Learning arbitrary visuomotor associations: temporal dynamic of brain activity

The prefrontal cortex: from monkey to man

The prefrontal cortex is so important to human beings that, if deprived of it, our behaviour is reduced to action-reactions and automatisms, with no ability to make deliberate decisions. Why does the prefrontal cortex hold such importance in humans? In answer, this review draws on the proximity between humans and other primates, which enables us, through comparative anatomical-functional analysis, to understand the cognitive functions we have in common and specify those that distinguish humans from their closest cousins. First, a focus on the lateral region of the prefrontal cortex illustrates the existence of a continuum between rhesus monkeys (the most studied primates in neuroscience) and humans for most of the major cognitive functions in which this region of the brain plays a central role. This continuum involves the presence of elementary mental operations in the rhesus monkey (e.g. working memory or response inhibition) that are constitutive of 'macro-functions' such as planning, problem-solving and even language production. Second, the human prefrontal cortex has developed dramatically compared to that of other primates. This increase seems to concern the most anterior part (the frontopolar cortex). In humans, the development of the most anterior prefrontal cortex is associated with three major and interrelated cognitive changes: (i) a greater working memory capacity, allowing for greater integration of past experiences and prospective futures; (ii) a greater capacity to link discontinuous or distant data, whether temporal or semantic; and (iii) a greater capacity for abstraction, allowing humans to classify knowledge in different ways, to engage in analogical reasoning or to acquire abstract values that give rise to our beliefs and morals. Together, these new skills enable us, among other things, to develop highly sophisticated social interactions based on language, enabling us to conceive beliefs and moral judgements and to conceptualize, create and extend our vision of our environment beyond what we can physically grasp. Finally, a model of the transition of prefrontal functions between humans and non-human primates concludes this review.

Connectivity by the Frontal Aslant Tract (FAT) Explains Local Functional Specialization of the Superior and Inferior Frontal Gyri in Humans When Choosing Predictive over Reactive Strategies: A Tractography-Guided TMS Study

Predictive and reactive behaviors represent two mutually exclusive strategies in a sensorimotor task. Predictive behavior consists in internally estimating timing and features of a target stimulus and relies on a cortical medial frontal system [superior frontal gyrus (SFG)]. Reactive behavior consists in waiting for actual perception of the target stimulus and relies on the lateral frontal cortex [inferior frontal gyrus (IFG)]. We investigated whether SFG-IFG connections by the frontal aslant tract (FAT) can mediate predictive/reactive interactions. In 19 healthy human volunteers, we applied online transcranial magnetic stimulation (TMS) to six spots along the medial and lateral terminations of the FAT, during the set period of a delayed reaction task. Such scenario can be solved using either predictive or reactive strategies. TMS increased the propensity toward reactive behavior if applied to a specific portion of the IFG and increased predictive behavior when applied to a specific SFG spot. The two active spots in the SFG and IFG were directly connected by a sub-bundle of FAT fibers as indicated by diffusion-weighted imaging (DWI) tractography. Since FAT connectivity identifies two distant cortical nodes with opposite functions, we propose that the FAT mediates mutually inhibitory interactions between SFG and IFG to implement a "winner takes all" decisional process. We hypothesize such role of the FAT to be domain-general, whenever competition occurs between internal predictive and external reactive behaviors. Finally, we also show that anatomic connectivity is a powerful factor to explain and predict the spatial distribution of brain stimulation effects.SIGNIFICANCE STATEMENT We interact with sensory cues adopting two main mutually-exclusive strategies: (1) trying to anticipate the occurrence of the cue or (2) waiting for the GO-signal to be manifest and react to it. Here, we showed, by using noninvasive brain stimulation [transcranial magnetic stimulation (TMS)], that two specific cortical regions in the superior frontal gyrus (SFG) and the inferior frontal gyrus (IFG) have opposite roles in facilitating a predictive or a reactive strategy. Importantly these two very distant regions but with highly interconnected functions are specifically connected by a small white matter bundle, which mediates the direct competition and exclusiveness between predictive and reactive strategies. More generally, implementing anatomic connectivity in TMS studies strongly reduces spatial noise.

Learning without contingencies: A loss of synergy between memory and reward circuits in schizophrenia

Motivational deficits in schizophrenia may interact with foundational cognitive processes including learning and memory to induce impaired cognitive proficiency. If such a loss of synergy exists, it is likely to be underpinned by a loss of synchrony between the brains learning and reward sub-networks. Moreover, this loss should be observed even during tasks devoid of explicit reward contingencies given that such tasks are better models of real world performance than those with artificial contingencies. Here we applied undirected functional connectivity (uFC) analyses to fMRI data acquired while participants engaged in an associative learning task without contingencies or feedback. uFC was estimated and inter-group differences (between schizophrenia patients and controls, n = 54 total, n = 28 patients) were assessed within and between reward (VTA and NAcc) and learning/memory (Basal Ganglia, DPFC, Hippocampus, Parahippocampus, Occipital Lobe) sub-networks. The task paradigm itself alternated between Encoding, Consolidation, and Retrieval conditions, and uFC differences were quantified for each of the conditions. Significantly reduced uFC dominated the connectivity profiles of patients across all conditions. More pertinent to our motivations, these reductions were observed within and across classes of sub-networks (reward-related and learning/memory related). We suggest that disrupted functional connectivity between reward and learning sub-networks may drive many of the performance deficits that characterize schizophrenia. Thus, cognitive deficits in schizophrenia may in fact be underpinned by a loss of synergy between reward-sensitivity and cognitive processes.

A randomized pharmacological fMRI trial investigating D-cycloserine and brain plasticity mechanisms in learned pain responses

Learning and negative outcome expectations can increase pain sensitivity, a phenomenon known as nocebo hyperalgesia. Here, we examined how a targeted pharmacological manipulation of learning would impact nocebo responses and their brain correlates. Participants received either a placebo (n = 27) or a single 80 mg dose of D-cycloserine (a partial NMDA receptor agonist; n = 23) and underwent fMRI. Behavioral conditioning and negative suggestions were used to induce nocebo responses. Participants underwent pre-conditioning outside the scanner. During scanning, we first delivered baseline pain stimulations, followed by nocebo acquisition and extinction phases. During acquisition, high intensity thermal pain was paired with supposed activation of sham electrical stimuli (nocebo trials), whereas moderate pain was administered with inactive electrical stimulation (control trials). Nocebo hyperalgesia was induced in both groups (p < 0.001). Nocebo magnitudes and brain activations did not show significant differences between D-cycloserine and placebo. In acquisition and extinction, there were significantly increased activations bilaterally in the amygdala, ACC, and insula, during nocebo compared to control trials. Nocebo acquisition trials also showed increased vlPFC activation. Increased opercular activation differentiated nocebo-augmented pain aggravation from baseline pain. These results support the involvement of integrative cognitive-emotional processes in nocebo hyperalgesia.

