Examining for gender differences in return to learn following sport-related concussion in high school student athletes.

OBJECTIVE: Prior studies have investigated associations between gender, symptom resolution, and time to return to play following sport-related concussion (SRC). However, there is a notable gap in research regarding the association between gender and return to learn (RTL) in adolescents. Therefore, this study 1) compared the patterns of RTL between boys and girls who are high school student athletes, and 2) evaluated the possible association between gender and time to RTL after adjusting for covariates. METHODS: A retrospective cohort study of a prospective surveillance program that monitored concussion recovery of athletes in high schools throughout the state of Maine between February 2015 and January 2023 was performed. The primary independent variable was gender, dichotomized as boys and girls. The primary outcome was time to RTL, defined by the number of days for an athlete to return to school without accommodations. Mann-Whitney U-tests were used to compare RTL between the boys and girls. Each athlete's RTL status was dichotomized (i.e., returned vs had not returned) at several time points following injury (i.e., 1, 2, 3, and 4 weeks), and chi-square tests were performed to compare the proportions who achieved RTL between groups. Multivariable linear regression analyses were performed to evaluate the predictive value of gender on RTL. Covariates included age, number of previous concussions, history of learning disability or attention-deficit disorder or attention-deficit/hyperactivity disorder, history of a psychological condition, history of headaches or migraines, initial Sport Concussion Assessment Tool (SCAT3/SCAT5) score, and days to evaluation. RESULTS: Of 895 high school athletes, 488 (54.5%) were boys and 407 (45.5%) were girls. There was no statistically significant difference in median [IQR] days to RTL between genders (6.0 [3.0-11.0] vs 6.0 [3.0-12.0] days; U = 84,365.00, p < 0.375). A greater proportion of boys successfully returned to learn without accommodations by 3 weeks following concussion (93.5% vs 89.4%; χ2 = 4.68, p = 0.030), but no differences were found at 1, 2, or 4 weeks. A multivariable model predicting days to RTL showed that gender was not a significant predictor of RTL (p > 0.05). Longer days to evaluation (ß = 0.10, p = 0.021) and higher initial SCAT3/SCAT5 scores (ß = 0.15, p < 0.001) predicted longer RTL. CONCLUSIONS: In a cohort of high school athletes, RTL did not differ between boys and girls following SRC. Gender was not a significant predictor of RTL. Longer days to evaluation and higher initial symptom scores were associated with longer RTL.

Ventrointermediate thalamic stimulation improves motor learning in humans.

Ventrointermediate thalamic stimulation (VIM-DBS) modulates oscillatory activity in a cortical network including primary motor cortex, premotor cortex, and parietal cortex. Here we show that, beyond the beneficial effects of VIM-DBS on motor execution, this form of invasive stimulation facilitates production of sequential finger movements that follow a repeated sequence. These results highlight the role of thalamo-cortical activity in motor learning.

Limb-related sensory prediction errors and task-related performance errors facilitate human sensorimotor learning through separate mechanisms.

The unpredictable nature of our world can introduce a variety of errors in our actions, including sensory prediction errors (SPEs) and task performance errors (TPEs). SPEs arise when our existing internal models of limb-environment properties and interactions become miscalibrated due to changes in the environment, while TPEs occur when environmental perturbations hinder achievement of task goals. The precise mechanisms employed by the sensorimotor system to learn from such limb- and task-related errors and improve future performance are not comprehensively understood. To gain insight into these mechanisms, we performed a series of learning experiments wherein the location and size of a reach target were varied, the visual feedback of the motion was perturbed in different ways, and instructions were carefully manipulated. Our findings indicate that the mechanisms employed to compensate SPEs and TPEs are dissociable. Specifically, our results fail to support theories that suggest that TPEs trigger implicit refinement of reach plans or that their occurrence automatically modulates SPE-mediated learning. Rather, TPEs drive improved action selection, that is, the selection of verbally sensitive, volitional strategies that reduce future errors. Moreover, we find that exposure to SPEs is necessary and sufficient to trigger implicit recalibration. When SPE-mediated implicit learning and TPE-driven improved action selection combine, performance gains are larger. However, when actions are always successful and strategies are not employed, refinement in behavior is smaller. Flexibly weighting strategic action selection and implicit recalibration could thus be a way of controlling how much, and how quickly, we learn from errors.

