Predicting functional activity from structural connectivity
نویسندگان
چکیده
منابع مشابه
Predicting human resting-state functional connectivity from structural connectivity.
In the cerebral cortex, the activity levels of neuronal populations are continuously fluctuating. When neuronal activity, as measured using functional MRI (fMRI), is temporally coherent across 2 populations, those populations are said to be functionally connected. Functional connectivity has previously been shown to correlate with structural (anatomical) connectivity patterns at an aggregate le...
متن کاملPredicting Resting-State Functional Connectivity from Structural Connectivity
C. J. Honey, O. Sporns, L. Cammoun, X. Gigandet, J-P. Thiran, R. Meuli, and P. Hagmann 1 Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, United States, Signal Processing Laboratory 5, Ecole Polytechnique Fédérale de Lausanne, Lausanne, VD, Switzerland, Department of Radiology, University Hospital Center and University of Lausanne (CHUV), Lausanne, VD, Switze...
متن کاملAccurately predicting functional connectivity from diffusion imaging
Understanding the relationship between the dynamics of neural processes and the anatomical substrate of the brain is a central question in neuroscience. On the one hand, modern neuroimaging technologies, such as diffusion tensor imaging, can be used to construct structural graphs representing the architecture of white matter streamlines linking cortical and subcortical structures. On the other ...
متن کاملPrediction of functional connectivity from structural brain connectivity
Introduction: Studies that examine the relationship of functional and structural connectivity are important in interpreting neurophysiological data. Although, the relationship between functional and structural connectivity has been explored with a number of statistical tools [1, 2], there is no explicit attempt to quantitatively measure how well functional data can be predicted from structural ...
متن کاملOn inferring structural connectivity from brain functional-MRI data
The anatomical structure of the brain can be observed via non-invasive techniques such as diffusion imaging. However, these are imperfect because they miss connections that are actually known to exist, especially long range interhemispheric ones. In this paper we formulate the inverse problem of inferring the structural connectivity of brain networks from experimentally observed functional conn...
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ژورنال
عنوان ژورنال: Frontiers in Neuroinformatics
سال: 2011
ISSN: 1662-5196
DOI: 10.3389/conf.fninf.2011.08.00010