Closed-loop experiments to investigate spatial contrast integration in the retina

The fundamental goal of all neuronal processing is to make optimal decisions, and thereby to generate optimal behavior. To this end, the brain performs at each point in time millions of parallel computations. Right now, your brain might weigh thoroughly if it is worth to continue reading this thesis or not. In the end however, weighing is not enough: a decision has to be made. Such a decision is an intrinsically nonlinear process. If two possibilities are nearly equally evaluated, a small change in your considerations might lead to the acceptance of one alternative, and the rejection of the other. Furthermore, not all considerations have to contribute linearly to the decision. For example, a lack of time might certainly keep you from reading this thesis, while having excess spare time might still not make you read it. Such a nonlinear weighing of considerations does not only occur on the conscious level, but all the time in the individual neuronal circuits of the brain. Each neuron can be interpreted as a decision unit, computing whether to spike or not. It typically receives multiple parallel streams of information, and based on these generates its own neuronal output. The inputs resemble the considerations taken into account, while the output conveys the decision to subsequent circuits. How the decision is made is therefore determined by the way the inputs are combined into the neuronal output. In particular, individual inputs might contribute either linearly or nonlinearly to the decision. Thus, in order to understand which role a neuron plays in information processing, we have to assess the nonlinearities involved in the integration of different neuronal inputs. In this thesis, we study this ubiquitous signal integration in the output neurons of the amphibian retina, the retinal ganglion cells. Thereby we hope to gain a better understanding of the general mechanisms underlying signal integration in the circuits of the brain. This will also help us elucidate the functions of the retina in particular. Because of the high similarity of the retinas among all vertebrates, by studying the amphibian retina we also learn to better understand human vision. The amphibian retina is particularly suited to study the nonlinear integration of neuronal signals, because each single ganglion cell receives distinct inputs originating from tens to hundreds of photoreceptors. Indeed, ganglion cells do not just linearly average these inputs, but combine them in a nonlinear fashion. It turned out that it is precisely this nonlinearity which allows specific ganglion cells to decide whether particular features were present in their visual input. Hence, an understanding of how the retina encodes images into neuronal activity requires an understanding of how the spatially distinct light stimuli, that each cell experiences, are combined into the output of this very cell. This is the question of spatial integration which we address in the following. Many facts about this question are already available on a cellular level. Today we know which cell types mediate the signals from the photoreceptors to the ganglion cell, and we know much about the connections between the involved cells. Furthermore, in recent studies the transmission functions of some of the involved circuit elements were measured. In particular, it turned out that many of the processing steps are highly nonlinear. Although all these details are known, a detailed phenomenological description of spatial integration is still lacking. Most current models assume a linear integration, and thereby simply neglect the nonlinearities occurring on the cellular level. In this thesis, we attempt to fill the gap and strive for a functional characterization of spatial integration, and in particular of the involved nonlinearities. We pursued the investigation by performing electrophysiological experiments on retinal ganglion cells. In particular, we measured the neuronal output with an array of electrodes. While measuring, we presented videos containing well-defined light stimuli to the retina. We performed the experiments in a closed-loop approach which allowed us to assess the neuronal response online and use the results to determine the subsequently shown stimuli. The visual area, over which a ganglion cell pools its input, is called the receptive field of the cell. It has been known for almost 60 years that the receptive fields of many ganglion cells are organized in a center-surround structure. In the receptive field center, the cell is most sensitive to visual stimulation. Depending on the cell, it preferentially responds to either a brightening (ON cell) or a darkening (OFF cell) of the image. In contrast, the response in the receptive field surround is weaker, and it is of opposite sign than the center response. Taking this structural segregation of the receptive field into account, we divided our experiments into two parts. First, we determined how different stimuli are combined within the receptive field center. Afterwards, we focused on the integration of stimuli in the center and the surround. Throughout this thesis, we used a specific approach to study spatial integration. This approach is the measurement of so-called iso-response stimuli. Instead of showing predefined stimuli and measuring the neuronal outputs, we did the experiments the other way round: we predefined the output, and then searched for those stimuli which yielded the chosen response. The result of such a measurement was a set of stimuli which all triggered the same neuronal response in a given ganglion cell. Thereby, the cell’s response was either defined as the number of elicited spikes (iso-rate stimuli), or the first-spike latency (iso-latency stimuli). Iso-response stimuli allowed us to directly assess the nonlinearities involved in signal integration in retinal ganglion cells

