The Fractal Geometry of the Brain / edited by Antonio Di Ieva.

Format:

Book

Contributor:

Di Ieva, Antonio, editor.

Series:

Advances in Neurobiology, 2190-5223 ; 36

Language:

English

Subjects (All):

Neurosciences.

Neurology.

Neuroscience.

Local Subjects:

Neuroscience.

Neurology.

Physical Description:

1 online resource (999 pages)

Edition:

2nd ed. 2024.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2024.

Summary:

The new edition of the highly popular, The Fractal Geometry of the Brain, reviews the most intriguing applications of fractal analysis in neuroscience with a focus on current and future potential, limits, advantages, and disadvantages. It brings an understanding of fractals to clinicians and researchers even if they do not have a mathematical background, and it serves as a valuable tool for teaching the translational applications of computational fractal-based models to both students and scholars. As a consequence of the novel research developed at Professor Di Ieva's laboratory and other centers around the world, the second edition will explore the use of computational fractal-based analysis in many clinical disciplines and different fields of research, including neurology and neurosurgery, neuroanatomy and psychology, magnetoencephalography (MEG), eye-tracking devices (for the fractal computational characterization of “scanpaths”), deep learning in image analysis, radiomics for the characterization of brain MRIs, characterization of neuropsychological and psychiatric diseases and traits, signal complexity analysis in time series, and functional MRI, amongst others.

Contents:

Part I. Introduction to Fractal Geometry and its Applications to Neurosciences

The Fractal Geometry of the Brain: An Overview

2. Box-Counting Fractal Analysis: A Primer for the Clinician

Tenets and Methods of Fractal Analysis (1/f noise)

4. Tenets, Methods and Applications of Multifractal Analysis in Neurosciences

Part II. Fractals in Neuroanatomy and Basic Neurosciences

Fractals in Neuroanatomy and Basic Neurosciences: An Overview

Morphology and Fractal-Based Classifications of Neurons and Microglia

The Morphology of the Brain Neurons: Box-counting Method in Quantitative Analysis of 2D Image

Neuronal Fractal Dynamics

Does a Self-Similarity Logic Shape the Organization of the Nervous System?

Fractality of Cranial Sutures

The Fractal Geometry of the Human Brain: An Evolutionary Perspective

Part III. Fractals in Clinical Neurosciences

Fractal Analysis in Clinical Neurosciences: An Overview

Fractal Analysis in Neurological Diseases

Fractal Dimension Studiesof the Brain Shape in Aging and Neurodegenerative Diseases

Fractal Analysis in Neurodegenerative Diseases

Fractal Analysis of the Cerebrovascular System Physiopathology

Fractal and Chaos in the Hemodynamics of Intracranial Aneurysms

Fractal-based Analysis of Arteriovenous Malformations (AVMs)

Fractals in Neuroimaging

Computational Fractal-Based Analysis of MR Susceptibility Weighted Imaging (SWI) in Neuro-oncology and neurotraumatology

Texture Estimation for Abnormal Tissue Segmentation in Brain MRI

Tumor Growth in the Brain: Complexity and Fractality

Histological Fractal-based Classification of Brain Tumors

Computational Fractal-based Analysis of the Brain Tumors Microvascular Networks

Fractal analysis of electroencephalographic time-series (EEG-signals)

On Multiscaling of Parkinsonian Rest Tremor Signals and Their Classification

Fractals and Electromyograms

Fractal analysis in Neuro-ophthalmology

Fractals in Affective and Anxiety Disorders.-Fractal Fluency: An Intimate Relationship Between the Brain and Processing of Fractal Stimuli

Part IV. Computational Fractal-Based Neurosciences

Computational Fractal-based Neurosciences: An Overview

ImageJ in Computational Fractal-based Neuroscience: Pattern Extraction and Translational Research

Fractal Analysis in MATLAB: A Tutorial for Neuroscientists

Methodology to Increase the Computational Speed to Obtain the Fractal Dimension Using GPU Programming

Fractal Electronics as a Generic Interface to Neurons

Fractal Geometry meets Computational Intelligence: Future Perspectives.

Notes:

Includes bibliographical references and index.

ISBN:

3-031-47606-9