Distinguishing transient from persistent tactile agnosia after partial anterior circulation infarcts - Behavioral and neuroimaging evidence for white matter disconnection

From a cohort of 36 patients presenting apperceptive tactile agnosia after first cortical ischemic stroke, 14 showed temporary impairment at admission. A previous multi-voxel analysis of the cortical lesions, using as explanatory variable the course of tactile object recognition performance over the recovery period of 9 months, partitioned the cohort into three subgroups. Of the 14 patients constituting two of the subgroups, 7 recovered from their impairment whereas 7 did not. These two subgroups could not be distinguished at admission. The primary aim of the present study is to present two assessments that can do so. The first assessment comprises a pattern of behavioral measures, determined via principal component analysis, encoded in three tests: picking small objects, macrogeometrical discrimination and tactile object recognition. The receiver operating characteristic curve derived from permutation of the behavioral test scores yielded an 80% probability of correct identification of the patient subgroup and an 8% probability for false identification. As done with the permuted scores, the pattern could predict the persistence of affliction of new stroke patients with tactile agnosia. The second predictive assessment extends our previous evaluation of cortical MRI lesion maps to include subcortical regions. Confirming our previous study, the lesions of the persistently impaired subgroup disrupted significantly the anterior arcuatus fasciculus and associated superior longitudinal fasciculus III in the ipsilesional hemisphere, impeding reciprocal information transfer between supramarginal gyrus and both the ventral premotor cortex and Brodmann area 44. Due to the importance of interhemispheric information transfer in tactile agnosia, we performed a supplementary analysis of tactile object recognition scores. It showed that haptic information transfer from the non-affected to the affected hands in the persistent cases partly restored function during the nine months, possibly following restoration of functional interhemispheric haptic information transfer at the border of posterior corpus callosum and splenium. In conclusion, the combined findings of the cortical lesion at subarea PFt of the inferior parietal lobule and the associated subcortical tract lesions permit almost perfect prediction of persistent impairment of tactile object recognition. The study substantiates the need for combined analysis of both cortical lesions and white matter tract disconnections.

The Effects of Subthalamic Nucleus Deep Brain Stimulation in Parkinson's Disease on Associative Learning of Verbal and Non-Verbal Information by Trial and Error or with Corrective Feedback

BACKGROUND

Parkinson's disease (PD) and subthalamic nucleus deep brain stimulation (STN-DBS) are both known to induce cognitive changes.

OBJECTIVE

The aim of our study was to investigate the impact of STN-DBS on two forms of conditional associative learning (CAL), trial and error or corrective feedback learning, which differed in difficulty to test the load-dependency hypothesis of the cognitive effects of STN-DBS in PD.

METHODS

We recruited two groups of PD patients, those who had STN-DBS surgery bilaterally (n = 24) and a second unoperated group (n = 9) who were assessed on two versions of a task of visual CAL involving either a more difficult trial and error learning or a relatively easier corrective feedback learning. Each task was completed twice by both groups, On and Off STN-DBS for the operated group and a first and second time by the unoperated group.

RESULTS

With STN-DBS Off, corrective feedback learning was superior to trial and error CAL, but not with STN-DBS On. The unoperated PD group had improved performance during the second assessment. To control for the improvement observed with repeated assessment in the PD control group, we split the STN-DBS group into two subgroups based on the condition of the first assessment (Off first vs. On first). While we found no STN-DBS effects for the Off first subgroup (N = 14), we observed improved performance during the second STN-DBS Off session for the On first subgroup (N = 10).

CONCLUSION

The findings suggest that in PD, STN-DBS interferes with use of corrective feedback and its integration in the conditional associative learning process. Also STN stimulation affected the ability of operated patients to resolve proactive interference during learning of the arbitrary visual associations by trial and error or with corrective feedback.

The Right Inferior Frontal Gyrus Plays an Important Role in Unconscious Information Processing: Activation Likelihood Estimation Analysis Based on Functional Magnetic Resonance Imaging

Unconsciousness is a kind of brain activity that occurs below the level of consciousness, and the masked priming paradigm is a classic paradigm to study unconscious perceptual processing. With the deepening of unconscious perception research, different researchers mostly use different experimental materials and different masked priming paradigms in a single experiment but not for the comprehensive analysis of the unconscious information processing mechanism itself. Thus, the purpose of this study is to conduct a comprehensive analysis through a cross-experimental paradigm, cross-experimental materials, and cross-experimental purposes. We used activation likelihood estimation to test functional magnetic resonance imaging studies, involving 361 subjects, 124 foci in eight studies representing direct comparison of unconscious processing with baseline, and 115 foci in 10 studies representing direct comparison of unconscious priming effects. In the comparison of unconscious processing and baseline, clusters formed in the left superior parietal gyrus, the right insular gyrus, and the right inferior frontal gyrus (IFG) triangular part after correcting for familywise error (FWE). In the comparison of priming effects, clusters formed in only the right IFG triangular part after correcting for FWE. Here, we found that ventral and dorsal pathways jointly regulate unconscious perceptual processes, but only the ventral pathway is involved in the regulation of unconscious priming effects. The IFG triangular part is involved in the regulation of unconscious perceptual processing and unconscious priming effects and may be an important brain area in unconscious information processing. These preliminary data provide conditions for further study of the neural correlation of unconscious information processing.

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.

Stimulating parietal regions of the multiple-demand cortex impairs novel vocabulary learning

Neuroimaging research demonstrated that the early stages of learning engage domain-general networks, non-specialist brain regions that process a wide variety of cognitive tasks. Those networks gradually disengage as learning progresses and learned information becomes processed in brain networks specialised for the specific function (e.g., language). In the current study, we used repetitive transcranial magnetic stimulation (rTMS) in the form of continuous theta burst stimulation (cTBS) to test whether stimulation of the bilateral parietal region of the domain-general network impairs learning new vocabulary, indicating its causal engagement in this process. Twenty participants, with no prior knowledge of Polish, learned Polish words for well-known objects across three training stages. The first training stage started with cTBS applied to either the experimental domain-general bilateral parietal site or the control bilateral precentral site. Immediately after cTBS, the vocabulary training commenced. A different set of words was learned for each site. Immediately after the training stage, participants performed a novel vocabulary test, designed to measure their knowledge of the new words and the effect of stimulation on learning. To measure stimulation effect when the words were more established in the mental lexicon, participants received additional training on the same words but without cTBS (second training stage) and then the full procedures from the first training stage were repeated (third training stage). Results demonstrated that stimulation impaired novel word learning when applied to the bilateral parietal site at the first stage of learning only. This effect was not present when newly learned words were used more proficiently in the third training stage, or at any learning stage during control site stimulation. Our results show that the bilateral parietal region of the domain-general network causally contributes to the successful learning of novel words.

