Explaining deep learning-based representations of resting state functional connectivity data: focusing on interpreting nonlinear patterns in autism spectrum disorder.

Background: Resting state Functional Magnetic Resonance Imaging fMRI (rs-fMRI) has been used extensively to study brain function in psychiatric disorders, yielding insights into brain organization. However, the high dimensionality of the rs-fMRI data presents significant challenges for data analysis. Variational autoencoders (VAEs), a type of neural network, have been instrumental in extracting low-dimensional latent representations of resting state functional connectivity (rsFC) patterns, thereby addressing the complex nonlinear structure of rs-fMRI data.

Application of Delayed Contrast Extravasation Magnetic Resonance Imaging for Depicting Subtle Blood-Brain Barrier Disruption in a Traumatic Brain Injury Model.

The blood-brain barrier (BBB) is composed of brain microvasculature that provides selective transport of solutes from the systemic circulation into the central nervous system to protect the brain and spinal microenvironment. Damage to the BBB in the acute phase after traumatic brain injury (TBI) is recognized as a major underlying mechanism leading to secondary long-term damage. Because of the lack of technological ability to detect subtle BBB disruption (BBBd) in the chronic phase, however, the presence of chronic BBBd is disputable.

Explaining Deep Learning-Based Representations of Resting State Functional Connectivity Data: Focusing on Interpreting Nonlinear Patterns in Autism Spectrum Disorder.

Background: Resting state Functional Magnetic Resonance Imaging fMRI (rs-fMRI) has been used to study brain function in psychiatric disorders, yielding insight into brain organization. However, the high dimensionality of the rs-fMRI data presents challenges, and requires dimensionality reduction before applying machine learning techniques. Neural networks, specifically variational autoencoders (VAEs), have been instrumental in extracting low-dimensional latent representations of resting state functional connectivity patterns, addressing the complex nonlinear structure of rs-fMRI.

BBB opening by low pulsed electric fields, depicted by delayed-contrast MRI, enables efficient delivery of therapeutic doxorubicin doses into mice brains.

Background: Pharmacological treatment of CNS diseases is limited due to the presence of the blood-brain barrier (BBB). Recent years showed significant advancement in the field of CNS drug delivery enablers, with technologies such as MR-guided focused ultrasound reaching clinical trials. This have inspired researchers in the field to invent novel brain barriers opening (BBo) technologies that are required to be simple, fast, safe and efficient.