The roles of the caudate nucleus in human classification learning

The role of visuospatial and verbal working memory in perceptual category learning

The role of verbal and visuospatial working memory in rule-based and information-integration category learning was examined. Previously, Maddox, Ashby, Ing, and Pickering found that a sequentially presented verbal working memory task did not affect information-integration learning, but disrupted rule-based learning when the rule was on the spatial frequency of a Gabor stimulus. This pattern was replicated in Experiment 1, in which the same category structures were used, but in which the verbal working memory task was replaced with a visuospatial analog. Experiment 2A examined rule-based learning on an oblique orientation and also found both verbal and visuospatial working memory tasks disrupting learning. Experiment 2B examined rule-based learning on a cardinal orientation and found a minimal effect of the verbal working memory task, but a large effect of the visuospatial working memory task. The conceptual significance of cardinal orientations and the role of visuospatial and verbal working memory in category learning are discussed.

The role of the orbitofrontal cortex in human discrimination learning

Several lines of evidence implicate the prefrontal cortex in learning but there is little evidence from studies of human lesion patients to demonstrate the critical role of this structure. To this end, we tested patients with lesions of the frontal lobe (n=36) and healthy controls (n=35) on two learning tasks: the weather prediction task (WPT), and an eight-pair concurrent visual discrimination task ('Choose'). Performance of both tasks was previously shown to be disrupted in patients with Parkinson's disease; the Choose deficit was only present when patients were medicated. Patients with damage to the orbitofrontal cortex (OFC) were significantly impaired on Choose, compared to both healthy controls and non-OFC lesion patients. The OFC lesion patients showed a mild deficit on the first 50 trials of the WPT, compared to the control subjects but not non-OFC lesion patients. The selective deficit in the OFC patients on Choose performance could not be attributed to the larger lesion size in this group, and the deficit was not correlated with the volume of damage to adjacent prefrontal subregions (e.g. anterior cingulate cortex). These data support the notion that the OFC play a role in normal discrimination learning, and suggest qualitative similarities in learning performance of patients with OFC damage and medicated PD patients.

Reinforcement learning signals in the human striatum distinguish learners from nonlearners during reward-based decision making

The computational framework of reinforcement learning has been used to forward our understanding of the neural mechanisms underlying reward learning and decision-making behavior. It is known that humans vary widely in their performance in decision-making tasks. Here, we used a simple four-armed bandit task in which subjects are almost evenly split into two groups on the basis of their performance: those who do learn to favor choice of the optimal action and those who do not. Using models of reinforcement learning we sought to determine the neural basis of these intrinsic differences in performance by scanning both groups with functional magnetic resonance imaging. We scanned 29 subjects while they performed the reward-based decision-making task. Our results suggest that these two groups differ markedly in the degree to which reinforcement learning signals in the striatum are engaged during task performance. While the learners showed robust prediction error signals in both the ventral and dorsal striatum during learning, the nonlearner group showed a marked absence of such signals. Moreover, the magnitude of prediction error signals in a region of dorsal striatum correlated significantly with a measure of behavioral performance across all subjects. These findings support a crucial role of prediction error signals, likely originating from dopaminergic midbrain neurons, in enabling learning of action selection preferences on the basis of obtained rewards. Thus, spontaneously observed individual differences in decision making performance demonstrate the suggested dependence of this type of learning on the functional integrity of the dopaminergic striatal system in humans.

Cognitive complexity effects in perceptual classification are dissociable

It has been proposed that a procedural-based classification system mediates the learning of information-integration categories, whereas a hypothesis-testing system mediates the learning of rule-based categories. Ashby, Ell and Waldron (2003) provided support for this claim by showing that a button switch introduced during classification transfer adversely affected information-integration but not rule-based performance. Nosofsky, Stanton and Zaki (2005) showed that increasing "cognitive complexity" can lead to button switch costs on rule-based performance. They argue that "cognitive complexity," and not the existence of separable classification systems, accounts for Ashby et al.'s empirical dissociation. The present study shows that experimental manipulations that increase "cognitive complexity" often have dissociable effects on information-integration and rule-based classification that are predicted a priori from the processing characteristics associated with the procedural-based and hypothesis-testing systems. These results suggest that manipulations of "cognitive complexity" can be dissociated, suggesting that "cognitive complexity" in not a unitary construct that affects a single psychological process.

