Lesion Area in the Cerebral Cortex Determines the Patterns of Axon Rewiring of Motor and Sensory Corticospinal Tracts After Stroke

The corticospinal tract (CST) is an essential neural pathway for reorganization that recovers motor functions after brain injuries such as stroke. CST comprises multiple pathways derived from different sensorimotor areas of the cerebral cortex; however, the patterns of reorganization in such complex pathways postinjury are largely unknown. Here we comprehensively examined the rewiring patterns of the CST pathways of multiple cerebral origins in a mouse stroke model that varied in size and location in the sensorimotor cortex. We found that spared contralesional motor and sensory CST axons crossed the midline and sprouted into the denervated side of the cervical spinal cord after stroke in a large cortical area. In contrast, the contralesional CST fibers did not sprout in a small stroke, whereas the ipsilesional axons from the spared motor area grew on the denervated side. We further showed that motor and sensory CST axons did not innervate the projecting areas mutually when either one was injured. The present results reveal the basic principles that generate the patterns of CST rewiring, which depend on stroke location and CST subtype. Our data indicate the importance of targeting different neural substrates to restore function among the types of injury.

Influence of stroke infarct location on quality of life assessed in a multivariate lesion-symptom mapping study

Stroke has a deleterious impact on quality of life. However, it is less well known if stroke lesions in different brain regions are associated with reduced quality of life (QoL). We therefore investigated this association by multivariate lesion-symptom mapping. We analyzed magnetic resonance imaging and clinical data from the WAKE-UP trial. European Quality of Life 5 Dimensions (EQ-5D) 3 level questionnaires were completed 90 days after stroke. Lesion symptom mapping was performed using a multivariate machine learning algorithm (support vector regression) based on stroke lesions 22–36 h after stroke. Brain regions with significant associations were explored in reference to white matter tracts. Of 503 randomized patients, 329 were included in the analysis (mean age 65.4 years, SD 11.5; median NIHSS = 6, IQR 4–9; median EQ-5D score 90 days after stroke 1, IQR 0–4, median lesion volume 3.3 ml, IQR 1.1–16.9 ml). After controlling for lesion volume, significant associations between lesions and EQ-5D score were detected for the right putamen, and internal capsules of both hemispheres. Multivariate lesion inference analysis revealed an association between injuries of the cortico-spinal tracts with worse self-reported quality of life 90 days after stroke in comparably small stroke lesions, extending previous reports of the association of striato-capsular lesions with worse functional outcome. Our findings are of value to identify patients at risk of impaired QoL after stroke.

Investigations Regarding Repeatability of Small Strokes of Electrically Activated SMA Wires

This work makes a contribution regearding research of the generation of small strokes of electrically activated shape memory actuator wires. Binary Ni50Ti50 wires of 100 mm length and diameter of 0.3mm are investigated. Within the scope of this work, a test rig has been designed and built to carry out the performed experiments. One side of the wire was fixed while the other side worked against a spring. The spring force provided the resetting of the wire. The spring constant was chosen low to avoid a strong influence of the spring deflection on the force. The activation of the shape memory effect of the wires on this test rig was executed electrically by resistance heating and the adjustment of the mechanical load has been solved by pretensioning the spring. Four series of tests have been carried out to determine the feasibility and operational reliability of small stroke ranges. The focus here is on whether such strokes can be generated at all by means of electrical activation and on the other hand, how precisely these strokes can be achieved repeatably.

Three-Dimensional Holographic Electromagnetic Imaging for Accessing Brain Stroke

The authors recently developed a two-dimensional (2D) holographic electromagnetic induction imaging (HEI) for biomedical imaging applications. However, this method was unable to detect small inclusions accurately. For example, only one of two inclusions can be detected in the reconstructed image if the two inclusions were located at the same XY plane but in different Z-directions. This paper provides a theoretical framework of three-dimensional (3D) HEI to accurately and effectively detect inclusions embedded in a biological object. A numerical system, including a realistic head phantom, a 16-element excitation sensor array, a 16-element receiving sensor array, and image processing model has been developed to evaluate the effectiveness of the proposed method for detecting small stroke. The achieved 3D HEI images have been compared with 2D HEI images. Simulation results show that the 3D HEI method can accurately and effectively identify small inclusions even when two inclusions are located at the same XY plane but in different Z-directions. This preliminary study shows that the proposed method has the potential to develop a useful imaging tool for the diagnosis of neurological diseases and injuries in the future.

PENGENALAN AKSARA BALI DENGAN PENDEKATAN METODE DIRECTION FEATURE DAN AREA BINARY OBJECT FEATURE

The rise of technology has been contributing advances to science, and to human being in making jobs far much easier to do, including pattern recognition. This research focused on character recognition by developing a system capable to recognise images of printed Balinese traditional character, which has a distinct feature of having perceptually similar characters, where each others are often differentiated only by a small stroke or a curve. The system itself took several processes to recognise a character. First, the image containing Balinese characters is preprocessed. Afterwards, two object features are extracted from the image: Direction and Binary Object Area. Both features then tested for similarity using Euclidean distance with the same features already obtained from the control images. From 573 characters tested to the system, 559 are recognized as characters and 526 are correctly recognized as the right character, which yields an overall accuracy of 91.8%. Recognition results are dependent to character spacing condition.