Functional Diversity in the Retina Improves the Population Code.

Within a given brain region, individual neurons exhibit a wide variety of different feature selectivities. Here, we investigated the impact of this extensive functional diversity on the population neural code. Our approach was to build optimal decoders to discriminate among stimuli using the spiking output of a real, measured neural population and compare its performance against a matched, homogeneous neural population with the same number of cells and spikes. Analyzing large populations of retinal ganglion cells, we found that the real, heterogeneous population can yield a discrimination error lower than the homogeneous population by several orders of magnitude and consequently can encode much more visual information. This effect increases with population size and with graded degrees of heterogeneity. We complemented these results with an analysis of coding based on the Chernoff distance, as well as derivations of inequalities on coding in certain limits, from which we can conclude that the beneficial effect of heterogeneity occurs over a broad set of conditions. Together, our results indicate that the presence of functional diversity in neural populations can enhance their coding fidelity appreciably. A noteworthy outcome of our study is that this effect can be extremely strong and should be taken into account when investigating design principles for neural circuits.

Locomotion control of Caenorhabditis elegans through confinement.

The model organism Caenorhabditis elegans shows two distinct locomotion patterns in laboratory situations: it swims in low viscosity liquids and it crawls on the surface of an agar gel. This provides a unique opportunity to discern the respective roles of mechanosensation (perception and proprioception) and mechanics in the regulation of locomotion and in the gait selection. Using an original device, we present what to our knowledge are new experiments where the confinement of a worm between a glass plate and a soft agar gel is controlled while recording the worm's motion. We observed that the worm continuously varied its locomotion characteristics from free swimming to slow crawling with increasing confinement so that it was not possible to discriminate between two distinct intrinsic gaits. This unicity of the gait is also proved by the fact that wild-type worms immediately adapted their motion when the imposed confinement was changed with time. We then studied locomotory deficient mutants that also exhibited one single gait and showed that the light touch response was needed for the undulation propagation and that the ciliated sensory neurons participated in the joint selection of motion period and undulation-wave velocity. Our results reveal that the control of maximum curvature, at a sensory or mechanical level, is a key ingredient of the locomotion regulation.

Running worms: C. elegans self-sorting by electrotaxis.

The nematode C. elegans displays complex dynamical behaviors that are commonly used to identify relevant phenotypes. Although its maintenance is straightforward, sorting large populations of worms when looking for a behavioral phenotype is difficult, time consuming and hardly quantitative when done manually. Interestingly, when submitted to a moderate electric field, worms move steadily along straight trajectories. Here, we report an inexpensive method to measure worms crawling velocities and sort them within a few minutes by taking advantage of their electrotactic skills. This method allows to quantitatively measure the effect of mutations and aging on worm's crawling velocity. We also show that worms with different locomotory phenotypes can be spatially sorted, fast worms traveling away from slow ones. Group of nematodes with comparable locomotory fitness could then be isolated for further analysis. C. elegans is a growing model for neurodegenerative diseases and using electrotaxis for self-sorting can improve the high-throughput search of therapeutic bio-molecules.