Selective reinforcement learning deficits in schizophrenia support predictions from computational models of striatal-cortical dysfunction

BACKGROUND

Rewards and punishments may make distinct contributions to learning via separate striatal-cortical pathways. We investigated whether fronto-striatal dysfunction in schizophrenia (SZ) is characterized by selective impairment in either reward- (Go) or punishment-driven (NoGo) learning.

METHODS

We administered two versions of a probabilistic selection task to 40 schizophrenia patients and 31 control subjects, using difficult to verbalize stimuli (experiment 1) and nameable objects (experiment 2). In an acquisition phase, participants learned to choose between three different stimulus pairs (AB, CD, EF) presented in random order, based on probabilistic feedback (80%, 70%, 60%). We used analyses of variance (ANOVAs) to assess the effects of group and reinforcement probability on two measures of contingency learning. To characterize the preference of subjects for choosing the most rewarded stimulus and avoiding the most punished stimulus, we subsequently tested participants with novel pairs of stimuli involving either A or B, providing no feedback.

RESULTS

Control subjects demonstrated superior performance during the first 40 acquisition trials in each of the 80% and 70% conditions versus the 60% condition; patients showed similarly impaired (<60%) performance in all three conditions. In novel test pairs, patients showed decreased preference for the most rewarded stimulus (A; t = 2.674; p = .01). Patients were unimpaired at avoiding the most negative stimulus (B; t = .737).

CONCLUSIONS

The results of these experiments provide additional evidence for the presence of deficits in reinforcement learning in SZ, suggesting that reward-driven learning may be more profoundly impaired than punishment-driven learning.

How do the basal ganglia contribute to categorization? Their roles in generalization, response selection, and learning via feedback

This article examines how independent corticostriatal loops linking basal ganglia with cerebral cortex contribute to visual categorization. The first aspect of categorization discussed is the role of the visual corticostriatal loop, which connects the visual cortex and the body/tail of the caudate, in mapping visual stimuli to categories, including evaluating the degree to which this loop may generalize across individual category members. The second aspect of categorization discussed is the selection of appropriate actions or behaviors on the basis of category membership, and the role of the visual corticostriatal loop output and the motor corticostriatal loop, which connects motor planning areas with the putamen, in action selection. The third aspect of categorization discussed is how categories are learned with the aid of feedback linked dopaminergic projections to the basal ganglia. These projections underlie corticostriatal synaptic plasticity across the basal ganglia, and also serve as input to the executive and motivational corticostriatal loops that play a role in strategic use of feedback.

A review of medial temporal lobe and caudate contributions to visual category learning

Here we review recent functional neuroimaging, neuropsychological and behavioral studies examining the role of the medial temporal lobe (MTL) and the caudate in learning visual categories either by verbalizeable rules or without awareness. The MTL and caudate are found to play dissociable roles in different types of category learning with successful rule-based (RB) categorization depending selectively on the MTL and non-verbalizeable information-integration (II) category learning depending on the posterior caudate. These studies utilize a combination of experimental cognitive psychology, mathematical modeling (Decision Bound Theory (DBT)) and cognitive computational modeling (the COVIS model of Ashby et al. [1998. A neuropsychological theory of multiple systems in category learning. Psychological Review 105, 442-481]) to enhance the understanding of data obtained via functional magnetic resonance imaging (fMRI). The combination of approaches is used to both test hypotheses of the cognitive model and also to incorporate hypotheses about the strategies used by participants to direct analysis of fMRI data. Examination of the roles of the MTL and caudate in visual category learning holds the promise of bridging between abstract cognitive models of behavior, systems neuroscience, neuropsychology, and the underlying neurophysiology of these brain regions.

