Error Sonification of a Complex Motor Task

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Riener Robert

2011-12-01

Full Text Available Visual information is mainly used to master complex motor tasks. Thus, additional information providing augmented feedback should be displayed in other modalities than vision, e.g. hearing. The present work evaluated the potential of error sonification to enhance learning of a rowing-type motor task. In contrast to a control group receiving self-controlled terminal feedback, the experimental group could not significantly reduce spatial errors. Thus, motor learning was not enhanced by error sonification, although during the training the participant could benefit from it. It seems that the motor task was too slow, resulting in immediate corrections of the movement rather than in an internal representation of the general characteristics of the motor task. Therefore, further studies should elaborate the impact of error sonification when general characteristics of the motor tasks are already known.

The Applicability of Rhythm-Motor Tasks to a New Dual Task Paradigm for Older Adults

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Soo Ji Kim

2017-12-01

Full Text Available Given the interplay between cognitive and motor functions during walking, cognitive demands required during gait have been investigated with regard to dual task performance. Along with the needs to understand how the type of concurrent task while walking affects gait performance, there are calls for diversified dual tasks that can be applied to older adults with varying levels of cognitive decline. Therefore, this study aimed to examine how rhythm-motor tasks affect dual task performance and gait control, compared to a traditional cognitive-motor task. Also, it examined whether rhythm-motor tasks are correlated with traditional cognitive-motor task performance and cognitive measures. Eighteen older adults without cognitive impairment participated in this study. Each participant was instructed to walk at self-paced tempo without performing a concurrent task (single walking task and walk while separately performing two types of concurrent tasks: rhythm-motor and cognitive-motor tasks. Rhythm-motor tasks included instrument playing (WalkIP, matching to rhythmic cueing (WalkRC, and instrument playing while matching to rhythmic cueing (WalkIP+RC. The cognitive-motor task involved counting forward by 3s (WalkCount.f3. In each condition, dual task costs (DTC, a measure for how dual tasks affect gait parameters, were measured in terms of walking speed and stride length. The ratio of stride length to walking speed, a measure for dynamic control of gait, was also examined. The results of this study demonstrated that the task type was found to significantly influence these measures. Rhythm-motor tasks were found to interfere with gait parameters to a lesser extent than the cognitive-motor task (WalkCount.f3. In terms of ratio measures, stride length remained at a similar level, walking speed greatly decreased in the WalkCount.f3 condition. Significant correlations between dual task-related measures during rhythm-motor and cognitive-motor tasks support the

In Vivo Neuromechanics: Decoding Causal Motor Neuron Behavior with Resulting Musculoskeletal Function.

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Sartori, Massimo; Yavuz, Utku Ş; Farina, Dario

2017-10-18

Human motor function emerges from the interaction between the neuromuscular and the musculoskeletal systems. Despite the knowledge of the mechanisms underlying neural and mechanical functions, there is no relevant understanding of the neuro-mechanical interplay in the neuro-musculo-skeletal system. This currently represents the major challenge to the understanding of human movement. We address this challenge by proposing a paradigm for investigating spinal motor neuron contribution to skeletal joint mechanical function in the intact human in vivo. We employ multi-muscle spatial sampling and deconvolution of high-density fiber electrical activity to decode accurate α-motor neuron discharges across five lumbosacral segments in the human spinal cord. We use complete α-motor neuron discharge series to drive forward subject-specific models of the musculoskeletal system in open-loop with no corrective feedback. We perform validation tests where mechanical moments are estimated with no knowledge of reference data over unseen conditions. This enables accurate blinded estimation of ankle function purely from motor neuron information. Remarkably, this enables observing causal associations between spinal motor neuron activity and joint moment control. We provide a new class of neural data-driven musculoskeletal modeling formulations for bridging between movement neural and mechanical levels in vivo with implications for understanding motor physiology, pathology, and recovery.

Decoding intention at sensorimotor timescales.

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Mathew Salvaris

Full Text Available The ability to decode an individual's intentions in real time has long been a 'holy grail' of research on human volition. For example, a reliable method could be used to improve scientific study of voluntary action by allowing external probe stimuli to be delivered at different moments during development of intention and action. Several Brain Computer Interface applications have used motor imagery of repetitive actions to achieve this goal. These systems are relatively successful, but only if the intention is sustained over a period of several seconds; much longer than the timescales identified in psychophysiological studies for normal preparation for voluntary action. We have used a combination of sensorimotor rhythms and motor imagery training to decode intentions in a single-trial cued-response paradigm similar to those used in human and non-human primate motor control research. Decoding accuracy of over 0.83 was achieved with twelve participants. With this approach, we could decode intentions to move the left or right hand at sub-second timescales, both for instructed choices instructed by an external stimulus and for free choices generated intentionally by the participant. The implications for volition are considered.

Performance in complex motor tasks deteriorates in hyperthermic humans

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Piil, Jacob Feder; Lundbye-Jensen, Jesper; Trangmar, Steven J

2017-01-01

-motor tracking performance was reduced by 10.7 ± 6.5% following exercise-induced hyperthermia when integrated in the multipart protocol and 4.4 ± 5.7% when tested separately (bothP 1.3% (P math tasks...... of information or decision-making prior to responding. We hypothesized that divergences could relate to task complexity and developed a protocol consisting of 1) simple motor task [TARGET_pinch], 2) complex motor task [Visuo-motor tracking], 3) simple math task [MATH_type], 4) combined motor-math task [MATH...

Motor-cognitive dual-task performance: effects of a concurrent motor task on distinct components of visual processing capacity.

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Künstler, E C S; Finke, K; Günther, A; Klingner, C; Witte, O; Bublak, P

2018-01-01

Dual tasking, or the simultaneous execution of two continuous tasks, is frequently associated with a performance decline that can be explained within a capacity sharing framework. In this study, we assessed the effects of a concurrent motor task on the efficiency of visual information uptake based on the 'theory of visual attention' (TVA). TVA provides parameter estimates reflecting distinct components of visual processing capacity: perceptual threshold, visual processing speed, and visual short-term memory (VSTM) storage capacity. Moreover, goodness-of-fit values and bootstrapping estimates were derived to test whether the TVA-model is validly applicable also under dual task conditions, and whether the robustness of parameter estimates is comparable in single- and dual-task conditions. 24 subjects of middle to higher age performed a continuous tapping task, and a visual processing task (whole report of briefly presented letter arrays) under both single- and dual-task conditions. Results suggest a decline of both visual processing capacity and VSTM storage capacity under dual-task conditions, while the perceptual threshold remained unaffected by a concurrent motor task. In addition, goodness-of-fit values and bootstrapping estimates support the notion that participants processed the visual task in a qualitatively comparable, although quantitatively less efficient way under dual-task conditions. The results support a capacity sharing account of motor-cognitive dual tasking and suggest that even performing a relatively simple motor task relies on central attentional capacity that is necessary for efficient visual information uptake.

Economic decision-making compared with an equivalent motor task.

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Wu, Shih-Wei; Delgado, Mauricio R; Maloney, Laurence T

2009-04-14

There is considerable evidence that human economic decision-making deviates from the predictions of expected utility theory (EUT) and that human performance conforms to EUT in many perceptual and motor decision tasks. It is possible that these results reflect a real difference in decision-making in the 2 domains but it is also possible that the observed discrepancy simply reflects typical differences in experimental design. We developed a motor task that is mathematically equivalent to choosing between lotteries and used it to compare how the same subject chose between classical economic lotteries and the same lotteries presented in equivalent motor form. In experiment 1, we found that subjects are more risk seeking in deciding between motor lotteries. In experiment 2, we used cumulative prospect theory to model choice and separately estimated the probability weighting functions and the value functions for each subject carrying out each task. We found no patterned differences in how subjects represented outcome value in the motor and the classical tasks. However, the probability weighting functions for motor and classical tasks were markedly and significantly different. Those for the classical task showed a typical tendency to overweight small probabilities and underweight large probabilities, and those for the motor task showed the opposite pattern of probability distortion. This outcome also accounts for the increased risk-seeking observed in the motor tasks of experiment 1. We conclude that the same subject distorts probability, but not value, differently in making identical decisions in motor and classical form.

Association Between Gross-Motor and Executive Function Depends on Age and Motor Task Complexity

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Spedden, Meaghan E; Malling, Anne Sofie B; Andersen, Ken K

2017-01-01

The objective was to examine associations between motor and executive function across the adult lifespan and to investigate the role of motor complexity in these associations. Young, middle-aged and older adults (n = 82; 19-83y) performed two gross-motor tasks with different levels of complexity...... and a Stroop-like computer task. Performance was decreased in older adults. The association between motor and cognitive performance was significant for older adults in the complex motor task (p = 0.03, rs = -0.41), whereas no significant associations were found for young or middle-aged groups, suggesting...... that the link between gross-motor and executive function emerges with age and depends on motor complexity....

An information-theoretic approach to motor action decoding with a reconfigurable parallel architecture.

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Craciun, Stefan; Brockmeier, Austin J; George, Alan D; Lam, Herman; Príncipe, José C

2011-01-01

Methods for decoding movements from neural spike counts using adaptive filters often rely on minimizing the mean-squared error. However, for non-Gaussian distribution of errors, this approach is not optimal for performance. Therefore, rather than using probabilistic modeling, we propose an alternate non-parametric approach. In order to extract more structure from the input signal (neuronal spike counts) we propose using minimum error entropy (MEE), an information-theoretic approach that minimizes the error entropy as part of an iterative cost function. However, the disadvantage of using MEE as the cost function for adaptive filters is the increase in computational complexity. In this paper we present a comparison between the decoding performance of the analytic Wiener filter and a linear filter trained with MEE, which is then mapped to a parallel architecture in reconfigurable hardware tailored to the computational needs of the MEE filter. We observe considerable speedup from the hardware design. The adaptation of filter weights for the multiple-input, multiple-output linear filters, necessary in motor decoding, is a highly parallelizable algorithm. It can be decomposed into many independent computational blocks with a parallel architecture readily mapped to a field-programmable gate array (FPGA) and scales to large numbers of neurons. By pipelining and parallelizing independent computations in the algorithm, the proposed parallel architecture has sublinear increases in execution time with respect to both window size and filter order.

Dual-Task Walking in Challenging Environments in People with Stroke: Cognitive-Motor Interference and Task Prioritization

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Celine Timmermans

2018-01-01

Full Text Available Cognitive-motor interference may contribute to the risk of falling in people with stroke, as may be the associated phenomenon of inappropriate task prioritization. Examining dual-task walking could provide valuable insights as to how to best evaluate and treat walking in people with stroke. This study aimed to examine the effect of different walking environments on cognitive-motor interference and task prioritization in dual-task walking in people with stroke. Using a repeated-measures design, cognitive-motor interference and task prioritization were assessed in 30 stroke survivors, while walking in a plain environment and in two challenging environments that were enriched with either stationary physical context or suddenly appearing projector-augmented context. All three walking environment conditions were performed with and without a concurrent serial-3 subtraction task. We found stronger cognitive-motor interference for the two challenging environments than for the plain walking environment. Cognitive-motor interference did not differ between challenging walking environments, but task prioritization did: motor performance was prioritized more in the environment with physical context than in the environment with projector-augmented context and vice versa for cognitive-task performance. In conclusion, walking environment strongly influenced cognitive-motor interference and task prioritization during dual-task walking in people with stroke.

Electrophysiological difference between mental state decoding and mental state reasoning.

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Cao, Bihua; Li, Yiyuan; Li, Fuhong; Li, Hong

2012-06-29

Previous studies have explored the neural mechanism of Theory of Mind (ToM), but the neural correlates of its two components, mental state decoding and mental state reasoning, remain unclear. In the present study, participants were presented with various photographs, showing an actor looking at 1 of 2 objects, either with a happy or an unhappy expression. They were asked to either decode the emotion of the actor (mental state decoding task), predict which object would be chosen by the actor (mental state reasoning task), or judge at which object the actor was gazing (physical task), while scalp potentials were recorded. Results showed that (1) the reasoning task elicited an earlier N2 peak than the decoding task did over the prefrontal scalp sites; and (2) during the late positive component (240-440 ms), the reasoning task elicited a more positive deflection than the other two tasks did at the prefrontal scalp sites. In addition, neither the decoding task nor the reasoning task has no left/right hemisphere difference. These findings imply that mental state reasoning differs from mental state decoding early (210 ms) after stimulus onset, and that the prefrontal lobe is the neural basis of mental state reasoning. Copyright © 2012 Elsevier B.V. All rights reserved.

Cognitive-motor interference during fine and gross motor tasks in children with Developmental Coordination Disorder (DCD).

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Schott, Nadja; El-Rajab, Inaam; Klotzbier, Thomas

2016-10-01

While typically developing children produce relatively automatized postural control processes, children with DCD seem to exhibit an automatization deficit. Dual tasks with various cognitive loads seem to be an effective way to assess the automatic deficit hypothesis. The aims of the study were: (1) to examine the effect of a concurrent cognitive task on fine and gross motor tasks in children with DCD, and (2) to determine whether the effect varied with different difficulty levels of the concurrent task. We examined dual-task performance (Trail-Making-Test, Trail-Walking-Test) in 20 children with DCD and 39 typically developing children. Based on the idea of the Trail-Making-Test, participants walked along a fixed pathway, following a prescribed path, delineated by target markers of (1) increasing sequential numbers, and (2) increasing sequential numbers and letters. The motor and cognitive dual-task effects (DTE) were calculated for each task. Regardless of the cognitive task, children with DCD performed equally well in fine and gross motor tasks, and were slower in the dual task conditions than under single task-conditions, compared with children without DCD. Increased cognitive task complexity resulted in slow trail walking as well as slower trail tracing. The motor interference for the gross motor tasks was least for the simplest conditions and greatest for the complex conditions and was more pronounced in children with DCD. Cognitive interference was low irrespective of the motor task. Children with DCD show a different approach to allocation of cognitive resources, and have difficulties making motor skills automatic. The latter notion is consistent with impaired cerebellar function and the "automatization deficit hypothesis", suggesting that any deficit in the automatization process will appear if conscious monitoring of the motor skill is made more difficult by integrating another task requiring attentional resources. Copyright © 2016 Elsevier Ltd. All

Self-Controlled Feedback for a Complex Motor Task

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Wolf Peter

2011-12-01

Full Text Available Self-controlled augmented feedback enhances learning of simple motor tasks. Thereby, learners tend to request feedback after trials that were rated as good by themselves. Feedback after good trials promotes positive reinforcement, which enhances motor learning. The goal of this study was to investigate when naïve learners request terminal visual feedback in a complex motor task, as conclusions drawn on simple tasks can hardly be transferred to complex tasks. Indeed, seven of nine learners stated to have intended to request feedback predominantly after good trials, but in contrast to their intention, kinematic analysis showed that feedback was rather requested randomly (23% after good, 44% after intermediate, 33% after bad trials. Moreover, requesting feedback after good trials did not correlate with learning success. It seems that self-estimation of performance in complex tasks is challenging. As a consequence, learners might have focused on certain movement aspects rather than on the overall movement. Further studies should assess the current focus of the learner in detail to gain more insight in self-estimation capabilities during complex motor task learning.

An Improved Unscented Kalman Filter Based Decoder for Cortical Brain-Machine Interfaces.

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Li, Simin; Li, Jie; Li, Zheng

2016-01-01

Brain-machine interfaces (BMIs) seek to connect brains with machines or computers directly, for application in areas such as prosthesis control. For this application, the accuracy of the decoding of movement intentions is crucial. We aim to improve accuracy by designing a better encoding model of primary motor cortical activity during hand movements and combining this with decoder engineering refinements, resulting in a new unscented Kalman filter based decoder, UKF2, which improves upon our previous unscented Kalman filter decoder, UKF1. The new encoding model includes novel acceleration magnitude, position-velocity interaction, and target-cursor-distance features (the decoder does not require target position as input, it is decoded). We add a novel probabilistic velocity threshold to better determine the user's intent to move. We combine these improvements with several other refinements suggested by others in the field. Data from two Rhesus monkeys indicate that the UKF2 generates offline reconstructions of hand movements (mean CC 0.851) significantly more accurately than the UKF1 (0.833) and the popular position-velocity Kalman filter (0.812). The encoding model of the UKF2 could predict the instantaneous firing rate of neurons (mean CC 0.210), given kinematic variables and past spiking, better than the encoding models of these two decoders (UKF1: 0.138, p-v Kalman: 0.098). In closed-loop experiments where each monkey controlled a computer cursor with each decoder in turn, the UKF2 facilitated faster task completion (mean 1.56 s vs. 2.05 s) and higher Fitts's Law bit rate (mean 0.738 bit/s vs. 0.584 bit/s) than the UKF1. These results suggest that the modeling and decoder engineering refinements of the UKF2 improve decoding performance. We believe they can be used to enhance other decoders as well.

Compromised Motor Dexterity Confounds Processing Speed Task Outcomes in Stroke Patients

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Essie Low

2017-09-01

Full Text Available Most conventional measures of information processing speed require motor responses to facilitate performance. However, although not often addressed clinically, motor impairment, whether due to age or acquired brain injury, would be expected to confound the outcome measure of such tasks. The current study recruited 29 patients (20 stroke and 9 transient ischemic attack with documented reduction in dexterity of the dominant hand, and 29 controls, to investigate the extent to which 3 commonly used processing speed measures with varying motor demands (a Visuo-Motor Reaction Time task, and the Wechsler Adult Intelligence Scale-IV Symbol Search and Coding subtests may be measuring motor-related speed more so than cognitive speed. Analyses include correlations between indices of cognitive and motor speed obtained from two other tasks (Inspection Time and Pegboard task, respectively with the three speed measures, followed by hierarchical regressions to determine the relative contribution of cognitive and motor speed indices toward task performance. Results revealed that speed outcomes on tasks with relatively high motor demands, such as Coding, were largely reflecting motor speed in individuals with reduced dominant hand dexterity. Thus, findings indicate the importance of employing measures with minimal motor requirements, especially when the assessment of speed is aimed at understanding cognitive rather than physical function.

Linear methods for reducing EMG contamination in peripheral nerve motor decodes.

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Kagan, Zachary B; Wendelken, Suzanne; Page, David M; Davis, Tyler; Hutchinson, Douglas T; Clark, Gregory A; Warren, David J

2016-08-01

Signals recorded from the peripheral nervous system (PNS) with high channel count penetrating microelectrode arrays, such as the Utah Slanted Electrode Array (USEA), often have electromyographic (EMG) signals contaminating the neural signal. This common-mode signal source may prevent single neural units from successfully being detected, thus hindering motor decode algorithms. Reducing this EMG contamination may lead to more accurate motor decode performance. A virtual reference (VR), created by a weighted linear combination of signals from a subset of all available channels, can be used to reduce this EMG contamination. Four methods of determining individual channel weights and six different methods of selecting subsets of channels were investigated (24 different VR types in total). The methods of determining individual channel weights were equal weighting, regression-based weighting, and two different proximity-based weightings. The subsets of channels were selected by a radius-based criteria, such that a channel was included if it was within a particular radius of inclusion from the target channel. These six radii of inclusion were 1.5, 2.9, 3.2, 5, 8.4, and 12.8 electrode-distances; the 12.8 electrode radius includes all USEA electrodes. We found that application of a VR improves the detectability of neural events via increasing the SNR, but we found no statistically meaningful difference amongst the VR types we examined. The computational complexity of implementation varies with respect to the method of determining channel weights and the number of channels in a subset, but does not correlate with VR performance. Hence, we examined the computational costs of calculating and applying the VR and based on these criteria, we recommend an equal weighting method of assigning weights with a 3.2 electrode-distance radius of inclusion. Further, we found empirically that application of the recommended VR will require less than 1 ms for 33.3 ms of data from one USEA.

A continuous time-resolved measure decoded from EEG oscillatory activity predicts working memory task performance.

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Astrand, Elaine

2018-06-01

Working memory (WM), crucial for successful behavioral performance in most of our everyday activities, holds a central role in goal-directed behavior. As task demands increase, inducing higher WM load, maintaining successful behavioral performance requires the brain to work at the higher end of its capacity. Because it is depending on both external and internal factors, individual WM load likely varies in a continuous fashion. The feasibility to extract such a continuous measure in time that correlates to behavioral performance during a working memory task remains unsolved. Multivariate pattern decoding was used to test whether a decoder constructed from two discrete levels of WM load can generalize to produce a continuous measure that predicts task performance. Specifically, a linear regression with L2-regularization was chosen with input features from EEG oscillatory activity recorded from healthy participants while performing the n-back task, [Formula: see text]. The feasibility to extract a continuous time-resolved measure that correlates positively to trial-by-trial working memory task performance is demonstrated (r  =  0.47, p  performance before action (r  =  0.49, p  <  0.05). We show that the extracted continuous measure enables to study the temporal dynamics of the complex activation pattern of WM encoding during the n-back task. Specifically, temporally precise contributions of different spectral features are observed which extends previous findings of traditional univariate approaches. These results constitute an important contribution towards a wide range of applications in the field of cognitive brain-machine interfaces. Monitoring mental processes related to attention and WM load to reduce the risk of committing errors in high-risk environments could potentially prevent many devastating consequences or using the continuous measure as neurofeedback opens up new possibilities to develop novel rehabilitation techniques for

Decoding 3D reach and grasp from hybrid signals in motor and premotor cortices: spikes, multiunit activity, and local field potentials.

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Bansal, Arjun K; Truccolo, Wilson; Vargas-Irwin, Carlos E; Donoghue, John P

2012-03-01

Neural activity in motor cortex during reach and grasp movements shows modulations in a broad range of signals from single-neuron spiking activity (SA) to various frequency bands in broadband local field potentials (LFPs). In particular, spatiotemporal patterns in multiband LFPs are thought to reflect dendritic integration of local and interareal synaptic inputs, attentional and preparatory processes, and multiunit activity (MUA) related to movement representation in the local motor area. Nevertheless, the relationship between multiband LFPs and SA, and their relationship to movement parameters and their relative value as brain-computer interface (BCI) control signals, remain poorly understood. Also, although this broad range of signals may provide complementary information channels in primary (MI) and ventral premotor (PMv) areas, areal differences in information have not been systematically examined. Here, for the first time, the amount of information in SA and multiband LFPs was compared for MI and PMv by recording from dual 96-multielectrode arrays while monkeys made naturalistic reach and grasp actions. Information was assessed as decoding accuracy for 3D arm end point and grip aperture kinematics based on SA or LFPs in MI and PMv, or combinations of signal types across areas. In contrast with previous studies with ≤16 simultaneous electrodes, here ensembles of >16 units (on average) carried more information than multiband, multichannel LFPs. Furthermore, reach and grasp information added by various LFP frequency bands was not independent from that in SA ensembles but rather typically less than and primarily contained within the latter. Notably, MI and PMv did not show a particular bias toward reach or grasp for this task or for a broad range of signal types. For BCIs, our results indicate that neuronal ensemble spiking is the preferred signal for decoding, while LFPs and combined signals from PMv and MI can add robustness to BCI control.

Task-irrelevant auditory feedback facilitates motor performance in musicians

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Virginia eConde

2012-05-01

Full Text Available An efficient and fast auditory–motor network is a basic resource for trained musicians due to the importance of motor anticipation of sound production in musical performance. When playing an instrument, motor performance always goes along with the production of sounds and the integration between both modalities plays an essential role in the course of musical training. The aim of the present study was to investigate the role of task-irrelevant auditory feedback during motor performance in musicians using a serial reaction time task (SRTT. Our hypothesis was that musicians, due to their extensive auditory–motor practice routine during musical training, have a superior performance and learning capabilities when receiving auditory feedback during SRTT relative to musicians performing the SRTT without any auditory feedback. Here we provide novel evidence that task-irrelevant auditory feedback is capable to reinforce SRTT performance but not learning, a finding that might provide further insight into auditory-motor integration in musicians on a behavioral level.

Cognitive and motor dual task gait training improve dual task gait performance after stroke - A randomized controlled pilot trial.

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Liu, Yan-Ci; Yang, Yea-Ru; Tsai, Yun-An; Wang, Ray-Yau

2017-06-22

This study investigated effects of cognitive and motor dual task gait training on dual task gait performance in stroke. Participants (n = 28) were randomly assigned to cognitive dual task gait training (CDTT), motor dual task gait training (MDTT), or conventional physical therapy (CPT) group. Participants in CDTT or MDTT group practiced the cognitive or motor tasks respectively during walking. Participants in CPT group received strengthening, balance, and gait training. The intervention was 30 min/session, 3 sessions/week for 4 weeks. Three test conditions to evaluate the training effects were single walking, walking while performing cognitive task (serial subtraction), and walking while performing motor task (tray-carrying). Parameters included gait speed, dual task cost of gait speed (DTC-speed), cadence, stride time, and stride length. After CDTT, cognitive-motor dual task gait performance (stride length and DTC-speed) was improved (p = 0.021; p = 0.015). After MDTT, motor dual task gait performance (gait speed, stride length, and DTC-speed) was improved (p = 0.008; p = 0.008; p = 0.008 respectively). It seems that CDTT improved cognitive dual task gait performance and MDTT improved motor dual task gait performance although such improvements did not reach significant group difference. Therefore, different types of dual task gait training can be adopted to enhance different dual task gait performance in stroke.

Task-dependent activation of distinct fast and slow(er) motor pathways during motor imagery.

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Keller, Martin; Taube, Wolfgang; Lauber, Benedikt

2018-02-22

Motor imagery and actual movements share overlapping activation of brain areas but little is known about task-specific activation of distinct motor pathways during mental simulation of movements. For real contractions, it was demonstrated that the slow(er) motor pathways are activated differently in ballistic compared to tonic contractions but it is unknown if this also holds true for imagined contractions. The aim of the present study was to assess the activity of fast and slow(er) motor pathways during mentally simulated movements of ballistic and tonic contractions. H-reflexes were conditioned with transcranial magnetic stimulation at different interstimulus intervals to assess the excitability of fast and slow(er) motor pathways during a) the execution of tonic and ballistic contractions, b) motor imagery of these contraction types, and c) at rest. In contrast to the fast motor pathways, the slow(er) pathways displayed a task-specific activation: for imagined ballistic as well as real ballistic contractions, the activation was reduced compared to rest whereas enhanced activation was found for imagined tonic and real tonic contractions. This study provides evidence that the excitability of fast and slow(er) motor pathways during motor imagery resembles the activation pattern observed during real contractions. The findings indicate that motor imagery results in task- and pathway-specific subliminal activation of distinct subsets of neurons in the primary motor cortex. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

The change in perceived motor competence and motor task values during elementary school : Gender and motor performance differences

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Noordstar, J.J.; van der Net, J.; Jak, S.; Helders, P.J.M.; Jongmans, M.J.

2016-01-01

Participation in motor activities is essential for social interaction and life satisfaction in children. Self-perceptions and task values have a central position in why children do or do not participate in (motor) activities. Investigating developmental changes in motor self-perceptions and motor

A continuous time-resolved measure decoded from EEG oscillatory activity predicts working memory task performance

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Astrand, Elaine

2018-06-01

Objective. Working memory (WM), crucial for successful behavioral performance in most of our everyday activities, holds a central role in goal-directed behavior. As task demands increase, inducing higher WM load, maintaining successful behavioral performance requires the brain to work at the higher end of its capacity. Because it is depending on both external and internal factors, individual WM load likely varies in a continuous fashion. The feasibility to extract such a continuous measure in time that correlates to behavioral performance during a working memory task remains unsolved. Approach. Multivariate pattern decoding was used to test whether a decoder constructed from two discrete levels of WM load can generalize to produce a continuous measure that predicts task performance. Specifically, a linear regression with L2-regularization was chosen with input features from EEG oscillatory activity recorded from healthy participants while performing the n-back task, n\\in [1,2] . Main results. The feasibility to extract a continuous time-resolved measure that correlates positively to trial-by-trial working memory task performance is demonstrated (r  =  0.47, p  <  0.05). It is furthermore shown that this measure allows to predict task performance before action (r  =  0.49, p  <  0.05). We show that the extracted continuous measure enables to study the temporal dynamics of the complex activation pattern of WM encoding during the n-back task. Specifically, temporally precise contributions of different spectral features are observed which extends previous findings of traditional univariate approaches. Significance. These results constitute an important contribution towards a wide range of applications in the field of cognitive brain–machine interfaces. Monitoring mental processes related to attention and WM load to reduce the risk of committing errors in high-risk environments could potentially prevent many devastating consequences or

Profiles of Cognitive-Motor Interference During Walking in Children: Does the Motor or the Cognitive Task Matter?

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Nadja Schott

2018-06-01

Full Text Available The evidence supporting the effects of age on the ability to coordinate a motor and a cognitive task show inconsistent results in children and adolescents, where the Dual-Task Effects (DTE – if computed at all – range from either being lower or comparable or higher in younger children than in older children, adolescents and adults. A feasible reason for the variability in such findings is the wide range of cognitive tasks (and to some extend of motor tasks used to study Cognitive-Motor Interference (CMI. Our study aims at determining the differences in CMI when performing cognitive tasks targeting different cognitive functions at varying walking pathways. 69 children and adolescents (boys, n = 45; girls, n = 24; mean age, 11.5 ± 1.50 years completed higher-level executive function tasks (2-Back, Serial Subtraction, Auditory Stroop, Clock Task, TMT-B in comparison to non-executive distracter tasks [Motor Response Task (MRT, TMT-A] to assess relative effects on gait during straight vs. repeated Change of Direction (COD walking. DT during COD walking was assessed using the Trail-Walking-Test (TWT. The motor and cognitive DTE were calculated for each task. There were significant differences between 5th and 8th graders on single gait speed on the straight (p = 0.016 and the COD pathway (p = 0.023, but not on any of the DT conditions. The calculation of DTEs revealed that motor DTEs were lowest for the MRT and highest for the TWT in the numbers/letters condition (p < 0.05 for all comparisons. In contrast, there were cognitive benefits for the higher-order cognitive tasks on the straight pathways, but cognitive costs for both DT conditions on the COD pathway (p < 0.01 for all comparisons. Our findings demonstrate that DT changes in walking when completing a secondary task that involve higher-level cognition are attributable to more than low-level divided attention or motor response processes. These results specifically show the direct competition

Decoding and Encoding Facial Expressions in Preschool-Age Children.

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Zuckerman, Miron; Przewuzman, Sylvia J.

1979-01-01

Preschool-age children drew, decoded, and encoded facial expressions depicting five different emotions. Accuracy of drawing, decoding and encoding each of the five emotions was consistent across the three tasks; decoding ability was correlated with drawing ability among female subjects, but neither of these abilities was correlated with encoding…

Enhanced motor learning following task-concurrent dual transcranial direct current stimulation.

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Sophia Karok

Full Text Available OBJECTIVE: Transcranial direct current stimulation (tDCS of the primary motor cortex (M1 has beneficial effects on motor performance and motor learning in healthy subjects and is emerging as a promising tool for motor neurorehabilitation. Applying tDCS concurrently with a motor task has recently been found to be more effective than applying stimulation before the motor task. This study extends this finding to examine whether such task-concurrent stimulation further enhances motor learning on a dual M1 montage. METHOD: Twenty healthy, right-handed subjects received anodal tDCS to the right M1, dual tDCS (anodal current over right M1 and cathodal over left M1 and sham tDCS in a repeated-measures design. Stimulation was applied for 10 mins at 1.5 mA during an explicit motor learning task. Response times (RT and accuracy were measured at baseline, during, directly after and 15 mins after stimulation. Motor cortical excitability was recorded from both hemispheres before and after stimulation using single-pulse transcranial magnetic stimulation. RESULTS: Task-concurrent stimulation with a dual M1 montage significantly reduced RTs by 23% as early as with the onset of stimulation (p<0.01 with this effect increasing to 30% at the final measurement. Polarity-specific changes in cortical excitability were observed with MEPs significantly reduced by 12% in the left M1 and increased by 69% in the right M1. CONCLUSION: Performance improvement occurred earliest in the dual M1 condition with a stable and lasting effect. Unilateral anodal stimulation resulted only in trendwise improvement when compared to sham. Therefore, task-concurrent dual M1 stimulation is most suited for obtaining the desired neuromodulatory effects of tDCS in explicit motor learning.

Motor unit recruitment for dynamic tasks: current understanding and future directions.

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Hodson-Tole, Emma F; Wakeling, James M

2009-01-01

Skeletal muscle contains many muscle fibres that are functionally grouped into motor units. For any motor task there are many possible combinations of motor units that could be recruited and it has been proposed that a simple rule, the 'size principle', governs the selection of motor units recruited for different contractions. Motor units can be characterised by their different contractile, energetic and fatigue properties and it is important that the selection of motor units recruited for given movements allows units with the appropriate properties to be activated. Here we review what is currently understood about motor unit recruitment patterns, and assess how different recruitment patterns are more or less appropriate for different movement tasks. During natural movements the motor unit recruitment patterns vary (not always holding to the size principle) and it is proposed that motor unit recruitment is likely related to the mechanical function of the muscles. Many factors such as mechanics, sensory feedback, and central control influence recruitment patterns and consequently an integrative approach (rather than reductionist) is required to understand how recruitment is controlled during different movement tasks. Currently, the best way to achieve this is through in vivo studies that relate recruitment to mechanics and behaviour. Various methods for determining motor unit recruitment patterns are discussed, in particular the recent wavelet-analysis approaches that have allowed motor unit recruitment to be assessed during natural movements. Directions for future studies into motor recruitment within and between functional task groups and muscle compartments are suggested.

Cortical Decoding of Individual Finger and Wrist Kinematics for an Upper-Limb Neuroprosthesis

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Aggarwal, Vikram; Tenore, Francesco; Acharya, Soumyadipta; Schieber, Marc H.; Thakor, Nitish V.

2010-01-01

Previous research has shown that neuronal activity can be used to continuously decode the kinematics of gross movements involving arm and hand trajectory. However, decoding the kinematics of fine motor movements, such as the manipulation of individual fingers, has not been demonstrated. In this study, single unit activities were recorded from task-related neurons in M1 of two trained rhesus monkey as they performed individuated movements of the fingers and wrist. The primates’ hand was placed in a manipulandum, and strain gauges at the tips of each finger were used to track the digit’s position. Both linear and non-linear filters were designed to simultaneously predict kinematics of each digit and the wrist, and their performance compared using mean squared error and correlation coefficients. All models had high decoding accuracy, but the feedforward ANN (R=0.76–0.86, MSE=0.04–0.05) and Kalman filter (R=0.68–0.86, MSE=0.04–0.07) performed better than a simple linear regression filter (0.58–0.81, 0.05–0.07). These results suggest that individual finger and wrist kinematics can be decoded with high accuracy, and be used to control a multi-fingered prosthetic hand in real-time. PMID:19964645

The effectiveness of robotic training depends on motor task characteristics.

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Marchal-Crespo, Laura; Rappo, Nicole; Riener, Robert

2017-12-01

Previous research suggests that the effectiveness of robotic training depends on the motor task to be learned. However, it is still an open question which specific task's characteristics influence the efficacy of error-modulating training strategies. Motor tasks can be classified based on the time characteristics of the task, in particular the task's duration (discrete vs. continuous). Continuous tasks require movements without distinct beginning or end. Discrete tasks require fast movements that include well-defined postures at the beginning and the end. We developed two games, one that requires a continuous movement-a tracking task-and one that requires discrete movements-a fast reaching task. We conducted an experiment with thirty healthy subjects to evaluate the effectiveness of three error-modulating training strategies-no guidance, error amplification (i.e., repulsive forces proportional to errors) and haptic guidance-on self-reported motivation and learning of the continuous and discrete games. Training with error amplification resulted in better motor learning than haptic guidance, besides the fact that error amplification reduced subjects' interest/enjoyment and perceived competence during training. Only subjects trained with error amplification improved their performance after training the discrete game. In fact, subjects trained without guidance improved the performance in the continuous game significantly more than in the discrete game, probably because the continuous task required greater attentional levels. Error-amplifying training strategies have a great potential to provoke better motor learning in continuous and discrete tasks. However, their long-lasting negative effects on motivation might limit their applicability in intense neurorehabilitation programs.

Motor-cognitive dual-task performance: effects of a concurrent motor task on distinct components of visual processing capacity

OpenAIRE

Künstler, E. C. S.; Finke, K.; Günther, A.; Klingner, C.; Witte, O.; Bublak, P.

2017-01-01

Dual tasking, or the simultaneous execution of two continuous tasks, is frequently associated with a performance decline that can be explained within a capacity sharing framework. In this study, we assessed the effects of a concurrent motor task on the efficiency of visual information uptake based on the ‘theory of visual attention’ (TVA). TVA provides parameter estimates reflecting distinct components of visual processing capacity: perceptual threshold, visual processing speed, and visual sh...

Feature Selection Methods for Robust Decoding of Finger Movements in a Non-human Primate

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Padmanaban, Subash; Baker, Justin; Greger, Bradley

2018-01-01

Objective: The performance of machine learning algorithms used for neural decoding of dexterous tasks may be impeded due to problems arising when dealing with high-dimensional data. The objective of feature selection algorithms is to choose a near-optimal subset of features from the original feature space to improve the performance of the decoding algorithm. The aim of our study was to compare the effects of four feature selection techniques, Wilcoxon signed-rank test, Relative Importance, Principal Component Analysis (PCA), and Mutual Information Maximization on SVM classification performance for a dexterous decoding task. Approach: A nonhuman primate (NHP) was trained to perform small coordinated movements—similar to typing. An array of microelectrodes was implanted in the hand area of the motor cortex of the NHP and used to record action potentials (AP) during finger movements. A Support Vector Machine (SVM) was used to classify which finger movement the NHP was making based upon AP firing rates. We used the SVM classification to examine the functional parameters of (i) robustness to simulated failure and (ii) longevity of classification. We also compared the effect of using isolated-neuron and multi-unit firing rates as the feature vector supplied to the SVM. Main results: The average decoding accuracy for multi-unit features and single-unit features using Mutual Information Maximization (MIM) across 47 sessions was 96.74 ± 3.5% and 97.65 ± 3.36% respectively. The reduction in decoding accuracy between using 100% of the features and 10% of features based on MIM was 45.56% (from 93.7 to 51.09%) and 4.75% (from 95.32 to 90.79%) for multi-unit and single-unit features respectively. MIM had best performance compared to other feature selection methods. Significance: These results suggest improved decoding performance can be achieved by using optimally selected features. The results based on clinically relevant performance metrics also suggest that the decoding

Task-specific effect of transcranial direct current stimulation on motor learning

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Cinthia Maria Saucedo Marquez

2013-07-01

Full Text Available Transcranial direct current stimulation (tDCS is a relatively new non-invasive brain stimulation technique that modulates neural processes. When applied to the human primary motor cortex (M1, tDCS has beneficial effects on motor skill learning and consolidation in healthy controls and in patients. However, it remains unclear whether tDCS improves motor learning in a general manner or whether these effects depend on which motor task is acquired. Here we compare whether the effect of tDCS differs when the same individual acquires (1 a Sequential Finger Tapping Task (SEQTAP and (2 a Visual Isometric Pinch Force Task (FORCE. Both tasks have been shown to be sensitive to tDCS applied over M1, however, the underlying processes mediating learning and memory formation might benefit differently from anodal-tDCS. Thirty healthy subjects were randomly assigned to an anodal-tDCS group or sham-group. Using a double-blind, sham-controlled cross-over design, tDCS was applied over M1 while subjects acquired each of the motor tasks over 3 consecutive days, with the order being randomized across subjects. We found that anodal-tDCS affected each task differently: The SEQTAP task benefited from anodal-tDCS during learning, whereas the FORCE task showed improvements only at retention. These findings suggest that anodal tDCS applied over M1 appears to have a task-dependent effect on learning and memory formation.

Motor cortical encoding of serial order in a context-recall task.

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Carpenter, A F; Georgopoulos, A P; Pellizzer, G

1999-03-12

The neural encoding of serial order was studied in the motor cortex of monkeys performing a context-recall memory scanning task. Up to five visual stimuli were presented successively on a circle (list presentation phase), and then one of them (test stimulus) changed color; the monkeys had to make a single motor response toward the stimulus that immediately followed the test stimulus in the list. Correct performance in this task depends on memorization of the serial order of the stimuli during their presentation. It was found that changes in neural activity during the list presentation phase reflected the serial order of the stimuli; the effect on cell activity of the serial order of stimuli during their presentation was at least as strong as the effect of motor direction on cell activity during the execution of the motor response. This establishes the serial order of stimuli in a motor task as an important determinant of motor cortical activity during stimulus presentation and in the absence of changes in peripheral motor events, in contrast to the commonly held view of the motor cortex as just an "upper motor neuron."

Task Complexity Modulates Sleep-Related Offline Learning in Sequential Motor Skills

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Klaus Blischke

2017-07-01

Full Text Available Recently, a number of authors have advocated the introduction of gross motor tasks into research on sleep-related motor offline learning. Such tasks are often designed to be more complex than traditional key-pressing tasks. However, until now, little effort has been undertaken to scrutinize the role of task complexity in any systematic way. Therefore, the effect of task complexity on the consolidation of gross motor sequence memory was examined by our group in a series of three experiments. Criterion tasks always required participants to produce unrestrained arm movement sequences by successively fitting a small peg into target holes on a pegboard. The sequences always followed a certain spatial pattern in the horizontal plane. The targets were visualized prior to each transport movement on a computer screen. The tasks differed with respect to sequence length and structural complexity. In each experiment, half of the participants initially learned the task in the morning and were retested 12 h later following a wake retention interval. The other half of the subjects underwent practice in the evening and was retested 12 h later following a night of sleep. The dependent variables were the error rate and total sequence execution time (inverse to the sequence execution speed. Performance generally improved during acquisition. The error rate was always low and remained stable during retention. The sequence execution time significantly decreased again following sleep but not after waking when the sequence length was long and structural complexity was high. However, sleep-related offline improvements were absent when the sequence length was short or when subjects performed a highly regular movement pattern. It is assumed that the occurrence of sleep-related offline performance improvements in sequential motor tasks is associated with a sufficient amount of motor task complexity.

The change in perceived motor competence and motor task values during elementary school : A longitudinal cohort study

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Noordstar, Johannes J; van der Net, Janjaap; Jak, Suzanne; Helders, Paul J M; Jongmans, Marian J

Participation in motor activities is essential for social interaction and life satisfaction in children. Self-perceptions and task values have a central position in why children do or do not participate in (motor) activities. Investigating developmental changes in motor self-perceptions and motor

Neural Correlates of Task Cost for Stance Control with an Additional Motor Task: Phase-Locked Electroencephalogram Responses

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Hwang, Ing-Shiou; Huang, Cheng-Ya

2016-01-01

With appropriate reallocation of central resources, the ability to maintain an erect posture is not necessarily degraded by a concurrent motor task. This study investigated the neural control of a particular postural-suprapostural procedure involving brain mechanisms to solve crosstalk between posture and motor subtasks. Participants completed a single posture task and a dual-task while concurrently conducting force-matching and maintaining a tilted stabilometer stance at a target angle. Stabilometer movements and event-related potentials (ERPs) were recorded. The added force-matching task increased the irregularity of postural response rather than the size of postural response prior to force-matching. In addition, the added force-matching task during stabilometer stance led to marked topographic ERP modulation, with greater P2 positivity in the frontal and sensorimotor-parietal areas of the N1-P2 transitional phase and in the sensorimotor-parietal area of the late P2 phase. The time-frequency distribution of the ERP primary principal component revealed that the dual-task condition manifested more pronounced delta (1–4 Hz) and beta (13–35 Hz) synchronizations but suppressed theta activity (4–8 Hz) before force-matching. The dual-task condition also manifested coherent fronto-parietal delta activity in the P2 period. In addition to a decrease in postural regularity, this study reveals spatio-temporal and temporal-spectral reorganizations of ERPs in the fronto-sensorimotor-parietal network due to the added suprapostural motor task. For a particular set of postural-suprapostural task, the behavior and neural data suggest a facilitatory role of autonomous postural response and central resource expansion with increasing interregional interactions for task-shift and planning the motor-suprapostural task. PMID:27010634

Functional MR study of a motor task and the Tower of London task at 1.0 T

International Nuclear Information System (INIS)

Boghi, A.; Rampado, O.; Ropolo, R.; Bergui, M.; Coriasco, M.; Bradac, G.B.; Avidano, F.; Manzone, C.; Mortara, P.; Orsi, L.

2006-01-01

The use of functional magnetic resonance imaging (fMRI) for clinical applications and basic neuroscience is constantly increasing. The discussion about minimum performance requirement for a correct implementation of fMRI is still open, and one of the critical points is the magnetic field strength. We tested the feasibility of fMRI at 1.0 T during motor and cognitive tasks. Fourteen healthy subjects were scanned during a motor task and 12 while performing the Tower of London task. In the activated areas, the percentage signal change due to BOLD (blood oxygenation level dependent) contrast was analysed. To check basic image quality of the acquisition system we measured quality indices in a temporal series of images of a phantom. Motor and cognitive brain activations matched previous results obtained at higher field strengths. The mean percentage change over subjects in the motor task was in the range 1.3-2.6% for the primary motor area and 0.8-6.7% for the cerebellum. In the cognitive task, the mean percentage change over subjects was 0.7-1.2% for a frontal area and 0.6-2.8% for a parietal area. The percentage noise of the phantom temporal series was less than 0.4%. Percentage changes and signal to noise ratio, although lower than that obtained with high-field systems, allowed activation maps to be obtained in all subjects. (orig.)

Correlations between Motor Symptoms across Different Motor Tasks, Quantified via Random Forest Feature Classification in Parkinson’s Disease

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Andreas Kuhner

2017-11-01

Full Text Available BackgroundObjective assessments of Parkinson’s disease (PD patients’ motor state using motion capture techniques are still rarely used in clinical practice, even though they may improve clinical management. One major obstacle relates to the large dimensionality of motor abnormalities in PD. We aimed to extract global motor performance measures covering different everyday motor tasks, as a function of a clinical intervention, i.e., deep brain stimulation (DBS of the subthalamic nucleus.MethodsWe followed a data-driven, machine-learning approach and propose performance measures that employ Random Forests with probability distributions. We applied this method to 14 PD patients with DBS switched-off or -on, and 26 healthy control subjects performing the Timed Up and Go Test (TUG, the Functional Reach Test (FRT, a hand coordination task, walking 10-m straight, and a 90° curve.ResultsFor each motor task, a Random Forest identified a specific set of metrics that optimally separated PD off DBS from healthy subjects. We noted the highest accuracy (94.6% for standing up. This corresponded to a sensitivity of 91.5% to detect a PD patient off DBS, and a specificity of 97.2% representing the rate of correctly identified healthy subjects. We then calculated performance measures based on these sets of metrics and applied those results to characterize symptom severity in different motor tasks. Task-specific symptom severity measures correlated significantly with each other and with the Unified Parkinson’s Disease Rating Scale (UPDRS, part III, correlation of r2 = 0.79. Agreement rates between different measures ranged from 79.8 to 89.3%.ConclusionThe close correlation of PD patients’ various motor abnormalities quantified by different, task-specific severity measures suggests that these abnormalities are only facets of the underlying one-dimensional severity of motor deficits. The identification and characterization of this underlying motor deficit

Motor-cognitive dual-task deficits in individuals with early-mid stage Huntington disease.

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Fritz, Nora E; Hamana, Katy; Kelson, Mark; Rosser, Anne; Busse, Monica; Quinn, Lori

2016-09-01

Huntington disease (HD) results in a range of cognitive and motor impairments that progress throughout the disease stages; however, little research has evaluated specific dual-task abilities in this population, and the degree to which they may be related to functional ability. The purpose of this study was to a) examine simple and complex motor-cognitive dual-task performance in individuals with HD, b) determine relationships between dual-task walking ability and disease-specific measures of motor, cognitive and functional ability, and c) examine the relationship of dual-task measures to falls in individuals with HD. Thirty-two individuals with HD were evaluated for simple and complex dual-task ability using the Walking While Talking Test. Demographics and disease-specific measures of motor, cognitive and functional ability were also obtained. Individuals with HD had impairments in simple and complex dual-task ability. Simple dual-task walking was correlated to disease-specific motor scores as well as cognitive performance, but complex dual-task walking was correlated with total functional capacity, as well as a range of cognitive measures. Number of prospective falls was moderately-strongly correlated to dual-task measures. Our results suggest that individuals with HD have impairments in cognitive-motor dual-task ability that are related to disease progression and specifically functional ability. Dual-task measures appear to evaluate a unique construct in individuals with early to mid-stage HD, and may have value in improving the prediction of falls risk in this population. Copyright © 2016 Elsevier B.V. All rights reserved.

Fine and gross motor skills: The effects on skill-focused dual-tasks.

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Raisbeck, Louisa D; Diekfuss, Jed A

2015-10-01

Dual-task methodology often directs participants' attention towards a gross motor skill involved in the execution of a skill, but researchers have not investigated the comparative effects of attention on fine motor skill tasks. Furthermore, there is limited information about participants' subjective perception of workload with respect to task performance. To examine this, the current study administered the NASA-Task Load Index following a simulated shooting dual-task. The task required participants to stand 15 feet from a projector screen which depicted virtual targets and fire a modified Glock 17 handgun equipped with an infrared laser. Participants performed the primary shooting task alone (control), or were also instructed to focus their attention on a gross motor skill relevant to task execution (gross skill-focused) and a fine motor skill relevant to task execution (fine skill-focused). Results revealed that workload was significantly greater during the fine skill-focused task for both skill levels, but performance was only affected for the lesser-skilled participants. Shooting performance for the lesser-skilled participants was greater during the gross skill-focused condition compared to the fine skill-focused condition. Correlational analyses also demonstrated a significant negative relationship between shooting performance and workload during the gross skill-focused task for the higher-skilled participants. A discussion of the relationship between skill type, workload, skill level, and performance in dual-task paradigms is presented. Copyright © 2015 Elsevier B.V. All rights reserved.

Grasp movement decoding from premotor and parietal cortex.

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Townsend, Benjamin R; Subasi, Erk; Scherberger, Hansjörg

2011-10-05

Despite recent advances in harnessing cortical motor-related activity to control computer cursors and robotic devices, the ability to decode and execute different grasping patterns remains a major obstacle. Here we demonstrate a simple Bayesian decoder for real-time classification of grip type and wrist orientation in macaque monkeys that uses higher-order planning signals from anterior intraparietal cortex (AIP) and ventral premotor cortex (area F5). Real-time decoding was based on multiunit signals, which had similar tuning properties to cells in previous single-unit recording studies. Maximum decoding accuracy for two grasp types (power and precision grip) and five wrist orientations was 63% (chance level, 10%). Analysis of decoder performance showed that grip type decoding was highly accurate (90.6%), with most errors occurring during orientation classification. In a subsequent off-line analysis, we found small but significant performance improvements (mean, 6.25 percentage points) when using an optimized spike-sorting method (superparamagnetic clustering). Furthermore, we observed significant differences in the contributions of F5 and AIP for grasp decoding, with F5 being better suited for classification of the grip type and AIP contributing more toward decoding of object orientation. However, optimum decoding performance was maximal when using neural activity simultaneously from both areas. Overall, these results highlight quantitative differences in the functional representation of grasp movements in AIP and F5 and represent a first step toward using these signals for developing functional neural interfaces for hand grasping.

Transcranial direct current stimulation (tDCS) to the supplementary motor area (SMA) influences performance on motor tasks.

