Functional Magnetic Resonance Imaging

Objective imaging-based biomarker discovery for psychiatric conditions is critical for accurate diagnosis and treatment. Using a machine learning framework, this work investigated the utility of brain's functional network topology (complex network features) extracted from functional magnetic resonance imaging (fMRI) functional connectivity (FC) as viable biomarker of autism spectrum disorder (ASD). To this end, we utilized resting-state fMRI data from the publicly available ABIDE dataset consisting of 432 ASD patients and 556 matched healthy controls.
The use of advanced technological solutions (“neurotechnologies”) can improve the clinical outcomes of neurorehabilitation after stroke. Here, Micera et al. propose a paradigm shift that is based on a deep understanding of the basic mechanisms of natural stroke recovery and technology-assisted neurorehabilitation to improve the clinical effectiveness of neurotechnology.
Background: Memory for music has attracted much recent interest in Alzheimer's disease but the underlying brain mechanisms have not been defined in patients directly. Here we addressed this issue in an Alzheimer's disease cohort using activation fMRI of two core musical memory systems. Methods: We studied 34 patients with younger onset Alzheimer's disease led either by episodic memory decline (typical Alzheimer's disease)or by visuospatial impairment (posterior cortical atrophy)in relation to 19 age-matched healthy individuals.
Obsessive-compulsive disorder is a severe and disabling psychiatric disorder that presents several challenges for neuroscience. Recent advances in its genetic and developmental causation, as well as its neuropsychological basis, are reviewed. Hypotheses concerning an imbalance between goal-directed and habitual behavior together with neural correlates in cortico-striatal circuitry are evaluated and contrasted with metacognitive theories.