Characterization of proprioceptive system dynamics in behaving Drosophila larvae using high-speed volumetric microscopy, bioRxiv, 2018-11-12

SummaryProprioceptors provide feedback about body position that is essential for coordinated movement. Proprioceptive sensing of the position of rigid joints has been described in detail in several systems, however it is not known how animals with an elastic skeleton encode their body positions. Understanding how diverse larval body positions are dynamically encoded requires knowledge of proprioceptor activity patterns in vivo during natural movement. Here we applied high-speed volumetric SCAPE microscopy to simultaneously track the position, physical deformation, and temporal patterns of intracellular calcium activity of multidendritic proprioceptors in crawling Drosophila larvae. During the periodic segment contraction and relaxation that occurs during crawling, proprioceptors with diverse morphologies showed sequential onset of activity throughout each periodic episode. A majority of these proprioceptors showed activity during segment contraction with one neuron type activated by segment extension. Different timing of activity of contraction-sensing proprioceptors was related to distinct dendrite terminal targeting, providing a continuum of position encoding during all phases of crawling. These dynamics could endow different proprioceptors with specific roles in monitoring the progression of contraction waves, as well as body shape during other behaviors. We provide activity measurements during exploration as one example. Our results provide powerful new insights into the body-wide neuronal dynamics of the proprioceptive system in crawling Drosophila, and demonstrate the utility of our approach for characterization of neural encoding throughout the nervous system of a freely behaving animal.

biorxiv neuroscience 200-500-users 2018

The emergence of multiple retinal cell types through efficient coding of natural movies, bioRxiv, 2018-10-31

AbstractOne of the most striking aspects of early visual processing in the retina is the immediate parcellation of visual information into multiple parallel pathways, formed by different retinal ganglion cell types each tiling the entire visual field. Existing theories of efficient coding have been unable to account for the functional advantages of such cell-type diversity in encoding natural scenes. Here we go beyond previous theories to analyze how a simple linear retinal encoding model with different convolutional cell types efficiently encodes naturalistic spatiotemporal movies given a fixed firing rate budget. We find that optimizing the receptive fields and cell densities of two cell types makes them match the properties of the two main cell types in the primate retina, midget and parasol cells, in terms of spatial and temporal sensitivity, cell spacing, and their relative ratio. Moreover, our theory gives a precise account of how the ratio of midget to parasol cells decreases with retinal eccentricity. Also, we train a nonlinear encoding model with a rectifying nonlinearity to efficiently encode naturalistic movies, and again find emergent receptive fields resembling those of midget and parasol cells that are now further subdivided into ON and OFF types. Thus our work provides a theoretical justification, based on the efficient coding of natural movies, for the existence of the four most dominant cell types in the primate retina that together comprise 70% of all ganglion cells.

biorxiv neuroscience 0-100-users 2018

 

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