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Computational Models for Neuroscience: Human Cortical Information Processing - Softcover

 
9781447111115: Computational Models for Neuroscience: Human Cortical Information Processing

Inhaltsangabe

Formal study of neuroscience (broadly defined) has been underway for millennia. For example, writing 2,350 years ago, Aristotle! asserted that association - of which he defined three specific varieties - lies at the center of human cognition. Over the past two centuries, the simultaneous rapid advancements of technology and (conse­ quently) per capita economic output have fueled an exponentially increasing effort in neuroscience research. Today, thanks to the accumulated efforts of hundreds of thousands of scientists, we possess an enormous body of knowledge about the mind and brain. Unfortunately, much of this knowledge is in the form of isolated factoids. In terms of "big picture" understanding, surprisingly little progress has been made since Aristotle. In some arenas we have probably suffered negative progress because certain neuroscience and neurophilosophy precepts have clouded our self-knowledge; causing us to become largely oblivious to some of the most profound and fundamental aspects of our nature (such as the highly distinctive propensity of all higher mammals to automatically seg­ ment all aspects of the world into distinct holistic objects and the massive reorganiza­ tion of large portions of our brains that ensues when we encounter completely new environments and life situations). At this epoch, neuroscience is like a huge collection of small, jagged, jigsaw puz­ zle pieces piled in a mound in a large warehouse (with neuroscientists going in and tossing more pieces onto the mound every month).

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Über die Autorin bzw. den Autor

The cerebral cortex is the area of the brain where almost all of the mental capabilities that distinguish humans from other animals are based. Understanding how it works is vital to the progress in many areas of medicine and science, including the development of more efficient and flexible neural networks. Although extensive research has been carried out over the last 150 years, very little real progress has been made. This book provides a unique overview of work by key researchers, and shows how current research can be used to develop and improve computational models for neural networks.

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Formal study of neuroscience (broadly defined) has been underway for millennia. For example, writing 2,350 years ago, Aristotle! asserted that association - of which he defined three specific varieties - lies at the center of human cognition. Over the past two centuries, the simultaneous rapid advancements of technology and (conse­ quently) per capita economic output have fueled an exponentially increasing effort in neuroscience research. Today, thanks to the accumulated efforts of hundreds of thousands of scientists, we possess an enormous body of knowledge about the mind and brain. Unfortunately, much of this knowledge is in the form of isolated factoids. In terms of "big picture" understanding, surprisingly little progress has been made since Aristotle. In some arenas we have probably suffered negative progress because certain neuroscience and neurophilosophy precepts have clouded our self-knowledge; causing us to become largely oblivious to some of the most profound and fundamental aspects of our nature (such as the highly distinctive propensity of all higher mammals to automatically seg­ ment all aspects of the world into distinct holistic objects and the massive reorganiza­ tion of large portions of our brains that ensues when we encounter completely new environments and life situations). At this epoch, neuroscience is like a huge collection of small, jagged, jigsaw puz­ zle pieces piled in a mound in a large warehouse (with neuroscientists going in and tossing more pieces onto the mound every month).

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