Cargando…

Cortical complexity estimation using fractal dimension: A systematic review of the literature on clinical and nonclinical samples

Fractal geometry has recently been proposed as a useful tool for characterizing the complexity of the brain cortex, which is likely to derive from the recurrence of sulci–gyri convolution patterns. The index used to describe the cortical complexity is called fractal dimensional (FD) and was employed...

Descripción completa

Detalles Bibliográficos
Autores principales: Meregalli, Valentina, Alberti, Francesco, Madan, Christopher R., Meneguzzo, Paolo, Miola, Alessandro, Trevisan, Nicolò, Sambataro, Fabio, Favaro, Angela, Collantoni, Enrico
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9313853/
https://www.ncbi.nlm.nih.gov/pubmed/35229388
http://dx.doi.org/10.1111/ejn.15631
_version_ 1784754175925551104
author Meregalli, Valentina
Alberti, Francesco
Madan, Christopher R.
Meneguzzo, Paolo
Miola, Alessandro
Trevisan, Nicolò
Sambataro, Fabio
Favaro, Angela
Collantoni, Enrico
author_facet Meregalli, Valentina
Alberti, Francesco
Madan, Christopher R.
Meneguzzo, Paolo
Miola, Alessandro
Trevisan, Nicolò
Sambataro, Fabio
Favaro, Angela
Collantoni, Enrico
author_sort Meregalli, Valentina
collection PubMed
description Fractal geometry has recently been proposed as a useful tool for characterizing the complexity of the brain cortex, which is likely to derive from the recurrence of sulci–gyri convolution patterns. The index used to describe the cortical complexity is called fractal dimensional (FD) and was employed by different research exploring the neurobiological correlates of distinct pathological and nonpathological conditions. This review aims to describe the literature on the application of this index, summarize the heterogeneities between studies and inform future research on this topic. Sixty‐two studies were included in the systematic review. The main research lines concern neurodevelopment, aging and the neurobiology of specific psychiatric and neurological disorders. Overall, the included papers indicate that cortical complexity is likely to reduce during aging and in various pathological processes affecting the brain. Nevertheless, the high heterogeneity between studies strongly prevents the possibility of drawing conclusions. Further research considering this index besides other morphological values is needed to better clarify the role of FD in characterizing the cortical structure.
format Online
Article
Text
id pubmed-9313853
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-93138532022-07-30 Cortical complexity estimation using fractal dimension: A systematic review of the literature on clinical and nonclinical samples Meregalli, Valentina Alberti, Francesco Madan, Christopher R. Meneguzzo, Paolo Miola, Alessandro Trevisan, Nicolò Sambataro, Fabio Favaro, Angela Collantoni, Enrico Eur J Neurosci Cognitive Neuroscience Fractal geometry has recently been proposed as a useful tool for characterizing the complexity of the brain cortex, which is likely to derive from the recurrence of sulci–gyri convolution patterns. The index used to describe the cortical complexity is called fractal dimensional (FD) and was employed by different research exploring the neurobiological correlates of distinct pathological and nonpathological conditions. This review aims to describe the literature on the application of this index, summarize the heterogeneities between studies and inform future research on this topic. Sixty‐two studies were included in the systematic review. The main research lines concern neurodevelopment, aging and the neurobiology of specific psychiatric and neurological disorders. Overall, the included papers indicate that cortical complexity is likely to reduce during aging and in various pathological processes affecting the brain. Nevertheless, the high heterogeneity between studies strongly prevents the possibility of drawing conclusions. Further research considering this index besides other morphological values is needed to better clarify the role of FD in characterizing the cortical structure. John Wiley and Sons Inc. 2022-03-09 2022-03 /pmc/articles/PMC9313853/ /pubmed/35229388 http://dx.doi.org/10.1111/ejn.15631 Text en © 2022 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Cognitive Neuroscience
Meregalli, Valentina
Alberti, Francesco
Madan, Christopher R.
Meneguzzo, Paolo
Miola, Alessandro
Trevisan, Nicolò
Sambataro, Fabio
Favaro, Angela
Collantoni, Enrico
Cortical complexity estimation using fractal dimension: A systematic review of the literature on clinical and nonclinical samples
title Cortical complexity estimation using fractal dimension: A systematic review of the literature on clinical and nonclinical samples
title_full Cortical complexity estimation using fractal dimension: A systematic review of the literature on clinical and nonclinical samples
title_fullStr Cortical complexity estimation using fractal dimension: A systematic review of the literature on clinical and nonclinical samples
title_full_unstemmed Cortical complexity estimation using fractal dimension: A systematic review of the literature on clinical and nonclinical samples
title_short Cortical complexity estimation using fractal dimension: A systematic review of the literature on clinical and nonclinical samples
title_sort cortical complexity estimation using fractal dimension: a systematic review of the literature on clinical and nonclinical samples
topic Cognitive Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9313853/
https://www.ncbi.nlm.nih.gov/pubmed/35229388
http://dx.doi.org/10.1111/ejn.15631
work_keys_str_mv AT meregallivalentina corticalcomplexityestimationusingfractaldimensionasystematicreviewoftheliteratureonclinicalandnonclinicalsamples
AT albertifrancesco corticalcomplexityestimationusingfractaldimensionasystematicreviewoftheliteratureonclinicalandnonclinicalsamples
AT madanchristopherr corticalcomplexityestimationusingfractaldimensionasystematicreviewoftheliteratureonclinicalandnonclinicalsamples
AT meneguzzopaolo corticalcomplexityestimationusingfractaldimensionasystematicreviewoftheliteratureonclinicalandnonclinicalsamples
AT miolaalessandro corticalcomplexityestimationusingfractaldimensionasystematicreviewoftheliteratureonclinicalandnonclinicalsamples
AT trevisannicolo corticalcomplexityestimationusingfractaldimensionasystematicreviewoftheliteratureonclinicalandnonclinicalsamples
AT sambatarofabio corticalcomplexityestimationusingfractaldimensionasystematicreviewoftheliteratureonclinicalandnonclinicalsamples
AT favaroangela corticalcomplexityestimationusingfractaldimensionasystematicreviewoftheliteratureonclinicalandnonclinicalsamples
AT collantonienrico corticalcomplexityestimationusingfractaldimensionasystematicreviewoftheliteratureonclinicalandnonclinicalsamples