Negative Pragmatic Transfer in Bilinguals: Cross-Linguistic Influence in the Acquisition of Quantifiers.

Building on the cross-linguistic variability in the meaning of vague quantifiers, this study explores the potential for negative transfer in Italian-Slovenian bilinguals concerning the use of quantificational determiners, specifically the translational equivalents of the English "many", that is the Slovenian "precej" and "veliko". The aim is to identify relevant aspects of pragmatic knowledge for cross-linguistic influence. The study presents the results of a sentence-picture verification task in which Slovenian native speakers and Italian-Slovenian bilinguals evaluated sentences of the form "Quantifier X are Y" in relation to visual contexts. The results suggest that Italian learners of Slovenian, unlike Slovenian native speakers, fail to distinguish between "precej" and "veliko". This finding aligns with the negative transfer hypothesis. The study highlights the potential role of pragmatic knowledge in cross-linguistic transfer, particularly in the context of vague quantifiers.

Online Privacy-Preserving EEG Classification by Source-Free Transfer Learning.

Electroencephalogram (EEG) signals play an important role in brain-computer interface (BCI) applications. Recent studies have utilized transfer learning to assist the learning task in the new subject, i.e., target domain, by leveraging beneficial information from previous subjects, i.e., source domains. Nevertheless, EEG signals involve sensitive personal mental and health information. Thus, privacy concern becomes a critical issue. In addition, existing methods mostly assume that a portion of the new subject's data is available and perform alignment or adaptation between the source and target domains. However, in some practical scenarios, new subjects prefer prompt BCI utilization over the time-consuming process of collecting data for calibration and adaptation, which makes the above assumption difficult to hold. To address the above challenges, we propose Online Source-Free Transfer Learning (OSFTL) for privacy-preserving EEG classification. Specifically, the learning procedure contains offline and online stages. At the offline stage, multiple model parameters are obtained based on the EEG samples from multiple source subjects. OSFTL only needs access to these source model parameters to preserve the privacy of the source subjects. At the online stage, a target classifier is trained based on the online sequence of EEG instances. Subsequently, OSFTL learns a weighted combination of the source and target classifiers to obtain the final prediction for each target instance. Moreover, to ensure good transferability, OSFTL dynamically updates the transferred weight of each source domain based on the similarity between each source classifier and the target classifier. Comprehensive experiments on both simulated and real-world applications demonstrate the effectiveness of the proposed method, indicating the potential of OSFTL to facilitate the deployment of BCI applications outside of controlled laboratory settings.

Teach a man to fish: Hyper-brain evidence on scaffolding strategy enhancing creativity acquisition and transfer.

Creativity is an indispensable competency in today's innovation-driven society. Yet, the influences of instructional strategy, a key determinant of educational outcomes, on the creativity-fostering process remains an unresolved mystery. We proposed that instructional strategy affects creativity cultivation and further investigated the intricate neural mechanisms underlying this relationship. In a naturalistic laboratory setting, 66 instructor-learner dyads were randomized into three groups (scaffolding, explanation, and control), with divergent thinking instructions separately. Functional near-infrared spectroscopy (fNIRS) hyperscanning simultaneously collected brain signals in the prefrontal cortex and temporal-parietal junction regions. Results indicated that learners instructed with a scaffolding strategy demonstrated superior creative performance both in acquisition (direct learning) and transfer (use in a novel context) of creativity skills, compared to pretest levels. In contrast, the control and explanation groups did not exhibit such effects. Notably, we also observed remarkable interbrain neural synchronization (INS) between instructors and learners in the left superior frontal cortex in the scaffolding group, but not in the explanation or control groups. Furthermore, INS positively predicted enhancements in creativity performance (acquisition and transfer), indicating that it is a crucial neural mechanism in the creativity-fostering process. These findings reveal that scaffolding facilitates the acquisition and transfer of creativity and deepen our understanding of the neural mechanisms underlying the process of creativity-fostering. The current study provides valuable insights for implementing teaching strategies to fostering creativity.

Structural Learning Benefits in a Visuomotor Adaptation Task Generalize to a Contralateral Effector.