Basal ganglia and dopamine contributions to probabilistic category learning

Studies of the medial temporal lobe and basal ganglia memory systems have recently been extended towards understanding the neural systems contributing to category learning. The basal ganglia, in particular, have been linked to probabilistic category learning in humans. A separate parallel literature in systems neuroscience has emerged, indicating a role for the basal ganglia and related dopamine inputs in reward prediction and feedback processing. Here, we review behavioral, neuropsychological, functional neuroimaging, and computational studies of basal ganglia and dopamine contributions to learning in humans. Collectively, these studies implicate the basal ganglia in incremental, feedback-based learning that involves integrating information across multiple experiences. The medial temporal lobes, by contrast, contribute to rapid encoding of relations between stimuli and support flexible generalization of learning to novel contexts and stimuli. By breaking down our understanding of the cognitive and neural mechanisms contributing to different aspects of learning, recent studies are providing insight into how, and when, these different processes support learning, how they may interact with each other, and the consequence of different forms of learning for the representation of knowledge.

Interactive memory systems and category learning in schizophrenia

Schizophrenia is a devastating mental disorder with multiple facets, including the impairment of learning and memory. Recent evidence suggests that information is processed and represented by multiple interacting memory systems in the brain, including prefrontal cortex, basal ganglia, and medial temporal lobe. These structures are critical in the pathophysiology of schizophrenia. Whereas executive and declarative memory dysfunctions are well known in schizophrenia, habit learning deficits related to the basal ganglia are less clear, despite the fact that dopaminergic and other neurochemical processes in the basal ganglia may play a crucial role in the pathophysiology and pharmacology of schizophrenia. In this article, I propose that the investigation of different classification learning functions, including reward- and feedback-guided learning and acquired equivalence learning, may shed light on the neuropsychology, pathophysiology, pharmacology, and behavioral genetics of schizophrenia.

Imaging early practice effects in arithmetic

A better understanding of learning processes in arithmetic in healthy adults can guide research into learning disabilities such as dyscalculia. The goal of the present functional magnetic resonance imaging study was to investigate the ongoing process of learning itself. No training was provided prior to the scanning session. Training consisted in a higher frequency of repetition for one set of complex multiplication problems (repeated) and a lower frequency for the other set (novel). Repeated and novel problems were presented randomly in an event-related design. We observed activation decreases due to training in fronto-parietal areas and the caudate nucleus, and activation increases in temporo-parietal regions such as the left angular gyrus. Training effects became significant after approximately eight repetitions of a problem and remained stable over the course of the experiment. The change in brain activation patterns observed was similar to the results of previous neuroimaging studies investigating training effects in arithmetic after a week of extensive training. The paradigm employed seems to be a suitably sensitive tool to investigate and compare learning processes on group level for different populations. Furthermore, on a more general level, the early and robust changes in brain activation in healthy adults observed here indicate that repeating stimuli can profoundly and quickly affect fMRI results.

Probabilistic reversal learning impairments in schizophrenia: further evidence of orbitofrontal dysfunction

Impairments in feedback processing and reinforcement learning appear to be prominent aspects of schizophrenia (SZ), which may relate to symptoms of the disorder. Evidence from cognitive neuroscience investigations indicates that disparate brain systems may underlie different kinds of feedback-driven learning. The ability to rapidly shift response tendencies in the face of negative feedback, when reinforcement contingencies are reversed, is an important type of learning thought to depend on ventral prefrontal cortex (PFC). Schizophrenia has long been associated with dysfunction in dorsolateral areas of PFC, but evidence for ventral PFC impairment in more mixed. In order to assess whether SZ patients experience particular difficulty in carrying out a cognitive function commonly linked to ventral PFC function, we administered to 34 patients and 26 controls a modified version of an established probabilistic reversal learning task from the experimental literature [Cools, R., Clark, L., Owen, A.M., Robbins, T.W., 2002. Defining the neural mechanisms of probabilistic reversal learning using event-related functional magnetic resonance imaging. J. Neurosci. 22, 4563-4567]. Although SZ patients and controls performed similarly on the initial acquisition of probabilistic contingencies, patients showed substantial learning impairments when reinforcement contingencies were reversed, achieving significantly fewer reversals [chi(2)(6)=15.717, p=0.008]. Even when analyses were limited to subjects who acquired all probabilistic contingencies initially (22 patients and 20 controls), patients achieved significantly fewer reversals [chi(2)(3)=9.408, p=0.024]. These results support the idea that ventral PFC dysfunction is a prevalent aspect of schizophrenic pathophysiology, which may contribute to deficits in reinforcement learning exhibited by patients. Further studies are required to investigate the roles of dopaminergic systems in these impairments.