Regulation der O-Glykosylierung in GlcNAc/GalNAc-Epimerase-defizienten CHO-Mutanten

Aufgrund der sukzessiven Addition von Monosaccharid-Bausteinen wird vermutet, dass neben der Peptidsequenz auch epigenetische Parameter wie die Kompetition zwischen enzymatischen Schritten bei der Initiation und der Elongation von O-Glykanen einen Einfluss auf den Ort und die Struktur der Glykane ausueben. Durch die rekombinante Glykosylierungssonde MUC1 in ldlD-Zellen, die durch eine defekte UDP-GlcNAc/UDP-GalNAc-Epimerase gekennzeichnet sind, konnte extern die O-Glykosylierung durch Supplementierung mit GalNAc (Initiation der O-Glykosylierung) und Gal und GalNAc (Elongation) beeinflusst werden. Durch Kotransfektion der core2 defizienten Zellen mit der core2 spezifischen GlcNAc-Transferase (C2GnT3) konnten Einfluesse der core2-Synthese auf das O-Glykosylierungsprofil der MUC1-Sonde in ldlD-Zellen untersucht werden. In dem O-Glykosylierungsprofil nicht kotransfizierter ldlD-Zellen dominierten sialylierte core1-Trisaccharide vergleichbar mit dem Glykanprofil der Wildtyp-CHO-Zellen. Durch die Koexpression mit C2GnT3 konnten core2-Strukturen (bei Supplementierung mit Gal und GalNAc) detektiert werden. Wie erwartet konkurrierte die 6-Sialylierung von core1 (Gal-GalNAc) direkt mit der Addition von GlcNAc durch C2GnT3. Auch eine indirekte Kompetition zwischen 3-Sialyltransferase und C2GnT3 konnte nachgewiesen werden. Bei partieller Supplementierung mit GalNAc konnten die kotransfizierten Zellen keine core2-Strukturen bilden. Das Vorhandensein von core1 in Zellen, die nicht mit Gal supplementiert wurden, koennte ein Hinweis auf eine teilweise funktionierende Epimerase sein, wobei auch die Moeglichkeit einer Aufnahme von Gal aus Serumglykoproteinen des FKS nicht aufgeschlossen werden kann. In vitro Studien zeigten, dass Peptidsubstrate mit komplexer O-Glykosylierung (sialyl-T) sowohl eine weitere Initation in benachbarten Positionen erlauben als auch die Synthese von core2-Strukturen. Diese Erkenntnisse koennten Bedeutung fuer die Aufglykosylierung von Membranglykoproteinen haben, die durch das Trans-Golgi-Netzwerk rezyklisieren

General features of the retinal connectome determine the computation of motion anticipation

Motion anticipation allows the visual system to compensate for the slow speed of phototransduction so that a moving object can be accurately located. This correction is already present in the signal that ganglion cells send from the retina but the biophysical mechanisms underlying this computation are not known. Here we demonstrate that motion anticipation is computed autonomously within the dendritic tree of each ganglion cell and relies on feedforward inhibition. The passive and non-linear interaction of excitatory and inhibitory synapses enables the somatic voltage to encode the actual position of a moving object instead of its delayed representation. General rather than specific features of the retinal connectome govern this computation: an excess of inhibitory inputs over excitatory, with both being randomly distributed, allows tracking of all directions of motion, while the average distance between inputs determines the object velocities that can be compensated for

Mapping nonlinear receptive field structure in primate retina at single cone resolution

The function of a neural circuit is shaped by the computations performed by its interneurons, which in many cases are not easily accessible to experimental investigation. Here, we elucidate the transformation of visual signals flowing from the input to the output of the primate retina, using a combination of large-scale multi-electrode recordings from an identified ganglion cell type, visual stimulation targeted at individual cone photoreceptors, and a hierarchical computational model. The results reveal nonlinear subunits in the circuity of OFF midget ganglion cells, which subserve high-resolution vision. The model explains light responses to a variety of stimuli more accurately than a linear model, including stimuli targeted to cones within and across subunits. The recovered model components are consistent with known anatomical organization of midget bipolar interneurons. These results reveal the spatial structure of linear and nonlinear encoding, at the resolution of single cells and at the scale of complete circuits

