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The authors consider the input/output behavior of a realistic dynamical neural model in comparison to those typically used in artificial neural networks. They have found that such models duplicate well those behaviors seen in living neurons, displaying a range of behaviors commonly seen in a wide variety of nonlinear dynamical systems. This is not captured well by weighted sum/monotonic transfer function models. An example of the consequences of nonlinear dynamics in neural responses is presented for monotonically changing input transients.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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Stiber et al. (2002) studied this question.
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