Risk and protective haplotypes of the alpha-synuclein gene associated with Parkinson's disease differentially affect cognitive sequence learning

Alpha-synuclein (SNCA) is a key factor in the regulation of dopaminergic transmission and is related to Parkinson's disease. In this study, we investigated the effects of risk and protective SNCA haplotypes associated with Parkinson's disease on cognitive sequence learning in 204 healthy volunteers. We found that the 3'-block risk SNCA haplotypes are associated with less effective stimulus-reward learning of sequences and with superior context representation of sequences. In contrast, participants with protective haplotypes exhibit better stimulus-reward learning and worse context representation, which suggest that these functions are inversely affected by risk and protective haplotypes. The Rep1 promoter polymorphism does not influence cognitive sequence learning. Because stimulus-reward learning may be mediated by the basal ganglia and context learning may be related to the medial temporal lobe, our data raise the possibility that dopaminergic signals regulated by SNCA inversely affect these memory systems.

Reward-Related Responses in the Human Striatum

Much of our knowledge of how reward information is processed in the brain comes from a rich animal literature. Recently, the advancement of neuroimaging techniques has allowed researchers to extend such investigations to the human brain. A common finding across species and methodologies is the involvement of the striatum, the input structure of the basal ganglia, in a circuit responsible for mediating goal-directed behavior. Central to this idea is the role of the striatum in the processing of affective stimuli, such as rewards and punishments. The goal of this article is to probe the human reward circuit, specifically the striatum and its subdivisions, with an emphasis on how the affective properties of outcomes or feedback influence the underlying neural activity and subsequent decision making. Discussion will first focus on anatomical and functional considerations regarding the striatum that have emerged from animal models. The rest of the article will center on how human neuroimaging studies map to findings from the animal literature, and how more recently, this research can be extended into the social and economic domains.

Dissociation between Striatal Regions while Learning to Categorize via Feedback and via Observation

Convergent evidence from functional imaging and from neuropsychological studies of basal ganglia disorders indicates that the striatum is involved in learning to categorize visual stimuli with feedback. However, it is unclear which cognitive process or processes involved in categorization is or are responsible for striatal recruitment; different regions of the striatum have been linked to feedback processing and to acquisition of stimulus-category associations. We examined the effect of the presence of feedback during learning on striatal recruitment by comparing feedback learning with observational learning of an information integration task. In the feedback task, participants were shown a stimulus, made a button press response, and then received feedback as to whether they had made the correct response. In the observational task, participants were given the category label before the stimulus appeared and then made a button press indicating the correct category membership. A region-of-interest analysis was used to examine activity in three regions of the striatum: the head of the caudate, body and tail of the caudate, and the putamen. Activity in the left head of the caudate was modulated by the presence of feedback: The magnitude of activation change was greater during feedback learning than during observational learning. In contrast, the bilateral body and tail of the caudate and the putamen were active to a similar degree in both feedback and observational learning. This pattern of results supports a functional dissociation between regions of the striatum, such that the head of the caudate is involved in feedback processing, whereas the body and tail of the caudate and the putamen are involved in learning stimulus-category associations. The hippocampus was active bilaterally during both feedback and observational learning, indicating potential parallel involvement with the striatum in information integration category learning.

