Efficient transformation of an auditory population code in a small sensory system

Abstract

Optimal coding principles are implemented in many large sensory systems. They include the systematic transformation of external stimuli into a sparse and decorrelated neuronal representation, enabling a flexible readout of stimulus properties. Are these principles also applicable to size-constrained systems, which have to rely on a limited number of neurons and may only have to fulfill specific and restricted tasks? We studied this question in an insect system-the early auditory pathway of grasshoppers. Grasshoppers use genetically fixed songs to recognize mates. The first steps of neural processing of songs take place in a small three-layer feedforward network comprising only a few dozen neurons. We analyzed the transformation of the neural code within this network. Indeed, grasshoppers create a decorrelated and sparse representation, in accordance with optimal coding theory. Whereas the neuronal input layer is best read out as a summed population, a labeled-line population code for temporal features of the song is established after only two processing steps. At this stage, information about song identity is maximal for a population decoder that preserves neuronal identity. We conclude that optimal coding principles do apply to the early auditory system of the grasshopper, despite its size constraints. The inputs, however, are not encoded in a systematic, map-like fashion as in many larger sensory systems. Already at its periphery, part of the grasshopper auditory system seems to focus on behaviorally relevant features, and is in this property more reminiscent of higher sensory areas in vertebrates.metric | invertebrates | information theory T o increase their fitness, most animals strive to evaluate sensory signals that reveal the quality of a potential mate. What if an animal has only a few dozen neurons to preprocess this extremely important information? Optimal coding theory suggests that the creation of a sparse, decorrelated representation would be a wise investment of scarce neuronal resources (1).That is indeed what has been found in many sensory modalities and species under natural conditions (2-4).These early sensory networks often comprise large numbers of cells and organize information in a map-like fashion, where spatial proximity of neurons reflects similarity in the selectivity for fundamental stimulus features (5, 6). These maps tend to have a complete representation of sensory space and enable subsequent processing steps to select relevant features based on attention or associative learning. Reading out such a representation by "blind" summation of responses across different neurons would be highly inefficient to recover information, because stimulus features are not only encoded by neuronal activity per se but also by neuronal identity. This type of population code is referred to as labeled-line code (7,8). Accordingly, higher-order sensory areas need to take into account which neurons are active when producing more specific representations of behaviorally relevant stimulus aspects (9). Do the...

Asymmetrical integration of sensory information during mating decisions in grasshoppers

“…Neurons in the grasshopper's early auditory system-located in the metathoracic ganglion-are likely involved in feature extraction (23,24). Several neurons that project to the brain- so-called "ascending neurons"-are sensitive to the number of offsets in a syllable and thereby exhibit differential responses to positive and negative information; this is achieved through the interaction of differently timed excitatory and inhibitory inputs (25).…”

Nonlinear Computations Underlying Temporal and Population Sparseness in the Auditory System of the Grasshopper

“…To study the responses of the models to natural signals, we used a set of songs from eight different male grasshoppers of the species Chorthippus biguttulus (Clemens et al, 2011). It is well justified to use models fit to neurons recorded in one species of grasshopper, L. migratoria, to study the responses to signals of another species, C. biguttulus, as the morphological and physiological properties of neurons at the early stages of processing we are interested in are highly similar (Ronacher and Stumpner, 1988;Neuhofer et al, 2008, Creutzig et al, 2009.…”

“…Then, the average in Equation 1 was taken over the four cells in a population in each individual time bin, and S was averaged over all time bins and songs. For comparison, we included empirical sparseness values of the responses of local and ascending neurons to the same set of songs (Clemens et al, 2011).…”

“…The natural songs had a SD of 6 Ϯ 1 dB, close to the SD of the noise stimuli used for the estimation and evaluation of the models. To cover the range of firing rates between 20 and 50 Hz observed for natural stimuli (Clemens et al, 2011), we set the average amplitude to ϩ6 dB.…”

Temporal integration at consecutive processing stages in the auditory pathway of the grasshopper

“…Recent studies suggest that a change in coding strategy occurs in the auditory pathway, namely from a summed population code with emphasis on the timing of spikes, implemented in the receptors and local neurons, to a labeled-line code implemented in the ascending neurons (Clemens et al 2011(Clemens et al , 2012; see also Hildebrandt 2014). Since ascending neurons exhibit specific auditory filters with different properties, the assumption of a uniform temporal integration time constant in ascending neurons or in the whole auditory system seems less likely.…”