Neural representations of statistical and rule-based predictions in Gilles de la Tourette syndrome.

Gilles de la Tourette syndrome (GTS) is a disorder characterised by motor and vocal tics, which may represent habitual actions as a result of enhanced learning of associations between stimuli and responses (S-R). In this study, we investigated how adults with GTS and healthy controls (HC) learn two types of regularities in a sequence: statistics (non-adjacent probabilities) and rules (predefined order). Participants completed a visuomotor sequence learning task while EEG was recorded. To understand the neurophysiological underpinnings of these regularities in GTS, multivariate pattern analyses on the temporally decomposed EEG signal as well as sLORETA source localisation method were conducted. We found that people with GTS showed superior statistical learning but comparable rule-based learning compared to HC participants. Adults with GTS had different neural representations for both statistics and rules than HC adults; specifically, adults with GTS maintained the regularity representations longer and had more overlap between them than HCs. Moreover, over different time scales, distinct fronto-parietal structures contribute to statistical learning in the GTS and HC groups. We propose that hyper-learning in GTS is a consequence of the altered sensitivity to encode complex statistics, which might lead to habitual actions.

Adult age differences in language, communication, and learning from text.

This is an introduction to the special issue "Adult Age Differences in Language, Communication, and Learning from Text." These articles illustrate the great variety of language use through the adult lifespan, tell us a little more-and invite further inquiry. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Microstructural differences in the cingulum and the inferior longitudinal fasciculus are associated with (extinction) learning.

Cognitive functions, such as learning and memory processes, depend on effective communication between brain regions which is facilitated by white matter tracts (WMT). We investigated the microstructural properties and the contribution of WMT to extinction learning and memory in a predictive learning task. Forty-two healthy participants completed an extinction learning paradigm without a fear component. We examined differences in microstructural properties using diffusion tensor imaging to identify underlying neural connectivity and structural correlates of extinction learning and their potential implications for the renewal effect. Participants with good acquisition performance exhibited higher fractional anisotropy (FA) in WMT including the bilateral inferior longitudinal fasciculus (ILF) and the right temporal part of the cingulum (CNG). This indicates enhanced connectivity and communication between brain regions relevant to learning and memory resulting in better learning performance. Our results suggest that successful acquisition and extinction performance were linked to enhanced structural connectivity. Lower radial diffusivity (RD) in the right ILF and right temporal part of the CNG was observed for participants with good acquisition learning performance. This observation suggests that learning difficulties associated with increased RD may potentially be due to less myelinated axons in relevant WMT. Also, participants with good acquisition performance were more likely to show a renewal effect. The results point towards a potential role of structural integrity in extinction-relevant WMT for acquisition and extinction.

Unified control of temporal and spatial scales of sensorimotor behavior through neuromodulation of short-term synaptic plasticity.

Neuromodulators have been shown to alter the temporal profile of short-term synaptic plasticity (STP); however, the computational function of this neuromodulation remains unexplored. Here, we propose that the neuromodulation of STP provides a general mechanism to scale neural dynamics and motor outputs in time and space. We trained recurrent neural networks that incorporated STP to produce complex motor trajectories-handwritten digits-with different temporal (speed) and spatial (size) scales. Neuromodulation of STP produced temporal and spatial scaling of the learned dynamics and enhanced temporal or spatial generalization compared to standard training of the synaptic weights in the absence of STP. The model also accounted for the results of two experimental studies involving flexible sensorimotor timing. Neuromodulation of STP provides a unified and biologically plausible mechanism to control the temporal and spatial scales of neural dynamics and sensorimotor behaviors.

The dynamics of functional brain network segregation in feedback-driven learning.

Prior evidence suggests that increasingly efficient task performance in human learning is associated with large scale brain network dynamics. However, the specific nature of this general relationship has remained unclear. Here, we characterize performance improvement during feedback-driven stimulus-response (S-R) learning by learning rate as well as S-R habit strength and test whether and how these two behavioral measures are associated with a functional brain state transition from a more integrated to a more segregated brain state across learning. Capitalizing on two separate fMRI studies using similar but not identical experimental designs, we demonstrate for both studies that a higher learning rate is associated with a more rapid brain network segregation. By contrast, S-R habit strength is not reliably related to changes in brain network segregation. Overall, our current study results highlight the utility of dynamic functional brain state analysis. From a broader perspective taking into account previous study results, our findings align with a framework that conceptualizes brain network segregation as a general feature of processing efficiency not only in feedback-driven learning as in the present study but also in other types of learning and in other task domains.

