Innovative Fusion in Neuron Classification: Shared Information from Human and Mouse Electrophysiological Data The scientific community has long faced significant challenges in neuron classification. Accurate classification of neurons is crucial for understanding brain function in both healthy and diseased states. This study, led by Ofek Ophir, Orit...
A New Breakthrough in Neuroinformatics: Research Report on Cadence Tool for Calcium Event Detection Background Introduction Calcium imaging technology has revolutionized the study of neuron ensembles, providing researchers with a powerful tool to simultaneously visualize and monitor multiple neuronal activities. Calcium imaging utilizes fluorescent...
Functional Brain Connectivity Research Using Bayesian Multiplex Graph Classifier Research Background and Problem Statement In recent years, research on cognitive control in the elderly has garnered increasing attention, especially against the backdrop of accelerating population aging. Understanding cognitive functions in the elderly becomes particu...
Academic Background It is widely recognized that the cognitive function of patients with high-grade glioma is affected by the location and volume of the tumor. However, research on how to accurately predict individual patients’ cognitive function for personalized treatment decisions before and after surgery remains limited. Currently, most studies ...
Neuroinformatics Research: 3D Modeling of Neuroanatomy with Multi-Camera System Academic Background The surgical anatomy of the central nervous system, including the skull and spine, has an extremely complex three-dimensional (3D) structure, making it difficult for learners to fully understand the intricate relationships between various structures....
Image Classification Based on Bayesian Tensor Modeling for Alzheimer’s Disease Introduction Neuroimaging research is a crucial component of contemporary neuroscience, significantly enhancing our understanding of brain structure and function. Through these non-invasive visualization techniques, researchers can more accurately predict the risk of cer...
Identifying Diagnostic Biomarkers for Autism Spectrum Disorder using the PED Algorithm In the field of neuroinformatics, research on Autism Spectrum Disorder (ASD) predominantly focuses on the bidirectional connectivity between brain regions, with fewer studies addressing higher-order interaction anomalies among brain regions. To explore the comple...
Using fMRI to Guide TMS Target Selection: Reliability and Sensitivity of 3T and 1.5T fMRI Metrics [DOI: 10.1007/s12021-024-09667-5], published in Neuroinformatics Background Introduction The early application of functional magnetic resonance imaging (fMRI) mainly focused on inferring cognitive processes. However, modern medicine is gradually extend...
Research Report on the Enhanced Spatial Fuzzy C-Means Algorithm for Brain Tissue Segmentation Academic Background Magnetic Resonance Imaging (MRI) plays a vital role in neurology, particularly in the precise segmentation of brain tissue. Accurate tissue segmentation is crucial for diagnosing brain injuries and neurodegenerative diseases. Segmenting...
MRIO: A Magnetic Resonance Imaging Acquisition and Analysis Ontology Magnetic Resonance Imaging (MRI) is a biomedical imaging technology used to non-invasively visualize internal structures of tissues in three-dimensional space. MRI is widely used in studying the structure and function of the human brain and is a powerful tool for diagnosing neurol...