A novel approach to cytoarchitectonics: developing an objective framework for the morphological analysis of the cerebral cortex

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• Autor: Matija Vid Prkačin
• Autor: Zdravko Petanjek
• Autor: Ivan Banovac
• Autorova ustanova: Sveučilište u Zagrebu; Medicinski fakultet; (HRVATSKI INSTITUT ZA ISTRAŽIVANJE MOZGA)
• Autorova ustanova: Sveučilište u Zagrebu; Medicinski fakultet; (KATEDRA ZA ANATOMIJU)
• Znanstveno / umjetničko područje, polje i grana: BIOMEDICINA I ZDRAVSTVO; Temeljne medicinske znanosti; Anatomija

Sažetak (engleski)

Introduction: The cytoarchitectonic boundaries between cortical regions and layers are usually defined by the presence or absence of certain cell types. However, these cell types are often not clearly defined and determining the exact boundaries of regions and layers can be challenging. Therefore, in our research, we attempted to define cortical regions and layers based on clear quantitative criteria.

Methods: We performed immunofluorescent anti-NeuN labelling on five adult human brains in three cortical regions-Brodmann areas (BA) 9, 14r, and 24. We reconstructed the cell bodies of 90,723 NeuN-positive cells and analyzed their morphometric characteristics by cortical region and layer. We used a supervised neural network prediction algorithm to classify the reconstructions into morphological cell types. We used the results of the prediction algorithm to determine the proportions of different cell types in BA9, BA14r and BA24.

Results: Our analysis revealed that the cytoarchitectonic descriptions of BA9, BA14r and BA24 were reflected in the morphometric measures and cell classifications obtained by the prediction algorithm. BA9 was characterized by the abundance of large pyramidal cells in layer III, BA14r was characterized by relatively smaller and more elongated cells compared to BA9, and BA24 was characterized by the presence of extremely elongated cells in layer V as well as relatively higher proportions of irregularly shaped cells.

Discussion: The results of the prediction model agreed well with the qualitative expected cytoarchitectonic descriptions. This suggests that supervised machine learning could aid in defining the morphological characteristics of the cerebral cortex.

• Ključne riječi (engleski): cell classification; human; neural network; prediction model; prefrontal cortex
• Jezik: engleski
• Vrsta publikacije: Znanstveni rad - Izvorni znanstveni rad
• Status objave: Objavljen
• Vrsta recenzije: Recenziran
• Verzija publikacije: Objavljena verzija rada (izdavačev PDF)
• Naslov časopisa: Frontiers in Neuroanatomy
• Brojčani podaci: vol. 18, 1441645
• e-ISSN: 1662-5129
• DOI: https://doi.org/10.3389/fnana.2024.1441645
• URN:NBN: urn:nbn:hr:105:363987
• Datum objave publikacije: 2024-08-12
• Projekt: Šifra: IP-2022-10-8493; Naziv (hrvatski): Specifičnosti razvoja kortikalnih interneurona u prefrontalnom korteksu čovjeka tijekom fetalnog razvoja i prve godine života – uloga u nastanku shizofrenije i autizma; Naziv (engleski): Uniqueness in development of interneurons in human prefrontal cortex during fetal life and first postnatal year – implications in pathogenesis of schizophrenia and autism; Kratica: DEVINTERPFC; Voditelj: Zdravko Petanjek; Pravna nadležnost: Hrvatska; Financijer: Hrvatska zaklada za znanost; Linija financiranja: Research Projects
• Projekt: Šifra: IP-2019-04-3182; Naziv (hrvatski): Moždani izvanstanični matriks u razvitku i perinatalnoj hipoksiji; Naziv (engleski): Brain extracellular matrix in development and in perinatal hypoxia; Kratica: BRAINECM; Voditelj: Nataša Jovanov Milošević; Pravna nadležnost: Hrvatska; Financijer: Hrvatska zaklada za znanost; Linija financiranja: Research Projects
• Projekt: Šifra: 10106-23-2407; Naziv (hrvatski): Molekularna i morfološka osnova specijalizacije živčanih stanica u moždanoj kori; Naziv (engleski): Molecular and morphological basis of neuron specialization in the cerebral cortex; Voditelj: Ivan Banovac; Pravna nadležnost: Hrvatska; Financijer: Sveučilište u Zagrebu
• URL dokumenta: https://www.frontiersin.org/articles/10.3389/fnana.2024.1441645/full
• Vrsta resursa: Tekst
• Prava pristupa: Otvoreni pristup
• Datum i vrijeme pohrane: 2025-03-26 13:41:16