Feedback-based versus observational classification learning in healthy aging and Parkinson's disease

Previous studies underline the role of dopamine in cognitive reinforcement learning. This has been demonstrated by a striatal involvement in feedback-based probabilistic classification learning. In order to determine to which extent the dopaminergic loss of Parkinson's disease and aging affects the feedback aspect in classification learning, we applied two versions of the same visual classification task. One version had to be learnt by trial-by-trial feedback, the other by observing the correct assignment of stimulus and category. Performance was evaluated in test blocks that were identical under the feedback and the observational conditions. There were 31 patients with Parkinson's disease (PD), 30 older controls and 20 younger controls tested. The results show that younger healthy participants perform better than older participants in the classification task and this difference significantly interacts with the learning condition: both groups show nearly the same level of performance under the observational condition but younger participants show a better performance than older ones under the feedback condition. In contrast, PD patients and older controls did not differ in their performance in the classification task; both groups performed better under the observational than under the feedback condition. These results demonstrate that healthy aging affects feedback-based learning but does not affect learning by observation. The fact that PD patients showed no additional deficit in feedback-based learning is an indication that the loss of dopamine does not play the key role under the feedback condition of our classification task. This finding questions the general role of the striatum in feedback-based learning and demonstrates that healthy aging particularly affects feedback-based learning.

Separate neural substrates for skill learning and performance in the ventral and dorsal striatum

It is widely accepted that the striatum of the basal ganglia is a primary substrate for the learning and performance of skills. We provide evidence that two regions of the rat striatum, ventral and dorsal, play distinct roles in instrumental conditioning (skill learning), with the ventral striatum being critical for learning and the dorsal striatum being important for performance but, notably, not for learning. This implies an actor (dorsal) versus director (ventral) division of labor, which is a new variant of the widely discussed actor-critic architecture. Our results also imply that the successful performance of a skill can ultimately result in its establishment as a habit outside the basal ganglia.

The striatum and probabilistic implicit sequence learning

The distinction between implicit (unconscious) and explicit (conscious) learning is controversial. Some argue that explicit learning is dependent on the medial temporal lobes, whereas implicit learning is mediated by the basal ganglia and others propose that all learning is explicit. The purpose of the present study was to investigate the involvement of the basal ganglia in implicit learning by examining learning of a probabilistic sequence of targets, in patients with Parkinson's disease (PD) and controls. Following learning, we assessed participants' awareness of the sequence structure by asking them to generate or withhold sequence consistent responses (process dissociation procedure) and to perform a recognition test in which measures of priming and recognition were obtained concurrently. Although the PD group demonstrated evidence of probabilistic sequence learning in this study, learning was significantly attenuated compared to controls. Residual learning in the PD group was genuinely implicit in nature because (a) PD patients were not able to control the expression of their acquired knowledge, and (b) their knowledge supported subsequent priming of sequence-consistent responses but recognition ratings were at chance. In contrast, following learning controls were capable of above chance recognition indicating that their sequential knowledge was acquired in a more explicit way. The results support the view that (i) the basal ganglia contribute to probabilistic implicit sequence learning (ii) that such learning can occur implicitly without explicit knowledge in PD patients.

Volume of left amygdala subregion predicted temperamental trait of harm avoidance in female young subjects. A voxel-based morphometry study

We investigated the relationship between temperamental predisposition and brain structure by using a standard questionnaire and high-resolution T1-weighted magnetic resonance image (MRI) in normal young volunteers. Fifty-six subjects completed the Japanese version of the Temperament and Character Inventory (TCI, 125 items) and underwent an MRI acquisition of the brain. The gray matter (GM) was extracted from the whole brain image of the subjects and normalized to the standard brain template using statistical parametric mapping and the optimized voxel-based morphometry (VBM) method. When the score on the harm avoidance (HA) subscale was used as a dependent variable, the multiple regression analysis revealed that the HA score positively correlated with the volume of the part of left amygdala. The region-of-interest analysis showed that the correlation was significant in the female subjects but not in the male subjects. The correlation was significant even after the effects of age, depression score, and total GM volume were taken into account. The differential correlation between the sexes may be caused by differences in hormonal condition and the vulnerability of women to socio-psychological stress. In addition, the novelty seeking (NS) score positively correlated with the GM of the left middle frontal gyrus. The volume of the tail of the right caudate nucleus positively correlated with the reward dependence (RD) score. With regard to the NS and RD scores, no significant sex difference was observed in the correlation. These results indicate that the temperamental traits measured using the questionnaire may have a morphological basis in the human brain.

