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Titlebook: Computation in Neurons and Neural Systems; Frank H. Eeckman Book 1994 Springer Science+Business Media New York 1994 Motor.Sensor.cognition

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Simulating the foveal cone receptive fieldinal laterally connects to neighboring cones through electrical coupling and horizontal cells. To explore the contributions of the cone lateral connections to the receptive field, we constructed a compartmental model of the primate foveal outer plexiform layer based on the known anatomy and physiolo
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Computational Hermissenda Photoarray Modelment and analysis of computer models of the essential neural mechanisms leading to these capabilities elucidate design principles for flexible man-made remote sensing, vision, and control systems. The marine snail, Hermissenda crassicornis, is ideal for study and modeling of biological computing mec
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Limits On Image Representation In Early Visionect to a constraint on synaptic size, the optimal receptive fields (RFs) are spatially extensive and not particularly physiologic in character. However, when the same problem is solved with a constraint on the spatial extent of synaptic connections as well as their size, spatially localized physiolo
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Inward Rectifying Conductances in Inhibitory Neurons of Turtle Visual Cortexw method for estimating kinetic parameters from intracellular current-clamp experiments. We modeled the sag conductance as . and found that it has two components: a larger, rapidly-activating conductance, and a smaller, slower conductance. The estimated kinetic parameters are sufficient to completel
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Lecture Notes in Computer Sciencegically plausible RFs are produced which are distributed in a manner similar to the functional architecture of the visual cortex. For a given level of synaptic use, this localized set of RFs is just as efficient for image representation as the spatially extensive set.
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Lucas Robidou,Pierre Peterlongoa single location fixes the entire map. A comparison with optically recorded images of cortical maps suggests that orientation preference can indeed be predicted over a much larger spatial range than previously estimated on the basis of correlation measurements.
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An overview of the Valentino Computational Neuroscience Workbench for the simulation of neural systend powerful interconnection selection criteria and schema. The object-oriented and modular design make the system flexible and extendable. The graphical user-interface and workbench metaphor make it easy to use.
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