Structural learning is characterized by facilitated adaptation following training on a set of sensory perturbations all belonging to the same structure (e.g., 'visuomotor rotations'). This generalization of learning is a core feature of the motor system and is often studied in the context of interlimb transfer. However, such transfer has only been demonstrated when participants learn to counter a specific perturbation in the sensory feedback of their movements; we determined whether structural learning in one limb generalized to the contralateral limb. We trained 13 participants to counter random visual feedback rotations between +/-90 degrees with the right hand and subsequently tested the left hand on a fixed rotation. The structural training group showed faster adaptation in the left hand in both feedforward and feedback components of reaching compared to 13 participants who trained with veridical reaching, with lower initial reaching error, and straighter, faster, and smoother movements than in the control group. The transfer was ephemeral - benefits were confined to roughly the first 20 trials. The results demonstrate that the motor system can extract invariant properties of seemingly random environments in one limb, and that this information can be accessed by the contralateral limb.

Unraveling the influence of Pavlovian cues on decision-making: A pre-registered meta-analysis on Pavlovian-to-instrumental transfer.

Amidst the replicability crisis, promoting transparency and rigor in research becomes imperative. The Pavlovian-to-Instrumental Transfer (PIT) paradigm is increasingly used in human studies to offer insights into how Pavlovian cues, by anticipating rewards or punishments, influence decision-making and potentially contribute to the development of clinical conditions. However, research on this topic faces challenges, including methodological variability and the need for standardized approaches, which can undermine the quality and robustness of experimental findings. Hence, we conducted a meta-analysis to unravel the methodological, task-related, individual, training, and learning factors that can modulate PIT. By scrutinizing these factors, the present meta-analysis reviews the current literature on human PIT, provides practical guidelines for future research to enhance study outcomes and refine methodologies, and identifies knowledge gaps that can serve as a direction for future studies aiming to advance the comprehension of how Pavlovian cues shape decision-making.

Compulsive avoidance in youths and adults with OCD: an aversive pavlovian-to-instrumental transfer study.

Compulsive behaviour may often be triggered by Pavlovian cues. Assessing how Pavlovian cues drive instrumental behaviour in obsessive-compulsive disorder (OCD) is therefore crucial to understand how compulsions develop and are maintained. An aversive Pavlovian-to-Instrumental transfer (PIT) paradigm, particularly one involving avoidance/cancellation of negative outcomes, can enable such investigation and has not previously been studied in clinical-OCD. Forty-one participants diagnosed with OCD (21 adults; 20 youths) and 44 controls (21 adults; 23 youths) completed an aversive PIT task. Participants had to prevent the delivery of unpleasant noises by moving a joystick in the correct direction. They could infer these correct responses by learning appropriate response-outcome (instrumental) and stimulus-outcome (Pavlovian) associations. We then assessed whether Pavlovian cues elicited specific instrumental avoidance responses (specific PIT) and induced general instrumental avoidance (general PIT). We investigated whether task learning and confidence indices influenced PIT strength differentially between groups. There was no overall group difference in PIT performance, although youths with OCD showed weaker specific PIT than youth controls. However, urge to avoid unpleasant noises and preference for safe over unsafe stimuli influenced specific and general PIT respectively in OCD, while PIT in controls was more influenced by confidence in instrumental and Pavlovian learning. Thus, in OCD, implicit motivational factors, but not learnt knowledge, may contribute to the successful integration of aversive Pavlovian and instrumental cues. This implies that compulsive avoidance may be driven by these automatic processes. Youths with OCD show deficits in specific PIT, suggesting cue integration impairments are only apparent in adolescence. These findings may be clinically relevant as they emphasise the importance of targeting such implicit motivational processes when treating OCD.

Transfer of visual perceptual learning over a task-irrelevant feature through feature-invariant representations: Behavioral experiments and model simulations.

