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Author: Grafiati
Published: 4 June 2021
Last updated: 7 July 2024

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1

Alvarez-Mora, Maria Isabel, Ines Agusti, Robin Wijngaard, Estefania Martinez-Barrios, Tamara Barcos, Aina Borras, Sara Peralta, et al. "Evaluation of FMR4, FMR5 and FMR6 Expression Levels as Non-Invasive Biomarkers for the Diagnosis of Fragile X-Associated Primary Ovarian Insufficiency (FXPOI)." Journal of Clinical Medicine 11, no. 8 (April 14, 2022): 2186. http://dx.doi.org/10.3390/jcm11082186.

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Female FMR1 (Fragile X mental retardation 1) premutation carriers are at risk for developing fragile X-associated primary ovarian insufficiency (FXPOI), a condition characterized by amenorrhea before age 40 years. Not all women with a FMR1 premutation suffer from primary ovarian insufficiency and nowadays there are no molecular or other biomarkers that can help predict the occurrence of FXPOI. Long non-coding RNAs (lncRNAs) comprise a group of regulatory transcripts which have versatile molecular functions, making them important regulators in all aspects of gene expression. In recent medical studies, lncRNAs have been described as potential diagnostic biomarkers in many diseases. The present study was designed to determine the expression profile of three lncRNAs derived from the FMR1 locus, FMR4, FMR5 and FMR6, in female FMR1 premutation carriers in order: (i) to determine a possible role in the pathogenesis of FXPOI and (ii) to investigate whether they could serve as a biomarker for the diagnosis of FXPOI. FMR4, FMR5 and FMR6 transcripts levels were evaluated in total RNA extracted from peripheral blood by digital droplet PCR and compared between FMR1 premutation carriers with FXPOI and without FXPOI. The diagnostic value of lncRNAs was evaluated by receiver operating characteristic (ROC) analysis. Results revealed a significant association between FXPOI and high expression levels of FMR4. No association was obtained for FMR5 or FMR6. ROC curve analysis revealed that FMR4 can distinguish FMR1 premutation carrier with FXPOI with a diagnostic power of 0.67. These findings suggest a potential role of FMR4 as a possible biomarker for FXPOI.
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Choi, Uk-Su, Yul-Wan Sung, and Seiji Ogawa. "Effects of Physiological Signal Removal on Resting-State Functional MRI Metrics." Brain Sciences 13, no. 1 (December 20, 2022): 8. http://dx.doi.org/10.3390/brainsci13010008.

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Resting-state fMRIs (rs-fMRIs) have been widely used for investigation of diverse brain functions, including brain cognition. The rs-fMRI has easily elucidated rs-fMRI metrics, such as the fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), voxel-mirrored homotopic connectivity (VMHC), and degree centrality (DC). To increase the applicability of these metrics, higher reliability is required by reducing confounders that are not related to the functional connectivity signal. Many previous studies already demonstrated the effects of physiological artifact removal from rs-fMRI data, but few have evaluated the effect on rs-fMRI metrics. In this study, we examined the effect of physiological noise correction on the most common rs-fMRI metrics. We calculated the intraclass correlation coefficient of repeated measurements on parcellated brain areas by applying physiological noise correction based on the RETROICOR method. Then, we evaluated the correction effect for five rs-fMRI metrics for the whole brain: FC, fALFF, ReHo, VMHC, and DC. The correction effect depended not only on the brain region, but also on the metric. Among the five metrics, the reliability in terms of the mean value of all ROIs was significantly improved for FC, but it deteriorated for fALFF, with no significant differences for ReHo, VMHC, and DC. Therefore, the decision on whether to perform the physiological correction should be based on the type of metric used.
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Schabdach, Jenna, Rafael Ceschin, Vanessa Schmithorst, M. Dylan Tisdall, Aaron Alexander-Bloch, and Ashok Panigrahy. "A Descriptive Review of the Impact of Patient Motion in Early Childhood Resting-State Functional Magnetic Resonance Imaging." Diagnostics 12, no. 5 (April 20, 2022): 1032. http://dx.doi.org/10.3390/diagnostics12051032.

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Resting-state functional magnetic images (rs-fMRIs) can be used to map and delineate the brain activity occurring while the patient is in a task-free state. These resting-state activity networks can be informative when diagnosing various neurodevelopmental diseases, but only if the images are high quality. The quality of an rs-fMRI rapidly degrades when the patient moves during the scan. Herein, we describe how patient motion impacts an rs-fMRI on multiple levels. We begin with how the electromagnetic field and pulses of an MR scanner interact with a patient’s physiology, how movement affects the net signal acquired by the scanner, and how motion can be quantified from rs-fMRI. We then present methods for preventing motion through educational and behavioral interventions appropriate for different age groups, techniques for prospectively monitoring and correcting motion during the acquisition process, and pipelines for mitigating the effects of motion in existing scans.
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Desai, Virendra R., Aditya Vedantam, Sandi K. Lam, Lucia Mirea, Stephen T. Foldes, Daniel J. Curry, P. David Adelson, Angus A. Wilfong, and Varina L. Boerwinkle. "Language lateralization with resting-state and task-based functional MRI in pediatric epilepsy." Journal of Neurosurgery: Pediatrics 23, no. 2 (February 2019): 171–77. http://dx.doi.org/10.3171/2018.7.peds18162.

