scholarly journals Presurgical Brain Mapping of the Ventral Somatomotor Network in Patients with Brain Tumors Using Resting-State fMRI

2017 ◽  
Vol 38 (5) ◽  
pp. 1006-1012 ◽  
Author(s):  
N. Yahyavi-Firouz-Abadi ◽  
J.J. Pillai ◽  
M.A. Lindquist ◽  
V.D. Calhoun ◽  
S. Agarwal ◽  
...  
Keyword(s):  
Brain Tumors ◽  
Brain Mapping ◽  
Resting State ◽  
Resting State Fmri

scholarly journals Presurgical brain mapping of the language network in patients with brain tumors using resting-state fMRI: Comparison with task fMRI

2015 ◽  
Vol 37 (3) ◽  
pp. 913-923 ◽  
Author(s):  
Haris I. Sair ◽  
Noushin Yahyavi-Firouz-Abadi ◽  
Vince D. Calhoun ◽  
Raag D. Airan ◽  
Shruti Agarwal ◽  
...  
Keyword(s):  
Brain Tumors ◽  
Brain Mapping ◽  
Resting State ◽  
Resting State Fmri ◽  
Language Network

Longitudinal Changes in Cerebellar and Thalamic Spontaneous Neuronal Activity After Wide-Awake Surgery of Brain Tumors: a Resting-State fMRI Study

2015 ◽  
Vol 15 (4) ◽  
pp. 451-465 ◽  
Author(s):  
Anthony Boyer ◽  
Jérémy Deverdun ◽  
Hugues Duffau ◽  
Emmanuelle Le Bars ◽  
François Molino ◽  
...  
Keyword(s):  
Brain Tumors ◽  
Neuronal Activity ◽  
Resting State ◽  
Resting State Fmri ◽  
Awake Surgery ◽  
Longitudinal Changes ◽  
Fmri Study ◽  
Spontaneous Neuronal Activity ◽  
Wide Awake

scholarly journals Real‐time presurgical resting‐state fMRI in patients with brain tumors: Quality control and comparison with task‐fMRI and intraoperative mapping

2019 ◽  
Vol 41 (3) ◽  
pp. 797-814 ◽  
Author(s):  
Kishore Vakamudi ◽  
Stefan Posse ◽  
Rex Jung ◽  
Brad Cushnyr ◽  
Muhammad O. Chohan
Keyword(s):  
Quality Control ◽  
Brain Tumors ◽  
Real Time ◽  
Resting State ◽  
Resting State Fmri ◽  
Intraoperative Mapping

scholarly journals Whole brain mapping of somatosensory responses in awake marmosets investigated with ultra-high-field fMRI

2020 ◽  
Vol 124 (6) ◽  
pp. 1900-1913
Author(s):  
Justine C. Cléry ◽  
Yuki Hori ◽  
David J. Schaeffer ◽  
Joseph S. Gati ◽  
J. Andrew Pruszynski ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Brain Mapping ◽  
Resting State ◽  
High Field ◽  
Body Representation ◽  
Resting State Fmri ◽  
Fmri Data ◽  
Ultra High Field ◽  
Somatosensory Stimulation ◽  
Somatosensory Responses

We used somatosensory stimulation combined with functional MRI (fMRI) in awake marmosets to reveal the topographic body representation in areas S1, S2, thalamus, and putamen. We showed the existence of a body representation organization within the thalamus and the cingulate cortex by computing functional connectivity maps from seeds defined in S1/S2 using resting-state fMRI data. This noninvasive approach will be essential for chronic studies by guiding invasive recording and manipulation techniques.

scholarly journals Resting state fMRI in pre-surgical brain mapping. Literature review

2018 ◽  
pp. 6-13 ◽  
Author(s):  
A. S. Smirnov ◽  
M. G. Sharaev ◽  
T. V. Melnikova-Pitskhelauri ◽  
V. Yu. Zhukov ◽  
A. E. Bikanov ◽  
...  
Keyword(s):  
Brain Mapping ◽  
Resting State ◽  
Preoperative Planning ◽  
Clinical Information ◽  
Complete Information ◽  
Resting State Fmri ◽  
Blood Oxygen Level Dependent ◽  
Blood Oxygen Level ◽  
Spontaneous Fluctuations ◽  
The Brain

