Scales for the clinical evaluation of cerebellar disorders

Clinical scales represent an important tool not only for the initial grading/scoring of disease and assessment of progression, but also for the quantification of therapeutic effects in clinical trials. There are several scales available for the clinical evaluation of cerebellar symptoms. While some scales have been developed and evaluated for specific cerebellar disorders such as Friedreich ataxia, others reliably capture cerebellar symptoms with no respect to the underlying etiology. Each scale has its strengths and weaknesses. Extensive scales are certainly useful for thorough documentation of specific features of certain phenotypes, but this gain of information is not always essential for the purpose of a study. Therefore, compact and manageable scales like the Scale for the Assessment and Rating of Ataxia (SARA) or Brief Ataxia Rating Scale (BARS) are often preferred compared to more complex scales in observational and therapeutic studies.</p

Neural Signatures of Autism Spectrum Disorders: Insights into Brain Network Dynamics

Neuroimaging investigations of autism spectrum disorders (ASDs) have advanced our understanding of atypical brain function and structure, and have recently converged on a model of altered network-level connectivity. Traditional task-based functional magnetic resonance imaging (MRI) and volume-based structural MRI studies have identified widespread atypicalities in brain regions involved in social behavior and other core ASD-related behavioral deficits. More recent advances in MR-neuroimaging methods allow for quantification of brain connectivity using diffusion tensor imaging, functional connectivity, and graph theoretic methods. These newer techniques have moved the field toward a systems-level understanding of ASD etiology, integrating functional and structural measures across distal brain regions. Neuroimaging findings in ASD as a whole have been mixed and at times contradictory, likely due to the vast genetic and phenotypic heterogeneity characteristic of the disorder. Future longitudinal studies of brain development will be crucial to yield insights into mechanisms of disease etiology in ASD sub-populations. Advances in neuroimaging methods and large-scale collaborations will also allow for an integrated approach linking neuroimaging, genetics, and phenotypic data