Unusual Physiological Properties of Smooth Monostratified Ganglion Cell Types in Primate Retina

Rhoades, Colleen; Shah, Nishal P.; Manookin, Michael B.; Brackbill, Nora; Kling, Alexandra; Goetz, Georges; Sher, Alexander; Litke, A. M.; Chichilnisky, E. J.

doi:10.1016/j.neuron.2019.05.036

Cited by 56 publications

(106 citation statements)

References 71 publications

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“…Comparing the predicted and the recorded traces, we observed that the model was too fast for the first (slow) batch, approximately aligned for the second (medium) batch and too slow for the third (fast) batch. This observation is in line with a previous study that reported systematic differences in the response speed of ganglion cells recorded from different macaque retinae 46 .…”

Section: Resultssupporting

confidence: 94%

“…Again, we found that most functional groups were present across experiments, suggesting that experiment-specific speed differences did not induce additional functional clusters. A similar strategy was recently employed in a study on primate RGCs 46 , where the response profile of well-characterized parasol cells was used to normalize and then combine data from different experiments. Thus, if a readily identified and well-calibrated reference exists, batch effects can be reduced by excluding recordings that deviate strongly.…”

Section: Discussionmentioning

confidence: 99%

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The temporal structure of the inner retina at a single glance

Zhao

Klindt

Chagas

et al. 2019

Preprint

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21The retina decomposes visual stimuli into parallel channels that encode different features of the visual 22 environment. Central to this computation is the synaptic processing in a dense and thick layer of 23 neuropil, the so-called inner plexiform layer (IPL). Here, different types of bipolar cells stratifying at 24 distinct depths relay the excitatory feedforward drive from photoreceptors to amacrine and ganglion 25 cells. Current experimental techniques for studying processing in the IPL do not allow imaging the entire 26 IPL simultaneously in the intact tissue. Here, we extend a two-photon microscope with an electrically 27 tunable lens allowing us to obtain optical vertical slices of the IPL, which provide a complete picture of 28 the response diversity of bipolar cells at a "single glance". The nature of these axial recordings 29additionally allowed us to isolate and investigate batch effects, i.e. inter-experimental variations 30 resulting in systematic differences in response speed. As a proof of principle, we developed a simple 31 model that disentangles biological from experimental causes of variability, and allowed us to recover 32 the characteristic gradient of response speeds across the IPL with higher precision than before. Our 33 new framework will make it possible to study the computations performed in the central synaptic layer 34 of the retina more efficiently. 353

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Section: Resultssupporting

confidence: 94%

Section: Discussionmentioning

confidence: 99%

The temporal structure of the inner retina at a single glance

Zhao

Klindt

Chagas

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…Comparing the predicted and the recorded traces, we observed that the model was too fast for the first (slow) batch, approximately aligned for the second (medium) batch and too slow for the third (fast) batch. This observation is in line with a previous study that reported systematic differences in the response speed of RGCs recorded from different macaque retinae 47 .…”

Section: Identification Of Batch Effectssupporting

confidence: 94%

“…Recent evidence indicates that batch effects or inter-retina variability are also present in electrophysiological recordings of primate RGCs 47 , where the response profile of well-characterized parasol cells was used to normalize (by temporal rescaling) and then combine data from different experiments. This adds further support to the hypothesis of temporal rescaling, but it also highlights the presence of batch effects in other experimental modalities.…”

