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Specialty: Neuroscience
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Total 286 results found since Jan 2013.
Re-learning to be different: Increased neural differentiation supports post-stroke language recovery
Publication date: 15 November 2019Source: NeuroImage, Volume 202Author(s): Jeremy J. Purcell, Robert W. Wiley, Brenda RappAbstractIdentifying the neural changes that support recovery of cognitive functions after a brain lesion is important to advance our understanding of human neuroplasticity, which, in turn, forms the basis for the development of effective treatments. To date, the preponderance of neuroimaging studies has focused on localizing changes in average brain activity associated with functional recovery. Here, we took a novel approach by evaluating whether cognitive recovery in chronic stroke is related to increa...
Source: NeuroImage - September 17, 2019 Category: Neuroscience Source Type: research
Potential benefits of music playing in stroke upper limb motor rehabilitation
Publication date: Available online 21 February 2020Source: Neuroscience & Biobehavioral ReviewsAuthor(s): Jennifer Grau-Sánchez, Thomas F. Münte, Eckart Altenmüller, Esther Duarte, Antoni Rodríguez-FornellsAbstractMusic-based interventions have emerged as a promising tool in stroke motor rehabilitation as they integrate most of the principles of motor training and multimodal stimulation. This paper aims to review the use of music in the rehabilitation of upper extremity motor function after stroke. First, we review the evidence supporting current music-based interventions including Music-supported Therapy, Music glove,...
Source: Neuroscience and Biobehavioral Reviews - February 23, 2020 Category: Neuroscience Source Type: research
Iterative Adjustment of Stimulation Timing and Intensity During FES-Assisted Treadmill Walking for Patients After Stroke
Functional electric stimulation (FES) is a common intervention to correct foot drop for patients after stroke. Due to the disturbances from internal time-varying muscle characteristics under electrical stimulation and external environmental uncertainties, most of the existing FES system used pre-set stimulation parameters and cannot achieve good gait performances during FES-assisted walking. Therefore, an adaptive FES control system, which used the iterative learning control to adjust the stimulation intensity based on kinematic data and a linear model to modulate the stimulation timing based on walking speed during FES-as...
Source: IEE Transactions on Neural Systems and Rehabilitation Engineering - May 31, 2020 Category: Neuroscience Source Type: research
Classification of Left-Versus Right-Hand Motor Imagery in Stroke Patients Using Supplementary Data Generated by CycleGAN
This study proposes a surrogate EEG data-generation system based on cycle-consistent adversarial networks (CycleGAN) that can expand the number of training data. This study used EEG2Image based on a modified S-transform (MST) to convert EEG data into EEG-topography. This method retains the frequency-domain characteristics and spatial information of the EEG signals. Then, the CycleGAN is used to learn and generate motor-imagery EEG data of stroke patients. From the visual inspection, there is no difference between the EEG topographies of the generated and original EEG data collected from the stroke patients. Finally, we use...
Source: IEE Transactions on Neural Systems and Rehabilitation Engineering - November 26, 2021 Category: Neuroscience Source Type: research
Monitoring Arm Movements Post-Stroke for Applications in Rehabilitation and Home Settings
Optimal recovery of arm function following stroke requires patients to perform a large number of functional arm movements in clinical therapy sessions, as well as at home. Technology to monitor adherence to this activity would be helpful to patients and clinicians. Current approaches to monitoring arm movements are limited because of challenges in distinguishing between functional and non-functional movements. Here, we present an Arm Rehabilitation Monitor (ARM), a device intended to make such measurements in an unobtrusive manner. The ARM device is based on a single Inertial Measurement Unit (IMU) worn on the wrist and us...
Source: IEE Transactions on Neural Systems and Rehabilitation Engineering - September 2, 2022 Category: Neuroscience Source Type: research
Electric field simulations of transcranial direct current stimulation in children with perinatal stroke
DiscussionIndividualized patient-centered tDCS EF simulations are prudent for clinical trial planning and may provide insight into the efficacy of tDCS interventions in children with PS.
Source: Frontiers in Human Neuroscience - February 2, 2023 Category: Neuroscience Source Type: research
A Novel Model to Generate Heterogeneous and Realistic Time-Series Data for Post-Stroke Rehabilitation Assessment
The application of machine learning-based tele-rehabilitation faces the challenge of limited availability of data. To overcome this challenge, data augmentation techniques are commonly employed to generate synthetic data that reflect the configurations of real data. One such promising data augmentation technique is the Generative Adversarial Network (GAN). However, GANs have been found to suffer from mode collapse, a common issue where the generated data fails to capture all the relevant information from the original dataset. In this paper, we aim to address the problem of mode collapse in GAN-based data augmentation techn...
Source: IEE Transactions on Neural Systems and Rehabilitation Engineering - June 20, 2023 Category: Neuroscience Source Type: research
An active learning approach for stroke lesion segmentation on multimodal MRI data
We report encouraging results over a dataset combining functional, anatomical and diffusion data.
