In recent years the ability of cell-to-cell transmission of protein species involved in almost all neurodegenerative diseases has been revealed from in vitro, animal models and human in vivo studies. Amyloid beta and tau in Alzheimer's disease, alpha-synuclein in Parkinson's disease, tau, SOD1 and TDP-43 in frontotemporal dementia, TDP-43 in ALS, and so on, are all capable of this kind of "trans-neuronal transmission". Since such transmission occurs along neural connections rather than spatially or randomly, it is therefore emerging that the patterns of spread and progression of neurodegenerative diseases must consequently occur along and within the connectivity networks of the brain. Not only does this view provide a mechanistic basis that underlies and explains the highly stereotypical patterns seen in these diseases, it also enables quantitative and model-based exploration of progression in these diseases.
Although much progress has been made in elucidating the mechanisms of protein transmission in cell cultures and animal models, these approaches do not typically address the entire brain network, nor do they provide a quantitative understanding of these concepts. Therefore this Research Topic is aimed at filling a critical gap. We solicit submissions concerned with mathematical, graph theoretic or other network-based models that can capture or inform the spread of neurodegenerative pathologies in a whole-brain and quantitative fashion. Papers on quantitative validation of trans-neuronal spread in animal, in vitro or in vivo data will also be of interest. The aim of this Research Topic is to generate a quantitative understanding of how brain connectivity may serve as general substrate to explain patterns of neurodegeneration, and to stimulate cross disciplinary thinking, involving researchers working in computer science, image processing, neuroscience, neurology and neuroimaging. We are looking for original research articles, review papers and perspectives for publication in Frontiers in Neurology, with cross-listing in Frontiers in Neuroscience.
In recent years the ability of cell-to-cell transmission of protein species involved in almost all neurodegenerative diseases has been revealed from in vitro, animal models and human in vivo studies. Amyloid beta and tau in Alzheimer's disease, alpha-synuclein in Parkinson's disease, tau, SOD1 and TDP-43 in frontotemporal dementia, TDP-43 in ALS, and so on, are all capable of this kind of "trans-neuronal transmission". Since such transmission occurs along neural connections rather than spatially or randomly, it is therefore emerging that the patterns of spread and progression of neurodegenerative diseases must consequently occur along and within the connectivity networks of the brain. Not only does this view provide a mechanistic basis that underlies and explains the highly stereotypical patterns seen in these diseases, it also enables quantitative and model-based exploration of progression in these diseases.
Although much progress has been made in elucidating the mechanisms of protein transmission in cell cultures and animal models, these approaches do not typically address the entire brain network, nor do they provide a quantitative understanding of these concepts. Therefore this Research Topic is aimed at filling a critical gap. We solicit submissions concerned with mathematical, graph theoretic or other network-based models that can capture or inform the spread of neurodegenerative pathologies in a whole-brain and quantitative fashion. Papers on quantitative validation of trans-neuronal spread in animal, in vitro or in vivo data will also be of interest. The aim of this Research Topic is to generate a quantitative understanding of how brain connectivity may serve as general substrate to explain patterns of neurodegeneration, and to stimulate cross disciplinary thinking, involving researchers working in computer science, image processing, neuroscience, neurology and neuroimaging. We are looking for original research articles, review papers and perspectives for publication in Frontiers in Neurology, with cross-listing in Frontiers in Neuroscience.
