Most previous stroke studies have been performed in heterogeneous patient populations. Moreover, the brain network might demonstrate different recovery dynamics according to lesion location. In this study, we investigated variation in motor network alterations according to lesion location. Forty patients with subcortical ischemic stroke were enrolled. Patients were divided into two groups: 21 patients with supratentorial stroke (STS) and 19 patients with infratentorial stroke (ITS). All patients underwent resting-state functional magnetic resonance imaging and behavioral assessment at 2 weeks and 3 months poststroke. Twenty-four healthy subjects participated as a control group. To compare altered connectivity between groups, measures used in previous studies to evaluate interhemispheric balance and global network reorganization were investigated and the relationship between network measures and motor functions were examined. Cortico-cerebellar connectivity was also extracted to investigate its relationship with interhemispheric connectivity. In the STS group, measures related to interhemispheric balance were disrupted compared to the control group 2 weeks poststroke, while this was not found in the ITS group. During recovery, measures related to global network reorganization in the STS group and measures related to interhemispheric balance in the ITS group demonstrated significant changes, respectively. Moreover, motor functions were correlated with altered network measures in both groups. There was an interactive relationship between cortico-cerebellar and interhemispheric cortical connectivity only in the ITS group. Different changes in the motor network were observed depending on the location of stroke lesions. These results might originate from differences in the interactions between cortico-cerebellar and interhemispheric connectivity.
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http://dx.doi.org/10.1002/hbm.24338 | DOI Listing |
Sensors (Basel)
December 2024
Department of Computer Science, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
This systematic review examines EEG-based imagined speech classification, emphasizing directional words essential for development in the brain-computer interface (BCI). This study employed a structured methodology to analyze approaches using public datasets, ensuring systematic evaluation and validation of results. This review highlights the feature extraction techniques that are pivotal to classification performance.
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December 2024
College of Computer and Information Sciences (CCIS), King Saud University, Riyadh 11543, Saudi Arabia.
One of the most promising applications for electroencephalogram (EEG)-based brain-computer interfaces (BCIs) is motor rehabilitation through motor imagery (MI) tasks. However, current MI training requires physical attendance, while remote MI training can be applied anywhere, facilitating flexible rehabilitation. Providing remote MI training raises challenges to ensuring an accurate recognition of MI tasks by healthcare providers, in addition to managing computation and communication costs.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Electrical Engineering, University of Belgrade, 11000 Belgrade, Serbia.
Traditional tactile brain-computer interfaces (BCIs), particularly those based on steady-state somatosensory-evoked potentials, face challenges such as lower accuracy, reduced bit rates, and the need for spatially distant stimulation points. In contrast, using transient electrical stimuli offers a promising alternative for generating tactile BCI control signals: somatosensory event-related potentials (sERPs). This study aimed to optimize the performance of a novel electrotactile BCI by employing advanced feature extraction and machine learning techniques on sERP signals for the classification of users' selective tactile attention.
View Article and Find Full Text PDFNutrients
December 2024
Department of Neurology, Rutgers University, New Brunswick, NJ 08854, USA.
Background: Coffee and tea are widely consumed beverages, but their long-term effects on cognitive function and aging remain largely unexplored. Lifestyle interventions, particularly dietary habits, offer promising strategies for enhancing cognitive performance and preventing cognitive decline.
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Life (Basel)
December 2024
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