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Guide to research techniques in neuroscience
Neuroscience is, by definition, a multidisciplinary field: some scientists study genes and proteins at the molecular level while others study neural circuitry using electrophysiology and high-resolution optics.A single topic can be studied using techniques from genetics, imaging, biochemistry, or electrophysiology.
eBook
Brain signal analysis : advances in neuroelectric and neuromagnetic methods
Recent developments in the tools and techniques of data acquisition and analysis in cognitive electrophysiology.
eBook
Translational Neuroscience
Translational neuroscience is at the heart of clinical advancement in the fields of psychiatry, neurology and neurodevelopmental disorders. Written and edited by leading scientists and clinicians, this is a comprehensive and authoritative analysis of this emerging strategy for developing more effective treatments for brain disorders. Introductory chapters bring together perspectives from both academia and industry, while subsequent sections focus on disease groups, including bipolar disorder and depression, attention deficit hyperactivity disorder, substance abuse, autism, Alzheimer's disease, pain, epilepsy, Parkinson's disease and multiple sclerosis. Each section includes topical introductory and summary chapters, providing an overview and synthesis of the field. Translational Neuroscience: Applications in Psychiatry, Neurology, and Neurodevelopmental Disorders is an important text for clinicians, scientists and students in academic settings, government agencies and industry, as well as those working in the fields of public health and the behavioural sciences.
eBook
Replicability or reproducibility? On the replication crisis in computational neuroscience and sharing only relevant detail
Replicability and reproducibility of computational models has been somewhat understudied by “the replication movement.” In this paper, we draw on methodological studies into the replicability of psychological experiments and on the mechanistic account of explanation to analyze the functions of model replications and model reproductions in computational neuroscience. We contend that model replicability, or independent researchers' ability to obtain the same output using original code and data, and model reproducibility, or independent researchers' ability to recreate a model without original code, serve different functions and fail for different reasons. This means that measures designed to improve model replicability may not enhance (and, in some cases, may actually damage) model reproducibility. We claim that although both are undesirable, low model reproducibility poses more of a threat to long-term scientific progress than low model replicability. In our opinion, low model reproducibility stems mostly from authors' omitting to provide crucial information in scientific papers and we stress that sharing all computer code and data is not a solution. Reports of computational studies should remain selective and include all and only relevant bits of code.
Journal Article
MATLAB for neuroscientists : an introduction to scientific computing in MATLAB
This is the first comprehensive teaching resource and textbook for the teaching of Matlab in the Neurosciences and in Psychology. Matlab is unique in that it can be used to learn the entire empirical and experimental process, including stimulus generation, experimental control, data collection, data analysis and modeling. Thus a wide variety of computational problems can be addressed in a single programming environment. The idea is to empower advanced undergraduates and beginning graduate students by allowing them to design and implement their own analytical tools. As students advance in their research careers, they will have achieved the fluency required to understand and adapt more specialized tools as opposed to treating them as \"black boxes\".
eBook
Guide to Research Techniques in Neuroscience
Neuroscience is, by definition, a multidisciplinary field: some scientists study genes and proteins at the molecular level while others study neural circuitry using electrophysiology and high-resolution optics. A single topic can be studied using techniques from genetics, imaging, biochemistry, or electrophysiology. Therefore, it can be daunting for young scientists or anyone new to neuroscience to learn how to read the primary literature and develop their own experiments.
This volume addresses that gap, gathering multidisciplinary knowledge and providing tools for understanding the neuroscience techniques that are essential to the field, and allowing the reader to design experiments in a variety of neuroscience disciplines.
eBook
Social Buffering of Stress in Development
This review provides a broad overview of my research group’s work on social buffering in human development in the context of the field. Much of the focus is on social buffering of the hypothalamic-pituitary-adrenocortical (HPA) system, one of the two major arms of the mammalian stress system. This focus reflects the centrality of the HPA system in research on social buffering in the fields of developmental psychobiology and developmental science. However, buffering of the cardiovascular and autonomic nervous system is also discussed. The central developmental question in this area derives from attachment theory, which argues that the infant’s experience of stress and arousal regulation in the context of her early attachment relationships is not an immature form of social buffering experienced in adulthood but rather the foundation out of which individual differences in the capacity to gain stress relief from social partners emerges. The emergence of social buffering in infancy, changes in social buffering throughout childhood and adolescence, the influence of early experience on later individual differences in social buffering, and critical gaps in our knowledge are described.
Journal Article