Perceptual error based on Bayesian cue combination drives implicit motor adaptation.

The sensorimotor system can recalibrate itself without our conscious awareness, a type of procedural learning whose computational mechanism remains undefined. Recent findings on implicit motor adaptation, such as over-learning from small perturbations and fast saturation for increasing perturbation size, challenge existing theories based on sensory errors. We argue that perceptual error, arising from the optimal combination of movement-related cues, is the primary driver of implicit adaptation. Central to our theory is the increasing sensory uncertainty of visual cues with increasing perturbations, which was validated through perceptual psychophysics (Experiment 1). Our theory predicts the learning dynamics of implicit adaptation across a spectrum of perturbation sizes on a trial-by-trial basis (Experiment 2). It explains proprioception changes and their relation to visual perturbation (Experiment 3). By modulating visual uncertainty in perturbation, we induced unique adaptation responses in line with our model predictions (Experiment 4). Overall, our perceptual error framework outperforms existing models based on sensory errors, suggesting that perceptual error in locating one's effector, supported by Bayesian cue integration, underpins the sensorimotor system's implicit adaptation.

Persistent vocal learning in an aging open-ended learner reflected in neural FoxP2 expression.

BACKGROUND: Most vocal learning species exhibit an early critical period during which their vocal control neural circuitry facilitates the acquisition of new vocalizations. Some taxa, most notably humans and parrots, retain some degree of neurobehavioral plasticity throughout adulthood, but both the extent of this plasticity and the neurogenetic mechanisms underlying it remain unclear. Differential expression of the transcription factor FoxP2 in both songbird and parrot vocal control nuclei has been identified previously as a key pattern facilitating vocal learning. We hypothesize that the resilience of vocal learning to cognitive decline in open-ended learners will be reflected in an absence of age-related changes in neural FoxP2 expression. We tested this hypothesis in the budgerigar (Melopsittacus undulatus), a small gregarious parrot in which adults converge on shared call types in response to shifts in group membership. We formed novel flocks of 4 previously unfamiliar males belonging to the same age class, either "young adult" (6 mo - 1 year) or "older adult" (≥ 3 year), and then collected audio-recordings over a 20-day learning period to assess vocal learning ability. Following behavioral recording, immunohistochemistry was performed on collected neural tissue to measure FoxP2 protein expression in a parrot vocal learning center, the magnocellular nucleus of the medial striatum (MMSt), and its adjacent striatum. RESULTS: Although older adults show lower vocal diversity (i.e. repertoire size) and higher absolute levels of FoxP2 in the MMSt than young adults, we find similarly persistent downregulation of FoxP2 and equivalent vocal plasticity and vocal convergence in the two age cohorts. No relationship between individual variation in vocal learning measures and FoxP2 expression was detected. CONCLUSIONS: We find neural evidence to support persistent vocal learning in the budgerigar, suggesting resilience to aging in the open-ended learning program of this species. The lack of a significant relationship between FoxP2 expression and individual variability in vocal learning performance suggests that other neurogenetic mechanisms could also regulate this complex behavior.

Which learning techniques supported by cognitive research do students use at secondary school? Prevalence and associations with students' beliefs and achievement.

Research in cognitive science has highlighted the effectiveness of several learning techniques, and a number of studies have analyzed their prevalence among university students and their relationship with academic achievement. In this study, we surveyed a large, heterogeneous sample of secondary school students to reveal how often they use research-supported techniques in comparison with other frequent techniques, and we analyzed the association between their study strategies and school achievement. We also assessed the associations between study techniques and several students' beliefs and attitudes toward learning (self-efficacy, goal orientation, control beliefs, growth mindset, and examination anxiety). Results showed that, except for distributed practice, only those techniques that are supported by previous research yielded an association with achievement, and they exhibited higher associations with self-efficacy, growth mindset, control beliefs, and learning goal orientation than non-supported techniques.

