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can be expected to be at the order of maybe tens to one hundred Hertz. As demonstrated in the Results
section, the dopamine signaling system can successfully tolerate noise of such frequencies even if the
noise amplitude is large (the simulations allowed for noise corresponding to 50% of the baseline).
As a natural system in an ever-changing environment, the dopamine system is always exposed to
noise of various frequencies. There is not much that an organism can do to avoid these perturbations.
Interestingly, the results of our combined noise-delay analysis show that unavoidable delays in the system,
which are due to the relatively slow physical processes of vesicle dynamics and dopamine release, are
not always detrimental and may even be advantageous, but only if they are short. Specifically, we found
that small delays, at the order of 10 milliseconds, effectively remove the negative effects of fast noise,
whereas much longer delays exaggerate the problems caused by noise, up to a point where the signal
is no longer reliably transduced. Thus, the cell must assure that delays are not overly long. Indeed,
it has been observed that vesicles filled with dopamine are primarily located close to the presynaptic
membrane [26], thereby minimizing unavoidable delays, and that vesicles elsewhere in the presynapse
primarily serve as back-up dopamine pools that move to the membrane when needed.
Like all mathematical models, the model proposed here is rather simplistic, and it remains to be seen
whether the investigated delays and noise frequencies constitute the most relevant combinations. With
the advent of in vivo imaging and measuring technologies [23,27], the near future will reveal more
biological details concerning noise and delays, and these will allow us to elucidate with greater accuracy
the types and features of perturbations that the dopamine signaling system is facing on a daily basis.
In spite of these uncertainties, the article demonstrates that the effects of combined noise and delays
are not easy to predict and may even lead to counterintuitive outcomes. Secondly, the article shows that
the embedding of a canonical formalism like BST in a hybrid framework like HFPN can substantially
and beneficially expand the repertoire of analytical tools for systems biology.
ACKNOWLEDGEMENTS
This work was supported by a grant from the National Institutes of Health (P01-ES016731, G.W.
Miller, PI) and an endowment from the Georgia Research Alliance (E.O.V). Any opinions, findings, and
conclusions or recommendations expressed in this material are those of the authors and do not necessarily
reflect the views of the sponsoring institutions.
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