Neural mechanisms of predicting individual preferences based on group membership

Successful social interaction requires humans to predict others’ behavior. To do so, internal models of others are generated based on previous observations. When predicting others’ preferences for objects, for example, observations are made at an individual level (5-year-old Rosie often chooses a pencil) or at a group level (kids often choose pencils). But previous research has focused either on already established group knowledge, i.e. stereotypes, or on the neural correlates of predicting traits and preferences of individuals. We identified the neural mechanisms underlying predicting individual behavior based on learned group knowledge using fMRI. We show that applying learned group knowledge hinges on both a network of regions commonly referred to as the mentalizing network, and a network of regions implicated in representing social knowledge. Additionally, we provide evidence for the presence of a gradient in the posterior temporal cortex and the medial frontal cortex, catering to different functions while applying learned group knowledge. This process is characterized by an increased connectivity between medial prefrontal cortex and other mentalizing network regions and increased connectivity between anterior temporal lobe and other social knowledge regions. Our study provides insights into the neural mechanisms underlying the application of learned group knowledge.

Neural Mechanisms of Observational Learning: A Neural Working Model

Humans and some animal species are able to learn stimulus-response (S-R) associations by observing others' behavior. It saves energy and time and avoids the danger of trying the wrong actions. Observational learning (OL) depends on the capability of mapping the actions of others into our own behaviors, processing outcomes, and combining this knowledge to serve our goals. Observational learning plays a central role in the learning of social skills, cultural knowledge, and tool use. Thus, it is one of the fundamental processes in which infants learn about and from adults (Byrne and Russon, 1998). In this paper, we review current methodological approaches employed in observational learning research. We highlight the important role of the prefrontal cortex and cognitive flexibility to support this learning process, develop a new neural working model of observational learning, illustrate how imitation relates to observational learning, and provide directions for future research.

Spatiotemporal Dynamics of Multiple Memory Systems During Category Learning

The brain utilizes distinct neural mechanisms that ease the transition through different stages of learning. Furthermore, evidence from category learning has shown that dissociable memory systems are engaged, depending on the structure of a task. This can even hold true for tasks that are very similar to each other, which complicates the process of classifying brain activity as relating to changes that are associated with learning or reflecting the engagement of a memory system suited for the task. The primary goals of these studies were to characterize the mechanisms that are associated with category learning and understand the extent to which different memory systems are recruited within a single task. Two studies providing spatial and temporal distinctions between learning-related changes in the brain and category-dependent memory systems are presented. The results from these experiments support the notion that exemplar memorization, rule-based, and perceptual similarity-based categorization are flexibly recruited in order to optimize performance during a single task. We conclude that these three methods, along with the memory systems they rely on, aid in the development of expertise, but their engagement might depend on the level of familiarity with a category.

Left Inferior Frontal Gyrus Participates in Mediating the Renewal Effect Irrespective of Context Salience

The renewal effect of extinction demonstrates the context-dependency of extinction learning. It is defined as the recovery of an extinguished response occurring when the contexts of extinction and recall differ. Behavioral studies showed that modulating context relevance can strengthen context-specific responses. In our fMRI study, we investigated to what extent a modulation of context salience can alter renewal levels and provide additional information about the neural basis for renewal. In a within-subjects design, participants completed two sessions of an associative learning task in randomized order. In the salient condition (SAL), a context was presented alone at the start of each trial, before being presented together with the stimulus. The regular condition (REG) contained no context-alone phase. In about one-third of participants (SWITCH), the context salience modulation significantly increased renewal rates in the SAL compared to the REG condition. The other participants showed either renewal (REN) or no renewal (NoREN) in both conditions. The modulation did not significantly affect learning performance during the initial forming of associations or extinction learning. In the SWITCH group, activation in left opercular inferior frontal gyrus (iFG) during the recall phase was associated with a renewal effect, together with activity in the bilateral posterior hippocampus and ventromedial prefrontal cortex (vmPFC). Also during the extinction phase, left opercular iFG activation was higher in groups exhibiting renewal in recall, irrespective of the context salience modulation. Besides confirming the participation of vmPFC in extinction recall, our findings provide novel insights regarding an as yet undetected, potentially important role for renewal-supporting processes in left iFG during extinction learning and recall, which are presumably based on the region's proposed function of evaluating competing response options under conditions of ambiguity.

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.

Neural representation of newly instructed rule identities during early implementation trials

By following explicit instructions, humans instantaneously get the hang of tasks they have never performed before. We used a specially calibrated multivariate analysis technique to uncover the elusive representational states during the first few implementations of arbitrary rules such as ‘for coffee, press red button’ following their first-time instruction. Distributed activity patterns within the ventrolateral prefrontal cortex (VLPFC) indicated the presence of neural representations specific of individual stimulus-response (S-R) rule identities, preferentially for conditions requiring the memorization of instructed S-R rules for correct performance. Identity-specific representations were detectable starting from the first implementation trial and continued to be present across early implementation trials. The increasingly fluent application of novel rule representations was channelled through increasing cooperation between VLPFC and anterior striatum. These findings inform representational theories on how the prefrontal cortex supports behavioral flexibility specifically by enabling the ad-hoc coding of newly instructed individual rule identities during their first-time implementation.

Probing cortical and sub-cortical contributions to instruction-based learning: Regional specialisation and global network dynamics

Diverse cortical networks and striatal brain regions are implicated in instruction-based learning (IBL); however, their distinct contributions remain unclear. We use a modified fMRI paradigm to test two hypotheses regarding the brain mechanisms that underlie IBL. One hypothesis proposes that anterior caudate and frontoparietal regions transiently co-activate when new rules are being bound in working memory. The other proposes that they mediate the application of the rules at different stages of the consolidation process. In accordance with the former hypothesis, we report strong activation peaks within and increased connectivity between anterior caudate and frontoparietal regions when rule-instruction slides are presented. However, similar effects occur throughout a broader set of cortical and sub-cortical regions, indicating a metabolically costly reconfiguration of the global brain state. The distinct functional roles of cingulo-opercular, frontoparietal and default-mode networks are apparent from their activation throughout, early and late in the practice phase respectively. Furthermore, there is tentative evidence of a peak in anterior caudate activity mid-way through the practice stage. These results demonstrate how performance of the same simple task involves a steadily shifting balance of brain systems as learning progresses. They also highlight the importance of distinguishing between regional specialisation and global dynamics when studying the network mechanisms that underlie cognition and learning.

