Biology subjects

Kim, W.-S.

Publications and source records attributed to Kim, W.-S..

6 recordsLinked to original sources

bioRxiv2024

Efficacy of foramen magnum decompression with and without cranioplasty in a rat model of Chiari-like malformation

In veterinary medicine, canine Chiari-like malformation (CLM) disease is surgically managed through foramen magnum decompression (FMD) with cranioplasty. This study aimed to assess the efficacy of cranioplasty surgery by establishing a rat CLM model and then applying FMD with and without cranioplasty and comparing the outcomes. Twenty-four 8-week-old male Sprague-Dawley rats underwent surgery to induce CLM by reducing the caudal cranial fossa volume, mimicking cerebellum herniation. The rats were randomly and equally assigned to three groups: a control group (induced CLM), an FO group (induced CLM rats undergoing FMD only), and a CR group (induced CLM rats undergoing FMD with cranioplasty). At 11 weeks of age, the FO and CR groups underwent FMD surgery. Four weeks later, magnetic resonance imaging (MRI) was used to measure the cisterna magna volume to assess surgical outcomes. Post-surgery MRI revealed that the mean cisterna magna volume was 23.82 {+/-} 1.70, 34.88 {+/-} 4.39, and 29.48 {+/-} 2.20 mm3 in the control, FO, and CR groups, respectively. There was a significant increase in the cisterna magna volume in the FO and CR groups compared to that in the control group (p < 0.05), with the FO group showing a significantly greater increase than the CR group (p < 0.05). These findings suggest that FMD surgery alone is more effective at restoring the cisterna magna volume than FMD surgery with cranioplasty. FMD surgery alone resulted in a greater increase in cisterna magna volume than FMD with cranioplasty in our rat CLM model, suggesting that FMD alone may be more effective to treat canine CLM. These findings challenge the typical approach of combining FMD with cranioplasty in treating canine CLM disease and underscore the need for further investigation into optimizing surgical techniques for CLM.

zoology↗

bioRxiv2024

Motor Hotspot Localization Based on Electroencephalography Using Convolutional Neural Network in Patients with Stroke

BackgroundAlthough transcranial magnetic stimulation (TMS) is the optimal tool for identifying individual motor hotspots for transcranial electrical stimulation (tES), it requires a cumbersome procedure in which patients must visit the hospital each time and rely on expert judgment to determine the motor hotspot. Therefore, in previous study, we proposed electroencephalography (EEG)-based machine learning approach to automatically identify individual motor hotspots. In this study, we proposed an advanced EEG-based motor hotspot identification algorithm using a deep learning model and assessed its clinical feasibility and benefits by applying it to stroke patient EEGs. MethodsEEG data were measured from thirty subjects as they performed a simple hand movement task. We utilized the five types of input data depending on the processing levels to assess the signal processing capability of our proposed deep learning model. The motor hotspot locations were estimated using a two-dimensional convolutional neural network (CNN) model. The error distance between the 3D coordinate information of the individual motor hotspots identified by the TMS (ground truth) and EEGs was calculated using the Euclidean distance. Additionally, we confirmed the clinical benefits of our proposed deep-learning algorithm by applying the EEG of stroke patients. ResultsA mean error distance between the motor hotspot locations identified by TMS and our approach was 2.34 {+/-} 0.19 mm when using raw data from only 9 channels around the motor area. When it was tested on stroke patients, the mean error distance was 1.77 {+/-} 0.15 mm using only 5 channels around the motor area. ConclusionWe have demonstrated that an EEG-based deep learning approach can effectively identify the individual motor hotspots. Moreover, we validated the clinical benefits of our algorithm by successfully implementing it in stroke patients. Our algorithm can be used as an alternative to TMS for identifying motor hotspots and maximizing rehabilitation effectiveness.

bioengineering↗

bioRxiv2022

Investigation of neuromodulatory effect of anodal cerebellar transcranial direct current stimulation on the primary motor cortex using functional near-infrared spectroscopy

BackgroundCerebellar brain inhibition (CBI), a neural connection between the cerebellum and primary motor cortex (M1), has been researched as a target pathway for neuromodulation to improve clinical outcomes in various neurological diseases. However, conflicting results of anodal cerebellar transcranial direct current stimulation (acb-tDCS) on M1 excitability indicate that additional investigation is required to examine its precise effect. Objective/HypothesisThis study aimed to gather evidence of the neuromodulatory effect of acb-tDCS on the M1 using functional near-infrared spectroscopy (fNIRS). MethodsSixteen healthy participants were included in this cross-over study. Participants received real and sham acb-tDCS in a random order, with a minimum one-week washout period between them. The anode and cathode were placed on the right cerebellum and the right buccinator muscle, respectively. Stimulation lasted 20 min at an intensity of 2 mA, and fNIRS data were recorded for 42 min (including a 4 min baseline before stimulation and an 18 min post-stimulation duration) using eight channels attached bilaterally on the M1. Resultsacb-tDCS induced a significant decrease in oxyhemoglobin (HbO) concentration (inhibitory effect) in the left (contralateral) M1, whereas it induced a significant increase in HbO concentration (excitatory effect) in the right (ipsilateral) M1 compared to sham tDCS during (p < 0.05) and after stimulation (p < 0.01) in a group level analysis. At the individual level, variations in the response to acb-tDCS were observed. ConclusionOur findings demonstrate the neuromodulatory effects of acb-tDCS on the bilateral M1 in terms of neuronal hemodynamics.

