We tested this by observing the real-time consumption of a limited budget relief from a series of 60 painful stimuli in the laboratory, over the course of approximately 15 minutes, in a group of participants whose intertemporal preferences for one-off future pains of the same nature had been elicited previously.

It is unclear whether such behavior is manifest in real-time , or indeed influences the kind of consumption choices demonstrated here.

Temporally inconsistent preferences theoretically compound the complexity of planning resource allocations in real-time , since they necessitate a dynamic model of the behavior of future selves [2, 30].

However very few studies have directly examined resource allocation decisions in real-time , tested the extent to which these are consistent with discount functions derived from one-off choices, or indeed found a parsimonious description that accounts well for actual choices.

Thus we designed a task that involved allocating a limited budget in real-time in which we could examine the various forms of inconsistency and explore possible heuristics in a rather open-ended manner.

In short, an iterative estimate 13” of the cell’s instantaneous firing rate was updated online after each AP, detected in real-time (i.e., as a positive crossing of a voltage threshold), using the following formula: where T = 1s acts as the time scale over which the instantaneous firing rate is estimated, weighing each new AP and the previous firing history [21, 31].

We specifically implemented a real-time system composed of a closed-loop controller of the cell instantaneous firing rate.

We therefore designed and implemented via software a real-time closed-loop control system (Fig.

(A) A real-time closed-loop in vitro setup for experimentally estimating the PRC at a fixed firing rate, based on a Proportional-lntegral-Derivative (PID) controller and on a reactive-clamp paradigm, was employed to rapidly and optimally explore the dependency of the PRC of PCs on the cell’s firing rate.

We show that in such situations critical knowledge to assess the real-time risk of infection can be extracted from past temporal contact data.

Although such knowledge would be a critical requirement to conduct risk assessment analyses in real-time , which need to be based on the updated and accurate description of the contacts relevant to the outbreak under study [9] , it can hardly be obtained in reality.

Data on livestock movements are routinely collected following European regulations [55] , however they may not be readily available in a real-time fashion upon an emergency, and a certain delay may thus be eXpected.