Neuronal circuitry consists of a web of neurons, each triggering others by launching bursts of neurotransmitters at targets on receiving neurons to produce nerve impulses in those targets. Neurons adjust the strength of those connections adaptively, to amplify or suppress connections. Some four decades ago, a general principle called the "efficient coding hypothesis" was formulated, holding that sensory systems adjust to efficiently represent the complex, dynamic sounds, sights, and other sensory input from the environment.
Writing in the August 4, 2005, issue of Neuron, researchers led by Christian K. Machens of Cold Spring Harbor Laboratory and Andreas Herz of Humboldt-University Berlin describe experiments with grasshopper auditory neurons that reveal new details of such sensory coding. Their findings show that "optimal stimulus ensembles" that trigger the neurons differ from those the grasshopper hears in the natural environment but largely overlap with components of natural sounds found in mating and mate-location calls.
In their experiments, the researchers first played various snippets of white noise to isolated grasshopper auditory nerves and measured the electrophysiological signals reflecting the reactions of the auditory neurons to those sounds. These experiments revealed the distribution of stimuli called the "optimal stimulus ensemble" (OSE) that allowed the neurons in the system to perform optimally.
Once the researchers had characterized the OSE, they then analyzed how this measure compared to the neuronal response to natural sounds--including environmental sounds like the rustling of grass an d insect communication signals such as grasshopper or cricket mating calls.
They found that the OSEs of the receptors particularly matched characteristic features of species-specific acoustic communication signals used by grasshoppers to attract mating partners.
"Hence, instead of maximizing the average information gained about natural stimuli, the receptors appear to maximize the information gained about specific, but less often occurring aspects of the stimuli," concluded the researchers. "This result suggests that an organism may seek to distribute its sensory resources according to the behavioral relevance of the natural important stimuli, rather than according to purely statistical principles.
"For instance, if a few important stimuli within the natural environment need to be encoded with high precision, a large part of a system's coding capacity could be designated to encode these stimuli. Consequently, it may well be that even small subensembles strongly influence the coding strategy of sensory neurons. In this case, the optimal stimulus ensemble will not match the ensemble of all natural stimuli encountered by the particular species."
The researchers also concluded that "We therefore suggest that the coding strategy of sensory neurons is not matched to the statistics of natural stimuli per se, but rather to a weighted ensemble of natural stimuli, where the different behavioral relevance of stimuli determines their relative weight in the ensemble."
Machens, Herz, and their colleagues also concluded that their analytical technique could yield broader insight into the evolution of sensory circuitry.
"Our approach presents a systematic way to uncover potential mismatches between the statistical properties of the natural environment and the coding strategy of sensory neurons. In turn, these discrepancies might improve our understanding of the evolutionary design of the specific sensory system," they wrote.