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Hupfeld, K E; Ketcham, C J; Schneider, H D

2017-03-01

The supplementary motor area (SMA) is believed to be highly involved in the planning and execution of both simple and complex motor tasks. This study aimed to examine the role of the SMA in planning the movements required to complete reaction time, balance, and pegboard tasks using anodal transcranial direct current stimulation (tDCS), which passes a weak electrical current between two electrodes, in order to modulate neuronal activity. Twenty healthy adults were counterbalanced to receive either tDCS (experimental condition) or no tDCS (control condition) for 3 days. During administration of tDCS, participants performed a balance task significantly faster than controls. After tDCS, subjects significantly improved their simple and choice reaction time. These results demonstrate that the SMA is highly involved in planning and executing fine and gross motor skill tasks and that tDCS is an effective modality for increasing SMA-related performance on these tasks. The findings may be generalizable and therefore indicate implications for future interventions using tDCS as a therapeutic tool.

Planning Ahead: Object-Directed Sequential Actions Decoded from Human Frontoparietal and Occipitotemporal Networks

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Gallivan, Jason P.; Johnsrude, Ingrid S.; Randall Flanagan, J.

2016-01-01

Object-manipulation tasks (e.g., drinking from a cup) typically involve sequencing together a series of distinct motor acts (e.g., reaching toward, grasping, lifting, and transporting the cup) in order to accomplish some overarching goal (e.g., quenching thirst). Although several studies in humans have investigated the neural mechanisms supporting the planning of visually guided movements directed toward objects (such as reaching or pointing), only a handful have examined how manipulatory sequences of actions—those that occur after an object has been grasped—are planned and represented in the brain. Here, using event-related functional MRI and pattern decoding methods, we investigated the neural basis of real-object manipulation using a delayed-movement task in which participants first prepared and then executed different object-directed action sequences that varied either in their complexity or final spatial goals. Consistent with previous reports of preparatory brain activity in non-human primates, we found that activity patterns in several frontoparietal areas reliably predicted entire action sequences in advance of movement. Notably, we found that similar sequence-related information could also be decoded from pre-movement signals in object- and body-selective occipitotemporal cortex (OTC). These findings suggest that both frontoparietal and occipitotemporal circuits are engaged in transforming object-related information into complex, goal-directed movements. PMID:25576538

High variability impairs motor learning regardless of whether it affects task performance.

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Cardis, Marco; Casadio, Maura; Ranganathan, Rajiv

2018-01-01

Motor variability plays an important role in motor learning, although the exact mechanisms of how variability affects learning are not well understood. Recent evidence suggests that motor variability may have different effects on learning in redundant tasks, depending on whether it is present in the task space (where it affects task performance) or in the null space (where it has no effect on task performance). We examined the effect of directly introducing null and task space variability using a manipulandum during the learning of a motor task. Participants learned a bimanual shuffleboard task for 2 days, where their goal was to slide a virtual puck as close as possible toward a target. Critically, the distance traveled by the puck was determined by the sum of the left- and right-hand velocities, which meant that there was redundancy in the task. Participants were divided into five groups, based on both the dimension in which the variability was introduced and the amount of variability that was introduced during training. Results showed that although all groups were able to reduce error with practice, learning was affected more by the amount of variability introduced rather than the dimension in which variability was introduced. Specifically, groups with higher movement variability during practice showed larger errors at the end of practice compared with groups that had low variability during learning. These results suggest that although introducing variability can increase exploration of new solutions, this may adversely affect the ability to retain the learned solution. NEW & NOTEWORTHY We examined the role of introducing variability during motor learning in a redundant task. The presence of redundancy allows variability to be introduced in different dimensions: the task space (where it affects task performance) or the null space (where it does not affect task performance). We found that introducing variability affected learning adversely, but the amount of

Motor dual-tasking deficits predict falls in Parkinson's disease: A prospective study.

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Heinzel, Sebastian; Maechtel, Mirjam; Hasmann, Sandra E; Hobert, Markus A; Heger, Tanja; Berg, Daniela; Maetzler, Walter

2016-05-01

Falls severely affect lives of Parkinson's disease (PD) patients. Cognitive impairment including dual-tasking deficits contribute to fall risk in PD. However, types of dual-tasking deficits preceding falls in PD are still unclear. Walking velocities during box-checking and subtracting serial 7s were assessed twice a year in 40 PD patients over 2.8 ± 1.0 years. Fourteen patients reported a fall within this period (4 excluded fallers already reported falls at baseline). Their dual-task costs (DTC; mean ± standard deviation) 4.2 ± 2.2 months before the first fall were compared with 22 patients never reporting falls. ROC analyses and logistic regressions accounting for DTC, UPDRS-III and disease duration were used for faller classification and prediction. Only walking/box-checking predicted fallers. Fallers showed higher DTC for walking while box-checking, p = 0.029, but not for box-checking while walking, p = 0.178 (combined motor DTC, p = 0.022), than non-fallers. Combined motor DTC classified fallers and non-fallers (area under curve: 0.75; 95% confidence interval, CI: 0.60-0.91) with 71.4% sensitivity (95%CI: 41.9%-91.6%) and 77.3% specificity (54.6%-92.2%), and significantly predicted future fallers (p = 0.023). Here, 20.4%-points higher combined motor DTC (i.e. the mean difference between fallers and non-fallers) was associated with a 2.6 (1.1-6.0) times higher odds to be a future faller. Motor dual-tasking is a potentially valuable predictor of falls in PD, suggesting that avoiding dual task situations as well as specific motor dual-task training might help to prevent falls in PD. These findings and their therapeutic relevance need to be further validated in PD patients without fall history, in early PD stages, and with various motor-motor dual-task challenges. Copyright © 2016 Elsevier Ltd. All rights reserved.

A square root ensemble Kalman filter application to a motor-imagery brain-computer interface.

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Kamrunnahar, M; Schiff, S J

2011-01-01

We here investigated a non-linear ensemble Kalman filter (SPKF) application to a motor imagery brain computer interface (BCI). A square root central difference Kalman filter (SR-CDKF) was used as an approach for brain state estimation in motor imagery task performance, using scalp electroencephalography (EEG) signals. Healthy human subjects imagined left vs. right hand movements and tongue vs. bilateral toe movements while scalp EEG signals were recorded. Offline data analysis was conducted for training the model as well as for decoding the imagery movements. Preliminary results indicate the feasibility of this approach with a decoding accuracy of 78%-90% for the hand movements and 70%-90% for the tongue-toes movements. Ongoing research includes online BCI applications of this approach as well as combined state and parameter estimation using this algorithm with different system dynamic models.

Classification of EEG signals to identify variations in attention during motor task execution.

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Aliakbaryhosseinabadi, Susan; Kamavuako, Ernest Nlandu; Jiang, Ning; Farina, Dario; Mrachacz-Kersting, Natalie

2017-06-01

Brain-computer interface (BCI) systems in neuro-rehabilitation use brain signals to control external devices. User status such as attention affects BCI performance; thus detecting the user's attention drift due to internal or external factors is essential for high detection accuracy. An auditory oddball task was applied to divert the users' attention during a simple ankle dorsiflexion movement. Electroencephalogram signals were recorded from eighteen channels. Temporal and time-frequency features were projected to a lower dimension space and used to analyze the effect of two attention levels on motor tasks in each participant. Then, a global feature distribution was constructed with the projected time-frequency features of all participants from all channels and applied for attention classification during motor movement execution. Time-frequency features led to significantly better classification results with respect to the temporal features, particularly for electrodes located over the motor cortex. Motor cortex channels had a higher accuracy in comparison to other channels in the global discrimination of attention level. Previous methods have used the attention to a task to drive external devices, such as the P300 speller. However, here we focus for the first time on the effect of attention drift while performing a motor task. It is possible to explore user's attention variation when performing motor tasks in synchronous BCI systems with time-frequency features. This is the first step towards an adaptive real-time BCI with an integrated function to reveal attention shifts from the motor task. Copyright © 2017 Elsevier B.V. All rights reserved.

Task and task-free fMRI reproducibility comparison for motor network identification

NARCIS (Netherlands)

Kristo, G.; Rutten, G.J.; Raemaekers, M.; de Gelder, B.; Rombouts, S.A.R.B.; Ramsey, N.F.

2014-01-01

Test-retest reliability of individual functional magnetic resonance imaging (fMRI) results is of importance in clinical practice and longitudinal experiments. While several studies have investigated reliability of task-induced motor network activation, less is known about the reliability of the

Region and task-specific activation of Arc in primary motor cortex of rats following motor skill learning.

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Hosp, J A; Mann, S; Wegenast-Braun, B M; Calhoun, M E; Luft, A R

2013-10-10

Motor learning requires protein synthesis within the primary motor cortex (M1). Here, we show that the immediate early gene Arc/Arg3.1 is specifically induced in M1 by learning a motor skill. Arc mRNA was quantified using a fluorescent in situ hybridization assay in adult Long-Evans rats learning a skilled reaching task (SRT), in rats performing reaching-like forelimb movement without learning (ACT) and in rats that were trained in the operant but not the motor elements of the task (controls). Apart from M1, Arc expression was assessed within the rostral motor area (RMA), primary somatosensory cortex (S1), striatum (ST) and cerebellum. In SRT animals, Arc mRNA levels in M1 contralateral to the trained limb were 31% higher than ipsilateral (pmotor skill learning in rats. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

Design and validation of a real-time spiking-neural-network decoder for brain-machine interfaces

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Dethier, Julie; Nuyujukian, Paul; Ryu, Stephen I.; Shenoy, Krishna V.; Boahen, Kwabena

2013-06-01

Objective. Cortically-controlled motor prostheses aim to restore functions lost to neurological disease and injury. Several proof of concept demonstrations have shown encouraging results, but barriers to clinical translation still remain. In particular, intracortical prostheses must satisfy stringent power dissipation constraints so as not to damage cortex. Approach. One possible solution is to use ultra-low power neuromorphic chips to decode neural signals for these intracortical implants. The first step is to explore in simulation the feasibility of translating decoding algorithms for brain-machine interface (BMI) applications into spiking neural networks (SNNs). Main results. Here we demonstrate the validity of the approach by implementing an existing Kalman-filter-based decoder in a simulated SNN using the Neural Engineering Framework (NEF), a general method for mapping control algorithms onto SNNs. To measure this system’s robustness and generalization, we tested it online in closed-loop BMI experiments with two rhesus monkeys. Across both monkeys, a Kalman filter implemented using a 2000-neuron SNN has comparable performance to that of a Kalman filter implemented using standard floating point techniques. Significance. These results demonstrate the tractability of SNN implementations of statistical signal processing algorithms on different monkeys and for several tasks, suggesting that a SNN decoder, implemented on a neuromorphic chip, may be a feasible computational platform for low-power fully-implanted prostheses. The validation of this closed-loop decoder system and the demonstration of its robustness and generalization hold promise for SNN implementations on an ultra-low power neuromorphic chip using the NEF.

Action observation versus motor imagery in learning a complex motor task: a short review of literature and a kinematics study.

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Gatti, R; Tettamanti, A; Gough, P M; Riboldi, E; Marinoni, L; Buccino, G

2013-04-12

Both motor imagery and action observation have been shown to play a role in learning or re-learning complex motor tasks. According to a well accepted view they share a common neurophysiological basis in the mirror neuron system. Neurons within this system discharge when individuals perform a specific action and when they look at another individual performing the same or a motorically related action. In the present paper, after a short review of literature on the role of action observation and motor imagery in motor learning, we report the results of a kinematics study where we directly compared motor imagery and action observation in learning a novel complex motor task. This involved movement of the right hand and foot in the same angular direction (in-phase movement), while at the same time moving the left hand and foot in an opposite angular direction (anti-phase movement), all at a frequency of 1Hz. Motor learning was assessed through kinematics recording of wrists and ankles. The results showed that action observation is better than motor imagery as a strategy for learning a novel complex motor task, at least in the fast early phase of motor learning. We forward that these results may have important implications in educational activities, sport training and neurorehabilitation. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Decoding communities in networks.

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Radicchi, Filippo

2018-02-01

According to a recent information-theoretical proposal, the problem of defining and identifying communities in networks can be interpreted as a classical communication task over a noisy channel: memberships of nodes are information bits erased by the channel, edges and nonedges in the network are parity bits introduced by the encoder but degraded through the channel, and a community identification algorithm is a decoder. The interpretation is perfectly equivalent to the one at the basis of well-known statistical inference algorithms for community detection. The only difference in the interpretation is that a noisy channel replaces a stochastic network model. However, the different perspective gives the opportunity to take advantage of the rich set of tools of coding theory to generate novel insights on the problem of community detection. In this paper, we illustrate two main applications of standard coding-theoretical methods to community detection. First, we leverage a state-of-the-art decoding technique to generate a family of quasioptimal community detection algorithms. Second and more important, we show that the Shannon's noisy-channel coding theorem can be invoked to establish a lower bound, here named as decodability bound, for the maximum amount of noise tolerable by an ideal decoder to achieve perfect detection of communities. When computed for well-established synthetic benchmarks, the decodability bound explains accurately the performance achieved by the best community detection algorithms existing on the market, telling us that only little room for their improvement is still potentially left.

Decoding communities in networks

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Radicchi, Filippo

2018-02-01

According to a recent information-theoretical proposal, the problem of defining and identifying communities in networks can be interpreted as a classical communication task over a noisy channel: memberships of nodes are information bits erased by the channel, edges and nonedges in the network are parity bits introduced by the encoder but degraded through the channel, and a community identification algorithm is a decoder. The interpretation is perfectly equivalent to the one at the basis of well-known statistical inference algorithms for community detection. The only difference in the interpretation is that a noisy channel replaces a stochastic network model. However, the different perspective gives the opportunity to take advantage of the rich set of tools of coding theory to generate novel insights on the problem of community detection. In this paper, we illustrate two main applications of standard coding-theoretical methods to community detection. First, we leverage a state-of-the-art decoding technique to generate a family of quasioptimal community detection algorithms. Second and more important, we show that the Shannon's noisy-channel coding theorem can be invoked to establish a lower bound, here named as decodability bound, for the maximum amount of noise tolerable by an ideal decoder to achieve perfect detection of communities. When computed for well-established synthetic benchmarks, the decodability bound explains accurately the performance achieved by the best community detection algorithms existing on the market, telling us that only little room for their improvement is still potentially left.

Visual Motor and Perceptual Task Performance in Astigmatic Students

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Erin M. Harvey

2017-01-01

Full Text Available Purpose. To determine if spectacle corrected and uncorrected astigmats show reduced performance on visual motor and perceptual tasks. Methods. Third through 8th grade students were assigned to the low refractive error control group (astigmatism < 1.00 D, myopia < 0.75 D, hyperopia < 2.50 D, and anisometropia < 1.50 D or bilateral astigmatism group (right and left eye ≥ 1.00 D based on cycloplegic refraction. Students completed the Beery-Buktenica Developmental Test of Visual Motor Integration (VMI and Visual Perception (VMIp. Astigmats were randomly assigned to testing with/without correction and control group was tested uncorrected. Analyses compared VMI and VMIp scores for corrected and uncorrected astigmats to the control group. Results. The sample included 333 students (control group 170, astigmats tested with correction 75, and astigmats tested uncorrected 88. Mean VMI score in corrected astigmats did not differ from the control group (p=0.829. Uncorrected astigmats had lower VMI scores than the control group (p=0.038 and corrected astigmats (p=0.007. Mean VMIp scores for uncorrected (p=0.209 and corrected astigmats (p=0.124 did not differ from the control group. Uncorrected astigmats had lower mean scores than the corrected astigmats (p=0.003. Conclusions. Uncorrected astigmatism influences visual motor and perceptual task performance. Previously spectacle treated astigmats do not show developmental deficits on visual motor or perceptual tasks when tested with correction.

The Effect of Haptic Guidance on Learning a Hybrid Rhythmic-Discrete Motor Task.

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Marchal-Crespo, Laura; Bannwart, Mathias; Riener, Robert; Vallery, Heike

2015-01-01

Bouncing a ball with a racket is a hybrid rhythmic-discrete motor task, combining continuous rhythmic racket movements with discrete impact events. Rhythmicity is exceptionally important in motor learning, because it underlies fundamental movements such as walking. Studies suggested that rhythmic and discrete movements are governed by different control mechanisms at different levels of the Central Nervous System. The aim of this study is to evaluate the effect of fixed/fading haptic guidance on learning to bounce a ball to a desired apex in virtual reality with varying gravity. Changing gravity changes dominance of rhythmic versus discrete control: The higher the value of gravity, the more rhythmic the task; lower values reduce the bouncing frequency and increase dwell times, eventually leading to a repetitive discrete task that requires initiation and termination, resembling target-oriented reaching. Although motor learning in the ball-bouncing task with varying gravity has been studied, the effect of haptic guidance on learning such a hybrid rhythmic-discrete motor task has not been addressed. We performed an experiment with thirty healthy subjects and found that the most effective training condition depended on the degree of rhythmicity: Haptic guidance seems to hamper learning of continuous rhythmic tasks, but it seems to promote learning for repetitive tasks that resemble discrete movements.

Differences in visuo-motor control in skilled vs. novice martial arts athletes during sustained and transient attention tasks: a motor-related cortical potential study.

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Sanchez-Lopez, Javier; Fernandez, Thalia; Silva-Pereyra, Juan; Martinez Mesa, Juan A; Di Russo, Francesco

2014-01-01

Cognitive and motor processes are essential for optimal athletic performance. Individuals trained in different skills and sports may have specialized cognitive abilities and motor strategies related to the characteristics of the activity and the effects of training and expertise. Most studies have investigated differences in motor-related cortical potential (MRCP) during self-paced tasks in athletes but not in stimulus-related tasks. The aim of the present study was to identify the differences in performance and MRCP between skilled and novice martial arts athletes during two different types of tasks: a sustained attention task and a transient attention task. Behavioral and electrophysiological data from twenty-two martial arts athletes were obtained while they performed a continuous performance task (CPT) to measure sustained attention and a cued continuous performance task (c-CPT) to measure transient attention. MRCP components were analyzed and compared between groups. Electrophysiological data in the CPT task indicated larger prefrontal positive activity and greater posterior negativity distribution prior to a motor response in the skilled athletes, while novices showed a significantly larger response-related P3 after a motor response in centro-parietal areas. A different effect occurred in the c-CPT task in which the novice athletes showed strong prefrontal positive activity before a motor response and a large response-related P3, while in skilled athletes, the prefrontal activity was absent. We propose that during the CPT, skilled athletes were able to allocate two different but related processes simultaneously according to CPT demand, which requires controlled attention and controlled motor responses. On the other hand, in the c-CPT, skilled athletes showed better cue facilitation, which permitted a major economy of resources and "automatic" or less controlled responses to relevant stimuli. In conclusion, the present data suggest that motor expertise

Robust tactile sensory responses in finger area of primate motor cortex relevant to prosthetic control

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Schroeder, Karen E.; Irwin, Zachary T.; Bullard, Autumn J.; Thompson, David E.; Bentley, J. Nicole; Stacey, William C.; Patil, Parag G.; Chestek, Cynthia A.

2017-08-01

Objective. Challenges in improving the performance of dexterous upper-limb brain-machine interfaces (BMIs) have prompted renewed interest in quantifying the amount and type of sensory information naturally encoded in the primary motor cortex (M1). Previous single unit studies in monkeys showed M1 is responsive to tactile stimulation, as well as passive and active movement of the limbs. However, recent work in this area has focused primarily on proprioception. Here we examined instead how tactile somatosensation of the hand and fingers is represented in M1. Approach. We recorded multi- and single units and thresholded neural activity from macaque M1 while gently brushing individual finger pads at 2 Hz. We also recorded broadband neural activity from electrocorticogram (ECoG) grids placed on human motor cortex, while applying the same tactile stimulus. Main results. Units displaying significant differences in firing rates between individual fingers (p  sensory information was present in M1 to correctly decode stimulus position from multiunit activity above chance levels in all monkeys, and also from ECoG gamma power in two human subjects. Significance. These results provide some explanation for difficulties experienced by motor decoders in clinical trials of cortically controlled prosthetic hands, as well as the general problem of disentangling motor and sensory signals in primate motor cortex during dextrous tasks. Additionally, examination of unit tuning during tactile and proprioceptive inputs indicates cells are often tuned differently in different contexts, reinforcing the need for continued refinement of BMI training and decoding approaches to closed-loop BMI systems for dexterous grasping.

Decoding Speech With Integrated Hybrid Signals Recorded From the Human Ventral Motor Cortex

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Kenji Ibayashi

2018-04-01

Full Text Available Restoration of speech communication for locked-in patients by means of brain computer interfaces (BCIs is currently an important area of active research. Among the neural signals obtained from intracranial recordings, single/multi-unit activity (SUA/MUA, local field potential (LFP, and electrocorticography (ECoG are good candidates for an input signal for BCIs. However, the question of which signal or which combination of the three signal modalities is best suited for decoding speech production remains unverified. In order to record SUA, LFP, and ECoG simultaneously from a highly localized area of human ventral sensorimotor cortex (vSMC, we fabricated an electrode the size of which was 7 by 13 mm containing sparsely arranged microneedle and conventional macro contacts. We determined which signal modality is the most capable of decoding speech production, and tested if the combination of these signals could improve the decoding accuracy of spoken phonemes. Feature vectors were constructed from spike frequency obtained from SUAs and event-related spectral perturbation derived from ECoG and LFP signals, then input to the decoder. The results showed that the decoding accuracy for five spoken vowels was highest when features from multiple signals were combined and optimized for each subject, and reached 59% when averaged across all six subjects. This result suggests that multi-scale signals convey complementary information for speech articulation. The current study demonstrated that simultaneous recording of multi-scale neuronal activities could raise decoding accuracy even though the recording area is limited to a small portion of cortex, which is advantageous for future implementation of speech-assisting BCIs.

Task-specificity of unilateral anodal and dual-M1 tDCS effects on motor learning.

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Karok, Sophia; Fletcher, David; Witney, Alice G

2017-01-08

Task-specific effects of transcranial direct current stimulation (tDCS) on motor learning were investigated in 30 healthy participants. In a sham-controlled, mixed design, participants trained on 3 different motor tasks (Purdue Pegboard Test, Visuomotor Grip Force Tracking Task and Visuomotor Wrist Rotation Speed Control Task) over 3 consecutive days while receiving either unilateral anodal over the right primary motor cortex (M1), dual-M1 or sham stimulation. Retention sessions were administered 7 and 28 days after the end of training. In the Purdue Pegboard Test, both anodal and dual-M1 stimulation reduced average completion time approximately equally, an improvement driven by online learning effects and maintained for about 1 week. The Visuomotor Grip Force Tracking Task and the Visuomotor Wrist Rotation Speed Control Task were associated with an advantage of dual-M1 tDCS in consolidation processes both between training sessions and when testing at long-term retention; both were maintained for at least 1 month. This study demonstrates that M1-tDCS enhances and sustains motor learning with different electrode montages. Stimulation-induced effects emerged at different learning phases across the tasks, which strongly suggests that the influence of tDCS on motor learning is dynamic with respect to the functional recruitment of the distributed motor system at the time of stimulation. Divergent findings regarding M1-tDCS effects on motor learning may partially be ascribed to task-specific consequences and the effects of offline consolidation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Improved prediction of bimanual movements by a two-staged (effector-then-trajectory) decoder with epidural ECoG in nonhuman primates

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Choi, Hoseok; Lee, Jeyeon; Park, Jinsick; Lee, Seho; Ahn, Kyoung-ha; Kim, In Young; Lee, Kyoung-Min; Jang, Dong Pyo

2018-02-01

Objective. In arm movement BCIs (brain-computer interfaces), unimanual research has been much more extensively studied than its bimanual counterpart. However, it is well known that the bimanual brain state is different from the unimanual one. Conventional methodology used in unimanual studies does not take the brain stage into consideration, and therefore appears to be insufficient for decoding bimanual movements. In this paper, we propose the use of a two-staged (effector-then-trajectory) decoder, which combines the classification of movement conditions and uses a hand trajectory predicting algorithm for unimanual and bimanual movements, for application in real-world BCIs. Approach. Two micro-electrode patches (32 channels) were inserted over the dura mater of the left and right hemispheres of two rhesus monkeys, covering the motor related cortex for epidural electrocorticograph (ECoG). Six motion sensors (inertial measurement unit) were used to record the movement signals. The monkeys performed three types of arm movement tasks: left unimanual, right unimanual, bimanual. To decode these movements, we used a two-staged decoder, which combines the effector classifier for four states (left unimanual, right unimanual, bimanual movements, and stationary state) and movement predictor using regression. Main results. Using this approach, we successfully decoded both arm positions using the proposed decoder. The results showed that decoding performance for bimanual movements were improved compared to the conventional method, which does not consider the effector, and the decoding performance was significant and stable over a period of four months. In addition, we also demonstrated the feasibility of epidural ECoG signals, which provided an adequate level of decoding accuracy. Significance. These results provide evidence that brain signals are different depending on the movement conditions or effectors. Thus, the two-staged method could be useful if BCIs are used to

State-Dependent Decoding Algorithms Improve the Performance of a Bidirectional BMI in Anesthetized Rats

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Vito De Feo

2017-05-01

Full Text Available Brain-machine interfaces (BMIs promise to improve the quality of life of patients suffering from sensory and motor disabilities by creating a direct communication channel between the brain and the external world. Yet, their performance is currently limited by the relatively small amount of information that can be decoded from neural activity recorded form the brain. We have recently proposed that such decoding performance may be improved when using state-dependent decoding algorithms that predict and discount the large component of the trial-to-trial variability of neural activity which is due to the dependence of neural responses on the network's current internal state. Here we tested this idea by using a bidirectional BMI to investigate the gain in performance arising from using a state-dependent decoding algorithm. This BMI, implemented in anesthetized rats, controlled the movement of a dynamical system using neural activity decoded from motor cortex and fed back to the brain the dynamical system's position by electrically microstimulating somatosensory cortex. We found that using state-dependent algorithms that tracked the dynamics of ongoing activity led to an increase in the amount of information extracted form neural activity by 22%, with a consequently increase in all of the indices measuring the BMI's performance in controlling the dynamical system. This suggests that state-dependent decoding algorithms may be used to enhance BMIs at moderate computational cost.

State-Dependent Decoding Algorithms Improve the Performance of a Bidirectional BMI in Anesthetized Rats.

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De Feo, Vito; Boi, Fabio; Safaai, Houman; Onken, Arno; Panzeri, Stefano; Vato, Alessandro

2017-01-01

Brain-machine interfaces (BMIs) promise to improve the quality of life of patients suffering from sensory and motor disabilities by creating a direct communication channel between the brain and the external world. Yet, their performance is currently limited by the relatively small amount of information that can be decoded from neural activity recorded form the brain. We have recently proposed that such decoding performance may be improved when using state-dependent decoding algorithms that predict and discount the large component of the trial-to-trial variability of neural activity which is due to the dependence of neural responses on the network's current internal state. Here we tested this idea by using a bidirectional BMI to investigate the gain in performance arising from using a state-dependent decoding algorithm. This BMI, implemented in anesthetized rats, controlled the movement of a dynamical system using neural activity decoded from motor cortex and fed back to the brain the dynamical system's position by electrically microstimulating somatosensory cortex. We found that using state-dependent algorithms that tracked the dynamics of ongoing activity led to an increase in the amount of information extracted form neural activity by 22%, with a consequently increase in all of the indices measuring the BMI's performance in controlling the dynamical system. This suggests that state-dependent decoding algorithms may be used to enhance BMIs at moderate computational cost.

Cortical ensemble activity increasingly predicts behaviour outcomes during learning of a motor task

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Laubach, Mark; Wessberg, Johan; Nicolelis, Miguel A. L.

2000-06-01

When an animal learns to make movements in response to different stimuli, changes in activity in the motor cortex seem to accompany and underlie this learning. The precise nature of modifications in cortical motor areas during the initial stages of motor learning, however, is largely unknown. Here we address this issue by chronically recording from neuronal ensembles located in the rat motor cortex, throughout the period required for rats to learn a reaction-time task. Motor learning was demonstrated by a decrease in the variance of the rats' reaction times and an increase in the time the animals were able to wait for a trigger stimulus. These behavioural changes were correlated with a significant increase in our ability to predict the correct or incorrect outcome of single trials based on three measures of neuronal ensemble activity: average firing rate, temporal patterns of firing, and correlated firing. This increase in prediction indicates that an association between sensory cues and movement emerged in the motor cortex as the task was learned. Such modifications in cortical ensemble activity may be critical for the initial learning of motor tasks.

Task-specific compensation and recovery following focal motor cortex lesion in stressed rats.

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Kirkland, Scott W; Smith, Lori K; Metz, Gerlinde A

2012-03-01

One reason for the difficulty to develop effective therapies for stroke is that intrinsic factors, such as stress, may critically influence pathological mechanisms and recovery. In cognitive tasks, stress can both exaggerate and alleviate functional loss after focal ischemia in rodents. Using a comprehensive motor assessment in rats, this study examined if chronic stress and corticosterone treatment affect skill recovery and compensation in a task-specific manner. Groups of rats received daily restraint stress or oral corticosterone supplementation for two weeks prior to a focal motor cortex lesion. After lesion, stress and corticosterone treatments continued for three weeks. Motor performance was assessed in two skilled reaching tasks, skilled walking, forelimb inhibition, forelimb asymmetry and open field behavior. The results revealed that persistent stress and elevated corticosterone levels mainly limit motor recovery. Treated animals dropped larger amounts of food in successful reaches and showed exaggerated loss of forelimb inhibition early after lesion. Stress also caused a moderate, but non-significant increase in infarct size. By contrast, stress and corticosterone treatments promoted reaching success and other quantitative measures in the tray reaching task. Comparative analysis revealed that improvements are due to task-specific development of compensatory strategies. These findings suggest that stress and stress hormones may partially facilitate task-specific and adaptive compensatory movement strategies. The observations support the notion that hypothalamic-pituitary-adrenal axis activation may be a key determinant of recovery and motor system plasticity after ischemic stroke.

Task-dependent output of human parasternal intercostal motor units across spinal levels.

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Hudson, Anna L; Gandevia, Simon C; Butler, Jane E

2017-12-01

During breathing, there is differential activity in the human parasternal intercostal muscles and the activity is tightly coupled to the known mechanical advantages for inspiration of the same regions of muscles. It is not known whether differential activity is preserved for the non-respiratory task of ipsilateral trunk rotation. In the present study, we compared single motor units during resting breathing and axial rotation of the trunk during apnoea. We not only confirmed non-uniform recruitment of motor units across parasternal intercostal muscles in breathing, but also demonstrated that the same motor units show an altered pattern of recruitment in the non-respiratory task of trunk rotation. The output of parasternal intercostal motoneurones is modulated differently across spinal levels depending on the task and these results help us understand the mechanisms that may govern task-dependent differences in motoneurone output. During inspiration, there is differential activity in the human parasternal intercostal muscles across interspaces. We investigated whether the earlier recruitment of motor units in the rostral interspaces compared to more caudal spaces during inspiration is preserved for the non-respiratory task of ipsilateral trunk rotation. Single motor unit activity (SMU) was recorded from the first, second and fourth parasternal interspaces on the right side in five participants in two tasks: resting breathing and 'isometric' axial rotation of the trunk during apnoea. Recruitment of the same SMUs was compared between tasks (n = 123). During resting breathing, differential activity was indicated by earlier recruitment of SMUs in the first and second interspaces compared to the fourth space in inspiration (P motor units showed an altered pattern of recruitment because SMUs in the first interspace were recruited later and at a higher rotation torque than those in the second and fourth interspaces (P recruitment measures, was good-excellent [intraclass

Comparing Recalibration Strategies for Electroencephalography-Based Decoders of Movement Intention in Neurological Patients with Motor Disability.

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López-Larraz, Eduardo; Ibáñez, Jaime; Trincado-Alonso, Fernando; Monge-Pereira, Esther; Pons, José Luis; Montesano, Luis

2017-12-17

Motor rehabilitation based on the association of electroencephalographic (EEG) activity and proprioceptive feedback has been demonstrated as a feasible therapy for patients with paralysis. To promote long-lasting motor recovery, these interventions have to be carried out across several weeks or even months. The success of these therapies partly relies on the performance of the system decoding movement intentions, which normally has to be recalibrated to deal with the nonstationarities of the cortical activity. Minimizing the recalibration times is important to reduce the setup preparation and maximize the effective therapy time. To date, a systematic analysis of the effect of recalibration strategies in EEG-driven interfaces for motor rehabilitation has not yet been performed. Data from patients with stroke (4 patients, 8 sessions) and spinal cord injury (SCI) (4 patients, 5 sessions) undergoing two different paradigms (self-paced and cue-guided, respectively) are used to study the performance of the EEG-based classification of motor intentions. Four calibration schemes are compared, considering different combinations of training datasets from previous and/or the validated session. The results show significant differences in classifier performances in terms of the true and false positives (TPs) and (FPs). Combining training data from previous sessions with data from the validation session provides the best compromise between the amount of data needed for calibration and the classifier performance. With this scheme, the average true (false) positive rates obtained are 85.3% (17.3%) and 72.9% (30.3%) for the self-paced and the cue-guided protocols, respectively. These results suggest that the use of optimal recalibration schemes for EEG-based classifiers of motor intentions leads to enhanced performances of these technologies, while not requiring long calibration phases prior to starting the intervention.

Cognitive-motor dual-task interference: A systematic review of neural correlates.

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Leone, Carmela; Feys, Peter; Moumdjian, Lousin; D'Amico, Emanuele; Zappia, Mario; Patti, Francesco

2017-04-01

Cognitive-motor interference refers to dual-tasking (DT) interference (DTi) occurring when the simultaneous performance of a cognitive and a motor task leads to a percentage change in one or both tasks. Several theories exist to explain DTi in humans: the capacity-sharing, the bottleneck and the cross-talk theories. Numerous studies investigating whether a specific brain locus is associated with cognitive-motor DTi have been conducted, but not systematically reviewed. We aimed to review the evidences on brain activity associated with the cognitive-motor DT, in order to better understand the neurological basis of the CMi. Results were reported according to the technique used to assess brain activity. Twenty-three articles met the inclusion criteria. Out of them, nine studies used functional magnetic resonance imaging to show an additive, under-additive, over- additive, or a mixed activation pattern of the brain. Seven studies used near-infrared spectroscopy, and seven neurophysiological instruments. Yet a specific DT locus in the brain cannot be concluded from the overall current literature. Future studies are warranted to overcome the shortcomings identified. Copyright © 2017 Elsevier Ltd. All rights reserved.

Local-learning-based neuron selection for grasping gesture prediction in motor brain machine interfaces

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Xu, Kai; Wang, Yiwen; Wang, Yueming; Wang, Fang; Hao, Yaoyao; Zhang, Shaomin; Zhang, Qiaosheng; Chen, Weidong; Zheng, Xiaoxiang

2013-04-01

Objective. The high-dimensional neural recordings bring computational challenges to movement decoding in motor brain machine interfaces (mBMI), especially for portable applications. However, not all recorded neural activities relate to the execution of a certain movement task. This paper proposes to use a local-learning-based method to perform neuron selection for the gesture prediction in a reaching and grasping task. Approach. Nonlinear neural activities are decomposed into a set of linear ones in a weighted feature space. A margin is defined to measure the distance between inter-class and intra-class neural patterns. The weights, reflecting the importance of neurons, are obtained by minimizing a margin-based exponential error function. To find the most dominant neurons in the task, 1-norm regularization is introduced to the objective function for sparse weights, where near-zero weights indicate irrelevant neurons. Main results. The signals of only 10 neurons out of 70 selected by the proposed method could achieve over 95% of the full recording's decoding accuracy of gesture predictions, no matter which different decoding methods are used (support vector machine and K-nearest neighbor). The temporal activities of the selected neurons show visually distinguishable patterns associated with various hand states. Compared with other algorithms, the proposed method can better eliminate the irrelevant neurons with near-zero weights and provides the important neuron subset with the best decoding performance in statistics. The weights of important neurons converge usually within 10-20 iterations. In addition, we study the temporal and spatial variation of neuron importance along a period of one and a half months in the same task. A high decoding performance can be maintained by updating the neuron subset. Significance. The proposed algorithm effectively ascertains the neuronal importance without assuming any coding model and provides a high performance with different

Task-dependent changes of corticospinal excitability during observation and motor imagery of balance tasks.

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Mouthon, A; Ruffieux, J; Wälchli, M; Keller, M; Taube, W

2015-09-10

Non-physical balance training has demonstrated to be efficient to improve postural control in young people. However, little is known about the potential to increase corticospinal excitability by mental simulation in lower leg muscles. Mental simulation of isolated, voluntary contractions of limb muscles increase corticospinal excitability but more automated tasks like walking seem to have no or only minor effects on motor-evoked potentials (MEPs) evoked by transcranial magnetic stimulation (TMS). This may be related to the way of performing the mental simulation or the task itself. Therefore, the present study aimed to clarify how corticospinal excitability is modulated during AO+MI, MI and action observation (AO) of balance tasks. For this purpose, MEPs and H-reflexes were elicited during three different mental simulations (a) AO+MI, (b) MI and (c) passive AO. For each condition, two balance tasks were evaluated: (1) quiet upright stance (static) and (2) compensating a medio-lateral perturbation while standing on a free-swinging platform (dynamic). AO+MI resulted in the largest facilitation of MEPs followed by MI and passive AO. MEP facilitation was significantly larger in the dynamic perturbation than in the static standing task. Interestingly, passive observation resulted in hardly any facilitation independent of the task. H-reflex amplitudes were not modulated. The current results demonstrate that corticospinal excitability during mental simulation of balance tasks is influenced by both the type of mental simulation and the task difficulty. As H-reflexes and background EMG were not modulated, it may be argued that changes in excitability of the primary motor cortex were responsible for the MEP modulation. From a functional point of view, our findings suggest best training/rehabilitation effects when combining MI with AO during challenging postural tasks. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

The manic phase of Bipolar disorder significantly impairs theory of mind decoding.

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Hawken, Emily R; Harkness, Kate L; Lazowski, Lauren K; Summers, David; Khoja, Nida; Gregory, James Gardner; Milev, Roumen

2016-05-30

Bipolar disorder is associated with significant deficits in the decoding of others' mental states in comparison to healthy participants. However, differences in theory of mind decoding ability among patients in manic, depressed, and euthymic phases of bipolar disorder is currently unknown. Fifty-nine patients with bipolar I or II disorder (13 manic, 25 depressed, 20 euthymic) completed the "Reading the Mind in the Eyes" Task (Eyes task) and the Animals Task developed to control for non-mentalistic response demands of the Eyes Task. Patients also completed self-report and clinician-rated measures of depression, mania, and anxiety symptoms. Patients in the manic phase were significantly less accurate than those in the depressed and euthymic phases at decoding mental states in the Eyes task, and this effect was strongest for eyes of a positive or neutral valence. Further Eyes task performance was negatively correlated with the symptoms of language/thought disorder, pressured speech, and disorganized thoughts and appearance. These effects held when controlling for accuracy on the Animals task, response times, and relevant demographic and clinical covariates. Results suggest that the state of mania, and particularly psychotic symptoms that may overlap with the schizophrenia spectrum, are most strongly related to social cognitive deficits in bipolar disorder. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Structural Correlates of Skilled Performance on a Motor Sequence Task

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Christopher J Steele

2012-10-01

Full Text Available The brain regions functionally engaged in motor sequence performance are well established, but the structural characteristics of these regions and the fibre pathways involved have been less well studied. In addition, relatively few studies have combined multiple magnetic resonance imaging (MRI and behavioural performance measures in the same sample. Therefore, the current study used diffusion tensor imaging, probabilistic tractography, and voxel-based morphometry to determine the structural correlates of skilled motor performance. Further, we compared these findings with fMRI results in the same sample. We correlated final performance and rate of improvement measures on a temporal motor sequence task with skeletonised fractional anisotropy (FA and whole brain grey matter (GM volume. Final synchronisation performance was negatively correlated with FA in white matter underlying bilateral sensorimotor cortex – an effect that was mediated by a positive correlation with radial diffusivity. Multi-fibre tractography indicated that this region contained crossing fibres from the corticospinal tract and superior longitudinal fasciculus (SLF. The identified SLF pathway linked parietal and auditory cortical regions that have been shown to be functionally engaged in this task. Thus, we hypothesise that enhanced synchronisation performance on this task may be related to greater fibre integrity of the SLF. Rate of improvement on synchronisation was positively correlated with GM volume in cerebellar lobules HVI and V – regions that showed training-related decreases in activity in the same sample. Taken together, our results link individual differences in brain structure and function to motor sequence performance on the same task. Further, our study illustrates the utility of using multiple MR measures and analysis techniques to specify the interpretation of structural findings.

Monte Carlo point process estimation of electromyographic envelopes from motor cortical spikes for brain-machine interfaces

Science.gov (United States)

Liao, Yuxi; She, Xiwei; Wang, Yiwen; Zhang, Shaomin; Zhang, Qiaosheng; Zheng, Xiaoxiang; Principe, Jose C.

2015-12-01

Objective. Representation of movement in the motor cortex (M1) has been widely studied in brain-machine interfaces (BMIs). The electromyogram (EMG) has greater bandwidth than the conventional kinematic variables (such as position, velocity), and is functionally related to the discharge of cortical neurons. As the stochastic information of EMG is derived from the explicit spike time structure, point process (PP) methods will be a good solution for decoding EMG directly from neural spike trains. Previous studies usually assume linear or exponential tuning curves between neural firing and EMG, which may not be true. Approach. In our analysis, we estimate the tuning curves in a data-driven way and find both the traditional functional-excitatory and functional-inhibitory neurons, which are widely found across a rat’s motor cortex. To accurately decode EMG envelopes from M1 neural spike trains, the Monte Carlo point process (MCPP) method is implemented based on such nonlinear tuning properties. Main results. Better reconstruction of EMG signals is shown on baseline and extreme high peaks, as our method can better preserve the nonlinearity of the neural tuning during decoding. The MCPP improves the prediction accuracy (the normalized mean squared error) 57% and 66% on average compared with the adaptive point process filter using linear and exponential tuning curves respectively, for all 112 data segments across six rats. Compared to a Wiener filter using spike rates with an optimal window size of 50 ms, MCPP decoding EMG from a point process improves the normalized mean square error (NMSE) by 59% on average. Significance. These results suggest that neural tuning is constantly changing during task execution and therefore, the use of spike timing methodologies and estimation of appropriate tuning curves needs to be undertaken for better EMG decoding in motor BMIs.

Over-focused? The relation between patients' inclination for conscious control and single- and dual-task motor performance after stroke.

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Denneman, R P M; Kal, E C; Houdijk, H; Kamp, J van der

2018-05-01

Many stroke patients are inclined to consciously control their movements. This is thought to negatively affect patients' motor performance, as it disrupts movement automaticity. However, it has also been argued that conscious control may sometimes benefit motor performance, depending on the task or patientś motor or cognitive capacity. To assess whether stroke patients' inclination for conscious control is associated with motor performance, and explore whether the putative association differs as a function of task (single- vs dual) or patientś motor and cognitive capacity. Univariate and multivariate linear regression analysis were used to assess associations between patients' disposition to conscious control (i.e., Conscious Motor Processing subscale of Movement-Specific Reinvestment Scale; MSRS-CMP) and single-task (Timed-up-and-go test; TuG) and motor dual-task costs (TuG while tone counting; motor DTC%). We determined whether these associations were influenced by patients' walking speed (i.e., 10-m-walk test) and cognitive capacity (i.e., working memory, attention, executive function). Seventy-eight clinical stroke patients (task TuG performance. However, patients with a strong inclination for conscious control showed higher motor DTC%. These associations were irrespective of patients' motor and cognitive abilities. Patients' disposition for conscious control was not associated with single task motor performance, but was associated with higher motor dual task costs, regardless of patients' motor or cognitive abilities. Therapists should be aware that patients' conscious control inclination can influence their dual-task performance while moving. Longitudinal studies are required to test whether reducing patients' disposition for conscious control would improve dual-tasking post-stroke. Copyright © 2018 Elsevier B.V. All rights reserved.

Superior arm-movement decoding from cortex with a new, unsupervised-learning algorithm

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Makin, Joseph G.; O'Doherty, Joseph E.; Cardoso, Mariana M. B.; Sabes, Philip N.

2018-04-01

Objective. The aim of this work is to improve the state of the art for motor-control with a brain-machine interface (BMI). BMIs use neurological recording devices and decoding algorithms to transform brain activity directly into real-time control of a machine, archetypically a robotic arm or a cursor. The standard procedure treats neural activity—vectors of spike counts in small temporal windows—as noisy observations of the kinematic state (position, velocity, acceleration) of the fingertip. Inferring the state from the observations then takes the form of a dynamical filter, typically some variant on Kalman’s (KF). The KF, however, although fairly robust in practice, is optimal only when the relationships between variables are linear and the noise is Gaussian, conditions usually violated in practice. Approach. To overcome these limitations we introduce a new filter, the ‘recurrent exponential-family harmonium’ (rEFH), that models the spike counts explicitly as Poisson-distributed, and allows for arbitrary nonlinear dynamics and observation models. Furthermore, the model underlying the filter is acquired through unsupervised learning, which allows temporal correlations in spike counts to be explained by latent dynamics that do not necessarily correspond to the kinematic state of the fingertip. Main results. We test the rEFH on offline reconstruction of the kinematics of reaches in the plane. The rEFH outperforms the standard, as well as three other state-of-the-art, decoders, across three monkeys, two different tasks, most kinematic variables, and a range of bin widths, amounts of training data, and numbers of neurons. Significance. Our algorithm establishes a new state of the art for offline decoding of reaches—in particular, for fingertip velocities, the variable used for control in most online decoders.

Decoding of Human Movements Based on Deep Brain Local Field Potentials Using Ensemble Neural Networks

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Mohammad S. Islam

2017-01-01

Full Text Available Decoding neural activities related to voluntary and involuntary movements is fundamental to understanding human brain motor circuits and neuromotor disorders and can lead to the development of neuromotor prosthetic devices for neurorehabilitation. This study explores using recorded deep brain local field potentials (LFPs for robust movement decoding of Parkinson’s disease (PD and Dystonia patients. The LFP data from voluntary movement activities such as left and right hand index finger clicking were recorded from patients who underwent surgeries for implantation of deep brain stimulation electrodes. Movement-related LFP signal features were extracted by computing instantaneous power related to motor response in different neural frequency bands. An innovative neural network ensemble classifier has been proposed and developed for accurate prediction of finger movement and its forthcoming laterality. The ensemble classifier contains three base neural network classifiers, namely, feedforward, radial basis, and probabilistic neural networks. The majority voting rule is used to fuse the decisions of the three base classifiers to generate the final decision of the ensemble classifier. The overall decoding performance reaches a level of agreement (kappa value at about 0.729±0.16 for decoding movement from the resting state and about 0.671±0.14 for decoding left and right visually cued movements.

Trial-to-trial reoptimization of motor behavior due to changes in task demands is limited.

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Orban de Xivry J-J

Full Text Available Each task requires a specific motor behavior that is tuned to task demands. For instance, writing requires a lot of accuracy while clapping does not. It is known that the brain adjusts the motor behavior to different task demands as predicted by optimal control theory. In this study, the mechanism of this reoptimization process is investigated by varying the accuracy demands of a reaching task. In this task, the width of the reaching target (0.5 or 8 cm was varied either on a trial-to-trial basis (random schedule or in blocks (blocked schedule. On some trials, the hand of the subjects was clamped to a rectilinear trajectory that ended 2 cm on the left or right of the target center. The rejection of this perturbation largely varied with target width in the blocked schedule but not in the random schedule. That is, subjects exhibited different motor behavior in the different schedules despite identical accuracy demands. Therefore, while reoptimization has been considered immediate and automatic, the differences in motor behavior observed across schedules suggest that the reoptimization of the motor behavior is neither happening on a trial-by-trial basis nor obligatory. The absence of trial-to-trial mechanisms, the inability of the brain to adapt to two conflicting task demands and the existence of a switching cost are discussed as possible sources of the non-optimality of motor behavior during the random schedule.

Real-time SHVC software decoding with multi-threaded parallel processing

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Gudumasu, Srinivas; He, Yuwen; Ye, Yan; He, Yong; Ryu, Eun-Seok; Dong, Jie; Xiu, Xiaoyu

2014-09-01

This paper proposes a parallel decoding framework for scalable HEVC (SHVC). Various optimization technologies are implemented on the basis of SHVC reference software SHM-2.0 to achieve real-time decoding speed for the two layer spatial scalability configuration. SHVC decoder complexity is analyzed with profiling information. The decoding process at each layer and the up-sampling process are designed in parallel and scheduled by a high level application task manager. Within each layer, multi-threaded decoding is applied to accelerate the layer decoding speed. Entropy decoding, reconstruction, and in-loop processing are pipeline designed with multiple threads based on groups of coding tree units (CTU). A group of CTUs is treated as a processing unit in each pipeline stage to achieve a better trade-off between parallelism and synchronization. Motion compensation, inverse quantization, and inverse transform modules are further optimized with SSE4 SIMD instructions. Simulations on a desktop with an Intel i7 processor 2600 running at 3.4 GHz show that the parallel SHVC software decoder is able to decode 1080p spatial 2x at up to 60 fps (frames per second) and 1080p spatial 1.5x at up to 50 fps for those bitstreams generated with SHVC common test conditions in the JCT-VC standardization group. The decoding performance at various bitrates with different optimization technologies and different numbers of threads are compared in terms of decoding speed and resource usage, including processor and memory.

The effect of caffeine on cognitive task performance and motor fatigue

NARCIS (Netherlands)

van Duinen, Hiske; Lorist, Monicque M.; Zijdewind, Inge

Rationale: In everyday life, people are usually capable of performing two tasks simultaneously. However, in a previous study we showed that during a fatiguing motor task, cognitive performance declined progressively. There is extensive literature on the ( positive) effects of caffeine on cognitive

Transcranial direct current stimulation over multiple days enhances motor performance of a grip task.

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Fan, Julie; Voisin, Julien; Milot, Marie-Hélène; Higgins, Johanne; Boudrias, Marie-Hélène

2017-09-01

Recovery of handgrip is critical after stroke since it is positively related to upper limb function. To boost motor recovery, transcranial direct current stimulation (tDCS) is a promising, non-invasive brain stimulation technique for the rehabilitation of persons with stroke. When applied over the primary motor cortex (M1), tDCS has been shown to modulate neural processes involved in motor learning. However, no studies have looked at the impact of tDCS on the learning of a grip task in both stroke and healthy individuals. To assess the use of tDCS over multiple days to promote motor learning of a grip task using a learning paradigm involving a speed-accuracy tradeoff in healthy individuals. In a double-blinded experiment, 30 right-handed subjects (mean age: 22.1±3.3 years) participated in the study and were randomly assigned to an anodal (n=15) or sham (n=15) stimulation group. First, subjects performed the grip task with their dominant hand while following the pace of a metronome. Afterwards, subjects trained on the task, at their own pace, over 5 consecutive days while receiving sham or anodal tDCS over M1. After training, subjects performed de novo the metronome-assisted task. The change in performance between the pre and post metronome-assisted task was used to assess the impact of the grip task and tDCS on learning. Anodal tDCS over M1 had a significant effect on the speed-accuracy tradeoff function. The anodal tDCS group showed significantly greater improvement in performance (39.28±15.92%) than the sham tDCS group (24.06±16.35%) on the metronome-assisted task, t(28)=2.583, P=0.015 (effect size d=0.94). Anodal tDCS is effective in promoting grip motor learning in healthy individuals. Further studies are warranted to test its potential use for the rehabilitation of fine motor skills in stroke patients. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Neuronal Substrates Underlying Performance Variability in Well-Trained Skillful Motor Task in Humans.

