Evidence for Functional Networks within the Human Brain's White Matter

Abstract

Investigation of the functional macro-scale organization of the human cortex is fundamental in modern neuroscience. Although numerous studies have identified networks of interacting functional modules in the gray-matter, limited research was directed to the functional organization of the white-matter. Recent studies have demonstrated that the white-matter exhibits blood oxygen level-dependent signal fluctuations similar to those of the gray-matter. Here we used these signal fluctuations to investigate whether the white-matter is organized as functional networks by applying a clustering analysis on resting-state functional MRI (RSfMRI) data from white-matter voxels, in 176 subjects (of both sexes). This analysis indicated the existence of 12 symmetrical white-matter functional networks, corresponding to combinations of white-matter tracts identified by diffusion tensor imaging. Six of the networks included interhemispheric commissural bridges traversing the corpus callosum. Signals in white-matter networks correlated with signals from functional gray-matter networks, providing missing knowledge on how these distributed networks communicate across large distances. These findings were replicated in an independent subject group and were corroborated by seed-based analysis in small groups and individual subjects. The identified white-matter functional atlases and analysis codes are available at http://mind.huji.ac.il/white-matter.aspx Our results demonstrate that the white-matter manifests an intrinsic functional organization as interacting networks of functional modules, similarly to the gray-matter, which can be investigated using RSfMRI. The discovery of functional networks within the white-matter may open new avenues of research in cognitive neuroscience and clinical neuropsychiatry. In recent years, functional MRI (fMRI) has revolutionized all fields of neuroscience, enabling identifications of functional modules and networks in the human brain. However, most fMRI studies ignored a major part of the brain, the white-matter, discarding signals from it as arising from noise. Here we use resting-state fMRI data from 176 subjects to show that signals from the human white-matter contain meaningful information. We identify 12 functional networks composed of interacting long-distance white-matter tracts. Moreover, we show that these networks are highly correlated to resting-state gray-matter networks, highlighting their functional role. Our findings enable reinterpretation of many existing fMRI datasets, and suggest a new way to explore the white-matter role in cognition and its disturbances in neuropsychiatric disorders.

Regional and network properties of white matter function in Parkinson's disease

“…Future neurophysiological studies on the WM BOLD signal are imperative to further explain the current findings in PD patients. Third, in accordance with previous studies (Ji, Liao, et al, ; Jiang et al, ; Peer et al, ), our main findings were based on data without global signal regression, but the complementary analysis indicated the findings of WM network properties may be sensitive to this processing. The effect of global signal regression has long been discussed when estimating GM function (Murphy & Fox, ); yet more specific investigations are needed to show its influence on WM functional analysis.…”

“…The mean signal in the CSF mask and the 24 head motion parameters (Friston, Williams, Howard, Frackowiak, & Turner, ) were regressed out from the functional images in each subject's individual space. To avoid elimination of signals of interest, we did not include WM and global brain signal as nuisance regressors (Ji, Liao, et al, ; Peer et al, ).…”

“…During resting state (i.e., absence of task requirement on subject), the BOLD signal in WM exhibits a topological organization rather than random distribution as noise (Ji, Liao, Chen, Zhang, & Wang, ). As the fibers are tracked using DTI data, anatomical bundles are able to be identified by resting‐state fMRI data as well (Ding et al, ; Marussich, Lu, Wen, & Liu, ; Peer, Nitzan, Bick, Levin, & Arzy, ). Additionally, the WM function, estimated by the low‐frequency BOLD signal, can be modulated by different tasks (Ding et al, ; Ji, Liao, et al, ; Marussich et al, ; Wu et al, ).…”

“…Combining dynamic functional connectivity in WM could provide valuable information in classifying mild cognitive impairment patients and healthy controls (Chen et al, ). More recently, Jiang and colleagues classified WM into several functional networks as a previous study (Peer et al, ), and estimated their disrupted synchronization with gray matter (GM) function in schizophrenia patients (Jiang et al, ).…”

Evaluation of different cerebrospinal fluid and white matter fMRI filtering strategies—Quantifying noise removal and neural signal preservation

“…The last potential area of interest is CSF/WM regression in studies examining the FC of WM. Recent studies suggest the potential of this method to study brain function in healthy subjects (Ding et al, ; Peer et al, ) and also under pathological conditions (Jiang et al ). The specific form of nuisance regression may differ from our reported results since we focused on GM denoising only.…”