To average or not to average: Trade-off in compressed sensing with noisy measurements

There are numerous different odorant molecules in nature but only a relatively small number of olfactory receptor neurons (ORNs) in brains. This “compressed sensing” challenge is compounded by the constraint that ORNs are nonlinear sensors with a finite dynamic range. Here, we investigate possible optimal olfactory coding strategies by maximizing mutual information between odor mixtures and ORNs’ responses with respect to the bipartite odor-receptor interaction network (ORIN) characterized by sensitivities between all odorant–ORN pairs. For ORNs without spontaneous (basal) activity, we find that the optimal ORIN is sparse—a finite fraction of sensitives are zero, and the nonzero sensitivities follow a broad distribution that depends on the odor statistics. We show analytically that sparsity in the optimal ORIN originates from a trade-off between the broad tuning of ORNs and possible interference. Furthermore, we show that the optimal ORIN enhances performances of downstream learning tasks (reconstruction and classification). For ORNs with a finite basal activity, we find that having inhibitory odor–receptor interactions increases the coding capacity and the fraction of inhibitory interactions increases with the ORN basal activity. We argue that basal activities in sensory receptors in different organisms are due to the trade-off between the increase in coding capacity and the cost of maintaining the spontaneous basal activity. Our theoretical findings are consistent with existing experiments and predictions are made to further test our theory. The optimal coding model provides a unifying framework to understand the peripheral olfactory systems across different organisms.

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A Flow-Preserving Algorithm for the Time-Cost Trade-Off Problem

IIE Transactions ◽

10.1080/05695558208974589 ◽

1982 ◽

Vol 14 (2) ◽

pp. 109-113 ◽

Cited By ~ 4

Author(s):

Suleyman Tufekci

Keyword(s):

Time Cost ◽

Trade Off

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Dual Goals for Speed and Accuracy on the Same Performance Task

Journal of Personnel Psychology ◽

10.1027/1866-5888/a000063 ◽

2012 ◽

Vol 11 (3) ◽

pp. 118-126 ◽

Cited By ~ 3

Author(s):

Olive Emil Wetter ◽

Jürgen Wegge ◽

Klaus Jonas ◽

Klaus-Helmut Schmidt

Keyword(s):

Memory Scanning ◽

Performance Task ◽

Performance Tasks ◽

Trade Off ◽

Test Experiment ◽

Trade Offs ◽

New Finding ◽

Sternberg Paradigm ◽

Speed Accuracy ◽

Speed And Accuracy

In most work contexts, several performance goals coexist, and conflicts between them and trade-offs can occur. Our paper is the first to contrast a dual goal for speed and accuracy with a single goal for speed on the same task. The Sternberg paradigm (Experiment 1, n = 57) and the d2 test (Experiment 2, n = 19) were used as performance tasks. Speed measures and errors revealed in both experiments that dual as well as single goals increase performance by enhancing memory scanning. However, the single speed goal triggered a speed-accuracy trade-off, favoring speed over accuracy, whereas this was not the case with the dual goal. In difficult trials, dual goals slowed down scanning processes again so that errors could be prevented. This new finding is particularly relevant for security domains, where both aspects have to be managed simultaneously.

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