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Mizuguchi, Nobuaki; Uehara, Shintaro; Hirose, Satoshi; Yamamoto, Shinji; Naito, Eiichi

2016-01-01

Motor performance fluctuates trial by trial even in a well-trained motor skill. Here we show neural substrates underlying such behavioral fluctuation in humans. We first scanned brain activity with functional magnetic resonance imaging while healthy participants repeatedly performed a 10 s skillful sequential finger-tapping task. Before starting the experiment, the participants had completed intensive training. We evaluated task performance per trial (number of correct sequences in 10 s) and depicted brain regions where the activity changes in association with the fluctuation of the task performance across trials. We found that the activity in a broader range of frontoparietocerebellar network, including the bilateral dorsolateral prefrontal cortex (DLPFC), anterior cingulate and anterior insular cortices, and left cerebellar hemisphere, was negatively correlated with the task performance. We further showed in another transcranial direct current stimulation (tDCS) experiment that task performance deteriorated, when we applied anodal tDCS to the right DLPFC. These results indicate that fluctuation of brain activity in the nonmotor frontoparietocerebellar network may underlie trial-by-trial performance variability even in a well-trained motor skill, and its neuromodulation with tDCS may affect the task performance.

Classification of EEG signals to identify variations in attention during motor task execution

DEFF Research Database (Denmark)

Aliakbaryhosseinabadi, Susan; Kamavuako, Ernest Nlandu; Jiang, Ning

2017-01-01

attentionlevels onmotor tasks ineachparticipant. Then, a globalfeature distribution was constructed with the projected time-frequency features of all participants from all channels and applied for attention classification during motor movement execution. Results: Time-frequency features led to significantly...... BCI systems with time-frequency features. This is the first step towards an adaptive real-time BCI with an integrated function to reveal attention shifts from the motor task....

Poststimulation time interval-dependent effects of motor cortex anodal tDCS on reaction-time task performance.

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Molero-Chamizo, Andrés; Alameda Bailén, José R; Garrido Béjar, Tamara; García López, Macarena; Jaén Rodríguez, Inmaculada; Gutiérrez Lérida, Carolina; Pérez Panal, Silvia; González Ángel, Gloria; Lemus Corchero, Laura; Ruiz Vega, María J; Nitsche, Michael A; Rivera-Urbina, Guadalupe N

2018-02-01

Anodal transcranial direct current stimulation (tDCS) induces long-term potentiation-like plasticity, which is associated with long-lasting effects on different cognitive, emotional, and motor performances. Specifically, tDCS applied over the motor cortex is considered to improve reaction time in simple and complex tasks. The timing of tDCS relative to task performance could determine the efficacy of tDCS to modulate performance. The aim of this study was to compare the effects of a single session of anodal tDCS (1.5 mA, for 15 min) applied over the left primary motor cortex (M1) versus sham stimulation on performance of a go/no-go simple reaction-time task carried out at three different time points after tDCS-namely, 0, 30, or 60 min after stimulation. Performance zero min after anodal tDCS was improved during the whole course of the task. Performance 30 min after anodal tDCS was improved only in the last block of the reaction-time task. Performance 60 min after anodal tDCS was not significantly different throughout the entire task. These findings suggest that the motor cortex excitability changes induced by tDCS can improve motor responses, and these effects critically depend on the time interval between stimulation and task performance.

Task-Dependent Intermuscular Motor Unit Synchronization between Medial and Lateral Vastii Muscles during Dynamic and Isometric Squats.

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Mohr, Maurice; Nann, Marius; von Tscharner, Vinzenz; Eskofier, Bjoern; Nigg, Benno Maurus

2015-01-01

Motor unit activity is coordinated between many synergistic muscle pairs but the functional role of this coordination for the motor output is unclear. The purpose of this study was to investigate the short-term modality of coordinated motor unit activity-the synchronized discharge of individual motor units across muscles within time intervals of 5ms-for the Vastus Medialis (VM) and Lateralis (VL). Furthermore, we studied the task-dependency of intermuscular motor unit synchronization between VM and VL during static and dynamic squatting tasks to provide insight into its functional role. Sixteen healthy male and female participants completed four tasks: Bipedal squats, single-leg squats, an isometric squat, and single-leg balance. Monopolar surface electromyography (EMG) was used to record motor unit activity of VM and VL. For each task, intermuscular motor unit synchronization was determined using a coherence analysis between the raw EMG signals of VM and VL and compared to a reference coherence calculated from two desynchronized EMG signals. The time shift between VM and VL EMG signals was estimated according to the slope of the coherence phase angle spectrum. For all tasks, except for singe-leg balance, coherence between 15-80Hz significantly exceeded the reference. The corresponding time shift between VM and VL was estimated as 4ms. Coherence between 30-60Hz was highest for the bipedal squat, followed by the single-leg squat and the isometric squat. There is substantial short-term motor unit synchronization between VM and VL. Intermuscular motor unit synchronization is enhanced for contractions during dynamic activities, possibly to facilitate a more accurate control of the joint torque, and reduced during single-leg tasks that require balance control and thus, a more independent muscle function. It is proposed that the central nervous system scales the degree of intermuscular motor unit synchronization according to the requirements of the movement task at hand.

Relationship between reaction time, fine motor control, and visual-spatial perception on vigilance and visual-motor tasks in 22q11.2 Deletion Syndrome.

LENUS (Irish Health Repository)

Howley, Sarah A

2012-10-15

22q11.2 Deletion Syndrome (22q11DS) is a common microdeletion disorder associated with mild to moderate intellectual disability and specific neurocognitive deficits, particularly in visual-motor and attentional abilities. Currently there is evidence that the visual-motor profile of 22q11DS is not entirely mediated by intellectual disability and that these individuals have specific deficits in visual-motor integration. However, the extent to which attentional deficits, such as vigilance, influence impairments on visual motor tasks in 22q11DS is unclear. This study examines visual-motor abilities and reaction time using a range of standardised tests in 35 children with 22q11DS, 26 age-matched typically developing (TD) sibling controls and 17 low-IQ community controls. Statistically significant deficits were observed in the 22q11DS group compared to both low-IQ and TD control groups on a timed fine motor control and accuracy task. The 22q11DS group performed significantly better than the low-IQ control group on an untimed drawing task and were equivalent to the TD control group on point accuracy and simple reaction time tests. Results suggest that visual motor deficits in 22q11DS are primarily attributable to deficits in psychomotor speed which becomes apparent when tasks are timed versus untimed. Moreover, the integration of visual and motor information may be intact and, indeed, represent a relative strength in 22q11DS when there are no time constraints imposed. While this may have significant implications for cognitive remediation strategies for children with 22q11DS, the relationship between reaction time, visual reasoning, cognitive complexity, fine motor speed and accuracy, and graphomotor ability on visual-motor tasks is still unclear.

Individual differences in implicit motor learning: task specificity in sensorimotor adaptation and sequence learning.

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Stark-Inbar, Alit; Raza, Meher; Taylor, Jordan A; Ivry, Richard B

2017-01-01

In standard taxonomies, motor skills are typically treated as representative of implicit or procedural memory. We examined two emblematic tasks of implicit motor learning, sensorimotor adaptation and sequence learning, asking whether individual differences in learning are correlated between these tasks, as well as how individual differences within each task are related to different performance variables. As a prerequisite, it was essential to establish the reliability of learning measures for each task. Participants were tested twice on a visuomotor adaptation task and on a sequence learning task, either the serial reaction time task or the alternating reaction time task. Learning was evident in all tasks at the group level and reliable at the individual level in visuomotor adaptation and the alternating reaction time task but not in the serial reaction time task. Performance variability was predictive of learning in both domains, yet the relationship was in the opposite direction for adaptation and sequence learning. For the former, faster learning was associated with lower variability, consistent with models of sensorimotor adaptation in which learning rates are sensitive to noise. For the latter, greater learning was associated with higher variability and slower reaction times, factors that may facilitate the spread of activation required to form predictive, sequential associations. Interestingly, learning measures of the different tasks were not correlated. Together, these results oppose a shared process for implicit learning in sensorimotor adaptation and sequence learning and provide insight into the factors that account for individual differences in learning within each task domain. We investigated individual differences in the ability to implicitly learn motor skills. As a prerequisite, we assessed whether individual differences were reliable across test sessions. We found that two commonly used tasks of implicit learning, visuomotor adaptation and the

Alpha band functional connectivity correlates with the performance of brain-machine interfaces to decode real and imagined movements

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Hisato eSugata

2014-08-01

Full Text Available Brain signals recorded from the primary motor cortex (M1 are known to serve a significant role in coding the information brain-machine interfaces (BMIs need to perform real and imagined movements, and also to form several functional networks with motor association areas. However, whether functional networks between M1 and other brain regions, such as these motor association areas, are related to performance of BMIs is unclear. To examine the relationship between functional connectivity and performance of BMIs, we analyzed the correlation coefficient between performance of neural decoding and functional connectivity over the whole brain using magnetoencephalography. Ten healthy participants were instructed to execute or imagine three simple right upper limb movements. To decode the movement type, we extracted 40 virtual channels in the left M1 via the beamforming approach, and used them as a decoding feature. In addition, seed-based functional connectivities of activities in the alpha band during real and imagined movements were calculated using imaginary coherence. Seed voxels were set as the same virtual channels in M1. After calculating the imaginary coherence in individuals, the correlation coefficient between decoding accuracy and strength of imaginary coherence was calculated over the whole brain. The significant correlations were distributed mainly to motor association areas for both real and imagined movements. These regions largely overlapped with brain regions that had significant connectivity to M1. Our results suggest that use of the strength of functional connectivity between M1 and motor association areas has the potential to improve the performance of BMIs to perform real and imagined movements.

Low Power LDPC Code Decoder Architecture Based on Intermediate Message Compression Technique

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Shimizu, Kazunori; Togawa, Nozomu; Ikenaga, Takeshi; Goto, Satoshi

Reducing the power dissipation for LDPC code decoder is a major challenging task to apply it to the practical digital communication systems. In this paper, we propose a low power LDPC code decoder architecture based on an intermediate message-compression technique which features as follows: (i) An intermediate message compression technique enables the decoder to reduce the required memory capacity and write power dissipation. (ii) A clock gated shift register based intermediate message memory architecture enables the decoder to decompress the compressed messages in a single clock cycle while reducing the read power dissipation. The combination of the above two techniques enables the decoder to reduce the power dissipation while keeping the decoding throughput. The simulation results show that the proposed architecture improves the power efficiency up to 52% and 18% compared to that of the decoder based on the overlapped schedule and the rapid convergence schedule without the proposed techniques respectively.

Effects of Gait and Cognitive Task Difficulty on Cognitive-Motor Interference in Aging

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Prudence Plummer-D'Amato

2012-01-01

Full Text Available Although gait-related dual-task interference in aging is well established, the effect of gait and cognitive task difficulty on dual-task interference is poorly understood. The purpose of this study was to examine the effect of gait and cognitive task difficulty on cognitive-motor interference in aging. Fifteen older adults (72.1 years, SD 5.2 and 20 young adults (21.7 years, SD 1.6 performed three walking tasks of varying difficulty (self-selected speed, fast speed, and fast speed with obstacle crossing under single- and dual-task conditions. The cognitive tasks were the auditory Stroop task and the clock task. There was a significant Group × Gait Task × Cognitive Task interaction for the dual-task effect on gait speed. After adjusting for education, there were no significant effects of gait or cognitive task difficulty on the dual-task effects on cognitive task performance. The results of this study provide evidence that gait task difficulty influences dual-task effects on gait speed, especially in older adults. Moreover, the effects of gait task difficulty on dual-task interference appear to be influenced by the difficulty of the cognitive task. Education is an important factor influencing cognitive-motor interference effects on cognition, but not gait.

Is Rest Really Rest? Resting State Functional Connectivity during Rest and Motor Task Paradigms.

Science.gov (United States)

Jurkiewicz, Michael T; Crawley, Adrian P; Mikulis, David J

2018-04-18

Numerous studies have identified the default mode network (DMN) within the brain of healthy individuals, which has been attributed to the ongoing mental activity of the brain during the wakeful resting-state. While engaged during specific resting-state fMRI paradigms, it remains unclear as to whether traditional block-design simple movement fMRI experiments significantly influence the default mode network or other areas. Using blood-oxygen level dependent (BOLD) fMRI we characterized the pattern of functional connectivity in healthy subjects during a resting-state paradigm and compared this to the same resting-state analysis performed on motor task data residual time courses after regressing out the task paradigm. Using seed-voxel analysis to define the DMN, the executive control network (ECN), and sensorimotor, auditory and visual networks, the resting-state analysis of the residual time courses demonstrated reduced functional connectivity in the motor network and reduced connectivity between the insula and the ECN compared to the standard resting-state datasets. Overall, performance of simple self-directed motor tasks does little to change the resting-state functional connectivity across the brain, especially in non-motor areas. This would suggest that previously acquired fMRI studies incorporating simple block-design motor tasks could be mined retrospectively for assessment of the resting-state connectivity.

Task-induced frequency modulation features for brain-computer interfacing.

Science.gov (United States)

Jayaram, Vinay; Hohmann, Matthias; Just, Jennifer; Schölkopf, Bernhard; Grosse-Wentrup, Moritz

2017-10-01

Task-induced amplitude modulation of neural oscillations is routinely used in brain-computer interfaces (BCIs) for decoding subjects' intents, and underlies some of the most robust and common methods in the field, such as common spatial patterns and Riemannian geometry. While there has been some interest in phase-related features for classification, both techniques usually presuppose that the frequencies of neural oscillations remain stable across various tasks. We investigate here whether features based on task-induced modulation of the frequency of neural oscillations enable decoding of subjects' intents with an accuracy comparable to task-induced amplitude modulation. We compare cross-validated classification accuracies using the amplitude and frequency modulated features, as well as a joint feature space, across subjects in various paradigms and pre-processing conditions. We show results with a motor imagery task, a cognitive task, and also preliminary results in patients with amyotrophic lateral sclerosis (ALS), as well as using common spatial patterns and Laplacian filtering. The frequency features alone do not significantly out-perform traditional amplitude modulation features, and in some cases perform significantly worse. However, across both tasks and pre-processing in healthy subjects the joint space significantly out-performs either the frequency or amplitude features alone. This result only does not hold for ALS patients, for whom the dataset is of insufficient size to draw any statistically significant conclusions. Task-induced frequency modulation is robust and straight forward to compute, and increases performance when added to standard amplitude modulation features across paradigms. This allows more information to be extracted from the EEG signal cheaply and can be used throughout the field of BCIs.

Task-induced frequency modulation features for brain-computer interfacing

Science.gov (United States)

Jayaram, Vinay; Hohmann, Matthias; Just, Jennifer; Schölkopf, Bernhard; Grosse-Wentrup, Moritz

2017-10-01

Objective. Task-induced amplitude modulation of neural oscillations is routinely used in brain-computer interfaces (BCIs) for decoding subjects’ intents, and underlies some of the most robust and common methods in the field, such as common spatial patterns and Riemannian geometry. While there has been some interest in phase-related features for classification, both techniques usually presuppose that the frequencies of neural oscillations remain stable across various tasks. We investigate here whether features based on task-induced modulation of the frequency of neural oscillations enable decoding of subjects’ intents with an accuracy comparable to task-induced amplitude modulation. Approach. We compare cross-validated classification accuracies using the amplitude and frequency modulated features, as well as a joint feature space, across subjects in various paradigms and pre-processing conditions. We show results with a motor imagery task, a cognitive task, and also preliminary results in patients with amyotrophic lateral sclerosis (ALS), as well as using common spatial patterns and Laplacian filtering. Main results. The frequency features alone do not significantly out-perform traditional amplitude modulation features, and in some cases perform significantly worse. However, across both tasks and pre-processing in healthy subjects the joint space significantly out-performs either the frequency or amplitude features alone. This result only does not hold for ALS patients, for whom the dataset is of insufficient size to draw any statistically significant conclusions. Significance. Task-induced frequency modulation is robust and straight forward to compute, and increases performance when added to standard amplitude modulation features across paradigms. This allows more information to be extracted from the EEG signal cheaply and can be used throughout the field of BCIs.

Directionality analysis on functional magnetic resonance imaging during motor task using Granger causality.

Science.gov (United States)

Anwar, A R; Muthalib, M; Perrey, S; Galka, A; Granert, O; Wolff, S; Deuschl, G; Raethjen, J; Heute, U; Muthuraman, M

2012-01-01

Directionality analysis of signals originating from different parts of brain during motor tasks has gained a lot of interest. Since brain activity can be recorded over time, methods of time series analysis can be applied to medical time series as well. Granger Causality is a method to find a causal relationship between time series. Such causality can be referred to as a directional connection and is not necessarily bidirectional. The aim of this study is to differentiate between different motor tasks on the basis of activation maps and also to understand the nature of connections present between different parts of the brain. In this paper, three different motor tasks (finger tapping, simple finger sequencing, and complex finger sequencing) are analyzed. Time series for each task were extracted from functional magnetic resonance imaging (fMRI) data, which have a very good spatial resolution and can look into the sub-cortical regions of the brain. Activation maps based on fMRI images show that, in case of complex finger sequencing, most parts of the brain are active, unlike finger tapping during which only limited regions show activity. Directionality analysis on time series extracted from contralateral motor cortex (CMC), supplementary motor area (SMA), and cerebellum (CER) show bidirectional connections between these parts of the brain. In case of simple finger sequencing and complex finger sequencing, the strongest connections originate from SMA and CMC, while connections originating from CER in either direction are the weakest ones in magnitude during all paradigms.

Closing the sensorimotor loop: haptic feedback facilitates decoding of motor imagery

Science.gov (United States)

Gomez-Rodriguez, M.; Peters, J.; Hill, J.; Schölkopf, B.; Gharabaghi, A.; Grosse-Wentrup, M.

2011-06-01

The combination of brain-computer interfaces (BCIs) with robot-assisted physical therapy constitutes a promising approach to neurorehabilitation of patients with severe hemiparetic syndromes caused by cerebrovascular brain damage (e.g. stroke) and other neurological conditions. In such a scenario, a key aspect is how to reestablish the disrupted sensorimotor feedback loop. However, to date it is an open question how artificially closing the sensorimotor feedback loop influences the decoding performance of a BCI. In this paper, we answer this issue by studying six healthy subjects and two stroke patients. We present empirical evidence that haptic feedback, provided by a seven degrees of freedom robotic arm, facilitates online decoding of arm movement intention. The results support the feasibility of future rehabilitative treatments based on the combination of robot-assisted physical therapy with BCIs.

Patterned-string tasks: relation between fine motor skills and visual-spatial abilities in parrots.

Directory of Open Access Journals (Sweden)

Anastasia Krasheninnikova

Full Text Available String-pulling and patterned-string tasks are often used to analyse perceptual and cognitive abilities in animals. In addition, the paradigm can be used to test the interrelation between visual-spatial and motor performance. Two Australian parrot species, the galah (Eolophus roseicapilla and the cockatiel (Nymphicus hollandicus, forage on the ground, but only the galah uses its feet to manipulate food. I used a set of string pulling and patterned-string tasks to test whether usage of the feet during foraging is a prerequisite for solving the vertical string pulling problem. Indeed, the two species used techniques that clearly differed in the extent of beak-foot coordination but did not differ in terms of their success in solving the string pulling task. However, when the visual-spatial skills of the subjects were tested, the galahs outperformed the cockatiels. This supports the hypothesis that the fine motor skills needed for advanced beak-foot coordination may be interrelated with certain visual-spatial abilities needed for solving patterned-string tasks. This pattern was also found within each of the two species on the individual level: higher motor abilities positively correlated with performance in patterned-string tasks. This is the first evidence of an interrelation between visual-spatial and motor abilities in non-mammalian animals.

Neuroprosthetic Decoder Training as Imitation Learning.

Science.gov (United States)

Merel, Josh; Carlson, David; Paninski, Liam; Cunningham, John P

2016-05-01

Neuroprosthetic brain-computer interfaces function via an algorithm which decodes neural activity of the user into movements of an end effector, such as a cursor or robotic arm. In practice, the decoder is often learned by updating its parameters while the user performs a task. When the user's intention is not directly observable, recent methods have demonstrated value in training the decoder against a surrogate for the user's intended movement. Here we show that training a decoder in this way is a novel variant of an imitation learning problem, where an oracle or expert is employed for supervised training in lieu of direct observations, which are not available. Specifically, we describe how a generic imitation learning meta-algorithm, dataset aggregation (DAgger), can be adapted to train a generic brain-computer interface. By deriving existing learning algorithms for brain-computer interfaces in this framework, we provide a novel analysis of regret (an important metric of learning efficacy) for brain-computer interfaces. This analysis allows us to characterize the space of algorithmic variants and bounds on their regret rates. Existing approaches for decoder learning have been performed in the cursor control setting, but the available design principles for these decoders are such that it has been impossible to scale them to naturalistic settings. Leveraging our findings, we then offer an algorithm that combines imitation learning with optimal control, which should allow for training of arbitrary effectors for which optimal control can generate goal-oriented control. We demonstrate this novel and general BCI algorithm with simulated neuroprosthetic control of a 26 degree-of-freedom model of an arm, a sophisticated and realistic end effector.

Neuroprosthetic Decoder Training as Imitation Learning.

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Josh Merel

2016-05-01

Full Text Available Neuroprosthetic brain-computer interfaces function via an algorithm which decodes neural activity of the user into movements of an end effector, such as a cursor or robotic arm. In practice, the decoder is often learned by updating its parameters while the user performs a task. When the user's intention is not directly observable, recent methods have demonstrated value in training the decoder against a surrogate for the user's intended movement. Here we show that training a decoder in this way is a novel variant of an imitation learning problem, where an oracle or expert is employed for supervised training in lieu of direct observations, which are not available. Specifically, we describe how a generic imitation learning meta-algorithm, dataset aggregation (DAgger, can be adapted to train a generic brain-computer interface. By deriving existing learning algorithms for brain-computer interfaces in this framework, we provide a novel analysis of regret (an important metric of learning efficacy for brain-computer interfaces. This analysis allows us to characterize the space of algorithmic variants and bounds on their regret rates. Existing approaches for decoder learning have been performed in the cursor control setting, but the available design principles for these decoders are such that it has been impossible to scale them to naturalistic settings. Leveraging our findings, we then offer an algorithm that combines imitation learning with optimal control, which should allow for training of arbitrary effectors for which optimal control can generate goal-oriented control. We demonstrate this novel and general BCI algorithm with simulated neuroprosthetic control of a 26 degree-of-freedom model of an arm, a sophisticated and realistic end effector.

Not all choices are created equal: Task-relevant choices enhance motor learning compared to task-irrelevant choices.

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Carter, Michael J; Ste-Marie, Diane M

2017-12-01

Lewthwaite et al. (2015) reported that the learning benefits of exercising choice (i.e., their self-controlled condition) are not restricted to task-relevant features (e.g., feedback). They found that choosing one's golf ball color (Exp. 1) or choosing which of two tasks to perform at a later time plus which of two artworks to hang (Exp. 2) resulted in better retention than did being denied these same choices (i.e., yoked condition). The researchers concluded that the learning benefits derived from choice, whether irrelevant or relevant to the to-be-learned task, are predominantly motivational because choice is intrinsically rewarding and satisfies basic psychological needs. However, the absence of a group that made task-relevant choices and the lack of psychological measures significantly weakened their conclusions. Here, we investigated how task-relevant and task-irrelevant choices affect motor-skill learning. Participants practiced a spatiotemporal motor task in either a task-relevant group (choice over feedback schedule), a task-irrelevant group (choice over the color of an arm-wrap plus game selection), or a no-choice group. The results showed significantly greater learning in the task-relevant group than in both the task-irrelevant and no-choice groups, who did not differ significantly. Critically, these learning differences were not attributed to differences in perceptions of competence or autonomy, but instead to superior error-estimation abilities. These results challenge the perspective that motivational influences are the root cause of self-controlled learning advantages. Instead, the findings add to the growing evidence highlighting that the informational value gained from task-relevant choices makes a greater relative contribution to these advantages than motivational influences do.

Neuron selection based on deflection coefficient maximization for the neural decoding of dexterous finger movements.

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Kim, Yong-Hee; Thakor, Nitish V; Schieber, Marc H; Kim, Hyoung-Nam

2015-05-01

Future generations of brain-machine interface (BMI) will require more dexterous motion control such as hand and finger movements. Since a population of neurons in the primary motor cortex (M1) area is correlated with finger movements, neural activities recorded in M1 area are used to reconstruct an intended finger movement. In a BMI system, decoding discrete finger movements from a large number of input neurons does not guarantee a higher decoding accuracy in spite of the increase in computational burden. Hence, we hypothesize that selecting neurons important for coding dexterous flexion/extension of finger movements would improve the BMI performance. In this paper, two metrics are presented to quantitatively measure the importance of each neuron based on Bayes risk minimization and deflection coefficient maximization in a statistical decision problem. Since motor cortical neurons are active with movements of several different fingers, the proposed method is more suitable for a discrete decoding of flexion-extension finger movements than the previous methods for decoding reaching movements. In particular, the proposed metrics yielded high decoding accuracies across all subjects and also in the case of including six combined two-finger movements. While our data acquisition and analysis was done off-line and post processing, our results point to the significance of highly coding neurons in improving BMI performance.

Real-time changes in corticospinal excitability related to motor imagery of a force control task

DEFF Research Database (Denmark)

Tatemoto, Tsuyoshi; Tsuchiya, Junko; Numata, Atsuki

2017-01-01

Objective To investigate real-time excitability changes in corticospinal pathways related to motor imagery in a changing force control task, using transcranial magnetic stimulation (TMS). Methods Ten healthy volunteers learnt to control the contractile force of isometric right wrist dorsiflexion...... in order to track an on-screen sine wave form. Participants performed the trained task 40 times with actual muscle contraction in order to construct the motor image. They were then instructed to execute the task without actual muscle contraction, but by imagining contraction of the right wrist...... in dorsiflexion. Motor evoked potentials (MEPs), induced by TMS in the right extensor carpi radialis muscle (ECR) and flexor carpi radialis muscle (FCR), were measured during motor imagery. MEPs were induced at five time points: prior to imagery, during the gradual generation of the imaged wrist dorsiflexion...

Task-Dependent Intermuscular Motor Unit Synchronization between Medial and Lateral Vastii Muscles during Dynamic and Isometric Squats.

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Maurice Mohr

Full Text Available Motor unit activity is coordinated between many synergistic muscle pairs but the functional role of this coordination for the motor output is unclear. The purpose of this study was to investigate the short-term modality of coordinated motor unit activity-the synchronized discharge of individual motor units across muscles within time intervals of 5ms-for the Vastus Medialis (VM and Lateralis (VL. Furthermore, we studied the task-dependency of intermuscular motor unit synchronization between VM and VL during static and dynamic squatting tasks to provide insight into its functional role.Sixteen healthy male and female participants completed four tasks: Bipedal squats, single-leg squats, an isometric squat, and single-leg balance. Monopolar surface electromyography (EMG was used to record motor unit activity of VM and VL. For each task, intermuscular motor unit synchronization was determined using a coherence analysis between the raw EMG signals of VM and VL and compared to a reference coherence calculated from two desynchronized EMG signals. The time shift between VM and VL EMG signals was estimated according to the slope of the coherence phase angle spectrum.For all tasks, except for singe-leg balance, coherence between 15-80Hz significantly exceeded the reference. The corresponding time shift between VM and VL was estimated as 4ms. Coherence between 30-60Hz was highest for the bipedal squat, followed by the single-leg squat and the isometric squat.There is substantial short-term motor unit synchronization between VM and VL. Intermuscular motor unit synchronization is enhanced for contractions during dynamic activities, possibly to facilitate a more accurate control of the joint torque, and reduced during single-leg tasks that require balance control and thus, a more independent muscle function. It is proposed that the central nervous system scales the degree of intermuscular motor unit synchronization according to the requirements of the movement

Time of Day Does Not Modulate Improvements in Motor Performance following a Repetitive Ballistic Motor Training Task

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Sale, Martin V.; Ridding, Michael C.; Nordstrom, Michael A.

2013-01-01

Repetitive performance of a task can result in learning. The neural mechanisms underpinning such use-dependent plasticity are influenced by several neuromodulators. Variations in neuromodulator levels may contribute to the variability in performance outcomes following training. Circulating levels of the neuromodulator cortisol change throughout the day. High cortisol levels inhibit neuroplasticity induced with a transcranial magnetic stimulation (TMS) paradigm that has similarities to use-dependent plasticity. The present study investigated whether performance changes following a motor training task are modulated by time of day and/or changes in endogenous cortisol levels. Motor training involving 30 minutes of repeated maximum left thumb abduction was undertaken by twenty-two participants twice, once in the morning (8 AM) and once in the evening (8 PM) on separate occasions. Saliva was assayed for cortisol concentration. Motor performance, quantified by measuring maximum left thumb abduction acceleration, significantly increased by 28% following training. Neuroplastic changes in corticomotor excitability of abductor pollicis brevis, quantified with TMS, increased significantly by 23% following training. Training-related motor performance improvements and neuroplasticity were unaffected by time of day and salivary cortisol concentration. Although similar neural elements and processes contribute to motor learning, training-induced neuroplasticity, and TMS-induced neuroplasticity, our findings suggest that the influence of time of day and cortisol differs for these three interventions. PMID:23577271

Time of Day Does Not Modulate Improvements in Motor Performance following a Repetitive Ballistic Motor Training Task

Directory of Open Access Journals (Sweden)

Martin V. Sale

2013-01-01

Full Text Available Repetitive performance of a task can result in learning. The neural mechanisms underpinning such use-dependent plasticity are influenced by several neuromodulators. Variations in neuromodulator levels may contribute to the variability in performance outcomes following training. Circulating levels of the neuromodulator cortisol change throughout the day. High cortisol levels inhibit neuroplasticity induced with a transcranial magnetic stimulation (TMS paradigm that has similarities to use-dependent plasticity. The present study investigated whether performance changes following a motor training task are modulated by time of day and/or changes in endogenous cortisol levels. Motor training involving 30 minutes of repeated maximum left thumb abduction was undertaken by twenty-two participants twice, once in the morning (8 AM and once in the evening (8 PM on separate occasions. Saliva was assayed for cortisol concentration. Motor performance, quantified by measuring maximum left thumb abduction acceleration, significantly increased by 28% following training. Neuroplastic changes in corticomotor excitability of abductor pollicis brevis, quantified with TMS, increased significantly by 23% following training. Training-related motor performance improvements and neuroplasticity were unaffected by time of day and salivary cortisol concentration. Although similar neural elements and processes contribute to motor learning, training-induced neuroplasticity, and TMS-induced neuroplasticity, our findings suggest that the influence of time of day and cortisol differs for these three interventions.

Second-order motor planning in children: insights from a cup-manipulation-task.

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Wunsch, Kathrin; Weiss, Daniel J; Schack, Thomas; Weigelt, Matthias

2015-07-01

The present study examined the development of anticipatory motor planning in an object manipulation task that has been used to successfully demonstrate motor planning in non-human primates (Weiss et al. in Psychol Sci 18:1063-1068, 2007). Seventy-five participants from four different age groups participated in a cup-manipulation task. One group was preschool children (average age of 5.1 years), two groups were primary school children (7.7 and 9.8 years old respectively) and the final group was comprised of adults. The experimental task entailed reaching for a plastic cup that was vertically suspended in an apparatus in either upright or inverted orientation, removing the cup by its stem and then retrieving a small toy from the inside of the cup. When the cup was inverted in the apparatus, evidence for anticipatory motor planning could be achieved by initially gripping the stem using an inverted (thumb-down) grip posture. We found that when the cup was in upright orientation, all participants reached for the cup using an upright grip (i.e., thumb-up posture). However, when the cup was inverted in the apparatus, only adults consistently used an inverted grasping posture, though the percentage of inverted grips among participants did increase with age. These results suggest a protracted development for anticipatory motor planning abilities in children. Surprisingly, the performance of adults on this task more closely resembles the performance of several nonhuman primate species as opposed to children even at approximately 10 years of age. We discuss how morphological constraints on flexibility may help account for these findings.

Emergence of motor synergy in vertical reaching task via tacit learning.

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Hayashibe, Mitsuhiro; Shimoda, Shingo

2013-01-01

The dynamics of multijoint limbs often causes complex dynamic interaction torques which are the inertial effect of other joints motion. It is known that Cerebellum takes important role in a motor learning by developing the internal model. In this paper, we propose a novel computational control paradigm in vertical reaching task which involves the management of interaction torques and gravitational effect. The obtained results demonstrate that the proposed method is valid for acquiring motor synergy in the system with actuation redundancy and resulted in the energy efficient solutions. It is highlighted that the tacit learning in vertical reaching task can bring computational adaptability and optimality with model-free and cost-function-free approach differently from previous studies.

Distributed coding/decoding complexity in video sensor networks.

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Cordeiro, Paulo J; Assunção, Pedro

2012-01-01

Video Sensor Networks (VSNs) are recent communication infrastructures used to capture and transmit dense visual information from an application context. In such large scale environments which include video coding, transmission and display/storage, there are several open problems to overcome in practical implementations. This paper addresses the most relevant challenges posed by VSNs, namely stringent bandwidth usage and processing time/power constraints. In particular, the paper proposes a novel VSN architecture where large sets of visual sensors with embedded processors are used for compression and transmission of coded streams to gateways, which in turn transrate the incoming streams and adapt them to the variable complexity requirements of both the sensor encoders and end-user decoder terminals. Such gateways provide real-time transcoding functionalities for bandwidth adaptation and coding/decoding complexity distribution by transferring the most complex video encoding/decoding tasks to the transcoding gateway at the expense of a limited increase in bit rate. Then, a method to reduce the decoding complexity, suitable for system-on-chip implementation, is proposed to operate at the transcoding gateway whenever decoders with constrained resources are targeted. The results show that the proposed method achieves good performance and its inclusion into the VSN infrastructure provides an additional level of complexity control functionality.

Efficient decoding with steady-state Kalman filter in neural interface systems.

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Malik, Wasim Q; Truccolo, Wilson; Brown, Emery N; Hochberg, Leigh R

2011-02-01

The Kalman filter is commonly used in neural interface systems to decode neural activity and estimate the desired movement kinematics. We analyze a low-complexity Kalman filter implementation in which the filter gain is approximated by its steady-state form, computed offline before real-time decoding commences. We evaluate its performance using human motor cortical spike train data obtained from an intracortical recording array as part of an ongoing pilot clinical trial. We demonstrate that the standard Kalman filter gain converges to within 95% of the steady-state filter gain in 1.5±0.5 s (mean ±s.d.). The difference in the intended movement velocity decoded by the two filters vanishes within 5 s, with a correlation coefficient of 0.99 between the two decoded velocities over the session length. We also find that the steady-state Kalman filter reduces the computational load (algorithm execution time) for decoding the firing rates of 25±3 single units by a factor of 7.0±0.9. We expect that the gain in computational efficiency will be much higher in systems with larger neural ensembles. The steady-state filter can thus provide substantial runtime efficiency at little cost in terms of estimation accuracy. This far more efficient neural decoding approach will facilitate the practical implementation of future large-dimensional, multisignal neural interface systems.

Video encoder/decoder for encoding/decoding motion compensated images

NARCIS (Netherlands)

1996-01-01

Video encoder and decoder, provided with a motion compensator for motion-compensated video coding or decoding in which a picture is coded or decoded in blocks in alternately horizontal and vertical steps. The motion compensator is provided with addressing means (160) and controlled multiplexers

Effect of cognitive and motor tasks on postural stability in Parkinson's disease: a posturographic study.

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Marchese, Roberta; Bove, Marco; Abbruzzese, Giovanni

2003-06-01

To analyse the effect of concomitant cognitive or motor task performance on balance control in Parkinson's disease (PD), we performed a posturographic study in 24 PD patients and in 20 sex- and age-matched control subjects. Postural sway was measured with eyes open (EO) and eyes closed (EC) during quiet stance and during performance of calculation or motor sequence of thumb opposition to the other fingers. No difference of centre of foot pressure (COP) parameters was observed during quiet standing (either EO or EC) between patients and controls, but visual deprivation induced in both groups a worsening of postural stability. COP area was significantly increased in PD patients during dual task performance, whereas no difference of COP path and x-y axes was observed. The effects induced by the performance of cognitive or motor task were significantly more evident in PD patients with clinical evidence of postural instability (presence of prior falls in the history). This study demonstrates that dual task interference on postural control can be observed in PD patients during performance of cognitive as well as motor tasks. The balance deterioration during dual task performance was significantly enhanced in patients with history of prior falls. These findings have some implications for the strategies to be used in reducing the risk of fall in PD. Copyright 2003 Movement Disorder Society

Core stability exercise is as effective as task-oriented motor training in improving motor proficiency in children with developmental coordination disorder: a randomized controlled pilot study.

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Au, Mei K; Chan, Wai M; Lee, Lin; Chen, Tracy Mk; Chau, Rosanna Mw; Pang, Marco Yc

2014-10-01

To compare the effectiveness of a core stability program with a task-oriented motor training program in improving motor proficiency in children with developmental coordination disorder (DCD). Randomized controlled pilot trial. Outpatient unit in a hospital. Twenty-two children diagnosed with DCD aged 6-9 years were randomly allocated to the core stability program or the task-oriented motor program. Both groups underwent their respective face-to-face training session once per week for eight consecutive weeks. They were also instructed to carry out home exercises on a daily basis during the intervention period. Short Form of the Bruininks-Oseretsky Test of Motor Proficiency (Second Edition) and Sensory Organization Test at pre- and post-intervention. Intention-to-treat analysis revealed no significant between-group difference in the change of motor proficiency standard score (P=0.717), and composite equilibrium score derived from the Sensory Organization Test (P=0.100). Further analysis showed significant improvement in motor proficiency in both the core stability (mean change (SD)=6.3(5.4); p=0.008) and task-oriented training groups (mean change(SD)=5.1(4.0); P=0.007). The composite equilibrium score was significantly increased in the task-oriented training group (mean change (SD)=6.0(5.5); P=0.009), but not in the core stability group (mean change(SD) =0.0(9.6); P=0.812). In the task-oriented training group, compliance with the home program was positively correlated with change in motor proficiency (ρ=0.680, P=0.030) and composite equilibrium score (ρ=0.638, P=0.047). The core stability exercise program is as effective as task-oriented training in improving motor proficiency among children with DCD. © The Author(s) 2014.

Discordant tasks and motor adjustments affect interactions between adaptations to altered kinematics and dynamics

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Fritzie Arce

2010-01-01

Full Text Available Motor control and adaptation are multi-determinate processes with complex interactions. This is reflected for example in the ambiguous nature of interactions during sequential adaptation of reaching under kinematics and dynamics perturbations. It has been suggested that perturbations based on the same kinematic parameter interfere. Others posited that opposing motor adjustments underlie interference. Here, we examined the influence of discordances in task and in motor adjustments on sequential adaptations to visuomotor rotation and viscous force field perturbations. These two factors – perturbation direction and task discordance – have been examined separately by previous studies, thus the inherent difficulty to identify the roots of interference. Forty-eight human subjects adapted sequentially to one or two types of perturbations, of matched or conflicting directions. We found a gradient of interaction effects based on perturbation direction and task discordance. Perturbations of matched directions showed facilitation while perturbations of opposite directions, which required opposing motor adjustments, interfered with each other. Further, interaction effects increased with greater task discordance. We also found that force field and visuomotor rotation had mutual anterograde and retrograde effects. However, we found independence between anterograde and retrograde interferences between similar tasks. The results suggest that the newly acquired internal models of kinematic and dynamic perturbations are not independent but they share common neuronal resources and interact between them. Such overlap does not necessarily imply competition of resources. Rather, our results point to an additional principle of sensorimotor adaptation allowing the system to tap or harness common features across diverse sensory inputs and task contexts whenever available.

Task context impacts visual object processing differentially across the cortex

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Harel, Assaf; Kravitz, Dwight J.; Baker, Chris I.

2014-01-01

Perception reflects an integration of “bottom-up” (sensory-driven) and “top-down” (internally generated) signals. Although models of visual processing often emphasize the central role of feed-forward hierarchical processing, less is known about the impact of top-down signals on complex visual representations. Here, we investigated whether and how the observer’s goals modulate object processing across the cortex. We examined responses elicited by a diverse set of objects under six distinct tasks, focusing on either physical (e.g., color) or conceptual properties (e.g., man-made). Critically, the same stimuli were presented in all tasks, allowing us to investigate how task impacts the neural representations of identical visual input. We found that task has an extensive and differential impact on object processing across the cortex. First, we found task-dependent representations in the ventral temporal and prefrontal cortex. In particular, although object identity could be decoded from the multivoxel response within task, there was a significant reduction in decoding across tasks. In contrast, the early visual cortex evidenced equivalent decoding within and across tasks, indicating task-independent representations. Second, task information was pervasive and present from the earliest stages of object processing. However, although the responses of the ventral temporal, prefrontal, and parietal cortex enabled decoding of both the type of task (physical/conceptual) and the specific task (e.g., color), the early visual cortex was not sensitive to type of task and could only be used to decode individual physical tasks. Thus, object processing is highly influenced by the behavioral goal of the observer, highlighting how top-down signals constrain and inform the formation of visual representations. PMID:24567402

Broadband Prosthetic Interfaces: Combining Nerve Transfers and Implantable Multichannel EMG Technology to Decode Spinal Motor Neuron Activity

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Konstantin D. Bergmeister

2017-07-01

Full Text Available Modern robotic hands/upper limbs may replace multiple degrees of freedom of extremity function. However, their intuitive use requires a high number of control signals, which current man-machine interfaces do not provide. Here, we discuss a broadband control interface that combines targeted muscle reinnervation, implantable multichannel electromyographic sensors, and advanced decoding to address the increasing capabilities of modern robotic limbs. With targeted muscle reinnervation, nerves that have lost their targets due to an amputation are surgically transferred to residual stump muscles to increase the number of intuitive prosthetic control signals. This surgery re-establishes a nerve-muscle connection that is used for sensing nerve activity with myoelectric interfaces. Moreover, the nerve transfer determines neurophysiological effects, such as muscular hyper-reinnervation and cortical reafferentation that can be exploited by the myoelectric interface. Modern implantable multichannel EMG sensors provide signals from which it is possible to disentangle the behavior of single motor neurons. Recent studies have shown that the neural drive to muscles can be decoded from these signals and thereby the user's intention can be reliably estimated. By combining these concepts in chronic implants and embedded electronics, we believe that it is in principle possible to establish a broadband man-machine interface, with specific applications in prosthesis control. This perspective illustrates this concept, based on combining advanced surgical techniques with recording hardware and processing algorithms. Here we describe the scientific evidence for this concept, current state of investigations, challenges, and alternative approaches to improve current prosthetic interfaces.

Parental Writing Support and Preschoolers' Early Literacy, Language, and Fine Motor Skills

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Bindman, Samantha W.; Skibbe, Lori E.; Hindman, Annemarie H.; Aram, Dorit; Morrison, Frederick J.

2014-01-01

The current study examines the nature and variability of parents' aid to preschoolers in the context of a shared writing task, as well as the relations between this support and children's literacy, vocabulary, and fine motor skills. In total, 135 preschool children (72 girls) and their parents (primarily mothers) in an ethnically diverse, middle-income community were observed while writing a semi-structured invitation for a pretend birthday party together. Children's phonological awareness, alphabet knowledge, word decoding, vocabulary, and fine motor skills were also assessed. Results revealed that parents provided variable, but generally low–level, support for children's approximation of sound-symbol correspondence in their writing (i.e., graphophonemic support), as well as for their production of letter forms (i.e., print support). Parents frequently accepted errors rather than asking for corrections (i.e., demand for precision). Further analysis of the parent-child dyads (n = 103) who wrote the child's name on the invitation showed that parents provided higher graphophonemic, but not print, support when writing the child's name than other words. Overall parental graphophonemic support was positively linked to children's decoding and fine motor skills, whereas print support and demand for precision were not related to any of the child outcomes. In sum, this study indicates that while parental support for preschoolers' writing may be minimal, it is uniquely linked to key literacy-related outcomes in preschool. PMID:25284957

Decoding human mental states by whole-head EEG+fNIRS during category fluency task performance

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Omurtag, Ahmet; Aghajani, Haleh; Onur Keles, Hasan

2017-12-01

Objective. Concurrent scalp electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), which we refer to as EEG+fNIRS, promises greater accuracy than the individual modalities while remaining nearly as convenient as EEG. We sought to quantify the hybrid system’s ability to decode mental states and compare it with its unimodal components. Approach. We recorded from healthy volunteers taking the category fluency test and applied machine learning techniques to the data. Main results. EEG+fNIRS’s decoding accuracy was greater than that of its subsystems, partly due to the new type of neurovascular features made available by hybrid data. Significance. Availability of an accurate and practical decoding method has potential implications for medical diagnosis, brain-computer interface design, and neuroergonomics.

Adaptation and Retention of a Perceptual-Motor Task in Children: Effects of a Single Bout of Intense Endurance Exercise.

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Ferrer-Uris, Blai; Busquets, Albert; Angulo-Barroso, Rosa

2018-02-01

We assessed the effect of an acute intense exercise bout on the adaptation and consolidation of a visuomotor adaptation task in children. We also sought to assess if exercise and learning task presentation order could affect task consolidation. Thirty-three children were randomly assigned to one of three groups: (a) exercise before the learning task, (b) exercise after the learning task, and (c) only learning task. Baseline performance was assessed by practicing the learning task in a 0° rotation condition. Afterward, a 60° rotation-adaptation set was applied followed by three rotated retention sets after 1 hr, 24 hr, and 7 days. For the exercise groups, exercise was presented before or after the motor adaptation. Results showed no group differences during the motor adaptation while exercise seemed to enhance motor consolidation. Greater consolidation enhancement was found in participants who exercised before the learning task. Our data support the importance of exercise to improve motor-memory consolidation in children.

Mental workload and motor performance dynamics during practice of reaching movements under various levels of task difficulty.

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Shuggi, Isabelle M; Oh, Hyuk; Shewokis, Patricia A; Gentili, Rodolphe J

2017-09-30

The assessment of mental workload can inform attentional resource allocation during task performance that is essential for understanding the underlying principles of human cognitive-motor behavior. While many studies have focused on mental workload in relation to human performance, a modest body of work has examined it in a motor practice/learning context without considering individual variability. Thus, this work aimed to examine mental workload by employing the NASA TLX as well as the changes in motor performance resulting from the practice of a novel reaching task. Two groups of participants practiced a reaching task at a high and low nominal difficulty during which a group-level analysis assessed the mental workload, motor performance and motor improvement dynamics. A secondary cluster analysis was also conducted to identify specific individual patterns of cognitive-motor responses. Overall, both group- and cluster-level analyses revealed that: (i) all participants improved their performance throughout motor practice, and (ii) an increase in mental workload was associated with a reduction of the quality of motor performance along with a slower rate of motor improvement. The results are discussed in the context of the optimal challenge point framework and in particular it is proposed that under the experimental conditions employed here, functional task difficulty: (i) would possibly depend on an individuals' information processing capabilities, and (ii) could be indexed by the level of mental workload which, when excessively heightened can decrease the quality of performance and more generally result in delayed motor improvements. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

Task-Relevant Information Modulates Primary Motor Cortex Activity Before Movement Onset.

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Calderon, Cristian B; Van Opstal, Filip; Peigneux, Philippe; Verguts, Tom; Gevers, Wim

2018-01-01

Monkey neurophysiology research supports the affordance competition hypothesis (ACH) proposing that cognitive information useful for action selection is integrated in sensorimotor areas. In this view, action selection would emerge from the simultaneous representation of competing action plans, in parallel biased by relevant task factors. This biased competition would take place up to primary motor cortex (M1). Although ACH is plausible in environments affording choices between actions, its relevance for human decision making is less clear. To address this issue, we designed an functional magnetic resonance imaging (fMRI) experiment modeled after monkey neurophysiology studies in which human participants processed cues conveying predictive information about upcoming button presses. Our results demonstrate that, as predicted by the ACH, predictive information (i.e., the relevant task factor) biases activity of primary motor regions. Specifically, first, activity before movement onset in contralateral M1 increases as the competition is biased in favor of a specific button press relative to activity in ipsilateral M1. Second, motor regions were more tightly coupled with fronto-parietal regions when competition between potential actions was high, again suggesting that motor regions are also part of the biased competition network. Our findings support the idea that action planning dynamics as proposed in the ACH are valid both in human and non-human primates.

On minimizing the maximum broadcast decoding delay for instantly decodable network coding

KAUST Repository

Douik, Ahmed S.

2014-09-01

In this paper, we consider the problem of minimizing the maximum broadcast decoding delay experienced by all the receivers of generalized instantly decodable network coding (IDNC). Unlike the sum decoding delay, the maximum decoding delay as a definition of delay for IDNC allows a more equitable distribution of the delays between the different receivers and thus a better Quality of Service (QoS). In order to solve this problem, we first derive the expressions for the probability distributions of maximum decoding delay increments. Given these expressions, we formulate the problem as a maximum weight clique problem in the IDNC graph. Although this problem is known to be NP-hard, we design a greedy algorithm to perform effective packet selection. Through extensive simulations, we compare the sum decoding delay and the max decoding delay experienced when applying the policies to minimize the sum decoding delay and our policy to reduce the max decoding delay. Simulations results show that our policy gives a good agreement among all the delay aspects in all situations and outperforms the sum decoding delay policy to effectively minimize the sum decoding delay when the channel conditions become harsher. They also show that our definition of delay significantly improve the number of served receivers when they are subject to strict delay constraints.

Functional near infrared spectroscopy of the sensory and motor brain regions with simultaneous kinematic and EMG monitoring during motor tasks.

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Sukal-Moulton, Theresa; de Campos, Ana Carolina; Stanley, Christopher J; Damiano, Diane L

2014-12-05

There are several advantages that functional near-infrared spectroscopy (fNIRS) presents in the study of the neural control of human movement. It is relatively flexible with respect to participant positioning and allows for some head movements during tasks. Additionally, it is inexpensive, light weight, and portable, with very few contraindications to its use. This presents a unique opportunity to study functional brain activity during motor tasks in individuals who are typically developing, as well as those with movement disorders, such as cerebral palsy. An additional consideration when studying movement disorders, however, is the quality of actual movements performed and the potential for additional, unintended movements. Therefore, concurrent monitoring of both blood flow changes in the brain and actual movements of the body during testing is required for appropriate interpretation of fNIRS results. Here, we show a protocol for the combination of fNIRS with muscle and kinematic monitoring during motor tasks. We explore gait, a unilateral multi-joint movement (cycling), and two unilateral single-joint movements (isolated ankle dorsiflexion, and isolated hand squeezing). The techniques presented can be useful in studying both typical and atypical motor control, and can be modified to investigate a broad range of tasks and scientific questions.

ESVD: An Integrated Energy Scalable Framework for Low-Power Video Decoding Systems

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Wen Ji

2010-01-01

Full Text Available Video applications using mobile wireless devices are a challenging task due to the limited capacity of batteries. The higher complex functionality of video decoding needs high resource requirements. Thus, power efficient control has become more critical design with devices integrating complex video processing techniques. Previous works on power efficient control in video decoding systems often aim at the low complexity design and not explicitly consider the scalable impact of subfunctions in decoding process, and seldom consider the relationship with the features of compressed video date. This paper is dedicated to developing an energy-scalable video decoding (ESVD strategy for energy-limited mobile terminals. First, ESVE can dynamically adapt the variable energy resources due to the device aware technique. Second, ESVD combines the decoder control with decoded data, through classifying the data into different partition profiles according to its characteristics. Third, it introduces utility theoretical analysis during the resource allocation process, so as to maximize the resource utilization. Finally, it adapts the energy resource as different energy budget and generates the scalable video decoding output under energy-limited systems. Experimental results demonstrate the efficiency of the proposed approach.

COMMUNICATION: On variability and use of rat primary motor cortex responses in behavioral task discrimination

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Jensen, Winnie; Rousche, Patrick J.

