Attitudes in Physics Education: An Alternative Approach to Teaching Physics to Non-Science College Students

In this article, we present an alternative way of teaching conceptual physics for non-science majors by depicting the role of physics in today\u27s technology. The goal of this approach is to increase in the minds of non-science students the acceptance of physics as a useful component in general education, and as a major tool in comprehending the present-day technological world experienced by students outside the classroom

Magnetoencephalography as a tool in psychiatric research: current status and perspective

The application of neuroimaging to provide mechanistic insights into circuit dysfunctions in major psychiatric conditions and the development of biomarkers are core challenges in current psychiatric research. In this review, we propose that recent technological and analytic advances in Magnetoencephalography (MEG), a technique which allows the measurement of neuronal events directly and non-invasively with millisecond resolution, provides novel opportunities to address these fundamental questions. Because of its potential in delineating normal and abnormal brain dynamics, we propose that MEG provides a crucial tool to advance our understanding of pathophysiological mechanisms of major neuropsychiatric conditions, such as Schizophrenia, Autism Spectrum Disorders, and the dementias. In our paper, we summarize the mechanisms underlying the generation of MEG signals and the tools available to reconstruct generators and underlying networks using advanced source-reconstruction techniques. We then survey recent studies that have utilized MEG to examine aberrant rhythmic activity in neuropsychiatric disorders. This is followed by links with preclinical research, which have highlighted possible neurobiological mechanisms, such as disturbances in excitation/inhibition parameters, which could account for measured changes in neural oscillations. In the final section of the paper, challenges as well as novel methodological developments are discussed which could pave the way for a widespread application of MEG in translational research with the aim of developing biomarkers for early detection and diagnosis

Neurology in the 21st century: contemporary state of diagnostics and therapeutics

Although neurological disease has been recognized since antiquity, neurology as a systematic clinical discipline is less than 130 years old. Neurological practice has traditionally been constrained by the complexity of the human nervous system, which has been slow to yield its secrets. Over the last three decades, however, clinical neurology has been transformed in terms of both diagnostics and therapeutics and now marches in lockstep with the cutting edge of medicine. Efficacious treatments are now available for the majority of neurological diseases, including epilepsy, migraine, Guillain-Barre syndrome, Parkinson\u27s disease, multiple sclerosis, and ischemic stroke. This neurological revolution has been enabled by advances in neuroimaging and through the integrated application of basic research, drug development, biotechnology and clinical trial methodology. Neurology in the 21st century is a dynamic specialty offering relief and benefit to many patients, and holding the promise for one day conquering neurological disease in all its manifestations

Focal Spot, Summer/Fall 2009

https://digitalcommons.wustl.edu/focal_spot_archives/1112/thumbnail.jp

Graph analysis of functional brain networks: practical issues in translational neuroscience

The brain can be regarded as a network: a connected system where nodes, or units, represent different specialized regions and links, or connections, represent communication pathways. From a functional perspective communication is coded by temporal dependence between the activities of different brain areas. In the last decade, the abstract representation of the brain as a graph has allowed to visualize functional brain networks and describe their non-trivial topological properties in a compact and objective way. Nowadays, the use of graph analysis in translational neuroscience has become essential to quantify brain dysfunctions in terms of aberrant reconfiguration of functional brain networks. Despite its evident impact, graph analysis of functional brain networks is not a simple toolbox that can be blindly applied to brain signals. On the one hand, it requires a know-how of all the methodological steps of the processing pipeline that manipulates the input brain signals and extract the functional network properties. On the other hand, a knowledge of the neural phenomenon under study is required to perform physiological-relevant analysis. The aim of this review is to provide practical indications to make sense of brain network analysis and contrast counterproductive attitudes