Axons in Cat Visual Cortex are Topologically Self-similar

The axonal arbors of the different types of neocortical and thalamic neurons appear highly dissimilar when viewed in conventional 2D reconstructions. Nevertheless, we have found that their one-dimensional metrics and topologies are surprisingly similar. To discover this, we analysed the axonal branching pattern of 39 neurons (23 spiny, 13 smooth and three thalamic axons) that were filled intracellularly with horseradish peroxidase (HRP) during in vivo experiments in cat area 17. The axons were completely reconstructed and translated into dendrograms. Topological, fractal and Horton-Strahler analyses indicated that axons of smooth and spiny neurons had similar complexity, length ratios (a measure of the relative increase in the length of collateral segments as the axon branches) and bifurcation ratios (a measure of the relative increase in the number of collateral segments as the axon branches). We show that a simple random branching model (Galton-Watson process) predicts with reasonable accuracy the bifurcation ratio, length ratio and collateral length distribution of the axonal arbor

Pharmacokinetics of 1,25-dihydroxyvitamin D3 glycosides from Solanum glaucophyllum extract given in a rumen bolus on blood mineral profiles in dry pregnant dairy cows.

Providing tablets of 1,25-dihydroxyvitamin D3 (1,25(OH)2D3), the biologically active metabolite of vitamin D3, in a rumen bolus may be used as prevention for periparturient hypocalcemia in dairy cows. This study investigated the pharmacokinetics of 1,25(OH)2D3 glycosides extracted from Solanum glaucophyllum (SGE) on blood serum 1,25(OH)2D3, Ca, P and Mg response in dry pregnant dairy cows. Boluses contained tablets of SGE which differed in their release properties (rapid release, slow release and combination) and galenics (200 μg uncoated, 300 μg and 500 μg uncoated or coated, 2 × 500 μg uncoated). Nineteen blood samples were collected from 29 cows between 96 h before and 336 h after bolus administration. Blood serum 1,25(OH)2D3, Ca and P increased between 12 h and 120 h, 12 h and 264 h and 24 h and 264 h, respectively. Highest values were reached at 30 h, 72 h and 120 h for 1,25(OH)2D3, Ca and P, respectively. Baseline values were then reached at 216 h for 1,25(OH)2D3 and 336 h for Ca and P. Concentration of Mg decreased between 24 h and 216 h, before reaching values comparable to baseline at 264 h. Highest Ca values were obtained with the combined rapid and slow release properties (500 μg) and there was no effect from coating on pharmacokinetics. In conclusion, the antepartum oral SGE bolus administration may be suitable for the prevention of periparturient hypocalcemia

Potential of a rumen bolus containing 1,25-dihydroxyvitamin D3 glycosides for the prevention of hypocalcaemia in primiparous and multiparous dairy cows

Periparturient hypocalcaemia is a widespread metabolic disorder in dairy cows. Clinical and subclinical cases occur primarily in multiparous (Multi) cows, but subclinical cases have also been reported in primiparous (Primi) cows. A preventive strategy was investigated by administering the physiologically active vitamin D3 metabolite, 1,25-dihydroxyvitamin D3 (1,25-dihydroxycholecalciferol, 1,25(OH)2D3) as a rumen bolus. The bolus contained tablets of 1,25(OH)2D3 glycoside extract from Solanum glaucophyllum (SGE), releasing SGE over several days. The aim was to study the effect of a bolus containing 0 (C) or 500 µg (SGE) of 1,25(OH)2D3 on 1,25(OH)2D3 and mineral status in periparturient cows up to three weeks into lactation and on colostrum, milk and calves' blood mineral contents. The bolus was administered three to four days prior to expected calving to Primi and Multi cows fed a herbage-based diet (dietary cation-anion difference of +522 mEq/kg DM). One C or SGE bolus was applied to 12 Primi and 12 Multi cows. Blood was regularly sampled (and selected a posteriori for antepartum samples) in regard to the actual calving day (d0), immediately prior to bolus application and at day -2, 0.5, 1, 1.5, 2, 4, 8, 11, 15, 18 and 22. Additional samples included urine (at bolus application, d0.5 and d2), colostrum, milk samples (weekly) and calves' blood (d2). Blood serum 1,25(OH)2D3 increased between d0.5 and d2 in Primi-SGE, but remained unchanged in Primi-C, as did parathyroid hormone (PTH) and Ca in all Primi. Urinary Ca of Primi-SGE was increased on d2, indicating regulation of Ca excess. Three Multi-C cows with confirmed clinical hypocalcaemia needed treatment and thus were excluded from the dataset and replaced. Blood serum 1,25(OH)2D3 and PTH increased while Ca dropped by 40% between d0.5 and d2 in Multi-C, whereas 1,25(OH)2D3, Ca and PTH remained unchanged in Multi-SGE. Blood serum carboxyterminal telopeptide of type I collagen was higher in Primi than in Multi and increased with time, except in Primi-C. Mineral contents in colostrum, milk and blood serum of calves were not influenced to a relevant degree. In conclusion, Primi-C did not, in contrast to Multi-C, develop subclinical hypocalcaemia (<2.0 mmol Ca/l). Prevention of hypocalcaemia with one SGE bolus applied three to four days prior to expected calving was successful in maintaining blood Ca within normal range in Multi over the critical first two days and up to the first three weeks of lactation, without any observed detrimental effects on cows or calves