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OBJECTIVEDetermining language laterality in patients with intractable epilepsy is important in operative planning. Wada testing is the gold standard, but it has a risk of stroke. Both Wada and task-based functional MRI (tb-fMRI) require patient cooperation. Recently, resting-state fMRI (rs-fMRI) has been explored for language lateralization. In the present study, the correlation between rs-fMRI and tb-fMRI in language lateralization is estimated in a pediatric population with intractable epilepsy.METHODSrs-fMRI and tb-fMRI language lateralization testing performed as part of epilepsy surgery evaluation was retrospectively reviewed.RESULTSTwenty-nine patients underwent rs-fMRI and tb-fMRI; a total of 38 rs-fMRI studies and 30 tb-fMRI studies were obtained. tb-fMRI suggested left dominance in 25 of 30 cases (83%), right in 3 (10%), and in 2 (7%) the studies were nondiagnostic. In rs-fMRI, 26 of 38 studies (68%) suggested left dominance, 3 (8%) right dominance, 6 (16%) bilateral, and 3 (8%) were nondiagnostic. When tb-fMRI lateralized to the left hemisphere (25 cases), rs-fMRI was lateralized to the left in 23 patients (92%) and it was bilateral/equal in 2 (8%). When tb-fMRI lateralized to the right (3 cases), rs-fMRI lateralized to the right in all cases (100%). The overall concordance rate was 0.93 (95% CI 0.76–0.99) when considering cases with tb-fMRI and rs-fMRI performed within 6 months of each other, and tb-fMRI results were not nondiagnostic.CONCLUSIONSrs-fMRI significantly correlated with tb-fMRI in lateralizing language and suggests the potential role for identifying hemispheric dominance via rs-fMRI. Further investigation and validation studies are warranted.
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5

Wei, Pengxu, Zhi Lan, Zeping Lv, and Yubo Fan. "Brainstem fMRI." Encyclopedia 1, no. 1 (December 22, 2020): 4–11. http://dx.doi.org/10.3390/encyclopedia1010003.

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The human brainstem plays important roles in maintaining basic vital functions. In comparison with brain functional magnetic resonance imaging (fMRI), only a few fMRI studies investigating the brainstem have been reported because of a number of technical challenges. This entry briefly introduces technical difficulties, recent advances, and further directions of brainstem fMRI in humans.
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6

Nielsen, F. A., M. S. Christ, K. H. Madsen, T. E. Lund, and L. K. Hansen. "fMRI neuroinformatics." IEEE Engineering in Medicine and Biology Magazine 25, no. 2 (March 2006): 112–19. http://dx.doi.org/10.1109/memb.2006.1607675.

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7

Utting, Jane F. "BLOODLESS fMRI." Neuroreport 12, no. 15 (October 2001): A87. http://dx.doi.org/10.1097/00001756-200110290-00002.

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8

Jasanoff, Alan. "Bloodless fMRI." Trends in Neurosciences 30, no. 11 (November 2007): 603–10. http://dx.doi.org/10.1016/j.tins.2007.08.002.

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9

Hoge, Richard D. "Calibrated fMRI." NeuroImage 62, no. 2 (August 2012): 930–37. http://dx.doi.org/10.1016/j.neuroimage.2012.02.022.

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10

Bartelle, Benjamin B., Ali Barandov, and Alan Jasanoff. "Molecular fMRI." Journal of Neuroscience 36, no. 15 (April 13, 2016): 4139–48. http://dx.doi.org/10.1523/jneurosci.4050-15.2016.

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11

Fink, Andreas. "fMRI/EEG." Neuroscience Letters 500 (July 2011): e15. http://dx.doi.org/10.1016/j.neulet.2011.05.105.

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12

Lang, ST, B. Goodyear, J. Kelly, and P. Federico. "Neurophysiology (fMRI)." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 42, S1 (May 2015): S38. http://dx.doi.org/10.1017/cjn.2015.173.