Today, functional magnetic resonance imaging (fMRI) allows to plan surgery based on the topography of functionally important areas of the human brain cortex and tumor. This method can complement the surgical strategy with significant clinical information. The stimulus-dependent fMRI with motor and language paradigms is generally used for preoperative planning. The study outcome depends on the patient's ability to perform tasks paradigm, which is broken in brain tumors. In an attempt to overcome this problem, resting-state fMRI (rs-fMRI) is used for brain mapping. Rs-fMRI is based on the measurement of spontaneous fluctuations of the BOLD signal (blood oxygen level-dependent), representing the functional structure of the brain. In contrast to stimulus-dependent fMRI, rs-fMRI provides more complete information about functional architecture of the brain. rs-fMRI is used in conditions where the results of stimulusdependent fMRI may be falsely positive or in the absence of the possibility of its implementation. In aggregate, both methods significantly expand the efficiency and specificity of preoperative planning.

Presurgical brain mapping of the language network in pediatric patients with epilepsy using resting-state fMRI

2021 ◽  
pp. 1-10
Author(s):  
Daiana R. Pur ◽  
Roy Eagleson ◽  
Marcus Lo ◽  
Michael T. Jurkiewicz ◽  
Andrea Andrade ◽  
...  
Keyword(s):  
Brain Mapping ◽  
Resting State ◽  
Template Matching ◽  
Pediatric Patients ◽  
Resting State Fmri ◽  
Fmri Data ◽  
Epileptogenic Zone ◽  
Anatomical Landmarks ◽  
Language Lateralization ◽  
Language Network

OBJECTIVEEpilepsy affects neural processing and often causes intra- or interhemispheric language reorganization, rendering localization solely based on anatomical landmarks (e.g., Broca’s area) unreliable. Preoperative brain mapping is necessary to weigh the risk of resection with the risk of postoperative deficit. However, the use of conventional mapping methods (e.g., somatosensory stimulation, task-based functional MRI [fMRI]) in pediatric patients is technically difficult due to low compliance and their unique neurophysiology. Resting-state fMRI (rs-fMRI), a “task-free” technique based on the neural activity of the brain at rest, has the potential to overcome these limitations. The authors hypothesized that language networks can be identified from rs-fMRI by applying functional connectivity analyses.METHODSCases in which both task-based fMRI and rs-fMRI were acquired as part of the preoperative clinical protocol for epilepsy surgery were reviewed. Task-based fMRI consisted of 2 language tasks and 1 motor task. Resting-state fMRI data were acquired while the patients watched an animated movie and were analyzed using independent component analysis (i.e., data-driven method). The authors extracted language networks from rs-fMRI data by performing a similarity analysis with functionally defined language network templates via a template-matching procedure. The Dice coefficient was used to quantify the overlap.RESULTSThirteen children underwent conventional task-based fMRI (e.g., verb generation, object naming), rs-fMRI, and structural imaging at 1.5T. The language components with the highest overlap with the language templates were identified for each patient. Language lateralization results from task-based fMRI and rs-fMRI mapping were comparable, with good concordance in most cases. Resting-state fMRI–derived language maps indicated that language was on the left in 4 patients (31%), on the right in 5 patients (38%), and bilateral in 4 patients (31%). In some cases, rs-fMRI indicated a more extensive language representation.CONCLUSIONSResting-state fMRI–derived language network data were identified at the patient level using a template-matching method. More than half of the patients in this study presented with atypical language lateralization, emphasizing the need for mapping. Overall, these data suggest that this technique may be used to preoperatively identify language networks in pediatric patients. It may also optimize presurgical planning of electrode placement and thereby guide the surgeon’s approach to the epileptogenic zone.

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