Motor learning in multijoint virtual arm movements with novel kinematics.

Humans move their hands toward precise positions, a skill supported by the coordination of multiple joint movements, even in the presence of inherent redundancy. However, it remains unclear how the central nervous system learns the relationship between redundant joint movements and hand positions when starting from scratch. To address this question, a virtual-arm reaching task was performed in which participants were required to move a cursor corresponding to the hand of a virtual arm to a target. The joint angles of the virtual arm were determined by the heights of the participants' fingers. The results demonstrated that the participants moved the cursor to the target straighter and faster in the late phase than they did in the initial phase of learning. This improvement was accompanied by a reduction in the amount of angular changes in the virtual limb joint, predominantly characterized by an increased reliance on the virtual shoulder joint as opposed to the virtual wrist joint. These findings suggest that the central nervous system selects a combination of multijoint movements that minimize motor effort while learning novel upper-limb kinematics.

Feature variability determines specificity and transfer in multiorientation feature detection learning.

Historically, in many perceptual learning experiments, only a single stimulus is practiced, and learning is often specific to the trained feature. Our prior work has demonstrated that multi-stimulus learning (e.g., training-plus-exposure procedure) has the potential to achieve generalization. Here, we investigated two important characteristics of multi-stimulus learning, namely, roving and feature variability, and their impacts on multi-stimulus learning and generalization. We adopted a feature detection task in which an oddly oriented target bar differed by 16° from the background bars. The stimulus onset asynchrony threshold between the target and the mask was measured with a staircase procedure. Observers were trained with four target orientation search stimuli, either with a 5° deviation (30°-35°-40°-45°) or with a 45° deviation (30°-75°-120°-165°), and the four reference stimuli were presented in a roving manner. The transfer of learning to the swapped target-background orientations was evaluated after training. We found that multi-stimulus training with a 5° deviation resulted in significant learning improvement, but learning failed to transfer to the swapped target-background orientations. In contrast, training with a 45° deviation slowed learning but produced a significant generalization to swapped orientations. Furthermore, a modified training-plus-exposure procedure, in which observers were trained with four orientation search stimuli with a 5° deviation and simultaneously passively exposed to orientations with high feature variability (45° deviation), led to significant orientation learning generalization. Learning transfer also occurred when the four orientation search stimuli with a 5° deviation were presented in separate blocks. These results help us to specify the condition under which multistimuli learning produces generalization, which holds potential for real-world applications of perceptual learning, such as vision rehabilitation and expert training.

Study protocol to examine the effects of acute exercise on motor learning and brain activity in children with developmental coordination disorder (ExLe-Brain-DCD).

INTRODUCTION: Developmental coordination disorder (DCD) is one of the most prevalent pediatric chronic conditions. Without proper intervention, significant delays in motor skill performance and learning may persist until adulthood. Moderate-to-vigorous physical exercise has been proven to improve motor learning (adaptation and consolidation) in children with or without disorders. However, the effect of a short bout of physical exercise on motor adaptation and consolidation in children with DCD has not been examined. Furthermore, the role of perceptual-motor integration and attention as mediators of learning has not been examined via neuroimaging in this population. OBJECTIVES: Therefore, the primary aims of this project will be to compare children with and without DCD to (a) examine the effect of acute exercise on motor learning (adaptation and consolidation) while performing a rotational visuo-motor adaptation task (rVMA), and (b) explore cortical activation in the dorsolateral- and ventrolateral-prefrontal cortex areas while learning the rVMA task under rest or post-exercise conditions. METHODS: One hundred twenty children will be recruited (60 DCD, 60 controls) and within-cohort randomly assigned to either exercise (13-minute shuttle run task) or rest prior to performing the rVMA task. Adaptation and consolidation will be evaluated via two error variables and three retention tests (1h, 24h and 7 days post adaptation). Cortical activation will be registered via functional near-infrared spectroscopy (fNIRS) during the baseline, adaptation, and consolidation. DISCUSSION: We expect to find exercise benefits on motor learning and attention so that children with DCD profiles will be closer to those of children with typical development. The results of this project will provide further evidence to: (a) better characterize children with DCD for the design of educational materials, and (b) establish acute exercise as a potential intervention to improve motor learning and attention.