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Background: Resting state functional MRI (rs-fMRI) provides many advantages to task-based fMRI in neurosurgical populations, foremost of which is the lack of the need to perform a task. Many networks can be identified by rs-fMRI in a single period of scanning. Despite the advantages, there is a paucity of literature on rs-fMRI in neurosurgical populations. Methods: Eight patients with tumours near areas traditionally considered as eloquent cortex participated in a five minute rs-fMRI scan. Resting-state fMRI data underwent Independent Component Analysis (ICA) using the Multivariate Exploratory Linear Optimized Decomposition into Independent Components (MELODIC) toolbox in FSL. Resting state networks (RSNs) were identified on a visual basis. Results: Several RSNs, including language (N=7), sensorimotor (N=7), visual (N=7), default mode network (N=8) and frontoparietal attentional control (n=7) networks were readily identifiable using ICA of rs-fMRI data. Conclusion: These pilot data suggest that ICA applied to rs-fMRI data can be used to identify motor and language networks in patients with brain tumours. We have also shown that RSNs associated with cognitive functioning, including the default mode network and the frontoparietal attentional control network can be identified in individual subjects with brain tumours. While preliminary, this suggests that rs-fMRI may be used pre-operatively to localize areas of cortex important for higher order cognitive functioning.
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Thulborn, Keith R. "Clinical fMRI." Current Protocols in Magnetic Resonance Imaging 1, no. 1 (June 2001): A6.0.1—A6.0.3. http://dx.doi.org/10.1002/0471142719.mia0600s01.

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Hocke, Lia Maria, Yunjie Tong, and Blaise deBonneval Frederick. "An Automatic Motion-Based Artifact Reduction Algorithm for fNIRS in Concurrent Functional Magnetic Resonance Imaging Studies (AMARA–fMRI)." Algorithms 16, no. 5 (April 28, 2023): 230. http://dx.doi.org/10.3390/a16050230.

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Multimodal functional near-infrared spectroscopy–functional magnetic resonance imaging (fNIRS–fMRI) studies have been highly beneficial for both the fNIRS and fMRI field as, for example, they shed light on the underlying mechanism of each method. However, several noise sources exist in both methods. Motion artifact removal is an important preprocessing step in fNIRS analysis. Several manual motion–artifact removal methods have been developed which require time and are highly dependent on expertise. Only a few automatic methods have been proposed. AMARA (acceleration-based movement artifact reduction algorithm) is one of the most promising automatic methods and was originally tested in an fNIRS sleep study with long acquisition times (~8 h). However, it relies on accelerometry data, which is problematic when performing concurrent fNIRS–fMIRI experiments. Most accelerometers are not MR compatible, and in any case, existing datasets do not have this data. Here, we propose a new way to retrospectively determine acceleration data for motion correction methods, such as AMARA in multimodal fNIRS–fMRI studies. We do so by considering the individual slice stack acquisition times of simultaneous multislice (SMS) acquisition and reconstructing high-resolution motion traces from each slice stack time. We validated our method on 10 participants during a memory task (2- and 3-back) with 6 fNIRS channels over the prefrontal cortex (limited field of view with fMRI). We found that this motion correction significantly improved the detection of activation in deoxyhemoglobin and outperformed up-sampled motion traces. However, we found no improvement in oxyhemoglobin. Furthermore, our data show a high overlap with fMRI activation when considering activation in channels according to both deoxyhemoglobin and oxyhemoglobin.
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Ihalainen, Toni, Linda Kuusela, Sampsa Turunen, Sami Heikkinen, Sauli Savolainen, and Outi Sipilä. "Data quality in fMRI and simultaneous EEG–fMRI." Magnetic Resonance Materials in Physics, Biology and Medicine 28, no. 1 (April 26, 2014): 23–31. http://dx.doi.org/10.1007/s10334-014-0443-6.

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16

Chen, Xuming, Yuanyuan Jiang, Sangcheon Choi, Rolf Pohmann, Klaus Scheffler, David Kleinfeld, and Xin Yu. "Assessment of single-vessel cerebral blood velocity by phase contrast fMRI." PLOS Biology 19, no. 9 (September 9, 2021): e3000923. http://dx.doi.org/10.1371/journal.pbio.3000923.

