Capacity and energy cost of information in biological and silicon photoreceptors

We outline a theoretical framework to analyze information processing in biological sensory organs and in engineered microsystems: We employ the mathematical tools of communication theory and model natural or synthetic physical structures as microscale communication networks, studying them under physical constraints at two different levels of abstraction. At the functional level, we examine the operational and tusk specification, while at the physical level, we examine ike material specification and realization. Both levels of abstraction are characterized by Shannon's channel capacity, as determined by the channel bandwidth, the signal power, and the noise power. The link between the functional level ana the physical level of abstraction is established through models for transformations on the signal, physical constraints on the system, and noise that dégrades the signal. As a specific example, we present a comparative study of information capacity (in oils per second) versus energy cost of information (in joules per bit) in a biological and in a silicon adaptive photoreceptor. The communication channel model for each of the t\vo systems is a cascade of linear bandlimiting sections followed by additive noise. We model the filters and the noise from first principles whenever possible and phenomenologically uthenvise. The parameters for the blowfly model are determined from biophysical data available in She literature, and the parameters of the silicon model are determined from our experimental data. This comparative study is a first step toward a fundamental and quantitative understanding of the tradeoffs between system performance and associated costs such as size, reliability, and energy requirements for natural and engineered sensory microsystems.