Cognitive and neural mechanisms of learning and interventions for improvement across the adult lifespan: A systematic review protocol.

BACKGROUND: There continues to be growing interest in the Science of Learning including identifying applications for findings from this work outside the laboratory to support learning. Presently, there exists a gap in our understanding of learning during healthy adulthood as well as effective ways in which that learning can be improved. Developing a more comprehensive understanding of learning during adulthood, and effective ways of improving that learning, are crucial goals given the impact of a rapidly aging global population. The main objective of the proposed systematic review is to identify and synthesize all recent cognitive and brain research investigating learning across the adult lifespan. METHODS: Searches will be performed across Scopus, Web of Science, and ProQuest databases. Both published and unpublished literature will be screened for inclusion. Included articles will be limited to research in healthy adult samples reporting measures of learning-related cognition, brain structure or function and their relationship with age, or the impact of interventions to improve learning. All steps of the review will be performed by three trained reviewers. Tabular, narrative, and quantitative syntheses will be provided based on the characteristics of included studies. DISCUSSION: Findings from the proposed review will contribute to our understanding of learning in adulthood. Additionally, this review will identify research gaps in need of further investigation and relevant findings for translation, informing the scope of future funding priorities in the Science of Learning.

Higher surface folding of the human premotor cortex is associated with better long-term learning capability.

The capacity to learn enabled the human species to adapt to various challenging environmental conditions and pass important achievements on to the next generation. A growing body of research suggests links between neocortical folding properties and numerous aspects of human behavior, but their impact on enhanced human learning capacity remains unexplored. Here we leverage three training cohorts to demonstrate that higher levels of premotor cortical folding reliably predict individual long-term learning gains in a challenging new motor task, above and beyond initial performance differences. Individual folding-related predisposition to motor learning was found to be independent of cortical thickness and intracortical microstructure, but dependent on larger cortical surface area in premotor regions. We further show that learning-relevant features of cortical folding occurred in close spatial proximity to practice-induced structural brain plasticity. Our results suggest a link between neocortical surface folding and human behavioral adaptability.

Context-informed incremental learning improves both the performance and resilience of myoelectric control.

Despite its rich history of success in controlling powered prostheses and emerging commercial interests in ubiquitous computing, myoelectric control continues to suffer from a lack of robustness. In particular, EMG-based systems often degrade over prolonged use resulting in tedious recalibration sessions, user frustration, and device abandonment. Unsupervised adaptation is one proposed solution that updates a model's parameters over time based on its own predictions during real-time use to maintain robustness without requiring additional user input or dedicated recalibration. However, these strategies can actually accelerate performance deterioration when they begin to classify (and thus adapt) incorrectly, defeating their own purpose. To overcome these limitations, we propose a novel adaptive learning strategy, Context-Informed Incremental Learning (CIIL), that leverages in situ context to better inform the prediction of pseudo-labels. In this work, we evaluate these CIIL strategies in an online target acquisition task for two use cases: (1) when there is a lack of training data and (2) when a drastic and enduring alteration in the input space has occurred. A total of 32 participants were evaluated across the two experiments. The results show that the CIIL strategies significantly outperform the current state-of-the-art unsupervised high-confidence adaptation and outperform models trained with the conventional screen-guided training approach, even after a 45-degree electrode shift (p < 0.05). Consequently, CIIL has substantial implications for the future of myoelectric control, potentially reducing the training burden while bolstering model robustness, and leading to improved real-time control.

The representation of contextual cue is stimulus-specific yet its expression is flexible.

