Principles Of Neural Science (Principles Of Neu...
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Reviewer: Yash D Shah, MD MPH(Northwell Health)Description: Commonly referred to as a "bible" for neuroscientists, this is the sixth edition of, by far, the most complete account of scientific theory on the brain and its physical, mechanical, and biochemical structures.Purpose: The purpose is to highlight the intellectual challenges and excitement of neurological science. The book presents clear descriptions of the basics of neural anatomy, neural science, and brain-behavior.Audience: The information this book presents is not only intended to serve as a starting point for undergraduates, medical students, and graduate students in the neurosciences, but also is immensely useful for neuroscientists and neurologists who want to remain current in the field.Features: Part I provides an overall perspective on the brain, genes, nervous circuitry, and neuroanatomical and computational bases of behavior. Part II examines the molecular biology of cells, which is crucial to an understanding of the complex mechanism of synaptic transmission in part III. Part IV presents an in-depth account of the sensory system, and part V deals with the motor system. Parts VI, VII, and VIII provide the fundamentals of the biology of emotion, motivation, behavior, cognition, and memory. The book ends with discussion of some important diseases of the nervous system.Assessment: This is one of the seminal works that comprehensively catalogs the advances and principles of neuroscience. It is not a beginner's book, yet it is still fairly accessible. It is worth the investment, especially for neuroscientists or neurologists, or readers just deeply interested in the science of the brain and nervous system.
An introduction to the principles by which the neural tube (brain and spinal cord) forms during embryonic development. Subjects include the cellular and molecular mechanisms underlying the formation of a three-dimensional neural tube and its division into forebrain, midbrain, hindbrain, and spinal cord. Three lecture hours a week for one semester. Biology 365N and Biology 367C may not both be counted. Prerequisite: One of the following with a grade of at least C-: Biology 325, Neuroscience 330, 365R.
Introduction to the nervous system with an emphasis on neural development and on the neural mechanisms of memory, emotions, and other higher cognitive functions. Intended for neuroscience majors and those considering neuroscience as a major. Three lecture hours a week for one semester. Only one of the following may be counted: Biology 335, 337 (Topic: Neural Systems II), Neuroscience 335. Prerequisite: The following with a grade of at least C-: Biology 206L, and 311D or 325H; Mathematics 408C or 408S; Neuroscience 330; and Physics 303L, 316, or 317L.
Introduction to the basic principles of pharmacology; including how drugs get into the body, exert their actions, and are metabolized and excreted. Three lecture hours a week for one semester. Biology 365D (Topic: Principles of Drug Action) and Neuroscience 365D may not both be counted. Prerequisite: Neuroscience 335 with a grade of at least C-.
The neurobiological basis of disorders of the brain, with the main focus on mental illness. Emphasizes the neural circuitries and neurochemical events that underlie specific mental processes and behaviors. Three lecture hours a week for one semester. Biology 365T and Neuroscience 365T may not both be counted. Prerequisite: Neuroscience 335 with a grade of at least C-.
Basic principles of image formation and techniques of fluorescent imaging and confocal laser-scanning microscopy. Includes image processing and analysis to extract quantitative information from digital images. Survey of imaging techniques, including electron microscopy and functional MRI. One lecture hour and four laboratory hours a week for one semester. Only one of the following may be counted: Biology 337 (Topic: Microscopy and Fluorescence Imaging Laboratory), 366L, Neuroscience 366L. Prerequisite: Neuroscience 335 with a grade of at least C-.
Overview of the basic mathematical and computational tools central to the analysis of neural systems in a laboratory setting. Subjects include linear algebra, differential equations, filtering, correlation, probability, and inference, with an emphasis on quantitative methodology and applications to neuroscience. Three lecture hours and one and one-half laboratory hours a week for one semester. Prerequisite: Mathematics 408D or 408M, and Neuroscience 335 with a grade of at least C- in each.
Continuation of Neuroscience 466M. Introduction to basic mathematical and computational tools for the analysis of neural systems. Subjects include computational and quantitative methods, with an emphasis on their applications to neuroscience. Three lecture hours and one laboratory hour a week for one semester. Biology 366N and Neuroscience 366N may not both be counted. Prerequisite: Neuroscience 466M with a grade of at least C-.
