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Download MIT Department of Brain and Cognitive Sciences Instructor: Professor Sebastian Seung
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MIT Department of Brain and Cognitive Sciences 9.641J, Spring 2005 - Introduction to Neural Networks Instructor: Professor Sebastian Seung Lateral inhibition Truth 1: Lateral inhibition amplifies differences relative to commonalities. Truth 2: Lateral inhibition regulates response selectivity by setting a dynamic threshold Truths 1 and 2 are related: The ratio between differential gain and common gain is dynamic in a nonlinear network. Rectification vs. thresholding All-to-all inhibition Consider α<1 for now. Increasing α or β enhances selectivity Without nonlinearity Response of a linear network Piecewise linear behavior A dynamic threshold All neurons active Conditional winner-take-all The active set is scale invariant Gain depends on the active set Nonlinear amplifier • Unique steady state • State-dependent gain There is a unique output