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Soetedjo, R.

Publications and source records attributed to Soetedjo, R..

2 recordsLinked to original sources

Conserved Circuits for Direction Selectivity in the Primate Retina

The detection of motion direction is a fundamental visual function and a classic model for neural computation1,2. In the non-primate mammalian retina, direction selectivity arises in starburst amacrine cell (SAC) dendrites, which provide selective inhibition to ON and ON-OFF direction selective retinal ganglion cells (dsRGCs)3,4. While SACs are present in primates5, their connectivity is unknown and the existence of primate dsRGCs remains an open question. Here we present a connectomic reconstruction of the primate ON SAC circuit from a serial electron microscopy volume of macaque central retina. We show that the structural basis for the SACs ability to compute and confer directional selectivity on post-synaptic RGCs6 is conserved in primates and that SACs selectively target a single ganglion cell type, a candidate homolog to the mammalian ON-sustained dsRGCs that project to the accessory optic system and contribute to gaze-stabilizing reflexes7,8. These results indicate that the capacity to compute motion direction is present in the retina, far earlier in the primate visual system than classically thought, and they shed light on the distinguishing features of primate motion processing by revealing the extent to which ancestral motion circuits are conserved.

neuroscience

P-sort: an open-source software for cerebellar neurophysiology

Analysis of electrophysiological data from Purkinje cells (P-cells) of the cerebellum presents challenges for spike detection. Complex spikes have waveforms that vary significantly from one event to the next, raising the problem of misidentification. Even when complex spikes are detected correctly, the simple spikes may belong to a different P-cell, raising the danger of misattribution. Here, we analyzed data from over 300 P-cells in marmosets, macaques, and mice, using an open-source, semi-automated software called P-sort that addresses the spike identification and attribution problems. Like other sorting software, P-sort relies on nonlinear dimensionality reduction to cluster spikes. However, it also uses the statistical relationship between simple and complex spikes to merge seemingly disparate clusters, or split a single cluster. In comparison with expert manual curation, occasionally P-sort identified significantly more complex spikes, as well as prevented misattribution of clusters. Three existing automatic sorters performed less well, particularly for identification of complex spikes. To improve development of analysis tools for the cerebellum, we provide labeled data for 313 recording sessions, as well as statistical characteristics of waveforms and firing patterns.

neuroscience