Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: To overcome the limitations of independent component analysis (ICA), today’s most popular analysis tool for investigating whole-brain spatial activation in resting state functional magnetic resonance imaging (fMRI),  present a new class of local dimension-reduced dynamical spatio-temporal model which dispenses the independence assumptions that severely limit deeper connectivity descriptions beten spatial components. The new method combines novel concepts of group sparsity with contiguity-constrained clusterization to produce physiologically consistent regions of interest in illustrative fMRI data whose causal interactions may then be easily estimated, something impossible under the usual ICA assumptions.
['Gilson Vieira', 'Edson Amaro', 'Luiz A. Baccalá']
I am writing a research paper on a idea Local Dimension-Reduced Dynamical Spatio-Temporal Models for Resting State Network Estimation
[{"from": "human", "value": "I am writing a research paper on a idea Local Dimension-Reduced Dynamical Spatio-Temporal Models for Resting State Network Estimation"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: To overcome the limitations of independent component analysis (ICA), today\u2019s most popular analysis tool for investigating whole-brain spatial activation in resting state functional magnetic resonance imaging (fMRI),  present a new class of local dimension-reduced dynamical spatio-temporal model which dispenses the independence assumptions that severely limit deeper connectivity descriptions beten spatial components. The new method combines novel concepts of group sparsity with contiguity-constrained clusterization to produce physiologically consistent regions of interest in illustrative fMRI data whose causal interactions may then be easily estimated, something impossible under the usual ICA assumptions."}]