Computational Neuroscience szeminariumok

COMPUTATIONAL NEUROSCIENCE szeminariumok MTA KFKI RMKI, III. epulet, Tancsterem) November 10, Szerda 14.00 - 15.00 Laurenz Wiskott Innovationskolleg Theoretische Biologie Humboldt-Universität zu Berlin Unsupervised Learning of Invariances in a Simple Model of the Visual System November 17, Szerda 14.00 - 16.30 Minoru Tsukada - Yuki Kobayashi Department of Information & Communication Engineering and Brain Science Institute Tamagawa University, Tokyo-Machida Spatial distribution on LTP and in the hippocampal CA1 region: from experiments to theory Erdeklodoket szivesen latunk. *************************************************************** Abstracts Wiskott: A new algorithm for unsupervised learning of invariances is presented. The basic idea is to learn a nonlinear input-output function which extracts slowly varying aspects from the input signal by minimizing the temporal variation of the output signal. This is a known approach. The algorithm, however, differs from existing learning rules. Firstly, it computes the solution in a closed form (like PCA) and is guaranteed to find the optimum within the considered function class. Secondly, not only one but many uncorrelated output signal components can be generated easily, which is important for hierarchical networks. The algorithm is then applied to a simple model of the visual system with a one-dimensional retina. Depending on what stimuli are used for training, the network can learn translation-, scale-, rotation- (cyclic shift), contrast-, or illumination-invariance. Relatively few stimulus patterns are needed for training to achieve good generalization to new patterns. The representation generated is suitable for pattern recognition. Overall the model suggests that it may be plausible that our visual system learns invariances based on fairly limited visual experience. Tsukada - Kobayashi: The spatial distriution of LTP and LTD induced by temporal modulated stimulus, composed of high and low frequencies, was investigated in a slice preparation from the hippocampus of aguine-pig by using optical imaging method.Stimulus dependent LTP and LTD were simultaneously observed in the sepcific areas in CA1. The area of LTD corresponds to the localized area of pyramidal cell output layer of CA1 with feedback inhibition from basket cells, which differs from the area (stratum radiatum) of that induced by low frequncy stimulation. The coding mechanism is discussed in the relation between the stimulus pattern and the network structure.