Does using artificial intelligence assistance accelerate skill decay and hinder skill development without performers' awareness?

Artificial intelligence in the workplace is becoming increasingly common. These tools are sometimes used to aid users in performing their task, for example, when an artificial intelligence tool assists a radiologist in their search for abnormalities in radiographic images. The use of artificial intelligence brings a wealth of benefits, such as increasing the efficiency and efficacy of performance. However, little research has been conducted to determine how the use of artificial intelligence assistants might affect the user's cognitive skills. In this theoretical perspective, we discuss how artificial intelligence assistants might accelerate skill decay among experts and hinder skill acquisition among learners. Further, we discuss how AI assistants might also prevent experts and learners from recognizing these deleterious effects. We then discuss the types of questions: use-inspired basic cognitive researchers, applied researchers, and computer science researchers should seek to answer. We conclude that multidisciplinary research from use-inspired basic cognitive research, domain-specific applied research, and technical research (e.g., human factors research, computer science research) is needed to (a) understand these potential consequences, (b) design artificial intelligence systems to mitigate these impacts, and (c) develop training and use protocols to prevent negative impacts on users' cognitive skills. Only by answering these questions from multidisciplinary perspectives can we harness the benefits of artificial intelligence in the workplace while preventing negative impacts on users' cognitive skills.

Half a century legacy of long-term potentiation.

In 1973, two papers from Bliss and Lømo and from Bliss and Gardner-Medwin reported that high-frequency synaptic stimulation in the dentate gyrus of rabbits resulted in a long-lasting increase in synaptic strength. This form of synaptic plasticity, commonly referred to as long-term potentiation (LTP), was immediately considered as an attractive mechanism accounting for the ability of the brain to store information. In this historical piece looking back over the past 50 years, we discuss how these two landmark contributions directly motivated a colossal research effort and detail some of the resulting milestones that have shaped our evolving understanding of the molecular and cellular underpinnings of LTP. We highlight the main features of LTP, cover key experiments that defined its induction and expression mechanisms, and outline the evidence supporting a potential role of LTP in learning and memory. We also briefly explore some ramifications of LTP on network stability, consider current limitations of LTP as a model of associative memory, and entertain future research orientations.

Efficacy of perceptual learning in low vision: A systematic review and meta-analysis.

BACKGROUND: Visual perceptual learning (PL) shows promise for enhancing visual functions in individuals with visual impairment. OBJECTIVE: This systematic review aimed to evaluate the effectiveness of PL in improving visual function. STUDY ELIGIBILITY: Eligible studies were those examining the efficacy of PL in individuals with low vision. STUDY APPRAISAL AND SYNTHESIS METHODS: The review protocol was registered with the international Prospective Register of Systematic Reviews (ID CRD42022327545) and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Screened studies were synthesized using random-effects meta-analysis and narrative synthesis following Synthesis Without Meta-analysis guidelines. The quality of the evidence was assessed using the Cochrane risk-of-bias tool and the JBI Critical Appraisal Tool for Quasi-Experimental studies. RESULTS: Fifty studies were included, covering various visual impairments and employing different PL interventions. Most studies had low risk of bias. Meta-analysis showed significant improvement in visual search for individuals with cortical blindness (Hedges' g = 0.71; 95% confidence interval, 0.48 to 0.93; p=0.002); all other analyses did not show significant improvements-reading in central vision loss and cortical blindness, and visual field in peripheral vision loss and cortical blindness. However, the narrative synthesis provided evidence showing effectiveness, particularly in individuals with central vision loss and cortical blindness, demonstrating positive effects on reading, contrast sensitivity, visual field, and motion perception. LIMITATIONS: Variations in study design, PL protocols, outcome measures, and measurement methods introduced heterogeneity, limiting the analysis. CONCLUSIONS: The efficacy of PL in vision rehabilitation remains uncertain. Although meta-analysis results were mostly inconclusive, the narrative synthesis indicated improved visual functions following PL, consistent with individual study findings. IMPLICATIONS OF KEY FINDINGS: Future research should optimize intervention parameters, explore long-term effects, and assess generalizability across diverse populations and visual impairment etiologies. Larger randomized controlled trials using standardized outcome measures are needed to advance the field.

