The Morphological Identity of Insect Dendrites

Dendrite morphology, a neuron's anatomical fingerprint, is a neuroscientist's asset in unveiling organizational principles in the brain. However, the genetic program encoding the morphological identity of a single dendrite remains a mystery. In order to obtain a formal understanding of dendritic branching, we studied distributions of morphological parameters in a group of four individually identifiable neurons of the fly visual system. We found that parameters relating to the branching topology were similar throughout all cells. Only parameters relating to the area covered by the dendrite were cell type specific. With these areas, artificial dendrites were grown based on optimization principles minimizing the amount of wiring and maximizing synaptic democracy. Although the same branching rule was used for all cells, this yielded dendritic structures virtually indistinguishable from their real counterparts. From these principles we derived a fully-automated model-based neuron reconstruction procedure validating the artificial branching rule. In conclusion, we suggest that the genetic program implementing neuronal branching could be constant in all cells whereas the one responsible for the dendrite spanning field should be cell specific

The Morphological Identity of Insect Dendrites

Dendrite morphology, a neuron's anatomical fingerprint, is a neuroscientist's asset in unveiling organizational principles in the brain. However, the genetic program encoding the morphological identity of a single dendrite remains a mystery. In order to obtain a formal understanding of dendritic branching, we studied distributions of morphological parameters in a group of four individually identifiable neurons of the fly visual system. We found that parameters relating to the branching topology were similar throughout all cells. Only parameters relating to the area covered by the dendrite were cell type specific. With these areas, artificial dendrites were grown based on optimization principles minimizing the amount of wiring and maximizing synaptic democracy. Although the same branching rule was used for all cells, this yielded dendritic structures virtually indistinguishable from their real counterparts. From these principles we derived a fully-automated model-based neuron reconstruction procedure validating the artificial branching rule. In conclusion, we suggest that the genetic program implementing neuronal branching could be constant in all cells whereas the one responsible for the dendrite spanning field should be cell specific

The morphological identity of insect dendrites

Dendrite morphology is the most prominent feature of nerve cells, investigated since the origins of modern neuroscience. The last century of neuroanatomical research has revealed an overwhelming diversity of different dendritic shapes and complexities. Its great variability, however, largely interferes with understanding the underlying principles of neuronal wiring and its functional implications. This work addresses this issue by studying a morphological and functional exception- ally conserved network of neurons located in the visual system of flies. Lobula Plate Tangential Cells (LPTCs) have been shown to compute motion vision and contribute to the impressive flight capabilities of flies. Cells of this system exhibit a high degree of constancy in topographic location, morphology and function over all individuals of one species. This constancy allows investigation of functionally identical cells over a large population of flies, and therefore potentially to truly understand the underlying principles of their morphologies. Supported by a large database of in vivo cell reconstructions and a computational quantification framework, it was possible to uncover some of those principles of LPTC anatomy. We show that the key to the cells’ morphological identity lies in the size and shape of the area they span into. Their detailed branching structure and topology is then merely a result of a common growth program shared by all analyzed cells. Application of a previously published branching theory confirmed this finding. When grown into the spanning fields obtained from the in vivo cell reconstruction, artificial cells could be synthesized that resembled all anatomical properties that characterize their natural counterparts. Furthermore, the morphological comparison of the same identified cells in Calliphora and Drosophila allowed to study a functionally conserved system under the influence of extensive down-scaling. The huge size reduction did not affect the underlying branching principles: Drosophila LPTCs followed the very same rules as their Calliphora coun- terparts. On the other hand, we observed significant differences in complexity and relative diameter scaling. An electrotonic analysis revealed that these differences can be explained by a common functional architecture implemented in the LPTCs of both species. Finally, we could modify the LPTC neuronal interaction behavior thanks to the genetical accessibility of Drosophila’s wiring program. The transmembrane protein family Dscam has been shown to mediate the process of adhesion and repulsion of neurites. By manipulating the molecular Dscam profile in Drosophila LPTCs it was possible to change their morphological expansion. The low variability of the LPTCs spanning field in wild type flies and their two-dimensional extension allowed to thoroughly map these morphological alterations in flies with Dscam modifications. In line with the LPTCs retinotopic input arrangement, electrophysiological experiments yielded an inherent linear relationship of their locally reduced dendritic coverage and their locally reduced stimulus sensitivity. With this work I hope to contribute to the general understanding of neuronal morphology of LPTCs and to present a valuable workflow for the analysis of neuronal structure

