after rest that might be easily interpreted as learning deficits could rather result from disease-related deficiencies in motor control.

Frontostriatal mechanisms in instruction-based learning as a hallmark of flexible goal-directed behavior

The present review intends to provide a neuroscientific perspective on the flexible (here: almost instantaneous) adoption of novel goal-directed behaviors. The overarching goal is to sketch the emerging framework for examining instruction-based learning and how this can be related to more established research approaches to instrumental learning and goal-directed action. We particularly focus on the contribution of frontal and striatal brain regions drawing on studies in both, animals and humans, but with an emphasize put on human neuroimaging studies. In section one, we review and integrate a selection of previous studies that are suited to generally delineate the neural underpinnings of goal-directed action as opposed to more stimulus-based (i.e., habitual) action. Building on that the second section focuses more directly on the flexibility to rapidly implement novel behavioral rules as a hallmark of goal-directed action with a special emphasis on instructed rules. In essence, the current neuroscientific evidence suggests that the prefrontal cortex and associative striatum are able to selectively and transiently code the currently relevant relationship between stimuli, actions, and the effects of these actions in both, instruction-based learning as well as in trial-and-error learning. The premotor cortex in turn seems to form more durable associations between stimuli and actions or stimuli, actions and effects (but not incentive values) thus representing the available action possibilities. Together, the central message of the present review is that instruction-based learning should be understood as a prime example of goal-directed action, necessitating a closer interlacing with basic mechanisms of goal-directed action on a more general level.

Action selection and action value in frontal-striatal circuits

The role that frontal-striatal circuits play in normal behavior remains unclear. Two of the leading hypotheses suggest that these circuits are important for action selection or reinforcement learning. To examine these hypotheses, we carried out an experiment in which monkeys had to select actions in two different task conditions. In the first (random) condition, actions were selected on the basis of perceptual inference. In the second (fixed) condition, the animals used reinforcement from previous trials to select actions. Examination of neural activity showed that the representation of the selected action was stronger in lateral prefrontal cortex (lPFC), and occurred earlier in the lPFC than it did in the dorsal striatum (dSTR). In contrast to this, the representation of action values, in both the random and fixed conditions, was stronger in the dSTR. Thus, the dSTR contains an enriched representation of action value, but it followed frontal cortex in action selection.

Corticostriatal plasticity is necessary for learning intentional neuroprosthetic skills

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

Encoding of both positive and negative reward prediction errors by neurons of the primate lateral prefrontal cortex and caudate nucleus

Learning can be motivated by unanticipated success or unexpected failure. The former encourages us to repeat an action or activity, whereas the latter leads us to find an alternative strategy. Understanding the neural representation of these unexpected events is therefore critical to elucidate learning-related circuits. We examined the activity of neurons in the lateral prefrontal cortex (PFC) and caudate nucleus of monkeys as they performed a trial-and-error learning task. Unexpected outcomes were widely represented in both structures, and neurons driven by unexpectedly negative outcomes were as frequent as those activated by unexpectedly positive outcomes. Moreover, both positive and negative reward prediction errors (RPEs) were represented primarily by increases in firing rate, unlike the manner in which dopamine neurons have been observed to reflect these values. Interestingly, positive RPEs tended to appear with shorter latency than negative RPEs, perhaps reflecting the mechanism of their generation. Last, in the PFC but not the caudate, trial-by-trial variations in outcome-related activity were linked to the animals' subsequent behavioral decisions. More broadly, the robustness of RPE signaling by these neurons suggests that actor-critic models of reinforcement learning in which the PFC and particularly the caudate are considered primarily to be "actors" rather than "critics," should be reconsidered to include a prominent evaluative role for these structures.