Titlebook: Connectionist Models in Cognitive Neuroscience; The 5th Neural Compu Dietmar Heinke,Glynn W. Humphreys,Andrew Olson Conference proceedings

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Towards an Emotional Robot: Simulating Hippocampal-Mediated Anxietyr part of the simulation is a neural network representation of the mammalian hippocampus. Experiments are presented in which the robot exhibits anxiety-like behaviour, which changes in a biologically realistic manner after a “lesion”.

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A Connectionist Model for Frequency Effects in Recall and Recognitionanism is found essential to simulate low frequency advantage in recognition. The familiarity is measured as the absolute net input. This mechanism accounts for the advantage of high frequency in recall, words over non-words in recognition, and high frequency cues. The model is implemented in a modified Hopfield network and analyzed analytically.

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Phonon-Assisted Tunneling in Semiconductors,information and the possible existence of visual units which are larger than single letters. Simulations here are intended to model the early stages of visual word recognition in both normal reading and in cases of peripheral dyslexia. In a feedforward network, letter units are coarse coded for posi

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Magnetotunneling Effects in Semiconductors,ociations and what they really mean, especially when connectionist or neural network models are involved. In this paper I attempt to clarify matters by looking at the subject from the point of view of patterns of learning rates in neural network models.

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Supporting action of anchors/boltsrsion did not allow for the matching process nor was delayed matching to sample with non-recurring stimuli possible. Here an extension is presented which allows for the representation of various objects as well as for a more realistic output. This is done via the adjunction of a grid of multimodal c

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