A novel machine learning-based approach for the detection and analysis of spontaneous synaptic currents

Spontaneous synaptic activity is a hallmark of biological neural networks. A thorough description of these synaptic signals is essential for understanding neurotransmitter release and the generation of a postsynaptic response. However, the complexity of synaptic current trajectories has either precluded an in-depth analysis or it has forced human observers to resort to manual or semi-automated approaches based on subjective amplitude and area threshold settings. Both procedures are time-consuming, error-prone and likely affected by human bias. Here, we present three complimentary methods for a fully automated analysis of spontaneous excitatory postsynaptic currents measured in major cell types of the mouse retina and in a primary culture of mouse auditory cortex. Two approaches rely on classical threshold methods, while the third represents a novel machine learning-based algorithm. Comparison with frequently used existing methods demonstrates the suitability of our algorithms for an unbiased and efficient analysis of synaptic signals in the central nervous system

The structure dilemma in biological and artificial neural networks

Brain research up to date has revealed that structure and function are highly related. Thus, for example, studies have repeatedly shown that the brains of patients suffering from schizophrenia or other diseases have a different connectome compared to healthy people. Apart from stochastic processes, however, an inherent logic describing how neurons connect to each other has not yet been identified. We revisited this structural dilemma by comparing and analyzing artificial and biological-based neural networks. Namely, we used feed-forward and recurrent artificial neural networks as well as networks based on the structure of the micro-connectome of C. elegans and of the human macro-connectome. We trained these diverse networks, which markedly differ in their architecture, initialization and pruning technique, and we found remarkable parallels between biological-based and artificial neural networks, as we were additionally able to show that the dilemma is also present in artificial neural networks. Our findings show that structure contains all the information, but that this structure is not exclusive. Indeed, the same structure was able to solve completely different problems with only minimal adjustments. We particularly put interest on the influence of weights and the neuron offset value, as they show a different adaption behaviour. Our findings open up new questions in the fields of artificial and biological information processing research

Effektivitätsmessung durch die Evaluation von Lehr-Lernarrangements

Im vorliegenden Beitrag wird die Thematik der Effektivitätsmessung von pädagogischen Maßnahmen im Masterstudiengang Qualitäts- und Prozessmanagement abgehandelt. Hierbei wird versucht, an Hand des Vier-Stufen-Modells nach Kirkpatrick die Überlegungen zur Messung und Interpretation der Maßnahmeneffektivität aufzuzeigen. Am Ende erfolgen ein Resümee und eine kritische Würdigung der eingesetzten Maßnahmen

Eine bioinformatische und immunocytochemische Charakterisierung von Horizontalzellen der Retina

This work was intended to characterize retinal horizontal cells on the basis of especially bioinformatic scRNA seq analyses but as well immunocytochemical investigations. The results consist of a classification of horizontal cell subtypes, and the expression data of glutamate receptors, ionotropic as well as metabotropic, calcium and sodium channels, and GABA receptors in four different species: mouse, human, macaque and chicken. One key finding of this work was the lack of transferability of results, even within very closely related species. This mainly concerns the expression and distribution of ion channels and receptors, but has also already been clearly demonstrated in the study and classification of horizontal cell subtypes.Ziel dieser Arbeit war die Charakterisierung retinaler Horizontalzellen auf der Basis von insbesondere bioinformatischen scRNA seq-Analysen, aber auch immuncytochemischen Untersuchungen. Die Ergebnisse bestehen aus einer Klassifizierung der horizontalen Zellsubtypen und den Expressionsdaten von Glutamatrezeptoren, ionotropen und metabotropen, Kalzium- und Natriumkanälen sowie GABA-Rezeptoren in vier verschiedenen Spezies: Maus, Mensch, Makake und Huhn. Eine wichtige Erkenntnis dieser Arbeit war die mangelnde Übertragbarkeit der Ergebnisse, selbst innerhalb sehr eng verwandter Arten. Dies betrifft vor allem die Expression und Verteilung von Ionenkanälen und Rezeptoren, wurde aber auch schon bei der Untersuchung und Klassifizierung von horizontalen Zellsubtypen deutlich

Coexpression of PD-1, 2B4, CD160 and KLRG1 on exhausted HCV-specific CD8+ T cells is linked to antigen recognition and T cell differentiation.

Exhausted CD8+ T cell responses during chronic viral infections are defined by a complex expression pattern of inhibitory receptors. However, very little information is currently available about the coexpression patterns of these receptors on human virus-specific CD8+ T cells and their correlation with antiviral functions, T cell differentiation and antigen recognition. We addressed these important aspects in a cohort of 38 chronically HCV infected patients and found a coexpression of inhibitory receptors such as 2B4, CD160 and KLRG1 in association with PD-1 in about half of the HCV-specific CD8+ T cell responses. Importantly, this exhaustive phenotype was associated with low and intermediate levels of CD127 expression, an impaired proliferative capacity, an intermediate T cell differentiation stage and absence of sequence variations within the corresponding epitopes, indicating ongoing antigen triggering. In contrast, a low expression of inhibitory receptors by the remaining HCV-specific CD8+ T cells occurred in concert with a CD127hi phenotype, an early T cell differentiation stage and presence of viral sequence variations within the corresponding epitopes. In sum, these results suggest that T cell exhaustion contributes to the failure of about half of HCV-specific CD8+ T cell responses and that it is determined by a complex interplay of immunological (e.g. T cell differentiation) and virological (e.g. ongoing antigen triggering) factors

Cell Types and Synapses Expressing the SNARE Complex Regulating Proteins Complexin 1 and Complexin 2 in Mammalian Retina

Complexins (Cplxs) 1 to 4 are components of the presynaptic compartment of chemical synapses where they regulate important steps in synaptic vesicle exocytosis. In the retina, all four Cplxs are present, and while we know a lot about Cplxs 3 and 4, little is known about Cplxs 1 and 2. Here, we performed in situ hybridization experiments and bioinformatics and exploited Cplx 1 and Cplx 2 single-knockout mice combined with immunocytochemistry and light microscopy to characterize in detail the cell type and synapse-specific distribution of Cplx 1 and Cplx 2. We found that Cplx 2 and not Cplx 1 is the main isoform expressed in normal and displaced amacrine cells and ganglion cells in mouse retinae and that amacrine cells seem to operate with a single Cplx isoform at their conventional chemical synapses. Surprising was the finding that retinal function, determined with electroretinographic recordings, was altered in Cplx 1 but not Cplx 2 single-knockout mice. In summary, the results provide an important basis for future studies on the function of Cplxs 1 and 2 in the processing of visual signals in the mammalian retina