Since the first lesion studies of Broca and Wernicke scientists have been trying to relate function to specific cortical areas and to generate functional maps of the human cortex. Mapping approaches based on histology, morphology, or function (through task-based fMRI and PET), have been used to delineate sub-regions in the brain. This proposal presents a new approach for mapping cortical subunits through analysis of resting-state connectivity data. The over-arching goal is to develop and validate a method that uses resting-state fMRI connectivity data to delineate functional subunits within each cortical and subcortical region throughout the brain and to produce a whole-brain probabilistic atlas based on these functional subunits. These subunits then provide a starting point for network analysis leading ultimately to a human connectome.
The aims are to extend our working algorithm to include additional spatial constraints, and to validate the algorithm on data from healthy control subjects using 3 validation approaches.
The final aim i s to pilot this approach in intractable epilepsy patients to test the hypothesis that this approach allows for the identification of specific abnormal nodes or networks that may be associated with seizure generation. The immediate practical use of a map of the functional subunits throughout the brain will be to provide a framework for simplifying the analysis, interpretation, and reporting, of conventional task-based neuroimaging results aimed at determining the specific functions of these areas. The atlas generated will also provide a basis set from which a range of neurological disorders may be contrasted to reveal abnormal functional units and/or networks that may be affected by disease. This work could have substantial impact in translation clinical application of these methods and in understanding the impact on the functional organization of the brain of a range of neurological disorders such as Alzheimer's, Parkinson's, MS, and epilepsy, and on psychiatric disorders such as schizophrenia. Finally, this work will provide a methodology for assessing individual variance in organization of these functional subunits potentially leading to methods that will allow the impact of disease, genetics, and environment, to be studied without the constraints of task-based fMRI.
This project is aimed at developing a method to produce an atlas of the functional subunits in the human brain. This work could have substantial impact in understanding the impact on the functional organization of the brain of a range of neurological disorders such as Alzheimer's, Parkinson's, MS, and epilepsy and on psychiatric disorders such as schizophrenia. It also represents the first step in the path towards a human connectome.
|Salehi, Mehraveh; Karbasi, Amin; Shen, Xilin et al. (2018) An exemplar-based approach to individualized parcellation reveals the need for sex specific functional networks. Neuroimage 170:54-67|
|Qiu, Maolin; Scheinost, Dustin; Ramani, Ramachandran et al. (2017) Multi-modal analysis of functional connectivity and cerebral blood flow reveals shared and unique effects of propofol in large-scale brain networks. Neuroimage 148:130-140|
|Shen, Xilin; Finn, Emily S; Scheinost, Dustin et al. (2017) Using connectome-based predictive modeling to predict individual behavior from brain connectivity. Nat Protoc 12:506-518|
|Rosenberg, Monica D; Zhang, Sheng; Hsu, Wei-Ting et al. (2016) Methylphenidate Modulates Functional Network Connectivity to Enhance Attention. J Neurosci 36:9547-57|
|Scheinost, Dustin; Tokoglu, Fuyuze; Shen, Xilin et al. (2016) Fluctuations in Global Brain Activity Are Associated With Changes in Whole-Brain Connectivity of Functional Networks. IEEE Trans Biomed Eng 63:2540-2549|
|Rosenberg, Monica D; Finn, Emily S; Scheinost, Dustin et al. (2016) A neuromarker of sustained attention from whole-brain functional connectivity. Nat Neurosci 19:165-71|
|Finn, Emily S; Shen, Xilin; Scheinost, Dustin et al. (2015) Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity. Nat Neurosci 18:1664-71|
|Lee, Hyang Woon; Arora, Jagriti; Papademetris, Xenophon et al. (2014) Altered functional connectivity in seizure onset zones revealed by fMRI intrinsic connectivity. Neurology 83:2269-77|
|Scheinost, Dustin; Papademetris, Xenophon; Constable, R Todd (2014) The impact of image smoothness on intrinsic functional connectivity and head motion confounds. Neuroimage 95:13-21|
|Scheinost, Dustin; Shen, Xilin; Finn, Emily et al. (2014) Coupled Intrinsic Connectivity Distribution analysis: a method for exploratory connectivity analysis of paired FMRI data. PLoS One 9:e93544|
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