Brain morphology is individual-specific information

Takao, Hidemasa; Hayashi, Naoto; Ohtomo, Kuni

doi:10.1016/j.mri.2015.03.010

Cited by 15 publications

(9 citation statements)

References 39 publications

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“…These cells formed the cerebellar folia, which are vast in numbers depend on the learned sequential movement in one's daily life. The vast number of one's cerebellar folia might be correlated to the number of sequential movement that has been learned by this individual (Glickstein et al, 2009;Watson et al, 2010;Takao et al, 2015).…”

Section: Discussionmentioning

confidence: 99%

Quantitative Study on Human Cerebellar Cortex from Anatomy Cadaver Preparations

2017

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SUMMARY:Human cerebellum is important for motor coordination; muscle tones and maintaing the equilibrium of the body. In our region, limited data is available on the normal morphology of human cerebellum, whilst fresh biopsy is quite difficult to obtain. Here adult male cerebellum from cadaver anatomy preparations embalmed with 37 % formalin fixative solution for over a year are studied (n=3). After removal, right cerebellum hemisphere was sliced into cubicle then temporary soaked into 50-60 % of alcohol before being paraffinated. Two parasagittal adjacent slices from each sample were deparaffinated (5 µm) and then stained with hematoxyllin-eosin (HE). Slides were observed under light microscope (Olympus, Japan). Pictures were analysed from 6 field numbers of each, with Optilab and Image Raster 3 software (Indonesia). The density of the Purkinje cells (Neuron purkinjense), the number and density of the Purkinje cells and the thickness of the molecular layer are measured. Data were analysed with the level of significance of p<0.05 (ANOVA, Microsoft Excel 2007). The distance between 2 Purkinje cells is ranged between 82.6-346.6 µm, although no significant differences found (p=0.1). There are no significant differences in the number and in the density of the Purkinje cells amongst samples (p=0.72 and 0.34, respectively); might be due to the similar age, sex and race of these cadavers. However, there is a significant difference in the thickness of the molecular layer (p=0.015). Variations amongst individual cerebelli are observed, with a significant different thickness in the molecular layer. The cellular composition of each cerebellum is unique, arguably correlated to the individual cerebellum activity when alive.

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Section: Discussionmentioning

confidence: 99%

Quantitative Study on Human Cerebellar Cortex from Anatomy Cadaver Preparations

2017

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“…endo-phenotype approaches Analogous strategy-based approaches can be devised to comprehensively taxonomize individual-specificity in physiology and morphology. Examples are endo-phenotype approaches in molecular psychiatry [50], approaches taxonomizing individual-specific brain morphology [51], and ecto-phenotype approaches taxonomizing individuals' face or body morphology [52,53].…”

Section: Content-basedmentioning

confidence: 99%

Taxonomic models of individual differences: a guide to transdisciplinary approaches

Uher

2018

Phil. Trans. R. Soc. B

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Models and constructs of individual differences are numerous and diverse. But detecting commonalities, differences and interrelations is hindered by the common abstract terms (e.g. 'personality', 'temperament', 'traits') that do not reveal the particular phenomena denoted. This article applies a transdisciplinary paradigm for research on individuals that builds on complexity theory and epistemological complementarity. Its philosophical, metatheoretical and methodological frameworks provide concepts to differentiate various kinds of phenomena (e.g. physiology, behaviour, psyche, language). They are used to scrutinize the field's basic concepts and to elaborate methodological foundations for taxonomizing individual variations in humans and other species. This guide to developing comprehensive and representative models explores the decisions taxonomists must make about which individual variations to include, which to retain and how to model them. Selection and reduction approaches from various disciplines are classified by their underlying rationales, pinpointing possibilities and limitations. Analyses highlight that individuals' complexity cannot be captured by one universal model. Instead, multiple models phenotypically taxonomizing different kinds of variability in different kinds of phenomena are needed to explore their causal and functional interrelations and ontogenetic development that are then modelled in integrative and explanatory taxonomies. This research agenda requires the expertise of many disciplines and is inherently transdisciplinary.This article is part of the theme issue 'Diverse perspectives on diversity: multi-disciplinary approaches to taxonomies of individual differences'.

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“…It is the process to epitomize the raw image in its reduced outline to simplify the decision making. In extracting the features from the image the most widely used application in medical image processing is Principal Component Analysis (PCA) [8]. In this paper, images are denoised using SANLM filter, extracted the features using PCA and then segmented the images using the Modified FCM correlated with ABC algorithms and these results are compared with the Minkowski score.…”

Section: A Denoisingmentioning

confidence: 99%

Brain Tissue Classification using PCA with Hybrid Clustering Algorithms

Karuna¹,

Saladi²,

Bhattacharyya³

2018

IJET

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Distinct algorithms were developed to segment the MRI images, to satisfy the accuracy in segmenting the regions of the brain. In this paper, we proposed a novel methodology for segmenting the MRI brain images using the clustering techniques. The Modified Fuzzy CMeans (MFCM) algorithm is pooled with the Artificial Bee Colony (ABC) algorithm after denoising images, features are extracted using Principal Component Analysis (PCA) for better results of segmentation. This improves the ability to extract the regions (cluster centres) and cells in the normal and abnormal brain MRI images. The comparative analysis of proposed methodology with existing FCM, ABC algorithms is evaluated in terms of Minkowski score. The proposed MFCM-ABC method is more robust and efficient to hostile noise in images when compared to existing FCM and ABC methods.

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Brain morphology is individual-specific information

Cited by 15 publications

References 39 publications

Quantitative Study on Human Cerebellar Cortex from Anatomy Cadaver Preparations

Quantitative Study on Human Cerebellar Cortex from Anatomy Cadaver Preparations

Taxonomic models of individual differences: a guide to transdisciplinary approaches

Brain Tissue Classification using PCA with Hybrid Clustering Algorithms

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