2006-03-01

The success of a cortical motor neuroprosthetic system will rely on the system's ability to effectively execute complex motor tasks in a changing environment. Invasive, intra-cortical electrodes have been successfully used to predict joint movement and grip force of a robotic arm/hand with a non-human primate (Chapin J K, Moxon K A, Markowitz R S and Nicolelis M A L 1999 Real-time control of a robotic arm using simultaneously recorded neurons in the motor cortex Nat. Neurosci. 2 664-70). It is well known that cortical encoding occurs with a high degree of cortical plasticity and depends on both the functional and behavioral context. Questions on the expected robustness of future motor prosthesis systems therefore still remain. The objective of the present work was to study the effect of minor changes in functional movement strategies on the M1 encoding. We compared the M1 encoding in freely moving, non-constrained animals that performed two similar behavioral tasks with the same end-goal, and investigated if these behavioral tasks could be discriminated based on the M1 recordings. The rats depressed a response paddle either with a set of restrictive bars ('WB') or without the bars ('WOB') placed in front of the paddle. The WB task required changes in the motor strategy to complete the paddle press and resulted in highly stereotyped movements, whereas in the WOB task the movement strategy was not restricted. Neural population activity was recorded from 16-channel micro-wire arrays and data up to 200 ms before a paddle hit were analyzed off-line. The analysis showed a significant neural firing difference between the two similar WB and WOB tasks, and using principal component analysis it was possible to distinguish between the two tasks with a best classification at 76.6%. While the results are dependent upon a small, randomly sampled neural population, they indicate that information about similar behavioral tasks may be extracted from M1 based on relatively few

On minimizing the maximum broadcast decoding delay for instantly decodable network coding

KAUST Repository

Douik, Ahmed S.; Sorour, Sameh; Alouini, Mohamed-Slim; Ai-Naffouri, Tareq Y.

2014-01-01

In this paper, we consider the problem of minimizing the maximum broadcast decoding delay experienced by all the receivers of generalized instantly decodable network coding (IDNC). Unlike the sum decoding delay, the maximum decoding delay as a

Real-time changes in corticospinal excitability related to motor imagery of a force control task.

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Tatemoto, Tsuyoshi; Tsuchiya, Junko; Numata, Atsuki; Osawa, Ryuji; Yamaguchi, Tomofumi; Tanabe, Shigeo; Kondo, Kunitsugu; Otaka, Yohei; Sugawara, Kenichi

2017-09-29

To investigate real-time excitability changes in corticospinal pathways related to motor imagery in a changing force control task, using transcranial magnetic stimulation (TMS). Ten healthy volunteers learnt to control the contractile force of isometric right wrist dorsiflexion in order to track an on-screen sine wave form. Participants performed the trained task 40 times with actual muscle contraction in order to construct the motor image. They were then instructed to execute the task without actual muscle contraction, but by imagining contraction of the right wrist in dorsiflexion. Motor evoked potentials (MEPs), induced by TMS in the right extensor carpi radialis muscle (ECR) and flexor carpi radialis muscle (FCR), were measured during motor imagery. MEPs were induced at five time points: prior to imagery, during the gradual generation of the imaged wrist dorsiflexion (Increasing phase), the peak value of the sine wave, during the gradual reduction (Decreasing phase), and after completion of the task. The MEP ratio, as the ratio of imaged MEPs to resting-state, was compared between pre- and post-training at each time point. In the ECR muscle, the MEP ratio significantly increased during the Increasing phase and at the peak force of dorsiflexion imagery after training. Moreover, the MEP ratio was significantly greater in the Increasing phase than in the Decreasing phase. In the FCR, there were no significant consistent changes. Corticospinal excitability during motor imagery in an isometric contraction task was modulated in relation to the phase of force control after image construction. Copyright © 2017 Elsevier B.V. All rights reserved.

Motor planning flexibly optimizes performance under uncertainty about task goals.

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Wong, Aaron L; Haith, Adrian M

2017-03-03

In an environment full of potential goals, how does the brain determine which movement to execute? Existing theories posit that the motor system prepares for all potential goals by generating several motor plans in parallel. One major line of evidence for such theories is that presenting two competing goals often results in a movement intermediate between them. These intermediate movements are thought to reflect an unintentional averaging of the competing plans. However, normative theories suggest instead that intermediate movements might actually be deliberate, generated because they improve task performance over a random guessing strategy. To test this hypothesis, we vary the benefit of making an intermediate movement by changing movement speed. We find that participants generate intermediate movements only at (slower) speeds where they measurably improve performance. Our findings support the normative view that the motor system selects only a single, flexible motor plan, optimized for uncertain goals.

Upper Extremity Motor Learning among Individuals with Parkinson's Disease: A Meta-Analysis Evaluating Movement Time in Simple Tasks

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K. Felix

2012-01-01

Full Text Available Motor learning has been found to occur in the rehabilitation of individuals with Parkinson's disease (PD. Through repetitive structured practice of motor tasks, individuals show improved performance, confirming that motor learning has probably taken place. Although a number of studies have been completed evaluating motor learning in people with PD, the sample sizes were small and the improvements were variable. The purpose of this meta-analysis was to determine the ability of people with PD to learn motor tasks. Studies which measured movement time in upper extremity reaching tasks and met the inclusion criteria were included in the analysis. Results of the meta-analysis indicated that people with PD and neurologically healthy controls both demonstrated motor learning, characterized by a decrease in movement time during upper extremity movements. Movement time improvements were greater in the control group than in individuals with PD. These results support the findings that the practice of upper extremity reaching tasks is beneficial in reducing movement time in persons with PD and has important implications for rehabilitation.

Cognitive-motor dual-task ability of athletes with and without intellectual impairment.

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Van Biesen, Debbie; Jacobs, Lore; McCulloch, Katina; Janssens, Luc; Vanlandewijck, Yves C

2018-03-01

Cognition is important in many sports, for example, making split-second-decisions under pressure, or memorising complex movement sequences. The dual-task (DT) paradigm is an ecologically valid approach for the assessment of cognitive function in conjunction with motor demands. This study aimed to determine the impact of impaired intelligence on DT performance. The motor task required balancing on one leg on a beam, and the cognitive task was a multiple-object-tracking (MOT) task assessing dynamic visual-search capacity. The sample included 206 well-trained athletes with and without intellectual impairment (II), matched for sport, age and training volume (140 males, 66 females, M age = 23.2 ± 4.1 years, M training experience = 12.3 ± 5.7 years). In the single-task condition, II-athletes showed reduced balance control (F = 55.9, P balance and the MOT task between both groups. The DT costs were significantly larger for the II-athletes (-8.28% versus -1.34% for MOT and -33.13% versus -12.89% for balance). The assessment of MOT in a DT paradigm provided insight in how impaired intelligence constrains the ability of II-athletes to successfully perform at the highest levels in the complex and dynamical sport-environment.

Deep learning with convolutional neural networks for EEG decoding and visualization.

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Schirrmeister, Robin Tibor; Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio

2017-11-01

Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end-to-end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end-to-end EEG analysis, but a better understanding of how to design and train ConvNets for end-to-end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task-related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG-based brain mapping. Hum Brain Mapp 38:5391-5420, 2017. © 2017 Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Knowledge discovery in databases of biomechanical variables: application to the sit to stand motor task

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Benvenuti Francesco

2004-10-01

Full Text Available Abstract Background The interpretation of data obtained in a movement analysis laboratory is a crucial issue in clinical contexts. Collection of such data in large databases might encourage the use of modern techniques of data mining to discover additional knowledge with automated methods. In order to maximise the size of the database, simple and low-cost experimental set-ups are preferable. The aim of this study was to extract knowledge inherent in the sit-to-stand task as performed by healthy adults, by searching relationships among measured and estimated biomechanical quantities. An automated method was applied to a large amount of data stored in a database. The sit-to-stand motor task was already shown to be adequate for determining the level of individual motor ability. Methods The technique of search for association rules was chosen to discover patterns as part of a Knowledge Discovery in Databases (KDD process applied to a sit-to-stand motor task observed with a simple experimental set-up and analysed by means of a minimum measured input model. Selected parameters and variables of a database containing data from 110 healthy adults, of both genders and of a large range of age, performing the task were considered in the analysis. Results A set of rules and definitions were found characterising the patterns shared by the investigated subjects. Time events of the task turned out to be highly interdependent at least in their average values, showing a high level of repeatability of the timing of the performance of the task. Conclusions The distinctive patterns of the sit-to-stand task found in this study, associated to those that could be found in similar studies focusing on subjects with pathologies, could be used as a reference for the functional evaluation of specific subjects performing the sit-to-stand motor task.

Task-specific modulation of effective connectivity during two simple unimanual motor tasks: A 122-channel EEG study

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Herz, Damian M.; Christensen, Mark S.; Reck, Christiane

2012-01-01

Neural oscillations are thought to underlie coupling of spatially remote neurons and gating of information within the human sensorimotor system. Here we tested the hypothesis that different unimanual motor tasks are specifically associated with distinct patterns of oscillatory coupling in human...

Positron computed tomography studies of cerebral metabolic responses to complex motor tasks

International Nuclear Information System (INIS)

Phelps, M.E.; Mazziotta, J.C.

1984-01-01

Human motor system organization was explored in 8 right-handed male subjects using /sup 18/F-fluorodeoxyglucose and positron computed tomography to measure cerebral glucose metabolism. Five subjects had triple studies (eyes closed) including: control (hold pen in right hand without moving), normal size writing (subject repeatedly writes name) and large (10-15 X normal) name writing. In these studies normal and large size writing had a similar distribution of metabolic responses when compared to control studies. Activations (percent change from control) were in the range of 12-20% and occurred in the striatum bilaterally > contralateral Rolandic cortex > contralateral thalamus. No significant activations were observed in the ipsilateral thalamus, Rolandic cortex or cerebellum (supplementary motor cortex was not examined). The magnitude of the metabolic response in the striatum was greater with the large versus normal sized writing. This differential response may be due to an increased number and topographic distribution of neurons responding with the same average activity between tasks or an increase in the functional activity of the same neuronal population between the two tasks (present spatial resolution inadequate to differentiate). When subjects (N=3) performed novel sequential finger movements, the maximal metabolic response was in the contralateral Rolandic cortex > striatum. Such studies provide a means of exploring human motor system organization, motor learning and provide a basis for examining patients with motor system disorders

Walking and talking: an investigation of cognitive-motor dual tasking in multiple sclerosis.

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Hamilton, F; Rochester, L; Paul, L; Rafferty, D; O'Leary, C P; Evans, J J

2009-10-01

Deficits in motor functioning, including walking, and in cognitive functions, including attention, are known to be prevalent in multiple sclerosis (MS), though little attention has been paid to how impairments in these areas of functioning interact. This study investigated the effects of performing a concurrent cognitive task when walking in people with MS. Level of task demand was manipulated to investigate whether this affected level of dual-task decrement. Eighteen participants with MS and 18 healthy controls took part. Participants completed walking and cognitive tasks under single- and dual-task conditions. Compared to healthy controls, MS participants showed greater decrements in performance under dual-task conditions in cognitive task performance, walking speed and swing time variability. In the MS group, the degree of decrement under dual-task conditions was related to levels of fatigue, a measure of general cognitive functioning and self-reported everyday cognitive errors, but not to measures of disease severity or duration. Difficulty with walking and talking in MS may be a result of a divided attention deficit or of overloading of the working memory system, and further investigation is needed. We suggest that difficulty with walking and talking in MS may lead to practical problems in everyday life, including potentially increasing the risk of falls. Clinical tools to assess cognitive-motor dual-tasking ability are needed.

Structural integrity of callosal midbody influences intermanual transfer in a motor reaction-time task.

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Bonzano, Laura; Tacchino, Andrea; Roccatagliata, Luca; Mancardi, Giovanni Luigi; Abbruzzese, Giovanni; Bove, Marco

2011-02-01

Training one hand on a motor task results in performance improvements in the other hand, also when stimuli are randomly presented (nonspecific transfer). Corpus callosum (CC) is the main structure involved in interhemispheric information transfer; CC pathology occurs in patients with multiple sclerosis (PwMS) and is related to altered performance of tasks requiring interhemispheric transfer of sensorimotor information. To investigate the role of CC in nonspecific transfer during a pure motor reaction-time task, we combined motor behavior with diffusion tensor imaging analysis in PwMS. Twenty-two PwMS and 10 controls, all right-handed, were asked to respond to random stimuli with appropriate finger opposition movements with the right (learning) and then the left (transfer) hand. PwMS were able to improve motor performance reducing response times with practice with a trend similar to controls and preserved the ability to transfer the acquired motor information from the learning to the transfer hand. A higher variability in the transfer process, indicated by a significantly larger standard deviation of mean nonspecific transfer, was found in the PwMS group with respect to the control group, suggesting the presence of subtle impairments in interhemispheric communication in some patients. Then, we correlated the amount of nonspecific transfer with mean fractional anisotropy (FA) values, indicative of microstructural damage, obtained in five CC subregions identified on PwMS's FA maps. A significant correlation was found only in the subregion including posterior midbody (Pearson's r = 0.74, P = 0.003), which thus seems to be essential for the interhemispheric transfer of information related to pure sensorimotor tasks. Copyright © 2010 Wiley-Liss, Inc.

Decoding of interleaved Reed-Solomon codes using improved power decoding

DEFF Research Database (Denmark)

Puchinger, Sven; Rosenkilde ne Nielsen, Johan

2017-01-01

We propose a new partial decoding algorithm for m-interleaved Reed-Solomon (IRS) codes that can decode, with high probability, a random error of relative weight 1 − Rm/m+1 at all code rates R, in time polynomial in the code length n. For m > 2, this is an asymptotic improvement over the previous...... state-of-the-art for all rates, and the first improvement for R > 1/3 in the last 20 years. The method combines collaborative decoding of IRS codes with power decoding up to the Johnson radius....

The Effects of Divided Attention on Speech Motor, Verbal Fluency, and Manual Task Performance

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Dromey, Christopher; Shim, Erin

2008-01-01

Purpose: The goal of this study was to evaluate aspects of the "functional distance hypothesis," which predicts that tasks regulated by brain networks in closer anatomic proximity will interfere more with each other than tasks controlled by spatially distant regions. Speech, verbal fluency, and manual motor tasks were examined to ascertain whether…

Age-Related Differences in Corticospinal Excitability during Observation and Motor Imagery of Balance Tasks.

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Mouthon, Audrey A; Ruffieux, Jan; Keller, Martin; Taube, Wolfgang

2016-01-01

Postural control declines across adult lifespan. Non-physical balance training has been suggested as an alternative to improve postural control in frail/immobilized elderly people. Previous studies showed that this kind of training can improve balance control in young and older adults. However, it is unclear whether the brain of young and older adults is activated differently during mental simulations of balance tasks. For this purpose, soleus (SOL) and tibialis motor evoked potentials (MEPs) and SOL H-reflexes were elicited while 15 elderly (mean ± SD = 71 ± 4.6 years) and 15 young participants (mean ± SD = 27 ± 4.6 years) mentally simulated static and dynamic balance tasks using motor imagery (MI), action observation (AO) or the combination of AO and MI (AO + MI). Young subjects displayed significant modulations of MEPs that depended on the kind of mental simulation and the postural task. Elderly adults also revealed differences between tasks, but not between mental simulation conditions. Furthermore, the elderly displayed larger MEP facilitation during mental simulation (AGE-GROUP; F (1,28) = 5.9; p = 0.02) in the SOL muscle compared to the young and a task-dependent modulation of the tibialis background electromyography (bEMG) activity. H-reflex amplitudes and bEMG in the SOL showed neither task- nor age-dependent modulation. As neither mental simulation nor balance tasks modulated H-reflexes and bEMG in the SOL muscle, despite large variations in the MEP-amplitudes, there seems to be an age-related change in the internal cortical representation of balance tasks. Moreover, the modulation of the tibialis bEMG in the elderly suggests that aging partially affects the ability to inhibit motor output.

Functional MRI of tongue motor tasks in patients with tongue cancer: observations before and after partial glossectomy

International Nuclear Information System (INIS)

Haupage, Samantha; Branski, Ryan C.; Kraus, Dennis; Peck, Kyung K.; Hsu, Meier; Holodny, Andrei

2010-01-01

The current study seeks to provide preliminary data regarding this central, adaptive response during tongue motor tasks utilizing functional magnetic resonance imaging (fMRI) before and after glossectomy. Six patients, with confirmed histological diagnoses of oral tongue cancer, underwent fMRI before and 6 months after partial glossectomy. These data were compared to nine healthy controls. All subjects performed three tongue motor tasks during fMRI: tongue tapping (TT), dry swallow (Dry), and wet swallow (Wet). Following surgery, increased activation was subjectively observed in the superior parietal lobule, supplementary motor area, and anterior cingulate. Region of interest (ROI) analysis of the precentral gyrus confirmed increased cortical activity following surgery. In addition, comparisons between pre-surgical scans and controls suggested the dry swallow task was sensitive to elicit tongue-related activation in the precentral gyrus (p ≤ 0.05). The adaptive changes in the cortex following partial glossectomy reflect recruitment of the parietal, frontal, and cingulate cortex during tongue motor tasks. In addition, post-operative activation patterns more closely approximated control levels than the pre-operative scans. Furthermore, the dry swallow task appears most specific to elicit tongue-related cortical activity. (orig.)

Functional MRI of tongue motor tasks in patients with tongue cancer: observations before and after partial glossectomy

Energy Technology Data Exchange (ETDEWEB)

Haupage, Samantha; Branski, Ryan C.; Kraus, Dennis [Memorial Sloan-Kettering Cancer Center, Head and Neck Surgery, New York, NY (United States); Peck, Kyung K. [Memorial Sloan-Kettering Cancer Center, Department of Radiology, New York, NY (United States); Memorial Sloan-Kettering Cancer Center, Medical Physics, New York, NY (United States); Memorial Sloan-Kettering Cancer Center, Department of Medical Physics and Radiology, New York, NY (United States); Hsu, Meier [Memorial Sloan-Kettering Cancer Center, Department of Epidemiology and Biostatistics, New York, NY (United States); Holodny, Andrei [Memorial Sloan-Kettering Cancer Center, Department of Radiology, New York, NY (United States)

2010-12-15

The current study seeks to provide preliminary data regarding this central, adaptive response during tongue motor tasks utilizing functional magnetic resonance imaging (fMRI) before and after glossectomy. Six patients, with confirmed histological diagnoses of oral tongue cancer, underwent fMRI before and 6 months after partial glossectomy. These data were compared to nine healthy controls. All subjects performed three tongue motor tasks during fMRI: tongue tapping (TT), dry swallow (Dry), and wet swallow (Wet). Following surgery, increased activation was subjectively observed in the superior parietal lobule, supplementary motor area, and anterior cingulate. Region of interest (ROI) analysis of the precentral gyrus confirmed increased cortical activity following surgery. In addition, comparisons between pre-surgical scans and controls suggested the dry swallow task was sensitive to elicit tongue-related activation in the precentral gyrus (p {<=} 0.05). The adaptive changes in the cortex following partial glossectomy reflect recruitment of the parietal, frontal, and cingulate cortex during tongue motor tasks. In addition, post-operative activation patterns more closely approximated control levels than the pre-operative scans. Furthermore, the dry swallow task appears most specific to elicit tongue-related cortical activity. (orig.)

Low-Power Bitstream-Residual Decoder for H.264/AVC Baseline Profile Decoding

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Xu Ke

2009-01-01

Full Text Available Abstract We present the design and VLSI implementation of a novel low-power bitstream-residual decoder for H.264/AVC baseline profile. It comprises a syntax parser, a parameter decoder, and an Inverse Quantization Inverse Transform (IQIT decoder. The syntax parser detects and decodes each incoming codeword in the bitstream under the control of a hierarchical Finite State Machine (FSM; the IQIT decoder performs inverse transform and quantization with pipelining and parallelism. Various power reduction techniques, such as data-driven based on statistic results, nonuniform partition, precomputation, guarded evaluation, hierarchical FSM decomposition, TAG method, zero-block skipping, and clock gating , are adopted and integrated throughout the bitstream-residual decoder. With innovative architecture, the proposed design is able to decode QCIF video sequences of 30 fps at a clock rate as low as 1.5 MHz. A prototype H.264/AVC baseline decoding chip utilizing the proposed decoder is fabricated in UMC 0.18  m 1P6M CMOS technology. The proposed design is measured under 1 V 1.8 V supply with 0.1 V step. It dissipates 76  W at 1 V and 253  W at 1.8 V.

Online decoding of object-based attention using real-time fMRI.

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Niazi, Adnan M; van den Broek, Philip L C; Klanke, Stefan; Barth, Markus; Poel, Mannes; Desain, Peter; van Gerven, Marcel A J

2014-01-01

Visual attention is used to selectively filter relevant information depending on current task demands and goals. Visual attention is called object-based attention when it is directed to coherent forms or objects in the visual field. This study used real-time functional magnetic resonance imaging for moment-to-moment decoding of attention to spatially overlapped objects belonging to two different object categories. First, a whole-brain classifier was trained on pictures of faces and places. Subjects then saw transparently overlapped pictures of a face and a place, and attended to only one of them while ignoring the other. The category of the attended object, face or place, was decoded on a scan-by-scan basis using the previously trained decoder. The decoder performed at 77.6% accuracy indicating that despite competing bottom-up sensory input, object-based visual attention biased neural patterns towards that of the attended object. Furthermore, a comparison between different classification approaches indicated that the representation of faces and places is distributed rather than focal. This implies that real-time decoding of object-based attention requires a multivariate decoding approach that can detect these distributed patterns of cortical activity. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

The cognitive complexity of concurrent cognitive-motor tasks reveals age-related deficits in motor performance

DEFF Research Database (Denmark)

Oliveira, Anderson Souza; Reiche, Mikkel Staall; Vinescu, Cristina Ioana

2018-01-01

Aging reduces cognitive functions, and such impairments have implications in mental and motor performance. Cognitive function has been recently linked to the risk of falls in older adults. Physical activities have been used to attenuate the declines in cognitive functions and reduce fall incidence......, but little is known whether a physically active lifestyle can maintain physical performance under cognitively demanding conditions. The aim of this study was to verify whether physically active older adults present similar performance deficits during upper limb response time and precision stepping walking...... tasks when compared to younger adults. Both upper limb and walking tasks involved simple and complex cognitive demands through decision-making. For both tasks, decision-making was assessed by including a distracting factor to the execution. The results showed that older adults were substantially slower...

Reward Motivation Enhances Task Coding in Frontoparietal Cortex.

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Etzel, Joset A; Cole, Michael W; Zacks, Jeffrey M; Kay, Kendrick N; Braver, Todd S

2016-04-01

Reward motivation often enhances task performance, but the neural mechanisms underlying such cognitive enhancement remain unclear. Here, we used a multivariate pattern analysis (MVPA) approach to test the hypothesis that motivation-related enhancement of cognitive control results from improved encoding and representation of task set information. Participants underwent two fMRI sessions of cued task switching, the first under baseline conditions, and the second with randomly intermixed reward incentive and no-incentive trials. Information about the upcoming task could be successfully decoded from cue-related activation patterns in a set of frontoparietal regions typically associated with task control. More critically, MVPA classifiers trained on the baseline session had significantly higher decoding accuracy on incentive than non-incentive trials, with decoding improvement mediating reward-related enhancement of behavioral performance. These results strongly support the hypothesis that reward motivation enhances cognitive control, by improving the discriminability of task-relevant information coded and maintained in frontoparietal brain regions. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Effect of Error Augmentation on Brain Activation and Motor Learning of a Complex Locomotor Task

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Laura Marchal-Crespo

2017-09-01

Full Text Available Up to date, the functional gains obtained after robot-aided gait rehabilitation training are limited. Error augmenting strategies have a great potential to enhance motor learning of simple motor tasks. However, little is known about the effect of these error modulating strategies on complex tasks, such as relearning to walk after a neurologic accident. Additionally, neuroimaging evaluation of brain regions involved in learning processes could provide valuable information on behavioral outcomes. We investigated the effect of robotic training strategies that augment errors—error amplification and random force disturbance—and training without perturbations on brain activation and motor learning of a complex locomotor task. Thirty-four healthy subjects performed the experiment with a robotic stepper (MARCOS in a 1.5 T MR scanner. The task consisted in tracking a Lissajous figure presented on a display by coordinating the legs in a gait-like movement pattern. Behavioral results showed that training without perturbations enhanced motor learning in initially less skilled subjects, while error amplification benefited better-skilled subjects. Training with error amplification, however, hampered transfer of learning. Randomly disturbing forces induced learning and promoted transfer in all subjects, probably because the unexpected forces increased subjects' attention. Functional MRI revealed main effects of training strategy and skill level during training. A main effect of training strategy was seen in brain regions typically associated with motor control and learning, such as, the basal ganglia, cerebellum, intraparietal sulcus, and angular gyrus. Especially, random disturbance and no perturbation lead to stronger brain activation in similar brain regions than error amplification. Skill-level related effects were observed in the IPS, in parts of the superior parietal lobe (SPL, i.e., precuneus, and temporal cortex. These neuroimaging findings

Decoding sequence learning from single-trial intracranial EEG in humans.

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Marzia De Lucia

Full Text Available We propose and validate a multivariate classification algorithm for characterizing changes in human intracranial electroencephalographic data (iEEG after learning motor sequences. The algorithm is based on a Hidden Markov Model (HMM that captures spatio-temporal properties of the iEEG at the level of single trials. Continuous intracranial iEEG was acquired during two sessions (one before and one after a night of sleep in two patients with depth electrodes implanted in several brain areas. They performed a visuomotor sequence (serial reaction time task, SRTT using the fingers of their non-dominant hand. Our results show that the decoding algorithm correctly classified single iEEG trials from the trained sequence as belonging to either the initial training phase (day 1, before sleep or a later consolidated phase (day 2, after sleep, whereas it failed to do so for trials belonging to a control condition (pseudo-random sequence. Accurate single-trial classification was achieved by taking advantage of the distributed pattern of neural activity. However, across all the contacts the hippocampus contributed most significantly to the classification accuracy for both patients, and one fronto-striatal contact for one patient. Together, these human intracranial findings demonstrate that a multivariate decoding approach can detect learning-related changes at the level of single-trial iEEG. Because it allows an unbiased identification of brain sites contributing to a behavioral effect (or experimental condition at the level of single subject, this approach could be usefully applied to assess the neural correlates of other complex cognitive functions in patients implanted with multiple electrodes.

Decoding English Alphabet Letters Using EEG Phase Information

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YiYan Wang

2018-02-01

Full Text Available Increasing evidence indicates that the phase pattern and power of the low frequency oscillations of brain electroencephalograms (EEG contain significant information during the human cognition of sensory signals such as auditory and visual stimuli. Here, we investigate whether and how the letters of the alphabet can be directly decoded from EEG phase and power data. In addition, we investigate how different band oscillations contribute to the classification and determine the critical time periods. An English letter recognition task was assigned, and statistical analyses were conducted to decode the EEG signal corresponding to each letter visualized on a computer screen. We applied support vector machine (SVM with gradient descent method to learn the potential features for classification. It was observed that the EEG phase signals have a higher decoding accuracy than the oscillation power information. Low-frequency theta and alpha oscillations have phase information with higher accuracy than do other bands. The decoding performance was best when the analysis period began from 180 to 380 ms after stimulus presentation, especially in the lateral occipital and posterior temporal scalp regions (PO7 and PO8. These results may provide a new approach for brain-computer interface techniques (BCI and may deepen our understanding of EEG oscillations in cognition.

Dual Task of Fine Motor Skill and Problem Solving in Individuals With Multiple Sclerosis: A Pilot Study.

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Goverover, Y; Sandroff, B M; DeLuca, J

2018-04-01

To (1) examine and compare dual-task performance in patients with multiple sclerosis (MS) and healthy controls (HCs) using mathematical problem-solving questions that included an everyday competence component while performing an upper extremity fine motor task; and (2) examine whether difficulties in dual-task performance are associated with problems in performing an everyday internet task. Pilot study, mixed-design with both a within and between subjects' factor. A nonprofit rehabilitation research institution and the community. Participants (N=38) included persons with MS (n=19) and HCs (n=19) who were recruited from a nonprofit rehabilitation research institution and from the community. Not applicable. Participant were presented with 2 testing conditions: (1) solving mathematical everyday problems or placing bolts into divots (single-task condition); and (2) solving problems while putting bolts into divots (dual-task condition). Additionally, participants were required to perform a test of everyday internet competence. As expected, dual-task performance was significantly worse than either of the single-task tasks (ie, number of bolts into divots or correct answers, and time to answer the questions). Cognitive but not motor dual-task cost was associated with worse performance in activities of everyday internet tasks. Cognitive dual-task cost is significantly associated with worse performance of everyday technology. This was not observed in the motor dual-task cost. The implications of dual-task costs on everyday activity are discussed. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Event-related near-infrared spectroscopy detects conflict in the motor cortex in a Stroop task.

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Szűcs, Dénes; Killikelly, Clare; Cutini, Simone

2012-10-05

The Stroop effect is one of the most popular models of conflict processing in neuroscience and psychology. The response conflict theory of the Stroop effect explains decreased performance in the incongruent condition of Stroop tasks by assuming that the task-relevant and the task-irrelevant stimulus features elicit conflicting response tendencies. However, to date, there is not much explicit neural evidence supporting this theory. Here we used functional near-infrared imaging (fNIRS) to examine whether conflict at the level of the motor cortex can be detected in the incongruent relative to the congruent condition of a Stroop task. Response conflict was determined by comparing the activity of the hemisphere ipsilateral to the response hand in the congruent and incongruent conditions. First, results provided explicit hemodynamic evidence supporting the response conflict theory of the Stroop effect: there was greater motor cortex activation in the hemisphere ipsilateral to the response hand in the incongruent than in the congruent condition during the initial stage of the hemodynamic response. Second, as fNIRS is still a relatively novel technology, it is methodologically significant that our data shows that fNIRS is able to detect a brief and transient increase in hemodynamic activity localized to the motor cortex, which in this study is related to subthreshold motor response activation. Copyright © 2012 Elsevier B.V. All rights reserved.

Cathodal Transcranial Direct Current Stimulation Over Left Dorsolateral Prefrontal Cortex Area Promotes Implicit Motor Learning in a Golf Putting Task.

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Zhu, Frank F; Yeung, Andrew Y; Poolton, Jamie M; Lee, Tatia M C; Leung, Gilberto K K; Masters, Rich S W

2015-01-01

Implicit motor learning is characterized by low dependence on working memory and stable performance despite stress, fatigue, or multi-tasking. However, current paradigms for implicit motor learning are based on behavioral interventions that are often task-specific and limited when applied in practice. To investigate whether cathodal transcranial direct current stimulation (tDCS) over the left dorsolateral prefrontal cortex (DLPFC) area during motor learning suppressed working memory activity and reduced explicit verbal-analytical involvement in movement control, thereby promoting implicit motor learning. Twenty-seven healthy individuals practiced a golf putting task during a Training Phase while receiving either real cathodal tDCS stimulation over the left DLPFC area or sham stimulation. Their performance was assessed during a Test phase on another day. Verbal working memory capacity was assessed before and after the Training Phase, and before the Test Phase. Compared to sham stimulation, real stimulation suppressed verbal working memory activity after the Training Phase, but enhanced golf putting performance during the Training Phase and the Test Phase, especially when participants were required to multi-task. Cathodal tDCS over the left DLPFC may foster implicit motor learning and performance in complex real-life motor tasks that occur during sports, surgery or motor rehabilitation. Copyright © 2015 Elsevier Inc. All rights reserved.

Learning a common dictionary for subject-transfer decoding with resting calibration.

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Morioka, Hiroshi; Kanemura, Atsunori; Hirayama, Jun-ichiro; Shikauchi, Manabu; Ogawa, Takeshi; Ikeda, Shigeyuki; Kawanabe, Motoaki; Ishii, Shin

2015-05-01

Brain signals measured over a series of experiments have inherent variability because of different physical and mental conditions among multiple subjects and sessions. Such variability complicates the analysis of data from multiple subjects and sessions in a consistent way, and degrades the performance of subject-transfer decoding in a brain-machine interface (BMI). To accommodate the variability in brain signals, we propose 1) a method for extracting spatial bases (or a dictionary) shared by multiple subjects, by employing a signal-processing technique of dictionary learning modified to compensate for variations between subjects and sessions, and 2) an approach to subject-transfer decoding that uses the resting-state activity of a previously unseen target subject as calibration data for compensating for variations, eliminating the need for a standard calibration based on task sessions. Applying our methodology to a dataset of electroencephalography (EEG) recordings during a selective visual-spatial attention task from multiple subjects and sessions, where the variability compensation was essential for reducing the redundancy of the dictionary, we found that the extracted common brain activities were reasonable in the light of neuroscience knowledge. The applicability to subject-transfer decoding was confirmed by improved performance over existing decoding methods. These results suggest that analyzing multisubject brain activities on common bases by the proposed method enables information sharing across subjects with low-burden resting calibration, and is effective for practical use of BMI in variable environments. Copyright © 2015 Elsevier Inc. All rights reserved.

Completion time reduction in instantly decodable network coding through decoding delay control

KAUST Repository

Douik, Ahmed S.; Sorour, Sameh; Alouini, Mohamed-Slim; Al-Naffouri, Tareq Y.

2014-01-01

For several years, the completion time and the decoding delay problems in Instantly Decodable Network Coding (IDNC) were considered separately and were thought to completely act against each other. Recently, some works aimed to balance the effects of these two important IDNC metrics but none of them studied a further optimization of one by controlling the other. In this paper, we study the effect of controlling the decoding delay to reduce the completion time below its currently best known solution. We first derive the decoding-delay-dependent expressions of the users' and their overall completion times. Although using such expressions to find the optimal overall completion time is NP-hard, we use a heuristic that minimizes the probability of increasing the maximum of these decoding-delay-dependent completion time expressions after each transmission through a layered control of their decoding delays. Simulation results show that this new algorithm achieves both a lower mean completion time and mean decoding delay compared to the best known heuristic for completion time reduction. The gap in performance becomes significant for harsh erasure scenarios.

Completion time reduction in instantly decodable network coding through decoding delay control

KAUST Repository

Douik, Ahmed S.

2014-12-01

For several years, the completion time and the decoding delay problems in Instantly Decodable Network Coding (IDNC) were considered separately and were thought to completely act against each other. Recently, some works aimed to balance the effects of these two important IDNC metrics but none of them studied a further optimization of one by controlling the other. In this paper, we study the effect of controlling the decoding delay to reduce the completion time below its currently best known solution. We first derive the decoding-delay-dependent expressions of the users\\' and their overall completion times. Although using such expressions to find the optimal overall completion time is NP-hard, we use a heuristic that minimizes the probability of increasing the maximum of these decoding-delay-dependent completion time expressions after each transmission through a layered control of their decoding delays. Simulation results show that this new algorithm achieves both a lower mean completion time and mean decoding delay compared to the best known heuristic for completion time reduction. The gap in performance becomes significant for harsh erasure scenarios.

Effect of visual feedback on brain activation during motor tasks: an FMRI study.

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Noble, Jeremy W; Eng, Janice J; Boyd, Lara A

2013-07-01

This study examined the effect of visual feedback and force level on the neural mechanisms responsible for the performance of a motor task. We used a voxel-wise fMRI approach to determine the effect of visual feedback (with and without) during a grip force task at 35% and 70% of maximum voluntary contraction. Two areas (contralateral rostral premotor cortex and putamen) displayed an interaction between force and feedback conditions. When the main effect of feedback condition was analyzed, higher activation when visual feedback was available was found in 22 of the 24 active brain areas, while the two other regions (contralateral lingual gyrus and ipsilateral precuneus) showed greater levels of activity when no visual feedback was available. The results suggest that there is a potentially confounding influence of visual feedback on brain activation during a motor task, and for some regions, this is dependent on the level of force applied.

Inferior frontal gyrus links visual and motor cortices during a visuomotor precision grip force task.

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Papadelis, Christos; Arfeller, Carola; Erla, Silvia; Nollo, Giandomenico; Cattaneo, Luigi; Braun, Christoph

2016-11-01

Coordination between vision and action relies on a fronto-parietal network that receives visual and proprioceptive sensory input in order to compute motor control signals. Here, we investigated with magnetoencephalography (MEG) which cortical areas are functionally coupled on the basis of synchronization during visuomotor integration. MEG signals were recorded from twelve healthy adults while performing a unimanual visuomotor (VM) task and control conditions. The VM task required the integration of pinch motor commands with visual sensory feedback. By using a beamformer, we localized the neural activity in the frequency range of 1-30Hz during the VM compared to rest. Virtual sensors were estimated at the active locations. A multivariate autoregressive model was used to estimate the power and coherence of estimated activity at the virtual sensors. Event-related desynchronisation (ERD) during VM was observed in early visual areas, the rostral part of the left inferior frontal gyrus (IFG), the right IFG, the superior parietal lobules, and the left hand motor cortex (M1). Functional coupling in the alpha frequency band bridged the regional activities observed in motor and visual cortices (the start and the end points in the visuomotor loop) through the left or right IFG. Coherence between the left IFG and left M1 correlated inversely with the task performance. Our results indicate that an occipital-prefrontal-motor functional network facilitates the modulation of instructed motor responses to visual cues. This network may supplement the mechanism for guiding actions that is fully incorporated into the dorsal visual stream. Copyright © 2016 Elsevier B.V. All rights reserved.

Abnormal motor cortex excitability during linguistic tasks in adductor-type spasmodic dysphonia.

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Suppa, A; Marsili, L; Giovannelli, F; Di Stasio, F; Rocchi, L; Upadhyay, N; Ruoppolo, G; Cincotta, M; Berardelli, A

2015-08-01

In healthy subjects (HS), transcranial magnetic stimulation (TMS) applied during 'linguistic' tasks discloses excitability changes in the dominant hemisphere primary motor cortex (M1). We investigated 'linguistic' task-related cortical excitability modulation in patients with adductor-type spasmodic dysphonia (ASD), a speech-related focal dystonia. We studied 10 ASD patients and 10 HS. Speech examination included voice cepstral analysis. We investigated the dominant/non-dominant M1 excitability at baseline, during 'linguistic' (reading aloud/silent reading/producing simple phonation) and 'non-linguistic' tasks (looking at non-letter strings/producing oral movements). Motor evoked potentials (MEPs) were recorded from the contralateral hand muscles. We measured the cortical silent period (CSP) length and tested MEPs in HS and patients performing the 'linguistic' tasks with different voice intensities. We also examined MEPs in HS and ASD during hand-related 'action-verb' observation. Patients were studied under and not-under botulinum neurotoxin-type A (BoNT-A). In HS, TMS over the dominant M1 elicited larger MEPs during 'reading aloud' than during the other 'linguistic'/'non-linguistic' tasks. Conversely, in ASD, TMS over the dominant M1 elicited increased-amplitude MEPs during 'reading aloud' and 'syllabic phonation' tasks. CSP length was shorter in ASD than in HS and remained unchanged in both groups performing 'linguistic'/'non-linguistic' tasks. In HS and ASD, 'linguistic' task-related excitability changes were present regardless of the different voice intensities. During hand-related 'action-verb' observation, MEPs decreased in HS, whereas in ASD they increased. In ASD, BoNT-A improved speech, as demonstrated by cepstral analysis and restored the TMS abnormalities. ASD reflects dominant hemisphere excitability changes related to 'linguistic' tasks; BoNT-A returns these excitability changes to normal. © 2015 Federation of European Neuroscience Societies and John

Automatic motor task selection via a bandit algorithm for a brain-controlled button

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Fruitet, Joan; Carpentier, Alexandra; Munos, Rémi; Clerc, Maureen

2013-02-01

Objective. Brain-computer interfaces (BCIs) based on sensorimotor rhythms use a variety of motor tasks, such as imagining moving the right or left hand, the feet or the tongue. Finding the tasks that yield best performance, specifically to each user, is a time-consuming preliminary phase to a BCI experiment. This study presents a new adaptive procedure to automatically select (online) the most promising motor task for an asynchronous brain-controlled button. Approach. We develop for this purpose an adaptive algorithm UCB-classif based on the stochastic bandit theory and design an EEG experiment to test our method. We compare (offline) the adaptive algorithm to a naïve selection strategy which uses uniformly distributed samples from each task. We also run the adaptive algorithm online to fully validate the approach. Main results. By not wasting time on inefficient tasks, and focusing on the most promising ones, this algorithm results in a faster task selection and a more efficient use of the BCI training session. More precisely, the offline analysis reveals that the use of this algorithm can reduce the time needed to select the most appropriate task by almost half without loss in precision, or alternatively, allow us to investigate twice the number of tasks within a similar time span. Online tests confirm that the method leads to an optimal task selection. Significance. This study is the first one to optimize the task selection phase by an adaptive procedure. By increasing the number of tasks that can be tested in a given time span, the proposed method could contribute to reducing ‘BCI illiteracy’.

Observing human movements helps decoding environmental forces.

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Zago, Myrka; La Scaleia, Barbara; Miller, William L; Lacquaniti, Francesco

2011-11-01

Vision of human actions can affect several features of visual motion processing, as well as the motor responses of the observer. Here, we tested the hypothesis that action observation helps decoding environmental forces during the interception of a decelerating target within a brief time window, a task intrinsically very difficult. We employed a factorial design to evaluate the effects of scene orientation (normal or inverted) and target gravity (normal or inverted). Button-press triggered the motion of a bullet, a piston, or a human arm. We found that the timing errors were smaller for upright scenes irrespective of gravity direction in the Bullet group, while the errors were smaller for the standard condition of normal scene and gravity in the Piston group. In the Arm group, instead, performance was better when the directions of scene and target gravity were concordant, irrespective of whether both were upright or inverted. These results suggest that the default viewer-centered reference frame is used with inanimate scenes, such as those of the Bullet and Piston protocols. Instead, the presence of biological movements in animate scenes (as in the Arm protocol) may help processing target kinematics under the ecological conditions of coherence between scene and target gravity directions.

Iterative List Decoding

DEFF Research Database (Denmark)

Justesen, Jørn; Høholdt, Tom; Hjaltason, Johan

2005-01-01

We analyze the relation between iterative decoding and the extended parity check matrix. By considering a modified version of bit flipping, which produces a list of decoded words, we derive several relations between decodable error patterns and the parameters of the code. By developing a tree...... of codewords at minimal distance from the received vector, we also obtain new information about the code....

Adaptive decoding of convolutional codes

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Hueske, K.; Geldmacher, J.; Götze, J.

2007-06-01

Convolutional codes, which are frequently used as error correction codes in digital transmission systems, are generally decoded using the Viterbi Decoder. On the one hand the Viterbi Decoder is an optimum maximum likelihood decoder, i.e. the most probable transmitted code sequence is obtained. On the other hand the mathematical complexity of the algorithm only depends on the used code, not on the number of transmission errors. To reduce the complexity of the decoding process for good transmission conditions, an alternative syndrome based decoder is presented. The reduction of complexity is realized by two different approaches, the syndrome zero sequence deactivation and the path metric equalization. The two approaches enable an easy adaptation of the decoding complexity for different transmission conditions, which results in a trade-off between decoding complexity and error correction performance.

Learning-induced Dependence of Neuronal Activity in Primary Motor Cortex on Motor Task Condition.

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Cai, X; Shimansky, Y; He, Jiping

2005-01-01

A brain-computer interface (BCI) system such as a cortically controlled robotic arm must have a capacity of adjusting its function to a specific environmental condition. We studied this capacity in non-human primates based on chronic multi-electrode recording from the primary motor cortex of a monkey during the animal's performance of a center-out 3D reaching task and adaptation to external force perturbations. The main condition-related feature of motor cortical activity observed before the onset of force perturbation was a phasic raise of activity immediately before the perturbation onset. This feature was observed during a series of perturbation trials, but were absent under no perturbations. After adaptation has been completed, it usually was taking the subject only one trial to recognize a change in the condition to switch the neuronal activity accordingly. These condition-dependent features of neuronal activity can be used by a BCI for recognizing a change in the environmental condition and making corresponding adjustments, which requires that the BCI-based control system possess such advanced properties of the neural motor control system as capacity to learn and adapt.

Decoding Xing-Ling codes

DEFF Research Database (Denmark)

Nielsen, Rasmus Refslund

2002-01-01

This paper describes an efficient decoding method for a recent construction of good linear codes as well as an extension to the construction. Furthermore, asymptotic properties and list decoding of the codes are discussed.......This paper describes an efficient decoding method for a recent construction of good linear codes as well as an extension to the construction. Furthermore, asymptotic properties and list decoding of the codes are discussed....

Task-dependent engagements of the primary visual cortex during kinesthetic and visual motor imagery.

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Mizuguchi, Nobuaki; Nakamura, Maiko; Kanosue, Kazuyuki

2017-01-01

Motor imagery can be divided into kinesthetic and visual aspects. In the present study, we investigated excitability in the corticospinal tract and primary visual cortex (V1) during kinesthetic and visual motor imagery. To accomplish this, we measured motor evoked potentials (MEPs) and probability of phosphene occurrence during the two types of motor imageries of finger tapping. The MEPs and phosphenes were induced by transcranial magnetic stimulation to the primary motor cortex and V1, respectively. The amplitudes of MEPs and probability of phosphene occurrence during motor imagery were normalized based on the values obtained at rest. Corticospinal excitability increased during both kinesthetic and visual motor imagery, while excitability in V1 was increased only during visual motor imagery. These results imply that modulation of cortical excitability during kinesthetic and visual motor imagery is task dependent. The present finding aids in the understanding of the neural mechanisms underlying motor imagery and provides useful information for the use of motor imagery in rehabilitation or motor imagery training. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Adaptive decoding of convolutional codes

Directory of Open Access Journals (Sweden)

K. Hueske

2007-06-01

Full Text Available Convolutional codes, which are frequently used as error correction codes in digital transmission systems, are generally decoded using the Viterbi Decoder. On the one hand the Viterbi Decoder is an optimum maximum likelihood decoder, i.e. the most probable transmitted code sequence is obtained. On the other hand the mathematical complexity of the algorithm only depends on the used code, not on the number of transmission errors. To reduce the complexity of the decoding process for good transmission conditions, an alternative syndrome based decoder is presented. The reduction of complexity is realized by two different approaches, the syndrome zero sequence deactivation and the path metric equalization. The two approaches enable an easy adaptation of the decoding complexity for different transmission conditions, which results in a trade-off between decoding complexity and error correction performance.

Parietal neural prosthetic control of a computer cursor in a graphical-user-interface task

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Revechkis, Boris; Aflalo, Tyson NS; Kellis, Spencer; Pouratian, Nader; Andersen, Richard A.

2014-12-01

Objective. To date, the majority of Brain-Machine Interfaces have been used to perform simple tasks with sequences of individual targets in otherwise blank environments. In this study we developed a more practical and clinically relevant task that approximated modern computers and graphical user interfaces (GUIs). This task could be problematic given the known sensitivity of areas typically used for BMIs to visual stimuli, eye movements, decision-making, and attentional control. Consequently, we sought to assess the effect of a complex, GUI-like task on the quality of neural decoding. Approach. A male rhesus macaque monkey was implanted with two 96-channel electrode arrays in area 5d of the superior parietal lobule. The animal was trained to perform a GUI-like ‘Face in a Crowd’ task on a computer screen that required selecting one cued, icon-like, face image from a group of alternatives (the ‘Crowd’) using a neurally controlled cursor. We assessed whether the crowd affected decodes of intended cursor movements by comparing it to a ‘Crowd Off’ condition in which only the matching target appeared without alternatives. We also examined if training a neural decoder with the Crowd On rather than Off had any effect on subsequent decode quality. Main results. Despite the additional demands of working with the Crowd On, the animal was able to robustly perform the task under Brain Control. The presence of the crowd did not itself affect decode quality. Training the decoder with the Crowd On relative to Off had no negative influence on subsequent decoding performance. Additionally, the subject was able to gaze around freely without influencing cursor position. Significance. Our results demonstrate that area 5d recordings can be used for decoding in a complex, GUI-like task with free gaze. Thus, this area is a promising source of signals for neural prosthetics that utilize computing devices with GUI interfaces, e.g. personal computers, mobile devices, and tablet

Parietal neural prosthetic control of a computer cursor in a graphical-user-interface task.

Science.gov (United States)

Revechkis, Boris; Aflalo, Tyson N S; Kellis, Spencer; Pouratian, Nader; Andersen, Richard A

2014-12-01

To date, the majority of Brain-Machine Interfaces have been used to perform simple tasks with sequences of individual targets in otherwise blank environments. In this study we developed a more practical and clinically relevant task that approximated modern computers and graphical user interfaces (GUIs). This task could be problematic given the known sensitivity of areas typically used for BMIs to visual stimuli, eye movements, decision-making, and attentional control. Consequently, we sought to assess the effect of a complex, GUI-like task on the quality of neural decoding. A male rhesus macaque monkey was implanted with two 96-channel electrode arrays in area 5d of the superior parietal lobule. The animal was trained to perform a GUI-like 'Face in a Crowd' task on a computer screen that required selecting one cued, icon-like, face image from a group of alternatives (the 'Crowd') using a neurally controlled cursor. We assessed whether the crowd affected decodes of intended cursor movements by comparing it to a 'Crowd Off' condition in which only the matching target appeared without alternatives. We also examined if training a neural decoder with the Crowd On rather than Off had any effect on subsequent decode quality. Despite the additional demands of working with the Crowd On, the animal was able to robustly perform the task under Brain Control. The presence of the crowd did not itself affect decode quality. Training the decoder with the Crowd On relative to Off had no negative influence on subsequent decoding performance. Additionally, the subject was able to gaze around freely without influencing cursor position. Our results demonstrate that area 5d recordings can be used for decoding in a complex, GUI-like task with free gaze. Thus, this area is a promising source of signals for neural prosthetics that utilize computing devices with GUI interfaces, e.g. personal computers, mobile devices, and tablet computers.

Motor Unit Action Potential Clustering—Theoretical Consideration for Muscle Activation during a Motor Task

Directory of Open Access Journals (Sweden)

Michael J. Asmussen

2018-01-01

Full Text Available During dynamic or sustained isometric contractions, bursts of muscle activity appear in the electromyography (EMG signal. Theoretically, these bursts of activity likely occur because motor units are constrained to fire temporally close to one another and thus the impulses are “clustered” with short delays to elicit bursts of muscle activity. The purpose of this study was to investigate whether a sequence comprised of “clustered” motor unit action potentials (MUAP can explain spectral and amplitude changes of the EMG during a simulated motor task. This question would be difficult to answer experimentally and thus, required a model to study this type of muscle activation pattern. To this end, we modeled two EMG signals, whereby a single MUAP was either convolved with a randomly distributed impulse train (EMG-rand or a “clustered” sequence of impulses (EMG-clust. The clustering occurred in windows lasting 5–100 ms. A final mixed signal of EMG-clust and EMG-rand, with ratios (1:1–1:10, was also modeled. A ratio of 1:1 would indicate that 50% of MUAP were randomly distributed, while 50% of “clustered” MUAP occurred in a given time window (5–100 ms. The results of the model showed that clustering MUAP caused a downshift in the mean power frequency (i.e., ~30 Hz with the largest shift occurring with a cluster window of 10 ms. The mean frequency shift was largest when the ratio of EMG-clust to EMG-rand was high. Further, the clustering of MUAP also caused a substantial increase in the amplitude of the EMG signal. This model potentially explains an activation pattern that changes the EMG spectra during a motor task and thus, a potential activation pattern of muscles observed experimentally. Changes in EMG measurements during fatiguing conditions are typically attributed to slowing of conduction velocity but could, per this model, also result from changes of the clustering of MUAP. From a clinical standpoint, this type of muscle

Motor imagery in Asperger syndrome: testing action simulation by the hand laterality task.

