A retinal origin of nystagmus—a perspective

Congenital nystagmus is a condition where the eyes of patients oscillate, mostly horizontally, with a frequency of between 2 and 10 Hz. Historically, nystagmus is believed to be caused by a maladaptation of the oculomotor system and is thus considered a disease of the brain stem. However, we have recently shown that congenital nystagmus associated with congenital stationary night blindness is caused by synchronously oscillating retinal ganglion cells. In this perspective article, we discuss how some details of nystagmus can be accounted for by the retinal mechanism we propose

Development of refractive errors - what can we learn from inherited retinal dystrophies?

PURPOSE: It is unknown which retinal cells are involved in the retina-to-sclera signaling cascade causing myopia. As inherited retinal dystrophies (IRD) are characterized by dysfunction of a single retinal cell type and have a high risk of refractive errors, a study investigating the affected cell type, causal gene and refractive error in IRDs may provide insight herein. DESIGN: Case-control study. METHODS: _Study population:_ 302 patients with IRD from two ophthalmogenetic centers in the Netherlands. _Reference population:_ population-based Rotterdam Study-III and ERF Study (N=5,550). Distributions and mean spherical equivalent (SE) were calculated for main affected cell type and causal gene; and risks of myopia and hyperopia were evaluated using logistic regression. RESULTS: Bipolar cell related dystrophies were associated with the highest risk of SE high myopia 239.7; OR mild hyperopia 263.2, both P<0.0001; SE -6.86 D [SD 6.38]); followed by cone dominated dystrophies (OR high myopia 19.5, P<0.0001; OR high hyperopia 10.7, P=0.033; SE -3.10 D [SD 4.49]); rod dominated dystrophies (OR high myopia 10.1, P<0.0001; OR high hyperopia 9.7, P=0.001; SE -2.27 D [SD 4.65]); and RPE related dystrophies (OR low myopia 2.7; P=0.001; OR high hyperopia 5.8; P=0.025; SE -0.10 D [SD 3.09]). Mutations in RPGR (SE -7.63 D [SD 3.31]) and CACNA1F (SE -5.33 D [SD 3.10]) coincided with the highest degree of myopia; in CABP4 (SE 4.81 D [SD 0.35]) with the highest degree of hyperopia. CONCLUSIONS: Refractive errors, in particular myopia, are common in IRD. The bipolar synapse, and the inner and outer segments of the photoreceptor may serve as critical sites for myopia development

Synaptic Transmission from Horizontal Cells to Cones Is Impaired by Loss of Connexin Hemichannels

In the vertebrate retina, horizontal cells generate the inhibitory surround of bipolar cells, an essential step in contrast enhancement. For the last decades, the mechanism involved in this inhibitory synaptic pathway has been a major controversy in retinal research. One hypothesis suggests that connexin hemichannels mediate this negative feedback signal; another suggests that feedback is mediated by protons. Mutant zebrafish were generated that lack connexin 55.5 hemichannels in horizontal cells. Whole cell voltage clamp recordings were made from isolated horizontal cells and cones in flat mount retinas. Light-induced feedback from horizontal cells to cones was reduced in mutants. A reduction of feedback was also found when horizontal cells were pharmacologically hyperpolarized but was absent when they were pharmacologically depolarized. Hemichannel currents in isolated horizontal cells showed a similar behavior. The hyperpolarization-induced hemichannel current was strongly reduced in the mutants while the depolarization-induced hemichannel current was not. Intracellular recordings were made from horizontal cells. Consistent with impaired feedback in the mutant, spectral opponent responses in horizontal cells were diminished in these animals. A behavioral assay revealed a lower contrast-sensitivity, illustrating the role of the horizontal cell to cone feedback pathway in contrast enhancement. Model simulations showed that the observed modifications of feedback can be accounted for by an ephaptic mechanism. A model for feedback, in which the number of connexin hemichannels is reduced to about 40%, fully predicts the specific asymmetric modification of feedback. To our knowledge, this is the first successful genetic interference in the feedback pathway from horizontal cells to cones. It provides direct evidence for an unconventional role of connexin hemichannels in the inhibitory synapse between horizontal cells and cones. This is an important step in resolving a long-standing debate about the unusual form of (ephaptic) synaptic transmission between horizontal cells and cones in the vertebrate retina

