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Normative aging trends of the brain can serve as an important reference in the assessment of neurological structural disorders. Such models are typically developed from longitudinal brain image data -- follow-up data of the same subject…

Computer Vision and Pattern Recognition · Computer Science 2021-06-29 Alphin J Thottupattu , Jayanthi Sivaswamy , Venkateswaran P. Krishnan

We apply the phenomenological renormalization group to resting-state fMRI time series of brain activity in a large population. By recursively coarse-graining the data, we compute scaling exponents for the series variance, log probability of…

Disordered Systems and Neural Networks · Physics 2024-11-15 Daniel M. Castro , Ernesto P. Raposo , Mauro Copelli , Fernando A. N. Santos

In a variety of systems which exhibit aging, the two-time response function scales as $R(t,s)\approx s^{-1-a} f(t/s)$. We argue that dynamical scaling can be extended towards conformal invariance, obtaining thus the explicit form of the…

High Energy Physics - Theory · Physics 2012-10-18 Malte Henkel , Michel Pleimling , Claude Godreche , Jean-Marc Luck

Some geometric properties of the wavelet analysis performed by visual neurons are discussed and compared with experimental data. In particular, several relationships between the cortical morphologies and the parametric dependencies of…

Neurons and Cognition · Quantitative Biology 2016-01-20 Davide Barbieri

Recent studies proposed the use of Total Correlation to describe functional connectivity among brain regions as a multivariate alternative to conventional pair-wise measures such as correlation or mutual information. In this work we build…

Neurons and Cognition · Quantitative Biology 2022-11-28 Qiang Li , Greg Ver Steeg , Shujian Yu , Jesus Malo

During morphogenesis, a featureless convex cerebellum develops folds. As it does so, the cortex thickness is thinnest at the crest (gyri) and thickest at the trough (sulci) of the folds. This observation cannot be simply explained by…

Soft Condensed Matter · Physics 2021-12-24 M. C. Gandikota , J. M. Schwarz

We present a novel method for quantifying the microscopic structure of brain tissue. It is based on the automated recognition of interpretable features obtained by analyzing the shapes of cells. This contrasts with prevailing methods of…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Kui Qian , Litao Qiao , Beth Friedman , Edward O'Donnell , David Kleinfeld , Yoav Freund

Complexity and heterogeneity of bone tissue require a multiscale modelling to understand their mechanical behaviour and their remodelling mechanism. Human cortical bone structure consists of six structural scale levels which are the…

Medical Physics · Physics 2011-12-07 Abdelwahed Barkaoui , Ridha Hambli

Multiple studies of neural avalanches across different data modalities led to the prominent hypothesis that the brain operates near a critical point. The observed exponents often indicate the mean-field directed-percolation universality…

Neurons and Cognition · Quantitative Biology 2022-11-14 Roxana Zeraati , Victor Buendía , Tatiana A. Engel , Anna Levina

Two fundamental issues surrounding research on the image of the city respectively focus on the city's external and internal representations. The external representation in the context of this paper refers to the city itself, external to…

Adaptation and Self-Organizing Systems · Physics 2013-10-22 Bin Jiang

We propose a hierarchically structured variational inference model for accurately disentangling observable evidence of disease (e.g. brain lesions or atrophy) from subject-specific anatomy in brain MRIs. With flexible, partially…

Computer Vision and Pattern Recognition · Computer Science 2022-11-17 Anjun Hu , Jean-Pierre R. Falet , Brennan S. Nichyporuk , Changjian Shui , Douglas L. Arnold , Sotirios A. Tsaftaris , Tal Arbel

Cognitive neuroscience explores the mechanisms of cognition by studying its structural and functional brain correlates. Here, we report the first systematic review that assesses how information from structural and functional neuroimaging…

Neurons and Cognition · Quantitative Biology 2022-02-07 Marta Czime Litwińczuk , Nelson Trujillo-Barreto , Nils Muhlert , Lauren Cloutman , Anna Woollams

The cortical magnification matrix M is introduced founded on a notion similar to that of the scalar cortical magnification factor M. Unlike M, this matrix is suitable to describe anisotropy in cortical magnification, which is of particular…

Neurons and Cognition · Quantitative Biology 2012-11-01 Markus A. Dahlem , Jan Tusch

The human brain exhibits a complex structure made of scale-free highly connected modules loosely interconnected by weaker links to form a small-world network. These features appear in healthy patients whereas neurological diseases often…

Neurons and Cognition · Quantitative Biology 2014-03-26 Roberta Russo , Hans J Herrmann , Lucilla de Arcangelis

The scaling property of the brain dynamics is studied based on the zero-crossing of the local electroencephalographic (EEG) recording taken from healthy young adults in eyes closed and eyes open. Evidence of coupling between the EEG fractal…

Biological Physics · Physics 2007-05-23 Der Chyan Lin , Asif Sharif , Hon Kwan

Scaling laws illuminate Nature's fundamental biological principles and guide bioinspired materials and structural designs. In simple cases they are based on the fundamental principle that all laws of nature remain unchanged (i.e.,…

Biological Physics · Physics 2025-02-18 Huan Liu , Shashank Priya , Richard D. James

During the first years of life, the human brain undergoes dynamic spatially-heterogeneous changes, involving differentiation of neuronal types, dendritic arborization, axonal ingrowth, outgrowth and retraction, synaptogenesis, and…

Many materials quenched into their ordered phase undergo ageing and there show dynamical scaling. For any given dynamical exponent z, this can be extended to a new form of local scale-invariance which acts as a dynamical symmetry. The…

Statistical Mechanics · Physics 2010-04-23 Malte Henkel

Deep graph models (e.g., graph neural networks and graph transformers) have become important techniques for leveraging knowledge across various types of graphs. Yet, the neural scaling laws on graphs, i.e., how the performance of deep graph…

Machine Learning · Computer Science 2024-12-03 Jingzhe Liu , Haitao Mao , Zhikai Chen , Tong Zhao , Neil Shah , Jiliang Tang

Background: People with bipolar disorder (BD) tend to show widespread cognitive impairment compared to healthy controls. Impairments in processing speed (PS), attention, and executive function (EF) may represent 'core' impairments that have…

Neurons and Cognition · Quantitative Biology 2023-11-06 Bethany Little , Carly Flowers , Andrew Blamire , Peter Thelwall , John-Paul Taylor , Peter Gallagher , David Andrew Cousins , Yujiang Wang