Differences In Learning Success Research Articles

Emerging native-similar neural representations underlie non-native speech category learning success.

Learning non-native phonetic categories in adulthood is an exceptionally challenging task, characterized by large inter-individual differences in learning speed and outcomes. The neurobiological mechanisms underlying the inter-individual differences in the learning efficacy are not fully understood. Here we examined the extent to which training-induced neural representations of non-native Mandarin tone categories in English listeners (n = 53) are increasingly similar to those of the native listeners (n = 33) who acquired these categories early in infancy. We particularly assessed whether the neural similarities in representational structure between non-native learners and native listeners are robust neuromarkers of inter-individual differences in learning success. Using inter-subject neural representational similarity (IS-NRS) analysis and predictive modeling on two functional magnetic resonance imaging (fMRI) datasets, we examined the neural representational mechanisms underlying speech category learning success. Learners' neural representations that were significantly similar to the native listeners emerged in brain regions mediating speech perception following training; the extent of the emerging neural similarities with native listeners significantly predicted the learning speed and outcome in learners. The predictive power of IS-NRS outperformed models with other neural representational measures. Furthermore, neural representations underlying successful learning are multidimensional but cost-efficient in nature. The degree of the emergent native-similar neural representations was closely related to the robust neural sensitivity to feedback in the frontostriatal network. These findings provide important insights on experience-dependent representational neuroplasticity underlying successful speech learning in adulthood and could be leveraged in designing individualized feedback-based training paradigms that maximize learning efficiency.

Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real‐time fMRI neurofeedback studies report large inter‐individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta‐analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no‐feedback runs (i.e., self‐regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain‐based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.

Neural changes underlying successful second language word learning: An fMRI study

A great deal of research has examined behavioral performance changes associated with second language learning. But what changes are taking place in the brain as learning progresses? How can we identify differences in brain changes that reflect successes of learning? To answer these questions, we conducted a functional magnetic resonance imaging (fMRI) study to examine the neural activities associated with second language word learning. Participants were 39 native English speakers who had no prior knowledge of Chinese or other tonal language, and were trained to learn a novel tonal vocabulary in a six-week training session. Functional MRI scans as well as behavioral performances were obtained from these learners at two different times (pre- and post-training). We performed region of interest (ROI) and connectivity analyses to identify effective connectivity changes associated with success in second language word learning. We compared a learner group with a control group, and also examined the differences between successful learners and less successful learners within the learner group across the two time points. Our results indicated that (1) after training, learners and non-learners rely on different patterns of brain networks to process tonal and lexical information of target L2 words; (2) within the learner group, successful learners compared to less successful learners showed significant differences in language-related regions; and (3) successful learners compared to less successful learners showed a more coherent and integrated multi-path brain network. These results suggest that second language experience shapes neural changes in short-term training, and that analyses of these neural changes also reflect individual differences in learning success.

Using an audience response system to improve learning success in practical skills training courses in dental studies – a randomised, controlled cross‐over study

The aim of this study was to examine whether the use of an audience response system (ARS) in a high-quality study design, in a course in pre-clinical dentistry leads to an improvement in cognitive and psycho-motor performance. As part of the Phantom Course I, a randomised, controlled study in cross-over design with 63 students was conducted over 4weeks. The intervention was carried out by means of an ARS (TurningPoint(®) ), while a verbal question-and-answer session was conducted within the control group. Differences in learning success were determined via a formative multiple-choice (MC) test (cognitive) and a summative practical test (psycho-motor). Both groups achieved significantly better results in the MC tests with the use of the intervention, when compared with the control group (group A 11.6 vs. 9.5 and group B 13.7 vs. 12.1, maximum 16 points). A further analysis of the results showed that the overall effect was induced primarily by a marked improvement in below-average students. The practical tests showed no clear effect. Despite the careful selection and set-up of the conditions for the study in the regular course of the semester, a cohort effect emerged. This was due to varying degrees of performance between the two groups, because no adequate performance parameters were available, which could have been taken into account for the stratified randomisation. The results indicate that the use of the ARS leads to better results in cognitive performance, especially where independent learning is required and should be encouraged. Weaker students in particular seem to benefit.

Task-Based Core-Periphery Organization of Human Brain Dynamics

As a person learns a new skill, distinct synapses, brain regions, and circuits are engaged and change over time. In this paper, we develop methods to examine patterns of correlated activity across a large set of brain regions. Our goal is to identify properties that enable robust learning of a motor skill. We measure brain activity during motor sequencing and characterize network properties based on coherent activity between brain regions. Using recently developed algorithms to detect time-evolving communities, we find that the complex reconfiguration patterns of the brain's putative functional modules that control learning can be described parsimoniously by the combined presence of a relatively stiff temporal core that is composed primarily of sensorimotor and visual regions whose connectivity changes little in time and a flexible temporal periphery that is composed primarily of multimodal association regions whose connectivity changes frequently. The separation between temporal core and periphery changes over the course of training and, importantly, is a good predictor of individual differences in learning success. The core of dynamically stiff regions exhibits dense connectivity, which is consistent with notions of core-periphery organization established previously in social networks. Our results demonstrate that core-periphery organization provides an insightful way to understand how putative functional modules are linked. This, in turn, enables the prediction of fundamental human capacities, including the production of complex goal-directed behavior.

Training of tonal similarity ratings in non-musicians: a "rapid learning" approach.

Although cognitive music psychology has a long tradition of expert–novice comparisons, experimental training studies are rare. Studies on the learning progress of trained novices in hearing harmonic relationships are still largely lacking. This paper presents a simple training concept using the example of tone/triad similarity ratings, demonstrating the gradual progress of non-musicians compared to musical experts: In a feedback-based “rapid learning” paradigm, participants had to decide for single tones and chords whether paired sounds matched each other well. Before and after the training sessions, they provided similarity judgments for a complete set of sound pairs. From these similarity matrices, individual relational sound maps, intended to display mental representations, were calculated by means of non-metric multidimensional scaling (NMDS), and were compared to an expert model through procrustean transformation. Approximately half of the novices showed substantial learning success, with some participants even reaching the level of professional musicians. Results speak for a fundamental ability to quickly train an understanding of harmony, show inter-individual differences in learning success, and demonstrate the suitability of the scaling method used for learning research in music and other domains. Results are discussed in the context of the “giftedness” debate.