科研之友
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摘要
Several recent studies have demonstrated that neuronal models allow multiple parameter value solutions for a given output. In the face of this variability of parameter values, what can be learned about neural function through parameter value differences? Here, in two different models, we examine this question by attempting to reconstruct the source of model output changes based on simple statistical analyses of parameter distributions generated by automated searches. We conclude that changes to parameter values or their associated distributions do not reliably reflect the specific mechanisms responsible for a given change in output.
- 出版日期2011-6