Directory of Open Access Journals (Sweden)

Massimiliano Conson

Full Text Available Asperger syndrome (AS is a neurodevelopmental condition within the Autism Spectrum Disorders (ASD characterized by specific difficulties in social interaction, communication and behavioural control. In recent years, it has been suggested that ASD is related to a dysfunction of action simulation processes, but studies employing imitation or action observation tasks provided mixed results. Here, we addressed action simulation processes in adolescents with AS by means of a motor imagery task, the classical hand laterality task (to decide whether a rotated hand image is left or right; mental rotation of letters was also evaluated. As a specific marker of action simulation in hand rotation, we assessed the so-called biomechanical effect, that is the advantage for judging hand pictures showing physically comfortable versus physically awkward positions. We found the biomechanical effect in typically-developing participants but not in participants with AS. Overall performance on both hand laterality and letter rotation tasks, instead, did not differ in the two groups. These findings demonstrated a specific alteration of motor imagery skills in AS. We suggest that impaired mental simulation and imitation of goal-less movements in ASD could be related to shared cognitive mechanisms.

Task-specific recruitment of motor units for vibration damping.

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Wakeling, James M; Liphardt, Anna-Maria

2006-01-01

Vibrations occur within the soft tissues of the lower extremities due to the heel-strike impact during walking. Increases in muscle activity in the lower extremities result in increased damping to reduce this vibration. The myoelectric intensity spectra were compared using principal component analysis from the tibialis anterior and lateral gastrocnemius of 40 subjects walking with different shoe conditions. The soft insert condition resulted in a significant, simultaneous increase in muscle activity with a shift to higher myoelectric frequencies in the period 0-60 ms after heel-strike which is the period when the greater vibration damping occurred. These increases in myoelectric frequency match the spectral patterns which indicate increases in recruitment of faster motor units. It is concluded that fast motor units are recruited during the task of damping the soft-tissue resonance that occurs following heel-strike.

Decoding ensemble activity from neurophysiological recordings in the temporal cortex.

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Kreiman, Gabriel

2011-01-01

We study subjects with pharmacologically intractable epilepsy who undergo semi-chronic implantation of electrodes for clinical purposes. We record physiological activity from tens to more than one hundred electrodes implanted in different parts of neocortex. These recordings provide higher spatial and temporal resolution than non-invasive measures of human brain activity. Here we discuss our efforts to develop hardware and algorithms to interact with the human brain by decoding ensemble activity in single trials. We focus our discussion on decoding visual information during a variety of visual object recognition tasks but the same technologies and algorithms can also be directly applied to other cognitive phenomena.

Decoding Facial Expressions: A New Test with Decoding Norms.

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Leathers, Dale G.; Emigh, Ted H.

1980-01-01

Describes the development and testing of a new facial meaning sensitivity test designed to determine how specialized are the meanings that can be decoded from facial expressions. Demonstrates the use of the test to measure a receiver's current level of skill in decoding facial expressions. (JMF)

More than meets the eye: the role of self-identity in decoding complex emotional states.

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Stevenson, Michael T; Soto, José A; Adams, Reginald B

2012-10-01

Folk wisdom asserts that "the eyes are the window to the soul," and empirical science corroborates a prominent role for the eyes in the communication of emotion. Herein we examine variation in the ability to "read" the eyes of others as a function of social group membership, employing a widely used emotional state decoding task: "Reading the Mind in Eyes." This task has documented impaired emotional state decoding across racial groups, with cross-race performance on par with that previously reported as a function of autism spectrum disorders. The present study extended this work by examining the moderating role of social identity in such impairments. For college students more highly identified with their university, cross-race performance differences were not found for judgments of "same-school" eyes but remained for "rival-school" eyes. These findings suggest that impaired emotional state decoding across groups may thus be more amenable to remediation than previously realized.

Effects of practice schedule and task specificity on the adaptive process of motor learning.

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Barros, João Augusto de Camargo; Tani, Go; Corrêa, Umberto Cesar

2017-10-01

This study investigated the effects of practice schedule and task specificity based on the perspective of adaptive process of motor learning. For this purpose, tasks with temporal and force control learning requirements were manipulated in experiments 1 and 2, respectively. Specifically, the task consisted of touching with the dominant hand the three sequential targets with specific movement time or force for each touch. Participants were children (N=120), both boys and girls, with an average age of 11.2years (SD=1.0). The design in both experiments involved four practice groups (constant, random, constant-random, and random-constant) and two phases (stabilisation and adaptation). The dependent variables included measures related to the task goal (accuracy and variability of error of the overall movement and force patterns) and movement pattern (macro- and microstructures). Results revealed a similar error of the overall patterns for all groups in both experiments and that they adapted themselves differently in terms of the macro- and microstructures of movement patterns. The study concludes that the effects of practice schedules on the adaptive process of motor learning were both general and specific to the task. That is, they were general to the task goal performance and specific regarding the movement pattern. Copyright © 2017 Elsevier B.V. All rights reserved.

Measurement of functional task difficulty during motor learning: What level of difficulty corresponds to the optimal challenge point?

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Akizuki, Kazunori; Ohashi, Yukari

2015-10-01

The relationship between task difficulty and learning benefit was examined, as was the measurability of task difficulty. Participants were required to learn a postural control task on an unstable surface at one of four different task difficulty levels. Results from the retention test showed an inverted-U relationship between task difficulty during acquisition and motor learning. The second-highest level of task difficulty was the most effective for motor learning, while learning was delayed at the most and least difficult levels. Additionally, the results indicate that salivary α-amylase and the performance dimension of the National Aeronautics and Space Administration-Task Load Index (NASA-TLX) are useful indices of task difficulty. Our findings suggested that instructors may be able to adjust task difficulty based on salivary α-amylase and the performance dimension of the NASA-TLX to enhance learning. Copyright © 2015 Elsevier B.V. All rights reserved.

How Major Depressive Disorder affects the ability to decode multimodal dynamic emotional stimuli

Directory of Open Access Journals (Sweden)

FILOMENA SCIBELLI

2016-09-01

Full Text Available Most studies investigating the processing of emotions in depressed patients reported impairments in the decoding of negative emotions. However, these studies adopted static stimuli (mostly stereotypical facial expressions corresponding to basic emotions which do not reflect the way people experience emotions in everyday life. For this reason, this work proposes to investigate the decoding of emotional expressions in patients affected by Recurrent Major Depressive Disorder (RMDDs using dynamic audio/video stimuli. RMDDs’ performance is compared with the performance of patients with Adjustment Disorder with Depressed Mood (ADs and healthy (HCs subjects. The experiments involve 27 RMDDs (16 with acute depression - RMDD-A, and 11 in a compensation phase - RMDD-C, 16 ADs and 16 HCs. The ability to decode emotional expressions is assessed through an emotion recognition task based on short audio (without video, video (without audio and audio/video clips. The results show that AD patients are significantly less accurate than HCs in decoding fear, anger, happiness, surprise and sadness. RMDD-As with acute depression are significantly less accurate than HCs in decoding happiness, sadness and surprise. Finally, no significant differences were found between HCs and RMDD-Cs in a compensation phase. The different communication channels and the types of emotion play a significant role in limiting the decoding accuracy.

Forced Sequence Sequential Decoding

DEFF Research Database (Denmark)

Jensen, Ole Riis; Paaske, Erik

1998-01-01

We describe a new concatenated decoding scheme based on iterations between an inner sequentially decoded convolutional code of rate R=1/4 and memory M=23, and block interleaved outer Reed-Solomon (RS) codes with nonuniform profile. With this scheme decoding with good performance is possible as low...... as Eb/N0=0.6 dB, which is about 1.25 dB below the signal-to-noise ratio (SNR) that marks the cutoff rate for the full system. Accounting for about 0.45 dB due to the outer codes, sequential decoding takes place at about 1.7 dB below the SNR cutoff rate for the convolutional code. This is possible since...... the iteration process provides the sequential decoders with side information that allows a smaller average load and minimizes the probability of computational overflow. Analytical results for the probability that the first RS word is decoded after C computations are presented. These results are supported...

A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control

Science.gov (United States)

Li, Lin; Brockmeier, Austin J.; Choi, John S.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

2014-01-01

Brain machine interfaces (BMIs) have attracted intense attention as a promising technology for directly interfacing computers or prostheses with the brain's motor and sensory areas, thereby bypassing the body. The availability of multiscale neural recordings including spike trains and local field potentials (LFPs) brings potential opportunities to enhance computational modeling by enriching the characterization of the neural system state. However, heterogeneity on data type (spike timing versus continuous amplitude signals) and spatiotemporal scale complicates the model integration of multiscale neural activity. In this paper, we propose a tensor-product-kernel-based framework to integrate the multiscale activity and exploit the complementary information available in multiscale neural activity. This provides a common mathematical framework for incorporating signals from different domains. The approach is applied to the problem of neural decoding and control. For neural decoding, the framework is able to identify the nonlinear functional relationship between the multiscale neural responses and the stimuli using general purpose kernel adaptive filtering. In a sensory stimulation experiment, the tensor-product-kernel decoder outperforms decoders that use only a single neural data type. In addition, an adaptive inverse controller for delivering electrical microstimulation patterns that utilizes the tensor-product kernel achieves promising results in emulating the responses to natural stimulation. PMID:24829569

Cognitive-motor dual-task interference modulates mediolateral dynamic stability during gait in post-stroke individuals.

Science.gov (United States)

Tisserand, R; Armand, S; Allali, G; Schnider, A; Baillieul, S

2018-04-01

Gait asymmetry and dynamic balance impairments observed in post-stroke individuals increase their risk of fall. Moreover, walking while performing a cognitive task (i.e. dual-task) disturbs the control of balance in post-stroke individuals. Here we investigated the mediolateral dynamic stability in twenty-two community-dwelling participants (12 post-strokes and 10 healthy controls) while walking in single-task (normal gait) and four different dual-tasks (cognitive-motor interference). Positions of the extrapolated center of mass and mediolateral widths of both margin of stability and base of support were extracted from 35 marker trajectories. Post-stroke participants presented larger margin of stability and base of support than controls during single-task (both p dual-task was found between groups. In post-stroke participants, dual-task induced slight modification of the mediolateral stability strategy, as the margin of stability was not different between the two limbs at foot-strike, and significantly reduced the performance in every cognitive task. Post-stroke participants increased their dynamic stability in the frontal plane in single-task by extending their base of support and mainly relying on their non-paretic limb. Under cognitive-motor interference (dual-task), post-stroke participants prioritized dynamic stability over cognitive performance to ensure a safe locomotion. Thus, rehabilitation programs should consider both dynamic balance and dual-task training, even at a chronic delay following stroke, to reduce the risk of fall in post-stroke individuals. Copyright © 2018 Elsevier B.V. All rights reserved.

The Influence of Parkinson’s Disease Motor Symptom Asymmetry on Hand Performance: An Examination of the Grooved Pegboard Task

Directory of Open Access Journals (Sweden)

Sara M. Scharoun

2015-01-01

Full Text Available This study examined the influence of motor symptom asymmetry in Parkinson’s disease (PD on Grooved Pegboard (GP performance in right-handed participants. The Unified Parkinson’s Disease Rating Scale was used to assess motor symptoms and separate participants with PD into two groups (right-arm affected, left-arm affected for comparison with a group of healthy older adults. Participants completed the place and replace GP tasks two times with both hands. Laterality quotients were computed to quantify performance differences between the two hands. Comparisons among the three groups indicated that when the nonpreferred hand is affected by PD motor symptoms, superior preferred hand performance (as seen in healthy older adults is further exaggerated in tasks that require precision (i.e., place task. Regardless of the task, when the preferred hand is affected, there is an evident shift to superior left-hand performance, which may inevitably manifest as a switch in hand preference. Results add to the discussion of the relationship between handedness and motor symptom asymmetry in PD.

Location versus task relevance: The impact of differing internal focus of attention instructions on motor performance.

Science.gov (United States)

Pelleck, Valerie; Passmore, Steven R

2017-05-01

Impaired performance while executing a motor task is attributed to a disruption of normal automatic processes when an internal focus of attention is used. What remains unclear is whether the specificity of internally focused task instructions may impact task performance. The present study assessed the implications of changing the attentional focus of novice and skilled golfers by measuring behavioural, neurophysiological and kinematic changes during a golf putting task. Over six blocks of ten putting trials each, attention was directed either externally (towards the target) or internally in one of two ways: 1) proximal (keeping the elbows extended and the hands gripping the putter); or 2) distal (keeping the weight evenly distributed between both legs) to the critical elements of the task. Results provided evidence that when novice participants use an internal focus of attention more closely associated with task performance that their: 1) execution; 2) accuracy; 3) variability of surface electromyography (sEMG) activity; and 4) kinematics of the putter movement are all adversely affected. Skilled golfers are much more resilient to changes in attentional focus, while all participants interpret a distal internal focus of attention similar to an external focus. All participants produced decreased activity in the muscle (tibialis anterior) associated with the distal (less task relevant) focus of attention even when the "internal" focus was on the lower extremity. Our results provide evidence that the skill level of the participant and the distance of the internal focus of attention from the key elements of a motor skill directly impact the execution, muscle activity, and movement kinematics associated with skilled motor task performance. Copyright © 2017 Elsevier B.V. All rights reserved.

Functional BOLD MRI: comparison of different field strengths in a motor task

International Nuclear Information System (INIS)

Meindl, T.; Born, C.; Britsch, S.; Reiser, M.; Schoenberg, S.

2008-01-01

The purpose was to evaluate the benefit of an increased field strength for functional magnetic resonance imaging in a motor task. Six right-handed volunteers were scanned at 1.5 T and 3.0 T using a motor task. Each experiment consisted of two runs with four activation blocks, each with right- and left-hand tapping. Analysis was done using BrainVoyagerQX registered . Differences between both field strengths concerning signal to noise (SNR), blood oxygen level-dependent (BOLD) signal change, functional sensitivity and BOLD contrast to noise (CNR) were tested using a paired t test. Delineation of activations and artifacts were graded by two independent readers. Results were further validated by means of a phantom study. The sensorimotor and premotor cortex, the supplementary motor area, subcortical and cerebellar structures were activated at each field strength. Additional activations of the right premotor cortex and right superior temporal gyrus were found at 3.0 T. Signal-to-noise, percentage of BOLD signal change, BOLD CNR and functional sensitivity improved at 3.0 T by a factor of up to 2.4. Functional imaging at 3.0 T results in detection of additional activated areas, increased SNR, BOLD signal change, functional sensitivity and BOLD CNR. (orig.)

Remote one-qubit information concentration and decoding of operator quantum error-correction codes

International Nuclear Information System (INIS)

Hsu Liyi

2007-01-01

We propose the general scheme of remote one-qubit information concentration. To achieve the task, the Bell-correlated mixed states are exploited. In addition, the nonremote one-qubit information concentration is equivalent to the decoding of the quantum error-correction code. Here we propose how to decode the stabilizer codes. In particular, the proposed scheme can be used for the operator quantum error-correction codes. The encoded state can be recreated on the errorless qubit, regardless how many bit-flip errors and phase-flip errors have occurred

Functional near infrared spectroscopy of the sensory and motor brain regions with simultaneous kinematic and EMG monitoring during motor tasks

OpenAIRE

Sukal-Moulton, Theresa; de Campos, Ana Carolina; Stanley, Christopher J; Damiano, Diane L

2014-01-01

There are several advantages that functional near-infrared spectroscopy (fNIRS) presents in the study of the neural control of human movement. It is relatively flexible with respect to participant positioning and allows for some head movements during tasks. Additionally, it is inexpensive, light weight, and portable, with very few contraindications to its use. This presents a unique opportunity to study functional brain activity during motor tasks in individuals who are typically developing, ...

The effects of bromazepam over the central and frontal areas during a motor task: an EEG study

Directory of Open Access Journals (Sweden)

Suzete Fortunato

2015-04-01

Full Text Available The present study investigates the influence of bromazepam while executing a motor task. Specifically, we intend to analyze the changes in alpha absolute power under two experimental conditions, bromazepam and placebo. We also included analyses of theta and beta frequencies. We collected electroencephalographic data before, during, and after motor task execution. We used a Two Way ANOVA to investigate the condition (PL × Br6 mg and moment (pre and post variables for the following electrodes: Fp1, Fp2, F7, F3, Fz, F4, F8, C3, CZ and C4. We found a main effect for condition on the electrodes FP1, F7, F3, Fz, F4, C3 and CZ, for alpha and beta bands. For beta band we also found a main effect for condition on the electrodes Fp2, F8 and C4; for theta band we identified a main effect for condition on C3, Cz and C4 electrodes. This finding suggests that the motor task did not have any influence on the electrocortical activity in alpha, and that the existing modifications were a consequence due merely to the drug use. Despite its anxiolytic and sedative action, bromazepam did not show any significant changes when the individuals executed a finger extension motor task.

Forced Sequence Sequential Decoding

DEFF Research Database (Denmark)

Jensen, Ole Riis

In this thesis we describe a new concatenated decoding scheme based on iterations between an inner sequentially decoded convolutional code of rate R=1/4 and memory M=23, and block interleaved outer Reed-Solomon codes with non-uniform profile. With this scheme decoding with good performance...... is possible as low as Eb/No=0.6 dB, which is about 1.7 dB below the signal-to-noise ratio that marks the cut-off rate for the convolutional code. This is possible since the iteration process provides the sequential decoders with side information that allows a smaller average load and minimizes the probability...... of computational overflow. Analytical results for the probability that the first Reed-Solomon word is decoded after C computations are presented. This is supported by simulation results that are also extended to other parameters....

Mild cognitive impairment: loss of linguistic task-induced changes in motor cortex excitability.

Science.gov (United States)

Bracco, L; Giovannelli, F; Bessi, V; Borgheresi, A; Di Tullio, A; Sorbi, S; Zaccara, G; Cincotta, M

2009-03-10

In amnestic mild cognitive impairment (aMCI), functional neuronal connectivity may be altered, as suggested by quantitative EEG and neuroimaging data. In young healthy humans, the execution of linguistic tasks modifies the excitability of the hand area of the dominant primary motor cortex (M1(hand)), as tested by transcranial magnetic stimulation (TMS). We used TMS to investigate functional connectivity between language-related cortical areas and M1(hand) in aMCI. Ten elderly women with aMCI and 10 age-matched women were recruited. All participants were right handed and underwent a neuropsychological evaluation. In the first TMS experiment, participants performed three different tasks: reading aloud, viewing of non-letter strings (baseline), and nonverbal oral movements. The second experiment included the baseline condition and three visual searching/matching tasks using letters, geometric shapes, or digits as target stimuli. In controls, motor evoked potentials (MEP) elicited by suprathreshold TMS of the left M1(hand) were significantly larger during reading aloud (170% baseline) than during nonverbal oral movements, whereas no difference was seen for right M1(hand) stimulation. Similarly, MEP elicited by left M1(hand) stimulation during letter and shape searching/matching tasks were significantly larger compared to digit task. In contrast, linguistic task performance did not produce any significant MEP modulation in patients with aMCI, although neuropsychological evaluation showed normal language abilities. Findings suggest that functional connectivity between the language-related brain regions and the dominant M1(hand) may be altered in amnestic mild cognitive impairment. Follow-up studies will reveal whether transcranial magnetic stimulation application during linguistic tasks may contribute to characterize the risk of conversion to Alzheimer disease.

Motor Preparation Disrupts Proactive Control in the Stop Signal Task

Directory of Open Access Journals (Sweden)

Wuyi Wang

2018-05-01

Full Text Available In a study of the stop signal task (SST we employed Bayesian modeling to compute the estimated likelihood of stop signal or P(Stop trial by trial and identified regional processes of conflict anticipation and response slowing. A higher P(Stop is associated with prolonged go trial reaction time (goRT—a form of sequential effect—and reflects proactive control of motor response. However, some individuals do not demonstrate a sequential effect despite similar go and stop success (SS rates. We posited that motor preparation may disrupt proactive control more in certain individuals than others. Specifically, the time interval between trial and go signal onset—the fore-period (FP—varies across trials and a longer FP is associated with a higher level of motor preparation and shorter goRT. Greater motor preparatory activities may disrupt proactive control. To test this hypothesis, we compared brain activations and Granger causal connectivities of 81 adults who demonstrated a sequential effect (SEQ and 35 who did not (nSEQ. SEQ and nSEQ did not differ in regional activations to conflict anticipation, motor preparation, goRT slowing or goRT speeding. In contrast, SEQ and nSEQ demonstrated different patterns of Granger causal connectivities. P(Stop and FP activations shared reciprocal influence in SEQ but FP activities Granger caused P(Stop activities unidirectionally in nSEQ, and FP activities Granger caused goRT speeding activities in nSEQ but not SEQ. These findings support the hypothesis that motor preparation disrupts proactive control in nSEQ and provide direct neural evidence for interactive go and stop processes.

Self-Control of Task Difficulty During Early Practice Promotes Motor Skill Learning.

Science.gov (United States)

Andrieux, Mathieu; Boutin, Arnaud; Thon, Bernard

2016-01-01

This study was designed to determine whether the effect of self-control of task difficulty on motor learning is a function of the period of self-control administration. In a complex anticipation-coincidence task that required participants to intercept 3 targets with a virtual racquet, the task difficulty was either self-controlled or imposed to the participants in the two phases of the acquisition session. First, the results confirmed the beneficial effects of self-control over fully prescribed conditions. Second, the authors also demonstrated that a partial self-control of task difficulty better promotes learning than does a complete self-controlled procedure. Overall, the results revealed that these benefits are increased when this choice is allowed during early practice. The findings are discussed in terms of theoretical and applied perspectives.

On Decoding Interleaved Chinese Remainder Codes

DEFF Research Database (Denmark)

Li, Wenhui; Sidorenko, Vladimir; Nielsen, Johan Sebastian Rosenkilde

2013-01-01

We model the decoding of Interleaved Chinese Remainder codes as that of finding a short vector in a Z-lattice. Using the LLL algorithm, we obtain an efficient decoding algorithm, correcting errors beyond the unique decoding bound and having nearly linear complexity. The algorithm can fail...... with a probability dependent on the number of errors, and we give an upper bound for this. Simulation results indicate that the bound is close to the truth. We apply the proposed decoding algorithm for decoding a single CR code using the idea of “Power” decoding, suggested for Reed-Solomon codes. A combination...... of these two methods can be used to decode low-rate Interleaved Chinese Remainder codes....

Unsupervised learning of facial emotion decoding skills.

Science.gov (United States)

Huelle, Jan O; Sack, Benjamin; Broer, Katja; Komlewa, Irina; Anders, Silke

2014-01-01

Research on the mechanisms underlying human facial emotion recognition has long focussed on genetically determined neural algorithms and often neglected the question of how these algorithms might be tuned by social learning. Here we show that facial emotion decoding skills can be significantly and sustainably improved by practice without an external teaching signal. Participants saw video clips of dynamic facial expressions of five different women and were asked to decide which of four possible emotions (anger, disgust, fear, and sadness) was shown in each clip. Although no external information about the correctness of the participant's response or the sender's true affective state was provided, participants showed a significant increase of facial emotion recognition accuracy both within and across two training sessions two days to several weeks apart. We discuss several similarities and differences between the unsupervised improvement of facial decoding skills observed in the current study, unsupervised perceptual learning of simple stimuli described in previous studies and practice effects often observed in cognitive tasks.

Reaction Decoder Tool (RDT): extracting features from chemical reactions.

Science.gov (United States)

Rahman, Syed Asad; Torrance, Gilliean; Baldacci, Lorenzo; Martínez Cuesta, Sergio; Fenninger, Franz; Gopal, Nimish; Choudhary, Saket; May, John W; Holliday, Gemma L; Steinbeck, Christoph; Thornton, Janet M

2016-07-01

Extracting chemical features like Atom-Atom Mapping (AAM), Bond Changes (BCs) and Reaction Centres from biochemical reactions helps us understand the chemical composition of enzymatic reactions. Reaction Decoder is a robust command line tool, which performs this task with high accuracy. It supports standard chemical input/output exchange formats i.e. RXN/SMILES, computes AAM, highlights BCs and creates images of the mapped reaction. This aids in the analysis of metabolic pathways and the ability to perform comparative studies of chemical reactions based on these features. This software is implemented in Java, supported on Windows, Linux and Mac OSX, and freely available at https://github.com/asad/ReactionDecoder : asad@ebi.ac.uk or s9asad@gmail.com. © The Author 2016. Published by Oxford University Press.

Bayer image parallel decoding based on GPU

Science.gov (United States)

Hu, Rihui; Xu, Zhiyong; Wei, Yuxing; Sun, Shaohua

2012-11-01

In the photoelectrical tracking system, Bayer image is decompressed in traditional method, which is CPU-based. However, it is too slow when the images become large, for example, 2K×2K×16bit. In order to accelerate the Bayer image decoding, this paper introduces a parallel speedup method for NVIDA's Graphics Processor Unit (GPU) which supports CUDA architecture. The decoding procedure can be divided into three parts: the first is serial part, the second is task-parallelism part, and the last is data-parallelism part including inverse quantization, inverse discrete wavelet transform (IDWT) as well as image post-processing part. For reducing the execution time, the task-parallelism part is optimized by OpenMP techniques. The data-parallelism part could advance its efficiency through executing on the GPU as CUDA parallel program. The optimization techniques include instruction optimization, shared memory access optimization, the access memory coalesced optimization and texture memory optimization. In particular, it can significantly speed up the IDWT by rewriting the 2D (Tow-dimensional) serial IDWT into 1D parallel IDWT. Through experimenting with 1K×1K×16bit Bayer image, data-parallelism part is 10 more times faster than CPU-based implementation. Finally, a CPU+GPU heterogeneous decompression system was designed. The experimental result shows that it could achieve 3 to 5 times speed increase compared to the CPU serial method.

Temporary Nerve Block at Selected Digits Revealed Hand Motor Deficits in Grasping Tasks

Directory of Open Access Journals (Sweden)

Aude Carteron

2016-11-01

Full Text Available Peripheral sensory feedback plays a crucial role in ensuring correct motor execution throughout hand grasp control. Previous studies utilized local anesthesia to deprive somatosensory feedback in the digits or hand, observations included sensorimotor deficits at both corticospinal and peripheral levels. However, the questions of how the disturbed and intact sensory input integrate and interact with each other to assist the motor program execution, and whether the motor coordination based on motor output variability between affected and non-affected elements (e.g., digits becomes interfered by the local sensory deficiency, have not been answered. The current study aims to investigate the effect of peripheral deafferentation through digital nerve blocks at selective digits on motor performance and motor coordination in grasp control. Our results suggested that the absence of somatosensory information induced motor deficits in hand grasp control, as evidenced by reduced maximal force production ability in both local and non-local digits, impairment of force and moment control during object lift and hold, and attenuated motor synergies in stabilizing task performance variables, namely the tangential force and moment of force. These findings implied that individual sensory input is shared across all the digits and the disturbed signal from local sensory channel(s has a more comprehensive impact on the process of the motor output execution in the sensorimotor integration process. Additionally, a feedback control mechanism with a sensation-based component resides in the formation process for the motor covariation structure.

User Experience May be Producing Greater Heart Rate Variability than Motor Imagery Related Control Tasks during the User-System Adaptation in Brain-Computer Interfaces

Science.gov (United States)

Alonso-Valerdi, Luz M.; Gutiérrez-Begovich, David A.; Argüello-García, Janet; Sepulveda, Francisco; Ramírez-Mendoza, Ricardo A.

2016-01-01

Brain-computer interface (BCI) is technology that is developing fast, but it remains inaccurate, unreliable and slow due to the difficulty to obtain precise information from the brain. Consequently, the involvement of other biosignals to decode the user control tasks has risen in importance. A traditional way to operate a BCI system is via motor imagery (MI) tasks. As imaginary movements activate similar cortical structures and vegetative mechanisms as a voluntary movement does, heart rate variability (HRV) has been proposed as a parameter to improve the detection of MI related control tasks. However, HR is very susceptible to body needs and environmental demands, and as BCI systems require high levels of attention, perceptual processing and mental workload, it is important to assess the practical effectiveness of HRV. The present study aimed to determine if brain and heart electrical signals (HRV) are modulated by MI activity used to control a BCI system, or if HRV is modulated by the user perceptions and responses that result from the operation of a BCI system (i.e., user experience). For this purpose, a database of 11 participants who were exposed to eight different situations was used. The sensory-cognitive load (intake and rejection tasks) was controlled in those situations. Two electrophysiological signals were utilized: electroencephalography and electrocardiography. From those biosignals, event-related (de-)synchronization maps and event-related HR changes were respectively estimated. The maps and the HR changes were cross-correlated in order to verify if both biosignals were modulated due to MI activity. The results suggest that HR varies according to the experience undergone by the user in a BCI working environment, and not because of the MI activity used to operate the system. PMID:27458384

[Neuronal activity of monkey dorso-lateral premotor cortex during tasks of figure recognition guided motor sequence vs memorized spatial motor sequence].

Science.gov (United States)

Chen, Y C; Huang, F D; Chen, N H; Shou, J Y; Wu, L

1998-04-01

In the last 2-3 decades the role of the premotor cortex (PM) of monkey in memorized spatial sequential (MSS) movements has been amply investigated. However, it is as yet not known whether PM participates in the movement sequence behaviour guided by recognition of visual figures (i.e. the figure-recognition sequence, FRS). In the present work three monkeys were trained to perform both FRS and MSS tasks. Postmortem examination showed that 202 cells were in the dorso-lateral premotor cortex. Among 111 cells recorded during the two tasks, more than 50% changed their activity during the cue periods in either task. During the response period, the ratios of cells with changes of firing rate in both FRS and MSS were high and roughly equal to each other, while during the image period, the proportion in the FRS (83.7%) was significantly higher than that in the MSS (66.7%). Comparison of neuronal activities during same motor sequence of two different tasks showed that during the image periods PM neuronal activities were more closely related to the FRS task, while during the cue periods no difference could be found. Analysis of cell responses showed that the neurons with longer latency were much more in MSS than in FRS in either cue or image period. The present results indicate that the premotor cortex participates in FRS motor sequence as well as in MSS and suggest that the dorso-lateral PM represents another subarea in function shared by both FRS and MSS tasks. However, in view of the differences of PM neuronal responses in cue or image periods of FRS and MSS tasks, it seems likely that neural networks involved in FRS and MSS tasks are different.

Microprocessor controller for stepping motors

International Nuclear Information System (INIS)

Strait, B.G.; Thuot, M.E.

1977-01-01

A new concept for digital computer control of multiple stepping motors which operate in a severe electromagnetic pulse environment is presented. The motors position mirrors in the beam-alignment system of a 100-kJ CO 2 laser. An asynchronous communications channel of a computer is used to send coded messages, containing the motor address and stepping-command information, to the stepping-motor controller in a bit serial format over a fiber-optics communications link. The addressed controller responds by transmitting to the computer its address and other motor information, thus confirming the received message. Each controller is capable of controlling three stepping motors. The controller contains the fiber-optics interface, a microprocessor, and the stepping-motor driven circuits. The microprocessor program, which resides in an EPROM, decodes the received messages, transmits responses, performs the stepping-motor sequence logic, maintains motor-position information, and monitors the motor's reference switch. For multiple stepping-motor application, the controllers are connected in a daisy chain providing control of many motors from one asynchronous communications channel of the computer

List Decoding of Algebraic Codes

DEFF Research Database (Denmark)

Nielsen, Johan Sebastian Rosenkilde

We investigate three paradigms for polynomial-time decoding of Reed–Solomon codes beyond half the minimum distance: the Guruswami–Sudan algorithm, Power decoding and the Wu algorithm. The main results concern shaping the computational core of all three methods to a problem solvable by module...... Hermitian codes using Guruswami–Sudan or Power decoding faster than previously known, and we show how to Wu list decode binary Goppa codes....... to solve such using module minimisation, or using our new Demand–Driven algorithm which is also based on module minimisation. The decoding paradigms are all derived and analysed in a self-contained manner, often in new ways or examined in greater depth than previously. Among a number of new results, we...

Decoding Delay Controlled Completion Time Reduction in Instantly Decodable Network Coding

KAUST Repository

Douik, Ahmed

2016-06-27

For several years, the completion time and the decoding delay problems in Instantly Decodable Network Coding (IDNC) were considered separately and were thought to act completely against each other. Recently, some works aimed to balance the effects of these two important IDNC metrics but none of them studied a further optimization of one by controlling the other. This paper investigates the effect of controlling the decoding delay to reduce the completion time below its currently best-known solution in both perfect and imperfect feedback with persistent erasure channels. To solve the problem, the decodingdelay- dependent expressions of the users’ and overall completion times are derived in the complete feedback scenario. Although using such expressions to find the optimal overall completion time is NP-hard, the paper proposes two novel heuristics that minimizes the probability of increasing the maximum of these decoding-delay-dependent completion time expressions after each transmission through a layered control of their decoding delays. Afterward, the paper extends the study to the imperfect feedback scenario in which uncertainties at the sender affects its ability to anticipate accurately the decoding delay increase at each user. The paper formulates the problem in such environment and derives the expression of the minimum increase in the completion time. Simulation results show the performance of the proposed solutions and suggest that both heuristics achieves a lower mean completion time as compared to the best-known heuristics for the completion time reduction in perfect and imperfect feedback. The gap in performance becomes more significant as the erasure of the channel increases.

Decoding Delay Controlled Completion Time Reduction in Instantly Decodable Network Coding

KAUST Repository

Douik, Ahmed S.; Sorour, Sameh; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

2016-01-01

For several years, the completion time and the decoding delay problems in Instantly Decodable Network Coding (IDNC) were considered separately and were thought to act completely against each other. Recently, some works aimed to balance the effects of these two important IDNC metrics but none of them studied a further optimization of one by controlling the other. This paper investigates the effect of controlling the decoding delay to reduce the completion time below its currently best-known solution in both perfect and imperfect feedback with persistent erasure channels. To solve the problem, the decodingdelay- dependent expressions of the users’ and overall completion times are derived in the complete feedback scenario. Although using such expressions to find the optimal overall completion time is NP-hard, the paper proposes two novel heuristics that minimizes the probability of increasing the maximum of these decoding-delay-dependent completion time expressions after each transmission through a layered control of their decoding delays. Afterward, the paper extends the study to the imperfect feedback scenario in which uncertainties at the sender affects its ability to anticipate accurately the decoding delay increase at each user. The paper formulates the problem in such environment and derives the expression of the minimum increase in the completion time. Simulation results show the performance of the proposed solutions and suggest that both heuristics achieves a lower mean completion time as compared to the best-known heuristics for the completion time reduction in perfect and imperfect feedback. The gap in performance becomes more significant as the erasure of the channel increases.

Concurrent word generation and motor performance: further evidence for language-motor interaction.

Directory of Open Access Journals (Sweden)

Amy D Rodriguez

Full Text Available Embodied/modality-specific theories of semantic memory propose that sensorimotor representations play an important role in perception and action. A large body of evidence supports the notion that concepts involving human motor action (i.e., semantic-motor representations are processed in both language and motor regions of the brain. However, most studies have focused on perceptual tasks, leaving unanswered questions about language-motor interaction during production tasks. Thus, we investigated the effects of shared semantic-motor representations on concurrent language and motor production tasks in healthy young adults, manipulating the semantic task (motor-related vs. nonmotor-related words and the motor task (i.e., standing still and finger-tapping. In Experiment 1 (n = 20, we demonstrated that motor-related word generation was sufficient to affect postural control. In Experiment 2 (n = 40, we demonstrated that motor-related word generation was sufficient to facilitate word generation and finger tapping. We conclude that engaging semantic-motor representations can have a reciprocal influence on motor and language production. Our study provides additional support for functional language-motor interaction, as well as embodied/modality-specific theories.

Motor Learning of a Bimanual Task in Children with Unilateral Cerebral Palsy

Science.gov (United States)

Hung, Ya-Ching; Gordon, Andrew M.

2013-01-01

Children with unilateral cerebral palsy (CP) have been shown to improve their motor performance with sufficient practice. However, little is known about how they learn goal-oriented tasks. In the current study, 21 children with unilateral CP (age 4-10 years old) and 21 age-matched typically developed children (TDC) practiced a simple bimanual…

Object-directed imitation in autism spectrum disorder is differentially influenced by motoric task complexity, but not social contextual cues.

Science.gov (United States)

Chetcuti, Lacey; Hudry, Kristelle; Grant, Megan; Vivanti, Giacomo

2017-11-01

We examined the role of social motivation and motor execution factors in object-directed imitation difficulties in autism spectrum disorder. A series of to-be-imitated actions was presented to 35 children with autism spectrum disorder and 20 typically developing children on an Apple ® iPad ® by a socially responsive or aloof model, under conditions of low and high motor demand. There were no differences in imitation performance (i.e. the number of actions reproduced within a fixed sequence), for either group, in response to a model who acted socially responsive or aloof. Children with autism spectrum disorder imitated the high motor demand task more poorly than the low motor demand task, while imitation performance for typically developing children was equivalent across the low and high motor demand conditions. Furthermore, imitative performance in the autism spectrum disorder group was unrelated to social reciprocity, though positively associated with fine motor coordination. These results suggest that difficulties in object-directed imitation in autism spectrum disorder are the result of motor execution difficulties, not reduced social motivation.

Decoding task-based attentional modulation during face categorization.

Science.gov (United States)

Chiu, Yu-Chin; Esterman, Michael; Han, Yuefeng; Rosen, Heather; Yantis, Steven

2011-05-01

Attention is a neurocognitive mechanism that selects task-relevant sensory or mnemonic information to achieve current behavioral goals. Attentional modulation of cortical activity has been observed when attention is directed to specific locations, features, or objects. However, little is known about how high-level categorization task set modulates perceptual representations. In the current study, observers categorized faces by gender (male vs. female) or race (Asian vs. White). Each face was perceptually ambiguous in both dimensions, such that categorization of one dimension demanded selective attention to task-relevant information within the face. We used multivoxel pattern classification to show that task-specific modulations evoke reliably distinct spatial patterns of activity within three face-selective cortical regions (right fusiform face area and bilateral occipital face areas). This result suggests that patterns of activity in these regions reflect not only stimulus-specific (i.e., faces vs. houses) responses but also task-specific (i.e., race vs. gender) attentional modulation. Furthermore, exploratory whole-brain multivoxel pattern classification (using a searchlight procedure) revealed a network of dorsal fronto-parietal regions (left middle frontal gyrus and left inferior and superior parietal lobule) that also exhibit distinct patterns for the two task sets, suggesting that these regions may represent abstract goals during high-level categorization tasks.

Improved decoding for a concatenated coding system

DEFF Research Database (Denmark)

Paaske, Erik

1990-01-01

The concatenated coding system recommended by CCSDS (Consultative Committee for Space Data Systems) uses an outer (255,233) Reed-Solomon (RS) code based on 8-b symbols, followed by the block interleaver and an inner rate 1/2 convolutional code with memory 6. Viterbi decoding is assumed. Two new...... decoding procedures based on repeated decoding trials and exchange of information between the two decoders and the deinterleaver are proposed. In the first one, where the improvement is 0.3-0.4 dB, only the RS decoder performs repeated trials. In the second one, where the improvement is 0.5-0.6 dB, both...... decoders perform repeated decoding trials and decoding information is exchanged between them...

Neuroplasticity & Motor Learning

DEFF Research Database (Denmark)

Jensen, Jesper Lundbye

Practice of a new motor task is usually associated with an improvement in performance. Indeed, if we stop practicing and return the next day to the same task, we find that our performance has been maintained and may even be better than it was at the start of the first day. This improvement...... is a measure of our ability to form and store a motor memory of the task. However, the initial memory of the task is labile and may be subject to interference. During and following motor learning plastic changes occur within the central nervous system. On one hand these changes are driven by motor practice......, on the other hand the changes underlie the formation of motor memory and the retention of improved motor performance. During motor learning changes may occur at many different levels within the central nervous system dependent on the type of task and training. Here, we demonstrate different studies from our...

Motor-commands decoding using peripheral nerve signals: a review

Science.gov (United States)

Hong, Keum-Shik; Aziz, Nida; Ghafoor, Usman

2018-06-01

During the last few decades, substantial scientific and technological efforts have been focused on the development of neuroprostheses. The major emphasis has been on techniques for connecting the human nervous system with a robotic prosthesis via natural-feeling interfaces. The peripheral nerves provide access to highly processed and segregated neural command signals from the brain that can in principle be used to determine user intent and control muscles. If these signals could be used, they might allow near-natural and intuitive control of prosthetic limbs with multiple degrees of freedom. This review summarizes the history of neuroprosthetic interfaces and their ability to record from and stimulate peripheral nerves. We also discuss the types of interfaces available and their applications, the kinds of peripheral nerve signals that are used, and the algorithms used to decode them. Finally, we explore the prospects for future development in this area.

Multimodal decoding and congruent sensory information enhance reaching performance in subjects with cervical spinal cord injury

Directory of Open Access Journals (Sweden)

Elaine Anna Corbett

2014-05-01

Full Text Available Cervical spinal cord injury (SCI paralyzes muscles of the hand and arm, making it difficult to perform activities of daily living. Restoring the ability to reach can dramatically improve quality of life for people with cervical SCI. Any reaching system requires a user interface to decode parameters of an intended reach, such as trajectory and target. A challenge in developing such decoders is that often few physiological signals related to the intended reach remain under voluntary control, especially in patients with high cervical injuries. Furthermore, the decoding problem changes when the user is controlling the motion of their limb, as opposed to an external device. The purpose of this study was to investigate the benefits of combining disparate signal sources to control reach in people with a range of impairments, and to consider the effect of two feedback approaches. Subjects with cervical SCI performed robot-assisted reaching, controlling trajectories with either shoulder electromyograms (EMGs or EMGs combined with gaze. We then evaluated how reaching performance was influenced by task-related sensory feedback, testing the EMG-only decoder in two conditions. The first involved moving the arm with the robot, providing congruent sensory feedback through their remaining sense of proprioception. In the second, the subjects moved the robot without the arm attached, as in applications that control external devices. We found that the multimodal decoding algorithm worked well for all subjects, enabling them to perform straight, accurate reaches. The inclusion of gaze information, used to estimate target location, was especially important for the most impaired subjects. In the absence of gaze information, congruent sensory feedback improved performance. These results highlight the importance of proprioceptive feedback, and suggest that multi-modal decoders are likely to be most beneficial for highly impaired subjects and in tasks where such

Decoding Pigeon Behavior Outcomes Using Functional Connections among Local Field Potentials.

Science.gov (United States)

Chen, Yan; Liu, Xinyu; Li, Shan; Wan, Hong

2018-01-01

Recent studies indicate that the local field potential (LFP) carries information about an animal's behavior, but issues regarding whether there are any relationships between the LFP functional networks and behavior tasks as well as whether it is possible to employ LFP network features to decode the behavioral outcome in a single trial remain unresolved. In this study, we developed a network-based method to decode the behavioral outcomes in pigeons by using the functional connectivity strength values among LFPs recorded from the nidopallium caudolaterale (NCL). In our method, the functional connectivity strengths were first computed based on the synchronization likelihood. Second, the strength values were unwrapped into row vectors and their dimensions were then reduced by principal component analysis. Finally, the behavioral outcomes in single trials were decoded using leave-one-out combined with the k -nearest neighbor method. The results showed that the LFP functional network based on the gamma-band was related to the goal-directed behavior of pigeons. Moreover, the accuracy of the network features (74 ± 8%) was significantly higher than that of the power features (61 ± 12%). The proposed method provides a powerful tool for decoding animal behavior outcomes using a neural functional network.

Effects of short-term training on behavioral learning and skill acquisition during intraoral fine motor task

DEFF Research Database (Denmark)

Kumar, Abhishek; Grigoriadis, Joannis; Trulsson, Mats

2015-01-01

Sensory information from the orofacial mechanoreceptors are used by the nervous system to optimize the positioning of food, determine the force levels, and force vectors involved in biting of food morsels. Moreover, practice resulting from repetition could be a key to learning and acquiring a motor...... movements. Thirty healthy volunteers were asked to intraorally manipulate and split a chocolate candy, into two equal halves. The participants performed three series (with ten 10 trials) of the task before and after a short-term (approximately 30min) training. The accuracy of the split and vertical jaw...... task induces behavior learning, skill acquisition and optimization of jaw movements in terms of better performance and reduction in the duration of jaw movements, during the task. The finding of the present study provides insights on into how humans learn oral motor behaviors or the kind of adaptation...

Decoding Decoders: Finding Optimal Representation Spaces for Unsupervised Similarity Tasks

OpenAIRE

Zhelezniak, Vitalii; Busbridge, Dan; Shen, April; Smith, Samuel L.; Hammerla, Nils Y.

2018-01-01

Experimental evidence indicates that simple models outperform complex deep networks on many unsupervised similarity tasks. We provide a simple yet rigorous explanation for this behaviour by introducing the concept of an optimal representation space, in which semantically close symbols are mapped to representations that are close under a similarity measure induced by the model's objective function. In addition, we present a straightforward procedure that, without any retraining or architectura...

Serotonin and Dopamine Gene Variation and Theory of Mind Decoding Accuracy in Major Depression: A Preliminary Investigation.

Science.gov (United States)

Zahavi, Arielle Y; Sabbagh, Mark A; Washburn, Dustin; Mazurka, Raegan; Bagby, R Michael; Strauss, John; Kennedy, James L; Ravindran, Arun; Harkness, Kate L

2016-01-01

Theory of mind-the ability to decode and reason about others' mental states-is a universal human skill and forms the basis of social cognition. Theory of mind accuracy is impaired in clinical conditions evidencing social impairment, including major depressive disorder. The current study is a preliminary investigation of the association of polymorphisms of the serotonin transporter (SLC6A4), dopamine transporter (DAT1), dopamine receptor D4 (DRD4), and catechol-O-methyl transferase (COMT) genes with theory of mind decoding in a sample of adults with major depression. Ninety-six young adults (38 depressed, 58 non-depressed) completed the 'Reading the Mind in the Eyes task' and a non-mentalistic control task. Genetic associations were only found for the depressed group. Specifically, superior accuracy in decoding mental states of a positive valence was seen in those homozygous for the long allele of the serotonin transporter gene, 9-allele carriers of DAT1, and long-allele carriers of DRD4. In contrast, superior accuracy in decoding mental states of a negative valence was seen in short-allele carriers of the serotonin transporter gene and 10/10 homozygotes of DAT1. Results are discussed in terms of their implications for integrating social cognitive and neurobiological models of etiology in major depression.

Serotonin and Dopamine Gene Variation and Theory of Mind Decoding Accuracy in Major Depression: A Preliminary Investigation.

Directory of Open Access Journals (Sweden)

Arielle Y Zahavi

Full Text Available Theory of mind-the ability to decode and reason about others' mental states-is a universal human skill and forms the basis of social cognition. Theory of mind accuracy is impaired in clinical conditions evidencing social impairment, including major depressive disorder. The current study is a preliminary investigation of the association of polymorphisms of the serotonin transporter (SLC6A4, dopamine transporter (DAT1, dopamine receptor D4 (DRD4, and catechol-O-methyl transferase (COMT genes with theory of mind decoding in a sample of adults with major depression. Ninety-six young adults (38 depressed, 58 non-depressed completed the 'Reading the Mind in the Eyes task' and a non-mentalistic control task. Genetic associations were only found for the depressed group. Specifically, superior accuracy in decoding mental states of a positive valence was seen in those homozygous for the long allele of the serotonin transporter gene, 9-allele carriers of DAT1, and long-allele carriers of DRD4. In contrast, superior accuracy in decoding mental states of a negative valence was seen in short-allele carriers of the serotonin transporter gene and 10/10 homozygotes of DAT1. Results are discussed in terms of their implications for integrating social cognitive and neurobiological models of etiology in major depression.

A functional model and simulation of spinal motor pools and intrafascicular recordings of motoneuron activity in peripheral nerve

Directory of Open Access Journals (Sweden)

Mohamed N. Abdelghani

2014-11-01

Full Text Available Decoding motor intent from recorded neural signals is essential for the development of effective neural-controlled prostheses. To facilitate the development of online decoding algorithms we have developed a software platform to simulate neural motor signals recorded with peripheral nerve electrodes, such as longitudinal intrafascicular electrodes (LIFEs. The simulator uses stored motor intent signals to drive a pool of simulated motoneurons with various spike shapes, recruitment characteristics, and firing frequencies. Each electrode records a weighted sum of a subset of simulated motoneuron activity patterns. As designed, the simulator facilitates development of a suite of test scenarios that would not be possible with actual data sets because, unlike with actual recordings, in the simulator the individual contributions to the simulated composite recordings are known and can be methodically varied across a set of simulation runs. In this manner, the simulation tool is suitable for iterative development of real-time decoding algorithms prior to definitive evaluation in amputee subjects with implanted electrodes. The simulation tool was used to produce data sets that demonstrate its ability to capture some features of neural recordings that pose challenges for decoding algorithms.

Evaluation of Functional Correlation of Task-Specific Muscle Synergies with Motor Performance in Patients Poststroke

Directory of Open Access Journals (Sweden)

Si Li

2017-07-01

Full Text Available The central nervous system produces movements by activating specifically programmed muscle synergies that are also altered with injuries in the brain, such as stroke. In this study, we hypothesize that there exists a positive correlation between task-specific muscle synergy and motor functions at joint and task levels in patients following stroke. The purpose here is to define and evaluate neurophysiological metrics based on task-specific muscle synergy for assessing motor functions in patients. A patient group of 10 subjects suffering from stroke and a control group of nine age-matched healthy subjects were recruited to participate in this study. Electromyography (EMG signals and movement kinematics were recorded in patients and control subjects while performing arm reaching tasks. Muscle synergies of individual patients were extracted off-line from EMG records of each patient, and a baseline pattern of muscle synergy was obtained from the pooled EMG data of all nine control subjects. Peak velocities and movement durations of each reaching movement were computed from measured kinematics. Similarity indices of matching components to those of the baseline synergy were defined by synergy vectors and time profiles, respectively, as well as by a combined similarity of vector and time profile. Results showed that pathological synergies of patients were altered from the characteristics of baseline synergy with missing components, or varied vector patterns and time profiles. The kinematic performance measured by peak velocities and movement durations was significantly poorer for the patient group than the control group. In patients, all three similarity indices were found to correlate significantly to the kinematics of movements for the reaching tasks. The correlation to the Fugl-Meyer score of arm was the highest with the vector index, the lowest with the time profile index, and in between with the combined index. These findings illustrate that the

Brief periods of NREM sleep do not promote early offline gains but subsequent on-task performance in motor skill learning.

Science.gov (United States)

Maier, Jonathan G; Piosczyk, Hannah; Holz, Johannes; Landmann, Nina; Deschler, Christoph; Frase, Lukas; Kuhn, Marion; Klöppel, Stefan; Spiegelhalder, Kai; Sterr, Annette; Riemann, Dieter; Feige, Bernd; Voderholzer, Ulrich; Nissen, Christoph

2017-11-01

Sleep modulates motor learning, but its detailed impact on performance curves remains to be fully characterized. This study aimed to further determine the impact of brief daytime periods of NREM sleep on 'offline' (task discontinuation after initial training) and 'on-task' (performance within the test session) changes in motor skill performance (finger tapping task). In a mixed design (combined parallel group and repeated measures) sleep laboratory study (n=17 'active' wake vs. sleep, n=19 'passive' wake vs. sleep), performance curves were assessed prior to and after a 90min period containing either sleep, active or passive wakefulness. We observed a highly significant, but state- (that is, sleep/wake)-independent early offline gain and improved on-task performance after sleep in comparison to wakefulness. Exploratory curve fitting suggested that the observed sleep effect most likely emerged from an interaction of training-induced improvement and detrimental 'time-on-task' processes, such as fatigue. Our results indicate that brief periods of NREM sleep do not promote early offline gains but subsequent on-task performance in motor skill learning. Copyright © 2017 Elsevier Inc. All rights reserved.

