Developmental Changes in Pyramidal Cell Morphology in Multiple Visual Cortical Areas Using Cluster Analysis

Khalil, Reem; Farhat, Ahmad; Dłotko, Paweł

doi:10.3389/fncom.2021.667696

Cited by 4 publications

(3 citation statements)

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“…The neural circuit undergoes continuous changes throughout development in various brain regions, adapting for more complex computations and to perform more resilient behavior (Neural Circuit Development and Function in the Healthy and Diseased Brain: Comprehensive Developmental Neuroscience 2013;Tau and Peterson 2010). This functional adaptation across development is accompanied by the structural alterations, resulting in changes to both neuronal morphology and connectivity between neurons (Grueber et al 2005;Kroon et al 2019;Khalil, Farhat, and Dłotko 2021;Kolk and Rakic 2022;Witvliet et al 2021;Mulcahy et al 2022). To induce changes in neuronal morphology and connectivity, numerous intracellular organelles participate in the process, with mitochondria playing a central role through trafficking and reshaping (Harris, Jolivet, and Attwell 2012;Verstreken et al 2005;Kimura and Murakami 2014;Sheng and Cai 2012;Courchet et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Structural diversity of mitochondria in the neuromuscular system across development

Bae,

Choi,

Ahn

et al. 2024

Preprint

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As an animal matures, its neural circuit undergoes alterations, leading to changes in both neuronal morphology and the connectivity between neurons. However, less is known about the mitochondrial structure changes across development to facilitate these changes, while mitochondria are highly dynamic organelles related to neuronal development. Here, we attempt to answer this question with a model organismC. elegansusing 3D electron microscopy (EM). We developed semi-automated methods for reconstructing mitochondria inC. elegansEM images using deep learning. Consequently, we collected mitochondria reconstructions from normal reproductive stages and dauer, enabling comparative study on mitochondrial morphology and spatial organization within the neuromuscular system across different stages. We have identified that the mitochondria structural properties in neurons are correlated with synaptic properties. Neuronal compartments have distinct roles, leading axonal mitochondria to differ morphologically from dendritic mitochondria. We tested this by analyzing behavior in animals with a mutation indrp-1, required for proper mitochondrial fission, confirming that compartment-specific mitochondrial morphology is vital for effective functioning of synapses. Given that these functions are essential throughout development, the structural properties of mitochondria are preserved across development. We report that dauer inter- and motor neurons, predominantly cholinergic and glutamatergic, show distinctive mitochondrial structure and increased mitochondria density. In addition, mitochondria in dauer body wall muscles exhibit distinctive reticulum-like structure. We propose that the stage-specific mitochondrial structure observed inC. elegansdauer may constitute an adaptive mechanism to support stage-specific behavioral and physiological characteristics.

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Section: Introductionmentioning

confidence: 99%

Structural diversity of mitochondria in the neuromuscular system across development

Bae,

Choi,

Ahn

et al. 2024

Preprint

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“…Pyramidal cells play a critical role in circuit structure and function, and are the most abundant type in the cerebral cortex (70-80% of the total neuronal population) [5]. The dendritic morphology of pyramidal cells can vary substantially among cortical areas within a species [6][7][8][9], across species [10,11], and even across development [12][13][14]. Developmental changes in the dendritic morphology of pyramidal cells is mirrored by structural changes in connectivity [15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Topological Sholl descriptors for neuronal clustering and classification

et al. 2022

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Neuronal morphology is a fundamental factor influencing information processing within neurons and networks. Dendritic morphology in particular can widely vary among cell classes, brain regions, and animal species. Thus, accurate quantitative descriptions allowing classification of large sets of neurons is essential for their structural and functional characterization. Current robust and unbiased computational methods that characterize groups of neurons are scarce. In this work, we introduce a novel technique to study dendritic morphology, complementing and advancing many of the existing techniques. Our approach is to conceptualize the notion of a Sholl descriptor and associate, for each morphological feature, and to each neuron, a function of the radial distance from the soma, taking values in a metric space. Functional distances give rise to pseudo-metrics on sets of neurons which are then used to perform the two distinct tasks of clustering and classification. To illustrate the use of Sholl descriptors, four datasets were retrieved from the large public repository https://neuromorpho.org/ comprising neuronal reconstructions from different species and brain regions. Sholl descriptors were subsequently computed, and standard clustering methods enhanced with detection and metric learning algorithms were then used to objectively cluster and classify each dataset. Importantly, our descriptors outperformed conventional morphometric techniques (L-Measure metrics) in several of the tested datasets. Therefore, we offer a novel and effective approach to the analysis of diverse neuronal cell types, and provide a toolkit for researchers to cluster and classify neurons.

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“…The distinct neuronal structure is believed to give rise to the neuron's computational abilities (Cuntz, Borst, and Segev (2007); Ferrante, Migliore, and Ascoli (2013); Kanari et al (2018); van Elburg and van Ooyen (2010); Zomorrodi, Ferecskó, Kovács, Kröger, and Timofeev (2010)). In addition, morphological differences between neuronal cell types are thought to result in their functional differences (Khalil, Farhat, and D lotko (2021); Krichmar, Nasuto, Scorcioni, Washington, and Ascoli (2002); Mainen and Sejnowski (1996); Schaefer, Larkum, Sakmann, and Roth (2003); Vetter, Roth, and Häusser (2001)). During the development of this crucial structure in primary neurons, several morphological changes occur in distinct stages, but their features have not been statistically compared between days or stages (Dotti, Sullivan, and Banker (1988); Powell, Rivas, Rodriguez-Boulan, and Hatten (1997); Tahirovic and Bradke (2009)).…”

Section: Introductionmentioning

confidence: 99%

Quantitative evaluation of neuron developmental morphology in vitro using the change-point test

Liao

Cui

Zhang

et al. 2022

Preprint

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Neuron morphology gives rise to distinct axons and dendrites and plays an essential role in neuronal functionality and circuit dynamics. In rat hippocampal neurons, morphological development occurs over roughly one week in vitro. This development has been qualitatively described as occurring in 5 stages. Still, there is a need to quantify cell growth to monitor cell culture health, understand cell responses to sensory cues, and compare experimental results and computational growth model predictions. To address this need, embryonic rat hippocampal neurons were observed in vitro over six days, and their processes were quantified using both standard morphometrics (degree, number of neurites, total length, and tortuosity) and new metrics (distance between change points, relative turning angle, and the number of change points) based on the Change-Point Test to track changes in path trajectories. Of the standard morphometrics, the total length of neurites per cell and the number of endpoints were significantly different between 0.5, 1.5, and 5 days in vitro, which are typically associated with Stages 2-4. Using the Change-Point Test, the number of change points and the average distance between change points per cell were also significantly different between those key time points. This work highlights key quantitative characteristics, both among common and novel morphometrics, that can describe neuron development in vitro and provides a foundation for analyzing directional changes in neurite growth for future studies.

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Developmental Changes in Pyramidal Cell Morphology in Multiple Visual Cortical Areas Using Cluster Analysis

Cited by 4 publications

References 64 publications

Structural diversity of mitochondria in the neuromuscular system across development

Structural diversity of mitochondria in the neuromuscular system across development

Topological Sholl descriptors for neuronal clustering and classification

Quantitative evaluation of neuron developmental morphology in vitro using the change-point test

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