The role of non-native interactions in the folding of knotted proteins: insights from molecular dynamics simulations

For several decades, the presence of knots in naturally-occurring proteins was largely ruled out a priori for its supposed incompatibility with the efficiency and robustness of folding processes. For this very same reason, the later discovery of several unrelated families of knotted proteins motivated researchers to look into the physico-chemical mechanisms governing the concerted sequence of folding steps leading to the consistent formation of the same knot type in the same protein location. Besides experiments, computational studies are providing considerable insight into these mechanisms. Here, we revisit a number of such recent investigations within a common conceptual and methodological framework. By considering studies employing protein models with different structural resolution (coarse-grained or atomistic) and various force fields (from pure native-centric to realistic atomistic ones), we focus on the role of native and non-native interactions. For various unrelated instances of knotted proteins, non-native interactions are shown to be very important for favoring the emergence of conformations primed for successful self-knotting events

Knotted vs. Unknotted Proteins: Evidence of Knot-Promoting Loops

Knotted proteins, because of their ability to fold reversibly in the same topologically entangled conformation, are the object of an increasing number of experimental and theoretical studies. The aim of the present investigation is to assess, on the basis of presently available structural data, the extent to which knotted proteins are isolated instances in sequence or structure space, and to use comparative schemes to understand whether specific protein segments can be associated to the occurrence of a knot in the native state. A significant sequence homology is found among a sizeable group of knotted and unknotted proteins. In this family, knotted members occupy a primary sub-branch of the phylogenetic tree and differ from unknotted ones only by additional loop segments. These "knot-promoting" loops, whose virtual bridging eliminates the knot, are found in various types of knotted proteins. Valuable insight into how knots form, or are encoded, in proteins could be obtained by targeting these regions in future computational studies or excision experiments

The fractal globule as a model of chromatin architecture in the cell

The fractal globule is a compact polymer state that emerges during polymer condensation as a result of topological constraints which prevent one region of the chain from passing across another one. This long-lived intermediate state was introduced in 1988 (Grosberg et al. 1988) and has not been observed in experiments or simulations until recently (Lieberman-Aiden et al. 2009). Recent characterization of human chromatin using a novel chromosome conformational capture technique brought the fractal globule into the spotlight as a structural model of human chromosome on the scale of up to 10 Mb (Lieberman-Aiden et al. 2009). Here, we present the concept of the fractal globule, comparing it to other states of a polymer and focusing on its properties relevant for the biophysics of chromatin. We then discuss properties of the fractal globule that make it an attractive model for chromatin organization inside a cell. Next, we connect the fractal globule to recent studies that emphasize topological constraints as a primary factor driving formation of chromosomal territories. We discuss how theoretical predictions, made on the basis of the fractal globule model, can be tested experimentally. Finally, we discuss whether fractal globule architecture can be relevant for chromatin packing in other organisms such as yeast and bacteria

Spike-Triggered Covariance Analysis Reveals Phenomenological Diversity of Contrast Adaptation in the Retina

When visual contrast changes, retinal ganglion cells adapt by adjusting their sensitivity as well as their temporal filtering characteristics. The latter has classically been described by contrast-induced gain changes that depend on temporal frequency. Here, we explored a new perspective on contrast-induced changes in temporal filtering by using spike-triggered covariance analysis to extract multiple parallel temporal filters for individual ganglion cells. Based on multielectrode-array recordings from ganglion cells in the isolated salamander retina, we found that contrast adaptation of temporal filtering can largely be captured by contrast-invariant sets of filters with contrast-dependent weights. Moreover, differences among the ganglion cells in the filter sets and their contrast-dependent contributions allowed us to phenomenologically distinguish three types of filter changes. The first type is characterized by newly emerging features at higher contrast, which can be reproduced by computational models that contain response-triggered gain-control mechanisms. The second type follows from stronger adaptation in the Off pathway as compared to the On pathway in On-Off-type ganglion cells. Finally, we found that, in a subset of neurons, contrast-induced filter changes are governed by particularly strong spike-timing dynamics, in particular by pronounced stimulus-dependent latency shifts that can be observed in these cells. Together, our results show that the contrast dependence of temporal filtering in retinal ganglion cells has a multifaceted phenomenology and that a multi-filter analysis can provide a useful basis for capturing the underlying signal-processing dynamics