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Related Experiment Video

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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

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Published on: September 8, 2023

Energy consumption and cooperation for optimal sensing.

Vudtiwat Ngampruetikorn^1,2, David J Schwab^3,4, Greg J Stephens^5,6

¹Department of Physics and Astronomy, Northwestern University, Evanston, IL, 60208, USA. vngampruetikorn@gc.cuny.edu.

Nature Communications

|February 22, 2020

Summary

This summary is machine-generated.

Cellular sensing models reveal optimal strategies for detecting environmental molecules. Energy consumption and sensor cooperation are key for accurate signal detection, especially in noisy conditions.

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Area of Science:

Computational biology
Biophysics
Systems biology

Background:

Cells reliably detect environmental molecules amidst noise, a crucial function with poorly understood computational underpinnings.
Understanding cellular sensing mechanisms is vital for fields ranging from synthetic biology to medicine.

Purpose of the Study:

To develop and analyze a computational model of interacting sensors for exploring signal detection strategies.
To investigate the influence of signal statistics, cooperation, and energy consumption on sensing efficiency.

Main Methods:

A theoretical model of two interacting sensors was developed.
Mutual information was used to quantify the information gain between signals and sensors.
The model was extended to include time integration by a population of readout molecules.

Main Results:

Optimal sensing strategies are dependent on noise levels and signal statistics.
Asymmetric, energy-consuming couplings maximize information gain for correlated signals in low-noise environments.
Energy consumption is not universally required for optimal sensing; non-equilibrium processes can be beneficial.

Conclusions:

Sensor interaction and energy consumption are critical factors for optimal cellular sensing.
The findings provide insights into the biophysical principles governing biological information processing and signal detection.