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Current approaches to high-field functional MRI (fMRI) provide 2 means to map hemodynamics at the level of single vessels in the brain. One is through changes in deoxyhemoglobin in venules, i.e., blood oxygenation level–dependent (BOLD) fMRI, while the second is through changes in arteriole diameter, i.e., cerebral blood volume (CBV) fMRI. Here, we introduce cerebral blood flow–related velocity-based fMRI, denoted CBFv-fMRI, which uses high-resolution phase contrast (PC) MRI to form velocity measurements of flow. We use CBFv-fMRI in measure changes in blood velocity in single penetrating microvessels across rat parietal cortex. In contrast to the venule-dominated BOLD and arteriole-dominated CBV fMRI signals, CBFv-fMRI is comparable from both arterioles and venules. A single fMRI platform is used to map changes in blood pO2 (BOLD), volume (CBV), and velocity (CBFv). This combined high-resolution single-vessel fMRI mapping scheme enables vessel-specific hemodynamic mapping in animal models of normal and diseased states and further has translational potential to map vascular dementia in diseased or injured human brains with ultra–high-field fMRI.
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Zacà, Domenico, Jorge Jovicich, Francesco Corsini, Umberto Rozzanigo, Franco Chioffi, and Silvio Sarubbo. "ReStNeuMap: a tool for automatic extraction of resting-state functional MRI networks in neurosurgical practice." Journal of Neurosurgery 131, no. 3 (September 2019): 764–71. http://dx.doi.org/10.3171/2018.4.jns18474.

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OBJECTIVEResting-state functional MRI (rs-fMRI) represents a promising and cost-effective alternative to task-based fMRI for presurgical mapping. However, the lack of clinically streamlined and reliable rs-fMRI analysis tools has prevented wide adoption of this technique. In this work, the authors introduce an rs-fMRI processing pipeline (ReStNeuMap) for automatic single-patient rs-fMRI network analysis.METHODSThe authors provide a description of the rs-fMRI network analysis steps implemented in ReStNeuMap and report their initial experience with this tool after performing presurgical mapping in 6 patients. They verified the spatial agreement between rs-fMRI networks derived by ReStNeuMap and localization of activation with intraoperative direct electrical stimulation (DES).RESULTSThe authors automatically extracted rs-fMRI networks including eloquent cortex in spatial proximity with the resected lesion in all patients. The distance between DES points and corresponding rs-fMRI networks was less than 1 cm in 78% of cases for motor, 100% of cases for visual, 87.5% of cases for language, and 100% of cases for speech articulation mapping.CONCLUSIONSThe authors’ initial experience with ReStNeuMap showed good spatial agreement between presurgical rs-fMRI predictions and DES findings during awake surgery. The availability of the rs-fMRI analysis tools for clinicians aiming to perform noninvasive mapping of brain functional networks may extend its application beyond surgical practice.
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Zhong, Yuan, Gang Zheng, Yijun Liu, and Guangming Lu. "Independent Component Analysis of Instantaneous Power-Based fMRI." Computational and Mathematical Methods in Medicine 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/579652.

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In functional magnetic resonance imaging (fMRI) studies using spatial independent component analysis (sICA) method, a model of “latent variables” is often employed, which is based on the assumption that fMRI data are linear mixtures of statistically independent signals. However, actual fMRI signals are nonlinear and do not automatically meet with the requirement of sICA. To provide a better solution to this problem, we proposed a novel approach termed instantaneous power based fMRI (ip-fMRI) for regularization of fMRI data. Given that the instantaneous power of fMRI signals is a scalar value, it should be a linear mixture that naturally satisfies the “latent variables” model. Based on our simulated data, the curves of accuracy and resulting receiver-operating characteristic curves indicate that the proposed approach is superior to the traditional fMRI in terms of accuracy and specificity by using sICA. Experimental results from human subjects have shown that spatial components of a hand movement task-induced activation reveal a brain network more specific to motor function by ip-fMRI than that by the traditional fMRI. We conclude that ICA decomposition of ip-fMRI may be used to localize energy signal changes in the brain and may have a potential to be applied to detection of brain activity.
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Wang, Jue, Hai-Jiang Meng, Gong-Jun Ji, Ying Jing, Hong-Xiao Wang, Xin-Ping Deng, Zi-Jian Feng, Na Zhao, Yu-Feng Zang, and Jian Zhang. "Finger Tapping Task Activation vs. TMS Hotspot: Different Locations and Networks." Brain Topography 33, no. 1 (November 6, 2019): 123–34. http://dx.doi.org/10.1007/s10548-019-00741-9.

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Abstract Both functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS) have been used to non-invasively localize the human motor functional area. These locations can be clinically used as stimulation target of TMS treatment. However, it has been reported that the finger tapping fMRI activation and TMS hotspot were not well-overlapped. The aim of the current study was to measure the distance between the finger tapping fMRI activation and the TMS hotspot, and more importantly, to compare the network difference by using resting-state fMRI. Thirty healthy participants underwent resting-state fMRI, task fMRI, and then TMS hotspot localization. We found significant difference of locations between finger tapping fMRI activation and TMS hotspot. Specifically, the finger tapping fMRI activation was more lateral than the TMS hotspot in the premotor area. The fMRI activation peak and TMS hotspot were taken as seeds for resting-state functional connectivity analyses. Compared with TMS hotspot, finger tapping fMRI activation peak showed more intensive functional connectivity with, e.g., the bilateral premotor, insula, putamen, and right globus pallidus. The findings more intensive networks of finger tapping activation than TMS hotspot suggest that TMS treatment targeting on the fMRI activation area might result in more remote effects and would be more helpful for TMS treatment on movement disorders.
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Stopa, Brittany M., Joeky T. Senders, Marike L. D. Broekman, Mark Vangel, and Alexandra J. Golby. "Preoperative functional MRI use in neurooncology patients: a clinician survey." Neurosurgical Focus 48, no. 2 (February 2020): E11. http://dx.doi.org/10.3171/2019.11.focus19779.