When memory fails, intuition reigns: midazolam enhances implicit inference in humans

People often make logically sound decisions using explicit reasoning strategies, but sometimes it pays to rely on more implicit "gut-level" intuition. The transitive inference paradigm has been widely used as a test of explicit logical reasoning in animals and humans, but it can also be solved in a more implicit manner. Some researchers have argued that the hippocampus supports relational memories required for making logical inferences. Here we show that the benzodiazepene midazolam, which inactivates the hippocampus, causes profound explicit memory deficits in healthy participants, but enhances their ability in making implicit transitive inferences. These results are consistent with neurocomputational models of the basal ganglia-dopamine system that learn to make decisions through positive and negative reinforcement. We suggest that disengaging the hippocampal explicit memory system can be advantageous for this more implicit form of learning.

Perirhinal cortex activity during visual object discrimination: An event-related fMRI study

Previous fMRI studies have demonstrated preferential involvement of the perirhinal cortex and hippocampus in tasks of object and spatial memory, respectively. Here we investigated whether similar activity would also be present when object and spatial discrimination was assessed in the absence of explicit declarative memory demands. On each trial in the scanner, participants were presented simultaneously with two arrays of objects and were asked to indicate whether both arrays were identical, differed with respect to the identity of one object or differed with respect to the spatial arrangement of the objects. It was found that the detection of an object identity change was associated with significant right perirhinal cortex activity. We suggest that this perirhinal activity indicates a role of this structure in processes beyond declarative memory, for example, short-term visual working memory or higher order perception. Significantly greater hippocampal activity was not, however, observed during the spatial arrangement condition, perhaps due to the relatively low spatial processing demands of this task.

Stimulus modality interacts with category structure in perceptual category learning

Two experiments were conducted that examined information integration and rule-based category learning, using stimuli that contained auditory and visual information. The results suggest that it is easier to perceptually integrate information within these sensory modalities than across modalities. Conversely, it is easier to perform a disjunctive rule-based task when information comes from different sensory modalities, rather than from the same modality. Quantitative model-based analyses suggested that the information integration deficit for across-modality stimulus dimensions was due to an increase in the use of hypothesis-testing strategies to solve the task and to an increase in random responding. The modeling also suggested that the across-modality advantage for disjunctive, rule-based category learning was due to a greater reliance on disjunctive hypothesis-testing strategies, as opposed to unidimensional hypothesis-testing strategies and random responding.

Gender differences in the neural correlates of response inhibition during a stop signal task

We used functional magnetic resonance imaging to examine gender differences in the neural correlates of response inhibition during a stop signal task. The task has a frequent "go" signal to set up a pre-potent response tendency and a less frequent "stop" signal for subjects to withhold their response. A contrast in brain activation was made between successful and failed inhibitions for individual subjects. We compared 20 men and 20 women matched in age and years of education and in stop signal performance, with stop success rate, post-error slowing and task-related frustration ratings as covariates. The results showed greater activation in men, compared to women, in a wide array of cortical and subcortical areas, including the globus pallidus and motor thalamus during stop signal inhibition. In contrast, no brain regions demonstrated greater activation in women, even at a lower statistical threshold. Moreover, while men activated the medial superior frontal and anterior cingulate cortices, women activated the caudate tail to mediate response inhibition. These results extended gender differences in regional brain activation to response inhibition during a cognitive motor task. Men activated the motor circuitry while women appeared to involve visual association or habit learning during stop signal performance.

The basal ganglia in human learning

For many years, the basal ganglia were described in anatomy courses as strictly motor structures. Certainly, some of the most obvious and debilitating symptoms shown by persons with basal ganglia disorders are problems in motor control. However, the basal ganglia are not limited to motoric aspects of behavior: recent research shows that they are involved in most areas of cognitive and emotional functioning, consistent with their anatomical connections with all areas of the cortex. This review will focus on the roles of the basal ganglia in human learning, particularly sequence learning and category learning. Current areas of research that are discussed include the differing roles of different basal ganglia regions, patterns of interaction between the cortex and basal ganglia, differences in positive and negative association learning, effects of dopaminergic medication on learning, whether basal ganglia-mediated learning is implicit or explicit, and how the basal ganglia learning systems interact with other learning systems, particularly within the medial temporal lobe.