Prefrontal mechanisms combining rewards and beliefs in human decision-making

In uncertain and changing environments, optimal decision-making requires integrating reward expectations with probabilistic beliefs about reward contingencies. Little is known, however, about how the prefrontal cortex (PFC), which subserves decision-making, combines these quantities. Here, using computational modelling and neuroimaging, we show that the ventromedial PFC encodes both reward expectations and proper beliefs about reward contingencies, while the dorsomedial PFC combines these quantities and guides choices that are at variance with those predicted by optimal decision theory: instead of integrating reward expectations with beliefs, the dorsomedial PFC built context-dependent reward expectations commensurable to beliefs and used these quantities as two concurrent appetitive components, driving choices. This neural mechanism accounts for well-known risk aversion effects in human decision-making. The results reveal that the irrationality of human choices commonly theorized as deriving from optimal computations over false beliefs, actually stems from suboptimal neural heuristics over rational beliefs about reward contingencies.

Optimal decision-making requires integrating expectations about rewards with beliefs about reward contingencies. Here, the authors show that these aspects of reward are encoded in the ventromedial prefrontal cortex then combined in the dorsomedial prefrontal cortex, a process that guides choice biases characteristic of human decision-making.

Cerebellar contributions to sequence prediction in verbal working memory

Verbal working memory is one of the most studied non-motor functions with robust cerebellar involvement. While the superior cerebellum (lobule VI) has been associated with articulatory control, the inferior cerebellum (lobule VIIIa) has been linked to phonological storage. The present study was aimed to elucidate the differential roles of these regions by investigating whether the cerebellum might contribute to verbal working memory via predictions based on sequence learning/detection. 19 healthy adult subjects completed an fMRI-based Sternberg task which included repeating and novel letter sequences that were phonologically similar or dissimilar. It was hypothesized that learning a repeating sequence of study letters would reduce phonological storage demand and associated right inferior cerebellar activations and that this effect would be modulated by phonological similarity of the study letters. Specifically, while increased phonological storage demand due to high phonological similarity was expected to be reflected in increased right inferior cerebellar activations for similar relative to dissimilar study letters, the reduction in activation for repeating relative to novel sequences was expected to be more profound for phonologically similar than for dissimilar study letters, especially at higher memory load. Results confirmed the typical effects of cognitive load (5 vs. 2 study letters) and phonological similarity in several cerebellar and neocortical brain regions as well as in behavioral data (accuracy and response time). Importantly, activations in superior and inferior cerebellar regions were differentially modulated as a function of similarity and sequence novelty, indicating that particularly lobule VIIIa may contribute to verbal working memory by generating predictions of letter sequences that reduce the likelihood of phonological loop failure before stored items need to be retrieved. The present study is consistent with other investigations that support prediction, which can be based on sequence learning or detection, as an overarching cerebellar function.

Modulation of associative learning in the hippocampal-striatal circuit based on item-set similarity

Mounting evidence suggests that the medial temporal lobe (MTL) and striatal learning systems support different forms of learning, which can be competitive or cooperative depending on task demands. We have previously shown how activity in these regions can be modulated in a conditional visuomotor associative learning task based on the consistency of response mappings or reward feedback (Mattfeld & Stark, 2015). Here, we examined the shift in learning towards the MTL and away from the striatum by placing strong demands on pattern separation, a process of orthogonalizing similar inputs into distinct representations. Mnemonically, pattern separation processes have been shown to rely heavily on processing in the hippocampus. Therefore, we predicted modulation of hippocampal activity by pattern separation demands, but no such modulation of striatal activity. Using a variant of the conditional visuomotor associative learning task that we have used previously, we presented participants with two blocked conditions: items with high and low perceptual overlap during functional magnetic resonance imaging (fMRI). As predicted, we observed learning-related activity in the hippocampus, which was greater in the high than the low overlap condition, particularly in the dentate gyrus. In contrast, the associative striatum also showed learning related activity, but it was not modulated by overlap condition. Using functional connectivity analyses, we showed that the correlation between the hippocampus and dentate gyrus with the associative striatum was differentially modulated by high vs. low overlap, suggesting that the coordination between these regions was affected when pattern separation demands were high. These findings contribute to a growing literature that suggests that the hippocampus and striatal network both contribute to the learning of arbitrary associations that are computationally distinct and can be altered by task demands.

Dynamics of error-related activity in deterministic learning - an EEG and fMRI study

There is a close relationship between progress in learning and the error-monitoring system. EEG and fMRI studies using probabilistic learning have revealed the distinct dynamics of this system after response and feedback, i.e. an increase of error-related and a decrease of feedback-related activity in the anterior cingulate cortex (ACC). Based on the existing theories, it can be presumed that during deterministic learning feedback-related activity in ACC would also increase. Since these assumptions have not yet been confirmed, it can be only speculated based on the data from the probabilistic paradigms how the information is being integrated within the ACC during deterministic learning. Here we implemented the Paired Associate Deterministic Learning task to the EEG and fMRI experiments. The analysis of EEG data showed a significant increase in the amplitude for both ERN and FN. Similarly, the fMRI results showed an increase in response-related and feedback-related activity of the ACC in erroneous trials. Our findings are in line with the current theories of ACC function: increasing ACC activity can be linked to the detected discrepancy between expected and obtained outcomes. We argue that expectancy violations in the course of deterministic learning are signalled by both, internal and external evaluation system.

Causal role of the inferolateral prefrontal cortex in balancing goal-directed and habitual control of behavior

Successful adaptation to complex environments depends on the balance of at least two systems: a flexible but slow goal-directed system encoding action-outcome associations and an efficient but rigid habitual system linking responses to preceding stimuli. Recent evidence suggests that the inferolateral prefrontal cortex (ilPFC), a region well known to contribute to cognitive control processes, may play a crucial role in the balance of goal-directed and habitual responding. This evidence, however, comes mainly from correlational data and whether the ilPFC is indeed causally involved in the goal-directed vs. habitual control of behavior is unclear. Here, we used neuro-navigated theta-burst stimulation (TBS) to either inhibit or enhance right ilPFC functionality before participants completed an instrumental learning task designed to probe goal-directed vs. habitual behavioral control. TBS did not affect overall learning performance. However, participants that had received inhibitory TBS were less able to adapt their behavior to altered task demands, indicating a shift from goal-directed towards more habitual control of behavior. Sham or excitatory TMS groups showed no such effect and were comparable in their performance to an unstimulated control group. Our findings indicate a causal role of the ilPFC in the balance of goal-directed vs. habitual control of behavior.