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OBJECTIVEFunctional MRI (fMRI) is increasingly being investigated for use in neurosurgical patient care. In the current study, the authors characterize the clinical use of fMRI by surveying neurosurgeons’ use of and attitudes toward fMRI as a surgical planning tool in neurooncology patients.METHODSA survey was developed to inquire about clinicians’ use of and experiences with preoperative fMRI in the neurooncology patient population, including example case images. The survey was distributed to all neurosurgical departments with a residency program in the US.RESULTSAfter excluding incomplete surveys and responders that do not use fMRI (n = 11), 50 complete responses were included in the final analysis. Responders were predominantly from academic programs (88%), with 20 years or more in practice (40%), with a main area of practice in neurooncology (48%) and treating an adult population (90%). All 50 responders currently use fMRI in neurooncology patients, mostly for low- (94%) and high-grade glioma (82%). The leading decision factors for ordering fMRI were location of mass in dominant hemisphere, location in a functional area, motor symptoms, and aphasia. Across 10 cases, language fMRI yielded the highest interrater reliability agreement (Fleiss’ kappa 0.437). The most common reasons for ordering fMRI were to identify language laterality, plan extent of resection, and discuss neurological risks with patients. Clinicians reported that fMRI results were not obtained when ordered a median 10% of the time and were suboptimal a median 27% of the time. Of responders, 70% reported that they had ever resected an fMRI-positive functional site, of whom 77% did so because the site was “cleared” by cortical stimulation. Responders reported disagreement between fMRI and awake surgery 30% of the time. Overall, 98% of responders reported that if results of fMRI and intraoperative mapping disagreed, they would rely on intraoperative mapping.CONCLUSIONSAlthough fMRI is increasingly being adopted as a practical preoperative planning tool for brain tumor resection, there remains a substantial degree of discrepancy with regard to its current use and presumed utility. There is a need for further research to evaluate the use of preoperative fMRI in neurooncology patients. As fMRI continues to gain prominence, it will be important for clinicians to collectively share best practices and develop guidelines for the use of fMRI in the preoperative planning phase of brain tumor patients.
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Yang, Biao, Jinmeng Cao, Tiantong Zhou, Li Dong, Ling Zou, and Jianbo Xiang. "Exploration of Neural Activity under Cognitive Reappraisal Using Simultaneous EEG-fMRI Data and Kernel Canonical Correlation Analysis." Computational and Mathematical Methods in Medicine 2018 (July 2, 2018): 1–11. http://dx.doi.org/10.1155/2018/3018356.

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Background. Neural activity under cognitive reappraisal can be more accurately investigated using simultaneous EEG- (electroencephalography) fMRI (functional magnetic resonance imaging) than using EEG or fMRI only. Complementary spatiotemporal information can be found from simultaneous EEG-fMRI data to study brain function. Method. An effective EEG-fMRI fusion framework is proposed in this work. EEG-fMRI data is simultaneously sampled on fifteen visually stimulated healthy adult participants. Net-station toolbox and empirical mode decomposition are employed for EEG denoising. Sparse spectral clustering is used to construct fMRI masks that are used to constrain fMRI activated regions. A kernel-based canonical correlation analysis is utilized to fuse nonlinear EEG-fMRI data. Results. The experimental results show a distinct late positive potential (LPP, latency 200-700ms) from the correlated EEG components that are reconstructed from nonlinear EEG-fMRI data. Peak value of LPP under reappraisal state is smaller than that under negative state, however, larger than that under neutral state. For correlated fMRI components, obvious activation can be observed in cerebral regions, e.g., the amygdala, temporal lobe, cingulate gyrus, hippocampus, and frontal lobe. Meanwhile, in these regions, activated intensity under reappraisal state is obviously smaller than that under negative state and larger than that under neutral state. Conclusions. The proposed EEG-fMRI fusion approach provides an effective way to study the neural activities of cognitive reappraisal with high spatiotemporal resolution. It is also suitable for other neuroimaging technologies using simultaneous EEG-fMRI data.
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He, Yi, Maosen Wang, and Xin Yu. "High spatiotemporal vessel-specific hemodynamic mapping with multi-echo single-vessel fMRI." Journal of Cerebral Blood Flow & Metabolism 40, no. 10 (November 7, 2019): 2098–114. http://dx.doi.org/10.1177/0271678x19886240.