Using the Hand Laterality Judgement Task to assess motor imagery : a study of practice effects in repeated measurements

NARCIS (Netherlands)

Boonstra, Anne M.; de Vries, Sjoerd J.; Veenstra, Evelien; Tepper, Marga; Feenstra, Wya; Otten, Egbert

The aim of this study was to determine whether there is a practice effect on the Hand Laterality Judgement Task (HLJT). The HLJT task is a mental rotation task that can be used to assess motor imagery ability in stroke patients. Thirty-three healthy individuals performed the HLJT and two control

Using the Hand Laterality Judgement Task to Assess Motor Imagery: A Study of Practice Effects in Repeated Measurements

Science.gov (United States)

Boonstra, Anne M.; de Vries, Sjoerd J.; Veenstra, Evelien; Tepper, Marga; Feenstra, Wya; Otten, Egbert

2012-01-01

The aim of this study was to determine whether there is a practice effect on the Hand Laterality Judgement Task (HLJT). The HLJT task is a mental rotation task that can be used to assess motor imagery ability in stroke patients. Thirty-three healthy individuals performed the HLJT and two control tasks twice at a 3-week interval. Differences in the…

Mapping of MPEG-4 decoding on a flexible architecture platform

Science.gov (United States)

van der Tol, Erik B.; Jaspers, Egbert G.

2001-12-01

In the field of consumer electronics, the advent of new features such as Internet, games, video conferencing, and mobile communication has triggered the convergence of television and computers technologies. This requires a generic media-processing platform that enables simultaneous execution of very diverse tasks such as high-throughput stream-oriented data processing and highly data-dependent irregular processing with complex control flows. As a representative application, this paper presents the mapping of a Main Visual profile MPEG-4 for High-Definition (HD) video onto a flexible architecture platform. A stepwise approach is taken, going from the decoder application toward an implementation proposal. First, the application is decomposed into separate tasks with self-contained functionality, clear interfaces, and distinct characteristics. Next, a hardware-software partitioning is derived by analyzing the characteristics of each task such as the amount of inherent parallelism, the throughput requirements, the complexity of control processing, and the reuse potential over different applications and different systems. Finally, a feasible implementation is proposed that includes amongst others a very-long-instruction-word (VLIW) media processor, one or more RISC processors, and some dedicated processors. The mapping study of the MPEG-4 decoder proves the flexibility and extensibility of the media-processing platform. This platform enables an effective HW/SW co-design yielding a high performance density.

Deep learning with convolutional neural networks for EEG decoding and visualization

Science.gov (United States)

Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio

2017-01-01

Abstract Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end‐to‐end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end‐to‐end EEG analysis, but a better understanding of how to design and train ConvNets for end‐to‐end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task‐related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG‐based brain mapping. Hum Brain Mapp 38:5391–5420, 2017. © 2017 Wiley Periodicals, Inc. PMID:28782865

Can stereotype threat affect motor performance in the absence of explicit monitoring processes? Evidence using a strength task.

Science.gov (United States)

Chalabaev, Aïna; Brisswalter, Jeanick; Radel, Rémi; Coombes, Stephen A; Easthope, Christopher; Clément-Guillotin, Corentin

2013-04-01

Previous evidence shows that stereotype threat impairs complex motor skills through increased conscious monitoring of task performance. Given that one-step motor skills may not be susceptible to these processes, we examined whether performance on a simple strength task may be reduced under stereotype threat. Forty females and males performed maximum voluntary contractions under stereotypical or nullified-stereotype conditions. Results showed that the velocity of force production within the first milliseconds of the contraction decreased in females when the negative stereotype was induced, whereas maximal force did not change. In males, the stereotype induction only increased maximal force. These findings suggest that stereotype threat may impair motor skills in the absence of explicit monitoring processes, by influencing the planning stage of force production.

Hybrid EEG-fNIRS-Based Eight-Command Decoding for BCI: Application to Quadcopter Control.

Science.gov (United States)

Khan, Muhammad Jawad; Hong, Keum-Shik

2017-01-01

In this paper, a hybrid electroencephalography-functional near-infrared spectroscopy (EEG-fNIRS) scheme to decode eight active brain commands from the frontal brain region for brain-computer interface is presented. A total of eight commands are decoded by fNIRS, as positioned on the prefrontal cortex, and by EEG, around the frontal, parietal, and visual cortices. Mental arithmetic, mental counting, mental rotation, and word formation tasks are decoded with fNIRS, in which the selected features for classification and command generation are the peak, minimum, and mean ΔHbO values within a 2-s moving window. In the case of EEG, two eyeblinks, three eyeblinks, and eye movement in the up/down and left/right directions are used for four-command generation. The features in this case are the number of peaks and the mean of the EEG signal during 1 s window. We tested the generated commands on a quadcopter in an open space. An average accuracy of 75.6% was achieved with fNIRS for four-command decoding and 86% with EEG for another four-command decoding. The testing results show the possibility of controlling a quadcopter online and in real-time using eight commands from the prefrontal and frontal cortices via the proposed hybrid EEG-fNIRS interface.

EEG-based decoding of error-related brain activity in a real-world driving task

Science.gov (United States)

Zhang, H.; Chavarriaga, R.; Khaliliardali, Z.; Gheorghe, L.; Iturrate, I.; Millán, J. d. R.

2015-12-01

Objectives. Recent studies have started to explore the implementation of brain-computer interfaces (BCI) as part of driving assistant systems. The current study presents an EEG-based BCI that decodes error-related brain activity. Such information can be used, e.g., to predict driver’s intended turning direction before reaching road intersections. Approach. We executed experiments in a car simulator (N = 22) and a real car (N = 8). While subject was driving, a directional cue was shown before reaching an intersection, and we classified the presence or not of an error-related potentials from EEG to infer whether the cued direction coincided with the subject’s intention. In this protocol, the directional cue can correspond to an estimation of the driving direction provided by a driving assistance system. We analyzed ERPs elicited during normal driving and evaluated the classification performance in both offline and online tests. Results. An average classification accuracy of 0.698 ± 0.065 was obtained in offline experiments in the car simulator, while tests in the real car yielded a performance of 0.682 ± 0.059. The results were significantly higher than chance level for all cases. Online experiments led to equivalent performances in both simulated and real car driving experiments. These results support the feasibility of decoding these signals to help estimating whether the driver’s intention coincides with the advice provided by the driving assistant in a real car. Significance. The study demonstrates a BCI system in real-world driving, extending the work from previous simulated studies. As far as we know, this is the first online study in real car decoding driver’s error-related brain activity. Given the encouraging results, the paradigm could be further improved by using more sophisticated machine learning approaches and possibly be combined with applications in intelligent vehicles.

Localised task-dependent motor-unit recruitment in the masseter.

Science.gov (United States)

Schindler, H J; Hellmann, D; Giannakopoulos, N N; Eiglsperger, U; van Dijk, J P; Lapatki, B G

2014-07-01

Localised motor-unit (MU) recruitment in the masseter was analysed in this study. We investigated whether differential activation behaviour, which has already been reported for distant masseter regions, can also be detected in small muscle subvolumes at the level of single MUs. Two bipolar fine-wire electrodes and an intra-oral 3D bite-force transmitter were used to record intra-muscular electromyograms (EMG) resulting from controlled bite-forces of 10 healthy human subjects (mean age 24.1 ± 1.2 years). Two-hundred and seventeen decomposed MUs were organised into localised MU task groups with different (P < 0.001) force-direction-specific behaviour. Proportions of MUs involved in one, two, three or four examined tasks were 46%, 31%, 18% and 5%, respectively. This study provides evidence of the ability of the neuromuscular system to modify the mechanical output of small masseter subvolumes by differential control of adjacent MUs belonging to distinct task groups. Localised differential activation behaviour of the masseter may be the crucial factor enabling highly flexible and efficient adjustment of the muscle activity in response to complex local biomechanical needs, for example, continually varying bite-forces during the demanding masticatory process. © 2014 John Wiley & Sons Ltd.

Unsupervised learning of facial emotion decoding skills

Directory of Open Access Journals (Sweden)

Jan Oliver Huelle

2014-02-01

Full Text Available Research on the mechanisms underlying human facial emotion recognition has long focussed on genetically determined neural algorithms and often neglected the question of how these algorithms might be tuned by social learning. Here we show that facial emotion decoding skills can be significantly and sustainably improved by practise without an external teaching signal. Participants saw video clips of dynamic facial expressions of five different women and were asked to decide which of four possible emotions (anger, disgust, fear and sadness was shown in each clip. Although no external information about the correctness of the participant’s response or the sender’s true affective state was provided, participants showed a significant increase of facial emotion recognition accuracy both within and across two training sessions two days to several weeks apart. We discuss several similarities and differences between the unsupervised improvement of facial decoding skills observed in the current study, unsupervised perceptual learning of simple stimuli described in previous studies and practise effects often observed in cognitive tasks.

A small, portable, battery-powered brain-computer interface system for motor rehabilitation.

Science.gov (United States)

McCrimmon, Colin M; Ming Wang; Silva Lopes, Lucas; Wang, Po T; Karimi-Bidhendi, Alireza; Liu, Charles Y; Heydari, Payam; Nenadic, Zoran; Do, An H

2016-08-01

Motor rehabilitation using brain-computer interface (BCI) systems may facilitate functional recovery in individuals after stroke or spinal cord injury. Nevertheless, these systems are typically ill-suited for widespread adoption due to their size, cost, and complexity. In this paper, a small, portable, and extremely cost-efficient (microcontroller and touchscreen. The system's performance was tested using a movement-related BCI task in 3 able-bodied subjects with minimal previous BCI experience. Specifically, subjects were instructed to alternate between relaxing and dorsiflexing their right foot, while their EEG was acquired and analyzed in real-time by the BCI system to decode their underlying movement state. The EEG signals acquired by the custom amplifier array were similar to those acquired by a commercial amplifier (maximum correlation coefficient ρ=0.85). During real-time BCI operation, the average correlation between instructional cues and decoded BCI states across all subjects (ρ=0.70) was comparable to that of full-size BCI systems. Small, portable, and inexpensive BCI systems such as the one reported here may promote a widespread adoption of BCI-based movement rehabilitation devices in stroke and spinal cord injury populations.

Fast decoders for qudit topological codes

International Nuclear Information System (INIS)

Anwar, Hussain; Brown, Benjamin J; Campbell, Earl T; Browne, Dan E

2014-01-01

Qudit toric codes are a natural higher-dimensional generalization of the well-studied qubit toric code. However, standard methods for error correction of the qubit toric code are not applicable to them. Novel decoders are needed. In this paper we introduce two renormalization group decoders for qudit codes and analyse their error correction thresholds and efficiency. The first decoder is a generalization of a ‘hard-decisions’ decoder due to Bravyi and Haah (arXiv:1112.3252). We modify this decoder to overcome a percolation effect which limits its threshold performance for many-level quantum systems. The second decoder is a generalization of a ‘soft-decisions’ decoder due to Poulin and Duclos-Cianci (2010 Phys. Rev. Lett. 104 050504), with a small cell size to optimize the efficiency of implementation in the high dimensional case. In each case, we estimate thresholds for the uncorrelated bit-flip error model and provide a comparative analysis of the performance of both these approaches to error correction of qudit toric codes. (paper)

Neuroimaging of decoding and language comprehension in young very low birth weight (VLBW) adolescents: Indications for compensatory mechanisms.

Science.gov (United States)

van Ettinger-Veenstra, Helene; Widén, Carin; Engström, Maria; Karlsson, Thomas; Leijon, Ingemar; Nelson, Nina

2017-01-01

In preterm children with very low birth weight (VLBW ≤ 1500 g), reading problems are often observed. Reading comprehension is dependent on word decoding and language comprehension. We investigated neural activation-within brain regions important for reading-related to components of reading comprehension in young VLBW adolescents in direct comparison to normal birth weight (NBW) term-born peers, with the use of functional magnetic resonance imaging (fMRI). We hypothesized that the decoding mechanisms will be affected by VLBW, and expect to see increased neural activity for VLBW which may be modulated by task performance and cognitive ability. The study investigated 13 (11 included in fMRI) young adolescents (ages 12 to 14 years) born preterm with VLBW and in 13 NBW controls (ages 12-14 years) for performance on the Block Design and Vocabulary subtests of the Wechsler Intelligence Scale for Children; and for semantic, orthographic, and phonological processing during an fMRI paradigm. The VLBW group showed increased phonological activation in left inferior frontal gyrus, decreased orthographic activation in right supramarginal gyrus, and decreased semantic activation in left inferior frontal gyrus. Block Design was related to altered right-hemispheric activation, and VLBW showed lower WISC Block Design scores. Left angular gyrus showed activation increase specific for VLBW with high accuracy on the semantic test. Young VLBW adolescents showed no accuracy and reaction time performance differences on our fMRI language tasks, but they did exhibit altered neural activation during these tasks. This altered activation for VLBW was observed as increased activation during phonological decoding, and as mainly decreased activation during orthographic and semantic processing. Correlations of neural activation with accuracy on the semantic fMRI task and with decreased WISC Block Design performance were specific for the VLBW group. Together, results suggest compensatory

Impaired affective prosody decoding in severe alcohol use disorder and Korsakoff syndrome.

Science.gov (United States)

Brion, Mélanie; de Timary, Philippe; Mertens de Wilmars, Serge; Maurage, Pierre

2018-06-01

Recognizing others' emotions is a fundamental social skill, widely impaired in psychiatric populations. These emotional dysfunctions are involved in the development and maintenance of alcohol-related disorders, but their differential intensity across emotions and their modifications during disease evolution remain underexplored. Affective prosody decoding was assessed through a vocalization task using six emotions, among 17 patients with severe alcohol use disorder, 16 Korsakoff syndrome patients (diagnosed following DSM-V criteria) and 19 controls. Significant disturbances in emotional decoding, particularly for negative emotions, were found in alcohol-related disorders. These impairments, identical for both experimental groups, constitute a core deficit in excessive alcohol use. Copyright © 2018 Elsevier B.V. All rights reserved.

Real Time Decoding of Color Symbol for Optical Positioning System

Directory of Open Access Journals (Sweden)

Abdul Waheed Malik

2015-01-01

Full Text Available This paper presents the design and real-time decoding of a color symbol that can be used as a reference marker for optical navigation. The designed symbol has a circular shape and is printed on paper using two distinct colors. This pair of colors is selected based on the highest achievable signal to noise ratio. The symbol is designed to carry eight bit information. Real time decoding of this symbol is performed using a heterogeneous combination of Field Programmable Gate Array (FPGA and a microcontroller. An image sensor having a resolution of 1600 by 1200 pixels is used to capture images of symbols in complex backgrounds. Dynamic image segmentation, component labeling and feature extraction was performed on the FPGA. The region of interest was further computed from the extracted features. Feature data belonging to the symbol was sent from the FPGA to the microcontroller. Image processing tasks are partitioned between the FPGA and microcontroller based on data intensity. Experiments were performed to verify the rotational independence of the symbols. The maximum distance between camera and symbol allowing for correct detection and decoding was analyzed. Experiments were also performed to analyze the number of generated image components and sub-pixel precision versus different light sources and intensities. The proposed hardware architecture can process up to 55 frames per second for accurate detection and decoding of symbols at two Megapixels resolution. The power consumption of the complete system is 342mw.

Efficient Embedded Decoding of Neural Network Language Models in a Machine Translation System.

Science.gov (United States)

Zamora-Martinez, Francisco; Castro-Bleda, Maria Jose

2018-02-22

Neural Network Language Models (NNLMs) are a successful approach to Natural Language Processing tasks, such as Machine Translation. We introduce in this work a Statistical Machine Translation (SMT) system which fully integrates NNLMs in the decoding stage, breaking the traditional approach based on [Formula: see text]-best list rescoring. The neural net models (both language models (LMs) and translation models) are fully coupled in the decoding stage, allowing to more strongly influence the translation quality. Computational issues were solved by using a novel idea based on memorization and smoothing of the softmax constants to avoid their computation, which introduces a trade-off between LM quality and computational cost. These ideas were studied in a machine translation task with different combinations of neural networks used both as translation models and as target LMs, comparing phrase-based and [Formula: see text]-gram-based systems, showing that the integrated approach seems more promising for [Formula: see text]-gram-based systems, even with nonfull-quality NNLMs.

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes. Part 3; The Map and Related Decoding Algirithms

Science.gov (United States)

Lin, Shu; Fossorier, Marc

1998-01-01

In a coded communication system with equiprobable signaling, MLD minimizes the word error probability and delivers the most likely codeword associated with the corresponding received sequence. This decoding has two drawbacks. First, minimization of the word error probability is not equivalent to minimization of the bit error probability. Therefore, MLD becomes suboptimum with respect to the bit error probability. Second, MLD delivers a hard-decision estimate of the received sequence, so that information is lost between the input and output of the ML decoder. This information is important in coded schemes where the decoded sequence is further processed, such as concatenated coding schemes, multi-stage and iterative decoding schemes. In this chapter, we first present a decoding algorithm which both minimizes bit error probability, and provides the corresponding soft information at the output of the decoder. This algorithm is referred to as the MAP (maximum aposteriori probability) decoding algorithm.

Effect of the cognitive-motor dual-task using auditory cue on balance of surviviors with chronic stroke: a pilot study.

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Choi, Wonjae; Lee, GyuChang; Lee, Seungwon

2015-08-01

To investigate the effect of a cognitive-motor dual-task using auditory cues on the balance of patients with chronic stroke. Randomized controlled trial. Inpatient rehabilitation center. Thirty-seven individuals with chronic stroke. The participants were randomly allocated to the dual-task group (n=19) and the single-task group (n=18). The dual-task group performed a cognitive-motor dual-task in which they carried a circular ring from side to side according to a random auditory cue during treadmill walking. The single-task group walked on a treadmill only. All subjects completed 15 min per session, three times per week, for four weeks with conventional rehabilitation five times per week over the four weeks. Before and after intervention, both static and dynamic balance were measured with a force platform and using the Timed Up and Go (TUG) test. The dual-task group showed significant improvement in all variables compared to the single-task group, except for anteroposterior (AP) sway velocity with eyes open and TUG at follow-up: mediolateral (ML) sway velocity with eye open (dual-task group vs. single-task group: 2.11 mm/s vs. 0.38 mm/s), ML sway velocity with eye close (2.91 mm/s vs. 1.35 mm/s), AP sway velocity with eye close (4.84 mm/s vs. 3.12 mm/s). After intervention, all variables showed significant improvement in the dual-task group compared to baseline. The study results suggest that the performance of a cognitive-motor dual-task using auditory cues may influence balance improvements in chronic stroke patients. © The Author(s) 2014.

Toric Codes, Multiplicative Structure and Decoding

DEFF Research Database (Denmark)

Hansen, Johan Peder

2017-01-01

Long linear codes constructed from toric varieties over finite fields, their multiplicative structure and decoding. The main theme is the inherent multiplicative structure on toric codes. The multiplicative structure allows for \\emph{decoding}, resembling the decoding of Reed-Solomon codes and al...

Fast decoding algorithms for geometric coded apertures

International Nuclear Information System (INIS)

Byard, Kevin

2015-01-01

Fast decoding algorithms are described for the class of coded aperture designs known as geometric coded apertures which were introduced by Gourlay and Stephen. When compared to the direct decoding method, the algorithms significantly reduce the number of calculations required when performing the decoding for these apertures and hence speed up the decoding process. Experimental tests confirm the efficacy of these fast algorithms, demonstrating a speed up of approximately two to three orders of magnitude over direct decoding.

Gait disorders in the elderly and dual task gait analysis: a new approach for identifying motor phenotypes.

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Auvinet, Bernard; Touzard, Claude; Montestruc, François; Delafond, Arnaud; Goeb, Vincent

2017-01-31

allowed the identification of 3 motor phenotypes (p < 0.01), without any difference for white matter hyperintensities, but with an increased Scheltens score from the first to the third motor phenotype (p = 0.05). Gait analysis under dual-task conditions in elderly people suffering from gait disorders or memory impairment is of great value in assessing the severity of gait disorders, differentiating between peripheral pathologies and central nervous system pathologies, and identifying motor phenotypes. Correlations between motor phenotypes and brain imaging require further studies.

FPGA implementation of low complexity LDPC iterative decoder

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Verma, Shivani; Sharma, Sanjay

2016-07-01

Low-density parity-check (LDPC) codes, proposed by Gallager, emerged as a class of codes which can yield very good performance on the additive white Gaussian noise channel as well as on the binary symmetric channel. LDPC codes have gained lots of importance due to their capacity achieving property and excellent performance in the noisy channel. Belief propagation (BP) algorithm and its approximations, most notably min-sum, are popular iterative decoding algorithms used for LDPC and turbo codes. The trade-off between the hardware complexity and the decoding throughput is a critical factor in the implementation of the practical decoder. This article presents introduction to LDPC codes and its various decoding algorithms followed by realisation of LDPC decoder by using simplified message passing algorithm and partially parallel decoder architecture. Simplified message passing algorithm has been proposed for trade-off between low decoding complexity and decoder performance. It greatly reduces the routing and check node complexity of the decoder. Partially parallel decoder architecture possesses high speed and reduced complexity. The improved design of the decoder possesses a maximum symbol throughput of 92.95 Mbps and a maximum of 18 decoding iterations. The article presents implementation of 9216 bits, rate-1/2, (3, 6) LDPC decoder on Xilinx XC3D3400A device from Spartan-3A DSP family.

Unimodal Versus Bimodal EEG-fMRI Neurofeedback of a Motor Imagery Task

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Lorraine Perronnet

2017-04-01

Full Text Available Neurofeedback is a promising tool for brain rehabilitation and peak performance training. Neurofeedback approaches usually rely on a single brain imaging modality such as EEG or fMRI. Combining these modalities for neurofeedback training could allow to provide richer information to the subject and could thus enable him/her to achieve faster and more specific self-regulation. Yet unimodal and multimodal neurofeedback have never been compared before. In the present work, we introduce a simultaneous EEG-fMRI experimental protocol in which participants performed a motor-imagery task in unimodal and bimodal NF conditions. With this protocol we were able to compare for the first time the effects of unimodal EEG-neurofeedback and fMRI-neurofeedback versus bimodal EEG-fMRI-neurofeedback by looking both at EEG and fMRI activations. We also propose a new feedback metaphor for bimodal EEG-fMRI-neurofeedback that integrates both EEG and fMRI signal in a single bi-dimensional feedback (a ball moving in 2D. Such a feedback is intended to relieve the cognitive load of the subject by presenting the bimodal neurofeedback task as a single regulation task instead of two. Additionally, this integrated feedback metaphor gives flexibility on defining a bimodal neurofeedback target. Participants were able to regulate activity in their motor regions in all NF conditions. Moreover, motor activations as revealed by offline fMRI analysis were stronger during EEG-fMRI-neurofeedback than during EEG-neurofeedback. This result suggests that EEG-fMRI-neurofeedback could be more specific or more engaging than EEG-neurofeedback. Our results also suggest that during EEG-fMRI-neurofeedback, participants tended to regulate more the modality that was harder to control. Taken together our results shed first light on the specific mechanisms of bimodal EEG-fMRI-neurofeedback and on its added-value as compared to unimodal EEG-neurofeedback and fMRI-neurofeedback.

Effect of task-oriented training and high-variability practice on gross motor performance and activities of daily living in children with spastic diplegia.

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Kwon, Hae-Yeon; Ahn, So-Yoon

2016-10-01

[Purpose] This study investigates how a task-oriented training and high-variability practice program can affect the gross motor performance and activities of daily living for children with spastic diplegia and provides an effective and reliable clinical database for future improvement of motor performances skills. [Subjects and Methods] This study randomly assigned seven children with spastic diplegia to each intervention group including that of a control group, task-oriented training group, and a high-variability practice group. The control group only received neurodevelopmental treatment for 40 minutes, while the other two intervention groups additionally implemented a task-oriented training and high-variability practice program for 8 weeks (twice a week, 60 min per session). To compare intra and inter-relationships of the three intervention groups, this study measured gross motor performance measure (GMPM) and functional independence measure for children (WeeFIM) before and after 8 weeks of training. [Results] There were statistically significant differences in the amount of change before and after the training among the three intervention groups for the gross motor performance measure and functional independence measure. [Conclusion] Applying high-variability practice in a task-oriented training course may be considered an efficient intervention method to improve motor performance skills that can tune to movement necessary for daily livelihood through motor experience and learning of new skills as well as change of tasks learned in a complex environment or similar situations to high-variability practice.

Decreased Modulation of EEG Oscillations in High-Functioning Autism During a Motor Control Task

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Joshua Benjamin Ewen

2016-05-01

Full Text Available Autism spectrum disorders (ASD are thought to result in part from altered cortical excitatory-inhibitory balance; this pathophysiology may impact the generation of oscillations on EEG. We investigated premotor-parietal cortical physiology associated with praxis, which has strong theoretical and empirical associations with ASD symptomatology. 25 children with high-functioning ASD (HFA and 33 controls performed a praxis task involving the pantomiming of tool use, while EEG was recorded. We assessed task-related modulation of signal power in alpha and beta frequency bands. Compared with controls, subjects with HFA showed 27% less left central (motor/premotor beta (18-22 Hz event-related desynchronization (ERD (p = 0.030, as well as 24% less left parietal alpha (7-13 Hz ERD (p = 0.046. Within the HFA group, blunting of central ERD attenuation was associated with impairments in clinical measures of praxis imitation (r = -0.4; p = 0.04 and increased autism severity (r = 0.48; p = 0.016. The modulation of central beta activity is associated, among other things, with motor imagery, which may be necessary for imitation. Impaired imitation has been associated with core features of ASD. Altered modulation of oscillatory activity may be mechanistically involved in those aspects of motor network function that relate to the core symptoms of ASD.

Multisensory integration in non-human primates during a sensory-motor task

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Florian eLanz

2013-11-01

Full Text Available Daily our central nervous system receives inputs via several sensory modalities, processes them and integrates information in order to produce a suitable behaviour. The amazing part is that such a multisensory integration brings all information into a unified percept. An approach to start investigating this property is to show that perception is better and faster when multimodal stimuli are used as compared to unimodal stimuli. This forms the first part of the present study conducted in a non-human primate’s model (n=2 engaged in a detection sensory-motor task where visual and auditory stimuli were displayed individually or simultaneously. The measured parameters were the reaction time (RT between stimulus and onset of arm movement, successes and errors percentages, as well as the evolution as a function of time of these parameters with training. As expected, RTs were shorter when the subjects were exposed to combined stimuli. The gains for both subjects were around 20 and 40 msec, as compared with the auditory and visual stimulus alone, respectively. Moreover the number of correct responses increased in response to bimodal stimuli. We interpreted such multisensory advantage through redundant signal effect which decreases perceptual ambiguity, increases speed of stimulus detection and improves performance accuracy.The second part of the study presents single unit recordings derived from the premotor cortex (PM of the same subjects during the sensory-motor task. Response patterns to sensory/multisensory stimulation are documented and specific type proportions are reported. Characterization of bimodal neurons indicates a mechanism of audio-visual integration possibly through a decrease of inhibition. Nevertheless the neural processing leading to faster motor response from PM as a polysensory association cortical area remains still unclear.

Bounded-Angle Iterative Decoding of LDPC Codes

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Dolinar, Samuel; Andrews, Kenneth; Pollara, Fabrizio; Divsalar, Dariush

2009-01-01

Bounded-angle iterative decoding is a modified version of conventional iterative decoding, conceived as a means of reducing undetected-error rates for short low-density parity-check (LDPC) codes. For a given code, bounded-angle iterative decoding can be implemented by means of a simple modification of the decoder algorithm, without redesigning the code. Bounded-angle iterative decoding is based on a representation of received words and code words as vectors in an n-dimensional Euclidean space (where n is an integer).

Concatenated coding system with iterated sequential inner decoding

DEFF Research Database (Denmark)

Jensen, Ole Riis; Paaske, Erik

1995-01-01

We describe a concatenated coding system with iterated sequential inner decoding. The system uses convolutional codes of very long constraint length and operates on iterations between an inner Fano decoder and an outer Reed-Solomon decoder......We describe a concatenated coding system with iterated sequential inner decoding. The system uses convolutional codes of very long constraint length and operates on iterations between an inner Fano decoder and an outer Reed-Solomon decoder...

Dizzy people perform no worse at a motor imagery task requiring whole body mental rotation; a case-control comparison

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Sarah B Wallwork

2013-06-01

Full Text Available We wanted to find out whether people who suffer from dizziness take longer than people who do not, to perform a motor imagery task that involves implicit whole body rotation. Our prediction was that people in the ‘dizzy’ group would take longer at a left/right neck rotation judgment task but not a left/right hand judgment task, because actually performing the former, but not the latter, would exacerbate their dizziness. Secondly, we predicted that when dizzy participants responded to neck rotation images, responses would be greatest when images were in the upside-down orientation; an orientation with greatest dizzy-provoking potential. To test this idea, we used a case-control comparison design. One hundred and eighteen participants who suffered from dizziness and 118 age, gender, arm pain and neck pain matched controls took part in the study. Participants undertook two motor imagery tasks; a left/right neck rotation judgment task and a left/right hand judgment task. The tasks were completed using the Recognise program; an on-line reaction time task program. Images of neck rotation were shown in four different orientations; 0°, 90°, 180° and 270°. Participants were asked to respond to each ‘neck’ image identifying it as either ‘right neck rotation’ or a ‘left neck rotation’, or for hands, a right or a left hand. Results showed that participants in the ‘dizzy’ group were slower than controls at both tasks (p= 0.015, but this was not related to task (p= 0.498. Similarly, ‘dizzy’ participants were not proportionally worse at images of different orientations (p= 0.878. Our findings suggest impaired performance in dizzy people, an impairment that may be confined to motor imagery or may extend more generally.

Effects of an iPad-Supported Phonics Intervention on Decoding Performance and Time On-Task

Science.gov (United States)

Larabee, Kaitlyn M.; Burns, Matthew K.; McComas, Jennifer J.

2014-01-01

Despite their recent popularity in schools, there is minimal consensus in the educational literature regarding the use of mobile devices for reading intervention. The word box intervention (Joseph "Read Teach" 52:348-356, 1998) has been consistently associated with improvements in student decoding performance. This early efficacy study…

Soft-decision decoding of RS codes

DEFF Research Database (Denmark)

Justesen, Jørn

2005-01-01

By introducing a few simplifying assumptions we derive a simple condition for successful decoding using the Koetter-Vardy algorithm for soft-decision decoding of RS codes. We show that the algorithm has a significant advantage over hard decision decoding when the code rate is low, when two or more...

Decoding small surface codes with feedforward neural networks

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Varsamopoulos, Savvas; Criger, Ben; Bertels, Koen

2018-01-01

Surface codes reach high error thresholds when decoded with known algorithms, but the decoding time will likely exceed the available time budget, especially for near-term implementations. To decrease the decoding time, we reduce the decoding problem to a classification problem that a feedforward neural network can solve. We investigate quantum error correction and fault tolerance at small code distances using neural network-based decoders, demonstrating that the neural network can generalize to inputs that were not provided during training and that they can reach similar or better decoding performance compared to previous algorithms. We conclude by discussing the time required by a feedforward neural network decoder in hardware.

Can short-term oral fine motor training affect precision of task performance and induce cortical plasticity of the jaw muscles?

DEFF Research Database (Denmark)

Hong, Zhang; Kumar, Abhishek; Kothari, Mohit

2016-01-01

The aim was to test the hypothesis that short-term oral sensorimotor training of the jaw muscles would increase the precision of task performance and induce neuroplastic changes in the corticomotor pathways, related to the masseter muscle. Fifteen healthy volunteers performed six series with ten...... trials of an oral sensorimotor task. The task was to manipulate and position a spherical chocolate candy in between the anterior teeth and split it into two equal halves. The precision of the task performance was evaluated by comparing the ratio between the two split halves. A series of "hold......-and-split" tasks was also performed before and after the training. The hold force and split force along with the electromyographic (EMG) activity of jaw muscles were recorded. Motor-evoked potentials and cortical motor maps of the right masseter muscle were evoked by transcranial magnetic stimulation...

Decoding of intended saccade direction in an oculomotor brain-computer interface

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Jia, Nan; Brincat, Scott L.; Salazar-Gómez, Andrés F.; Panko, Mikhail; Guenther, Frank H.; Miller, Earl K.

2017-08-01

Objective. To date, invasive brain-computer interface (BCI) research has largely focused on replacing lost limb functions using signals from the hand/arm areas of motor cortex. However, the oculomotor system may be better suited to BCI applications involving rapid serial selection from spatial targets, such as choosing from a set of possible words displayed on a computer screen in an augmentative and alternative communication (AAC) application. Here we aimed to demonstrate the feasibility of a BCI utilizing the oculomotor system. Approach. We developed a chronic intracortical BCI in monkeys to decode intended saccadic eye movement direction using activity from multiple frontal cortical areas. Main results. Intended saccade direction could be decoded in real time with high accuracy, particularly at contralateral locations. Accurate decoding was evident even at the beginning of the BCI session; no extensive BCI experience was necessary. High-frequency (80-500 Hz) local field potential magnitude provided the best performance, even over spiking activity, thus simplifying future BCI applications. Most of the information came from the frontal and supplementary eye fields, with relatively little contribution from dorsolateral prefrontal cortex. Significance. Our results support the feasibility of high-accuracy intracortical oculomotor BCIs that require little or no practice to operate and may be ideally suited for ‘point and click’ computer operation as used in most current AAC systems.

Hybrid EEG–fNIRS-Based Eight-Command Decoding for BCI: Application to Quadcopter Control

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Khan, Muhammad Jawad; Hong, Keum-Shik

2017-01-01

In this paper, a hybrid electroencephalography–functional near-infrared spectroscopy (EEG–fNIRS) scheme to decode eight active brain commands from the frontal brain region for brain–computer interface is presented. A total of eight commands are decoded by fNIRS, as positioned on the prefrontal cortex, and by EEG, around the frontal, parietal, and visual cortices. Mental arithmetic, mental counting, mental rotation, and word formation tasks are decoded with fNIRS, in which the selected features for classification and command generation are the peak, minimum, and mean ΔHbO values within a 2-s moving window. In the case of EEG, two eyeblinks, three eyeblinks, and eye movement in the up/down and left/right directions are used for four-command generation. The features in this case are the number of peaks and the mean of the EEG signal during 1 s window. We tested the generated commands on a quadcopter in an open space. An average accuracy of 75.6% was achieved with fNIRS for four-command decoding and 86% with EEG for another four-command decoding. The testing results show the possibility of controlling a quadcopter online and in real-time using eight commands from the prefrontal and frontal cortices via the proposed hybrid EEG–fNIRS interface. PMID:28261084

Motor cortex is required for learning but not executing a motor skill

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Kawai, Risa; Markman, Timothy; Poddar, Rajesh; Ko, Raymond; Fantana, Antoniu; Dhawale, Ashesh; Kampff, Adam R.; Ölveczky, Bence P.

2018-01-01

Motor cortex is widely believed to underlie the acquisition and execution of motor skills, yet its contributions to these processes are not fully understood. One reason is that studies on motor skills often conflate motor cortex’s established role in dexterous control with roles in learning and producing task-specific motor sequences. To dissociate these aspects, we developed a motor task for rats that trains spatiotemporally precise movement patterns without requirements for dexterity. Remarkably, motor cortex lesions had no discernible effect on the acquired skills, which were expressed in their distinct pre-lesion forms on the very first day of post-lesion training. Motor cortex lesions prior to training, however, rendered rats unable to acquire the stereotyped motor sequences required for the task. These results suggest a remarkable capacity of subcortical motor circuits to execute learned skills and a previously unappreciated role for motor cortex in ‘tutoring’ these circuits during learning. PMID:25892304

Posture-Motor and Posture-Ideomotor Dual-Tasking: A Putative Marker of Psychomotor Retardation and Depressive Rumination in Patients With Major Depressive Disorder.

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Aftanas, Lyubomir I; Bazanova, Olga M; Novozhilova, Nataliya V

2018-01-01

Background: Recent studies have demonstrated that the assessment of postural performance may be a potentially reliable and objective marker of the psychomotor retardation (PMR) in the major depressive disorder (MDD). One of the important facets of MDD-related PMR is reflected in disrupted central mechanisms of psychomotor control, heavily influenced by compelling maladaptive depressive rumination. In view of this we designed a research paradigm that included sequential execution of simple single-posture task followed by more challenging divided attention posture tasks, involving concurring motor and ideomotor workloads. Another difficulty dimension assumed executing of all the tasks with eyes open (EO) (easy) and closed (EC) (difficult) conditions. We aimed at investigating the interplay between the severity of MDD, depressive rumination, and efficiency of postural performance. Methods: Compared with 24 age- and body mass index-matched healthy controls (HCs), 26 patients with MDD sequentially executed three experimental tasks: (1) single-posture task of maintaining a quiet stance (ST), (2) actual posture-motor dual task (AMT); and (3) mental/imaginary posture-motor dual task (MMT). All the tasks were performed in the EO and the EC conditions. The primary dependent variable was the amount of kinetic energy ( E ) expended for the center of pressure deviations (CoPDs), whereas the absolute divided attention cost index showed energy cost to the dual-tasking vs. the single-posture task according to the formula: Δ E = ( E Dual-task - E Single-task ). Results: The signs of PMR in the MDD group were objectively indexed by deficient posture control in the EC condition along with overall slowness of fine motor and ideomotor activity. Another important and probably more challenging feature of the findings was that the posture deficit manifested in the ST condition was substantially and significantly attenuated in the MMT and AMT performance dual-tasking activity. A multiple

Dual-echo ASL based assessment of motor networks: a feasibility study

Science.gov (United States)

Storti, Silvia Francesca; Boscolo Galazzo, Ilaria; Pizzini, Francesca B.; Menegaz, Gloria

2018-04-01

Objective. Dual-echo arterial spin labeling (DE-ASL) technique has been recently proposed for the simultaneous acquisition of ASL and blood-oxygenation-level-dependent (BOLD)-functional magnetic resonance imaging (fMRI) data. The assessment of this technique in detecting functional connectivity at rest or during motor and motor imagery tasks is still unexplored both per-se and in comparison with conventional methods. The purpose is to quantify the sensitivity of the DE-ASL sequence with respect to the conventional fMRI sequence (cvBOLD) in detecting brain activations, and to assess and compare the relevance of node features in decoding the network structure. Approach. Thirteen volunteers were scanned acquiring a pseudo-continuous DE-ASL sequence from which the concomitant BOLD (ccBOLD) simultaneously to the ASL can be extracted. The approach consists of two steps: (i) model-based analyses for assessing brain activations at individual and group levels, followed by statistical analysis for comparing the activation elicited by the three sequences under two conditions (motor and motor imagery), respectively; (ii) brain connectivity graph-theoretical analysis for assessing and comparing the network models properties. Main results. Our results suggest that cvBOLD and ccBOLD have comparable sensitivity in detecting the regions involved in the active task, whereas ASL offers a higher degree of co-localization with smaller activation volumes. The connectivity results and the comparative analysis of node features across sequences revealed that there are no strong changes between rest and tasks and that the differences between the sequences are limited to few connections. Significance. Considering the comparable sensitivity of the ccBOLD and cvBOLD sequences in detecting activated brain regions, the results demonstrate that DE-ASL can be successfully applied in functional studies allowing to obtain both ASL and BOLD information within a single sequence. Further, DE-ASL is a

Sleep-related offline improvements in gross motor task performance occur under free recall requirements

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Andreas eMalangre

2016-03-01

Full Text Available Nocturnal sleep effects on memory consolidation following gross motor sequence learning were examined using a complex arm movement task. This task required participants to produce non-regular spatial patterns in the horizontal plane by successively fitting a small peg into different target-holes on an electronic pegboard. The respective reaching movements typically differed in amplitude and direction. Targets were visualized prior to each transport movement on a computer screen. With this task we tested 18 subjects (22.6 +/- 1.9 years; 8 female using a between-subjects design. Participants initially learned a 10-element arm movement sequence either in the morning or in the evening. Performance was retested under free recall requirements 15 minutes post training, as well as 12 hrs and 24 hrs later. Thus each group was provided with one sleep-filled and one wake retention interval. Dependent variables were error rate (number of erroneous sequences and average sequence execution time (correct sequences only. Performance improved during acquisition. Error rate remained stable across retention. Sequence execution time (inverse to execution speed significantly decreased again during the sleep-filled retention intervals, but remained stable during the respective wake intervals. These results corroborate recent findings on sleep-related enhancement consolidation in ecological valid, complex gross motor tasks. At the same time they suggest this effect to be truly memory-based and independent from repeated access to extrinsic sequence information during retests.

Video coding for decoding power-constrained embedded devices

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Lu, Ligang; Sheinin, Vadim

2004-01-01

Low power dissipation and fast processing time are crucial requirements for embedded multimedia devices. This paper presents a technique in video coding to decrease the power consumption at a standard video decoder. Coupled with a small dedicated video internal memory cache on a decoder, the technique can substantially decrease the amount of data traffic to the external memory at the decoder. A decrease in data traffic to the external memory at decoder will result in multiple benefits: faster real-time processing and power savings. The encoder, given prior knowledge of the decoder"s dedicated video internal memory cache management scheme, regulates its choice of motion compensated predictors to reduce the decoder"s external memory accesses. This technique can be used in any standard or proprietary encoder scheme to generate a compliant output bit stream decodable by standard CPU-based and dedicated hardware-based decoders for power savings with the best quality-power cost trade off. Our simulation results show that with a relatively small amount of dedicated video internal memory cache, the technique may decrease the traffic between CPU and external memory over 50%.

A novel parallel pipeline structure of VP9 decoder

Science.gov (United States)

Qin, Huabiao; Chen, Wu; Yi, Sijun; Tan, Yunfei; Yi, Huan

2018-04-01

To improve the efficiency of VP9 decoder, a novel parallel pipeline structure of VP9 decoder is presented in this paper. According to the decoding workflow, VP9 decoder can be divided into sub-modules which include entropy decoding, inverse quantization, inverse transform, intra prediction, inter prediction, deblocking and pixel adaptive compensation. By analyzing the computing time of each module, hotspot modules are located and the causes of low efficiency of VP9 decoder can be found. Then, a novel pipeline decoder structure is designed by using mixed parallel decoding methods of data division and function division. The experimental results show that this structure can greatly improve the decoding efficiency of VP9.

SYMBOL LEVEL DECODING FOR DUO-BINARY TURBO CODES

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Yogesh Beeharry

2017-05-01

Full Text Available This paper investigates the performance of three different symbol level decoding algorithms for Duo-Binary Turbo codes. Explicit details of the computations involved in the three decoding techniques, and a computational complexity analysis are given. Simulation results with different couple lengths, code-rates, and QPSK modulation reveal that the symbol level decoding with bit-level information outperforms the symbol level decoding by 0.1 dB on average in the error floor region. Moreover, a complexity analysis reveals that symbol level decoding with bit-level information reduces the decoding complexity by 19.6 % in terms of the total number of computations required for each half-iteration as compared to symbol level decoding.

Proactive and retroactive transfer of middle age adults in a sequential motor learning task

NARCIS (Netherlands)

Verneau, M.; Kamp, J. van der; Savelsbergh, G,J.; Looze, M.P. de

2015-01-01

We assessed the effects of aging in the transfer of motor learning in a sequential manual assembly task that is representative for real working conditions. On two different days, young (18-30years) and middle-aged adults (50-65years) practiced to build two products that consisted of the same six

Proactive and Retroactive transfer of middle age adults in a sequential motor learing task

NARCIS (Netherlands)

Verneau, M.M.N.; van der Kamp, G.J.; Savelsbergh, G.J.P.; de Looze, M.P.

2015-01-01

We assessed the effects of aging in the transfer of motor learning in a sequential manual assembly task that is representative for real working conditions. On two different days, young (18-30. years) and middle-aged adults (50-65. years) practiced to build two products that consisted of the same six

Gene Expression Changes in the Motor Cortex Mediating Motor Skill Learning

Science.gov (United States)

Cheung, Vincent C. K.; DeBoer, Caroline; Hanson, Elizabeth; Tunesi, Marta; D'Onofrio, Mara; Arisi, Ivan; Brandi, Rossella; Cattaneo, Antonino; Goosens, Ki A.

2013-01-01

The primary motor cortex (M1) supports motor skill learning, yet little is known about the genes that contribute to motor cortical plasticity. Such knowledge could identify candidate molecules whose targeting might enable a new understanding of motor cortical functions, and provide new drug targets for the treatment of diseases which impair motor function, such as ischemic stroke. Here, we assess changes in the motor-cortical transcriptome across different stages of motor skill acquisition. Adult rats were trained on a gradually acquired appetitive reach and grasp task that required different strategies for successful pellet retrieval, or a sham version of the task in which the rats received pellet reward without needing to develop the reach and grasp skill. Tissue was harvested from the forelimb motor-cortical area either before training commenced, prior to the initial rise in task performance, or at peak performance. Differential classes of gene expression were observed at the time point immediately preceding motor task improvement. Functional clustering revealed that gene expression changes were related to the synapse, development, intracellular signaling, and the fibroblast growth factor (FGF) family, with many modulated genes known to regulate synaptic plasticity, synaptogenesis, and cytoskeletal dynamics. The modulated expression of synaptic genes likely reflects ongoing network reorganization from commencement of training till the point of task improvement, suggesting that motor performance improves only after sufficient modifications in the cortical circuitry have accumulated. The regulated FGF-related genes may together contribute to M1 remodeling through their roles in synaptic growth and maturation. PMID:23637843

Developmental Differences in Motor Task Integration: A Test of Pascual-Leone's Theory of Constructive Operators.

Science.gov (United States)

Todor, John I.

1979-01-01

Assesses the ability of Pascual-Leone's Theory of Constructive Operators to predict the minimum age or maturational level at which integration of a motor task could be achieved. Subjects were 114 elementary school children ranging in age from 5 to 12. (Author/MP)

Motor demand-dependent activation of ipsilateral motor cortex.

Science.gov (United States)

Buetefisch, Cathrin M; Revill, Kate Pirog; Shuster, Linda; Hines, Benjamin; Parsons, Michael

2014-08-15

The role of ipsilateral primary motor cortex (M1) in hand motor control during complex task performance remains controversial. Bilateral M1 activation is inconsistently observed in functional (f)MRI studies of unilateral hand performance. Two factors limit the interpretation of these data. As the motor tasks differ qualitatively in these studies, it is conceivable that M1 contributions differ with the demand on skillfulness. Second, most studies lack the verification of a strictly unilateral execution of the motor task during the acquisition of imaging data. Here, we use fMRI to determine whether ipsilateral M1 activity depends on the demand for precision in a pointing task where precision varied quantitatively while movement trajectories remained equal. Thirteen healthy participants used an MRI-compatible joystick to point to targets of four different sizes in a block design. A clustered acquisition technique allowed simultaneous fMRI/EMG data collection and confirmed that movements were strictly unilateral. Accuracy of performance increased with target size. Overall, the pointing task revealed activation in contralateral and ipsilateral M1, extending into contralateral somatosensory and parietal areas. Target size-dependent activation differences were found in ipsilateral M1 extending into the temporal/parietal junction, where activation increased with increasing demand on accuracy. The results suggest that ipsilateral M1 is active during the execution of a unilateral motor task and that its activity is modulated by the demand on precision. Copyright © 2014 the American Physiological Society.

NP-hardness of decoding quantum error-correction codes

Science.gov (United States)

Hsieh, Min-Hsiu; Le Gall, François

2011-05-01

Although the theory of quantum error correction is intimately related to classical coding theory and, in particular, one can construct quantum error-correction codes (QECCs) from classical codes with the dual-containing property, this does not necessarily imply that the computational complexity of decoding QECCs is the same as their classical counterparts. Instead, decoding QECCs can be very much different from decoding classical codes due to the degeneracy property. Intuitively, one expects degeneracy would simplify the decoding since two different errors might not and need not be distinguished in order to correct them. However, we show that general quantum decoding problem is NP-hard regardless of the quantum codes being degenerate or nondegenerate. This finding implies that no considerably fast decoding algorithm exists for the general quantum decoding problems and suggests the existence of a quantum cryptosystem based on the hardness of decoding QECCs.

NP-hardness of decoding quantum error-correction codes

International Nuclear Information System (INIS)

Hsieh, Min-Hsiu; Le Gall, Francois

2011-01-01

Although the theory of quantum error correction is intimately related to classical coding theory and, in particular, one can construct quantum error-correction codes (QECCs) from classical codes with the dual-containing property, this does not necessarily imply that the computational complexity of decoding QECCs is the same as their classical counterparts. Instead, decoding QECCs can be very much different from decoding classical codes due to the degeneracy property. Intuitively, one expects degeneracy would simplify the decoding since two different errors might not and need not be distinguished in order to correct them. However, we show that general quantum decoding problem is NP-hard regardless of the quantum codes being degenerate or nondegenerate. This finding implies that no considerably fast decoding algorithm exists for the general quantum decoding problems and suggests the existence of a quantum cryptosystem based on the hardness of decoding QECCs.

Motor learning in a complex balance task and associated neuroplasticity: a comparison between endurance athletes and nonathletes.

Science.gov (United States)

Seidel, Oliver; Carius, Daniel; Kenville, Rouven; Ragert, Patrick

2017-09-01

Studies suggested that motor expertise is associated with functional and structural brain alterations, which positively affect sensorimotor performance and learning capabilities. The purpose of the present study was to unravel differences in motor skill learning and associated functional neuroplasticity between endurance athletes (EA) and nonathletes (NA). For this purpose, participants had to perform a multimodal balance task (MBT) training on 2 sessions, which were separated by 1 wk. Before and after MBT training, a static balance task (SBT) had to be performed. MBT-induced functional neuroplasticity and neuromuscular alterations were assessed by means of functional near-infrared spectroscopy (fNIRS) and electromyography (EMG) during SBT performance. We hypothesized that EA would showed superior initial SBT performance and stronger MBT-induced improvements in SBT learning rates compared with NA. On a cortical level, we hypothesized that MBT training would lead to differential learning-dependent functional changes in motor-related brain regions [such as primary motor cortex (M1)] during SBT performance. In fact, EA showed superior initial SBT performance, whereas learning rates did not differ between groups. On a cortical level, fNIRS recordings (time × group interaction) revealed a stronger MBT-induced decrease in left M1 and inferior parietal lobe (IPL) for deoxygenated hemoglobin in EA. Even more interesting, learning rates were correlated with fNIRS changes in right M1/IPL. On the basis of these findings, we provide novel evidence for superior MBT training-induced functional neuroplasticity in highly trained athletes. Future studies should investigate these effects in different sports disciplines to strengthen previous work on experience-dependent neuroplasticity. NEW & NOTEWORTHY Motor expertise is associated with functional/structural brain plasticity. How such neuroplastic reorganization translates into altered motor learning processes remains elusive. We

Evaluation framework for K-best sphere decoders

KAUST Repository

Shen, Chungan; Eltawil, Ahmed M.; Salama, Khaled N.

2010-01-01

or receive antennas. Tree-searching type decoder structures such as Sphere decoder and K-best decoder present an interesting trade-off between complexity and performance. Many algorithmic developments and VLSI implementations have been reported in literature

Decoding magnetoencephalographic rhythmic activity using spectrospatial information.