Source: Neurocomputing - November 21, 2014 Category: Neuroscience Source Type: research
The effect of transcranial direct current stimulation on motor sequence learning and upper limb function after stroke
Stroke is a leading cause of adult disability and many people are left with impairments and are dependent on others for activities of daily living (Dobkin, 2005; DOH, 2007; Veerbeek et al., 2011). Strategies to improve plasticity and enhance motor learning are needed. One potential approach is to use transcranial direct current stimulation (tDCS) to enhance the effect of physical therapy.
Source: Clinical Neurophysiology - March 30, 2017 Category: Neuroscience Authors: Melanie K Fleming, John C Rothwell, Laszlo Sztriha, James T Teo, Di J Newham Source Type: research
Behavioral and neurophysiological mechanisms underlying motor skill learning in patients with post-stroke hemiparesis
Skilled actions of daily life such as reaching across a busy table to pick a coffee mug are often performed with accurate, yet fast and efficient arm movements. Such complex skilled actions require optimization of speed and accuracy; and rely on efficient planning and execution (Begliomini et al., 2014; Fang et al., 2015; Orban de Xivry et al., 2017; Stewart et al., 2013). Following a neurological insult such as stroke, skilled arm movements are greatly impaired in the paretic (weaker) arm such that task performance is slow, inaccurate and fragmented (Cirstea et al., 2003; Levin, 1996; Liu et al., 2013; Shaikh et al., 2014...
Source: Clinical Neurophysiology - October 25, 2017 Category: Neuroscience Authors: Shailesh Kantak, Robert McGrath, Nazaneen Zahedi, Dustin Luchmee Source Type: research
Inter- and Intra-Rater Reliability of Computer-Assisted Planimetry in Experimental Stroke Research
ConclusionComputer-assisted planimetry can be an appropriate method to determine hemispheric or ischemic lesion volume in rodents but requires a sufficiently long learning period of approximately two months. Even an experienced investigator can generate data with serious variation. Inter- and intra-rater-dependent bias should be considered during the design and performance of respective studies.
Source: Journal of Neuroscience Methods - November 19, 2018 Category: Neuroscience Source Type: research
Impairment and Compensation in Dexterous Upper-Limb Function After Stroke. From the Direct Consequences of Pyramidal Tract Lesions to Behavioral Involvement of Both Upper-Limbs in Daily Activities
Impairments in dexterous upper limb function are a significant cause of disability following stroke. While the physiological basis of movement deficits consequent to a lesion in the pyramidal tract is well demonstrated, specific mechanisms contributing to optimal recovery are less apparent. Various upper limb interventions (motor learning methods, neurostimulation techniques, robotics, virtual reality, and serious games) are associated with improvements in motor performance, but many patients continue to experience significant limitations with object handling in everyday activities. Exactly how we go about consolidating ad...
Source: Frontiers in Human Neuroscience - June 21, 2021 Category: Neuroscience Source Type: research
Small vessel disease burden predicts functional outcomes in patients with acute ischemic stroke using machine learning
CONCLUSIONS: Our results revealed that different SVD markers had distinct prognostic weights in AIS patients, and SVD burden alone may accurately predict the SVO-AIS patients' prognosis.PMID:36650639 | DOI:10.1111/cns.14071
Source: CNS Neuroscience and Therapeutics - January 17, 2023 Category: Neuroscience Authors: Xueyang Wang Jinhao Lyu Zhihua Meng Xiaoyan Wu Wen Chen Guohua Wang Qingliang Niu Xin Li Yitong Bian Dan Han Weiting Guo Shuai Yang Xiangbing Bian Yina Lan Liuxian Wang Qi Duan Tingyang Zhang Caohui Duan Chenglin Tian Ling Chen Xin Lou MR-STARS Investigat Source Type: research
AI-Driven Stroke Rehabilitation Systems and Assessment: A Systematic Review
This article reviews seminal works from 2013 onwards, qualitatively and quantitatively adapting the PRISMA approach to examine the potential of robot-assisted, virtual reality-based rehabilitation and automated assessments through data-driven learning. Extensive experimentation on KIMORE and UI-PRMD datasets reveal high agreement between automated methods and therapists. Our investigation shows that deep learning with spatio-temporal skeleton data and dynamic attention outperforms others, with an RMSE as low as 0.55. Fully automated rehabilitation is still in development, but, being an active research topic, it could haste...
Source: IEE Transactions on Neural Systems and Rehabilitation Engineering - January 31, 2023 Category: Neuroscience Source Type: research
Learning Post-Stroke Gait Training Strategies by Modeling Patient-Therapist Interaction
For safe and effective robot-aided gait training, it is essential to incorporate the knowledge and expertise of physical therapists. Toward this goal, we directly learn from physical therapists’ demonstrations of manual gait assistance in stroke rehabilitation. Lower-limb kinematics of patients and assistive force applied by therapists to the patient’s leg are measured using a wearable sensing system which includes a custom-made force sensing array. The collected data is then used to characterize a therapist’s strategies in response to unique gait behaviors found within a patient’s gait. Prelimi...
Source: IEE Transactions on Neural Systems and Rehabilitation Engineering - March 23, 2023 Category: Neuroscience Source Type: research
