Effect of long term enzyme replacement therapy in late onset Pompe disease: A single-centre experience.

Late onset Pompe disease (LOPD) is a slowly progressive metabolic myopathy with variable clinical severity. The advent of enzyme replacement therapy (ERT) has modified the natural course of the disease, though the treatment effect on adult patients is modest compared to infants with the classic form. This study aims to describe the long-term clinical outcome of the Greek LOPD cohort, as assessed by 6 min walk test, muscle strength using MRC grading scale and spirometry.

Decoding Time-Varying Functional Connectivity Networks via Linear Graph Embedding Methods.

An exciting avenue of neuroscientific research involves quantifying the time-varying properties of functional connectivity networks. As a result, many methods have been proposed to estimate the dynamic properties of such networks. However, one of the challenges associated with such methods involves the interpretation and visualization of high-dimensional, dynamic networks.

Real-time estimation of dynamic functional connectivity networks.

Two novel and exciting avenues of neuroscientific research involve the study of task-driven dynamic reconfigurations of functional connectivity networks and the study of functional connectivity in real-time. While the former is a well-established field within neuroscience and has received considerable attention in recent years, the latter remains in its infancy. To date, the vast majority of real-time fMRI studies have focused on a single brain region at a time.

The Automatic Neuroscientist: A framework for optimizing experimental design with closed-loop real-time fMRI.

Functional neuroimaging typically explores how a particular task activates a set of brain regions. Importantly though, the same neural system can be activated by inherently different tasks. To date, there is no approach available that systematically explores whether and how distinct tasks probe the same neural system.

Estimating time-varying brain connectivity networks from functional MRI time series.

At the forefront of neuroimaging is the understanding of the functional architecture of the human brain. In most applications functional networks are assumed to be stationary, resulting in a single network estimated for the entire time course. However recent results suggest that the connectivity between brain regions is highly non-stationary even at rest.