Bone in vivo: Surface mapping technique

Bone surface mapping technique is proposed on the bases of two kinds of uniqueness of bone in vivo, (i) magnitude of the principal moments of inertia, (ii) the direction cosines of principal axes of inertia relative to inertia reference frame. We choose the principal axes of inertia as the bone coordinate system axes. The geographical marks such as the prime meridian of the bone in vivo are defined and methods such as tomographic reconstruction and boundary development are employed so that the surface of bone in vivo can be mapped. Experimental results show that the surface mapping technique can both reflect the shape and help study the surface changes of bone in vivo. The prospect of such research into the surface shape and changing laws of organ, tissue or cell will be promising.Comment: 9 pages, 6 figure

Preserving neural function under extreme scaling

Important brain functions need to be conserved throughout organisms of extremely varying sizes. Here we study the scaling properties of an essential component of computation in the brain: the single neuron. We compare morphology and signal propagation of a uniquely identifiable interneuron, the HS cell, in the blowfly (Calliphora) with its exact counterpart in the fruit fly (Drosophila) which is about four times smaller in each dimension. Anatomical features of the HS cell scale isometrically and minimise wiring costs but, by themselves, do not scale to preserve the electrotonic behaviour. However, the membrane properties are set to conserve dendritic as well as axonal delays and attenuation as well as dendritic integration of visual information. In conclusion, the electrotonic structure of a neuron, the HS cell in this case, is surprisingly stable over a wide range of morphological scales

Wiring economy of pyramidal cells in the juvenile rat somatosensory cortex

Ever since Cajal hypothesized that the structure of neurons is designed in such a way as to save space, time and matter, numerous researchers have analyzed wiring properties at different scales of brain organization. Here we test the hypothesis that individual pyramidal cells, the most abundant type of neuron in the cerebral cortex, optimize brain connectivity in terms of wiring length. In this study, we analyze the neuronal wiring of complete basal arborizations of pyramidal neurons in layer II, III, IV, Va, Vb and VI of the hindlimb somatosensory cortical region of postnatal day 14 rats. For each cell, we search for the optimal basal arborization and compare its length with the length of the real dendritic structure. Here the optimal arborization is defined as the arborization that has the shortest total wiring length provided that all neuron bifurcations are respected and the extent of the dendritic arborizations remain unchanged. We use graph theory and evolutionary computation techniques to search for the minimal wiring arborizations. Despite morphological differences between pyramidal neurons located in different cortical layers, we found that the neuronal wiring is near-optimal in all cases (the biggest difference between the shortest synthetic wiring found for a dendritic arborization and the length of its real wiring was less than 5%). We found, however, that the real neuronal wiring was significantly closer to the best solution found in layers II, III and IV. Our studies show that the wiring economy of cortical neurons is related not to the type of neurons or their morphological complexities but to general wiring economy principles

Computational convergence of the path integral for real dendritic morphologies

Neurons are characterised by a morphological structure unique amongst biological cells, the core of which is the dendritic tree. The vast number of dendritic geometries, combined with heterogeneous properties of the cell membrane, continue to challenge scientists in predicting neuronal input-output relationships, even in the case of sub-threshold dendritic currents. The Green’s function obtained for a given dendritic geometry provides this functional relationship for passive or quasi-active dendrites and can be constructed by a sum-over-trips approach based on a path integral formalism. In this paper, we introduce a number of efficient algorithms for realisation of the sum-over-trips framework and investigate the convergence of these algorithms on different dendritic geometries. We demonstrate that the convergence of the trip sampling methods strongly depends on dendritic morphology as well as the biophysical properties of the cell membrane. For real morphologies, the number of trips to guarantee a small convergence error might become very large and strongly affect computational efficiency. As an alternative, we introduce a highly-efficient matrix method which can be applied to arbitrary branching structures

Wide-Field Motion Integration in Fly VS Cells: Insights from an Inverse Approach

Fly lobula plate tangential cells are known to perform wide-field motion integration. It is assumed that the shape of these neurons, and in particular the shape of the subclass of VS cells, is responsible for this type of computation. We employed an inverse approach to investigate the morphology-function relationship underlying wide-field motion integration in VS cells. In the inverse approach detailed, model neurons are optimized to perform a predefined computation: here, wide-field motion integration. We embedded the model neurons to be optimized in a biologically plausible model of fly motion detection to provide realistic inputs, and subsequently optimized model neuron with and without active conductances (gNa, gK, gK(Na)) along their dendrites to perform this computation. We found that both passive and active optimized model neurons perform well as wide-field motion integrators. In addition, all optimized morphologies share the same blueprint as real VS cells. In addition, we also found a recurring blueprint for the distribution of gK and gNa in the active models. Moreover, we demonstrate how this morphology and distribution of conductances contribute to wide-field motion integration. As such, by using the inverse approach we can predict the still unknown distribution of gK and gNa and their role in motion integration in VS cells