Section: Discussionmentioning

confidence: 99%

The temporal structure of the inner retina at a single glance

Zhao

Klindt

Chagas

et al. 2020

Sci Rep

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The retina decomposes visual stimuli into parallel channels that encode different features of the visual environment. Central to this computation is the synaptic processing in a dense layer of neuropil, the so-called inner plexiform layer (IPL). Here, different types of bipolar cells stratifying at distinct depths relay the excitatory feedforward drive from photoreceptors to amacrine and ganglion cells. Current experimental techniques for studying processing in the IPL do not allow imaging the entire IPL simultaneously in the intact tissue. Here, we extend a two-photon microscope with an electrically tunable lens allowing us to obtain optical vertical slices of the IPL, which provide a complete picture of the response diversity of bipolar cells at a "single glance". The nature of these axial recordings additionally allowed us to isolate and investigate batch effects, i.e. inter-experimental variations resulting in systematic differences in response speed. As a proof of principle, we developed a simple model that disentangles biological from experimental causes of variability and allowed us to recover the characteristic gradient of response speeds across the IPL with higher precision than before. Our new framework will make it possible to study the computations performed in the central synaptic layer of the retina more efficiently. The primary excitatory pathway of the mouse retina consists of photoreceptors, bipolar cells (BCs) and retinal ganglion cells (RGCs) (reviewed in refs. 1,2). At the core of this pathway is the inner plexiform layer (IPL), a dense synaptic plexus composed of the axon terminals of BCs, the neurites of amacrine cells, as well as the dendrites of RGCs. Specifically, the photoreceptor signal is relayed by the BCs to the RGCs via glutamatergic synapses (reviewed in ref. 3). This "vertical" transmission is shaped by mostly inhibitory interactions with amacrine cells, which integrate signals laterally along and/or vertically across the IPL (reviewed in ref. 4). Amacrine cells modulate, for instance, the sensitivity of BCs to certain spatio-temporal features 5-7. Within the IPL, the axon terminals of each of the 14 BC types 8-12 project to a distinct depth with axonal profiles of different BC types partially overlapping and jointly covering the whole depth of the IPL 10,11,13. Functionally, each BC type constitutes a particular feature channel, with certain temporal dynamics 7 , including On and Off BC types sensitive to light increments or decrements, respectively 14 , different kinetics 15,16 , and chromatic signals 17,18. Some of these features are systematically mapped across the IPL: For example, On BCs project to the inner and Off BCs to the outer portion of the IPL 14,19. Also kinetic response properties appear to be mapped, with the axonal profiles of more transient BCs localised in the IPL centre 7,15,20,21. To study BC function, early studies mostly used single-cell electrical recordings in vertical slices, where many lateral connections (e.g. large-scale amacrine cells) are severed, o...

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“…Notably, however, the inclusion of interaction terms between nearby cells of different types did slightly improve reconstructions, and the resulting oriented spatial filters were explained by the simple output nonlinearities in RGCs (Figure 9). As new cell types are identified and characterized (Puller et al, 2015;Rhoades et al, 2019), their contributions to vision may be revealed by these linear and simple nonlinear reconstruction approaches.…”

Section: Spatial Information In a Naturalistic Moviementioning

confidence: 99%

Reconstruction of natural images from responses of primate retinal ganglion cells

Brackbill

Rhoades

Kling

et al. 2020

Preprint

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The visual message conveyed by a retinal ganglion cell (RGC) is often summarized by its spatial receptive field, but in principle should also depend on other cells' responses and natural image statistics. To test this idea, linear reconstruction (decoding) of natural images was performed using combinations of responses of four high-density macaque RGC types, revealing consistent visual representations across retinas. Each cell's visual message, defined by the optimal reconstruction filter, reflected natural image statistics, and resembled the receptive field only when nearby, same-type cells were included. Reconstruction from each cell type revealed different and largely independent visual representations, consistent with their distinct properties. Stimulus-independent correlations primarily affected reconstructions from noisy responses. Nonlinear response transformation slightly improved reconstructions with either ON or OFF parasol cells, but not both. Inclusion of ON-OFF interactions enhanced reconstruction by emphasizing oriented edges, consistent with linear-nonlinear encoding models. Spatiotemporal reconstructions revealed similar spatial visual messages.

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Unusual Physiological Properties of Smooth Monostratified Ganglion Cell Types in Primate Retina

Cited by 56 publications

References 71 publications

The temporal structure of the inner retina at a single glance

The temporal structure of the inner retina at a single glance

The temporal structure of the inner retina at a single glance

Reconstruction of natural images from responses of primate retinal ganglion cells

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