Brain
Researchers at the Jack, Joseph and Morton Mandel School of Applied Social Sciences at Case Western Reserve University have made a groundbreaking discovery in the treatment of schizophrenia. By identifying a specific target in brain function, they have potentially changed the way young patients are treated for the condition. According
Brain
Perception researchers at Johns Hopkins University have developed novel artificial intelligence-generated images that appear to be one thing but reveal a different form when rotated. These "visual anagrams" hold promise for studying human visual perception and have already yielded insights into how people process real-world size effects. Key
Brain
A recent study published in the Epilepsy & Behavior journal has shed new light on the effectiveness of frontal lobe epilepsy surgery in pediatric and adolescent patients. Researchers from the Mayo Clinic in Rochester, Minnesota, conducted a retrospective review of 25 patients who underwent resective or ablative frontal lobe surgery
Brain
In a groundbreaking international collaboration, the Madras Diabetes Research Foundation (MDRF) in Chennai, the Centre for Brain Research (CBR) at the Indian Institute of Science (IISc) in Bengaluru, and the UK Dementia Research Institute (UK DRI) have joined forces to investigate the intricate relationship between diabetes and brain health. This
Brain cancer
Researchers at Technical University Munich (TU Munich) have published a comprehensive study on the quality-adjusted life years (QALYs) of brain tumor patients. The study, which was conducted between 2016 and 2019, aimed to assess the health preferences of patients with eloquent tumors, which are located in brain regions critical for
Brain
A new study published in Neurobiology of Disease has shed light on the pathologic effects of temporal lobe epilepsy (TLE), a disorder characterized by seizures and cognitive inefficiencies. Researchers at Thomas Jefferson University used resting-state functional magnetic resonance imaging (fMRI) and diffusion-weighted magnetic resonance imaging (DW-MRI) to detect dynamic brain
Brain research
New research has shed light on the effectiveness of anterior temporal lobectomy (ATL) in treating patients with drug-resistant epilepsy caused by mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS). The study, conducted by a team of researchers at the National University of Misiones (UNAM) in Mexico City, found that patients
Control systems
Researchers from King Fahd University of Petroleum and Minerals have made significant strides in the field of brain-based devices, developing a real-time classification framework for motor imagery using functional connectivity and ensemble learning. The breakthrough has the potential to revolutionize healthcare and industrial applications by enabling the development of assistive
Brain
Focal leptomeningeal extension, a newly identified entity, has been found to display patterns of intracranial failure similar to parenchymal brain metastases. Researchers at the Dana-Farber Cancer Institute conducted a study to assess whether patients with focal leptomeningeal extension can be managed with stereotactic radiation without excess development of marginal recurrences
Artificial neural networks
Researchers from Tulane University have made significant strides in multimodal neuroimaging data modeling, developing a novel approach that integrates functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), and structural MRI (sMRI) for joint analysis. This breakthrough has led to a deeper understanding of the intricate relationships between the brain&
Artificial neural networks
Researchers from China, collaborating with international teams, have made a significant breakthrough in brain mapping, publishing ten seminal studies on mesoscale brain atlases in leading journals. The studies, published in Cell, Neuron, and other Cell Press journals, demonstrate China's growing expertise and international leadership in mesoscale brain mapping
Artificial neural networks
Researchers at the University of Sevilla have developed an innovative approach to classify brain tumors using ensemble-based deep learning models. This method has shown significant promise in achieving high accuracy while maintaining interpretability for clinical use. By combining the strengths of multiple Convolutional Neural Network (CNN) architectures and incorporating explainability
