Distributed Dendritic Processing Facilitates Object Detection: A Computational Analysis on the Visual System of the Fly

Hennig P, Möller R, Egelhaaf M. Distributed Dendritic Processing Facilitates Object Detection: A Computational Analysis on the Visual System of the Fly. PLoS ONE. 2008;3(8): e3092.Background: Detecting objects is an important task when moving through a natural environment. Flies, for example, may land on salient objects or may avoid collisions with them. The neuronal ensemble of Figure Detection cells (FD-cells) in the visual system of the fly is likely to be involved in controlling these behaviours, as these cells are more sensitive to objects than to extended background structures. Until now the computations in the presynaptic neuronal network of FD-cells and, in particular, the functional significance of the experimentally established distributed dendritic processing of excitatory and inhibitory inputs is not understood. Methodology/Principal Findings: We use model simulations to analyse the neuronal computations responsible for the preference of FD-cells for small objects. We employed a new modelling approach which allowed us to account for the spatial spread of electrical signals in the dendrites while avoiding detailed compartmental modelling. The models are based on available physiological and anatomical data. Three models were tested each implementing an inhibitory neural circuit, but differing by the spatial arrangement of the inhibitory interaction. Parameter optimisation with an evolutionary algorithm revealed that only distributed dendritic processing satisfies the constraints arising from electrophysiological experiments. In contrast to a direct dendro-dendritic inhibition of the FD-cell (Direct Distributed Inhibition model), an inhibition of its presynaptic retinotopic elements (Indirect Distributed Inhibition model) requires smaller changes in input resistance in the inhibited neurons during visual stimulation. Conclusions/Significance: Distributed dendritic inhibition of retinotopic elements as implemented in our Indirect Distributed Inhibition model is the most plausible wiring scheme for the neuronal circuit of FD-cells. This microcircuit is computationally similar to lateral inhibition between the retinotopic elements. Hence, distributed inhibition might be an alternative explanation of perceptual phenomena currently explained by lateral inhibition networks

Elastosis in chronic radiodermatitis. An ultrastructural study

SCOPUS: ar.jFLWNAinfo:eu-repo/semantics/publishe

Pinguecula and Actinic Elastosis. An Ultrastructural Study

Three cases of pinguecula (conjunctival elastosis) were ultrastructurally investigated. Findings were compared with the features described in cutaneous actinic elastosis. Changes observed were not uniform. In both diseases, numerous elastotic fibers were present with a finely granular matrix and masses of dense grains. The degenerative changes of the elastotic fibers evolved differently in conjunctival stroma and in dermis. The superficial extracellular concretions observed in pinguecula seemed to be an ultimate stage of elastotic degeneration. Like actinic elastosis and elastosis observed in chronic radiodermatitis, pinguecula is believed to result from a dystrophic increased elastogenesis induced by chronic irradiation, with secondary degenerative changes.SCOPUS: ar.jFLWNAinfo:eu-repo/semantics/publishe

Minimal Conductance-Based Model of Auditory Coincidence Detector Neurons

Sound localization is a fundamental sensory function of a wide variety of animals. The interaural time difference (ITD), an important cue for sound localization, is computed in the auditory brainstem. In our previous modeling study, we introduced a two-compartment Hodgkin-Huxley type model to investigate how cellular and synaptic specializations may contribute to precise ITD computation of the barn owl's auditory coincidence detector neuron. Although our model successfully reproduced fundamental physiological properties observed in vivo, it was unsuitable for mathematical analyses and large scale simulations because of a number of nonlinear variables. In the present study, we reduce our former model into three types of conductance-based integrate-and-fire (IF) models. We test their electrophysiological properties using data from published in vivo and in vitro studies. Their robustness to parameter changes and computational efficiencies are also examined. Our numerical results suggest that the single-compartment active IF model is superior to other reduced models in terms of physiological reproducibility and computational performance. This model will allow future theoretical studies that use more rigorous mathematical analysis and network simulations