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Perception as acquisition of information from the environment
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Perception is fundamentally a process of acquiring, transmitting and processing information about the environment. Shannon's information theory provides the quantitative framework: each stimulus has an information content I = -logP(s) measured in bits, which is greater the less probable the stimulus is.
The capacity C of the sensory channel (how much information it can transmit per second) is limited by the bandwidth B and the signal-to-noise ratio SNR, following the Shannon-Hartley theorem. This fundamental limit applies to both the human optic nerve (C 10 bit/s) and any biological or artificial receptor.
Mutual information I(S;R) measures how much the uncertainty about the stimulus is reduced by knowing the sensor response: I(S;R) = H(S) - H(S|R). A perfect sensor has I(S;R) = H(S); a completely noisy sensor has I(S;R) = 0. This metric unifies the evaluation of any sensory system.
The Weber-Fechner law and Stevens power law empirically describe how the perceived subjective magnitude relates to the physical intensity . The log Fechner relationship implies that perception compresses enormous ranges of physical intensity into manageable ranges: the human ear covers 12 orders of magnitude in pressure (0130 dB) but perceives them as a linear scale of 'volume'.
The theory of signal detection (SDT) quantifies the discriminative capacity by d' = (_S - _N)/_N: a sensor with d' > 2 distinguishes signal from noise well; d' < 1 indicates marginal detection. This metric is independent of the observer's decision criteria and is essential for comparing sensory capabilities between species.
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