Perirhinal cortex learns a predictive map of the task environment.

Goal-directed tasks involve acquiring an internal model, known as a predictive map, of relevant stimuli and associated outcomes to guide behavior. Here, we identified neural signatures of a predictive map of task behavior in perirhinal cortex (Prh). Mice learned to perform a tactile working memory task by classifying sequential whisker stimuli over multiple training stages. Chronic two-photon calcium imaging, population analysis, and computational modeling revealed that Prh encodes stimulus features as sensory prediction errors. Prh forms stable stimulus-outcome associations that can progressively be decoded earlier in the trial as training advances and that generalize as animals learn new contingencies. Stimulus-outcome associations are linked to prospective network activity encoding possible expected outcomes. This link is mediated by cholinergic signaling to guide task performance, demonstrated by acetylcholine imaging and systemic pharmacological perturbation. We propose that Prh combines error-driven and map-like properties to acquire a predictive map of learned task behavior.

Social learning and culture in bees: Simple mechanisms, complex outcomes.

Bees have been excellent model systems to study social learning - the ability of animals to change their behaviour based on observations of other individuals. Researchers have investigated several aspects of social learning in bees, including how it can lead to cultural traditions. A recent study also argues that bees have the capacity to socially learn behaviours that they could not innovate on their own. To understand these findings better, I review what we know about the mechanisms underlying social learning in bees and use these findings to compare social learning and culture in bees and humans. The findings suggest that the seemingly complex social behaviours of bees could arise from simple mechanisms underlying learning in general. I highlight the importance of investigating cognitive mechanisms and how they might differ across animals.

Top-down and bottom-up oscillatory dynamics regulate implicit visuomotor sequence learning.

Implicit visuomotor sequence learning is crucial for acquiring skills that result in automated behaviors. The oscillatory dynamics underpinning this learning process are not well understood. To address this gap, the current study employed electroencephalography with a medium-density array (64 electrodes) to investigate oscillatory activity associated with implicit visuomotor sequence learning in the Serial Reaction Time task. In the task, participants unknowingly learn a series of finger movements. Eighty-five healthy adults participated in the study. Analyses revealed that theta activity at the vertex and alpha/beta activity over the motor areas decreased over the course of learning. No associations between alpha/beta and theta power were observed. These findings are interpreted within a dual-process framework: midline theta activity is posited to regulate top-down attentional processes, whereas beta activity from motor areas underlies the bottom-up encoding of sensory information from movement. From this model, we suggest that during implicit visuomotor sequence learning, top-down processes become disengaged (indicated by a reduction in theta activity), and modality specific bottom-up processes encode the motor sequence (indicated by a reduction in alpha/beta activity).

The odour of an unfamiliar stressed or relaxed person affects dogs' responses to a cognitive bias test.

Dogs can discriminate stressed from non-stressed human odour samples, but the effect on their cognition is unstudied. Using a cognitive bias task, we tested how human odours affect dogs' likelihood of approaching a food bowl placed at three ambiguous locations ("near-positive", "middle" and "near-negative") between trained "positive" (rewarded) and "negative" (unrewarded) locations. Using odour samples collected from three unfamiliar volunteers during stressful and relaxing activities, we tested eighteen dogs under three conditions: no odour, stress odour and relaxed odour, with the order of test odours counterbalanced across dogs. When exposed to stress odour during session three, dogs were significantly less likely to approach a bowl placed at one of the three ambiguous locations (near-negative) compared to no odour, indicating possible risk-reduction behaviours in response to the smell of human stress. Dogs' learning of trained positive and negative locations improved with repeated testing and was significant between sessions two and three only when exposed to stress odour during session three, suggesting odour influenced learning. This is the first study to show that without visual or auditory cues, olfactory cues of human stress may affect dogs' cognition and learning, which, if true, could have important consequences for dog welfare and working performance.

