Gap junctions are essential for generating the correlated spike activity of neighboring retinal ganglion cells

Cross-synaptic synchrony and transmission of signal and noise across the mouse retina

Cross-synaptic synchrony—correlations in transmitter release across output synapses of a single neuron—is a key determinant of how signal and noise traverse neural circuits. The anatomical connectivity between rod bipolar and A17 amacrine cells in the mammalian retina, specifically that neighboring A17s often receive input from many of the same rod bipolar cells, provides a rare technical opportunity to measure cross-synaptic synchrony under physiological conditions. This approach reveals that synchronization of rod bipolar cell synapses is near perfect in the dark and decreases with increasing light level. Strong synaptic synchronization in the dark minimizes intrinsic synaptic noise and allows rod bipolar cells to faithfully transmit upstream signal and noise to downstream neurons. Desynchronization in steady light lowers the sensitivity of the rod bipolar output to upstream voltage fluctuations. This work reveals how cross-synaptic synchrony shapes retinal responses to physiological light inputs and, more generally, signaling in complex neural networks.

DOI:http://dx.doi.org/10.7554/eLife.03892.001

The human eye is capable of detecting a single photon of starlight. This level of sensitivity is made possible by the high sensitivity of photoreceptors called rods. There are around 120 million rods in the retina, and they support vision in levels of light that are too low to activate the photoreceptors called cones that allow us to see in color. This is why we cannot see colors in the dark.

Signals are relayed through the retina via a circuit made up of multiple types of neurons. The activation of rods leads to activation of cells known as ‘rod bipolar cells’ which, in turn, activate amacrine cells and ganglion cells, with the latter sending signals via the optic nerve to the brain. All of these neurons communicate with one another at junctions called synapses. Activation of a rod bipolar cell, for example, triggers the release of molecules called neurotransmitters: these molecules bind to and activate receptors on the amacrine cells, enabling the signal to be transmitted.

For the brain to detect that a single photon has struck a rod, the eye must transmit information along this chain of neurons in a way that is highly reliable while adding very little noise to the signal. Grimes et al. have now revealed a key step in how this is achieved.

Electrical recordings from the mouse retina revealed that, in the dark, small fluctuations in the activity of rod bipolar cells lead to the near-deterministic release of neurotransmitters. This reduces the impact of random fluctuations in neurotransmitter release produced at individual synapses and ensures that the signals from rod bipolar cells (and thus from rods) are transmitted faithfully through the circuit with minimal added noise. As light levels increase, this tight synchrony of transmitter release breaks down, reducing the sensitivity to individual photons.

Given that many other brain regions share the features that enable retinal cells to coordinate the release of neurotransmitters, this mechanism might be used throughout the brain to increase the signal-to-noise ratio for the transmission of information through neural circuits.

DOI:http://dx.doi.org/10.7554/eLife.03892.002

Role of connexin channels in the retinal light response of a diurnal rodent

Several studies have shown that connexin channels play an important role in retinal neural coding in nocturnal rodents. However, the contribution of these channels to signal processing in the retina of diurnal rodents remains unclear. To gain insight into this problem, we studied connexin expression and the contribution of connexin channels to the retinal light response in the diurnal rodent Octodon degus (degu) compared to rat, using in vivo ERG recording under scotopic and photopic light adaptation. Analysis of the degu genome showed that the common retinal connexins present a high degree of homology to orthologs expressed in other mammals, and expression of Cx36 and Cx43 was confirmed in degu retina. Cx36 localized mainly to the outer and inner plexiform layers (IPLs), while Cx43 was expressed mostly in cells of the retinal pigment epithelium. Under scotopic conditions, the b-wave response amplitude was strongly reduced by 18-β-glycyrrhetinic acid (β-GA) (−45.1% in degu, compared to −52.2% in rat), suggesting that connexins are modulating this response. Remarkably, under photopic adaptation, β-GA increased the ERG b-wave amplitude in degu (+107.2%) while reducing it in rat (−62.3%). Moreover, β-GA diminished the spontaneous action potential firing rate in ganglion cells (GCs) and increased the response latency of ON and OFF GCs. Our results support the notion that connexins exert a fine-tuning control of the retinal light response and have an important role in retinal neural coding.

Retinal connectomics: towards complete, accurate networks

Connectomics is a strategy for mapping complex neural networks based on high-speed automated electron optical imaging, computational assembly of neural data volumes, web-based navigational tools to explore 10(12)-10(15) byte (terabyte to petabyte) image volumes, and annotation and markup tools to convert images into rich networks with cellular metadata. These collections of network data and associated metadata, analyzed using tools from graph theory and classification theory, can be merged with classical systems theory, giving a more completely parameterized view of how biologic information processing systems are implemented in retina and brain. Networks have two separable features: topology and connection attributes. The first findings from connectomics strongly validate the idea that the topologies of complete retinal networks are far more complex than the simple schematics that emerged from classical anatomy. In particular, connectomics has permitted an aggressive refactoring of the retinal inner plexiform layer, demonstrating that network function cannot be simply inferred from stratification; exposing the complex geometric rules for inserting different cells into a shared network; revealing unexpected bidirectional signaling pathways between mammalian rod and cone systems; documenting selective feedforward systems, novel candidate signaling architectures, new coupling motifs, and the highly complex architecture of the mammalian AII amacrine cell. This is but the beginning, as the underlying principles of connectomics are readily transferrable to non-neural cell complexes and provide new contexts for assessing intercellular communication.