Within-Subject Correlation Analysis to Detect Functional Areas Associated With Response Inhibition

Functional areas in fMRI studies are often detected by brain-behavior correlation, calculating across-subject correlation between the behavioral index and the brain activity related to a function of interest. Within-subject correlation analysis is also employed in a single subject level, which utilizes cognitive fluctuations in a shorter time period by correlating the behavioral index with the brain activity across trials. In the present study, the within-subject analysis was applied to the stop-signal task, a standard task to probe response inhibition, where efficiency of response inhibition can be evaluated by the stop-signal reaction time (SSRT). Since the SSRT is estimated, by definition, not in a trial basis but from pooled trials, the correlation across runs was calculated between the SSRT and the brain activity related to response inhibition. The within-subject correlation revealed negative correlations in the anterior cingulate cortex and the cerebellum. Moreover, the dissociation pattern was observed in the within-subject analysis when earlier vs. later parts of the runs were analyzed: negative correlation was dominant in earlier runs, whereas positive correlation was dominant in later runs. Regions of interest analyses revealed that the negative correlation in the anterior cingulate cortex, but not in the cerebellum, was dominant in earlier runs, suggesting multiple mechanisms associated with inhibitory processes that fluctuate on a run-by-run basis. These results indicate that the within-subject analysis compliments the across-subject analysis by highlighting different aspects of cognitive/affective processes related to response inhibition.

Striking a chord with healthy aging: memory system cooperation is related to preserved configural response learning in older adults

Evidence from tasks that primarily tap either hippocampal- or striatal-based memory systems suggests that although these systems often compete for control of behavior, aging is associated with greater cooperation between them. This may stem from altered prefrontal cortex function. Here, we use a configural response task designed to engage both memory systems to test how age affects their interaction with cortical regions including the prefrontal cortex. We found that although older and younger adults learned just as well, older adults showed greater initial activation in cortical networks associated with visuospatial-action mapping and resolving conflict for competing memory representations. Older adults also showed greater functional coupling of the striatum with the left inferior frontal gyrus, in parallel with similar hippocampal coupling to ventral visual regions as young adults. Overall, our results support the proposal that aging is associated with more cooperative memory systems, but we did not find that greater cooperation is associated with less interaction between the prefrontal cortex and core memory system structures during learning.

When global rule reversal meets local task switching: The neural mechanisms of coordinated behavioral adaptation to instructed multi-level demand changes

Cognitive flexibility is essential to cope with changing task demands and often it is necessary to adapt to combined changes in a coordinated manner. The present fMRI study examined how the brain implements such multi-level adaptation processes. Specifically, on a "local," hierarchically lower level, switching between two tasks was required across trials while the rules of each task remained unchanged for blocks of trials. On a "global" level regarding blocks of twelve trials, the task rules could reverse or remain the same. The current task was cued at the start of each trial while the current task rules were instructed before the start of a new block. We found that partly overlapping and partly segregated neural networks play different roles when coping with the combination of global rule reversal and local task switching. The fronto-parietal control network (FPN) supported the encoding of reversed rules at the time of explicit rule instruction. The same regions subsequently supported local task switching processes during actual implementation trials, irrespective of rule reversal condition. By contrast, a cortico-striatal network (CSN) including supplementary motor area and putamen was increasingly engaged across implementation trials and more so for rule reversal than for nonreversal blocks, irrespective of task switching condition. Together, these findings suggest that the brain accomplishes the coordinated adaptation to multi-level demand changes by distributing processing resources either across time (FPN for reversed rule encoding and later for task switching) or across regions (CSN for reversed rule implementation and FPN for concurrent task switching).

Stimulating Multiple-Demand Cortex Enhances Vocabulary Learning

It is well established that networks within multiple-demand cortex (MDC) become active when diverse skills and behaviors are being learnt. However, their causal role in learning remains to be established. In the present study, we first performed functional magnetic resonance imaging on healthy female and male human participants to confirm that MDC was most active in the initial stages of learning a novel vocabulary, consisting of pronounceable nonwords (pseudowords), each associated with a picture of a real object. We then examined, in healthy female and male human participants, whether repetitive transcranial magnetic stimulation of a frontal midline node of the cingulo-opercular MDC affected learning rates specifically during the initial stages of learning. We report that stimulation of this node, but not a control brain region, substantially improved both accuracy and response times during the earliest stage of learning pseudoword–object associations. This stimulation had no effect on the processing of established vocabulary, tested by the accuracy and response times when participants decided whether a real word was accurately paired with a picture of an object. These results provide evidence that noninvasive stimulation to MDC nodes can enhance learning rates, thereby demonstrating their causal role in the learning process. We propose that this causal role makes MDC candidate target for experimental therapeutics; for example, in stroke patients with aphasia attempting to reacquire a vocabulary.

SIGNIFICANCE STATEMENT Learning a task involves the brain system within which that specific task becomes established. Therefore, successfully learning a new vocabulary establishes the novel words in the language system. However, there is evidence that in the early stages of learning, networks within multiple-demand cortex (MDC), which control higher cognitive functions, such as working memory, attention, and monitoring of performance, become active. This activity declines once the task is learnt. The present study demonstrated that a node within MDC, located in midline frontal cortex, becomes active during the early stage of learning a novel vocabulary. Importantly, noninvasive brain stimulation of this node improved performance during this stage of learning. This observation demonstrated that MDC activity is important for learning.

Are individuals with higher psychopathic traits better learners at lying? Behavioural and neural evidence

High psychopathy is characterized by untruthfulness and manipulativeness. However, existing evidence on higher propensity or capacity to lie among non-incarcerated high-psychopathic individuals is equivocal. Of particular importance, no research has investigated whether greater psychopathic tendency is associated with better 'trainability' of lying. An understanding of whether the neurobehavioral processes of lying are modifiable through practice offers significant theoretical and practical implications. By employing a longitudinal design involving university students with varying degrees of psychopathic traits, we successfully demonstrate that the performance speed of lying about face familiarity significantly improved following two sessions of practice, which occurred only among those with higher, but not lower, levels of psychopathic traits. Furthermore, this behavioural improvement associated with higher psychopathic tendency was predicted by a reduction in lying-related neural signals and by functional connectivity changes in the frontoparietal and cerebellum networks. Our findings provide novel and pivotal evidence suggesting that psychopathic traits are the key modulating factors of the plasticity of both behavioural and neural processes underpinning lying. These findings broadly support conceptualization of high-functioning individuals with higher psychopathic traits as having preserved, or arguably superior, functioning in neural networks implicated in cognitive executive processing, but deficiencies in affective neural processes, from a neuroplasticity perspective.

