Synaptic inputs to retrogradely labeled ganglion cells in the retina of the cane toad, Bufo marinus

General features of the retinal connectome determine the computation of motion anticipation

Motion anticipation allows the visual system to compensate for the slow speed of phototransduction so that a moving object can be accurately located. This correction is already present in the signal that ganglion cells send from the retina but the biophysical mechanisms underlying this computation are not known. Here we demonstrate that motion anticipation is computed autonomously within the dendritic tree of each ganglion cell and relies on feedforward inhibition. The passive and non-linear interaction of excitatory and inhibitory synapses enables the somatic voltage to encode the actual position of a moving object instead of its delayed representation. General rather than specific features of the retinal connectome govern this computation: an excess of inhibitory inputs over excitatory, with both being randomly distributed, allows tracking of all directions of motion, while the average distance between inputs determines the object velocities that can be compensated for.

DOI:http://dx.doi.org/10.7554/eLife.06250.001

The retina is a structure at the back of the eye that converts light into nerve impulses, which are then processed in the brain to produce the images that we see. It normally takes about one-tenth of a second for the retina to send a signal to the brain after an object first moves into view. This is about the same time it takes a tennis ball to travel several meters during a tennis match, yet we are still able to see where the moving tennis ball is in real time. This is because a process called ‘motion anticipation’ is able to compensate for the delay in processing the position of a moving object. However, it was not known precisely how motion anticipation occurs.

Inside the retina, cells called photoreceptors detect light and ultimately send signals (via some intermediate cell types) to nerve cells known as retinal ganglion cells. These signals can either excite a retinal ganglion cell to cause it to send an electrical signal to the brain, or inhibit it, which temporarily prevents electrical activity. Each cell receives signals from several photoreceptors, which each connect to a different site along branch-like structures called dendrites that project out of the retinal ganglion cells.

Johnston and Lagnado have now investigated how motion anticipation occurs in the retina by using electrical recordings of the activity in the retinas of goldfish combined with computer simulations of this activity. This revealed inhibitory signals, sent from photoreceptors to retinal ganglion cells via a type of intermediate cell (called amacrine cells), play a key role in motion anticipation. The ability to track motion effectively in all directions requires more inhibitory signals to be sent to the dendrites of a retinal ganglion cell than excitatory signals. These two types of input must also be randomly distributed across the cell. Furthermore, it is the density of these input sites on a dendrite that determines how well the retina can compensate for the motion of a fast-moving object. The building blocks required for motion anticipation in the retina are also found in visual areas higher in the brain. Therefore, further work may reveal that higher visual areas also use this mechanism to predict the future location of moving objects.

DOI:http://dx.doi.org/10.7554/eLife.06250.002

Synaptology of the inner plexiform layer in the anuran retina

The inner plexiform layer of the retina is a synaptic layer mostly devoid of perikarya. It contains the processes of three major neuron types: the bipolar cells, which carry information from the photoreceptors, the ganglion cells, which are the output elements of the retina, and the amacrine cells, which are able to influence the communication between the former two. Since amacrine cells are the most diverse retinal neurons, they are in a position to carve out and delineate the neural circuits of the inner retina. The aim of this review is to offer a summary of findings related to the general synaptology of the inner retina in frogs and also to provide some insight into the synaptic organization of neurochemically identified amacrine cells. The main conclusions of this paper are as follows: (i) Most contacts are formed between amacrine cells. (2) Direct bipolar to ganglion cell synapses exist, but are rare in the anuran retina. (3) All neurochemically identified amacrine cell types receive inputs from bipolar cells, but not all of them form reciprocal contacts with bipolar cell axon terminals. (4) A major inhibitory transmitter, gamma-aminobutyric acid, is involved in more than 50% of the synapses. Since contacts between inhibitory elements were often observed, disinhibitory circuits must also play a role in retinal information processing. (5) Reciprocal relationship between dopaminergic and gamma-aminobutyric acid-containing cells have been confirmed. Similar situation was observed in case of serotoninergic and gamma-aminobutyric acid-positive elements. No contacts were verified between serotoninergic and dopaminergic elements. (6) Both monoamine- and neuropeptide-containing amacrine cells establish direct contacts with ganglion cell dendrites, providing a morphological basis for neuromodulatory influence on the output elements of the retina. Unfortunately, only a handful of studies have been carried out to identify the synaptic connections between neurochemically identified cells in the anuran retina. Double-label studies at the electron microscope level to reveal the synaptic relationship of cell populations containing two different transmitters/modulators are extremely rare. Further insight into retinal synaptic circuitries could be gained with a combination of electrophysiology and morphology at the electron microscopic level. These studies must also involve identification of the transmitter receptors on identified cell types. Only after this step can the function of different synaptic circuitries be better approximated.