Nystagmus in patients with congenital stationary night blindness (CSNB) originates from synchronously firing retinal ganglion cells

Congenital nystagmus, involuntary oscillating small eye movements, is commonly thought to originate from aberrant interactions between brainstem nuclei and foveal cortical pathways. Here, we investigated whether nystagmus associated with congenital stationary night blindness (CSNB) results from primary deficits in the retina. We found that

Localization of metabotropic glutamate receptors in the outer plexiform layer of the goldfish retina

We studied the localization of metabotropic glutamate receptors (mGluRs) in the goldfish outer plexiform layer by light-and electron-microscopical immunohistochemistry. The mGluR1α antibody labeled putative ON-type bipolar cell dendrites and horizontal cell processes in both rod spherules and cone triads. Immunolabeling for mGluR2/3 was absent in the rod synaptic complex but was found at horizontal cell dendrites directly opposing the cone synaptic ribbon. The mGluR5 antibody labeled Müller cell processes wrapping rod terminals and horizontal cell somata. The mGluR7 antibody labeled mainly horizontal cell dendrites invaginating rods and cones and some putative bipolar cell dendrites in the cone synaptic complex. The finding of abundant expression of various mGluRs in bipolar and horizontal cell dendrites suggests multiple sites of glutamatergic modulation in the outer retina

Correction:How the COVID-19 pandemic highlights the necessity of animal research (vol 30, pg R1014, 2020)

(Current Biology 30, R1014–R1018; September 21, 2020) As a result of an author oversight in the originally published version of this article, a number of errors were introduced in the author list and affiliations. First, the middle initials were omitted from the names of several authors. Second, the surname of Dr. van Dam was mistakenly written as “Dam.” Third, the first name of author Bernhard Englitz was misspelled as “Bernard” and the surname of author B.J.A. Pollux was misspelled as “Pullox.” Finally, Dr. Keijer's first name was abbreviated rather than written in full. These errors, as well as various errors in the author affiliations, have now been corrected online

OptiFlex: Multi-Frame Animal Pose Estimation Combining Deep Learning With Optical Flow

Animal pose estimation tools based on deep learning have greatly improved animal behaviour quantification. These tools perform pose estimation on individual video frames, but do not account for variability of animal body shape in their prediction and evaluation. Here, we introduce a novel multi-frame animal pose estimation framework, referred to as OptiFlex. This framework integrates a flexible base model (i.e., FlexibleBaseline), which accounts for variability in animal body shape, with an OpticalFlow model that incorporates temporal context from nearby video frames. Pose estimation can be optimised using multi-view information to leverage all four dimensions (3D space and time). We evaluate FlexibleBaseline using datasets of four different lab animal species (mouse, fruit fly, zebrafish, and monkey) and introduce an intuitive evaluation metric—adjusted percentage of correct key points (aPCK). Our analyses show that OptiFlex provides prediction accuracy that outperforms current deep learning based tools, highlighting its potential for studying a wide range of behaviours across different animal species

OptiFlex: Multi-Frame Animal Pose Estimation Combining Deep Learning With Optical Flow

Animal pose estimation tools based on deep learning have greatly improved animal behaviour quantification. These tools perform pose estimation on individual video frames, but do not account for variability of animal body shape in their prediction and evaluation. Here, we introduce a novel multi-frame animal pose estimation framework, referred to as OptiFlex. This framework integrates a flexible base model (i.e., FlexibleBaseline), which accounts for variability in animal body shape, with an OpticalFlow model that incorporates temporal context from nearby video frames. Pose estimation can be optimised using multi-view information to leverage all four dimensions (3D space and time). We evaluate FlexibleBaseline using datasets of four different lab animal species (mouse, fruit fly, zebrafish, and monkey) and introduce an intuitive evaluation metric—adjusted percentage of correct key points (aPCK). Our analyses show that OptiFlex provides prediction accuracy that outperforms current deep learning based tools, highlighting its potential for studying a wide range of behaviours across different animal species