OBJECTIVE: This study determined the clinical utility of an fMRI classification algorithm predicting medication-class of response in patients with challenging mood diagnoses.
The individual course of white matter fiber tracts is an important factor for analysis of white matter characteristics in healthy and diseased brains. Diffusion-weighted MRI tractography in combination with region-based or clustering-based selection ...
This work presents a novel approach to finding linkage/association between multimodal brain imaging data, such as structural MRI (sMRI) and functional MRI (fMRI). Motivated by the machine translation domain, we employ a deep learning model, and consi...
Exploring brain networks is an essential step towards understanding functional organization of the brain, which needs characterization of linear and nonlinear connections based on measurements like EEG or MEG. Conventional measures of connectivity ar...
The Journal of neuroscience : the official journal of the Society for Neuroscience
Jul 16, 2018
Measures of moment-to-moment fluctuations in brain activity of an individual at rest have been shown to be a sensitive and reliable metric for studying pathological brain mechanisms across various chronic pain patient populations. However, the relati...
Quality control (QC) is a fundamental component of any study. Diffusion MRI has unique challenges that make manual QC particularly difficult, including a greater number of artefacts than other MR modalities and a greater volume of data. The gold stan...
Individualized behavioral/cognitive prediction using machine learning (ML) regression approaches is becoming increasingly applied. The specific ML regression algorithm and sample size are two key factors that non-trivially influence prediction accura...
IEEE transactions on pattern analysis and machine intelligence
May 24, 2018
We present a method combining affinity prediction with region agglomeration, which improves significantly upon the state of the art of neuron segmentation from electron microscopy (EM) in accuracy and scalability. Our method consists of a 3D U-Net, t...
Contemporary cognitive neuroscience recognises unconstrained processing varies across individuals, describing variation in meaningful attributes, such as intelligence. It may also have links to patterns of on-going experience. This study examined whe...
Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.