There is currently no unique catalog of cortical GABAergic interneuron types. In 2013, we asked 48 leading neuroscientists to classify 320 interneurons by inspecting images of their morphology. That study was the first to quantify the degree of agreement among neuroscientists in morphology-based interneuron classification, showing high agreement for the chandelier and Martinotti types, yet low agreement for most of the remaining types considered. Here we present the dataset containing the classification choices by the neuroscientists according to interneuron type as well as to five prominent morphological features. These data can be used as crisp or soft training labels for learning supervised machine learning interneuron classifiers, while further analyses can try to pinpoint anatomical characteristics that make an interneuron especially difficult or especially easy to classify.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6805952 | PMC |
http://dx.doi.org/10.1038/s41597-019-0246-8 | DOI Listing |
Bioinformatics
November 2024
Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China.
Motivation: Neuroscientists have long endeavored to map brain connectivity, yet the intricate nature of brain networks often leads them to concentrate on specific regions, hindering efforts to unveil a comprehensive connectivity map. Recent advancements in imaging and text mining techniques have enabled the accumulation of a vast body of literature containing valuable insights into brain connectivity, facilitating the extraction of whole-brain connectivity relations from this corpus. However, the diverse representations of brain region names and connectivity relations pose a challenge for conventional machine learning methods and dictionary-based approaches in identifying all instances accurately.
View Article and Find Full Text PDFNeuroscientist
December 2024
Faculty of Engineering and Science, University of Greenwich London, Chatham Maritime, Kent, UK.
Swelling, stiffness, and pain in synovial joints are primary hallmarks of osteoarthritis and rheumatoid arthritis. Hyperactivity of nociceptors and excessive release of inflammatory factors and pain mediators play a crucial role, with emerging data suggesting extensive remodelling and plasticity of joint innervations. Herein, we review structural, functional, and molecular alterations in sensory and autonomic axons wiring arthritic joints and revisit mechanisms implicated in the sensitization of nociceptors, leading to chronic pain.
View Article and Find Full Text PDFDr. Rachael Dangarembizi is a Senior Lecturer in the Department of Human Biology and a neuroscientist in the Neuroscience Institute at the University of Cape Town in South Africa. She has established the first laboratory in Africa that studies the mechanisms of brain injury caused by fungal neuroinfections.
View Article and Find Full Text PDFPLoS Comput Biol
December 2024
Berlin Institute of Health at Charité, Universitätsmedizin Berlin, Berlin, Germany.
Simulations of large-scale brain dynamics are often impacted by overexcitation resulting from heavy-tailed structural network distributions, leading to biologically implausible simulation results. We implement a homeodynamic plasticity mechanism, known from other modeling work, in the widely used Jansen-Rit neural mass model for The Virtual Brain (TVB) simulation framework. We aim at heterogeneously adjusting the inhibitory coupling weights to reach desired dynamic regimes in each brain region.
View Article and Find Full Text PDFBasic Clin Neurosci
July 2024
Department of Biostatistics, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Introduction: Traumatic brain injury (TBI) is one of the leading causes of death globally and one of the most important diseases indicated by the World Health Organization (WHO). Several studies have concluded that brain damage can dramatically increase functional connectivity (FC) in the brain. The effects of this hyper-connectivity are not yet fully understood and are being studied by neuroscientists.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!