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Specialty: Neuroscience
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Total 286 results found since Jan 2013.
Examining cortical tracking of the speech envelope in post-stroke aphasia
ConclusionCTenv of the syllable-level properties was relatively preserved in individuals with less language impairment. In contrast, higher encoding of word- and phrase-level properties was relatively impaired and was predictive of more severe language impairments. CTenv and treatment response to sentence-level rhythm-based interventions need to be further investigated.
Source: Frontiers in Human Neuroscience - September 14, 2023 Category: Neuroscience Source Type: research
Role of artificial intelligence and machine learning in the diagnosis of cerebrovascular disease
ConclusionThe implementation of AI and ML algorithms to supplement clinical practice has conferred a high degree of accuracy, efficiency, and expedited detection in the clinical and radiographic evaluation and management of ischemic and hemorrhagic strokes, AVMs, and aneurysms. Such algorithms have been explored for further purposes of prognostication for these conditions, with promising preliminary results. Further studies should evaluate the longitudinal implementation of such techniques into hospital networks and residency programs to supplement clinical practice, and the extent to which these techniques improve patient...
Source: Frontiers in Human Neuroscience - September 7, 2023 Category: Neuroscience Source Type: research
A Novel Neurorehabilitation Prognosis Prediction Modeling on Separated Left-Right Hemiplegia Based on Brain-Computer Interfaces Assisted Rehabilitation
It is essential for neuroscience and clinic to estimate the influence of neuro-intervention after brain damage. Most related studies have used Mirrored Contralesional-Ipsilesional hemispheres (MCI) methods flipping the axial neuroimaging on the x-axis in prognosis prediction. But left-right hemispheric asymmetry in the brain has become a consensus. MCI confounds the intrinsic brain asymmetry with the asymmetry caused by unilateral damage, leading to questions about the reliability of the results and difficulties in physiological explanations. We proposed the Separated Left-Right hemiplegia (SLR) method to model left and ri...
Source: IEE Transactions on Neural Systems and Rehabilitation Engineering - August 25, 2023 Category: Neuroscience Source Type: research
A Novel Algorithmic Structure of EEG Channel Attention Combined With Swin Transformer for Motor Patterns Classification
With the development of brain-computer interfaces (BCI) technologies, EEG-based BCI applications have been deployed for medical purposes. Motor imagery (MI), applied to promote neural rehabilitation for stroke patients, is among the most common BCI paradigms that. The Electroencephalogram (EEG) signals, encompassing an extensive range of channels, render the training dataset a high-dimensional construct. This high dimensionality, inherent in such a dataset, tends to challenge traditional deep learning approaches, causing them to potentially disregard the intrinsic correlations amongst these channels. Such an oversight ofte...
Source: IEE Transactions on Neural Systems and Rehabilitation Engineering - August 8, 2023 Category: Neuroscience Source Type: research
An Intelligent Rehabilitation Assessment Method for Stroke Patients Based on Lower Limb Exoskeleton Robot
The 6-min walk distance (6MWD) and the Fugl-Meyer assessment lower-limb subscale (FMA-LE) of the stroke patients provide the critical evaluation standards for the effect of training and guidance of the training programs. However, gait assessment for stroke patients typically relies on manual observation and table scoring, which raises concerns about wasted manpower and subjective observation results. To address this issue, this paper proposes an intelligent rehabilitation assessment method (IRAM) for rehabilitation assessment of the stroke patients based on sensor data of the lower limb exoskeleton robot. Firstly, the feat...
Source: IEE Transactions on Neural Systems and Rehabilitation Engineering - August 4, 2023 Category: Neuroscience Source Type: research
Moderate-intensity cardiovascular exercise performed before motor practice attenuates offline implicit motor learning in stroke survivors but not age-matched neurotypical adults
Exp Brain Res. 2023 Jul 3. doi: 10.1007/s00221-023-06659-w. Online ahead of print.ABSTRACTThe acute impact of cardiovascular exercise on implicit motor learning of stroke survivors is still unknown. We investigated the effects of cardiovascular exercise on implicit motor learning of mild-moderately impaired chronic stroke survivors and neurotypical adults. We addressed whether exercise priming effects are time-dependent (e.g., exercise before or after practice) in the encoding (acquisition) and recall (retention) phases. Forty-five stroke survivors and 45 age-matched neurotypical adults were randomized into three sub-group...
Source: Experimental Brain Research - July 3, 2023 Category: Neuroscience Authors: Giordano Marcio Gatinho Bonuzzi Flavio Henrique Bastos Nicolas Schweighofer Eric Wade Carolee Joyce Winstein Camila Torriani-Pasin Source Type: research
Edaravone Dexborneol Alleviates Neuroinflammation by Reducing Neuroglial Cell Proliferation and Suppresses Neuronal Apoptosis/Autophagy in Vascular Dementia Rats
In this study, we established the VD model of rats by bilateral carotid artery occlusion to explore the neuroprotective effect of EDB and its mechanism. Morris Water Maze test was applied to assess the cognitive function of rats. H&E and TUNEL staining were applied to observe the cellular structure of the hippocampus. Immunofluorescence labeling was used to observe the proliferation of astrocytes and microglia. ELISA was applied to examine the levels of TNF-α, IL-1β and IL-6, and RT-PCR was applied to examine their mRNA expression levels. Western blotting was applied to examine apoptosis-related proteins (Bax, Bcl-2,...
Source: Neurochemical Research - June 20, 2023 Category: Neuroscience Authors: Jiawei Zhang Yining Xiao Hongna Liu Lili Xu Xing Guo Yaran Gao Meixi Li Jing Xu Qianqian Qi Peiyuan Lv 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
The right uncinate fasciculus supports verbal short-term memory in aphasia
Brain Struct Funct. 2023 Apr 2. doi: 10.1007/s00429-023-02628-9. Online ahead of print.ABSTRACTVerbal short-term memory (STM) deficits are associated with language processing impairments in people with aphasia. Importantly, the integrity of STM can predict word learning ability and anomia therapy gains in aphasia. While the recruitment of perilesional and contralesional homologous brain regions has been proposed as a possible mechanism for aphasia recovery, little is known about the white-matter pathways that support verbal STM in post-stroke aphasia. Here, we investigated the relationships between the language-related whi...
Source: Brain Structure and Function - April 3, 2023 Category: Neuroscience Authors: Guillem Oliv é Claudia Pe ñaloza Luc ía Vaquero Matti Laine Nadine Martin Antoni Rodriguez-Fornells Source Type: research
