Task‐specific strength increases after lower‐limb compound resistance training occurred in the absence of corticospinal changes in vastus lateralis

Neural adaptations subserving strength increases have been shown to be task‐specific, but responses and adaptation to lower‐limb compound exercises such as the squat are commonly assessed in a single‐limb isometric task. This two‐part study assessed neuromuscular responses to an acute bout (Study A) and 4 weeks (Study B) of squat resistance training at 80% of one‐repetition‐maximum, with measures taken during a task‐specific isometric squat (IS) and non‐specific isometric knee extension (KE). Eighteen healthy volunteers (25 ± 5 years) were randomised into either a training (n = 10) or a control (n = 8) group. Neural responses were evoked at the intracortical, corticospinal and spinal levels, and muscle thickness was assessed using ultrasound. The results of Study A showed that the acute bout of squat resistance training decreased maximum voluntary contraction (MVC) for up to 45 min post‐exercise (−23%, P < 0.001). From 15–45 min post‐exercise, spinally evoked responses were increased in both tasks (P = 0.008); however, no other evoked responses were affected (P ≥ 0.240). Study B demonstrated that following short‐term resistance training, participants improved their one repetition maximum squat (+35%, P < 0.001), which was reflected by a task‐specific increase in IS MVC (+49%, P = 0.001), but not KE (+1%, P = 0.882). However, no training‐induced changes were observed in muscle thickness (P = 0.468) or any evoked responses (P = 0.141). Adjustments in spinal motoneuronal excitability are evident after acute resistance training. After a period of short‐term training, there were no changes in the responses to central nervous system stimulation, which suggests that alterations in corticospinal properties of the vastus lateralis might not contribute to increases in strength

Discriminative Training of Deep Fully-connected Continuous CRF with Task-specific Loss

Recent works on deep conditional random fields (CRF) have set new records on many vision tasks involving structured predictions. Here we propose a fully-connected deep continuous CRF model for both discrete and continuous labelling problems. We exemplify the usefulness of the proposed model on multi-class semantic labelling (discrete) and the robust depth estimation (continuous) problems. In our framework, we model both the unary and the pairwise potential functions as deep convolutional neural networks (CNN), which are jointly learned in an end-to-end fashion. The proposed method possesses the main advantage of continuously-valued CRF, which is a closed-form solution for the Maximum a posteriori (MAP) inference. To better adapt to different tasks, instead of using the commonly employed maximum likelihood CRF parameter learning protocol, we propose task-specific loss functions for learning the CRF parameters. It enables direct optimization of the quality of the MAP estimates during the course of learning. Specifically, we optimize the multi-class classification loss for the semantic labelling task and the Turkey's biweight loss for the robust depth estimation problem. Experimental results on the semantic labelling and robust depth estimation tasks demonstrate that the proposed method compare favorably against both baseline and state-of-the-art methods. In particular, we show that although the proposed deep CRF model is continuously valued, with the equipment of task-specific loss, it achieves impressive results even on discrete labelling tasks

Working Memory Training for Healthy Older Adults: The Role of Individual Characteristics in Explaining Short- and Long-Term Gains

Objective: The aim of the present study was to explore whether individual characteristics such as age, education, vocabulary, and baseline performance in a working memory (WM) task\u2014similar to the one used in the training (criterion task)\u2014predict the short- and long-term specific gains and transfer effects of a verbal WM training for older adults. Method: Four studies that adopted the Borella et al. (2010) verbal WM training procedure were found eligible for our analysis as they included: healthy older adults who attended either the training sessions (WM training group), or alternative activities (active control group); the same measures for assessing specific gains (on the criterion WM task), and transfer effects (nearest on a visuo-spatial WM task, near on short-term memory tasks and far on a measure of fluid intelligence, a measure of processing speed and two inhibitory measures); and a follow-up session. Results: Linear mixed models confirmed the overall efficacy of the training, in the short-term at least, and some maintenance effects. In the trained group, the individual characteristics considered were found to contribute (albeit only modestly in some cases) to explaining the effects of the training. Conclusions: Overall, our findings suggest the importance of taking individual characteristics and individual differences into account when examining WMtraining gains in older adults

Does repetitive task training improve functional activity after stroke? A Cochrane systematic review and meta-analysis.

Repetitive task training resulted in modest improvement across a range of lower limb outcome measures, but not upper limb outcome measures. Training may be sufficient to have a small impact on activities of daily living. Interventions involving elements of repetition and task training are diverse and difficult to classify: the results presented are specific to trials where both elements are clearly present in the intervention, without major confounding by other potential mechanisms of action

Post-training load-related changes of auditory working memory: An EEG study

Working memory (WM) refers to the temporary retention and manipulation of information, and its capacity is highly susceptible to training. Yet, the neural mechanisms that allow for increased performance under demanding conditions are not fully understood. We expected that post-training efficiency in WM performance modulates neural processing during high load tasks. We tested this hypothesis, using electroencephalography (EEG) (N = 39), by comparing source space spectral power of healthy adults performing low and high load auditory WM tasks. Prior to the assessment, participants either underwent a modality-specific auditory WM training, or a modality-irrelevant tactile WM training, or were not trained (active control). After a modality-specific training participants showed higher behavioral performance, compared to the control. EEG data analysis revealed general effects of WM load, across all training groups, in the theta-, alpha-, and beta-frequency bands. With increased load theta-band power increased over frontal, and decreased over parietal areas. Centro-parietal alpha-band power and central beta-band power decreased with load. Interestingly, in the high load condition a tendency toward reduced beta-band power in the right medial temporal lobe was observed in the modality-specific WM training group compared to the modality-irrelevant and active control groups. Our finding that WM processing during the high load condition changed after modality-specific WM training, showing reduced beta-band activity in voice-selective regions, possibly indicates a more efficient maintenance of task-relevant stimuli. The general load effects suggest that WM performance at high load demands involves complementary mechanisms, combining a strengthening of task-relevant and a suppression of task-irrelevant processing

Visual information transfer. Part 1: Assessment of specific information needs. Part 2: Parameters of appropriate instrument scanning behavior

The present study explored eye scan behavior as a function of level of subject training. Oculometric (eye scan) measures were recorded from each of ten subjects during training trials on a CRT based flight simulation task. The task developed for the study incorporated subtasks representative of specific activities performed by pilots, but which could be performed at asymptotic levels within relatively short periods of training. Changes in eye scan behavior were examined as initially untrained subjects developed skill in the task. Eye scan predictors of performance on the task were found. Examination of eye scan in proximity to selected task events revealed differences in the distribution of looks at the instruments as a function of level of training