TY - JOUR
T1 - Fractals in the neurosciences, part II
T2 - Clinical applications and future perspectives
AU - Di Ieva, Antonio
AU - Esteban, Francisco J.
AU - Grizzi, Fabio
AU - Klonowski, Wlodzimierz
AU - Martín-Landrove, Miguel
PY - 2015/2/17
Y1 - 2015/2/17
N2 - It has been ascertained that the human brain is a complex system studied at multiple scales, from neurons and microcircuits to macronetworks. The brain is characterized by a hierarchical organization that gives rise to its highly topological and functional complexity. Over the last decades, fractal geometry has been shown as a universal tool for the analysis and quantification of the geometric complexity of natural objects, including the brain. The fractal dimension has been identified as a quantitative parameter for the evaluation of the roughness of neural structures, the estimation of time series, and the description of patterns, thus able to discriminate different states of the brain in its entire physiopathological spectrum. Fractal-based computational analyses have been applied to the neurosciences, particularly in the field of clinical neurosciences including neuroimaging and neuroradiology, neurology and neurosurgery, psychiatry and psychology, and neuro-oncology and neuropathology. After a review of the basic concepts of fractal analysis and its main applications to the basic neurosciences in part I of this series, here, we review the main applications of fractals to the clinical neurosciences for a holistic approach towards a fractal geometry model of the brain.
AB - It has been ascertained that the human brain is a complex system studied at multiple scales, from neurons and microcircuits to macronetworks. The brain is characterized by a hierarchical organization that gives rise to its highly topological and functional complexity. Over the last decades, fractal geometry has been shown as a universal tool for the analysis and quantification of the geometric complexity of natural objects, including the brain. The fractal dimension has been identified as a quantitative parameter for the evaluation of the roughness of neural structures, the estimation of time series, and the description of patterns, thus able to discriminate different states of the brain in its entire physiopathological spectrum. Fractal-based computational analyses have been applied to the neurosciences, particularly in the field of clinical neurosciences including neuroimaging and neuroradiology, neurology and neurosurgery, psychiatry and psychology, and neuro-oncology and neuropathology. After a review of the basic concepts of fractal analysis and its main applications to the basic neurosciences in part I of this series, here, we review the main applications of fractals to the clinical neurosciences for a holistic approach towards a fractal geometry model of the brain.
KW - brain
KW - electroencephalography
KW - fractal analysis
KW - fractal geometry
KW - neuroanatomy
KW - neuroimaging
KW - self-similarity
KW - tumors
UR - http://www.scopus.com/inward/record.url?scp=84920996396&partnerID=8YFLogxK
U2 - 10.1177/1073858413513928
DO - 10.1177/1073858413513928
M3 - Review article
C2 - 24362814
AN - SCOPUS:84920996396
SN - 1073-8584
VL - 21
SP - 30
EP - 43
JO - Neuroscientist
JF - Neuroscientist
IS - 1
ER -