Topological self-similarity on the random binary-tree model

Asymptotic analysis on some statistical properties of the random binary-tree model is developed. We quantify a hierarchical structure of branching patterns based on the Horton-Strahler analysis. We introduce a transformation of a binary tree, and derive a recursive equation about branch orders. As an application of the analysis, topological self-similarity and its generalization is proved in an asymptotic sense. Also, some important examples are presented

A simple rule for axon outgrowth and synaptic competition generates realistic connection lengths and filling fractions

Neural connectivity at the cellular and mesoscopic level appears very specific and is presumed to arise from highly specific developmental mechanisms. However, there are general shared features of connectivity in systems as different as the networks formed by individual neurons in Caenorhabditis elegans or in rat visual cortex and the mesoscopic circuitry of cortical areas in the mouse, macaque, and human brain. In all these systems, connection length distributions have very similar shapes, with an initial large peak and a long flat tail representing the admixture of long-distance connections to mostly short-distance connections. Furthermore, not all potentially possible synapses are formed, and only a fraction of axons (called filling fraction) establish synapses with spatially neighboring neurons. We explored what aspects of these connectivity patterns can be explained simply by random axonal outgrowth. We found that random axonal growth away from the soma can already reproduce the known distance distribution of connections. We also observed that experimentally observed filling fractions can be generated by competition for available space at the target neurons--a model markedly different from previous explanations. These findings may serve as a baseline model for the development of connectivity that can be further refined by more specific mechanisms.Comment: 31 pages (incl. supplementary information); Cerebral Cortex Advance Access published online on May 12, 200

Synaptic Scaling Balances Learning in a Spiking Model of Neocortex

Learning in the brain requires complementary mechanisms: potentiation and activity-dependent homeostatic scaling. We introduce synaptic scaling to a biologically-realistic spiking model of neocortex which can learn changes in oscillatory rhythms using STDP, and show that scaling is necessary to balance both positive and negative changes in input from potentiation and atrophy. We discuss some of the issues that arise when considering synaptic scaling in such a model, and show that scaling regulates activity whilst allowing learning to remain unaltered.Comment: 10 page

A Comprehensive Workflow for General-Purpose Neural Modeling with Highly Configurable Neuromorphic Hardware Systems

In this paper we present a methodological framework that meets novel requirements emerging from upcoming types of accelerated and highly configurable neuromorphic hardware systems. We describe in detail a device with 45 million programmable and dynamic synapses that is currently under development, and we sketch the conceptual challenges that arise from taking this platform into operation. More specifically, we aim at the establishment of this neuromorphic system as a flexible and neuroscientifically valuable modeling tool that can be used by non-hardware-experts. We consider various functional aspects to be crucial for this purpose, and we introduce a consistent workflow with detailed descriptions of all involved modules that implement the suggested steps: The integration of the hardware interface into the simulator-independent model description language PyNN; a fully automated translation between the PyNN domain and appropriate hardware configurations; an executable specification of the future neuromorphic system that can be seamlessly integrated into this biology-to-hardware mapping process as a test bench for all software layers and possible hardware design modifications; an evaluation scheme that deploys models from a dedicated benchmark library, compares the results generated by virtual or prototype hardware devices with reference software simulations and analyzes the differences. The integration of these components into one hardware-software workflow provides an ecosystem for ongoing preparative studies that support the hardware design process and represents the basis for the maturity of the model-to-hardware mapping software. The functionality and flexibility of the latter is proven with a variety of experimental results

Structural and functional properties of a probabilistic model of neuronal connectivity in a simple locomotor network.

Although, in most animals, brain connectivity varies between individuals, behaviour is often similar across a species. What fundamental structural properties are shared across individual networks that define this behaviour? We describe a probabilistic model of connectivity in the hatchling Xenopus tadpole spinal cord which, when combined with a spiking model, reliably produces rhythmic activity corresponding to swimming. The probabilistic model allows calculation of structural characteristics that reflect common network properties, independent of individual network realisations. We use the structural characteristics to study examples of neuronal dynamics, in the complete network and various sub-networks, and this allows us to explain the basis for key experimental findings, and make predictions for experiments. We also study how structural and functional features differ between detailed anatomical connectomes and those generated by our new, simpler, model

Synchronization in complex networks

Synchronization processes in populations of locally interacting elements are in the focus of intense research in physical, biological, chemical, technological and social systems. The many efforts devoted to understand synchronization phenomena in natural systems take now advantage of the recent theory of complex networks. In this review, we report the advances in the comprehension of synchronization phenomena when oscillating elements are constrained to interact in a complex network topology. We also overview the new emergent features coming out from the interplay between the structure and the function of the underlying pattern of connections. Extensive numerical work as well as analytical approaches to the problem are presented. Finally, we review several applications of synchronization in complex networks to different disciplines: biological systems and neuroscience, engineering and computer science, and economy and social sciences.Comment: Final version published in Physics Reports. More information available at http://synchronets.googlepages.com