Limits...
Thermodynamic costs of information processing in sensory adaptation.

Sartori P, Granger L, Lee CF, Horowitz JM - PLoS Comput. Biol. (2014)

Bottom Line: We apply these principles to the E. coli's chemotaxis pathway during binary ligand concentration changes.In this regime, we quantify the amount of information stored by each methyl group and show that receptors consume energy in the range of the information-theoretic minimum.Our work provides a basis for further inquiries into more complex phenomena, such as gradient sensing and frequency response.

View Article: PubMed Central - PubMed

Affiliation: Max Planck Institute for the Physics of Complex Systems, Dresden, Germany.

ABSTRACT
Biological sensory systems react to changes in their surroundings. They are characterized by fast response and slow adaptation to varying environmental cues. Insofar as sensory adaptive systems map environmental changes to changes of their internal degrees of freedom, they can be regarded as computational devices manipulating information. Landauer established that information is ultimately physical, and its manipulation subject to the entropic and energetic bounds of thermodynamics. Thus the fundamental costs of biological sensory adaptation can be elucidated by tracking how the information the system has about its environment is altered. These bounds are particularly relevant for small organisms, which unlike everyday computers, operate at very low energies. In this paper, we establish a general framework for the thermodynamics of information processing in sensing. With it, we quantify how during sensory adaptation information about the past is erased, while information about the present is gathered. This process produces entropy larger than the amount of old information erased and has an energetic cost bounded by the amount of new information written to memory. We apply these principles to the E. coli's chemotaxis pathway during binary ligand concentration changes. In this regime, we quantify the amount of information stored by each methyl group and show that receptors consume energy in the range of the information-theoretic minimum. Our work provides a basis for further inquiries into more complex phenomena, such as gradient sensing and frequency response.

Show MeSH
Information measurement and erasure in sensory adaptation.(A) Information acquired about the new signal as a function of time. The information stored in the activity  (dark blue) grows as the system responds, and then goes down as it adapts, when the information in the memory  (red) grows. The total information measured  (black) shows the effect of both. (B) Information lost about the old signal  (black), and its decomposition in memory (red) and activity (blue) information. Model parameters are  for x = a, m, g;  and .
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4263364&req=5

pcbi-1003974-g003: Information measurement and erasure in sensory adaptation.(A) Information acquired about the new signal as a function of time. The information stored in the activity (dark blue) grows as the system responds, and then goes down as it adapts, when the information in the memory (red) grows. The total information measured (black) shows the effect of both. (B) Information lost about the old signal (black), and its decomposition in memory (red) and activity (blue) information. Model parameters are for x = a, m, g; and .

Mentions: To illustrate this, we calculate the flow of information in the non-disspative feedforward model for , which is a 1-bit operation (because ). Fig. 3A displays the evolution of the measured information (in black), which we decomposed as(3)where (red) is the information stored in the memory and (blue) in the activity. We see the growth of proceeds first by a rapid () increase as information is stored in the activity ( grows) while the system responds, followed by a slower growth as adaptation sets in (), and the memory begins to track the signal. At the end, the system is adapted, and there is almost no information in the activity, . With the small errors we have, the information acquired reaches nearly the maximum value of 1 bit, which is stored in the memory . Fig. 3B shows the erasure of information, visible by the decrease of from an initial value of nearly one bit to zero when the system has decorrelated from the initial signal .


Thermodynamic costs of information processing in sensory adaptation.

Sartori P, Granger L, Lee CF, Horowitz JM - PLoS Comput. Biol. (2014)

Information measurement and erasure in sensory adaptation.(A) Information acquired about the new signal as a function of time. The information stored in the activity  (dark blue) grows as the system responds, and then goes down as it adapts, when the information in the memory  (red) grows. The total information measured  (black) shows the effect of both. (B) Information lost about the old signal  (black), and its decomposition in memory (red) and activity (blue) information. Model parameters are  for x = a, m, g;  and .
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4263364&req=5

pcbi-1003974-g003: Information measurement and erasure in sensory adaptation.(A) Information acquired about the new signal as a function of time. The information stored in the activity (dark blue) grows as the system responds, and then goes down as it adapts, when the information in the memory (red) grows. The total information measured (black) shows the effect of both. (B) Information lost about the old signal (black), and its decomposition in memory (red) and activity (blue) information. Model parameters are for x = a, m, g; and .
Mentions: To illustrate this, we calculate the flow of information in the non-disspative feedforward model for , which is a 1-bit operation (because ). Fig. 3A displays the evolution of the measured information (in black), which we decomposed as(3)where (red) is the information stored in the memory and (blue) in the activity. We see the growth of proceeds first by a rapid () increase as information is stored in the activity ( grows) while the system responds, followed by a slower growth as adaptation sets in (), and the memory begins to track the signal. At the end, the system is adapted, and there is almost no information in the activity, . With the small errors we have, the information acquired reaches nearly the maximum value of 1 bit, which is stored in the memory . Fig. 3B shows the erasure of information, visible by the decrease of from an initial value of nearly one bit to zero when the system has decorrelated from the initial signal .

Bottom Line: We apply these principles to the E. coli's chemotaxis pathway during binary ligand concentration changes.In this regime, we quantify the amount of information stored by each methyl group and show that receptors consume energy in the range of the information-theoretic minimum.Our work provides a basis for further inquiries into more complex phenomena, such as gradient sensing and frequency response.

View Article: PubMed Central - PubMed

Affiliation: Max Planck Institute for the Physics of Complex Systems, Dresden, Germany.

ABSTRACT
Biological sensory systems react to changes in their surroundings. They are characterized by fast response and slow adaptation to varying environmental cues. Insofar as sensory adaptive systems map environmental changes to changes of their internal degrees of freedom, they can be regarded as computational devices manipulating information. Landauer established that information is ultimately physical, and its manipulation subject to the entropic and energetic bounds of thermodynamics. Thus the fundamental costs of biological sensory adaptation can be elucidated by tracking how the information the system has about its environment is altered. These bounds are particularly relevant for small organisms, which unlike everyday computers, operate at very low energies. In this paper, we establish a general framework for the thermodynamics of information processing in sensing. With it, we quantify how during sensory adaptation information about the past is erased, while information about the present is gathered. This process produces entropy larger than the amount of old information erased and has an energetic cost bounded by the amount of new information written to memory. We apply these principles to the E. coli's chemotaxis pathway during binary ligand concentration changes. In this regime, we quantify the amount of information stored by each methyl group and show that receptors consume energy in the range of the information-theoretic minimum. Our work provides a basis for further inquiries into more complex phenomena, such as gradient sensing and frequency response.

Show MeSH