Closed-loop measurements of iso-response stimuli reveal dynamic nonlinear stimulus integration in the retina
Retinal circuit model and function
Circuit and function of nonlinear signal integration by retinal ganglion cells. Left: A retinal ganglion cell (G) integrates inputs from several bipolar cells (B), whose signals are thresholded and squared. For some ganglion cells, a gain control mechanism reduces the effectiveness of the local inputs as these become stronger. Right: Representation of an image by populations of ganglion cells with and without the gain control mechanism, according to the model on the left. Without gain control, small high-contrast objects are well represented; with gain control, large objects are enhanced.
D. Bölinger, T. Gollisch (2012). Neuron 73:333-346.
Neurons often integrate information from multiple parallel signaling streams. How a neuron combines these inputs largely determines its computational role in signal processing. Experimental assessment of neuronal signal integration, however, is often confounded by cell-intrinsic nonlinear processes that arise after signal integration has taken place. To overcome this problem and determine how ganglion cells in the salamander retina integrate visual contrast over space, we used automated online analysis of recorded spike trains and closed-loop control of the visual stimuli to identify different stimulus patterns that give the same neuronal response. These iso-response stimuli revealed a threshold-quadratic transformation as a fundamental nonlinearity within the receptive field center. Moreover, for a subset of ganglion cells, the method revealed an additional dynamic nonlinearity that renders these cells particularly sensitive to spatially homogeneous stimuli. This function is shown to arise from a local inhibition-mediated dynamic gain control mechanism.
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