Background: Contextual cueing refers to the phenomenon in which individuals utilize frequently encountered environmental contexts, comprised of distractors, as cues to expedite a target search. Due to the conflict between the widespread occurrence of contextual cue transfer and the observed impact of changing the identity of distractors on contextual cue learning, the content of contextual cue representations remains contentious. Considering the independent nature of contextual cue learning and expression, our proposition is twofold: (1) Contextual cue representations are stimulus-specific, and (2) their expression is highly flexible. Methods: To validate the model, two experiments were conducted. Experiment 1 aimed to confirm the hypothesis that contextual cue representations are stimulus-specific. We manipulated the identity consistency of distractors within repeated scenes during contextual cue learning. Difficulty in contextual cue learning under the identity-changing condition would suggest the necessity of identity within contextual cue representation, indicating the stimulus-specific nature of these representations. Experiment 2 was designed to affirm the conclusion of Experiment 1 and explore the flexibility in the expression of contextual cue representations. This experiment comprised two phases: learning and testing. During the learning phase, participants were exposed to two sets of repeated scenes in different colors under two learning conditions: load and no-load. Working memory load was introduced to interfere with the expression to prevent it from becoming automatic. In the subsequent testing phase, the colors of the two scene sets were interchanged to impede retrieval based on identity. If both load and no-load conditions demonstrate similar levels of contextual cue effects during the testing phase, it implies the flexibility in the expression of contextual cue representations and confirms the conclusion of Experiment 1. Results: In Experiment 1, a notable contextual cue learning effect was observed under the identity-consistent condition (p = 0.001). However, this effect was not evident under the identity-changing condition (p = 0.286). This finding strongly supports the stimulus-specific nature of contextual cue representation. In Experiment 2, the contextual cueing effect appeared but did not show a significant difference between the two conditions (t(23) = 0.02, p = 0.987, BF10 = 0.215), indicating the cognitive system's ability to flexibly redefine retrieval cues. This adaptability aligns with our hypothesis and confirms the high flexibility in the expression process of contextual cue representations and confirms the conclusion of Experiment 1.

Stanislas Dehaene.

Stanislas Dehaene is a cognitive neuroscientist elucidating the biological mechanisms that give rise to human perception and cognition. In a conversation with Neuron, he talks about his ongoing interest in consciousness research, the role of theory in neuroscience, and his current work on education and the science of learning.

Do Chosen Learning Strategies Predict Academic Performance in First-Year DPT Anatomy Students?

INTRODUCTION: The purpose of this study was to identify predictors of anatomy final course grades from first-year physical therapist students' characteristics and chosen learning strategies, as indicated on the Motivated Strategies for Learning Questionnaire (MSLQ). Identifying factors that contribute to success in content intensive classes may aid in coaching successful learning strategies as students transition from undergraduate coursework to Doctor of Physical Therapy (DPT) programs. REVIEW OF LITERATURE: Previous studies show that first-year graduate students use ineffective learning strategies that are insufficient for graduate-level study. The MSLQ correlates with academic performance at several educational levels. To date, only one study has examined the correlation of MSLQ with physical therapist students' academic performance for an anatomy course. SUBJECTS: Thirty-nine first-year physical therapist students participated in the study (27 from a hybrid program, 12 from a traditional program). METHODS: This study analyzed MSLQ scores for the total instrument, each domain, and each subscale using regression analyses to determine predictors of final anatomy grades. RESULTS: The subscales of Self-Efficacy and Test Anxiety had significant predictive value for anatomy grades (R2 = 0.455, F = 5.203, P = .029). Test Anxiety had an inverse relationship to anatomy grades, meaning lower test anxiety scores correlated with higher anatomy grades. The combination of Self-Efficacy, Test Anxiety, and Critical Thinking subscales resulted in a significant prediction of anatomy grades (R2 = 0.603, F = 6.659, P = .014). DISCUSSION AND CONCLUSION: This study found moderate correlations between MSLQ Motivation subscales and final grades in DPT anatomy classes. Self-Efficacy and Test Anxiety subscales had the strongest correlations and were significantly predictive of anatomy grades. Faculty may benefit from using inventories like the MSLQ for first-year physical therapist students to identify motivational characteristics associated with success and to remediate students' learning strategies to prevent academic failure.