Domain-general subregions of the medial prefrontal cortex contribute to recovery of language after stroke

We hypothesized that the recovery of speech production after left hemisphere stroke not only depends on the integrity of language-specialized brain systems, but also on 'domain-general' brain systems that have much broader functional roles. The presupplementary motor area/dorsal anterior cingulate forms part of the cingular-opercular network, which has a broad role in cognition and learning. Consequently, we have previously suggested that variability in the recovery of speech production after aphasic stroke may relate in part to differences in patients' abilities to engage this domain-general brain region. To test our hypothesis, 27 patients (aged 59 ± 11 years) with a left hemisphere stroke performed behavioural assessments and event-related functional magnetic resonance imaging tasks at two time points; first in the early phase (∼2 weeks) and then ∼4 months after the ictus. The functional magnetic resonance imaging tasks were designed to differentiate between activation related to language production (sentential overt speech production-Speech task) and activation related to cognitive processing (non-verbal decision making). Simple rest and counting conditions were also included in the design. Task-evoked regional brain activations during the early and late phases were compared with a longitudinal measure of recovery of language production. In accordance with a role in cognitive processing, substantial activity was observed within the presupplementary motor area/dorsal anterior cingulate during the decision-making task. Critically, the level of activation within this region during speech production correlated positively with the longitudinal recovery of speech production across the two time points (as measured by the in-scanner performance in the Speech task). This relationship was observed for activation in both the early phase (r = 0.363, P = 0.03 one-tailed) and the late phase (r = 0.538, P = 0.004). Furthermore, presupplementary motor area/dorsal anterior cingulate activity was a predictor of both language recovery over time and language outcome at ∼4 months, over and above that predicted by lesion volume, age and the initial language impairment (general linear model overall significant at P < 0.0001; ExpB 1.01, P = 0.02). The particularly prominent relationship of the presupplementary motor area/dorsal anterior cingulate region with recovery of language was confirmed in voxel-wise correlation analysis, conducted unconstrained for the whole brain volume. These results accord with the hypothesis that the functionality of the presupplementary motor area/dorsal anterior cingulate contributes to language recovery after stroke. Given that this brain region is often spared in aphasic stroke, we propose that it is a sensible target for future research into rehabilitative treatments. More broadly, baseline assessment of domain-general systems could help provide a better prediction of language recovery.

I Don't Want to Miss a Thing - Learning Dynamics and Effects of Feedback Type and Monetary Incentive in a Paired Associate Deterministic Learning Task

Effective functioning in a complex environment requires adjusting of behavior according to changing situational demands. To do so, organisms must learn new, more adaptive behaviors by extracting the necessary information from externally provided feedback. Not surprisingly, feedback-guided learning has been extensively studied using multiple research paradigms. The purpose of the present study was to test the newly designed Paired Associate Deterministic Learning task (PADL), in which participants were presented with either positive or negative deterministic feedback. Moreover, we manipulated the level of motivation in the learning process by comparing blocks with strictly cognitive, informative feedback to blocks where participants were additionally motivated by anticipated monetary reward or loss. Our results proved the PADL to be a useful tool not only for studying the learning process in a deterministic environment, but also, due to the varying task conditions, for assessing differences in learning patterns. Particularly, we show that the learning process itself is influenced by manipulating both the type of feedback information and the motivational significance associated with the expected monetary reward.

Relative cortico-subcortical shift in brain activity but preserved training-induced neural modulation in older adults during bimanual motor learning

To study age-related differences in neural activation during motor learning, functional magnetic resonance imaging scans were acquired from 25 young (mean 21.5-year old) and 18 older adults (mean 68.6-year old) while performing a bimanual coordination task before (pretest) and after (posttest) a 2-week training intervention on the task. We studied whether task-related brain activity and training-induced brain activation changes differed between age groups, particularly with respect to the hyperactivation typically observed in older adults. Findings revealed that older adults showed lower performance levels than younger adults but similar learning capability. At the cerebral level, the task-related hyperactivation in parietofrontal areas and underactivation in subcortical areas observed in older adults were not differentially modulated by the training intervention. However, brain activity related to task planning and execution decreased from pretest to posttest in temporo-parieto-frontal areas and subcortical areas in both age groups, suggesting similar processes of enhanced activation efficiency with advanced skill level. Furthermore, older adults who displayed higher activity in prefrontal regions at pretest demonstrated larger training-induced performance gains. In conclusion, in spite of prominent age-related brain activation differences during movement planning and execution, the mechanisms of learning-related reduction of brain activation appear to be similar in both groups. Importantly, cerebral activity during early learning can differentially predict the amplitude of the training-induced performance benefit between young and older adults.

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.

Insights into Seeing and Grasping: Distinguishing the Neural Correlates of Perception and Action

Vision contributes to both perception and visuomotor control, and it has been suggested that many higher brain structures specialize in one or the other function. An alternative view, presented here, is that most higher brain areas participate in both visuomotor and perceptual functions. In the anterior frontal cortex, for example, the activity of one population of neurons reflects perceptual reports about a visual stimulus, whereas the activity of an intermingled population reflects movements aimed at the same stimulus. Similarly, posterior parietal and inferior temporal areas appear to function in both visual perception and visuomotor control. Visuomotor signals in higher order cortical areas could contribute to the perception of one’s own action. They also might reflect the existence of two systems for visual information processing: one stressing accuracy for the control of movement and the other generating hypotheses about the world.

Addiction History Associates with the Propensity to Form Habits

Learned habitual responses to environmental stimuli allow efficient interaction with the environment, freeing cognitive resources for more demanding tasks. However, when the outcome of such actions is no longer a desired goal, established stimulus-response (S-R) associations or habits must be overcome. Among people with substance use disorders (SUDs), difficulty in overcoming habitual responses to stimuli associated with their addiction in favor of new, goal-directed behaviors contributes to relapse. Animal models of habit learning demonstrate that chronic self-administration of drugs of abuse promotes habitual responding beyond the domain of compulsive drug seeking. However, whether a similar propensity toward domain-general habitual responding occurs in humans with SUDs has remained unclear. To address this question, we used a visuomotor S-R learning and relearning task, the Hidden Association between Images Task, which employs abstract visual stimuli and manual responses. This task allows us to measure new S-R association learning and well-learned S-R association execution and includes a response contingency change manipulation to quantify the degree to which responding is habit-based, rather than goal-directed. We find that people with SUDs learn new S-R associations as well as healthy control participants do. Moreover, people with an SUD history slightly outperform controls in S-R execution. In contrast, people with SUDs are specifically impaired in overcoming well-learned S-R associations; those with SUDs make a significantly greater proportion of perseverative errors during well-learned S-R replacement, indicating the more habitual nature of their responses. Thus, with equivalent training and practice, people with SUDs appear to show enhanced domain-general habit formation.