Performance feedback drives caudate activation in a phonological learning task

Adults have difficulty discriminating nonnative phonetic contrasts, but under certain circumstances training can lead to improvement in this ability. Despite the ubiquitous use of performance feedback in training paradigms in this and many other domains, the mechanisms by which feedback affects learning are not well understood. In this event-related functional magnetic resonance imaging study, we examined how performance feedback is processed during perceptual learning. Thirteen Japanese speakers for whom the English phonemes [r] and [l] were nondistinct performed an identification task of the words "road" and "load" that has been shown to be effective in inducing learning only when performance feedback is present. Each subject performed alternating runs of training with and without feedback, followed by performance of a card-guessing task with monetary reward and punishment outcomes. We found that the caudate nucleus was more robustly activated bilaterally when performing the perceptual identification task with feedback than without feedback, and the right caudate nucleus also showed a differential response to positive and negative feedback. Moreover, using a within-subjects design, we found that the caudate nucleus also showed a similar activation pattern to monetary reward and punishment outcomes in the card-guessing task. These results demonstrate that the caudate responds to positive and negative feedback during learning in a manner analogous to its processing of extrinsic affective reinforcers and indicate that this region may be a critical moderator of the influence of feedback on learning. These findings impact our broader understanding of the mechanisms underlying nondeclarative learning and language acquisition.

Neural correlates of artificial syntactic structure classification

The human brain supports acquisition mechanisms that extract structural regularities implicitly from experience without the induction of an explicit model. It has been argued that the capacity to generalize to new input is based on the acquisition of abstract representations, which reflect underlying structural regularities in the input ensemble. In this study, we explored the outcome of this acquisition mechanism, and to this end, we investigated the neural correlates of artificial syntactic classification using event-related functional magnetic resonance imaging. The participants engaged once a day during an 8-day period in a short-term memory acquisition task in which consonant-strings generated from an artificial grammar were presented in a sequential fashion without performance feedback. They performed reliably above chance on the grammaticality classification tasks on days 1 and 8 which correlated with a corticostriatal processing network, including frontal, cingulate, inferior parietal, and middle occipital/occipitotemporal regions as well as the caudate nucleus. Part of the left inferior frontal region (BA 45) was specifically related to syntactic violations and showed no sensitivity to local substring familiarity. In addition, the head of the caudate nucleus correlated positively with syntactic correctness on day 8 but not day 1, suggesting that this region contributes to an increase in cognitive processing fluency.

Differential hippocampal and prefrontal-striatal contributions to instance-based and rule-based learning

It is a topic of current interest whether learning in humans relies on the acquisition of abstract rule knowledge (rule-based learning) or whether it depends on superficial item-specific information (instance-based learning). Here, we identified brain regions that mediate either of the two learning mechanisms by combining fMRI with an experimental protocol shown to be able to dissociate both learning mechanisms. Subjects had to learn object-position conjunctions in several trials and blocks. In a learning condition, either objects (Experiment 1) or positions (Experiment 2) were held constant within-blocks. In contrast to a control condition in which object-position conjunctions were trial-unique, a performance increase within and across-blocks was observed in the learning condition of both experiments. We hypothesized that within-block learning mainly relies on instance-based processes, whereas across-block learning might depend on rule-based mechanisms. A within-block parametric fMRI analysis revealed a learning-related increase of lateral prefrontal and striatal activity and a learning-related decrease of hippocampal activity in both experiments. By contrast, across-block learning was associated with an activation modulation in distinct prefrontal-striatal brain regions, but not in the hippocampus. These data indicate that hippocampal and prefrontal-striatal brain regions differentially contribute to instance-based and rule-based learning.

Recognition memory is modulated by visual similarity

We used event-related fMRI to test whether recognition memory depends on visual similarity between familiar prototypes and novel exemplars. Subjects memorized portraits, landscapes, and abstract compositions by six painters with a unique style, and later performed a memory recognition task. The prototypes were presented with new exemplars that were either visually similar or dissimilar. Behaviorally, novel, dissimilar items were detected faster and more accurately. We found activation in a distributed cortical network that included face- and object-selective regions in the visual cortex, where familiar prototypes evoked stronger responses than new exemplars; attention-related regions in parietal cortex, where responses elicited by new exemplars were reduced with decreased similarity to the prototypes; and the hippocampus and memory-related regions in parietal and prefrontal cortices, where stronger responses were evoked by the dissimilar exemplars. Our findings suggest that recognition memory is mediated by classification of novel exemplars as a match or a mismatch, based on their visual similarity to familiar prototypes.

