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The first two editions of this title had a tremendous impact in neuroscience. Between the Second edition in 1989 and today, there has been an explosion of information in the field, including advances in molecular techniques, such as genomics and proteomics, which have become increasing important in neuroscience. A renaissance in fluorescence has occurred, driven by the development of new probes, new microscopes, live imagers, and computer processing. The introduction of new markers has enormously stimulated the field, moving it from tissue culture to neurophysiology to functional MRI techniques.
Fifty years ago, enthused by successes in creating digital computers and the DNA model of heredity, scientists were con?dent that solutions to the problems of und- standing biological intelligence and creating machine intelligence were within their grasp. Progress at ?rst seemed rapid. Giant ‘brains’ that ?lled air-conditioned rooms were shrunk into briefcases. The speed of computation doubled every two years. What these advances revealed is not the solutions but the dif?culties of the pr- lems. We are like the geographers who ‘discovered’ America, not as a collection of islands but as continents seen only at shores and demanding exploration. We are astounded less by the magnitude of...
In Computational Neuroanatomy: Principles and Methods, the path-breaking investigators who founded the field review the principles and key techniques available to begin the creation of anatomically accurate and complete models of the brain. Combining the vast, data-rich field of anatomy with the computational power of novel hardware, software, and computer graphics, these pioneering investigators lead the reader from the subcellular details of dendritic branching and firing to system-level assemblies and models.
This edited volume addresses the importance of mathematics for industry and society by presenting highlights from contract research at the Department of Applied Mathematics at SINTEF, the largest independent research organization in Scandinavia. Examples range from computer-aided geometric design, via general purpose computing on graphics cards, to reservoir simulation for enhanced oil recovery. Contributions are written in a tutorial style.
The huge volume of neuroscience data and the wide variety of data formats generated across different neuroscience communities has posed a challenge to traditional methods of data management, data sharing and data mining. Mandates on data sharing and the demand for using open data has driven the development of advanced methodologies and tools to effectively explore, mine and integrate data. However, the growing number of resources make it harder for researchers to navigate this landscape. Awareness of these tools and resources is vital for effective data mining and unlocking new discoveries. The goal of this research collection is to provide an overview of available resources, centred around making data findable, accessible, interoperable and reusable (FAIR).
The name Prachurya means Goddess of wealth in ancient Sanskrit. True to that meaning, Prachurya Bharadwaj the author, has accumulated herself an ocean of experiences, that very few 28-year-olds would fathom. She didn’t just stop at one post-graduate degree in engineering but pursued another one, then some more professional courses after that. At 21, when she went abroad to study, she found internship opportunities in one country, created a start-up in another followed by full-time positions, then again in another country where she bought her first house. This book is a story of her defeating all odds, taking proactive measures, rising above those who thought too little of her, healing hers...
Supercomputing facilities are becoming increasingly available for simulating activity dynamics in large-scale neuronal networks. On today's most advanced supercomputers, networks with up to a billion of neurons can be readily simulated. However, building biologically realistic, full-scale brain models requires more than just a huge number of neurons. In addition to network size, the detailed local and global anatomy of neuronal connections is of crucial importance. Moreover, anatomical connectivity is not fixed, but can rewire throughout life (structural plasticity)—an aspect that is missing in most current network models, in which plasticity is confined to changes in synaptic strength (sy...