Intrinsic properties and functional circuitry of the AII amacrine cell

JB Demb, JH Singer - Visual neuroscience, 2012 - cambridge.org
Visual neuroscience, 2012cambridge.org
Amacrine cells represent the most diverse class of retinal neuron, comprising dozens of
distinct cell types. Each type exhibits a unique morphology and generates specific visual
computations through its synapses with a subset of excitatory interneurons (bipolar cells),
other amacrine cells, and output neurons (ganglion cells). Here, we review the intrinsic and
network properties that underlie the function of the most common amacrine cell in the
mammalian retina, the AII amacrine cell. The AII connects rod and cone photoreceptor …
Amacrine cells represent the most diverse class of retinal neuron, comprising dozens of distinct cell types. Each type exhibits a unique morphology and generates specific visual computations through its synapses with a subset of excitatory interneurons (bipolar cells), other amacrine cells, and output neurons (ganglion cells). Here, we review the intrinsic and network properties that underlie the function of the most common amacrine cell in the mammalian retina, the AII amacrine cell. The AII connects rod and cone photoreceptor pathways, forming an essential link in the circuit for rod-mediated (scotopic) vision. As such, the AII has become known as the rod–amacrine cell. We, however, now understand that AII function extends to cone-mediated (photopic) vision, and AII function in scotopic and photopic conditions utilizes the same underlying circuit: AIIs are electrically coupled to each other and to the terminals of some types of ON cone bipolar cells. The direction of signal flow, however, varies with illumination. Under photopic conditions, the AII network constitutes a crossover inhibition pathway that allows ON signals to inhibit OFF ganglion cells and contributes to motion sensitivity in certain ganglion cell types. We discuss how the AII’s combination of intrinsic and network properties accounts for its unique role in visual processing.
Cambridge University Press