A large body of literature has examined specificity and transfer of perceptual learning, suggesting a complex picture. Here, we distinguish between transfer over variations in a "task-relevant" feature (e.g., transfer of a learned orientation task to a different reference orientation) and transfer over a "task-irrelevant" feature (e.g., transfer of a learned orientation task to a different retinal location or different spatial frequency), and we focus on the mechanism for the latter. Experimentally, we assessed whether learning a judgment of one feature (such as orientation) using one value of an irrelevant feature (e.g., spatial frequency) transfers to another value of the irrelevant feature. Experiment 1 examined whether learning in eight-alternative orientation identification with one or multiple spatial frequencies transfers to stimuli at five different spatial frequencies. Experiment 2 paralleled Experiment 1, examining whether learning in eight-alternative spatial-frequency identification at one or multiple orientations transfers to stimuli with five different orientations. Training the orientation task with a single spatial frequency transferred widely to all other spatial frequencies, with a tendency to specificity when training with the highest spatial frequency. Training the spatial frequency task fully transferred across all orientations. Computationally, we extended the identification integrated reweighting theory (I-IRT) to account for the transfer data (Dosher, Liu, & Lu, 2023; Liu, Dosher, & Lu, 2023). Just as location-invariant representations in the original IRT explain transfer over retinal locations, incorporating feature-invariant representations effectively accounted for the observed transfer. Taken together, we suggest that feature-invariant representations can account for transfer of learning over a "task-irrelevant" feature.

Post-stroke hand gesture recognition via one-shot transfer learning using prototypical networks.

BACKGROUND: In-home rehabilitation systems are a promising, potential alternative to conventional therapy for stroke survivors. Unfortunately, physiological differences between participants and sensor displacement in wearable sensors pose a significant challenge to classifier performance, particularly for people with stroke who may encounter difficulties repeatedly performing trials. This makes it challenging to create reliable in-home rehabilitation systems that can accurately classify gestures. METHODS: Twenty individuals who suffered a stroke performed seven different gestures (mass flexion, mass extension, wrist volar flexion, wrist dorsiflexion, forearm pronation, forearm supination, and rest) related to activities of daily living. They performed these gestures while wearing EMG sensors on the forearm, as well as FMG sensors and an IMU on the wrist. We developed a model based on prototypical networks for one-shot transfer learning, K-Best feature selection, and increased window size to improve model accuracy. Our model was evaluated against conventional transfer learning with neural networks, as well as subject-dependent and subject-independent classifiers: neural networks, LGBM, LDA, and SVM. RESULTS: Our proposed model achieved 82.2% hand-gesture classification accuracy, which was better (P<0.05) than one-shot transfer learning with neural networks (63.17%), neural networks (59.72%), LGBM (65.09%), LDA (63.35%), and SVM (54.5%). In addition, our model performed similarly to subject-dependent classifiers, slightly lower than SVM (83.84%) but higher than neural networks (81.62%), LGBM (80.79%), and LDA (74.89%). Using K-Best features improved the accuracy in 3 of the 6 classifiers used for evaluation, while not affecting the accuracy in the other classifiers. Increasing the window size improved the accuracy of all the classifiers by an average of 4.28%. CONCLUSION: Our proposed model showed significant improvements in hand-gesture recognition accuracy in individuals who have had a stroke as compared with conventional transfer learning, neural networks and traditional machine learning approaches. In addition, K-Best feature selection and increased window size can further improve the accuracy. This approach could help to alleviate the impact of physiological differences and create a subject-independent model for stroke survivors that improves the classification accuracy of wearable sensors. TRIAL REGISTRATION NUMBER: The study was registered in Chinese Clinical Trial Registry with registration number CHiCTR1800017568 in 2018/08/04.

Limited training and transfer effects in older and young adults who participated in 12 sessions of process-based working memory training. A three-armed pretest-posttest design study.

OBJECTIVE: Numerous studies confirm the effectiveness of cognitive training in older adults. However, there is limited evidence of the transfer occurrence. The part of the study presented here tested the effect of 12 process-based working memory training sessions on the performance of the trained task (training effect) and other cognitive tasks (transfer effect). A pretest-posttest study design with one experimental group and two control (passive and active) groups. The sample comprised three groups of older adults: experimental (n = 25), passive control (n = 22), active control (n = 7), and young adults: experimental (n = 25), passive control (n = 25), and active control (n = 12). The study was registered after completion with a ClinicalTrials.gov Identifier: NCT06235840 on 31 January 2024. RESULTS: Under the influence of training, the performance of the trained task improved significantly, but only in young adults. Transfer of WM training effects was not revealed. Among young adults, a testing effect was observed for the indicator of attentional focus and psychomotor speed. Moreover, the obtained results suggest the transfer from practice in multi-domain training, implemented in the active control group, to tasks that require the use of fluid intelligence. However, this finding should be interpreted with great caution due to the small size of active control groups.

