Numbers of neurons and their spatial variation are fundamental organizational features of the brain. Despite the large corpus of cytoarchitectonic data available in the literature, the statistical distributions of neuron densities within and across brain areas remain largely uncharacterized. Here, we show that neuron densities are compatible with a lognormal distribution across cortical areas in several mammalian species, and find that this also holds true within cortical areas. A minimal model of noisy cell division, in combination with distributed proliferation times, can account for the coexistence of lognormal distributions within and across cortical areas. Our findings uncover a new organizational principle of cortical cytoarchitecture: the ubiquitous lognormal distribution of neuron densities, which adds to a long list of lognormal variables in the brain.
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http://dx.doi.org/10.1093/cercor/bhad160 | DOI Listing |
Eur Arch Psychiatry Clin Neurosci
December 2024
Laboratory of Clinical Neuropathology, Mental Health Research Center, Kashirskoe Shosse 34, 115522, Moscow, Russia.
Previously we found altered microglia-neuron interactions in the prefrontal cortex in schizophrenia. We hypothesized that microglia-neuron interactions may be dysregulated in the caudate nucleus in schizophrenia. A postmortem ultrastructural morphometric study was performed to investigate satellite microglia (SatMg) and adjacent neurons in the head of the caudate nucleus in 21 cases of schizophrenia and 20 healthy controls.
View Article and Find Full Text PDFSci Rep
December 2024
Research Group for Implantable Microsystems, Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter utca 50/a, Budapest, 1083, Hungary.
Infrared neural stimulation has consistently shown that temperature is a critical neuronal state variable. However, a comprehensive understanding of the biophysical background is essential. In this study, using high-density laminar electrode recordings, we investigated the impact of pulsed and continuous-wave infrared illumination on cortical neurons in anesthetized rats ([Formula: see text]).
View Article and Find Full Text PDFMol Cell Neurosci
December 2024
Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Türkiye; Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Türkiye; Department of Neuroscience, Institute of Health Sciences, Dokuz Eylul University, Izmir, Türkiye. Electronic address:
Alzheimer's disease (AD) is a neurodegenerative disorder that is characterized by the accumulation of amyloid plaques, phosphorylated tau tangles and microglia toxicity, resulting in neuronal death and cognitive decline. Since microglia are recognized as one of the key players in the disease, it is crucial to understand how microglia operate in disease conditions and incorporate them into models. The studies on human microglia functions are thought to reflect the post-symptomatic stage of the disease.
View Article and Find Full Text PDFJ Biomol Struct Dyn
December 2024
Centre for Biotechnology, Siksha 'O' Anusandhan (Deemed to Be University), Bhubaneswar, Odisha, India.
In the relentless pursuit of unraveling the intricate pathophysiology of Alzheimer's disease (AD), amyloid β (Aβ) proteins emerge as focal points due to their pivotal role in disease progression. The pathological hallmark of AD involves the aberrant aggregation of Aβ peptides into amyloid fibrils, precipitating a cascade of neurodegenerative events culminating in cognitive decline and neuronal loss. This study adopts a computational framework to investigate the potential therapeutic efficacy of novel biosurfactants (BS) in mitigating Aβ fibril formation.
View Article and Find Full Text PDFAcad Radiol
December 2024
School of Public Health, Jiangxi Medical College, Nanchang University, Nanchang 330006, China (C.X., L.D., W.C., M.H.); Jiangxi Provincial Key Laboratory of Disease Prevention and Public Health, Nanchang University, Nanchang 330006, China (C.X., L.D., W.C., M.H.). Electronic address:
Rationale And Objectives: To develop and validate a multimodal deep learning (DL) model based on computed tomography (CT) images and clinical knowledge to predict lymph node metastasis (LNM) in early lung adenocarcinoma.
Materials And Methods: A total of 724 pathologically confirmed early invasive lung adenocarcinoma patients were retrospectively included from two centers. Clinical and CT semantic features of the patients were collected, and 3D radiomics features were extracted from nonenhanced CT images.
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