The effect of cue length and position on noticing and learning of determiner agreement pairings: Evidence from a cue-balanced artificial vocabulary learning task.

The importance of cues in language learning has long been established and it is clear that cues are an essential part of both first language (L1) and second/additional language (L2/A) acquisition. The effects of cue reliability and frequency, along with the competition between cues have been shown to significantly impact learners' pace of acquisition of these language-specific patterns. However, natural languages do not allow for a clear picture of how the forms of cues themselves affect their perception, uptake, and generalizability. In this study, we developed an artificial vocabulary consisting of determiners and nouns. Within these nouns, completely reliable cues were developed and equally distributed as long and short cues over three possible positions: beginning, middle, or end. Through a word-pair learning study, we show that length and position of cues variably affects agreement accuracy, and that noticing of cues during training is less important for known words, and more important for novel ones when deciding on inter-word gender-like agreement.

Want to learn? think again!

One of the best ways to improve new learning and increase memory strength is by reprocessing the recently acquired information, for example, by thinking of it again. Synaptic plasticity, the process by which neurons change the strength of their connections with each other, is fundamental for learning and memory formation. Yet, at present, it is unclear how reprocessing information drives synaptic plasticity to support memory improvement. A new study suggests that reprocessing enhances memory formation by recruiting more synapses to represent the new memory, thus increasing its strength.

Circuit dynamics of the olfactory pathway during olfactory learning.

The olfactory system plays crucial roles in perceiving and interacting with their surroundings. Previous studies have deciphered basic odor perceptions, but how information processing in the olfactory system is associated with learning and memory is poorly understood. In this review, we summarize recent studies on the anatomy and functional dynamics of the mouse olfactory learning pathway, focusing on how neuronal circuits in the olfactory bulb (OB) and olfactory cortical areas integrate odor information in learning. We also highlight in vivo evidence for the role of the lateral entorhinal cortex (LEC) in olfactory learning. Altogether, these studies demonstrate that brain regions throughout the olfactory system are critically involved in forming and representing learned knowledge. The role of olfactory areas in learning and memory, and their susceptibility to dysfunction in neurodegenerative diseases, necessitate further research.

Flexible decision-making is related to strategy learning, vicarious trial and error, and medial prefrontal rhythms during spatial set-shifting.

Flexible decision-making requires a balance between exploring features of an environment and exploiting prior knowledge. Behavioral flexibility is typically measured by how long it takes subjects to consistently make accurate choices after reward contingencies switch or task rules change. This measure, however, only allows for tracking flexibility across multiple trials, and does not assess the degree of flexibility. Plus, although increases in decision-making accuracy are strong indicators of learning, other decision-making behaviors have also been suggested as markers of flexibility, such as the on-the-fly decision reversals known as vicarious trial and error (VTE) or switches to a different, but incorrect, strategy. We sought to relate flexibility, learning, and neural activity by comparing choice history-derived evaluation of strategy use with changes in decision-making accuracy and VTE behavior while recording from the medial prefrontal cortex (mPFC) in rats. Using a set-shifting task that required rats to repeatedly switch between spatial decision-making strategies, we show that a previously developed strategy likelihood estimation procedure could identify putative learning points based on decision history. We confirm the efficacy of learning point estimation by showing increases in decision-making accuracy aligned to the learning point. Additionally, we show increases in the rate of VTE behavior surrounding identified learning points. By calculating changes in strategy likelihoods across trials, we tracked flexibility on a trial-by-trial basis and show that flexibility scores also increased around learning points. Further, we demonstrate that VTE behaviors could be separated into indecisive and deliberative subtypes depending on whether they occurred during periods of high or low flexibility and whether they led to correct or incorrect choice outcomes. Field potential recordings from the mPFC during decisions exhibited increased beta band activity on trials with VTE compared to non-VTE trials, as well as increased gamma during periods when learned strategies could be exploited compared to prelearning, exploratory periods. This study demonstrates that increased behavioral flexibility and VTE rates are often aligned to task learning. These relationships can break down, however, suggesting that VTE is not always an indicator of deliberative decision-making. Additionally, we further implicate the mPFC in decision-making and learning by showing increased beta-based activity on VTE trials and increased gamma after learning.

