Knowledge of the structural properties of biological neural networks can help in understanding how particular responses and actions are generated. Recently, Witvliet et al. published the connectomes of eight isogenic hermaphrodites at different postembryonic ages, from birth to adulthood. We analyzed the basic structural properties of these biological neural networks. From birth to adulthood, the asymmetry between in-degrees and out-degrees over the neuronal network increased with age, in addition to an increase in the number of nodes and edges. The degree distributions were neither Poisson distributions nor pure power-law distributions. We have proposed a model of network evolution with different initial attractiveness for in-degrees and out-degrees of nodes and preferential attachment, which reproduces the asymmetry between in-degrees and out-degrees and similar degree distributions via the tuning of the initial attractiveness values. In this study, we present the well-preserved structural properties of neuronal networks across development, and provide some insight into understanding the evolutionary processes of biological neural networks through a simple network model.
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http://dx.doi.org/10.3390/e25010051 | DOI Listing |
Radiol Med
January 2025
Neuromuscular Imaging Ordinationszentrum Döbling, Heiligenstädter Straße 46-48, 1190, Vienna, Austria.
Purpose: Thread release of the carpal tunnel is the most recent of several minimally invasive ultrasound-guided carpal tunnel release techniques. The purpose of this article is to provide a step-by-step guide for minimally invasive, ultrasound-guided thread release of the carpal tunnel focused on transecting the transverse carpal ligament with minimal damage to the palmar aponeurosis on anatomical specimens.
Methods: Fifteen ultrasound-guided carpal tunnel thread releases were performed on the wrists of soft-embalmed anatomical specimens, which were dissected immediately after the intervention.
Elife
January 2025
Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, United Kingdom.
Cognitive flexibility requires both the encoding of task-relevant and the ignoring of task-irrelevant stimuli. While the neural coding of task-relevant stimuli is increasingly well understood, the mechanisms for ignoring task-irrelevant stimuli remain poorly understood. Here, we study how task performance and biological constraints jointly determine the coding of relevant and irrelevant stimuli in neural circuits.
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January 2025
Department of Biomedicine, Aarhus University, Aarhus, Denmark.
The claustrum complex is viewed as fundamental for higher-order cognition; however, the circuit organization and function of its neuroanatomical subregions are not well understood. We demonstrated that some of the key roles of the CLA complex can be attributed to the connectivity and function of a small group of neurons in its ventral subregion, the endopiriform (EN). We identified a subpopulation of EN neurons by their projection to the ventral CA1 (EN.
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January 2025
Department of Neurology, Weill Institute for Neuroscience, University of California San Francisco, San Francisco, United States.
Mutations in Sonic Hedgehog (SHH) signaling pathway genes, for example, (SUFU), drive granule neuron precursors (GNP) to form medulloblastomas (MB). However, how different molecular lesions in the Shh pathway drive transformation is frequently unclear, and mutations in the cerebellum seem distinct. In this study, we show that fibroblast growth factor 5 (FGF5) signaling is integral for many infantile MB cases and that expression is uniquely upregulated in infantile MB tumors.
View Article and Find Full Text PDFComput Methods Biomech Biomed Engin
January 2025
Department of Clinical Surgery, Cty Clin Emergency Hosp, Sibiu, Romania.
This study examines heat transfer and nanofluid-enhanced blood flow behaviour in stenotic arteries under inflammatory conditions, addressing critical challenges in cardiovascular health. The blood, treated as a Newtonian fluid, is augmented with gold nanoparticles to improve thermal conductivity and support drug delivery applications. A hybrid methodology combining finite element method (FEM) for numerical modelling and artificial neural networks (ANN) for stability prediction provides a robust analytical framework.
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