Applying Super-Resolution and Tomography Concepts to Identify Receptive Field Subunits in the Retina.

Spatially nonlinear stimulus integration by retinal ganglion cells lies at the heart of various computations performed by the retina. It arises from the nonlinear transmission of signals that ganglion cells receive from bipolar cells, which thereby constitute functional subunits within a ganglion cell's receptive field. Inferring these subunits from recorded ganglion cell activity promises a new avenue for studying the functional architecture of the retina. This calls for efficient methods, which leave sufficient experimental time to leverage the acquired knowledge for further investigating identified subunits. Here, we combine concepts from super-resolution microscopy and computed tomography and introduce super-resolved tomographic reconstruction (STR) as a technique to efficiently stimulate and locate receptive field subunits. Simulations demonstrate that this approach can reliably identify subunits across a wide range of model variations, and application in recordings of primate parasol ganglion cells validates the experimental feasibility. STR can potentially reveal comprehensive subunit layouts within only a few tens of minutes of recording time, making it ideal for online analysis and closed-loop investigations of receptive field substructure in retina recordings. Author summary: Neural computations in sensory systems often involve nonlinear pooling of sensory information. In the vertebrate retina, nonlinear signal transmission between bipolar cells and downstream ganglion cells, the output neurons of the retina, shapes the ganglion cells' functional properties and structures a ganglion cell's receptive field into smaller subunits. Methods for identifying these subunits from recordings of ganglion cell activity are needed to better understand the signal flow and the computations occurring between bipolar and ganglion cells. We here show that concepts from super-resolution microscopy and tomography can be used to design a visual stimulus and corresponding analysis to efficiently trigger ganglion cell activity while maintaining high spatial resolution for revealing subunits. As demonstrated by computer simulations and recordings from the primate retina, the method can identify subunit layouts with little experimental recording time, providing for the possibility to be combined with in-depth functional analyses or applied in closed-loop experiments. [ABSTRACT FROM AUTHOR]