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High-resolution fMRI enables noninvasive mapping of the hemodynamic responses from individual penetrating vessels in animal brains. Here, a 2D multi-echo single-vessel fMRI (MESV-fMRI) method has been developed to map the fMRI signal from arterioles and venules with a 100 ms sampling rate at multiple echo times (TE, 3–30 ms) and short acquisition windows (<1 ms). The T2*-weighted signal shows the increased extravascular effect on venule voxels as a function of TE. In contrast, the arteriole voxels show an increased fMRI signal with earlier onset than venules voxels at the short TE (3 ms) with increased blood inflow and volume effects. MESV-fMRI enables vessel-specific T2* mapping and presents T2*-based fMRI time courses with higher contrast-to-noise ratios (CNRs) than the T2*-weighted fMRI signal at a given TE. The vessel-specific T2* mapping also allows semi-quantitative estimation of the oxygen saturation levels (Y) and their changes (ΔY) at a given blood volume fraction upon neuronal activation. The MESV-fMRI method enables vessel-specific T2* measurements with high spatiotemporal resolution for better modeling of the fMRI signal based on the hemodynamic parameters.
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Håberg, Asta, Kjell Arne Kvistad, Geirmund Unsgård, and Olav Haraldseth. "Preoperative Blood Oxygen Level-dependent Functional Magnetic Resonance Imaging in Patients with Primary Brain Tumors: Clinical Application and Outcome." Neurosurgery 54, no. 4 (April 1, 2004): 902–15. http://dx.doi.org/10.1227/01.neu.0000114510.05922.f8.

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Abstract OBJECTIVE This study sought to evaluate the ability of blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) to successfully identify functional cortical areas in patients with primary brain tumors, to evaluate the use of the fMRI results in presurgical planning, and to assess the functional outcome of the patients with respect to the functional maps obtained with fMRI. METHODS The study included 25 consecutive preoperative fMRI sessions in patients with primary brain tumors in or near sensorimotor and/or language cortices. All fMRI paradigms were analyzed and rated according to the degree of success. Several distances between tumor and functional cortex as delineated with BOLD fMRI were measured to assess the topographic relationship between these two structures. Pre- and postoperative neurological statuses were obtained from the patients' journals. RESULTS Acquisition of BOLD fMRI images was successful in 80% of the cases. The primary cause of unsuccessful fMRI was echo-planar imaging signal voids that were the result of previous craniotomy; the secondary cause was excessive motion. The neurosurgeons used the fMRI results for preoperative planning in 75% of the cases in which fMRI was successful. The risk of postoperative loss of function tested with fMRI was significantly lower when the distance between tumor periphery and BOLD activity was 10 mm or more. CONCLUSION The majority of patients with primary brain tumors were capable of satisfactorily performing the fMRI paradigms, and the information obtained was used in the preoperative planning. A distance of 10 mm or more between the functional cortex, as delineated with fMRI, and the tumor significantly reduced the risk of postoperative loss of function.
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Pur, Daiana R., Roy Eagleson, Marcus Lo, Michael T. Jurkiewicz, Andrea Andrade, and Sandrine de Ribaupierre. "Presurgical brain mapping of the language network in pediatric patients with epilepsy using resting-state fMRI." Journal of Neurosurgery: Pediatrics 27, no. 3 (March 2021): 259–68. http://dx.doi.org/10.3171/2020.8.peds20517.

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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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Smirnov, A. S., M. G. Sharaev, T. V. Melnikova-Pitskhelauri, V. Yu Zhukov, A. E. Bikanov, E. V. Sharova, E. L. Pogosbekyan, et al. "Resting state fMRI in pre-surgical brain mapping. Literature review." Medical Visualization, no. 5 (October 28, 2018): 6–13. http://dx.doi.org/10.24835/1607-0763-2018-5-6-13.

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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.
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Maus, Bärbel, and Gerard J. P. van Breukelen. "Optimal Design for Functional Magnetic Resonance Imaging Experiments." Zeitschrift für Psychologie 221, no. 3 (January 2013): 174–89. http://dx.doi.org/10.1027/2151-2604/a000145.