Translational Research on Habit and Alcohol

Habitual actions enable efficient daily living, but they can also contribute to pathological behaviors that resistant change, such as alcoholism. Habitual behaviors are learned actions that appear goal-directed but are in fact no longer under the control of the action's outcome. Instead, these actions are triggered by stimuli, which may be exogenous or interoceptive, discrete or contextual. A major hallmark characteristic of alcoholism is continued alcohol use despite serious negative consequences. In essence, although the outcome of alcohol seeking and drinking is dramatically devalued, these actions persist, often triggered by environmental cues associated with alcohol use. Thus, alcoholism meets the definition of an initially goal-directed behavior that converts to a habit-based process. Habit and alcohol have been well investigated in rodent models, with comparatively less research in non-human primates and people. This review focuses on translational research on habit and alcohol with an emphasis on cross-species methodology and neural circuitry.

Network mechanisms of intentional learning

The ability to learn new tasks rapidly is a prominent characteristic of human behaviour. This ability relies on flexible cognitive systems that adapt in order to encode temporary programs for processing non-automated tasks. Previous functional imaging studies have revealed distinct roles for the lateral frontal cortices (LFCs) and the ventral striatum in intentional learning processes. However, the human LFCs are complex; they house multiple distinct sub-regions, each of which co-activates with a different functional network. It remains unclear how these LFC networks differ in their functions and how they coordinate with each other, and the ventral striatum, to support intentional learning. Here, we apply a suite of fMRI connectivity methods to determine how LFC networks activate and interact at different stages of two novel tasks, in which arbitrary stimulus-response rules are learnt either from explicit instruction or by trial-and-error. We report that the networks activate en masse and in synchrony when novel rules are being learnt from instruction. However, these networks are not homogeneous in their functions; instead, the directed connectivities between them vary asymmetrically across the learning timecourse and they disengage from the task sequentially along a rostro-caudal axis. Furthermore, when negative feedback indicates the need to switch to alternative stimulus–response rules, there is additional input to the LFC networks from the ventral striatum. These results support the hypotheses that LFC networks interact as a hierarchical system during intentional learning and that signals from the ventral striatum have a driving influence on this system when the internal program for processing the task is updated.

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We examine lateral frontal cortex (LFC) network dynamics across the learning process.

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LFC networks activate en masse and in synchrony when learning from instruction.

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Directed connectivities between LFC regions vary asymmetrically and hierarchically.

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LFC networks sequentially disengage from the task along an anterior–posterior axis.

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Corticostriatal circuits are selectively engaged during trial-and-error learning.

Distinct contributions of lateral orbito-frontal cortex, striatum, and fronto-parietal network regions for rule encoding and control of memory-based implementation during instructed reversal learning

A key element of behavioral flexibility is to quickly learn to modify or reverse previously acquired stimulus-response associations. Such reversal learning (RL) can either be driven by feedback or by explicit instruction, informing either retrospectively or prospectively about the changed response requirements. Neuroimaging studies have thus far exclusively focused either on feedback-driven RL or on instructed initial learning of novel rules. The present study examined the neural basis of instructed RL as compared to instructed initial learning, separately assessing reversal-related instruction-based encoding processes and reversal-related control processes required for implementing reversed rules under competition from the initially learned rules. We found that instructed RL is partly supported by similar regions as feedback-driven RL, including lateral orbitofrontal cortex (lOFC) and anterior dorsal caudate. Encoding-related activation in both regions determined resilience against response competition during subsequent memory-based reversal implementation. Different from feedback-driven RL, instruction-based RL relied heavily on the generic fronto-parietal cognitive control network--not for encoding but for reversal-related control processes during memory-based implementation. These findings are consistent with a model of partly decoupled, yet interacting, systems of (i) symbolic rule representations that are instantaneously updated upon instruction and (ii) pragmatic representations of reward-associated S-R links mediating the enduring competition from initially learned rules.

The Association Between Eye Movements and Cerebellar Activation in a Verbal Working Memory Task

It has been argued that cerebellar activations during cognitive tasks may masquerade as cognition, while actually reflecting processes related to movement planning or motor learning. The present study investigated whether the cerebellar load effect for verbal working memory, that is, increased activations in lobule VI/Crus I and lobule VIIB/VIIIA, is related to eye movements and oculomotor processing. Fifteen participants performed an fMRI-based Sternberg verbal working memory task. Oculomotor and cognitive task demands were manipulated by using closely and widely spaced stimuli, and high and low cognitive load. Trial-based quantitative eye movement parameters were obtained from concurrent eye tracking. Conventional MRI analysis replicated the cerebellar load effect in lobules VI and VIIB/VIIIa. With quantitative eye movement parameters as regressors, analysis yielded very similar activation patterns. While load effect and eye regressor generally recruited spatially distinct neocortical and cerebellar regions, conjunction analysis showed that a small subset of prefrontal areas implicated in the load effect also responded to the eye regressor. The present results indicate that cognitive load-dependent activations in lateral superior and posteroinferior cerebellar regions in the Sternberg task are independent of eye movements occurring during stimulus encoding. This is inconsistent with the notion that cognitive load-dependent cerebellar activations merely reflect oculomotor processing.

Contrasting network and modular perspectives on inhibitory control

A prominent theory proposes that the right inferior frontal cortex of the human brain houses a dedicated region for motor response inhibition. However, there is growing evidence to support the view that this inhibitory control hypothesis is incorrect. Here, we discuss evidence in favour of our alternative hypothesis, which states that response inhibition is one example of a broader class of control processes that are supported by the same set of frontoparietal networks. These domain-general networks exert control by modulating local lateral inhibition processes, which occur ubiquitously throughout the cortex. We propose that to fully understand the neural basis of behavioural control requires a more holistic approach that considers how common network mechanisms support diverse cognitive processes.

The Neural Signature of Subliminal Visuomotor Priming: Brain Activity and Functional Connectivity Profiles

Unconscious visuomotor priming defined as the advantage in reaction time (RT) or accuracy for target shapes mapped to the same (congruent condition) when compared with a different (incongruent condition) motor response as a preceding subliminally presented prime shape has been shown to modulate activity within a visuomotor network comprised of parietal and frontal motor areas in previous functional magnetic resonance imaging (fMRI) studies. The present fMRI study investigated whether, in addition to changes in brain activity, unconscious visuomotor priming results in a modulation of functional connectivity profiles. Activity associated with congruent compared with incongruent trials was lower in the bilateral inferior and medial superior frontal gyri, in the inferior parietal lobules, and in the right caudate nucleus and adjacent portions of the thalamus. Functional connectivity increased under congruent relative to incongruent conditions between ventral visual stream areas (e.g., calcarine, fusiform, and lingual gyri), the precentral gyrus, the supplementary motor area, posterior parietal areas, the inferior frontal gyrus, and the caudate nucleus. Our findings suggest that an increase in coupling between visuomotor regions, reflecting higher efficiency of processing, is an important neural mechanism underlying unconscious visuomotor priming, in addition to changes in the magnitude of activation.