Visual statistical learning in preverbal infants at a higher likelihood of autism and its association with later social communication skills.

Visual statistical Learning (SL) allows infants to extract the statistical relationships embedded in a sequence of elements. SL plays a crucial role in language and communication competencies and has been found to be impacted in Autism Spectrum Disorder (ASD). This study aims to investigate visual SL in infants at higher likelihood of developing ASD (HL-ASD) and its predictive value on autistic-related traits at 24-36 months. At 6 months of age, SL was tested using a visual habituation task in HL-ASD and neurotypical (NT) infants. All infants were habituated to a visual sequence of shapes containing statistically predictable patterns. In the test phase, infants viewed the statistically structured, familiar sequence in alternation with a novel sequence that did not contain any statistical information. HL-ASD infants were then evaluated at 24-36 months to investigate the associations between visual SL and ASD-related traits. Our results showed that NT infants were able to learn the statistical structure embedded in the visual sequences, while HL-ASD infants showed different learning patterns. A regression analysis revealed that SL ability in 6-month-old HL-ASD infants was related to social communication and interaction abilities at 24-36 months of age. These findings indicate that early differences in learning visual statistical patterns might contribute to later social communication skills.

Oculomotor behavior can be adjusted on the basis of artificial feedback signals indicating externally caused errors.

Whether a saccade is accurate and has reached the target cannot be evaluated during its execution, but relies on post-saccadic feedback. If the eye has missed the target object, a secondary corrective saccade has to be made to align the fovea with the target. If a systematic post-saccadic error occurs, adaptive changes to the oculomotor behavior are made, such as shortening or lengthening the saccade amplitude. Systematic post-saccadic errors are typically attributed internally to erroneous motor commands. The corresponding adaptive changes to the motor command reduce the error and the need for secondary corrective saccades, and, in doing so, restore accuracy and efficiency. However, adaptive changes to the oculomotor behavior also occur if a change in saccade amplitude is beneficial for task performance, or if it is rewarded. Oculomotor learning thus is more complex than reducing a post-saccadic position error. In the current study, we used a novel oculomotor learning paradigm and investigated whether human participants are able to adapt their oculomotor behavior to improve task performance even when they attribute the error externally. The task was to indicate the intended target object among several objects to a simulated human-machine interface by making eye movements. The participants were informed that the system itself could make errors. The decoding process depended on a distorted landing point of the saccade, resulting in decoding errors. Two different types of visual feedback were added to the post-saccadic scene and we compared how participants used the different feedback types to adjust their oculomotor behavior to avoid errors. We found that task performance improved over time, regardless of the type of feedback. Thus, error feedback from the simulated human-machine interface was used for post-saccadic error evaluation. This indicates that 1) artificial visual feedback signals and 2) externally caused errors might drive adaptive changes to oculomotor behavior.

Wings of Change: aPKC/FoxP-dependent plasticity in steering motor neurons underlies operant self-learning in Drosophila.

Background: Motor learning is central to human existence, such as learning to speak or walk, sports moves, or rehabilitation after injury. Evidence suggests that all forms of motor learning share an evolutionarily conserved molecular plasticity pathway. Here, we present novel insights into the neural processes underlying operant self-learning, a form of motor learning in the fruit fly Drosophila. Methods: We operantly trained wild type and transgenic Drosophila fruit flies, tethered at the torque meter, in a motor learning task that required them to initiate and maintain turning maneuvers around their vertical body axis (yaw torque). We combined this behavioral experiment with transgenic peptide expression, CRISPR/Cas9-mediated, spatio-temporally controlled gene knock-out and confocal microscopy. Results: We find that expression of atypical protein kinase C (aPKC) in direct wing steering motoneurons co-expressing the transcription factor FoxP is necessary for this type of motor learning and that aPKC likely acts via non-canonical pathways. We also found that it takes more than a week for CRISPR/Cas9-mediated knockout of FoxP in adult animals to impair motor learning, suggesting that adult FoxP expression is required for operant self-learning. Conclusions: Our experiments suggest that, for operant self-learning, a type of motor learning in Drosophila, co-expression of atypical protein kinase C (aPKC) and the transcription factor FoxP is necessary in direct wing steering motoneurons. Some of these neurons control the wing beat amplitude when generating optomotor responses, and we have discovered modulation of optomotor behavior after operant self-learning. We also discovered that aPKC likely acts via non-canonical pathways and that FoxP expression is also required in adult flies.