neuroscience↗

bioRxiv2022

Magneto-acoustic protein nanostructures for non-invasive imaging of tissue mechanics in vivo

Measuring cellular and tissue mechanics inside intact living organisms is essential for interrogating the roles of force in physiological and disease processes, and is a major goal in the field of mechanobiology. However, existing biosensors for 3D tissue mechanics, primarily based on fluorescent emissions and deformable materials, are limited for in vivo measurement due to the limited light penetration and poor material stability inside intact, living organisms. While magneto-motive ultrasound (MMUS), which uses superparamagnetic nanoparticles as imaging contrast agents, has emerged as a promising modality for real-time in vivo imaging of tissue mechanics, it has poor sensitivity and spatiotemporal resolution. To overcome these limitations, we introduce magneto-gas vesicles (MGVs), a unique class of protein nanostructures based on gas vesicles and magnetic nanoparticles that produces differential ultrasound signals in response to varying mechanical properties of surrounding tissues. These hybrid protein nanostructures significantly improve signal strength and detection sensitivity. Furthermore, MGVs enable non-invasive, long-term, and quantitative measurement of mechanical properties within 3D tissues and organs in vivo. We demonstrated the performance of MGV-based mechano-sensors in vitro, in fibrosis models of organoids, and in vivo in mouse liver fibrosis models.

biochemistry↗

bioRxiv2021

An artificial Neural-Network Approach for Motor Hotspot Identification Based on Electroencephalography: A Proof-of-Concept Study

BackgroundTo apply transcranial electrical stimulation (tES) to the motor cortex, motor hotspots are generally identified using motor evoked potentials by transcranial magnetic stimulation (TMS). The objective of this study is to validate the feasibility of a novel electroencephalography (EEG)-based motor-hotspot-identification approach using a machine learning technique as a potential alternative to TMS. MethodsEEG data were measured using 63 channels from thirty subjects as they performed a simple finger tapping task. Power spectral densities of the EEG data were extracted from six frequency bands (delta, theta, alpha, beta, gamma, and full) and were independently used to train and test an artificial neural network for motor hotspot identification. The 3D coordinate information of individual motor hotspots identified by TMS were quantitatively compared with those estimated by our EEG-based motor-hotspot-identification approach to assess its feasibility. ResultsThe minimum mean error distance between the motor hotspot locations identified by TMS and our proposed motor-hotspot-identification approach was 0.22 {+/-} 0.03 cm, demonstrating the proof-of-concept of our proposed EEG-based approach. A mean error distance of 1.32 {+/-} 0.15 cm was measured when using only nine channels attached to the middle of the motor cortex, showing the possibility of practically using the proposed motor-hotspot-identification approach based on a relatively small number of EEG channels. ConclusionWe demonstrated the feasibility of our novel EEG-based motor-hotspot-identification method. It is expected that our approach can be used as an alternative to TMS for motor hotspot identification. In particular, its usability would significantly increase when using a recently developed portable tES device integrated with an EEG device.

bioengineering↗

bioRxiv2021

Immersive virtual prism adaptation therapy with depth sensing camera: A feasibility study with functional near infrared spectroscopy in healthy adults

Unilateral spatial neglect (USN) is common after stroke and associated with poor functional recovery. Prism adaptation (PA) is one of the most supported modality able to ameliorate USN but underapplied due to several issues. Using immersive virtual reality and depth-sensing camera, we developed the virtual prism adaptation therapy (VPAT) to overcome the limitations in conventional PA. In this study, we investigated whether VPAT can induce behavioral adaptations and which cortical area is most significantly activated. Fourteen healthy subjects participated in this study. The experiment consisted of four sequential phases (pre-VAPT, VPAT-10{degrees}, VPAT-20{degrees}, and post-VPAT) with functional near-infrared spectroscopy recordings. Each phase consisted of alternating target pointing and resting (or clicking) blocks. To find out the most significantly activated area during pointing in different phases (VPAT-10{degrees}, VPAT-20{degrees}, and Post-VPAT) in contrast to pointing during the pre-VPAT phase, we analyzed changes in oxyhemoglobin concentration during pointing. The pointing errors of the virtual hand deviated to the right-side during early pointing blocks in the VPAT-10{degrees} and VPAT-20{degrees} phases. There was a left-side deviation of the real hand to the target in the post-VPAT phase. The most significantly activated channels were all located in the right hemisphere, and possible corresponding cortical areas included the dorsolateral prefrontal cortex and frontal eye field. In conclusion, VPAT may induce behavioral adaptation with modulation of the dorsal attentional network. Future clinical trials using multiple sessions of a high degree of rightward deviation VPAT over a more extended period are required in stroke patients with unilateral spatial neglect.

bioengineering↗