Many studies have shown that cells use temporal dynamics of signaling molecules to encode information. One particular class of temporal dynamics is sustained and transient signals, i.e. signals of long and short durations respectively. This paper formulates a detection problem for distinguishing sustained signals from transient ones. The solution of the detection problem is to compute the likelihood ratio of observing a sustained signal to a transient signal. We show that, if the logarithm of this likelihood ratio is positive (i.e. when the signal is likely to be sustained), then this log-likelihood ratio can be approximately computed by a coherent feedforward loop . Although the capability of coherent feedforward loops to discriminate sustained signals is known, its statistical information processing interpretation has not been pointed out before .
Many studies have shown that cells use temporal dynamics of signalling molecules to encode information. One particular class of temporal dynamics is persistent and transient signals, i.e. signals of long and short durations respectively. It has been shown that the coherent type-1 feedforward loop with an AND logic at the output (or C1-FFL for short) can be used to discriminate a persistent input signal from a transient one. This has been done by modelling the C1-FFL, and then use the model to show that persistent and transient input signals give, respectively, a non-zero and zero output. Instead of assuming the structure of C1-FFL, this paper shows that it is possible to deduce the C1-FFL model from the requirement of discriminating a persistent signal. We do this by first formulating a statistical detection problem of distinguishing persistent signals from transient ones. The solution of the detection problem is to compute the log-likelihood ratio of observing a persistent signal to a transient signal. We show that, if this log-likelihood ratio is positive , which happens when the signal is likely to be persistent, then it can be approximately computed by a C1-FFL . Although the capability of C1-FFL to discriminate persistent signals is known, this paper adds an information processing interpretation on how a C1-FFL works as a detector of persistent signals .
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This paper formulates a detection problem for distinguishing sustained
It has been shown that the coherent type-1 feedforward loop with an AND logic at the output (or C1-FFL for short) can be used to discriminate a persistent input signal from a transient one. This has been done by modelling the C1-FFL, and then use the model to show that persistent and transient input signals give, respectively, a non-zero and zero output. Instead of assuming the structure of C1-FFL, this paper shows that it is possible to deduce the C1-FFL model from the requirement of discriminating a persistent signal. We do this by first formulating a statistical detection problem of distinguishing persistent
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the logarithm of this likelihood
this log-likelihood
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coherent feedforward loop
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coherent feedforward loops to discriminate sustained
C1-FFL to discriminate persistent
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this paper adds an
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on how a C1-FFL works as a detector of persistent signals