scholarly journals Walking Drosophila navigate complex plumes using stochastic decisions biased by the timing of odor encounters

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Mahmut Demir ◽  
Nirag Kadakia ◽  
Hope D Anderson ◽  
Damon A Clark ◽  
Thierry Emonet

How insects navigate complex odor plumes, where the location and timing of odor packets are uncertain, remains unclear. Here we imaged complex odor plumes simultaneously with freely-walking flies, quantifying how behavior is shaped by encounters with individual odor packets. We found that navigation was stochastic and did not rely on the continuous modulation of speed or orientation. Instead, flies turned stochastically with stereotyped saccades, whose direction was biased upwind by the timing of prior odor encounters, while the magnitude and rate of saccades remained constant. Further, flies used the timing of odor encounters to modulate the transition rates between walks and stops. In more regular environments, flies continuously modulate speed and orientation, even though encounters can still occur randomly due to animal motion. We find that in less predictable environments, where encounters are random in both space and time, walking flies navigate with random walks biased by encounter timing.

2020 ◽  
Author(s):  
Mahmut Demir ◽  
Nirag Kadakia ◽  
Hope D. Anderson ◽  
Damon A. Clark ◽  
Thierry Emonet

ABSTRACTInsects find food, mates, and egg-laying sites by tracking odor plumes swept by complex wind patterns. Previous studies have shown that moths and flies localize plumes by surging upwind at odor onset and turning cross- or downwind at odor offset. Less clear is how, once within the expanding cone of the odor plume, insects use their brief encounters with individual odor packets, whose location and timing are random, to progress towards the source. Experiments and theory have suggested that the timing of odor encounters might assist navigation, but connecting behaviors to individual encounters has been challenging. Here, we imaged complex odor plumes simultaneous with freely-walking flies, allowing us to quantify how behavior is shaped by individual odor encounters. Combining measurements, dynamical models, and statistical inference, we found that within the plume cone, individual encounters did not trigger reflexive surging, casting, or counterturning. Instead, flies turned stochastically with stereotyped saccades, whose direction was biased upwind by the timing of prior odor encounters, while the magnitude and rate of saccades remained constant. Odor encounters did not strongly affect walking speed. Instead, flies used encounter timing to modulate the rate of transitions between walks and stops. When stopped, flies initiated walks using information from multiple odor encounters, suggesting that integrating evidence without losing position was part of the strategy. These results indicate that once within the complex odor plume, where odor location and timing are unpredictable, animals navigate with biased random walks shaped by the entire sequence of encounters.


1981 ◽  
Vol 13 (01) ◽  
pp. 61-83 ◽  
Author(s):  
Richard Serfozo

This is a study of simple random walks, birth and death processes, and M/M/s queues that have transition probabilities and rates that are sequentially controlled at jump times of the processes. Each control action yields a one-step reward depending on the chosen probabilities or transition rates and the state of the process. The aim is to find control policies that maximize the total discounted or average reward. Conditions are given for these processes to have certain natural monotone optimal policies. Under such a policy for the M/M/s queue, for example, the service and arrival rates are non-decreasing and non-increasing functions, respectively, of the queue length. Properties of these policies and a linear program for computing them are also discussed.


1981 ◽  
Vol 13 (1) ◽  
pp. 61-83 ◽  
Author(s):  
Richard Serfozo

This is a study of simple random walks, birth and death processes, and M/M/s queues that have transition probabilities and rates that are sequentially controlled at jump times of the processes. Each control action yields a one-step reward depending on the chosen probabilities or transition rates and the state of the process. The aim is to find control policies that maximize the total discounted or average reward. Conditions are given for these processes to have certain natural monotone optimal policies. Under such a policy for the M/M/s queue, for example, the service and arrival rates are non-decreasing and non-increasing functions, respectively, of the queue length. Properties of these policies and a linear program for computing them are also discussed.


2005 ◽  
Vol DMTCS Proceedings vol. AE,... (Proceedings) ◽  
Author(s):  
Joshua Cooper ◽  
Benjamin Doerr ◽  
Joel Spencer ◽  
Gábor Tardos

International audience We analyze the one-dimensional version of Jim Propp's $P$-machine, a simple deterministic process that simulates a random walk on $\mathbb{Z}$. The "output'' of the machine is astonishingly close to the expected behavior of a random walk, even on long intervals of space and time.


2020 ◽  
Author(s):  
Marco Patriarca ◽  
Els Heinsalu ◽  
Jean Leó Leonard
Keyword(s):  

Author(s):  
Mikhail Menshikov ◽  
Serguei Popov ◽  
Andrew Wade
Keyword(s):  

Author(s):  
Alain Connes ◽  
Michael Heller ◽  
Roger Penrose ◽  
John Polkinghorne ◽  
Andrew Taylor
Keyword(s):  

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