Studies the principles of experimental design, execution, and interpretation by having students measure their own perceptual and behavioral responses to visual and auditory tests. Includes data analysis, statistical significance, and interpretation. Five laboratory hours a week for one semester. Only one of the following may be counted: Biology 337 (Topic: Visual Neuroscience), 366E, 366P, Neuroscience 366E, 366P. Prerequisite: Neuroscience 335 with a grade of at least C-.
Explores techniques used to study the molecular genetic basis for nervous system function and disease with a powerful invertebrate model system. Subjects will range from studying the conserved molecular basis for our senses and male/female-specific behaviors, to exploring how mutations of conserved neural genes cause neurological disorders, such as Parkinson's disease and Alzheimer's disease. Six laboratory hours a week for one semester. Biology 366S and Neuroscience 366S may not both be counted. Prerequisite: Neuroscience 335 with a grade of at least C-.
Survey of methods for neuroimaging research. Describes the physics of MRI image acquisition, the physiology of neural responses, and the design and analysis of MRI studies. Three lecture hours a week for one semester. Only one of the following may be counted: Biology 337 (Topic: Foundations of Human Neuroimaging), 367F, Neuroscience 367F. Prerequisite: Neuroscience 330 or 365R (or Biology 365R) with a grade of at least C-.
The principles of neuroscience, some would argue, stemmed from the work of Donald Hebb in the 1940s and his book, The Organization of Behavior, published in 1949. Other ground-breaking researchers in the field include Eric R Kandel, Adele Diamond, Joseph LeDoux, Robert Sapolsky, and Antonio Damasio. These are just a few of the stars of the exploding field of neuroscience which continues to fascinate us. As the research explodes, it can be tempting to extrapolate beyond the science and to speculate about what it means. There is a basis in neuroscience or education research for all of the neuromyths or misconcpetions discussed above. So it is critical to evaluate principles and ensure they are applied in the right ways.
What happens when we apply the principles of neuroscience in the right ways? Learning becomes less effortful, even joyful. We strengthen instructional effecitveness along with the brain, the command center of the nervous sytem, in the ways the brain learns best.
Kuhl, P. K. & Damasio, A. (2012). Language, in E. R. Kandel. J. H. Schwartz, T. M. Jessell, S. Siegelbaum, & J. Hudspeth (Eds.), Principles of neural science: 5th Edition (pp. 1353-1372). New York: McGraw Hill. Click here to receive a reprint
Description: An introductory lecture course covering the fundamental principles of neuroscience. Topics will include: principles of brain organization; structure and ultrastructure of neurons; neurophysiology and biophysics of excitable cells; synaptic transmission; neurotransmitter systems and neurochemistry; neuropharmacology; neuroendocrine relations; molecular biology of neurons; development and plasticity of the brain; aging and diseases of the nervous system; organization of sensory and motor systems; structure and function of cerebral cortex; modelling of neural systems.
This course aims to provide a comprehensive yet intuitive grasp of the mathematical and computational tools central to the analysis of neural systems and neural data. The course will introduce students to topics in linear algebra, differential equations, and probability & statistics, with a heavy emphasis on applications to neurobiology. Coursework will focus primarily on problem sets requiring the use of a simple computer programming language (e.g., Matlab, Python). The course will seek to develop intuition and achieve a practical mastery of the methods introduced, and will equip students with programming and data visualization skills that are increasingly important to scientific inquiry in general, and neuroscience in particular.
Daniel J. Siegel, M.D. is a pioneer in the field called interpersonal neurobiology (The Developing Mind, 1999) which seeks the similar patterns that arise from separate approaches to knowledge. This interdisciplinary approach invites all branches of science and other ways of knowing to come together and find the common principles from within their often disparate approaches to understanding human experience. Sciences contributing to this exciting framework include the following:
Neuroscience research has exploded, with more than fifty thousand neuroscientists applying increasingly advanced methods. A mountain of new facts and mechanisms has emerged. And yet a principled framework to organize this knowledge has been missing. In this book, Peter Sterling and Simon Laughlin, two leading neuroscientists, strive to fill this gap, outlining a set of organizing principles to explain the whys of neural design that allow the brain to compute so efficiently. 781b155fdc