Theta and alpha oscillations reflect differences in memory strategy and visual discrimination performance in patients with Parkinson's disease

The aim of the present study was to investigate alterations in brain oscillatory activity during transient intentional encoding of abstract novel shapes in patients with Parkinson's disease (PD). Combined time-frequency analyses of alpha and theta power revealed a clear dissociation between PD patients (N=10) and age-matched healthy controls (N=10). PD patients used sub-optimal stimulus encoding strategies for subsequent maintenance and recall, whereas the controls mainly used categorization processes. In contrast to controls, PD patients showed significantly less theta increase and upper alpha suppression at frontal locations and significant laterality of early posterior theta and lower-2 alpha oscillations at right posterior locations. These findings suggest that the fronto-striatal circuits participate in visual categorization processes. Furthermore, theta and alpha oscillations appear to be involved in mediating the integration processes in mnemonic networks underlying visual categorization.

Towards an explicit account of implicit learning

PURPOSE OF REVIEW

The human brain supports acquisition mechanisms that can extract structural regularities implicitly from experience without the induction of an explicit model. Reber defined the process by which an individual comes to respond appropriately to the statistical structure of the input ensemble as implicit learning. He argued that the capacity to generalize to new input is based on the acquisition of abstract representations that reflect underlying structural regularities in the acquisition input. We focus this review of the implicit learning literature on studies published during 2004 and 2005. We will not review studies of repetition priming ('implicit memory'). Instead we focus on two commonly used experimental paradigms: the serial reaction time task and artificial grammar learning. Previous comprehensive reviews can be found in Seger's 1994 article and the Handbook of Implicit Learning.

RECENT FINDINGS

Emerging themes include the interaction between implicit and explicit processes, the role of the medial temporal lobe, developmental aspects of implicit learning, age-dependence, the role of sleep and consolidation.

SUMMARY

The attempts to characterize the interaction between implicit and explicit learning are promising although not well understood. The same can be said about the role of sleep and consolidation. Despite the fact that lesion studies have relatively consistently suggested that the medial temporal lobe memory system is not necessary for implicit learning, a number of functional magnetic resonance studies have reported medial temporal lobe activation in implicit learning. This issue merits further research. Finally, the clinical relevance of implicit learning remains to be determined.

Long-term test-retest reliability of functional MRI in a classification learning task

Functional MRI is widely used for imaging the neural correlates of psychological processes and how these brain processes change with learning, development and neuropsychiatric disorder. In order to interpret changes in imaging signals over time, for example, in patient studies, the long-term reliability of fMRI must first be established. Here, eight healthy adult subjects were scanned on two sessions, 1 year apart, while performing a classification learning task known to activate frontostriatal circuitry. We show that behavioral performance and frontostriatal activation were highly concordant at a group level at both time-points. Furthermore, intra-class correlation coefficients (ICCs), which index the degree of correlation between subjects at different time-points, were high for behavior and for functional activation. ICC was significantly higher within the network recruited by learning than outside that network. We conclude that fMRI can have high long-term test-retest reliability, making it suitable as a biomarker for brain development and neurodegeneration.

Neuroeconomics: an overview from an economic perspective

Until now, economic theory has not systematically integrated the influence of emotions on decision-making. Since evidence from neuroscience suggests that decision-making as hypothesized in economic theory depends on prior emotional processing, interdisciplinary research under the label of "neuroeconomics" arose. The key idea of this approach is to employ recent neuroscientific methods in order to analyze economically relevant brain processes. This paper aims to provide an overview of the current state of neuroeconomic research by giving a brief description of the concept of neuroeconomics, outlining methods commonly used and describing current studies in this new research area. Finally, some future prospects and limitations are discussed.