Identification of a Circadian Clock-Controlled Neural Pathway in the Rabbit Retina

Background: Although the circadian clock in the mammalian retina regulates many physiological processes in the retina, it is not known whether and how the clock controls the neuronal pathways involved in visual processing. Methodology/Principal Findings: By recording the light responses of rabbit axonless (A-type) horizontal cells under darkadapted conditions in both the day and night, we found that rod input to these cells was substantially increased at night under control conditions and following selective blockade of dopamine D2, but not D1, receptors during the day, so that the horizontal cells responded to very dim light at night but not in the day. Using neurobiotin tracer labeling, we also found that the extent of tracer coupling between rabbit rods and cones was more extensive during the night, compared to the day, and more extensive in the day following D 2 receptor blockade. Because A-type horizontal cells make synaptic contact exclusively with cones, these observations indicate that the circadian clock in the mammalian retina substantially increases rod input to A-type horizontal cells at night by enhancing rod-cone coupling. Moreover, the clock-induced increase in D2 receptor activation during the day decreases rod-cone coupling so that rod input to A-type horizontal cells is minimal. Conclusions/Significance: Considered together, these results identify the rod-cone gap junction as a key site in mammals through which the retinal clock, using dopamine activation of D2 receptors, controls signal flow in the day and night fro

A model of direction selectivity in the starburst amacrine cell network

Displaced starburst amacrine cells (SACs) are retinal interneurons that exhibit GABAA receptor-mediated and Cl− cotransporter-mediated, directionally selective (DS) light responses in the rabbit retina. They depolarize to stimuli that move centrifugally through the receptive field surround and hyperpolarize to stimuli that move centripetally through the surround (Gavrikov et al, PNAS 100(26):16047–16052, 2003, PNAS 103(49):18793–18798, 2006). They also play a key role in the activity of DS ganglion cells (DS GC; Amthor et al, Vis Neurosci 19:495–509 2002; Euler et al, Nature 418:845–852, 2002; Fried et al, Nature 420:411– 414, 2002; Gavrikov et al, PNAS 100(26):16047–16052, 2003, PNAS 103(49):18793–18798, 2006; Lee and Zhou, Neuron 51:787–799 2006; Yoshida et al, Neuron 30:771–780, 2001). In this paper we present a model of strong DS behavior of SACs which relies on the GABA-mediated communication within a tightly interconnected network of these cells and on the glutamate signal that the SACs receive from bipolar cells (a presynaptic cell that receives input from cones). We describe how a moving light stimulus can produce a large, sustained depolarization of the SAC dendritic tips that point in the direction that the stimulus moves (i.e., centrifugal motion), but produce a minimal depolarization of the dendritic tips that point in the opposite direction (i.e., centripetal motion). This DS behavior, which is quantified based on the relative size and duration of the depolarizations evoked by stimulus motion at dendritic tips pointing in opposite directions, is robust to changes of many different parameter values and consistent with experimental data. In addition, the DS behavior is strengthened under the assumptions that the Cl− cotransporters Na + -K + -Cl − and K + -Cl − are located in different regions of the SAC dendritic tree (Gavrikov et al, PNAS 103(49):18793–18798, 2006) and that GABA evokes a long-lasting response (Gavrikov et al, PNAS 100(26):16047–16052, 2003, PNAS 103(49):18793–18798, 2006; Lee and Zhou, Neuron 51:787–799, 2006). A possible mechanism is discussed based on the generation of waves of local glutamate and GABA secretion, and their postsynaptic interplay as the waves travel between cell compartments

Towards Machine Wald

The past century has seen a steady increase in the need of estimating and predicting complex systems and making (possibly critical) decisions with limited information. Although computers have made possible the numerical evaluation of sophisticated statistical models, these models are still designed \emph{by humans} because there is currently no known recipe or algorithm for dividing the design of a statistical model into a sequence of arithmetic operations. Indeed enabling computers to \emph{think} as \emph{humans} have the ability to do when faced with uncertainty is challenging in several major ways: (1) Finding optimal statistical models remains to be formulated as a well posed problem when information on the system of interest is incomplete and comes in the form of a complex combination of sample data, partial knowledge of constitutive relations and a limited description of the distribution of input random variables. (2) The space of admissible scenarios along with the space of relevant information, assumptions, and/or beliefs, tend to be infinite dimensional, whereas calculus on a computer is necessarily discrete and finite. With this purpose, this paper explores the foundations of a rigorous framework for the scientific computation of optimal statistical estimators/models and reviews their connections with Decision Theory, Machine Learning, Bayesian Inference, Stochastic Optimization, Robust Optimization, Optimal Uncertainty Quantification and Information Based Complexity.Comment: 37 page