A cross-dataset adaptive domain selection transfer learning framework for motor imagery-based brain-computer interfaces.

Objective. In brain-computer interfaces (BCIs) that utilize motor imagery (MI), minimizing calibration time has become increasingly critical for real-world applications. Recently, transfer learning (TL) has been shown to effectively reduce the calibration time in MI-BCIs. However, variations in data distribution among subjects can significantly influence the performance of TL in MI-BCIs.Approach.We propose a cross-dataset adaptive domain selection transfer learning framework that integrates domain selection, data alignment, and an enhanced common spatial pattern (CSP) algorithm. Our approach uses a huge dataset of 109 subjects as the source domain. We begin by identifying non-BCI illiterate subjects from this huge dataset, then determine the source domain subjects most closely aligned with the target subjects using maximum mean discrepancy. After undergoing Euclidean alignment processing, features are extracted by multiple composite CSP. The final classification is carried out using the support vector machine.Main results.Our findings indicate that the proposed technique outperforms existing methods, achieving classification accuracies of 75.05% and 76.82% in two cross-dataset experiments, respectively.Significance.By reducing the need for extensive training data, yet maintaining high accuracy, our method optimizes the practical implementation of MI-BCIs.

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.

Stimulating prefrontal cortex facilitates training transfer by increasing representational overlap.

A recent hypothesis characterizes difficulties in multitasking as being the price humans pay for our ability to generalize learning across tasks. The mitigation of these costs through training has been associated with reduced overlap of constituent task representations within frontal, parietal, and subcortical regions. Transcranial direct current stimulation, which can modulate functional brain activity, has shown promise in generalizing performance gains when combined with multitasking training. However, the relationship between combined transcranial direct current stimulation and training protocols with task-associated representational overlap in the brain remains unexplored. Here, we paired prefrontal cortex transcranial direct current stimulation with multitasking training in 178 individuals and collected functional magnetic resonance imaging data pre- and post-training. We found that 1 mA transcranial direct current stimulation applied to the prefrontal cortex paired with multitasking training enhanced training transfer to spatial attention, as assessed via a visual search task. Using machine learning to assess the overlap of neural activity related to the training task in task-relevant brain regions, we found that visual search gains were predicted by changes in classification accuracy in frontal, parietal, and cerebellar regions for participants that received left prefrontal cortex stimulation. These findings demonstrate that prefrontal cortex transcranial direct current stimulation may interact with training-related changes to task representations, facilitating the generalization of learning.

Implicit visuospatial sequence representations are accessible in both the practice and the transfer hand.

A serial reaction time task was used to test whether the representations of a probabilistic second-order sequence structure are (i) stored in an effector-dependent, effector-independent intrinsic or effector-independent visuospatial code and (ii) are inter-manually accessible. Participants were trained either with the dominant or non-dominant hand. Tests were performed with both hands in the practice sequence, a random sequence, and a mirror sequence. Learning did not differ significantly between left and right-hand practice, suggesting symmetric intermanual transfer from the dominant to the non-dominant hand and vice versa. In the posttest, RTs were shorter for the practice sequence than for the random sequence, and longest for the mirror sequence. Participants were unable to freely generate or recognize the practice sequence, indicating implicit knowledge of the probabilistic sequence structure. Because sequence-specific learning did not differ significantly between hands, we conclude that representations of the probabilistic sequence structure are stored in an effector-independent visuospatial code.

The effect of tDCS on inhibitory control and its transfer effect on sustained attention in children with autism spectrum disorder: An fNIRS study.