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This paper provides an overview of optimal design for functional magnetic resonance imaging (fMRI) studies. We present the main types of fMRI designs, namely blocked and event-related designs, and common objectives of fMRI experiments, for example, localization of task-related activity in the human brain. Furthermore, we present an introduction into the methodology for analysis and optimization of fMRI experiments, for instance common analysis models and applied optimality criteria. We outline some of the problems encountered when optimizing fMRI experiments, for example, the temporal autocorrelation between measurements in fMRI data. The most important results for optimization of blocked and event-related designs with regard to the different design objectives are presented and explained. Finally, we conclude with future perspectives and challenges for optimization of fMRI experiments.
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Shen, Yuji, Risto A. Kauppinen, Rishma Vidyasagar, and Xavier Golay. "A Functional Magnetic Resonance Imaging Technique Based on Nulling Extravascular Gray Matter Signal." Journal of Cerebral Blood Flow & Metabolism 29, no. 1 (August 27, 2008): 144–56. http://dx.doi.org/10.1038/jcbfm.2008.96.

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A new functional magnetic resonance imaging (fMRI) technique is proposed based on nulling the extravascular gray matter (GM) signal, using a spatially nonselective inversion pulse. The remaining MR signal provides cerebral blood volume (CBV) information from brain activation. A theoretical framework is provided to characterize the sources of GM-nulled (GMN) fMRI signal, effects of partial voluming of cerebrospinal fluid (CSF) and white matter, and behaviors of GMN fMRI signal during brain activation. Visual stimulation paradigm was used to explore the GMN fMRI signal behavior in the human brain at 3T. It is shown that the GMN fMRI signal increases by 7.2% ± 1.5%, which is two to three times more than that obtained with vascular space occupancy (VASO)-dependent fMRI (−3.2% ± 0.2%) or blood oxygenation level-dependent (BOLD) fMRI (2.9% ± 0.7%), using a TR of 3,000 ms and a resolution of 2 × 2 × 5 mm3. Under these conditions the fMRI signal-to-noise ratio (SNRfMRI) for BOLD, GMN, and VASO images was 4.97 ± 0.76, 4.56 ± 0.86, and 2.43 ± 1.06, respectively. Our study shows that both signal intensity and activation volume in GMN fMRI depend on spatial resolution because of partial voluming from CSF. It is shown that GMN fMRI is a convenient tool to assess CBV changes associated with brain activation.
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Feigenson, Neal. "Brain imaging and courtroom evidence: on the admissibility and persuasiveness of fMRI." International Journal of Law in Context 2, no. 3 (September 2006): 233–55. http://dx.doi.org/10.1017/s174455230600303x.

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Functional magnetic resonance imaging (fMRI) is currently the most advanced technique for measuring and depicting brain function. Functional MRI studies abound in neuroscience, psychiatry and psychology. Inevitably, fMRI-based evidence will be offered in court as proof of matters involving parties’ mental states and capabilities. This paper analyses the likely admissibility of fMRI testimony and images. Cases involving other types of functional neuroimaging (PET and SPECT), which may shed light on judges’ receptivity to fMRI evidence, are briefly surveyed. The conceptual and methodological underpinnings of fMRI are then explored, prompting basic questions about the evidentiary reliability and relevance of fMRI results. The first reported case involving fMRI evidence, which raises several of these questions, is described. Finally, the admissibility and probative value of the fMRI images themselves are discussed. Assuming that the expert testimony that the images are offered to illustrate is admissible, it is argued that the law can obtain the benefits of fMRI science while minimising the judgmental risks by allowing triers of fact to see the images and encouraging experts and lawyers to educate the triers to interpret the images properly.
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Wang, Kainan S., David V. Smith, and Mauricio R. Delgado. "Using fMRI to study reward processing in humans: past, present, and future." Journal of Neurophysiology 115, no. 3 (March 1, 2016): 1664–78. http://dx.doi.org/10.1152/jn.00333.2015.

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Functional magnetic resonance imaging (fMRI) is a noninvasive tool used to probe cognitive and affective processes. Although fMRI provides indirect measures of neural activity, the advent of fMRI has allowed for 1) the corroboration of significant animal findings in the human brain, and 2) the expansion of models to include more common human attributes that inform behavior. In this review, we briefly consider the neural basis of the blood oxygenation level dependent signal to set up a discussion of how fMRI studies have applied it in examining cognitive models in humans and the promise of using fMRI to advance such models. Specifically, we illustrate the contribution that fMRI has made to the study of reward processing, focusing on the role of the striatum in encoding reward-related learning signals that drive anticipatory and consummatory behaviors. For instance, we discuss how fMRI can be used to link neural signals (e.g., striatal responses to rewards) to individual differences in behavior and traits. While this functional segregation approach has been constructive to our understanding of reward-related functions, many fMRI studies have also benefitted from a functional integration approach that takes into account how interconnected regions (e.g., corticostriatal circuits) contribute to reward processing. We contend that future work using fMRI will profit from using a multimodal approach, such as combining fMRI with noninvasive brain stimulation tools (e.g., transcranial electrical stimulation), that can identify causal mechanisms underlying reward processing. Consequently, advancements in implementing fMRI will promise new translational opportunities to inform our understanding of psychopathologies.
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Aulia Putra, Handityo. "Exploring Air Properties for fMRI-Compatible Interaction Devices." MATEC Web of Conferences 215 (2018): 01001. http://dx.doi.org/10.1051/matecconf/201821501001.

