Localization of brain function is important to minimize functional deficits after neurosurgical procedures. A long-standing goal has been to obtain this information pre-operatively to better predict risk and plan the surgical approach. Although many non-invasive tools are available, fMRI has seen the greatest clinical use. Unfortunately, pre-operative mapping with fMRI suffers from poor signal to noise ratio (SNR) and test-retest reliability at the single-subject level, and the resulting maps are not always consistent with the findings of invasive electrical cortical stimulation (ECS), causing many to question its clinical utility. Recently, our laboratory and others have made major advances that may help address these limitations. Many of these advances have focused on connectivity imaging based on spontaneous activity, catalyzed in part by the NIH Human Connectome Project (HCP). These technical innovations and theoretical advancements are now ripe for being translated to individual clinical patients, but require optimization and validation. The goal of this project is o translate cutting-edge connectivity-based imaging technology to the clinical arena by developing and validating a set of functional mapping tools that can provide individual-level precision and guide surgical intervention. Specifically, we will develop and validate a connectivity-based parcellation technology that can localize functional networks in individual subjects, including in patients with altered brain anatomy. Second, we will develop and validate a connectivity-based method to quantify the lateralization of important cognitive functions and overcome the influence of anatomical asymmetry. Finally, we propose a strategy to improve mapping accuracy when patients are able to perform tasks by flexibly combining the information obtained from spontaneous connectivity and task-evoked responses. This strategy will allow us to leverage the lessons learned from 20 years of exploration using task fMRI and recent revolutionary advancements in connectivity research. The successful completion of this project will greatly improve the clinical value of fMRI in surgical planning, as well as in a wide range of clinical applications. The project will offer a set of comprehensive and extensively tested functional mapping tools suitable for the study of individual subjects with greater sensitivity and reliabilit than are currently available. This increase in mapping precision will directly translate into an enhanced ability to a) predict and reduce postoperative functional deficits, as well as to b) design individualized treatment plans for many neurological and psychiatric patients.

Public Health Relevance

The goal of this project is to translate cutting-edge connectivity-based imaging technology to the clinical arena by developing and validating a set of tools that can accurately map an individual subject's brain and guide surgical intervention.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS091604-03
Application #
9252600
Study Section
Medical Imaging Study Section (MEDI)
Program Officer
Stewart, Randall R
Project Start
2015-04-01
Project End
2020-03-31
Budget Start
2017-04-01
Budget End
2018-03-31
Support Year
3
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02114
Li, Meiling; Becker, Benjamin; Zheng, Junjie et al. (2018) Dysregulated Maturation of the Functional Connectome in Antipsychotic-Naïve, First-Episode Patients With Adolescent-Onset Schizophrenia. Schizophr Bull :
Brennan, Brian P; Wang, Danhong; Li, Meiling et al. (2018) Use of an Individual-Level Approach to Identify Cortical Connectivity Biomarkers in Obsessive-Compulsive Disorder. Biol Psychiatry Cogn Neurosci Neuroimaging :
Kong, Ru; Li, Jingwei; Orban, Csaba et al. (2018) Spatial Topography of Individual-Specific Cortical Networks Predicts Human Cognition, Personality, and Emotion. Cereb Cortex :
Fu, Xiaoxuan; Wang, Youhua; Ge, Manling et al. (2018) Negative effects of interictal spikes on theta rhythm in human temporal lobe epilepsy. Epilepsy Behav :
Wang, Danhong; Li, Meiling; Wang, Meiyun et al. (2018) Individual-specific functional connectivity markers track dimensional and categorical features of psychotic illness. Mol Psychiatry :
Jing, Bin; Liu, Bo; Li, Hui et al. (2018) Within-subject test-retest reliability of the atlas-based cortical volume measurement in the rat brain: A voxel-based morphometry study. J Neurosci Methods 307:46-52
Taylor, Alexander N W; Kambeitz-Ilankovic, Lana; Gesierich, Benno et al. (2017) Tract-specific white matter hyperintensities disrupt neural network function in Alzheimer's disease. Alzheimers Dement 13:225-235
Shine, James M; Kucyi, Aaron; Foster, Brett L et al. (2017) Distinct Patterns of Temporal and Directional Connectivity among Intrinsic Networks in the Human Brain. J Neurosci 37:9667-9674
Tang, Wei; Liu, Hesheng; Douw, Linda et al. (2017) Dynamic connectivity modulates local activity in the core regions of the default-mode network. Proc Natl Acad Sci U S A 114:9713-9718
Nenning, Karl-Heinz; Liu, Hesheng; Ghosh, Satrajit S et al. (2017) Diffeomorphic functional brain surface alignment: Functional demons. Neuroimage 156:456-465

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