Science.gov (United States)

Kauppi, Jukka-Pekka; Parkkonen, Lauri; Hari, Riitta; Hyvärinen, Aapo

2013-12-01

We propose a new data-driven decoding method called Spectral Linear Discriminant Analysis (Spectral LDA) for the analysis of magnetoencephalography (MEG). The method allows investigation of changes in rhythmic neural activity as a result of different stimuli and tasks. The introduced classification model only assumes that each "brain state" can be characterized as a combination of neural sources, each of which shows rhythmic activity at one or several frequency bands. Furthermore, the model allows the oscillation frequencies to be different for each such state. We present decoding results from 9 subjects in a four-category classification problem defined by an experiment involving randomly alternating epochs of auditory, visual and tactile stimuli interspersed with rest periods. The performance of Spectral LDA was very competitive compared with four alternative classifiers based on different assumptions concerning the organization of rhythmic brain activity. In addition, the spectral and spatial patterns extracted automatically on the basis of trained classifiers showed that Spectral LDA offers a novel and interesting way of analyzing spectrospatial oscillatory neural activity across the brain. All the presented classification methods and visualization tools are freely available as a Matlab toolbox. © 2013.

Exploring the Link between Visual Perception, Visual-Motor Integration, and Reading in Normal Developing and Impaired Children using DTVP-2.

Science.gov (United States)

Bellocchi, Stéphanie; Muneaux, Mathilde; Huau, Andréa; Lévêque, Yohana; Jover, Marianne; Ducrot, Stéphanie

2017-08-01

Reading is known to be primarily a linguistic task. However, to successfully decode written words, children also need to develop good visual-perception skills. Furthermore, motor skills are implicated in letter recognition and reading acquisition. Three studies have been designed to determine the link between reading, visual perception, and visual-motor integration using the Developmental Test of Visual Perception version 2 (DTVP-2). Study 1 tests how visual perception and visual-motor integration in kindergarten predict reading outcomes in Grade 1, in typical developing children. Study 2 is aimed at finding out if these skills can be seen as clinical markers in dyslexic children (DD). Study 3 determines if visual-motor integration and motor-reduced visual perception can distinguish DD children according to whether they exhibit or not developmental coordination disorder (DCD). Results showed that phonological awareness and visual-motor integration predicted reading outcomes one year later. DTVP-2 demonstrated similarities and differences in visual-motor integration and motor-reduced visual perception between children with DD, DCD, and both of these deficits. DTVP-2 is a suitable tool to investigate links between visual perception, visual-motor integration and reading, and to differentiate cognitive profiles of children with developmental disabilities (i.e. DD, DCD, and comorbid children). Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Neural Decoder for Topological Codes

Science.gov (United States)

Torlai, Giacomo; Melko, Roger G.

2017-07-01

We present an algorithm for error correction in topological codes that exploits modern machine learning techniques. Our decoder is constructed from a stochastic neural network called a Boltzmann machine, of the type extensively used in deep learning. We provide a general prescription for the training of the network and a decoding strategy that is applicable to a wide variety of stabilizer codes with very little specialization. We demonstrate the neural decoder numerically on the well-known two-dimensional toric code with phase-flip errors.

LDPC Decoding on GPU for Mobile Device

Directory of Open Access Journals (Sweden)

Yiqin Lu

2016-01-01

Full Text Available A flexible software LDPC decoder that exploits data parallelism for simultaneous multicode words decoding on the mobile device is proposed in this paper, supported by multithreading on OpenCL based graphics processing units. By dividing the check matrix into several parts to make full use of both the local memory and private memory on GPU and properly modify the code capacity each time, our implementation on a mobile phone shows throughputs above 100 Mbps and delay is less than 1.6 millisecond in decoding, which make high-speed communication like video calling possible. To realize efficient software LDPC decoding on the mobile device, the LDPC decoding feature on communication baseband chip should be replaced to save the cost and make it easier to upgrade decoder to be compatible with a variety of channel access schemes.

Laterality of Temporoparietal Causal Connectivity during the Prestimulus Period Correlates with Phonological Decoding Task Performance in Dyslexic and Typical Readers

OpenAIRE

Frye, Richard E.; Liederman, Jacqueline; McGraw Fisher, Janet; Wu, Meng-Hung

2011-01-01

We examined how effective connectivity into and out of the left and right temporoparietal areas (TPAs) to/from other key cortical areas affected phonological decoding in 7 dyslexic readers (DRs) and 10 typical readers (TRs) who were young adults. Granger causality was used to compute the effective connectivity of the preparatory network 500 ms prior to presentation of nonwords that required phonological decoding. Neuromagnetic activity was analyzed within the low, medium, and high beta and ga...

The serial message-passing schedule for LDPC decoding algorithms

Science.gov (United States)

Liu, Mingshan; Liu, Shanshan; Zhou, Yuan; Jiang, Xue

2015-12-01

The conventional message-passing schedule for LDPC decoding algorithms is the so-called flooding schedule. It has the disadvantage that the updated messages cannot be used until next iteration, thus reducing the convergence speed . In this case, the Layered Decoding algorithm (LBP) based on serial message-passing schedule is proposed. In this paper the decoding principle of LBP algorithm is briefly introduced, and then proposed its two improved algorithms, the grouped serial decoding algorithm (Grouped LBP) and the semi-serial decoding algorithm .They can improve LBP algorithm's decoding speed while maintaining a good decoding performance.

Motor cortex is required for learning but not for executing a motor skill.

Science.gov (United States)

Kawai, Risa; Markman, Timothy; Poddar, Rajesh; Ko, Raymond; Fantana, Antoniu L; Dhawale, Ashesh K; Kampff, Adam R; Ölveczky, Bence P

2015-05-06

Motor cortex is widely believed to underlie the acquisition and execution of motor skills, but its contributions to these processes are not fully understood. One reason is that studies on motor skills often conflate motor cortex's established role in dexterous control with roles in learning and producing task-specific motor sequences. To dissociate these aspects, we developed a motor task for rats that trains spatiotemporally precise movement patterns without requirements for dexterity. Remarkably, motor cortex lesions had no discernible effect on the acquired skills, which were expressed in their distinct pre-lesion forms on the very first day of post-lesion training. Motor cortex lesions prior to training, however, rendered rats unable to acquire the stereotyped motor sequences required for the task. These results suggest a remarkable capacity of subcortical motor circuits to execute learned skills and a previously unappreciated role for motor cortex in "tutoring" these circuits during learning. Copyright © 2015 Elsevier Inc. All rights reserved.

Improved Power Decoding of One-Point Hermitian Codes

DEFF Research Database (Denmark)

Puchinger, Sven; Bouw, Irene; Rosenkilde, Johan Sebastian Heesemann

2017-01-01

We propose a new partial decoding algorithm for one-point Hermitian codes that can decode up to the same number of errors as the Guruswami–Sudan decoder. Simulations suggest that it has a similar failure probability as the latter one. The algorithm is based on a recent generalization of the power...... decoding algorithm for Reed–Solomon codes and does not require an expensive root-finding step. In addition, it promises improvements for decoding interleaved Hermitian codes....

Influence of age, circadian and homeostatic processes on inhibitory motor control: a Go/Nogo task study.

Directory of Open Access Journals (Sweden)

Patricia Sagaspe

Full Text Available INTRODUCTION: The contribution of circadian system and sleep pressure influences on executive performance as a function of age has never been studied. The aim of our study was to determine the age-related evolution of inhibitory motor control (i.e., ability to suppress a prepotent motor response and sustained attention under controlled high or low sleep pressure conditions. METHODS: 14 healthy young males (mean age = 23 ± 2.7; 20-29 years and 11 healthy older males (mean age = 68 ± 1.4; 66-70 years were recruited. The volunteers were placed for 40 hours in "constant routine". In the "Sleep Deprivation SD" condition, the volunteer was kept awake for 40 hours to obtain a high sleep pressure condition interacting with the circadian process. In the "NAP" condition, the volunteer adopted a short wake/sleep cycle (150/75 min resulting in a low sleep pressure condition to counteract the homeostatic pressure and investigate the circadian process. Performances were evaluated by a simple reaction time task and a Go/Nogo task repeated every 3H45. RESULTS: In the SD condition, inhibitory motor control (i.e., ability to inhibit an inappropriate response was impaired by extended wakefulness equally in both age groups (P<.01. Sustained attention (i.e. ability to respond accurately to appropriate stimuli on the executive task decreased under sleep deprivation in both groups, and even more in young participants (P<.05. In the NAP condition, age did not influence the time course of inhibitory motor control or sustained attention. In the SD and NAP conditions, older participants had a less fluctuating reaction time performance across time of day than young participants (P<.001. CONCLUSION: Aging could be a protective factor against the effects of extended wakefulness especially on sustained attention failures due to an attenuation of sleep pressure with duration of time awake.

Two-phase strategy of controlling motor coordination determined by task performance optimality.

Science.gov (United States)

Shimansky, Yury P; Rand, Miya K

2013-02-01

A quantitative model of optimal coordination between hand transport and grip aperture has been derived in our previous studies of reach-to-grasp movements without utilizing explicit knowledge of the optimality criterion or motor plant dynamics. The model's utility for experimental data analysis has been demonstrated. Here we show how to generalize this model for a broad class of reaching-type, goal-directed movements. The model allows for measuring the variability of motor coordination and studying its dependence on movement phase. The experimentally found characteristics of that dependence imply that execution noise is low and does not affect motor coordination significantly. From those characteristics it is inferred that the cost of neural computations required for information acquisition and processing is included in the criterion of task performance optimality as a function of precision demand for state estimation and decision making. The precision demand is an additional optimized control variable that regulates the amount of neurocomputational resources activated dynamically. It is shown that an optimal control strategy in this case comprises two different phases. During the initial phase, the cost of neural computations is significantly reduced at the expense of reducing the demand for their precision, which results in speed-accuracy tradeoff violation and significant inter-trial variability of motor coordination. During the final phase, neural computations and thus motor coordination are considerably more precise to reduce the cost of errors in making a contact with the target object. The generality of the optimal coordination model and the two-phase control strategy is illustrated on several diverse examples.

When Affordances Climb into Your Mind: Advantages of Motor Simulation in a Memory Task Performed by Novice and Expert Rock Climbers

Science.gov (United States)

Pezzulo, Giovanni; Barca, Laura; Bocconi, Alessandro Lamberti; Borghi, Anna M.

2010-01-01

Does the sight of multiple climbing holds laid along a path activate a motor simulation of climbing that path? One way of testing whether multiple affordances and their displacement influence the formation of a motor simulation is to study acquired motor skills. We used a behavioral task in which expert and novice rock climbers were shown three…

Decoding face information in time, frequency and space from direct intracranial recordings of the human brain.

Directory of Open Access Journals (Sweden)

Naotsugu Tsuchiya

Full Text Available Faces are processed by a neural system with distributed anatomical components, but the roles of these components remain unclear. A dominant theory of face perception postulates independent representations of invariant aspects of faces (e.g., identity in ventral temporal cortex including the fusiform gyrus, and changeable aspects of faces (e.g., emotion in lateral temporal cortex including the superior temporal sulcus. Here we recorded neuronal activity directly from the cortical surface in 9 neurosurgical subjects undergoing epilepsy monitoring while they viewed static and dynamic facial expressions. Applying novel decoding analyses to the power spectrogram of electrocorticograms (ECoG from over 100 contacts in ventral and lateral temporal cortex, we found better representation of both invariant and changeable aspects of faces in ventral than lateral temporal cortex. Critical information for discriminating faces from geometric patterns was carried by power modulations between 50 to 150 Hz. For both static and dynamic face stimuli, we obtained a higher decoding performance in ventral than lateral temporal cortex. For discriminating fearful from happy expressions, critical information was carried by power modulation between 60-150 Hz and below 30 Hz, and again better decoded in ventral than lateral temporal cortex. Task-relevant attention improved decoding accuracy more than 10% across a wide frequency range in ventral but not at all in lateral temporal cortex. Spatial searchlight decoding showed that decoding performance was highest around the middle fusiform gyrus. Finally, we found that the right hemisphere, in general, showed superior decoding to the left hemisphere. Taken together, our results challenge the dominant model for independent face representation of invariant and changeable aspects: information about both face attributes was better decoded from a single region in the middle fusiform gyrus.

Neuroimaging of decoding and language comprehension in young very low birth weight (VLBW adolescents: Indications for compensatory mechanisms.

Directory of Open Access Journals (Sweden)

Helene van Ettinger-Veenstra

Full Text Available In preterm children with very low birth weight (VLBW ≤ 1500 g, reading problems are often observed. Reading comprehension is dependent on word decoding and language comprehension. We investigated neural activation-within brain regions important for reading-related to components of reading comprehension in young VLBW adolescents in direct comparison to normal birth weight (NBW term-born peers, with the use of functional magnetic resonance imaging (fMRI. We hypothesized that the decoding mechanisms will be affected by VLBW, and expect to see increased neural activity for VLBW which may be modulated by task performance and cognitive ability. The study investigated 13 (11 included in fMRI young adolescents (ages 12 to 14 years born preterm with VLBW and in 13 NBW controls (ages 12-14 years for performance on the Block Design and Vocabulary subtests of the Wechsler Intelligence Scale for Children; and for semantic, orthographic, and phonological processing during an fMRI paradigm. The VLBW group showed increased phonological activation in left inferior frontal gyrus, decreased orthographic activation in right supramarginal gyrus, and decreased semantic activation in left inferior frontal gyrus. Block Design was related to altered right-hemispheric activation, and VLBW showed lower WISC Block Design scores. Left angular gyrus showed activation increase specific for VLBW with high accuracy on the semantic test. Young VLBW adolescents showed no accuracy and reaction time performance differences on our fMRI language tasks, but they did exhibit altered neural activation during these tasks. This altered activation for VLBW was observed as increased activation during phonological decoding, and as mainly decreased activation during orthographic and semantic processing. Correlations of neural activation with accuracy on the semantic fMRI task and with decreased WISC Block Design performance were specific for the VLBW group. Together, results suggest

On Lattice Sequential Decoding for The Unconstrained AWGN Channel

KAUST Repository

Abediseid, Walid

2012-10-01

In this paper, the performance limits and the computational complexity of the lattice sequential decoder are analyzed for the unconstrained additive white Gaussian noise channel. The performance analysis available in the literature for such a channel has been studied only under the use of the minimum Euclidean distance decoder that is commonly referred to as the lattice decoder. Lattice decoders based on solutions to the NP-hard closest vector problem are very complex to implement, and the search for low complexity receivers for the detection of lattice codes is considered a challenging problem. However, the low computational complexity advantage that sequential decoding promises, makes it an alternative solution to the lattice decoder. In this work, we characterize the performance and complexity tradeoff via the error exponent and the decoding complexity, respectively, of such a decoder as a function of the decoding parameter --- the bias term. For the above channel, we derive the cut-off volume-to-noise ratio that is required to achieve a good error performance with low decoding complexity.

On Lattice Sequential Decoding for The Unconstrained AWGN Channel

KAUST Repository

Abediseid, Walid

2013-04-04

In this paper, the performance limits and the computational complexity of the lattice sequential decoder are analyzed for the unconstrained additive white Gaussian noise channel. The performance analysis available in the literature for such a channel has been studied only under the use of the minimum Euclidean distance decoder that is commonly referred to as the \\\\textit{lattice decoder}. Lattice decoders based on solutions to the NP-hard closest vector problem are very complex to implement, and the search for low complexity receivers for the detection of lattice codes is considered a challenging problem. However, the low computational complexity advantage that sequential decoding promises, makes it an alternative solution to the lattice decoder. In this work, we characterize the performance and complexity tradeoff via the error exponent and the decoding complexity, respectively, of such a decoder as a function of the decoding parameter --- the bias term. For the above channel, we derive the cut-off volume-to-noise ratio that is required to achieve a good error performance with low decoding complexity.

On Lattice Sequential Decoding for The Unconstrained AWGN Channel

KAUST Repository

Abediseid, Walid; Alouini, Mohamed-Slim

2012-01-01

In this paper, the performance limits and the computational complexity of the lattice sequential decoder are analyzed for the unconstrained additive white Gaussian noise channel. The performance analysis available in the literature for such a channel has been studied only under the use of the minimum Euclidean distance decoder that is commonly referred to as the lattice decoder. Lattice decoders based on solutions to the NP-hard closest vector problem are very complex to implement, and the search for low complexity receivers for the detection of lattice codes is considered a challenging problem. However, the low computational complexity advantage that sequential decoding promises, makes it an alternative solution to the lattice decoder. In this work, we characterize the performance and complexity tradeoff via the error exponent and the decoding complexity, respectively, of such a decoder as a function of the decoding parameter --- the bias term. For the above channel, we derive the cut-off volume-to-noise ratio that is required to achieve a good error performance with low decoding complexity.

Interior point decoding for linear vector channels

International Nuclear Information System (INIS)

Wadayama, T

2008-01-01

In this paper, a novel decoding algorithm for low-density parity-check (LDPC) codes based on convex optimization is presented. The decoding algorithm, called interior point decoding, is designed for linear vector channels. The linear vector channels include many practically important channels such as inter-symbol interference channels and partial response channels. It is shown that the maximum likelihood decoding (MLD) rule for a linear vector channel can be relaxed to a convex optimization problem, which is called a relaxed MLD problem

Interior point decoding for linear vector channels

Energy Technology Data Exchange (ETDEWEB)

Wadayama, T [Nagoya Institute of Technology, Gokiso, Showa-ku, Nagoya, Aichi, 466-8555 (Japan)], E-mail: wadayama@nitech.ac.jp

2008-01-15

In this paper, a novel decoding algorithm for low-density parity-check (LDPC) codes based on convex optimization is presented. The decoding algorithm, called interior point decoding, is designed for linear vector channels. The linear vector channels include many practically important channels such as inter-symbol interference channels and partial response channels. It is shown that the maximum likelihood decoding (MLD) rule for a linear vector channel can be relaxed to a convex optimization problem, which is called a relaxed MLD problem.

The influence of motor imagery on the learning of a fine hand motor skill

NARCIS (Netherlands)

Sobierajewicz, Jagna; Przekoracka-Krawczyk, Anna; Jaśkowski, Wojciech; Verwey, Willem B.; van der Lubbe, Rob

2017-01-01

Motor imagery has been argued to affect the acquisition of motor skills. The present study examined the specificity of motor imagery on the learning of a fine hand motor skill by employing a modified discrete sequence production task: the Go/NoGo DSP task. After an informative cue, a response

Transfer of Short-Term Motor Learning across the Lower Limbs as a Function of Task Conception and Practice Order

Science.gov (United States)

Stockel, Tino; Wang, Jinsung

2011-01-01

Interlimb transfer of motor learning, indicating an improvement in performance with one limb following training with the other, often occurs asymmetrically (i.e., from non-dominant to dominant limb or vice versa, but not both). In the present study, we examined whether interlimb transfer of the same motor task could occur asymmetrically and in…

Symbol synchronization for the TDRSS decoder

Science.gov (United States)

Costello, D. J., Jr.

1983-01-01

Each 8 bits out of the Viterbi decoder correspond to one symbol of the R/S code. Synchronization must be maintained here so that each 8-bit symbol delivered to the R/S decoder corresponds to an 8-bit symbol from the R/S encoder. Lack of synchronization, would cause an error in almost every R/S symbol since even a - 1-bit sync slip shifts every bit in each 8-bit symbol by one position, therby confusing the mapping betweeen 8-bit sequences and symbols. The error correcting capability of the R/S code would be exceeded. Possible ways to correcting this condition include: (1) designing the R/S decoder to recognize the overload and shifting the output sequence of the inner decoder to establish a different sync state; (2) using the characteristics of the inner decoder to establish symbol synchronization for the outer code, with or without a deinterleaver and an interleaver; and (3) modifying the encoder to alternate periodically between two sets of generators.

A class of Sudan-decodable codes

DEFF Research Database (Denmark)

Nielsen, Rasmus Refslund

2000-01-01

In this article, Sudan's algorithm is modified into an efficient method to list-decode a class of codes which can be seen as a generalization of Reed-Solomon codes. The algorithm is specialized into a very efficient method for unique decoding. The code construction can be generalized based...... on algebraic-geometry codes and the decoding algorithms are generalized accordingly. Comparisons with Reed-Solomon and Hermitian codes are made....

Reconciling the influence of task-set switching and motor inhibition processes on stop signal after-effects.

Science.gov (United States)

Anguera, Joaquin A; Lyman, Kyle; Zanto, Theodore P; Bollinger, Jacob; Gazzaley, Adam

2013-01-01

Executive response functions can be affected by preceding events, even if they are no longer associated with the current task at hand. For example, studies utilizing the stop signal task have reported slower response times to "GO" stimuli when the preceding trial involved the presentation of a "STOP" signal. However, the neural mechanisms that underlie this behavioral after-effect are unclear. To address this, behavioral and electroencephalography (EEG) measures were examined in 18 young adults (18-30 years) on "GO" trials following a previously "Successful Inhibition" trial (pSI), a previously "Failed Inhibition" trial (pFI), and a previous "GO" trial (pGO). Like previous research, slower response times were observed during both pSI and pFI trials (i.e., "GO" trials that were preceded by a successful and unsuccessful inhibition trial, respectively) compared to pGO trials (i.e., "GO" trials that were preceded by another "GO" trial). Interestingly, response time slowing was greater during pSI trials compared to pFI trials, suggesting executive control is influenced by both task set switching and persisting motor inhibition processes. Follow-up behavioral analyses indicated that these effects resulted from between-trial control adjustments rather than repetition priming effects. Analyses of inter-electrode coherence (IEC) and inter-trial coherence (ITC) indicated that both pSI and pFI trials showed greater phase synchrony during the inter-trial interval compared to pGO trials. Unlike the IEC findings, differential ITC was present within the beta and alpha frequency bands in line with the observed behavior (pSI > pFI > pGO), suggestive of more consistent phase synchrony involving motor inhibition processes during the ITI at a regional level. These findings suggest that between-trial control adjustments involved with task-set switching and motor inhibition processes influence subsequent performance, providing new insights into the dynamic nature of executive control.

Multi-stage decoding for multi-level block modulation codes

Science.gov (United States)

Lin, Shu

1991-01-01

In this paper, we investigate various types of multi-stage decoding for multi-level block modulation codes, in which the decoding of a component code at each stage can be either soft-decision or hard-decision, maximum likelihood or bounded-distance. Error performance of codes is analyzed for a memoryless additive channel based on various types of multi-stage decoding, and upper bounds on the probability of an incorrect decoding are derived. Based on our study and computation results, we find that, if component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. In particular, we find that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum decoding of the overall code is very small: only a fraction of dB loss in SNR at the probability of an incorrect decoding for a block of 10(exp -6). Multi-stage decoding of multi-level modulation codes really offers a way to achieve the best of three worlds, bandwidth efficiency, coding gain, and decoding complexity.

On Rational Interpolation-Based List-Decoding and List-Decoding Binary Goppa Codes

DEFF Research Database (Denmark)

Beelen, Peter; Høholdt, Tom; Nielsen, Johan Sebastian Rosenkilde

2013-01-01

We derive the Wu list-decoding algorithm for generalized Reed–Solomon (GRS) codes by using Gröbner bases over modules and the Euclidean algorithm as the initial algorithm instead of the Berlekamp–Massey algorithm. We present a novel method for constructing the interpolation polynomial fast. We gi...... and a duality in the choice of parameters needed for decoding, both in the case of GRS codes and in the case of Goppa codes....

Balance Training Reduces Brain Activity during Motor Simulation of a Challenging Balance Task in Older Adults: An fMRI Study.

Science.gov (United States)

Ruffieux, Jan; Mouthon, Audrey; Keller, Martin; Mouthon, Michaël; Annoni, Jean-Marie; Taube, Wolfgang

2018-01-01

Aging is associated with a shift from an automatic to a more cortical postural control strategy, which goes along with deteriorations in postural stability. Although balance training has been shown to effectively counteract these behavioral deteriorations, little is known about the effect of balance training on brain activity during postural tasks in older adults. We, therefore, assessed postural stability and brain activity using fMRI during motor imagery alone (MI) and in combination with action observation (AO; i.e., AO+MI) of a challenging balance task in older adults before and after 5 weeks of balance training. Results showed a nonsignificant trend toward improvements in postural stability after balance training, accompanied by reductions in brain activity during AO+MI of the balance task in areas relevant for postural control, which have been shown to be over-activated in older adults during (simulation of) motor performance, including motor, premotor, and multisensory vestibular areas. This suggests that balance training may reverse the age-related cortical over-activations and lead to changes in the control of upright posture toward the one observed in young adults.

Encoder-decoder optimization for brain-computer interfaces.

Science.gov (United States)

Merel, Josh; Pianto, Donald M; Cunningham, John P; Paninski, Liam

2015-06-01

Neuroprosthetic brain-computer interfaces are systems that decode neural activity into useful control signals for effectors, such as a cursor on a computer screen. It has long been recognized that both the user and decoding system can adapt to increase the accuracy of the end effector. Co-adaptation is the process whereby a user learns to control the system in conjunction with the decoder adapting to learn the user's neural patterns. We provide a mathematical framework for co-adaptation and relate co-adaptation to the joint optimization of the user's control scheme ("encoding model") and the decoding algorithm's parameters. When the assumptions of that framework are respected, co-adaptation cannot yield better performance than that obtainable by an optimal initial choice of fixed decoder, coupled with optimal user learning. For a specific case, we provide numerical methods to obtain such an optimized decoder. We demonstrate our approach in a model brain-computer interface system using an online prosthesis simulator, a simple human-in-the-loop pyschophysics setup which provides a non-invasive simulation of the BCI setting. These experiments support two claims: that users can learn encoders matched to fixed, optimal decoders and that, once learned, our approach yields expected performance advantages.

Encoder-decoder optimization for brain-computer interfaces.

Directory of Open Access Journals (Sweden)

Josh Merel

2015-06-01

Full Text Available Neuroprosthetic brain-computer interfaces are systems that decode neural activity into useful control signals for effectors, such as a cursor on a computer screen. It has long been recognized that both the user and decoding system can adapt to increase the accuracy of the end effector. Co-adaptation is the process whereby a user learns to control the system in conjunction with the decoder adapting to learn the user's neural patterns. We provide a mathematical framework for co-adaptation and relate co-adaptation to the joint optimization of the user's control scheme ("encoding model" and the decoding algorithm's parameters. When the assumptions of that framework are respected, co-adaptation cannot yield better performance than that obtainable by an optimal initial choice of fixed decoder, coupled with optimal user learning. For a specific case, we provide numerical methods to obtain such an optimized decoder. We demonstrate our approach in a model brain-computer interface system using an online prosthesis simulator, a simple human-in-the-loop pyschophysics setup which provides a non-invasive simulation of the BCI setting. These experiments support two claims: that users can learn encoders matched to fixed, optimal decoders and that, once learned, our approach yields expected performance advantages.

Iterative Decoding of Concatenated Codes: A Tutorial

Directory of Open Access Journals (Sweden)

Phillip A. Regalia

2005-05-01

Full Text Available The turbo decoding algorithm of a decade ago constituted a milestone in error-correction coding for digital communications, and has inspired extensions to generalized receiver topologies, including turbo equalization, turbo synchronization, and turbo CDMA, among others. Despite an accrued understanding of iterative decoding over the years, the “turbo principle” remains elusive to master analytically, thereby inciting interest from researchers outside the communications domain. In this spirit, we develop a tutorial presentation of iterative decoding for parallel and serial concatenated codes, in terms hopefully accessible to a broader audience. We motivate iterative decoding as a computationally tractable attempt to approach maximum-likelihood decoding, and characterize fixed points in terms of a “consensus” property between constituent decoders. We review how the decoding algorithm for both parallel and serial concatenated codes coincides with an alternating projection algorithm, which allows one to identify conditions under which the algorithm indeed converges to a maximum-likelihood solution, in terms of particular likelihood functions factoring into the product of their marginals. The presentation emphasizes a common framework applicable to both parallel and serial concatenated codes.

Joint Decoding of Concatenated VLEC and STTC System

Directory of Open Access Journals (Sweden)

Chen Huijun

2008-01-01

Full Text Available Abstract We consider the decoding of wireless communication systems with both source coding in the application layer and channel coding in the physical layer for high-performance transmission over fading channels. Variable length error correcting codes (VLECs and space time trellis codes (STTCs are used to provide bandwidth efficient data compression as well as coding and diversity gains. At the receiver, an iterative joint source and space time decoding scheme are developed to utilize redundancy in both STTC and VLEC to improve overall decoding performance. Issues such as the inseparable systematic information in the symbol level, the asymmetric trellis structure of VLEC, and information exchange between bit and symbol domains have been considered in the maximum a posteriori probability (MAP decoding algorithm. Simulation results indicate that the developed joint decoding scheme achieves a significant decoding gain over the separate decoding in fading channels, whether or not the channel information is perfectly known at the receiver. Furthermore, how rate allocation between STTC and VLEC affects the performance of the joint source and space-time decoder is investigated. Different systems with a fixed overall information rate are studied. It is shown that for a system with more redundancy dedicated to the source code and a higher order modulation of STTC, the joint decoding yields better performance, though with increased complexity.

Joint Decoding of Concatenated VLEC and STTC System

Directory of Open Access Journals (Sweden)

Huijun Chen

2008-07-01

Full Text Available We consider the decoding of wireless communication systems with both source coding in the application layer and channel coding in the physical layer for high-performance transmission over fading channels. Variable length error correcting codes (VLECs and space time trellis codes (STTCs are used to provide bandwidth efficient data compression as well as coding and diversity gains. At the receiver, an iterative joint source and space time decoding scheme are developed to utilize redundancy in both STTC and VLEC to improve overall decoding performance. Issues such as the inseparable systematic information in the symbol level, the asymmetric trellis structure of VLEC, and information exchange between bit and symbol domains have been considered in the maximum a posteriori probability (MAP decoding algorithm. Simulation results indicate that the developed joint decoding scheme achieves a significant decoding gain over the separate decoding in fading channels, whether or not the channel information is perfectly known at the receiver. Furthermore, how rate allocation between STTC and VLEC affects the performance of the joint source and space-time decoder is investigated. Different systems with a fixed overall information rate are studied. It is shown that for a system with more redundancy dedicated to the source code and a higher order modulation of STTC, the joint decoding yields better performance, though with increased complexity.

FPGA Realization of Memory 10 Viterbi Decoder

DEFF Research Database (Denmark)

Paaske, Erik; Bach, Thomas Bo; Andersen, Jakob Dahl

1997-01-01

sequence mode when feedback from the Reed-Solomon decoder is available. The Viterbi decoder is realized using two Altera FLEX 10K50 FPGA's. The overall operating speed is 30 kbit/s, and since up to three iterations are performed for each frame and only one decoder is used, the operating speed...

The Perception and Decoding of Expressive Emotional Information by Hearing and Hearing-Impaired Children.

Science.gov (United States)

Sanders, Gina

1985-01-01

Hearing and hearing-impaired children between ages 4.5 to 15.5 years in England and Belgium were invited to abstract the concept of emotion from photographs and line drawings of facial expressions and body postures. A further experiment isloated the element of context in the task of decoding expression of emotion, resulting in comparatively…

High Speed Frame Synchronization and Viterbi Decoding

DEFF Research Database (Denmark)

Paaske, Erik; Justesen, Jørn; Larsen, Knud J.

1996-01-01

The purpose of Phase 1 of the study is to describe the system structure and algorithms in sufficient detail to allow drawing the high level architecture of units containing frame synchronization and Viterbi decoding. The systems we consider are high data rate space communication systems. Also...... components. Node synchronization performed within a Viterbi decoder is discussed, and algorithms for frame synchronization are described and analyzed. We present a list of system configurations that we find potentially useful. Further, the high level architecture of units that contain frame synchronization...... and various other functions needed in a complete system is presented. Two such units are described, one for placement before the Viterbi decoder and another for placement after the decoder. The high level architectures of three possible implementations of Viterbi decoders are described: The first...

High Speed Frame Synchronization and Viterbi Decoding

DEFF Research Database (Denmark)

Paaske, Erik; Justesen, Jørn; Larsen, Knud J.

1998-01-01

The study has been divided into two phases. The purpose of Phase 1 of the study was to describe the system structure and algorithms in sufficient detail to allow drawing the high level architecture of units containing frame synchronization and Viterbi decoding. After selection of which specific...... potentially useful.Algorithms for frame synchronization are described and analyzed. Further, the high level architecture of units that contain frame synchronization and various other functions needed in a complete system is presented. Two such units are described, one for placement before the Viterbi decoder...... towards a realization in an FPGA.Node synchronization performed within a Viterbi decoder is discussed, and the high level architectures of three possible implementations of Viterbi decoders are described: The first implementation uses a number of commercially available decoders while the the two others...

A Scalable Architecture of a Structured LDPC Decoder

Science.gov (United States)

Lee, Jason Kwok-San; Lee, Benjamin; Thorpe, Jeremy; Andrews, Kenneth; Dolinar, Sam; Hamkins, Jon

2004-01-01

We present a scalable decoding architecture for a certain class of structured LDPC codes. The codes are designed using a small (n,r) protograph that is replicated Z times to produce a decoding graph for a (Z x n, Z x r) code. Using this architecture, we have implemented a decoder for a (4096,2048) LDPC code on a Xilinx Virtex-II 2000 FPGA, and achieved decoding speeds of 31 Mbps with 10 fixed iterations. The implemented message-passing algorithm uses an optimized 3-bit non-uniform quantizer that operates with 0.2dB implementation loss relative to a floating point decoder.

From "rest" to language task: Task activation selects and prunes from broader resting-state network.

Science.gov (United States)

Doucet, Gaelle E; He, Xiaosong; Sperling, Michael R; Sharan, Ashwini; Tracy, Joseph I

2017-05-01

Resting-state networks (RSNs) show spatial patterns generally consistent with networks revealed during cognitive tasks. However, the exact degree of overlap between these networks has not been clearly quantified. Such an investigation shows promise for decoding altered functional connectivity (FC) related to abnormal language functioning in clinical populations such as temporal lobe epilepsy (TLE). In this context, we investigated the network configurations during a language task and during resting state using FC. Twenty-four healthy controls, 24 right and 24 left TLE patients completed a verb generation (VG) task and a resting-state fMRI scan. We compared the language network revealed by the VG task with three FC-based networks (seeding the left inferior frontal cortex (IFC)/Broca): two from the task (ON, OFF blocks) and one from the resting state. We found that, for both left TLE patients and controls, the RSN recruited regions bilaterally, whereas both VG-on and VG-off conditions produced more left-lateralized FC networks, matching more closely with the activated language network. TLE brings with it variability in both task-dependent and task-independent networks, reflective of atypical language organization. Overall, our findings suggest that our RSN captured bilateral activity, reflecting a set of prepotent language regions. We propose that this relationship can be best understood by the notion of pruning or winnowing down of the larger language-ready RSN to carry out specific task demands. Our data suggest that multiple types of network analyses may be needed to decode the association between language deficits and the underlying functional mechanisms altered by disease. Hum Brain Mapp 38:2540-2552, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Integrating robotic action with biologic perception: A brain-machine symbiosis theory

Science.gov (United States)

Mahmoudi, Babak

In patients with motor disability the natural cyclic flow of information between the brain and external environment is disrupted by their limb impairment. Brain-Machine Interfaces (BMIs) aim to provide new communication channels between the brain and environment by direct translation of brain's internal states into actions. For enabling the user in a wide range of daily life activities, the challenge is designing neural decoders that autonomously adapt to different tasks, environments, and to changes in the pattern of neural activity. In this dissertation, a novel decoding framework for BMIs is developed in which a computational agent autonomously learns how to translate neural states into action based on maximization of a measure of shared goal between user and the agent. Since the agent and brain share the same goal, a symbiotic relationship between them will evolve therefore this decoding paradigm is called a Brain-Machine Symbiosis (BMS) framework. A decoding agent was implemented within the BMS framework based on the Actor-Critic method of Reinforcement Learning. The rule of the Actor as a neural decoder was to find mapping between the neural representation of motor states in the primary motor cortex (MI) and robot actions in order to solve reaching tasks. The Actor learned the optimal control policy using an evaluative feedback that was estimated by the Critic directly from the user's neural activity of the Nucleus Accumbens (NAcc). Through a series of computational neuroscience studies in a cohort of rats it was demonstrated that NAcc could provide a useful evaluative feedback by predicting the increase or decrease in the probability of earning reward based on the environmental conditions. Using a closed-loop BMI simulator it was demonstrated the Actor-Critic decoding architecture was able to adapt to different tasks as well as changes in the pattern of neural activity. The custom design of a dual micro-wire array enabled simultaneous implantation of MI and

Evaluation framework for K-best sphere decoders

KAUST Repository

Shen, Chungan

2010-08-01

While Maximum-Likelihood (ML) is the optimum decoding scheme for most communication scenarios, practical implementation difficulties limit its use, especially for Multiple Input Multiple Output (MIMO) systems with a large number of transmit or receive antennas. Tree-searching type decoder structures such as Sphere decoder and K-best decoder present an interesting trade-off between complexity and performance. Many algorithmic developments and VLSI implementations have been reported in literature with widely varying performance to area and power metrics. In this semi-tutorial paper we present a holistic view of different Sphere decoding techniques and K-best decoding techniques, identifying the key algorithmic and implementation trade-offs. We establish a consistent benchmark framework to investigate and compare the delay cost, power cost, and power-delay-product cost incurred by each method. Finally, using the framework, we propose and analyze a novel architecture and compare that to other published approaches. Our goal is to explicitly elucidate the overall advantages and disadvantages of each proposed algorithms in one coherent framework. © 2010 World Scientific Publishing Company.

Effects of dual task difficulty in motor and cognitive performance: Differences between adults and adolescents.

Science.gov (United States)

Bustillo-Casero, Pilar; Villarrasa-Sapiña, Israel; García-Massó, Xavier

2017-10-01

In the present study our aim was to compare dual-task performance in thirteen adolescents and fifteen young adults while concurrently performing a cognitive and a motor task. The postural control variables were obtained under three different conditions: i) bipedal stance, ii) tandem stance and iii) unipedal stance. The cognitive task consisted of a backward digit span test in which the participants were asked to memorize a sequence of numbers and then repeat the number in reverse order at three different difficulty levels (i.e. with 3, 4 and 5 digits). The difficulty of the cognitive task was seen to have different effects on adolescents and young adults. Adolescents seem to prioritize postural control during high difficulty postural conditions while a cross-domain competition model appeared in easy postural conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Motor Cortex Activity During Functional Motor Skills: An fNIRS Study.

Science.gov (United States)

Nishiyori, Ryota; Bisconti, Silvia; Ulrich, Beverly

2016-01-01

Assessments of brain activity during motor task performance have been limited to fine motor movements due to technological constraints presented by traditional neuroimaging techniques, such as functional magnetic resonance imaging. Functional near-infrared spectroscopy (fNIRS) offers a promising method by which to overcome these constraints and investigate motor performance of functional motor tasks. The current study used fNIRS to quantify hemodynamic responses within the primary motor cortex in twelve healthy adults as they performed unimanual right, unimanual left, and bimanual reaching, and stepping in place. Results revealed that during both unimanual reaching tasks, the contralateral hemisphere showed significant activation in channels located approximately 3 cm medial to the C3 (for right-hand reach) and C4 (for left-hand reach) landmarks. Bimanual reaching and stepping showed activation in similar channels, which were located bilaterally across the primary motor cortex. The medial channels, surrounding Cz, showed significantly higher activations during stepping when compared to bimanual reaching. Our results extend the viability of fNIRS to study motor function and build a foundation for future investigation of motor development in infants during nascent functional behaviors and monitor how they may change with age or practice.

Can Emotional and Behavioral Dysregulation in Youth Be Decoded from Functional Neuroimaging?

Directory of Open Access Journals (Sweden)

Liana C L Portugal

Full Text Available High comorbidity among pediatric disorders characterized by behavioral and emotional dysregulation poses problems for diagnosis and treatment, and suggests that these disorders may be better conceptualized as dimensions of abnormal behaviors. Furthermore, identifying neuroimaging biomarkers related to dimensional measures of behavior may provide targets to guide individualized treatment. We aimed to use functional neuroimaging and pattern regression techniques to determine whether patterns of brain activity could accurately decode individual-level severity on a dimensional scale measuring behavioural and emotional dysregulation at two different time points.A sample of fifty-seven youth (mean age: 14.5 years; 32 males was selected from a multi-site study of youth with parent-reported behavioral and emotional dysregulation. Participants performed a block-design reward paradigm during functional Magnetic Resonance Imaging (fMRI. Pattern regression analyses consisted of Relevance Vector Regression (RVR and two cross-validation strategies implemented in the Pattern Recognition for Neuroimaging toolbox (PRoNTo. Medication was treated as a binary confounding variable. Decoded and actual clinical scores were compared using Pearson's correlation coefficient (r and mean squared error (MSE to evaluate the models. Permutation test was applied to estimate significance levels.Relevance Vector Regression identified patterns of neural activity associated with symptoms of behavioral and emotional dysregulation at the initial study screen and close to the fMRI scanning session. The correlation and the mean squared error between actual and decoded symptoms were significant at the initial study screen and close to the fMRI scanning session. However, after controlling for potential medication effects, results remained significant only for decoding symptoms at the initial study screen. Neural regions with the highest contribution to the pattern regression model

Brief Overview of Motor Learning and It's Application to Rehabilitation: Part Ⅰ: Motor Learning Theory

Institute of Scientific and Technical Information of China (English)

Christopher A Zaino

2003-01-01

@@ 1 DEFINITION OF MOTOR LEARNING Motor learning is the study of how we acquire and modify movements.1 The acquisition of motor skills is the process of learning how to do a particular movement (performance), but the real key to therapeutic intervention is being able to affect permanent changes in motor skills via the process of motor learning. Therefore, motor learning is defined as the ability to retain the ability to perform a motor task at a later time. In rehabilitation, it is important to be cognizant of the concepts of acquisition and retention. We can facilitate acquisition,but do little to assist in the retention of the task (learning). Conversely, we can arrange practice such that acquisition is slowed, but we can actually be assisting learning the task. It is important to have a clear goal in mind and work towards the eventual learning of the task to allow full functional use of that skill.

Orientation decoding: Sense in spirals?

Science.gov (United States)

Clifford, Colin W G; Mannion, Damien J

2015-04-15

The orientation of a visual stimulus can be successfully decoded from the multivariate pattern of fMRI activity in human visual cortex. Whether this capacity requires coarse-scale orientation biases is controversial. We and others have advocated the use of spiral stimuli to eliminate a potential coarse-scale bias-the radial bias toward local orientations that are collinear with the centre of gaze-and hence narrow down the potential coarse-scale biases that could contribute to orientation decoding. The usefulness of this strategy is challenged by the computational simulations of Carlson (2014), who reported the ability to successfully decode spirals of opposite sense (opening clockwise or counter-clockwise) from the pooled output of purportedly unbiased orientation filters. Here, we elaborate the mathematical relationship between spirals of opposite sense to confirm that they cannot be discriminated on the basis of the pooled output of unbiased or radially biased orientation filters. We then demonstrate that Carlson's (2014) reported decoding ability is consistent with the presence of inadvertent biases in the set of orientation filters; biases introduced by their digital implementation and unrelated to the brain's processing of orientation. These analyses demonstrate that spirals must be processed with an orientation bias other than the radial bias for successful decoding of spiral sense. Copyright © 2014 Elsevier Inc. All rights reserved.

O2-GIDNC: Beyond instantly decodable network coding

KAUST Repository

Aboutorab, Neda

2013-06-01

In this paper, we are concerned with extending the graph representation of generalized instantly decodable network coding (GIDNC) to a more general opportunistic network coding (ONC) scenario, referred to as order-2 GIDNC (O2-GIDNC). In the O2-GIDNC scheme, receivers can store non-instantly decodable packets (NIDPs) comprising two of their missing packets, and use them in a systematic way for later decodings. Once this graph representation is found, it can be used to extend the GIDNC graph-based analyses to the proposed O2-GIDNC scheme with a limited increase in complexity. In the proposed O2-GIDNC scheme, the information of the stored NIDPs at the receivers and the decoding opportunities they create can be exploited to improve the broadcast completion time and decoding delay compared to traditional GIDNC scheme. The completion time and decoding delay minimizing algorithms that can operate on the new O2-GIDNC graph are further described. The simulation results show that our proposed O2-GIDNC improves the completion time and decoding delay performance of the traditional GIDNC. © 2013 IEEE.

On decoding of multi-level MPSK modulation codes

Science.gov (United States)

Lin, Shu; Gupta, Alok Kumar

1990-01-01

The decoding problem of multi-level block modulation codes is investigated. The hardware design of soft-decision Viterbi decoder for some short length 8-PSK block modulation codes is presented. An effective way to reduce the hardware complexity of the decoder by reducing the branch metric and path metric, using a non-uniform floating-point to integer mapping scheme, is proposed and discussed. The simulation results of the design are presented. The multi-stage decoding (MSD) of multi-level modulation codes is also investigated. The cases of soft-decision and hard-decision MSD are considered and their performance are evaluated for several codes of different lengths and different minimum squared Euclidean distances. It is shown that the soft-decision MSD reduces the decoding complexity drastically and it is suboptimum. The hard-decision MSD further simplifies the decoding while still maintaining a reasonable coding gain over the uncoded system, if the component codes are chosen properly. Finally, some basic 3-level 8-PSK modulation codes using BCH codes as component codes are constructed and their coding gains are found for hard decision multistage decoding.

Multi-stage decoding of multi-level modulation codes

Science.gov (United States)

Lin, Shu; Kasami, Tadao; Costello, Daniel J., Jr.

1991-01-01

Various types of multi-stage decoding for multi-level modulation codes are investigated. It is shown that if the component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. Particularly, it is shown that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum soft-decision decoding of the code is very small, only a fraction of dB loss in signal to noise ratio at a bit error rate (BER) of 10(exp -6).

Decoding Grasping Movements from the Parieto-Frontal Reaching Circuit in the Nonhuman Primate.

Science.gov (United States)

Nelissen, Koen; Fiave, Prosper Agbesi; Vanduffel, Wim

2018-04-01

Prehension movements typically include a reaching phase, guiding the hand toward the object, and a grip phase, shaping the hand around it. The dominant view posits that these components rely upon largely independent parieto-frontal circuits: a dorso-medial circuit involved in reaching and a dorso-lateral circuit involved in grasping. However, mounting evidence suggests a more complex arrangement, with dorso-medial areas contributing to both reaching and grasping. To investigate the role of the dorso-medial reaching circuit in grasping, we trained monkeys to reach-and-grasp different objects in the dark and determined if hand configurations could be decoded from functional magnetic resonance imaging (MRI) responses obtained from the reaching and grasping circuits. Indicative of their established role in grasping, object-specific grasp decoding was found in anterior intraparietal (AIP) area, inferior parietal lobule area PFG and ventral premotor region F5 of the lateral grasping circuit, and primary motor cortex. Importantly, the medial reaching circuit also conveyed robust grasp-specific information, as evidenced by significant decoding in parietal reach regions (particular V6A) and dorsal premotor region F2. These data support the proposed role of dorso-medial "reach" regions in controlling aspects of grasping and demonstrate the value of complementing univariate with more sensitive multivariate analyses of functional MRI (fMRI) data in uncovering information coding in the brain.

Binary Systematic Network Coding for Progressive Packet Decoding

OpenAIRE

Jones, Andrew L.; Chatzigeorgiou, Ioannis; Tassi, Andrea

2015-01-01

We consider binary systematic network codes and investigate their capability of decoding a source message either in full or in part. We carry out a probability analysis, derive closed-form expressions for the decoding probability and show that systematic network coding outperforms conventional net- work coding. We also develop an algorithm based on Gaussian elimination that allows progressive decoding of source packets. Simulation results show that the proposed decoding algorithm can achieve ...

Power decoding Reed-Solomon codes up to the Johnson radius

DEFF Research Database (Denmark)

Rosenkilde, Johan Sebastian Heesemann

2018-01-01

Power decoding, or "decoding using virtual interleaving" is a technique for decoding Reed-Solomon codes up to the Sudan radius. Since the method's inception, it has been an open question if it is possible to use this approach to decode up to the Johnson radius - the decoding radius of the Guruswami...

Application of Beyond Bound Decoding for High Speed Optical Communications

DEFF Research Database (Denmark)

Li, Bomin; Larsen, Knud J.; Vegas Olmos, Juan José

2013-01-01

This paper studies the application of beyond bound decoding method for high speed optical communications. This hard-decision decoding method outperforms traditional minimum distance decoding method, with a total net coding gain of 10.36 dB.......This paper studies the application of beyond bound decoding method for high speed optical communications. This hard-decision decoding method outperforms traditional minimum distance decoding method, with a total net coding gain of 10.36 dB....

Changes in ipsilateral motor cortex activity during a unilateral isometric finger task are dependent on the muscle contraction force

International Nuclear Information System (INIS)

Shibuya, Kenichi; Kuboyama, Naomi; Tanaka, Junya

2014-01-01

It is possible to examine bilateral primary motor cortex (M1) activation during a sustained motor task using near-infrared spectroscopy (NIRS), in which it is assumed that increased oxygenation reflects cortical activation. The purpose of this study was to examine bilateral M1 activation in response to graded levels of force production during a unilateral finger task. Ten healthy right-handed male subjects participated in this study. NIRS probes were placed over the cortex to measure M1 activity while the subjects performed the finger task. The subjects performed a 10 s finger task at 20%, 40%, and 60% of the maximal voluntary contraction (MVC). Symmetrical activation was found over both M1 areas at all force levels investigated. In the contralateral M1, there were significant differences in oxygenation between 20% and 60% MVC, as well as between 40% and 60% MVC. In the ipsilateral M1, there were significant differences among all force levels. These results indicate the ipsilateral M1 takes part in muscle force control. (paper)

Polar Coding with CRC-Aided List Decoding

Science.gov (United States)

2015-08-01

TECHNICAL REPORT 2087 August 2015 Polar Coding with CRC-Aided List Decoding David Wasserman Approved...list decoding . RESULTS Our simulation results show that polar coding can produce results very similar to the FEC used in the Digital Video...standard. RECOMMENDATIONS In any application for which the DVB-S2 FEC is considered, polar coding with CRC-aided list decod - ing with N = 65536

Spatial attention and reading ability: ERP correlates of flanker and cue-size effects in good and poor adult phonological decoders.

Science.gov (United States)

Matthews, Allison Jane; Martin, Frances Heritage

2015-12-01

To investigate facilitatory and inhibitory processes during selective attention among adults with good (n=17) and poor (n=14) phonological decoding skills, a go/nogo flanker task was completed while EEG was recorded. Participants responded to a middle target letter flanked by compatible or incompatible flankers. The target was surrounded by a small or large circular cue which was presented simultaneously or 500ms prior. Poor decoders showed a greater RT cost for incompatible stimuli preceded by large cues and less RT benefit for compatible stimuli. Poor decoders also showed reduced modulation of ERPs by cue-size at left hemisphere posterior sites (N1) and by flanker compatibility at right hemisphere posterior sites (N1) and frontal sites (N2), consistent with processing differences in fronto-parietal attention networks. These findings have potential implications for understanding the relationship between spatial attention and phonological decoding in dyslexia. Copyright © 2015 Elsevier Inc. All rights reserved.

Relation between location of a motor unit in the human biceps brachii and its critical firing levels for different tasks

NARCIS (Netherlands)

Gielen, C.C.A.M.; Haar Romeny, B.M. ter; Gon, J.J.D. van der

1984-01-01

Critical firing levels (CFLs) of single motor units (MUs) in the long head of the human biceps brachii muscle were determined in combinations of two isometric tasks: flexion of the elbow, supination of the lower arm, and exorotation of the humerus, as well as the corresponding antagonistic tasks.

