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The Fractal Geometry of the Brain

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Cover of 'The Fractal Geometry of the Brain'

Table of Contents

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    Book Overview
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    Chapter 1 The Fractal Geometry of the Brain: An Overview
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    Chapter 2 Box-Counting Fractal Analysis: A Primer for the Clinician
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    Chapter 3 Tenets and Methods of Fractal Analysis (1/f Noise)
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    Chapter 4 Tenets, Methods, and Applications of Multifractal Analysis in Neurosciences
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    Chapter 5 Fractals in Neuroanatomy and Basic Neurosciences: An Overview
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    Chapter 6 Morphology and Fractal-Based Classifications of Neurons and Microglia
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    Chapter 7 The Morphology of the Brain Neurons: Box-Counting Method in Quantitative Analysis of 2D Image
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    Chapter 8 Neuronal Fractal Dynamics
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    Chapter 9 Does a Self-Similarity Logic Shape the Organization of the Nervous System?
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    Chapter 10 Fractality of Cranial Sutures
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    Chapter 11 The Fractal Geometry of the Human Brain: An Evolutionary Perspective
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    Chapter 12 Fractal Analysis in Clinical Neurosciences: An Overview
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    Chapter 13 Fractal Analysis in Neurological Diseases
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    Chapter 14 Fractal Dimension Studies of the Brain Shape in Aging and Neurodegenerative Diseases
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    Chapter 15 Fractal Analysis in Neurodegenerative Diseases
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    Chapter 16 Fractal Analysis of the Cerebrovascular System Physiopathology
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    Chapter 17 Fractals and Chaos in the Hemodynamics of Intracranial Aneurysms
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    Chapter 18 Fractal-Based Analysis of Arteriovenous Malformations (AVMs)
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    Chapter 19 Fractals in Neuroimaging
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    Chapter 20 Computational Fractal-Based Analysis of MR Susceptibility-Weighted Imaging (SWI) in Neuro-oncology and Neurotraumatology
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    Chapter 21 Texture Estimation for Abnormal Tissue Segmentation in Brain MRI
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    Chapter 22 Tumor Growth in the Brain: Complexity and Fractality
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    Chapter 23 Histological Fractal-Based Classification of Brain Tumors
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    Chapter 24 Computational Fractal-Based Analysis of Brain Tumor Microvascular Networks
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    Chapter 25 Fractal Analysis of Electroencephalographic Time Series (EEG Signals)
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    Chapter 26 On Multiscaling of Parkinsonian Rest Tremor Signals and Their Classification
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    Chapter 27 Fractals and Electromyograms
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    Chapter 28 Fractal Analysis in Neuro-ophthalmology
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    Chapter 29 Fractals in Affective and Anxiety Disorders
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    Chapter 30 Fractal Fluency: An Intimate Relationship Between the Brain and Processing of Fractal Stimuli
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    Chapter 31 Computational Fractal-Based Neurosciences: An Overview
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    Chapter 32 ImageJ in Computational Fractal-Based Neuroscience: Pattern Extraction and Translational Research
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    Chapter 33 Fractal Analysis in MATLAB: A Tutorial for Neuroscientists
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    Chapter 34 Methodology to Increase the Computational Speed to Obtain the Fractal Dimension Using GPU Programming
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    Chapter 35 Fractal Electronics as a Generic Interface to Neurons
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    Chapter 36 Fractal Geometry Meets Computational Intelligence: Future Perspectives
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    Chapter 37 Erratum to: The Fractal Geometry of the Brain
Attention for Chapter 30: Fractal Fluency: An Intimate Relationship Between the Brain and Processing of Fractal Stimuli
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Chapter title
Fractal Fluency: An Intimate Relationship Between the Brain and Processing of Fractal Stimuli
Chapter number 30
Book title
The Fractal Geometry of the Brain
Published by
Springer New York, August 2016
DOI 10.1007/978-1-4939-3995-4_30
Book ISBNs
978-1-4939-3993-0, 978-1-4939-3995-4

Richard P. Taylor, Branka Spehar


Antonio Di Ieva

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 19%
Student > Bachelor 5 16%
Professor 3 10%
Researcher 2 6%
Student > Master 2 6%
Other 1 3%
Unknown 12 39%
Readers by discipline Count As %
Psychology 4 13%
Neuroscience 3 10%
Agricultural and Biological Sciences 2 6%
Engineering 2 6%
Medicine and Dentistry 1 3%
Other 3 10%
Unknown 16 52%