Testing a global standard for quantifying species recovery and assessing conservation impact

Recognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a “Green List of Species” (now the IUCN Green Status of Species). A draft Green Status framework for assessing species’ progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species’ viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics (conservation legacy, conservation dependence, conservation gain, and recovery potential). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species’ recovery scores, we propose the following species recovery categories: fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty-nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics, indicating that conservation has, or will, play a role in improving or maintaining species status for the vast majority of these species. Based on our results, we devised an updated assessment framework that introduces the option of using a dynamic baseline to assess future impacts of conservation over the short term to avoid misleading results which were generated in a small number of cases, and redefines short term as 10 years to better align with conservation planning. These changes are reflected in the IUCN Green Status of Species Standard

Testing a global standard for quantifying species recovery and assessing conservation impact.

Recognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a "Green List of Species" (now the IUCN Green Status of Species). A draft Green Status framework for assessing species' progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species' viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics (conservation legacy, conservation dependence, conservation gain, and recovery potential). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species' recovery scores, we propose the following species recovery categories: fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty-nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics, indicating that conservation has, or will, play a role in improving or maintaining species status for the vast majority of these species. Based on our results, we devised an updated assessment framework that introduces the option of using a dynamic baseline to assess future impacts of conservation over the short term to avoid misleading results which were generated in a small number of cases, and redefines short term as 10 years to better align with conservation planning. These changes are reflected in the IUCN Green Status of Species Standard

Circadian clock regulation of cone to horizontal cell synaptic transfer in the goldfish retina.

Although it is well established that the vertebrate retina contains endogenous circadian clocks that regulate retinal physiology and function during day and night, the processes that the clocks affect and the means by which the clocks control these processes remain unresolved. We previously demonstrated that a circadian clock in the goldfish retina regulates rod-cone electrical coupling so that coupling is weak during the day and robust at night. The increase in rod-cone coupling at night introduces rod signals into cones so that the light responses of both cones and cone horizontal cells, which are post-synaptic to cones, become dominated by rod input. By comparing the light responses of cones, cone horizontal cells and rod horizontal cells, which are post-synaptic to rods, under dark-adapted conditions during day and night, we determined whether the daily changes in the strength of rod-cone coupling could account entirely for rhythmic changes in the light response properties of cones and cone horizontal cells. We report that although some aspects of the day/night changes in cone and cone horizontal cell light responses, such as response threshold and spectral tuning, are consistent with modulation of rod-cone coupling, other properties cannot be solely explained by this phenomenon. Specifically, we found that at night compared to the day the time course of spectrally-isolated cone photoresponses was slower, cone-to-cone horizontal cell synaptic transfer was highly non-linear and of lower gain, and the delay in cone-to-cone horizontal cell synaptic transmission was longer. However, under bright light-adapted conditions in both day and night, cone-to-cone horizontal cell synaptic transfer was linear and of high gain, and no additional delay was observed at the cone-to-cone horizontal cell synapse. These findings suggest that in addition to controlling rod-cone coupling, retinal clocks shape the light responses of cone horizontal cells by modulating cone-to-cone horizontal cell synaptic transmission

The retinal circadian clock uses dopamine and D₂ receptors to control the light responses of rabbit A-type horizontal cells.

<p><i>A-G</i>, Representative examples of A-type horizontal cell responses to a series of 500 ms full-field white light stimuli of increasing intensity recorded under dark-adapted conditions during the subjective day (<i>A</i>), the subjective night (<i>B</i>), the day (<i>C</i>), the night (<i>D</i>), the day in the presence of the D₂ dopamine receptor antagonist spiperone (10 µM) (<i>E</i>), the night in the presence of D₂ dopamine receptor agonist quinpirole (1 µM) (<i>F</i>), and the day in the presence of the D₁ dopamine receptor antagonist SCH23390 (10 µM) (<i>G</i>). The light responses of only 1 cell per retina to the full series of light intensities were recorded.</p