The goals of this proposal are to further investigate and evaluate recent new discoveries about the nature of temporal variations in magnetic resonance imaging (MRI) signals from the human brain, acquired in a resting state, which potentially provide a completely new basis for quantifying the functional architecture of white matter. We have recently shown that local inter-voxel correlations between resting state signal fluctuations within white matter are spatially anisotropic. Measurements of these anisotropic correlations and subsequent analyses permit the derivation of a new mathematical descriptor, a functional connectivity tensor (FCT) that quantifies the functional synchronization between neighboring voxels and delineates longer range dynamic connections. Some of the features of FCTs superficially closely resemble the appearance of diffusion tensor imaging (DTI) data across large brain regions but without the use of any diffusion gradients and based on completely different biophysical phenomena. This discovery demonstrates that white matter tracts exhibit functional, temporal variations which in turn suggest a new approach for integrating functional and structural information. The construction and analysis of FCTs permits tractography of functional pathways that often appear to follow white matter tracts, potentially revealing directions of flow of neural information. Furthermore, the functional tensors appear to change in response to neural stimulation, even though task-activation of white matter has proven elusive. Resting state connectivity has been extensively used to delineate functional circuits within the cortex but to date has been completely overlooked in white matter, and current opinions are biased against being able to detect neural activity in white matter using MRI. The objectives of this research therefore are to construct functional connectivity tensors in normal brains at rest, compare these to underlying structural features, and elucidate the underlying biophysical mechanisms that account for their origins.
Our specific aims are (i) to measure and characterize functional connectivity tensors in a resting state in normal subjects, assess their reproducibility, and determine how they depend on specific technical aspects of acquisition and post- processing; we will quantitatively assess whether FCT data conform to white matter tracts, which may be achieved by analyses of FCT and DTI atlases created from a population of normal subjects co-registered to the same space; (ii) to investigate the biophysical origins of resting state correlational anisotropy in humans, and how they vary with stimulation; and (iii) to validate the basis and interpretation of these correlations by high field studies of nn-human primates, in which we will determine whether the correlations originate from hemodynamic changes and how they relate to underlying neural electrical activity. Overall, these will be the first comprehensive evaluations of our novel observations of anisotropy of correlations in resting state MRI signals from white matter. The proposed use of FCTs for mapping of brain functional connectivity is compelling and offers to advance our understanding of the functional organization of complex neural networks in the brain.
This research builds on our recent demonstrations that signal fluctuations within white matter from neighboring regions are highly correlated when a subject is 'at rest', but these correlations are anisotropic and reveal an underlying structure that may be used to trace functional connections spanning large sections of the brain. This represents a new approach to assess the integrity of critical brain functions that are altered in various disorders, and a new way to detect and measure synchronized neural activity in the brain.
