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Titlebook: Exploration of Cortical Function; Imaging and Modeling Martin Stetter Book 2002 Springer Science+Business Media Dordrecht 2002 anatomy.biol

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发表于 2025-3-21 17:39:26 | 显示全部楼层 |阅读模式
书目名称Exploration of Cortical Function
副标题Imaging and Modeling
编辑Martin Stetter
视频video
图书封面Titlebook: Exploration of Cortical Function; Imaging and Modeling Martin Stetter Book 2002 Springer Science+Business Media Dordrecht 2002 anatomy.biol
描述.Exploration of Cortical Function. summarizes recent research efforts aiming at the revelation of cortical population coding and signal processing strategies. Topics include optical detection techniques of population activity in the sub-millimeter range, advanced methods for the statistical analysis of these data, and biologically inspired neuronal modeling techniques for population activities in the frameworks of optimal coding, statistical learning theory, and mean-field recurrent networks. ..Exploration of Cortical Function. is unique in that it covers one complete branch of population-based brain research ranging from techniques for data acquisition over data analysis up to modeling techniques for the quantification of functional principles. The volume covers an area which is of great current interest to researchers working on cerebral cortex. The combination of models and image analysis techniques to examine the activity of large cohorts of neurons is especially intriguing and prone to considerable error and debate. .
出版日期Book 2002
关键词anatomy; biologically inspired; computational neuroscience; cortex; image analysis; knowledge; learning; le
版次1
doihttps://doi.org/10.1007/978-94-010-0430-5
isbn_softcover978-1-4020-0436-0
isbn_ebook978-94-010-0430-5
copyrightSpringer Science+Business Media Dordrecht 2002
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The Early Visual System of Macaque Monkeys,form structure, as one proceeds laterally across its different areas. Despite its uniformity, different parts of the cerebral cortex perform a large variety of different signal processing tasks (cf. figure 1.1). Hence, it seems desirable to obtain a detailed understanding of one of these parts, beca
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Optical Imaging of Brain Activity,n of this complex system, it is very important not only to know responses of individual neurons to stimulation but also to be able to measure how the visual system responds to given stimuli as a whole. This reflects the hypothesis that the visual cortex represents many aspects of visual information
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Optical Imaging As Source Separation Problem,y an indirect measure of neuronal activity. This is particularly true for evoked metabolic changes such as intrinsic signals. Therefore, the relationship between neuronal activity and optical signals must be characterized in detail. The only direct method for doing this is the simultaneous electroph
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Regression Methods for Source Separation,may be some observable which has been measured at times ., and we wish to characterize die statistical structure in this data set. Often, there is some reason to believe that there is an underlying deterministic functional relationship between the pairs of data. The characterization of this underlyi
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Real World Applications of Source Separation Techniques,1997) has become an important experimental tool for die investigation of neuronal response properties and coding strategies. As mentioned in chapter 4, section 1.2, Ca. imaging uses the fact that postsynaptic intracellular Ca. concenttation often increases when die cells are activated, and that a pr
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Computational Models of Early Vision,ndividual neurons and large neuron populations respond to external stimuli. Understanding brain function means to understand the principles of information processing that underlie the observed response characteristics. These principles can be approached by the following questions: (.) What is the un
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