Functional diversity among sensory neurons from efficient coding principles

Abstract

In many sensory systems the neural signal is coded by multiple parallel pathways, suggesting an evolutionary fitness benefit of general nature. A common pathway splitting is that into ON and OFF cells, responding to stimulus increments and decrements, respectively. According to efficient coding theory, sensory neurons have evolved to an optimal configuration for maximizing information transfer given the structure of natural stimuli and circuit constraints. Using the efficient coding framework, we describe two aspects of neural coding: how to optimally split a population into ON and OFF pathways, and how to allocate the firing thresholds of individual neurons given realistic noise levels, stimulus distributions and optimality measures. We find that populations of ON and OFF neurons convey equal information about the stimulus regardless of the ON/OFF mixture, once the thresholds are chosen optimally, independent of stimulus statistics and noise. However, an equal ON/OFF mixture is the most efficient as it uses the fewest spikes to convey this information. The optimal thresholds and coding efficiency, however, depend on noise and stimulus statistics if information is decoded by an optimal linear readout. With non-negligible noise, mixed ON/OFF populations reap significant advantages compared to a homogeneous population. The best coding performance is achieved by a unique mixture of ON/OFF neurons tuned to stimulus asymmetries and noise. We provide a theory for how different cell types work together to encode the full stimulus range using a diversity of response thresholds. The optimal ON/OFF mixtures derived from the theory accord with certain biases observed experimentally.

Neuronal On- and Off-type heterogeneities improve population coding of envelope signals in the presence of stimulus-induced noise

“…This is expected based on their classification (Supplementary Figs. 1B-D) and previous results 17,18,34,35 . In contrast, On-and Off-type neurons responded with similar increases in firing rate ( Fig.…”

Nonlinear convergence boosts information coding in circuits with parallel outputs

“…Overall, the magnitude and source of noise can have a large effect on a circuit's ability to encode stimulus information (37,38,57,58). As a preliminary check, we confirmed that one of these known effects carries over to our convergent/divergent circuit.…”

Efficient sensory coding of multidimensional stimuli

“…Thus, if a population is optimal in the sense described here, it would be possible to predict the natural distribution of the stimuli being encoded from the Fisher information measured from the population responses. Such an inverse efficient coding scheme is similar to a method proposed in [ 39 ], which derives the stimulus distribution from the distribution of firing thresholds in an optimal population of spiking neurons.…”