BACKGROUND: Individuals with autism spectrum disorder (ASD) have inhibitory control deficits. The combination of transcranial direct current stimulation (tDCS) and inhibitory control training produces good transfer effects and improves neuroplasticity. However, no studies have explored whether applying tDCS over the dlPFC improves inhibitory control and produces transfer effects in children with ASD. OBJECTIVE: To explore whether multisession tDCS could enhance inhibitory control training (response inhibition), near-transfer (interference control) and far-transfer effects (sustained attention; stability of attention) in children with ASD and the generalizability of training effects in daily life and the class, as reflected by behavioral performance and neural activity measured by functional near-infrared spectroscopy (fNIRS). METHODS: Twenty-eight autistic children were randomly assigned to either the true or sham tDCS group. The experimental group received bifrontal tDCS stimulation at 1.5 mA, administered for 15 min daily across eight consecutive days. tDCS was delivered during a computerized Go/No-go training task. Behavioral performance in terms of inhibitory control (Dog/Monkey and Day/Night Stroop tasks), sustained attention (Continuous Performance and Cancellation tests), prefrontal cortex (PFC) neural activity and inhibitory control and sustained attention in the class and at home were evaluated. RESULTS: Training (response inhibition) and transfer effects (interference control; sustained attention) were significantly greater after receiving tDCS during the Go/No-go training task than after receiving sham tDCS. Changes in oxyhemoglobin (HbO) concentrations in the dlPFC and FPA associated with consistent conditions in the Day/Night Stroop and Continuous Performance test were observed after applying tDCS during the inhibitory control training task. Notably, transfer effects can be generalized to classroom environments. CONCLUSION: Inhibitory control training combined with tDCS may be a promising, safe, and effective method for improving inhibitory control and sustained attention in children with ASD.

Transfer of statistical learning between tasks.

Recent studies have shown that observers can learn to suppress locations in the visual field with a high distractor probability. Here, we investigated whether this learned suppression resulting from a spatial distractor imbalance transfers to a completely different search task that does not contain any distractors. Observers performed the additional singleton task and learned to suppress the location that was likely to contain a color singleton distractor. Within a block, the additional singleton task would randomly switch to a T-among-L task where observers searched in parallel (Experiment 1) or serially (Experiment 2) for a T among Ls. The upcoming search was either unpredictable (Experiment 1/2A) or cued (Experiment 1/2B). The results show that there was transfer of learning from one to the other task as the learned suppression stayed in place after the switch regardless of whether the T-among-L task was performed via parallel or serial search. Moreover, cueing that the task would switch had no effect on performance. The current findings indicate that implicit learned biases are rather inflexible and remain in place even when the task and the required search strategy are dramatically different and even when participants can anticipate that a change in the search required is imminent. This transfer of the suppression to a different task is consistent with the notion that suppression is proactively applied. Because the location is already suppressed proactively, that is, before display onset, regardless which display and task is presented, the suppressed location competes less for attention than all other locations. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Youth-like brain activation linked with greater cognitive training gains in older adults: Insights from the ACTOP study.

This study investigates the relationship between inter-individual neurofunctional differences in older adults and cognitive training efficacy, with a specific focus on the association between youth-like task-related brain activation and improvements in working memory (WM) training. The data is part of the Attentional Control Training for Older People (ACTOP) study, 30 older adults completed 12 half-hour WM training sessions. The WM performance slope, assessed at the conclusion of sessions 1 through 6 and sessions 7 to 12, determined early- and late-stage training gains, respectively. Transfer measures were taken before (PRE), midway (MID), and after (POST) training, and the differences in MID-PRE and POST-MID on transfer tasks were used to determine early- and late-stage transfer effects, respectively. The Goodness of Fit (GOF) metric was used to quantify the similarity between each older adult's activation pattern, as measured with functional magnetic resonance imaging (fMRI), to that of a group of younger adults. GOF scores were calculated for activation during low-load (1-0back) and high-load (2-0back) N-back tasks. The results indicated that larger GOF scores in the low-load condition were associated with greater training gains in both the early and late learning stages, and that larger GOF scores in the high-load condition were associated with greater training gains during the late-stage. These findings suggest that a youth-like brain activation pattern in older adults is associated with greater cognitive training benefits, underscoring the role of inter-individual neurofunctional differences to account for variations in training outcomes among older adults. TRIAL REGISTRATION: ClinicalTrials.gov NCT03532113; https://clinicaltrials.gov/ct2/show/NCT03532113.

Attention control training and transfer effects on cognitive tasks.

