Characteristics of the Structural Connectivity in Patients with Brain Injury and Chronic Health Symptoms: A Pilot Study

Study on Structural Connectivity Characteristics in Patients with Brain Injury and Chronic Health Symptoms Academic Background Traumatic Brain Injury (TBI) is one of the leading causes of post-traumatic death and disability. Even mild to moderate TBIs can result in a complex cluster of symptoms known as “post-concussion syndrome,” which includes he...

Photogrammetry Scans for Neuroanatomy Education - A New Multi-Camera System: Technical Note

Photogrammetry Scans for Neuroanatomy Education - A New Multi-Camera System: Technical Note

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....

Utilizing fMRI to Guide TMS Targets: The Reliability and Sensitivity of fMRI Metrics at 3T and 1.5T

Utilizing fMRI to Guide TMS Targets: The Reliability and Sensitivity of fMRI Metrics at 3T and 1.5T

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...

Sex Differences in the Extent of Acute Axonal Pathologies After Experimental Concussion

Gender Differences in Acute Axonal Pathology Following Experimental Concussion Academic Background Each year, approximately 50 million people worldwide suffer from concussions, also known as mild traumatic brain injuries (TBI). However, for more than 15% of patients, this “mild” brain injury can lead to lasting neurocognitive dysfunction. The exist...

Towards Machine Learning-Based Quantitative Hyperspectral Image Guidance for Brain Tumor Resection

Towards Machine Learning-Based Quantitative Hyperspectral Image Guidance for Brain Tumor Resection

Study on the Role of Machine Learning-Assisted Quantitative Hyperspectral Imaging in Brain Tumor Resection Background Introduction Complete resection of malignant gliomas has always been challenged by the difficulty of distinguishing tumor cells in invasive regions. The background of this study is: In neurosurgery, the application of 5-aminolevulin...