Decoding of concatenated codes with interleaved outer codes

DEFF Research Database (Denmark)

Justesen, Jørn; Høholdt, Tom; Thommesen, Christian

2004-01-01

Recently Bleichenbacher et al. proposed a decoding algorithm for interleaved (N, K) Reed-Solomon codes, which allows close to N-K errors to be corrected in many cases. We discuss the application of this decoding algorithm to concatenated codes.......Recently Bleichenbacher et al. proposed a decoding algorithm for interleaved (N, K) Reed-Solomon codes, which allows close to N-K errors to be corrected in many cases. We discuss the application of this decoding algorithm to concatenated codes....

Image transmission system using adaptive joint source and channel decoding

Science.gov (United States)

Liu, Weiliang; Daut, David G.

2005-03-01

In this paper, an adaptive joint source and channel decoding method is designed to accelerate the convergence of the iterative log-dimain sum-product decoding procedure of LDPC codes as well as to improve the reconstructed image quality. Error resilience modes are used in the JPEG2000 source codec, which makes it possible to provide useful source decoded information to the channel decoder. After each iteration, a tentative decoding is made and the channel decoded bits are then sent to the JPEG2000 decoder. Due to the error resilience modes, some bits are known to be either correct or in error. The positions of these bits are then fed back to the channel decoder. The log-likelihood ratios (LLR) of these bits are then modified by a weighting factor for the next iteration. By observing the statistics of the decoding procedure, the weighting factor is designed as a function of the channel condition. That is, for lower channel SNR, a larger factor is assigned, and vice versa. Results show that the proposed joint decoding methods can greatly reduce the number of iterations, and thereby reduce the decoding delay considerably. At the same time, this method always outperforms the non-source controlled decoding method up to 5dB in terms of PSNR for various reconstructed images.

Iterative channel decoding of FEC-based multiple-description codes.

Science.gov (United States)

Chang, Seok-Ho; Cosman, Pamela C; Milstein, Laurence B

2012-03-01

Multiple description coding has been receiving attention as a robust transmission framework for multimedia services. This paper studies the iterative decoding of FEC-based multiple description codes. The proposed decoding algorithms take advantage of the error detection capability of Reed-Solomon (RS) erasure codes. The information of correctly decoded RS codewords is exploited to enhance the error correction capability of the Viterbi algorithm at the next iteration of decoding. In the proposed algorithm, an intradescription interleaver is synergistically combined with the iterative decoder. The interleaver does not affect the performance of noniterative decoding but greatly enhances the performance when the system is iteratively decoded. We also address the optimal allocation of RS parity symbols for unequal error protection. For the optimal allocation in iterative decoding, we derive mathematical equations from which the probability distributions of description erasures can be generated in a simple way. The performance of the algorithm is evaluated over an orthogonal frequency-division multiplexing system. The results show that the performance of the multiple description codes is significantly enhanced.

Modified Decoding Algorithm of LLR-SPA

Directory of Open Access Journals (Sweden)

Zhongxun Wang

2014-09-01

Full Text Available In wireless sensor networks, the energy consumption is mainly occurred in the stage of information transmission. The Low Density Parity Check code can make full use of the channel information to save energy. Because of the widely used decoding algorithm of the Low Density Parity Check code, this paper proposes a new decoding algorithm which is based on the LLR-SPA (Sum-Product Algorithm in Log-Likelihood-domain to improve the accuracy of the decoding algorithm. In the modified algorithm, a piecewise linear function is used to approximate the complicated Jacobi correction term in LLR-SPA decoding algorithm. Construct the tangent by the tangency point to the function of Jacobi correction term, which is based on the first order Taylor Series. In this way, the proposed piecewise linear approximation offers almost a perfect match to the function of Jacobi correction term. Meanwhile, the proposed piecewise linear approximation could avoid the operation of logarithmic which is more suitable for practical application. The simulation results show that the proposed algorithm could improve the decoding accuracy greatly without noticeable variation of the computational complexity.

Real-time minimal-bit-error probability decoding of convolutional codes

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Lee, L.-N.

1974-01-01

A recursive procedure is derived for decoding of rate R = 1/n binary convolutional codes which minimizes the probability of the individual decoding decisions for each information bit, subject to the constraint that the decoding delay be limited to Delta branches. This new decoding algorithm is similar to, but somewhat more complex than, the Viterbi decoding algorithm. A real-time, i.e., fixed decoding delay, version of the Viterbi algorithm is also developed and used for comparison to the new algorithm on simulated channels. It is shown that the new algorithm offers advantages over Viterbi decoding in soft-decision applications, such as in the inner coding system for concatenated coding.

Real-time minimal bit error probability decoding of convolutional codes

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Lee, L. N.

1973-01-01

A recursive procedure is derived for decoding of rate R=1/n binary convolutional codes which minimizes the probability of the individual decoding decisions for each information bit subject to the constraint that the decoding delay be limited to Delta branches. This new decoding algorithm is similar to, but somewhat more complex than, the Viterbi decoding algorithm. A real-time, i.e. fixed decoding delay, version of the Viterbi algorithm is also developed and used for comparison to the new algorithm on simulated channels. It is shown that the new algorithm offers advantages over Viterbi decoding in soft-decision applications such as in the inner coding system for concatenated coding.

Direct migration motion estimation and mode decision to decoder for a low-complexity decoder Wyner-Ziv video coding

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Lei, Ted Chih-Wei; Tseng, Fan-Shuo

2017-07-01

This paper addresses the problem of high-computational complexity decoding in traditional Wyner-Ziv video coding (WZVC). The key focus is the migration of two traditionally high-computationally complex encoder algorithms, namely motion estimation and mode decision. In order to reduce the computational burden in this process, the proposed architecture adopts the partial boundary matching algorithm and four flexible types of block mode decision at the decoder. This approach does away with the need for motion estimation and mode decision at the encoder. The experimental results show that the proposed padding block-based WZVC not only decreases decoder complexity to approximately one hundredth that of the state-of-the-art DISCOVER decoding but also outperforms DISCOVER codec by up to 3 to 4 dB.

The impact of positive, negative and neutral stimuli in a virtual reality cognitive-motor rehabilitation task: a pilot study with stroke patients.

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Cameirão, Mónica S; Faria, Ana Lúcia; Paulino, Teresa; Alves, Júlio; Bermúdez I Badia, Sergi

2016-08-09

Virtual Reality (VR) based methods for stroke rehabilitation have mainly focused on motor rehabilitation, but there is increasing interest in integrating motor and cognitive training to increase similarity to real-world settings. Unfortunately, more research is needed for the definition of which type of content should be used in the design of these tools. One possibility is the use of emotional stimuli, which are known to enhance attentional processes. According to the Socioemotional Selectivity Theory, as people age, the emotional salience arises for positive and neutral, but not for negative stimuli. For this study we developed a cognitive-motor VR task involving attention and short-term memory, and we investigated the impact of using emotional images of varying valence. The task consisted of finding a target image, shown for only two seconds, among fourteen neutral distractors, and selecting it through arm movements. After performing the VR task, a recall task took place and the patients had to identify the target images among a valence-matched number of distractors. Ten stroke patients participated in a within-subjects experiment with three conditions based on the valence of the images: positive, negative and neutral. Eye movements were recorded during VR task performance with an eye tracking system. Our results show decreased attention for negative stimuli in the VR task performance when compared to neutral stimuli. The recall task shows significantly more wrongly identified images (false memories) for negative stimuli than for neutral. Regression and correlation analyses with the Montreal Cognitive Assessment and the Geriatric Depression Scale revealed differential effects of cognitive function and depressive symptomatology in the encoding and recall of positive, negative and neutral images. Further, eye movement data shows reduced search patterns for wrongly selected stimuli containing emotional content. The results of this study suggest that it is feasible

Study of bifurcation behavior of two-dimensional turbo product code decoders

International Nuclear Information System (INIS)

He Yejun; Lau, Francis C.M.; Tse, Chi K.

2008-01-01

Turbo codes, low-density parity-check (LDPC) codes and turbo product codes (TPCs) are high performance error-correction codes which employ iterative algorithms for decoding. Under different conditions, the behaviors of the decoders are different. While the nonlinear dynamical behaviors of turbo code decoders and LDPC decoders have been reported in the literature, the dynamical behavior of TPC decoders is relatively unexplored. In this paper, we investigate the behavior of the iterative algorithm of a two-dimensional TPC decoder when the input signal-to-noise ratio (SNR) varies. The quantity to be measured is the mean square value of the posterior probabilities of the information bits. Unlike turbo decoders or LDPC decoders, TPC decoders do not produce a clear 'waterfall region'. This is mainly because the TPC decoding algorithm does not converge to 'indecisive' fixed points even at very low SNR values

Architecture for time or transform domain decoding of reed-solomon codes

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Shao, Howard M. (Inventor); Truong, Trieu-Kie (Inventor); Hsu, In-Shek (Inventor); Deutsch, Leslie J. (Inventor)

1989-01-01

Two pipeline (255,233) RS decoders, one a time domain decoder and the other a transform domain decoder, use the same first part to develop an errata locator polynomial .tau.(x), and an errata evaluator polynominal A(x). Both the time domain decoder and transform domain decoder have a modified GCD that uses an input multiplexer and an output demultiplexer to reduce the number of GCD cells required. The time domain decoder uses a Chien search and polynomial evaluator on the GCD outputs .tau.(x) and A(x), for the final decoding steps, while the transform domain decoder uses a transform error pattern algorithm operating on .tau.(x) and the initial syndrome computation S(x), followed by an inverse transform algorithm in sequence for the final decoding steps prior to adding the received RS coded message to produce a decoded output message.

Reconciling the influence of task-set switching and motor inhibition processes on stop signal after-effects

Directory of Open Access Journals (Sweden)

Joaquin A. Anguera

2013-09-01

Full Text Available Executive response functions can be affected by preceding events, even if they are no longer associated with the current task at hand. For example, studies utilizing the stop signal task have reported slower response times to ‘GO’ stimuli when the preceding trial involved the presentation of a ‘STOP’ signal. However, the neural mechanisms that underlie this behavioral after-effect are unclear. To address this, behavioral and electroencephalography (EEG measures were examined in 18 young adults (18-30yrs on 'GO' trials following a previously ‘Successful Inhibition’ trial (pSI, a previously ‘Failed Inhibition’ trial (pFI, and a previous ‘GO’ trial (pGO. Like previous research, slower response times were observed during both pSI and pFI trials (i.e., ‘GO’ trials that were preceded by a successful and unsuccessful inhibition trial, respectively compared to pGO trials (i.e., ‘GO’ trials that were preceded by another ‘GO’ trial. Interestingly, response time slowing was greater during pSI trials compared to pFI trials, suggesting executive control is influenced by both task set switching and persisting motor inhibition processes. Follow-up behavioral analyses indicated that these effects resulted from between-trial control adjustments rather than repetition priming effects. Analyses of inter-electrode coherence (IEC and inter-trial coherence (ITC indicated that both pSI and pFI trials showed greater phase synchrony during the inter-trial interval compared to pGO trials. Unlike the IEC findings, differential ITC was present within the beta and alpha frequency bands in line with the observed behavior (pSI > pFI > pGO, suggestive of more consistent phase synchrony involving motor inhibition processes during the ITI at a regional level. These findings suggest that between-trial control adjustments involved with task-set switching and motor inhibition processes influence subsequent performance, providing new insights into the

Motor adaptation capacity as a function of age in carrying out a repetitive assembly task at imposed work paces.

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Gilles, Martine Annie; Guélin, Jean-Charles; Desbrosses, Kévin; Wild, Pascal

2017-10-01

The working population is getting older. Workers must adapt to changing conditions to respond to the efforts required by the tasks they have to perform. In this laboratory-based study, we investigated the capacities of motor adaptation as a function of age and work pace. Two phases were identified in the task performed: a collection phase, involving dominant use of the lower limbs; and an assembly phase, involving bi-manual motor skills. Results showed that senior workers were mainly limited during the collection phase, whereas they had less difficulty completing the assembly phase. However, senior workers did increase the vertical force applied while assembling parts, whatever the work pace. In younger and middle-aged subjects, vertical force was increased only for the faster pace. Older workers could adapt to perform repetitive tasks under different time constraints, but adaptation required greater effort than for younger workers. These results point towards a higher risk of developing musculoskeletal disorders among seniors. Copyright © 2017 Elsevier Ltd. All rights reserved.

Facial decoding in schizophrenia is underpinned by basic visual processing impairments.

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Belge, Jan-Baptist; Maurage, Pierre; Mangelinckx, Camille; Leleux, Dominique; Delatte, Benoît; Constant, Eric

2017-09-01

Schizophrenia is associated with a strong deficit in the decoding of emotional facial expression (EFE). Nevertheless, it is still unclear whether this deficit is specific for emotions or due to a more general impairment for any type of facial processing. This study was designed to clarify this issue. Thirty patients suffering from schizophrenia and 30 matched healthy controls performed several tasks evaluating the recognition of both changeable (i.e. eyes orientation and emotions) and stable (i.e. gender, age) facial characteristics. Accuracy and reaction times were recorded. Schizophrenic patients presented a performance deficit (accuracy and reaction times) in the perception of both changeable and stable aspects of faces, without any specific deficit for emotional decoding. Our results demonstrate a generalized face recognition deficit in schizophrenic patients, probably caused by a perceptual deficit in basic visual processing. It seems that the deficit in the decoding of emotional facial expression (EFE) is not a specific deficit of emotion processing, but is at least partly related to a generalized perceptual deficit in lower-level perceptual processing, occurring before the stage of emotion processing, and underlying more complex cognitive dysfunctions. These findings should encourage future investigations to explore the neurophysiologic background of these generalized perceptual deficits, and stimulate a clinical approach focusing on more basic visual processing. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Effects of aripiprazole and haloperidol on neural activation during a simple motor task in healthy individuals: A functional MRI study.

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Goozee, Rhianna; O'Daly, Owen; Handley, Rowena; Reis Marques, Tiago; Taylor, Heather; McQueen, Grant; Hubbard, Kathryn; Pariante, Carmine; Mondelli, Valeria; Reinders, Antje A T S; Dazzan, Paola

2017-04-01

The dopaminergic system plays a key role in motor function and motor abnormalities have been shown to be a specific feature of psychosis. Due to their dopaminergic action, antipsychotic drugs may be expected to modulate motor function, but the precise effects of these drugs on motor function remain unclear. We carried out a within-subject, double-blind, randomized study of the effects of aripiprazole, haloperidol and placebo on motor function in 20 healthy men. For each condition, motor performance on an auditory-paced task was investigated. We entered maps of neural activation into a random effects general linear regression model to investigate motor function main effects. Whole-brain imaging revealed a significant treatment effect in a distributed network encompassing posterior orbitofrontal/anterior insula cortices, and the inferior temporal and postcentral gyri. Post-hoc comparison of treatments showed neural activation after aripiprazole did not differ significantly from placebo in either voxel-wise or region of interest analyses, with the results above driven primarily by haloperidol. We also observed a simple main effect of haloperidol compared with placebo, with increased task-related recruitment of posterior cingulate and precentral gyri. Furthermore, region of interest analyses revealed greater activation following haloperidol compared with placebo in the precentral and post-central gyri, and the putamen. These diverse modifications in cortical motor activation may relate to the different pharmacological profiles of haloperidol and aripiprazole, although the specific mechanisms underlying these differences remain unclear. Evaluating healthy individuals can allow investigation of the effects of different antipsychotics on cortical activation, independently of either disease-related pathology or previous treatment. Hum Brain Mapp 38:1833-1845, 2017. © 2017 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Decoding subjective mental states from fMRI activity patterns

International Nuclear Information System (INIS)

Tamaki, Masako; Kamitani, Yukiyasu

2011-01-01

In recent years, functional magnetic resonance imaging (fMRI) decoding has emerged as a powerful tool to read out detailed stimulus features from multi-voxel brain activity patterns. Moreover, the method has been extended to perform a primitive form of 'mind-reading,' by applying a decoder 'objectively' trained using stimulus features to more 'subjective' conditions. In this paper, we first introduce basic procedures for fMRI decoding based on machine learning techniques. Second, we discuss the source of information used for decoding, in particular, the possibility of extracting information from subvoxel neural structures. We next introduce two experimental designs for decoding subjective mental states: the 'objective-to-subjective design' and the 'subjective-to-subjective design.' Then, we illustrate recent studies on the decoding of a variety of mental states, such as, attention, awareness, decision making, memory, and mental imagery. Finally, we discuss the challenges and new directions of fMRI decoding. (author)

Decoding of finger trajectory from ECoG using deep learning

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Xie, Ziqian; Schwartz, Odelia; Prasad, Abhishek

2018-06-01

Objective. Conventional decoding pipeline for brain-machine interfaces (BMIs) consists of chained different stages of feature extraction, time-frequency analysis and statistical learning models. Each of these stages uses a different algorithm trained in a sequential manner, which makes it difficult to make the whole system adaptive. The goal was to create an adaptive online system with a single objective function and a single learning algorithm so that the whole system can be trained in parallel to increase the decoding performance. Here, we used deep neural networks consisting of convolutional neural networks (CNN) and a special kind of recurrent neural network (RNN) called long short term memory (LSTM) to address these needs. Approach. We used electrocorticography (ECoG) data collected by Kubanek et al. The task consisted of individual finger flexions upon a visual cue. Our model combined a hierarchical feature extractor CNN and a RNN that was able to process sequential data and recognize temporal dynamics in the neural data. CNN was used as the feature extractor and LSTM was used as the regression algorithm to capture the temporal dynamics of the signal. Main results. We predicted the finger trajectory using ECoG signals and compared results for the least angle regression (LARS), CNN-LSTM, random forest, LSTM model (LSTM_HC, for using hard-coded features) and a decoding pipeline consisting of band-pass filtering, energy extraction, feature selection and linear regression. The results showed that the deep learning models performed better than the commonly used linear model. The deep learning models not only gave smoother and more realistic trajectories but also learned the transition between movement and rest state. Significance. This study demonstrated a decoding network for BMI that involved a convolutional and recurrent neural network model. It integrated the feature extraction pipeline into the convolution and pooling layer and used LSTM layer to capture the

Study of bifurcation behavior of two-dimensional turbo product code decoders

Energy Technology Data Exchange (ETDEWEB)

He Yejun [Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hunghom, Hong Kong (China); Lau, Francis C.M. [Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hunghom, Hong Kong (China)], E-mail: encmlau@polyu.edu.hk; Tse, Chi K. [Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hunghom, Hong Kong (China)

2008-04-15

Turbo codes, low-density parity-check (LDPC) codes and turbo product codes (TPCs) are high performance error-correction codes which employ iterative algorithms for decoding. Under different conditions, the behaviors of the decoders are different. While the nonlinear dynamical behaviors of turbo code decoders and LDPC decoders have been reported in the literature, the dynamical behavior of TPC decoders is relatively unexplored. In this paper, we investigate the behavior of the iterative algorithm of a two-dimensional TPC decoder when the input signal-to-noise ratio (SNR) varies. The quantity to be measured is the mean square value of the posterior probabilities of the information bits. Unlike turbo decoders or LDPC decoders, TPC decoders do not produce a clear 'waterfall region'. This is mainly because the TPC decoding algorithm does not converge to 'indecisive' fixed points even at very low SNR values.

Motor intensive anti-gravity training improves performance in dynamic balance related tasks in persons with Parkinson's disease

DEFF Research Database (Denmark)

Malling, Anne Sofie Bøgh; Jensen, Bente Rona

2016-01-01

, the aim was to study the effect of motor intensive training performed in a safe anti-gravity environment using lower-body positive pressure (LBPP) technology on performance during dynamic balance related tasks. Thirteen male PDP went through an 8-week control period followed by 8 weeks of motor intensive...... antigravity training. Seventeen healthy males constituted a control group (CON). Performance during a five repetition sit-to-stand test (STS; sagittal plane) and a dynamic postural balance test (DPB; transversal plane) was evaluated. Effect measures were completion time, functional rates of force development...

Interpolation decoding method with variable parameters for fractal image compression

International Nuclear Information System (INIS)

He Chuanjiang; Li Gaoping; Shen Xiaona

2007-01-01

The interpolation fractal decoding method, which is introduced by [He C, Yang SX, Huang X. Progressive decoding method for fractal image compression. IEE Proc Vis Image Signal Process 2004;3:207-13], involves generating progressively the decoded image by means of an interpolation iterative procedure with a constant parameter. It is well-known that the majority of image details are added at the first steps of iterations in the conventional fractal decoding; hence the constant parameter for the interpolation decoding method must be set as a smaller value in order to achieve a better progressive decoding. However, it needs to take an extremely large number of iterations to converge. It is thus reasonable for some applications to slow down the iterative process at the first stages of decoding and then to accelerate it afterwards (e.g., at some iteration as we need). To achieve the goal, this paper proposed an interpolation decoding scheme with variable (iteration-dependent) parameters and proved the convergence of the decoding process mathematically. Experimental results demonstrate that the proposed scheme has really achieved the above-mentioned goal

Neural signatures of attention: insights from decoding population activity patterns.

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Sapountzis, Panagiotis; Gregoriou, Georgia G

2018-01-01

Understanding brain function and the computations that individual neurons and neuronal ensembles carry out during cognitive functions is one of the biggest challenges in neuroscientific research. To this end, invasive electrophysiological studies have provided important insights by recording the activity of single neurons in behaving animals. To average out noise, responses are typically averaged across repetitions and across neurons that are usually recorded on different days. However, the brain makes decisions on short time scales based on limited exposure to sensory stimulation by interpreting responses of populations of neurons on a moment to moment basis. Recent studies have employed machine-learning algorithms in attention and other cognitive tasks to decode the information content of distributed activity patterns across neuronal ensembles on a single trial basis. Here, we review results from studies that have used pattern-classification decoding approaches to explore the population representation of cognitive functions. These studies have offered significant insights into population coding mechanisms. Moreover, we discuss how such advances can aid the development of cognitive brain-computer interfaces.

Sub-quadratic decoding of one-point hermitian codes

DEFF Research Database (Denmark)

Nielsen, Johan Sebastian Rosenkilde; Beelen, Peter

2015-01-01

We present the first two sub-quadratic complexity decoding algorithms for one-point Hermitian codes. The first is based on a fast realization of the Guruswami-Sudan algorithm using state-of-the-art algorithms from computer algebra for polynomial-ring matrix minimization. The second is a power...... decoding algorithm: an extension of classical key equation decoding which gives a probabilistic decoding algorithm up to the Sudan radius. We show how the resulting key equations can be solved by the matrix minimization algorithms from computer algebra, yielding similar asymptotic complexities....

Dynamics of intracellular information decoding.

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Kobayashi, Tetsuya J; Kamimura, Atsushi

2011-10-01

A variety of cellular functions are robust even to substantial intrinsic and extrinsic noise in intracellular reactions and the environment that could be strong enough to impair or limit them. In particular, of substantial importance is cellular decision-making in which a cell chooses a fate or behavior on the basis of information conveyed in noisy external signals. For robust decoding, the crucial step is filtering out the noise inevitably added during information transmission. As a minimal and optimal implementation of such an information decoding process, the autocatalytic phosphorylation and autocatalytic dephosphorylation (aPadP) cycle was recently proposed. Here, we analyze the dynamical properties of the aPadP cycle in detail. We describe the dynamical roles of the stationary and short-term responses in determining the efficiency of information decoding and clarify the optimality of the threshold value of the stationary response and its information-theoretical meaning. Furthermore, we investigate the robustness of the aPadP cycle against the receptor inactivation time and intrinsic noise. Finally, we discuss the relationship among information decoding with information-dependent actions, bet-hedging and network modularity.

Dynamics of intracellular information decoding

International Nuclear Information System (INIS)

Kobayashi, Tetsuya J; Kamimura, Atsushi

2011-01-01

A variety of cellular functions are robust even to substantial intrinsic and extrinsic noise in intracellular reactions and the environment that could be strong enough to impair or limit them. In particular, of substantial importance is cellular decision-making in which a cell chooses a fate or behavior on the basis of information conveyed in noisy external signals. For robust decoding, the crucial step is filtering out the noise inevitably added during information transmission. As a minimal and optimal implementation of such an information decoding process, the autocatalytic phosphorylation and autocatalytic dephosphorylation (aPadP) cycle was recently proposed. Here, we analyze the dynamical properties of the aPadP cycle in detail. We describe the dynamical roles of the stationary and short-term responses in determining the efficiency of information decoding and clarify the optimality of the threshold value of the stationary response and its information-theoretical meaning. Furthermore, we investigate the robustness of the aPadP cycle against the receptor inactivation time and intrinsic noise. Finally, we discuss the relationship among information decoding with information-dependent actions, bet-hedging and network modularity

Performance breakdown in optimal stimulus decoding.

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Lubomir Kostal; Lansky, Petr; Pilarski, Stevan

2015-06-01

One of the primary goals of neuroscience is to understand how neurons encode and process information about their environment. The problem is often approached indirectly by examining the degree to which the neuronal response reflects the stimulus feature of interest. In this context, the methods of signal estimation and detection theory provide the theoretical limits on the decoding accuracy with which the stimulus can be identified. The Cramér-Rao lower bound on the decoding precision is widely used, since it can be evaluated easily once the mathematical model of the stimulus-response relationship is determined. However, little is known about the behavior of different decoding schemes with respect to the bound if the neuronal population size is limited. We show that under broad conditions the optimal decoding displays a threshold-like shift in performance in dependence on the population size. The onset of the threshold determines a critical range where a small increment in size, signal-to-noise ratio or observation time yields a dramatic gain in the decoding precision. We demonstrate the existence of such threshold regions in early auditory and olfactory information coding. We discuss the origin of the threshold effect and its impact on the design of effective coding approaches in terms of relevant population size.

Relationships between Task-Oriented Postural Control and Motor Ability in Children and Adolescents with Down Syndrome

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Wang, Hui-Yi; Long, I-Man; Liu, Mei-Fang

2012-01-01

Individuals with Down syndrome (DS) have been characterized by greater postural sway in quiet stance and insufficient motor ability. However, there is a lack of studies to explore the properties of dynamic postural sway, especially under conditions of task-oriented movement. The purpose of this study was to investigate the relationships between…

Equal prefrontal cortex activation between males and females in a motor tasks and different visual imagery perspectives: a functional near-infrared spectroscopy (fNIRS study

Directory of Open Access Journals (Sweden)

Thiago F. Dias Kanthack

2013-09-01

Full Text Available The purpose of this study was to compare the prefrontal cortex (PFC blood flow variation and time on in males and females while performing a motor task and imagery perspectives. Eighteen right handed subjects (11 males and 7 females were volunteers to this study. All subjects went through three randomly conditions, a motor task condition (MT in which they had to do a simple finger tap. The other conditions included practicing imagery in first and third views. During all the conditions, the fNIRS device was attached to the subject forehead to obtain the blood flow; the total time in each task which was measured with a chronometer. No difference had been found in any condition for both sexes in the PFC and time, nor for all subjects integrated in the PFC. Therefore, we conclu-de that both imageries can be used to mentally train a motor task, and probably both sexes can be benefited.

Fine and Gross Motor Task Performance When Using Computer-Based Video Models by Students with Autism and Moderate Intellectual Disability

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Mechling, Linda C.; Swindle, Catherine O.

2013-01-01

This investigation examined the effects of video modeling on the fine and gross motor task performance by three students with a diagnosis of moderate intellectual disability (Group 1) and by three students with a diagnosis of autism spectrum disorder (Group 2). Using a multiple probe design across three sets of tasks, the study examined the…

Eye Gaze Correlates of Motor Impairment in VR Observation of Motor Actions.

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Alves, J; Vourvopoulos, A; Bernardino, A; Bermúdez I Badia, S

2016-01-01

This article is part of the Focus Theme of Methods of Information in Medicine on "Methodologies, Models and Algorithms for Patients Rehabilitation". Identify eye gaze correlates of motor impairment in a virtual reality motor observation task in a study with healthy participants and stroke patients. Participants consisted of a group of healthy subjects (N = 20) and a group of stroke survivors (N = 10). Both groups were required to observe a simple reach-and-grab and place-and-release task in a virtual environment. Additionally, healthy subjects were required to observe the task in a normal condition and a constrained movement condition. Eye movements were recorded during the observation task for later analysis. For healthy participants, results showed differences in gaze metrics when comparing the normal and arm-constrained conditions. Differences in gaze metrics were also found when comparing dominant and non-dominant arm for saccades and smooth pursuit events. For stroke patients, results showed longer smooth pursuit segments in action observation when observing the paretic arm, thus providing evidence that the affected circuitry may be activated for eye gaze control during observation of the simulated motor action. This study suggests that neural motor circuits are involved, at multiple levels, in observation of motor actions displayed in a virtual reality environment. Thus, eye tracking combined with action observation tasks in a virtual reality display can be used to monitor motor deficits derived from stroke, and consequently can also be used for rehabilitation of stroke patients.

Functional Brain Connectivity during Multiple Motor Imagery Tasks in Spinal Cord Injury

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Alkinoos Athanasiou

2018-01-01

Full Text Available Reciprocal communication of the central and peripheral nervous systems is compromised during spinal cord injury due to neurotrauma of ascending and descending pathways. Changes in brain organization after spinal cord injury have been associated with differences in prognosis. Changes in functional connectivity may also serve as injury biomarkers. Most studies on functional connectivity have focused on chronic complete injury or resting-state condition. In our study, ten right-handed patients with incomplete spinal cord injury and ten age- and gender-matched healthy controls performed multiple visual motor imagery tasks of upper extremities and walking under high-resolution electroencephalography recording. Directed transfer function was used to study connectivity at the cortical source space between sensorimotor nodes. Chronic disruption of reciprocal communication in incomplete injury could result in permanent significant decrease of connectivity in a subset of the sensorimotor network, regardless of positive or negative neurological outcome. Cingulate motor areas consistently contributed the larger outflow (right and received the higher inflow (left among all nodes, across all motor imagery categories, in both groups. Injured subjects had higher outflow from left cingulate than healthy subjects and higher inflow in right cingulate than healthy subjects. Alpha networks were less dense, showing less integration and more segregation than beta networks. Spinal cord injury patients showed signs of increased local processing as adaptive mechanism. This trial is registered with NCT02443558.

High-throughput GPU-based LDPC decoding

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Chang, Yang-Lang; Chang, Cheng-Chun; Huang, Min-Yu; Huang, Bormin

2010-08-01

Low-density parity-check (LDPC) code is a linear block code known to approach the Shannon limit via the iterative sum-product algorithm. LDPC codes have been adopted in most current communication systems such as DVB-S2, WiMAX, WI-FI and 10GBASE-T. LDPC for the needs of reliable and flexible communication links for a wide variety of communication standards and configurations have inspired the demand for high-performance and flexibility computing. Accordingly, finding a fast and reconfigurable developing platform for designing the high-throughput LDPC decoder has become important especially for rapidly changing communication standards and configurations. In this paper, a new graphic-processing-unit (GPU) LDPC decoding platform with the asynchronous data transfer is proposed to realize this practical implementation. Experimental results showed that the proposed GPU-based decoder achieved 271x speedup compared to its CPU-based counterpart. It can serve as a high-throughput LDPC decoder.

Effects of hand orientation on motor imagery--event related potentials suggest kinesthetic motor imagery to solve the hand laterality judgment task.

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Jongsma, Marijtje L A; Meulenbroek, Ruud G J; Okely, Judith; Baas, C Marjolein; van der Lubbe, Rob H J; Steenbergen, Bert

2013-01-01

Motor imagery (MI) refers to the process of imagining the execution of a specific motor action without actually producing an overt movement. Two forms of MI have been distinguished: visual MI and kinesthetic MI. To distinguish between these forms of MI we employed an event related potential (ERP) study to measure interference effects induced by hand orientation manipulations in a hand laterality judgement task. We hypothesized that this manipulation should only affect kinesthetic MI but not visual MI. The ERPs elicited by rotated hand stimuli contained the classic rotation related negativity (RRN) with respect to palm view stimuli. We observed that laterally rotated stimuli led to a more marked RRN than medially rotated stimuli. This RRN effect was observed when participants had their hands positioned in either a straight (control) or an inward rotated posture, but not when their hands were positioned in an outward rotated posture. Posture effects on the ERP-RRN have not previously been studied. Apparently, a congruent hand posture (hands positioned in an outward rotated fashion) facilitates the judgement of the otherwise more demanding laterally rotated hand stimuli. These ERP findings support a kinesthetic interpretation of MI involved in solving the hand laterality judgement task. The RRN may be used as a non-invasive marker for kinesthetic MI and seems useful in revealing the covert behavior of MI in e.g. rehabilitation programs.

Potentiation of motor sub-networks for motor control but not working memory: Interaction of dACC and SMA revealed by resting-state directed functional connectivity

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Diwadkar, Vaibhav A.; Asemi, Avisa; Burgess, Ashley; Chowdury, Asadur; Bressler, Steven L.

2017-01-01

The dorsal Anterior Cingulate Cortex (dACC) and the Supplementary Motor Area (SMA) are known to interact during motor coordination behavior. We previously discovered that the directional influences underlying this interaction in a visuo-motor coordination task are asymmetric, with the dACC→SMA influence being significantly greater than that in the reverse direction. To assess the specificity of this effect, here we undertook an analysis of the interaction between dACC and SMA in two distinct contexts. In addition to the motor coordination task, we also assessed these effects during a (n-back) working memory task. We applied directed functional connectivity analysis to these two task paradigms, and also to the rest condition of each paradigm, in which rest blocks were interspersed with task blocks. We report here that the previously known asymmetric interaction between dACC and SMA, with dACC→SMA dominating, was significantly larger in the motor coordination task than the memory task. Moreover the asymmetry between dACC and SMA was reversed during the rest condition of the motor coordination task, but not of the working memory task. In sum, the dACC→SMA influence was significantly greater in the motor task than the memory task condition, and the SMA→dACC influence was significantly greater in the motor rest than the memory rest condition. We interpret these results as suggesting that the potentiation of motor sub-networks during the motor rest condition supports the motor control of SMA by dACC during the active motor task condition. PMID:28278267

A Symbiotic Brain-Machine Interface through Value-Based Decision Making

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Mahmoudi, Babak; Sanchez, Justin C.

2011-01-01

Background In the development of Brain Machine Interfaces (BMIs), there is a great need to enable users to interact with changing environments during the activities of daily life. It is expected that the number and scope of the learning tasks encountered during interaction with the environment as well as the pattern of brain activity will vary over time. These conditions, in addition to neural reorganization, pose a challenge to decoding neural commands for BMIs. We have developed a new BMI framework in which a computational agent symbiotically decoded users' intended actions by utilizing both motor commands and goal information directly from the brain through a continuous Perception-Action-Reward Cycle (PARC). Methodology The control architecture designed was based on Actor-Critic learning, which is a PARC-based reinforcement learning method. Our neurophysiology studies in rat models suggested that Nucleus Accumbens (NAcc) contained a rich representation of goal information in terms of predicting the probability of earning reward and it could be translated into an evaluative feedback for adaptation of the decoder with high precision. Simulated neural control experiments showed that the system was able to maintain high performance in decoding neural motor commands during novel tasks or in the presence of reorganization in the neural input. We then implanted a dual micro-wire array in the primary motor cortex (M1) and the NAcc of rat brain and implemented a full closed-loop system in which robot actions were decoded from the single unit activity in M1 based on an evaluative feedback that was estimated from NAcc. Conclusions Our results suggest that adapting the BMI decoder with an evaluative feedback that is directly extracted from the brain is a possible solution to the problem of operating BMIs in changing environments with dynamic neural signals. During closed-loop control, the agent was able to solve a reaching task by capturing the action and reward

A symbiotic brain-machine interface through value-based decision making.

Directory of Open Access Journals (Sweden)

Babak Mahmoudi

Full Text Available BACKGROUND: In the development of Brain Machine Interfaces (BMIs, there is a great need to enable users to interact with changing environments during the activities of daily life. It is expected that the number and scope of the learning tasks encountered during interaction with the environment as well as the pattern of brain activity will vary over time. These conditions, in addition to neural reorganization, pose a challenge to decoding neural commands for BMIs. We have developed a new BMI framework in which a computational agent symbiotically decoded users' intended actions by utilizing both motor commands and goal information directly from the brain through a continuous Perception-Action-Reward Cycle (PARC. METHODOLOGY: The control architecture designed was based on Actor-Critic learning, which is a PARC-based reinforcement learning method. Our neurophysiology studies in rat models suggested that Nucleus Accumbens (NAcc contained a rich representation of goal information in terms of predicting the probability of earning reward and it could be translated into an evaluative feedback for adaptation of the decoder with high precision. Simulated neural control experiments showed that the system was able to maintain high performance in decoding neural motor commands during novel tasks or in the presence of reorganization in the neural input. We then implanted a dual micro-wire array in the primary motor cortex (M1 and the NAcc of rat brain and implemented a full closed-loop system in which robot actions were decoded from the single unit activity in M1 based on an evaluative feedback that was estimated from NAcc. CONCLUSIONS: Our results suggest that adapting the BMI decoder with an evaluative feedback that is directly extracted from the brain is a possible solution to the problem of operating BMIs in changing environments with dynamic neural signals. During closed-loop control, the agent was able to solve a reaching task by capturing the action and

Clumsiness in fine motor tasks: evidence from the quantitative drawing evaluation of children with Down Syndrome.

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Vimercati, S L; Galli, M; Stella, G; Caiazzo, G; Ancillao, A; Albertini, G

2015-03-01

Drawing tests are commonly used for the clinical evaluation of cognitive capabilities in children with learning disabilities. We analysed quantitatively the drawings of children with Down Syndrome (DS) and of healthy, mental age-matched controls to characterise the features of fine motor skills in DS during a drawing task, with particular attention to clumsiness, a well-known feature of DS gross movements. Twenty-three children with DS and 13 controls hand-copied the figures of a circle, a cross and a square on a sheet. An optoelectronic system allowed the acquisition of the three-dimensional track of the drawing. The participants' posture and upper limb movements were analysed as well. Results showed that the participants with DS tended to draw faster but with less accuracy than controls. While clumsiness in gross movements manifests mainly as slow, less efficient movements, it manifests as high velocity and inaccurate movements in fine motor tasks such as drawing. © 2014 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

Non-physical practice improves task performance in an unstable, perturbed environment: Motor imagery and observational balance training

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Wolfgang eTaube

2014-12-01

Full Text Available For consciously performed motor tasks executed in a defined and constant way, both motor imagery (MI and action observation (AO have been shown to promote motor learning. It is not known whether these forms of non-physical training also improve motor actions when these actions have to be variably applied in an unstable and unpredictable environment. The present study therefore investigated the influence of MI balance training (MI_BT and a balance training combining AO and MI (AO+MI_BT on postural control of undisturbed and disturbed upright stance on unstable ground. As spinal reflex excitability after classical (i.e., physical balance training (BT is generally decreased, we tested whether non-physical BT also has an impact on spinal reflex circuits. Thirty-six participants were randomly allocated into an MI_BT group, in which participants imagined postural exercises, an AO+MI_BT group, in which participants observed videos of other people performing balance exercises and imagined being the person in the video, and a non-active control group (CON. Before and after 4 weeks of non-physical training, balance performance was assessed on a free-moving platform during stance without perturbation and during perturbed stance. Soleus H-reflexes were recorded during stable and unstable stance. The post measurement revealed significantly decreased postural sway during undisturbed and disturbed stance after both MI_BT and AO+MI_BT. Spinal reflex excitability remained unchanged. This is the first study showing that non-physical training (MI_BT and AO+MI_BT not only promotes motor learning of ‘rigid’ postural tasks but also improves performance of highly variable and unpredictable balance actions. These findings may be relevant to improve postural control and thus reduce the risk of falls in temporarily immobilized patients.

Iterative List Decoding of Concatenated Source-Channel Codes

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Hedayat Ahmadreza

2005-01-01

Full Text Available Whenever variable-length entropy codes are used in the presence of a noisy channel, any channel errors will propagate and cause significant harm. Despite using channel codes, some residual errors always remain, whose effect will get magnified by error propagation. Mitigating this undesirable effect is of great practical interest. One approach is to use the residual redundancy of variable length codes for joint source-channel decoding. In this paper, we improve the performance of residual redundancy source-channel decoding via an iterative list decoder made possible by a nonbinary outer CRC code. We show that the list decoding of VLC's is beneficial for entropy codes that contain redundancy. Such codes are used in state-of-the-art video coders, for example. The proposed list decoder improves the overall performance significantly in AWGN and fully interleaved Rayleigh fading channels.

On Lattice Sequential Decoding for The Unconstrained AWGN Channel

KAUST Repository

Abediseid, Walid; Alouini, Mohamed-Slim

2013-01-01

channel has been studied only under the use of the minimum Euclidean distance decoder that is commonly referred to as the \\textit{lattice decoder}. Lattice decoders based on solutions to the NP-hard closest vector problem are very complex to implement

Performance-complexity tradeoff in sequential decoding for the unconstrained AWGN channel

KAUST Repository

Abediseid, Walid

2013-06-01

In this paper, the performance limits and the computational complexity of the lattice sequential decoder are analyzed for the unconstrained additive white Gaussian noise channel. The performance analysis available in the literature for such a channel has been studied only under the use of the minimum Euclidean distance decoder that is commonly referred to as the lattice decoder. Lattice decoders based on solutions to the NP-hard closest vector problem are very complex to implement, and the search for low complexity receivers for the detection of lattice codes is considered a challenging problem. However, the low computational complexity advantage that sequential decoding promises, makes it an alternative solution to the lattice decoder. In this work, we characterize the performance and complexity tradeoff via the error exponent and the decoding complexity, respectively, of such a decoder as a function of the decoding parameter - the bias term. For the above channel, we derive the cut-off volume-to-noise ratio that is required to achieve a good error performance with low decoding complexity. © 2013 IEEE.

Decoding emotional valence from electroencephalographic rhythmic activity.

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Celikkanat, Hande; Moriya, Hiroki; Ogawa, Takeshi; Kauppi, Jukka-Pekka; Kawanabe, Motoaki; Hyvarinen, Aapo

2017-07-01

We attempt to decode emotional valence from electroencephalographic rhythmic activity in a naturalistic setting. We employ a data-driven method developed in a previous study, Spectral Linear Discriminant Analysis, to discover the relationships between the classification task and independent neuronal sources, optimally utilizing multiple frequency bands. A detailed investigation of the classifier provides insight into the neuronal sources related with emotional valence, and the individual differences of the subjects in processing emotions. Our findings show: (1) sources whose locations are similar across subjects are consistently involved in emotional responses, with the involvement of parietal sources being especially significant, and (2) even though the locations of the involved neuronal sources are consistent, subjects can display highly varying degrees of valence-related EEG activity in the sources.

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes

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Lin, Shu

1998-01-01

A code trellis is a graphical representation of a code, block or convolutional, in which every path represents a codeword (or a code sequence for a convolutional code). This representation makes it possible to implement Maximum Likelihood Decoding (MLD) of a code with reduced decoding complexity. The most well known trellis-based MLD algorithm is the Viterbi algorithm. The trellis representation was first introduced and used for convolutional codes [23]. This representation, together with the Viterbi decoding algorithm, has resulted in a wide range of applications of convolutional codes for error control in digital communications over the last two decades. There are two major reasons for this inactive period of research in this area. First, most coding theorists at that time believed that block codes did not have simple trellis structure like convolutional codes and maximum likelihood decoding of linear block codes using the Viterbi algorithm was practically impossible, except for very short block codes. Second, since almost all of the linear block codes are constructed algebraically or based on finite geometries, it was the belief of many coding theorists that algebraic decoding was the only way to decode these codes. These two reasons seriously hindered the development of efficient soft-decision decoding methods for linear block codes and their applications to error control in digital communications. This led to a general belief that block codes are inferior to convolutional codes and hence, that they were not useful. Chapter 2 gives a brief review of linear block codes. The goal is to provide the essential background material for the development of trellis structure and trellis-based decoding algorithms for linear block codes in the later chapters. Chapters 3 through 6 present the fundamental concepts, finite-state machine model, state space formulation, basic structural properties, state labeling, construction procedures, complexity, minimality, and

Singer product apertures—A coded aperture system with a fast decoding algorithm

International Nuclear Information System (INIS)

Byard, Kevin; Shutler, Paul M.E.

2017-01-01

A new type of coded aperture configuration that enables fast decoding of the coded aperture shadowgram data is presented. Based on the products of incidence vectors generated from the Singer difference sets, we call these Singer product apertures. For a range of aperture dimensions, we compare experimentally the performance of three decoding methods: standard decoding, induction decoding and direct vector decoding. In all cases the induction and direct vector methods are several orders of magnitude faster than the standard method, with direct vector decoding being significantly faster than induction decoding. For apertures of the same dimensions the increase in speed offered by direct vector decoding over induction decoding is better for lower throughput apertures.

Singer product apertures—A coded aperture system with a fast decoding algorithm

Energy Technology Data Exchange (ETDEWEB)

Byard, Kevin, E-mail: kevin.byard@aut.ac.nz [School of Economics, Faculty of Business, Economics and Law, Auckland University of Technology, Auckland 1142 (New Zealand); Shutler, Paul M.E. [National Institute of Education, Nanyang Technological University, 1 Nanyang Walk, Singapore 637616 (Singapore)

2017-06-01

A new type of coded aperture configuration that enables fast decoding of the coded aperture shadowgram data is presented. Based on the products of incidence vectors generated from the Singer difference sets, we call these Singer product apertures. For a range of aperture dimensions, we compare experimentally the performance of three decoding methods: standard decoding, induction decoding and direct vector decoding. In all cases the induction and direct vector methods are several orders of magnitude faster than the standard method, with direct vector decoding being significantly faster than induction decoding. For apertures of the same dimensions the increase in speed offered by direct vector decoding over induction decoding is better for lower throughput apertures.

Behavioral decoding of working memory items inside and outside the focus of attention.

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Mallett, Remington; Lewis-Peacock, Jarrod A

2018-03-31

How we attend to our thoughts affects how we attend to our environment. Holding information in working memory can automatically bias visual attention toward matching information. By observing attentional biases on reaction times to visual search during a memory delay, it is possible to reconstruct the source of that bias using machine learning techniques and thereby behaviorally decode the content of working memory. Can this be done when more than one item is held in working memory? There is some evidence that multiple items can simultaneously bias attention, but the effects have been inconsistent. One explanation may be that items are stored in different states depending on the current task demands. Recent models propose functionally distinct states of representation for items inside versus outside the focus of attention. Here, we use behavioral decoding to evaluate whether multiple memory items-including temporarily irrelevant items outside the focus of attention-exert biases on visual attention. Only the single item in the focus of attention was decodable. The other item showed a brief attentional bias that dissipated until it returned to the focus of attention. These results support the idea of dynamic, flexible states of working memory across time and priority. © 2018 New York Academy of Sciences.

Fast decoding algorithms for coded aperture systems

International Nuclear Information System (INIS)

Byard, Kevin

2014-01-01

Fast decoding algorithms are described for a number of established coded aperture systems. The fast decoding algorithms for all these systems offer significant reductions in the number of calculations required when reconstructing images formed by a coded aperture system and hence require less computation time to produce the images. The algorithms may therefore be of use in applications that require fast image reconstruction, such as near real-time nuclear medicine and location of hazardous radioactive spillage. Experimental tests confirm the efficacy of the fast decoding techniques

Sequential decoding of intramuscular EMG signals via estimation of a Markov model.

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Monsifrot, Jonathan; Le Carpentier, Eric; Aoustin, Yannick; Farina, Dario

2014-09-01

This paper addresses the sequential decoding of intramuscular single-channel electromyographic (EMG) signals to extract the activity of individual motor neurons. A hidden Markov model is derived from the physiological generation of the EMG signal. The EMG signal is described as a sum of several action potentials (wavelet) trains, embedded in noise. For each train, the time interval between wavelets is modeled by a process that parameters are linked to the muscular activity. The parameters of this process are estimated sequentially by a Bayes filter, along with the firing instants. The method was tested on some simulated signals and an experimental one, from which the rates of detection and classification of action potentials were above 95% with respect to the reference decomposition. The method works sequentially in time, and is the first to address the problem of intramuscular EMG decomposition online. It has potential applications for man-machine interfacing based on motor neuron activities.

Individualized tracking of self-directed motor learning in group-housed mice performing a skilled lever positioning task in the home cage.

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Silasi, Gergely; Boyd, Jamie D; Bolanos, Federico; LeDue, Jeff M; Scott, Stephen H; Murphy, Timothy H

2018-01-01

Skilled forelimb function in mice is traditionally studied through behavioral paradigms that require extensive training by investigators and are limited by the number of trials individual animals are able to perform within a supervised session. We developed a skilled lever positioning task that mice can perform within their home cage. The task requires mice to use their forelimb to precisely hold a lever mounted on a rotary encoder within a rewarded position to dispense a water reward. A Raspberry Pi microcomputer is used to record lever position during trials and to control task parameters, thus making this low-footprint apparatus ideal for use within animal housing facilities. Custom Python software automatically increments task difficulty by requiring a longer hold duration, or a more accurate hold position, to dispense a reward. The performance of individual animals within group-housed mice is tracked through radio-frequency identification implants, and data stored on the microcomputer may be accessed remotely through an active internet connection. Mice continuously engage in the task for over 2.5 mo and perform ~500 trials/24 h. Mice required ~15,000 trials to learn to hold the lever within a 10° range for 1.5 s and were able to further refine movement accuracy by limiting their error to a 5° range within each trial. These results demonstrate the feasibility of autonomously training group-housed mice on a forelimb motor task. This paradigm may be used in the future to assess functional recovery after injury or cortical reorganization induced by self-directed motor learning. NEW & NOTEWORTHY We developed a low-cost system for fully autonomous training of group-housed mice on a forelimb motor task. We demonstrate the feasibility of tracking both end-point, as well as kinematic performance of individual mice, with each performing thousands of trials over 2.5 mo. The task is run and controlled by a Raspberry Pi microcomputer, which allows for cages to be

Evaluation of EEG Features in Decoding Individual Finger Movements from One Hand

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Ran Xiao

2013-01-01

Full Text Available With the advancements in modern signal processing techniques, the field of brain-computer interface (BCI is progressing fast towards noninvasiveness. One challenge still impeding these developments is the limited number of features, especially movement-related features, available to generate control signals for noninvasive BCIs. A few recent studies investigated several movement-related features, such as spectral features in electrocorticography (ECoG data obtained through a spectral principal component analysis (PCA and direct use of EEG temporal data, and demonstrated the decoding of individual fingers. The present paper evaluated multiple movement-related features under the same task, that is, discriminating individual fingers from one hand using noninvasive EEG. The present results demonstrate the existence of a broadband feature in EEG to discriminate individual fingers, which has only been identified previously in ECoG. It further shows that multiple spectral features obtained from the spectral PCA yield an average decoding accuracy of 45.2%, which is significantly higher than the guess level (P<0.05 and other features investigated (P<0.05, including EEG spectral power changes in alpha and beta bands and EEG temporal data. The decoding of individual fingers using noninvasive EEG is promising to improve number of features for control, which can facilitate the development of noninvasive BCI applications with rich complexity.

LDPC-based iterative joint source-channel decoding for JPEG2000.

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Pu, Lingling; Wu, Zhenyu; Bilgin, Ali; Marcellin, Michael W; Vasic, Bane

2007-02-01

A framework is proposed for iterative joint source-channel decoding of JPEG2000 codestreams. At the encoder, JPEG2000 is used to perform source coding with certain error-resilience (ER) modes, and LDPC codes are used to perform channel coding. During decoding, the source decoder uses the ER modes to identify corrupt sections of the codestream and provides this information to the channel decoder. Decoding is carried out jointly in an iterative fashion. Experimental results indicate that the proposed method requires fewer iterations and improves overall system performance.

Deep Learning Methods for Improved Decoding of Linear Codes

Science.gov (United States)

Nachmani, Eliya; Marciano, Elad; Lugosch, Loren; Gross, Warren J.; Burshtein, David; Be'ery, Yair

2018-02-01