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Here we introduce a circuit design method that compensates for parts uncertainty by identifying circuit topologies whose behavior is robust to variations in parameters.
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A reporter mouse strain with inducible expression would therefore be useful for identifying circuits involved in short and long term plasticity after stimulant and antipsychotic exposure but also with striatal-based learning paradigms.
Thus, our next task was identifying circuits along the pathways that contained such clusters and then to conduct extensive literature searches to annotate our discoveries.
More recently, investigators have begun to use this new methodology with central injections to identify circuit anatomy within the brain.
Here we developed a modeling framework to bridge this gap and identify circuit interactions capable of maintaining short-term memory.
In [17], it was shown that the evaluation of functional identification of an entire neural circuit can be more intuitively performed in the input space by decoding the stimuli with identified circuit parameters.
The identified circuit design happens to be consistent with a purely binary logic viewpoint of regulation.
In this work, we examined a role for the identified circuit in detecting displacements of the antennae and eliciting grooming.
In summary, by imaging neural activity at cellular resolution during naturalistic behavior, we have functionally identified circuit components that are likely to mediate the perceptual recognition of ethologically relevant stimuli and the release of an adaptive behavioral response.
The sparse duality result also enables us to evaluate the identified circuits in the input space.
We achieve the latter by computing the mean square error or signal-to-noise ratio (SNR) of novel stimuli decoded using the identified circuits [17].
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