Abstract

Light that enters the eye begins the process of vision by activating two types of photoreceptors: rods, which support vision under low light levels, and cones, which are responsible for fine detail and color vision. Activation of either type of photoreceptor triggers responses in bipolar cells, which activate the ganglion cells that transmit visual signals to the brain. Bipolar cells therefore belong to a class of cells called interneurons, which relay information from certain cell types to others. Interneurons play an important role in information processing throughout the brain, but directly accessing them or characterizing their role in neural computation is often difficult. To address this problem, Freeman, Field et al. have developed a combined computational and experimental approach to describe the flow of sensory signals through the circuits within the retina of primates. Large arrays of electrodes were used to record the responses of many retinal ganglion cells in response to the activation or de-activation of pairs of cones. These experiments revealed that the responses of ganglion cells are not simply the sum of the inputs that they receive from cones; specifically, the activation of one cone is not cancelled by the deactivation of another. Instead, the data suggest that bipolar cells add cone inputs together and then pass on the total activation (but not deactivation) to ganglion cells. By analyzing the responses of ganglion cells to numerous random patterns of cone activation, Freeman, Field et al. were able to estimate the locations and arrangements of bipolar cells that connect to them. These predicted patterns of connectivity agreed with observations from anatomical studies. This work provides detailed insights into how the primate retina works. It also suggests that similar approaches may be used to characterize how signals flow across other brain networks in which large-scale recordings are now possible.

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