Flexible multitask computation in recurrent networks utilizes shared dynamical motifs.

Flexible computation is a hallmark of intelligent behavior. However, little is known about how neural networks contextually reconfigure for different computations. In the present work, we identified an algorithmic neural substrate for modular computation through the study of multitasking artificial recurrent neural networks. Dynamical systems analyses revealed learned computational strategies mirroring the modular subtask structure of the training task set. Dynamical motifs, which are recurring patterns of neural activity that implement specific computations through dynamics, such as attractors, decision boundaries and rotations, were reused across tasks. For example, tasks requiring memory of a continuous circular variable repurposed the same ring attractor. We showed that dynamical motifs were implemented by clusters of units when the unit activation function was restricted to be positive. Cluster lesions caused modular performance deficits. Motifs were reconfigured for fast transfer learning after an initial phase of learning. This work establishes dynamical motifs as a fundamental unit of compositional computation, intermediate between neuron and network. As whole-brain studies simultaneously record activity from multiple specialized systems, the dynamical motif framework will guide questions about specialization and generalization.

High contextual interference improves retention in motor learning: systematic review and meta-analysis.

The effect of practice schedule on retention and transfer has been studied since the first publication on contextual interference (CI) in 1966. However, strongly advocated by scientists and practitioners, the CI effect also aroused some doubts. Therefore, our objective was to review the existing literature on CI and to determine how it affects retention in motor learning. We found 1255 articles in the following databases: Scopus, EBSCO, Web of Science, PsycINFO, ScienceDirect, supplemented by the Google Scholar search engine. We screened full texts of 294 studies, of which 54 were included in the meta-analysis. In the meta-analyses, two different models were applied, i.e., a three-level mixed model and random-effects model with averaged effect sizes from single studies. According to both analyses, high CI has a medium beneficial effect on the whole population. These effects were statistically significant. We found that the random practice schedule in laboratory settings effectively improved motor skills retention. On the contrary, in the applied setting, the beneficial effect of random practice on the retention was almost negligible. The random schedule was more beneficial for retention in older adults (large effect size) and in adults (medium effect size). In young participants, the pooled effect size was negligible and statically insignificant.

Transcranial direct current stimulation of the prefrontal and visual cortices diversely affects early and late perceptual learning.

BACKGROUND: Research has shown that visual perceptual learning (VPL) is related to modifying neural activity in higher level decision-making regions. However, the causal roles of the prefrontal and visual cortexes in VPL are still unclear. Here, we investigated how anodal transcranial direct current stimulation (tDCS) of the prefrontal and visual cortices modulates VPL in the early and later phases and the role of multiple brain regions. METHODS: Perceptual learning on the coherent motion direction identification task included early and later stages. After early training, participants needed to continuously train to reach a plateau; once the plateau was reached, participants entered a later stage. Sixty participants were randomly divided into five groups. Regardless of the training at the early and later stages, four groups received multitarget tDCS over the right dorsolateral prefrontal cortex (rDLPFC) and right middle temporal area (rMT), single-target tDCS over the rDLPFC, and single-target tDCS over the rMT or sham stimulation, and one group was stimulated at the ipsilateral brain region (i.e., left MT). RESULTS: Compared with sham stimulation, multitarget and two single-target tDCS over the rDLPFC or rMT improved posttest performance and accelerated learning during the early period. However, multitarget tDCS and two single-target tDCS led to equivalent benefits for VPL. Additionally, these beneficial effects were absent when anodal tDCS was applied to the ipsilateral brain region. For the later period, the above facilitating effects on VPL induced by multitarget or single-target tDCS disappeared. CONCLUSIONS: This study suggested the causal role of the prefrontal and visual cortices in visual motion perceptual learning by anodal tDCS but failed to find greater beneficial effects by simultaneously stimulating the prefrontal and visual cortices. Future research should investigate the functional associations between multiple brain regions to further promote VPL.