Functional contributions and interactions between the human hippocampus and subregions of the striatum during arbitrary associative learning and memory

The hippocampus and striatum are thought to have different functional roles in learning and memory. It is unknown under what experimental conditions their contributions are dissimilar or converge, and the extent to which they interact over the course of learning. In order to evaluate both the functional contributions of as well as the interactions between the human hippocampus and striatum, the present study used high-resolution functional magnetic resonance imaging (fMRI) and variations of a conditional visuomotor associative learning task that either taxed arbitrary associative learning (Experiment 1) or stimulus-response learning (Experiment 2). In the first experiment, we observed changes in activity in the hippocampus and anterior caudate that reflect differences between the two regions consistent with distinct computational principles. In the second experiment, we observed activity in the putamen that reflected content specific representations during the learning of arbitrary conditional visuomotor associations. In both experiments, the hippocampus and ventral striatum demonstrated dynamic functional coupling during the learning of new arbitrary associations, but not during retrieval of well-learned arbitrary associations using control variants of the tasks that did not preferentially tax one system versus the other. These findings suggest that both the hippocampus and subregions of the dorsal striatum contribute uniquely to the learning of arbitrary associations while the hippocampus and ventral striatum interact over the course of learning.

Using action understanding to understand the left inferior parietal cortex in the human brain

Humans have a sophisticated knowledge of the actions that can be performed with objects. In an fMRI study we tried to establish whether this depends on areas that are homologous with the inferior parietal cortex (area PFG) in macaque monkeys. Cells have been described in area PFG that discharge differentially depending upon whether the observer sees an object being brought to the mouth or put in a container. In our study the observers saw videos in which the use of different objects was demonstrated in pantomime; and after viewing the videos, the subject had to pick the object that was appropriate to the pantomime. We found a cluster of activated voxels in parietal areas PFop and PFt and this cluster was greater in the left hemisphere than in the right. We suggest a mechanism that could account for this asymmetry, relate our results to handedness and suggest that they shed light on the human syndrome of apraxia. Finally, we suggest that during the evolution of the hominids, this same pantomime mechanism could have been used to 'name' or request objects.

Grey matter volumetric changes related to recovery from hand paresis after cortical sensorimotor stroke

Preclinical studies using animal models have shown that grey matter plasticity in both perilesional and distant neural networks contributes to behavioural recovery of sensorimotor functions after ischaemic cortical stroke. Whether such morphological changes can be detected after human cortical stroke is not yet known, but this would be essential to better understand post-stroke brain architecture and its impact on recovery. Using serial behavioural and high-resolution magnetic resonance imaging (MRI) measurements, we tracked recovery of dexterous hand function in 28 patients with ischaemic stroke involving the primary sensorimotor cortices. We were able to classify three recovery subgroups (fast, slow, and poor) using response feature analysis of individual recovery curves. To detect areas with significant longitudinal grey matter volume (GMV) change, we performed tensor-based morphometry of MRI data acquired in the subacute phase, i.e. after the stage compromised by acute oedema and inflammation. We found significant GMV expansion in the perilesional premotor cortex, ipsilesional mediodorsal thalamus, and caudate nucleus, and GMV contraction in the contralesional cerebellum. According to an interaction model, patients with fast recovery had more perilesional than subcortical expansion, whereas the contrary was true for patients with impaired recovery. Also, there were significant voxel-wise correlations between motor performance and ipsilesional GMV contraction in the posterior parietal lobes and expansion in dorsolateral prefrontal cortex. In sum, perilesional GMV expansion is associated with successful recovery after cortical stroke, possibly reflecting the restructuring of local cortical networks. Distant changes within the prefrontal-striato-thalamic network are related to impaired recovery, probably indicating higher demands on cognitive control of motor behaviour.

The lateral prefrontal cortex and complex value-based learning and decision making

Tremendous progress has been made in discerning the neurocognitive basis of value-based decision making and learning. Although the majority of studies to date have employed simple task paradigms, recent work has started to examine more complex aspects of value processing including: the value of engaging rule-based cognitive control; the integration of multiple pieces of information (e.g., reward magnitude and delay) to discern the best course of action; pursuing future rewards; valuation of abstract concepts (e.g., fairness); and comparing the value of executed versus imagined alternative actions. We provide a comprehensive review of functional neuroimaging, electrophysiological, and lesion evidence suggesting that the lateral prefrontal cortex (LPFC) plays a critical role in these complex aspects of value processing. In particular, we focus on the specific information that the LPFC represents, and argue that it includes both cognitive and value-based information. We also discuss how the role of the LPFC is distinct from other value-related regions. Finally, we articulate a framework for understanding the contribution of subregions along the rostro-caudal axis of the LPFC, and thereby bridge the cognitive control and decision making literatures.

The nucleus accumbens as a nexus between values and goals in goal-directed behavior: a review and a new hypothesis

Goal-directed behavior is a fundamental means by which animals can flexibly solve the challenges posed by variable external and internal conditions. Recently, the processes and brain mechanisms underlying such behavior have been extensively studied from behavioral, neuroscientific and computational perspectives. This research has highlighted the processes underlying goal-directed behavior and associated brain systems including prefrontal cortex, basal ganglia and, in particular therein, the nucleus accumbens (NAcc). This paper focusses on one particular process at the core of goal-directed behavior: how motivational value is assigned to goals on the basis of internal states and environmental stimuli, and how this supports goal selection processes. Various biological and computational accounts have been given of this problem and of related multiple neural and behavior phenomena, but we still lack an integrated hypothesis on the generation and use of value for goal selection. This paper proposes an hypothesis that aims to solve this problem and is based on this key elements: (a) amygdala and hippocampus establish the motivational value of stimuli and goals; (b) prefrontal cortex encodes various types of action outcomes; (c) NAcc integrates different sources of value, representing them in terms of a common currency with the aid of dopamine, and thereby plays a major role in selecting action outcomes within prefrontal cortex. The “goals” pursued by the organism are the outcomes selected by these processes. The hypothesis is developed in the context of a critical review of relevant biological and computational literature which offer it support. The paper shows how the hypothesis has the potential to integrate existing interpretations of motivational value and goal selection.