Attention control is the common element underlying different executive functions. The backward Masking Majority Function Task (MFT-M) requires intensive attention control, and represents a diverse situation where attentional resources need to be allocated dynamically and flexibly to reduce uncertainty. Aiming to train attention control using MFT-M and examine the training transfer effects in various executive functions, we recruited healthy young adults (n = 84) and then equally randomized them into two groups trained with either MFT-M or a sham program for seven consecutive days. Cognitive evaluations were conducted before and after the training, and the electroencephalograph (EEG) signals were recorded for the revised Attention Network Test (ANT-R), N-back, and Task-switching (TS) tasks. Compared to the control group, the training group performed better on the congruent condition of Flanker and the double-congruency condition of Flanker and Location in the ANT-R task, and on the learning trials in the verbal memory test. The training group also showed a larger P2 amplitude decrease and P3 amplitude increase in the 2-back task and a larger P3 amplitude increase in the TS task's repeat condition than the control group, indicating improved neural efficiency in two tasks' attentional processes. Introversion moderated the transfer effects of training, as indicated by the significant group*introversion interactions on the post-training 1-back efficiency and TS switching cost. Our results suggested that attention control training with the MFT-M showed a broad transfer scope, and the transfer effect was influenced by the form of training task. Introversion facilitated the transfer to working memory and hindered the transfer to flexibility.

Between-task transfer of item-specific control is replicable and extends to novel conditions.

Learning-guided control refers to adjustments of cognitive control settings based on learned associations between predictive cues and the likelihood of conflict. In three preregistered experiments, we examined transfer of item-specific control settings beyond conditions under which they were learned. In Experiment 1, an item-specific proportion congruence (ISPC) manipulation was applied in a training phase in which target color in a Flanker task was biased (mostly congruent or mostly incongruent). In a subsequent transfer phase, participants performed a color-word Stroop task in which the same target colors were unbiased (50% congruent). The same design was implemented in Experiment 2, but training and transfer tasks were intermixed within blocks. Between-task transfer was evidenced in both experiments, suggesting learned control settings associated with the predictive cues were retrieved when encountering unbiased transfer items. In Experiment 3, we investigated a farther version of between-task transfer by using training (color-word Stroop) and transfer (picture-word Stroop) tasks that did not share the relevant (to-be-named) dimension or response sets. Despite the stronger, between-task boundary, we observed an ISPC effect for the transfer items, but it did not emerge until the second half of the experiment. The results provided converging evidence for the flexibility and automaticity of item-specific control. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Training semantic long-term memory retrieval transfers to executive function and reading fluency.

The retrieval of information from long-term memory is a fundamental cognitive ability, crucial for most aspects of successful human functioning. Whether and how long-term memory retrieval (LTMR) can be improved with training has clear societal importance but also theoretical value for furthering our understanding of underlying mechanisms. Here, we provide electrophysiological evidence for the plasticity of semantic LTMR. Thirty-five university students were randomly assigned to adaptive semantic LTMR training (using a Posner task) or to a non-adaptive version of the training. Before and after training they were assessed on measures of semantic LTMR, working memory, central executive function (interference control, switching), reading fluency, and fluid intelligence. Adaptive LTMR training (relative to non-adaptive training) led to significant improvements in semantic LTMR. The intervention group (in contrast to the control group) also showed a significant reduction in the mean amplitude of the N400 ERP component and 700-1000 ms measured during a semantic LTMR task, suggesting that changes in retrieval occurred at an early/automatic point and retrieval processing in semantic processing. Moreover, transfer effects were observed for switching, working memory and reading fluency, but not for interference control or fluid intelligence. These results point to the plasticity of semantic LTMR, and suggest that improvement in this ability can transfer to other domains for which LTMR is key.

Dual-Task and Single-Task Practice Does Not Influence the Attentional Demands of Movement Sequence Representations.

This study examined the attentional demands of movement sequence representations at different temporal points after single- or dual-task practice. The visual-spatial representation encodes the movement based on visual-spatial coordinates such as the target locations. The motor representation encodes the movement in motor coordinates including joint angles and muscle activation patterns. Participants were randomly assigned to a single-task or dual-task practice group. Following acquisition, participants performed two retention tests and inter-manual transfer tests, both under dual-task and single-task. The transfer tests consisted of a mirror and non-mirror test and examined motor and visual-spatial representation development. The main finding is that attentional demands of the sequence representations were not affected by the practice condition. However, movement initiation requires more attention than the end of the movement in both representations.