Heuristic test reveals little effect of learning and maturation on early prey capture experiences in a web-building spider.

Behaviors can vary throughout an animal's life and this variation can often be explained by changes associated with learning and/or maturing. Currently, there is little consensus regarding how these processes interact to affect behaviors. Here we proposed a heuristic approach to disentangle the effects of learning and maturation on behavior and applied it to the predatory behaviors of Physocyclus globosus spiderlings. We varied the degree of prey difficulty and familiarity spiderlings received along the first instar and across the molt to the second instar and quantified the time spiderlings spent wrapping prey, as a proxy for prey capture efficiency. We found no overall evidence for learning or maturation. Changes in efficiency were mainly due to the switch from difficult to easy prey, or vice versa. However, there was one treatment where spiderlings improved in efficiency before and after the molt, without a switch in prey type. This provides some indication that difficult prey may offer more opportunity for learning or maturation to impact behavior. Although we found little effect of learning or maturation on prey capture efficiency, we suggest that our heuristic approach is effective and could be useful in investigating these processes in other behaviors and other animals.

Electroacupuncture regulates Rab5a-mediating NGF transduction to improve learning and memory ability in the early stage of AD mice.

AIMS: Nerve growth factor (NGF) loss is a potential factor for the degeneration of basal forebrain cholinergic neurons (BFCNs) in Alzheimer's disease (AD), and Rab5a is a key regulatory molecule of NGF signaling transduction. Here, we investigated the changes of Rab5a in 5 × FAD mice and further explored the mechanism of Electroacupuncture (EA) treatment in improving cognition in the early stage of AD. METHODS: The total Rab5a and Rab5a-GTP in 5-month-old 5 × FAD mice and wild-type mice were detected using WB and IP technologies. 5 × FAD mice were treated with EA at the Bai hui (DU20) and Shen ting (DU24) acupoints for 4 weeks and CRE/LOXP technology was used to confirm the role of Rab5a in AD mediated by EA stimulation. The Novel Object Recognition and Morris water maze tests were used to evaluate the cognitive function of 5 × FAD mice. The Nissl, immunohistochemistry, and Thioflavin S staining were used to observe pathological morphological changes in the basal forebrain circuit. The Golgi staining was used to investigate the synaptic plasticity of the basal forebrain circuit and WB technology was used to detect the expression levels of cholinergic-related and NGF signal-related proteins. RESULTS: The total Rab5a was unaltered, but Rab5a-GTP increased and the rab5a-positive early endosomes appeared enlarged in the hippocampus of 5 × FAD mice. Notably, EA reduced Rab5a-GTP in the hippocampus in the early stage of 5 × FAD mice. EA could improve object recognition memory and spatial learning memory by reducing Rab5a activity in the early stage of 5 × FAD mice. Moreover, EA could reduce Rab5a activity to increase NGF transduction and increase the levels of phosphorylated TrkA, AKT, and ERK in the basal forebrain and hippocampus, and increase the expression of cholinergic-related proteins, such as ChAT, vAchT, ChT1, m1AchR, and m2AchR in the basal forebrain and ChAT, m1AchR, and m2AchR in the hippocampus, improving synaptic plasticity in the basal forebrain hippocampal circuit in the early stage of 5 × FAD mice. CONCLUSIONS: Rab5a hyperactivation is an early pathological manifestation of 5 × FAD mice. EA could suppress Rab5a-GTP to promote the transduction of NGF signaling, and enhance the synaptic plasticity of the basal forebrain hippocampal circuit improving cognitive impairment in the early stage of 5 × FAD mice.