The introduction of fractal geometry in the neurosciences has been a major paradigm shift over the last decades as it has helped overcome approximations and limitations that occur when Euclidean and reductionist approaches are used to analyze neurons or the entire brain. Fractal geometry allows for quantitative analysis and description of the geometric complexity of the brain, from its single units to the neuronal networks.
As illustrated in the second section of this book, fractal analysis provides a quantitative tool for the study of morphology of brain cells (i.e., neurons and microglia) and its components (e.g., dendritic trees, synapses) as well as the brain structure itself (cortex, functional modules, neuronal networks). The self-similar logic which generates and shapes the different hierarchical systems of the brain and even some structures related to its “container,” that is, the cranial sutures on the skull, is widely discussed in the following chapters, with a link between the applications of fractal analysis to the neuroanatomy and basic neurosciences to the clinical applications discussed in the third section.
|Name||Springer Series in Computational Neuroscience|
- neuronal networks