Identification and Characterization of a Y-Like Primate Retinal Ganglion Cell Type

Abstract

The primate retina communicates visual information to the brain via a set of parallel pathways that originate from at least 22 anatomically distinct types of retinal ganglion cells. Knowledge of the physiological properties of these ganglion cell types is of critical importance for understanding the functioning of the primate visual system. Nonetheless, the physiological properties of only a handful of retinal ganglion cell types have been studied in detail. Here we show, using a newly developed multielectrode array system for the large-scale recording of neural activity, the existence of a physiologically distinct population of ganglion cells in the primate retina with distinctive visual response properties. These cells, which we will refer to as upsilon cells, are characterized by large receptive fields, rapid and transient responses to light, and significant nonlinearities in their spatial summation. Based on the measured properties of these cells, we speculate that they correspond to the smooth/large radiate cells recently identified morphologically in the primate retina and may therefore provide visual input to both the lateral geniculate nucleus and the superior colliculus. We further speculate that the upsilon cells may be the primate retina's counterparts of the Y-cells observed in the cat and other mammalian species.

The Primate Retina Contains Distinct Types of Y-Like Ganglion Cells: Figure 1.

“…The existence of a primate homolog to the Y-cell has been a controversial subject, but recent studies have conclusively identified at least two types of Y-like primate RGCs (Petrusca et al, 2007;Crook et al, 2008a,b), underscoring the need to incorporate Y-cell physiological properties into our understanding of visual processing.…”

“…The primate retina also possesses a second Y-like RGC, the smooth monostratified (SM) cell (Crook et al, 2008b). SM cells, which may be the primate "upsilon cell" identified by Petrusca et al (2007), can be distinguished from parasol cells morphologically (Crook et al, 2008b). The dendritic fields of SM cells are more sparsely branched and approximately two times wider than those of parasol cells.…”

Fast Kalman filtering on quasilinear dendritic trees

“…Can we exploit these high-SNR superthreshold calcium observations to reconstruct (at least partially) the subthreshold voltage signal? More generally, we would like to optimally combine calcium and voltage measurements, where voltage measurements may be available via imaging techniques, or whole-cell patch recordings at the soma or apical dendrite, or even through dense multielectrode recordings (Petrusca et al, 2007).…”

“…As pointed out in (Morse et al, 2001;Wood et al, 2004;Huys et al, 2006), if we are given the full spatiotemporal voltage signal on the dendritic tree, then simple, direct statistical methods allow us to infer many biophysical quantities of interest, including passive cable parameters (e.g., the axial resistance at each point on the tree), active properties (e.g., the spatial membrane density distribution of voltage-gated channels), and in some cases even time-varying information (e.g., synaptic weights and presynaptic input conductances (Cox, 2004;Paninski and Ferreira, 2008;Paninski et al, 2009)). Unfortunately, multiple-electrode recordings from dendrites are quite technically challenging, and provide spatially-incomplete observations (Stuart and Sakmann, 1994;Cox and Griffith, 2001;Cox and Raol, 2004;Bell and Craciun, 2005;Petrusca et al, 2007), while high-resolution imaging techniques provide more spatially-complete observations, but with significantly lower signal-to-noise (Djurisic et al, 2004;Sacconi et al, 2006;Araya et al, 2006;Palmer and Stuart, 2006;Gobel and Helmchen, 2007;Vucinic and Sejnowski, 2007;Canepari et al, 2007;Djurisic et al, 2008).…”

Optimal experimental design for sampling voltage on dendritic trees in the low-SNR regime

“…If we have the full spatiotemporal voltage signal then it is possible to use straightforward statistical methods to infer many biophysical quantities of interest (Morse et al, 2001;Wood et al, 2004;Huys et al, 2006), such as passive cable parameters, active properties, and in some cases even time-varying information, such as the rate of synaptic input. Unfortunately, technical challenges limit multiple-electrode recordings from dendrites to only a few electrodes, typically targeted far from the tips of dendritic branches (Stuart and Sakmann, 1994;Cox and Griffith, 2001;Cox and Raol, 2004;Bell and Craciun, 2005;Petrusca et al, 2007;Nevian et al, 2007;Homma et al, 2009). High-resolution two-photon imaging techniques provide more spatially-complete observations, but with significantly lower signal-tonoise (Djurisic et al, 2008;Homma et al, 2009;Canepari et al, 2010Canepari et al, , 2011.…”