Fast and sensitive GCaMP calcium indicators for imaging neural populations.

Calcium imaging with protein-based indicators1,2 is widely used to follow neural activity in intact nervous systems, but current protein sensors report neural activity at timescales much slower than electrical signalling and are limited by trade-offs between sensitivity and kinetics. Here we used large-scale screening and structure-guided mutagenesis to develop and optimize several fast and sensitive GCaMP-type indicators3-8. The resulting 'jGCaMP8' sensors, based on the calcium-binding protein calmodulin and a fragment of endothelial nitric oxide synthase, have ultra-fast kinetics (half-rise times of 2 ms) and the highest sensitivity for neural activity reported for a protein-based calcium sensor. jGCaMP8 sensors will allow tracking of large populations of neurons on timescales relevant to neural computation.

Environmental differences in substrate mechanics do not affect sprinting performance in sand lizards (Uma scoparia and Callisaurus draconoides).

Running performance depends on a mechanical interaction between the feet of an animal and the substrate. This interaction may differ between two species of sand lizard from the Mojave Desert that have different locomotor morphologies and habitat distributions. Uma scorparia possesses toe fringes and inhabits dunes, whereas the closely related Callisaurus draconoides lacks fringes and is found on dune and wash habitats. The present study evaluated whether these distribution patterns are related to differential locomotor performance on the fine sand of the dunes and the course sand of the wash habitat. We measured the kinematics of sprinting and characterized differences in grain size distribution and surface strength of the soil in both habitats. Although wash sand had a surface strength (15.4±6.2 kPa) that was more than three times that of dune sand (4.7±2.1 kPa), both species ran with similar sprinting performance on the two types of soil. The broadly distributed C. draconoides ran with a slightly (22%) faster maximum speed (2.2±0.2 m s(-1)) than the dune-dwelling U. scorparia (1.8±0.2 m s(-1)) on dune sand, but not on wash sand. Furthermore, there were no significant differences in maximum acceleration or the time to attain maximum speed between species or between substrates. These results suggest that differences in habitat distribution between these species are not related to locomotor performance and that sprinting ability is dominated neither by environmental differences in substrate nor the presence of toe fringes.

Motor pattern control for increasing crushing force in the striped burrfish (Chilomycterus schoepfi).

The relationship between muscular force modulation and the underlying nervous system control signals has been difficult to quantify for in vivo animal systems. Our goal was to understand how animals alter muscle activation patterns to increase bite forces and to evaluate how accurate these patterns are in predicting crushing forces. We examined the relationship between commonly used measures of cranial muscle activity and force production during feeding events of the striped burrfish (Chilomycterus schoepfi), a mollusc crushing specialist. We quantified the force required to crush a common gastropod prey item (Littorina irrorata) of burrfish using a materials testing device. Burrfish were fed these calibrated prey items while we recorded electromyograms (EMGs) from the main jaw closing muscles (adductor mandibulae A1beta, A2alpha, and A2beta). We quantified EMG activity by measuring the burst duration, rectified integrated area, and then calculated the intensity of activity from these two variables. Least squares regressions relating force to crush (Fcrush) and all EMG variables were calculated for each fish. Multiple regression analyses were used to determine how much of the variation in Fcrush could be explained by muscle activation patterns. We found that 20 cm burrfish are capable of generating extremely high crushing forces (380 N peak force) primarily by increasing the duration of muscle activity. EMG variables explained 71% of the total variation in force production. After accounting for the inherent variation in Fcrush of snails, EMGs do a very good job of predicting bite forces for these fish.