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The strong magnetic field of functional magnetic resonance imaging (fMRI) and the supine position of participants in fMRI scanners severely limit how participants can interact during fMRI experiments. This paper explores the use of air properties to design interaction-device systems that allow various interaction styles inside a fMRI scanner. Airflow and air pressure are explored to design and develop the interaction system. A series of air-based devices are introduced and discussed to demonstrate the feasibility of an air-based approach. This includes soft tactile and conventional controls (e.g., button, slider, joystick, pedal). To achieve fMRI-compatibility, all parts used inside the scanner are built from non-ferromagnetic, off-the-shelf plastic, and/or 3D printed materials. The fMRI compatibility was evaluated on a 3.0 Tesla fMRI scanner. We conclude with example applications and thoughts on future avenues of research.
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Połczyńska, Monika M. "Organizing Variables Affecting fMRI Estimates of Language Dominance in Patients with Brain Tumors." Brain Sciences 11, no. 6 (May 25, 2021): 694. http://dx.doi.org/10.3390/brainsci11060694.

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Numerous variables can affect the assessment of language dominance using presurgical functional magnetic resonance (fMRI) in patients with brain tumors. This work organizes the variables into confounding and modulating factors. Confounding factors give the appearance of changed language dominance. Most confounding factors are fMRI-specific and they can substantially disrupt the evaluation of language dominance. Confounding factors can be divided into two categories: tumor-related and fMRI analysis. The tumor-related confounds further subdivide into tumor characteristics (e.g., tumor grade) and tumor-induced conditions (aphasia). The fMRI analysis confounds represent technical aspects of fMRI methods (e.g., a fixed versus an individual threshold). Modulating factors can modify language dominance without confounding it. They are not fMRI-specific, and they can impact language dominance both in healthy individuals and neurosurgical patients. The effect of most modulating factors on fMRI language dominance is smaller than that of confounding factors. Modulating factors include demographics (e.g., age) and linguistic variables (e.g., early bilingualism). Three cases of brain tumors in the left hemisphere are presented to illustrate how modulating confounding and modulating factors can impact fMRI estimates of language dominance. Distinguishing between confounding and modulating factors can help interpret the results of presurgical language mapping with fMRI.
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Roux, Franck-Emmanuel, Kader Boulanouar, Jean-Albert Lotterie, Mehdi Mejdoubi, James P. LeSage, and Isabelle Berry. "Language Functional Magnetic Resonance Imaging in Preoperative Assessment of Language Areas: Correlation with Direct Cortical Stimulation." Neurosurgery 52, no. 6 (June 1, 2003): 1335–47. http://dx.doi.org/10.1227/01.neu.0000064803.05077.40.

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Abstract OBJECTIVE The aim of this study was to analyze the usefulness of preoperative language functional magnetic resonance imaging (fMRI), by correlating fMRI data with intraoperative cortical stimulation results for patients with brain tumors. METHODS Naming and verb generation tasks were used, separately or in combination, for 14 right-handed patients with tumors in the left hemisphere. fMRI data obtained were analyzed with SPM software, with two standard analysis thresholds (P &lt; 0.005 and then P &lt; 0.05). The fMRI data were then registered in a frameless stereotactic neuronavigational device and correlated with direct brain mapping results. We used a statistical model with the fMRI information as a predictor, spatially correlating each intraoperatively mapped cortical site with fMRI data integrated in the neuronavigational system (site-by-site correlation). Eight patients were also studied with language fMRI postoperatively, with the same acquisition protocol. RESULTS We observed high variability in signal extents and locations among patients with both tasks. The activated areas were located mainly in the left hemisphere in the middle and inferior frontal gyri (F2 and F3), the superior and middle temporal gyri (T1 and T2), and the supramarginal and angular gyri. A total of 426 cortical sites were tested for each task among the 14 patients. In frontal and temporoparietal areas, poor sensitivity of the fMRI technique was observed for the naming and verb generation tasks (22 and 36%, respectively) with P &lt; 0.005 as the analysis threshold. Although not perfect, the specificity of the fMRI technique was good in all conditions (97% for the naming task and 98% for the verb generation task). Better correlation (sensitivity, 59%; specificity, 97%) was achieved by combining the two fMRI tasks. Variation of the analysis threshold to P &lt; 0.05 increased the sensitivity to 66% while decreasing the specificity to 91%. Postoperative fMRI data (for the cortical brain areas studied intraoperatively) were in accordance with brain mapping results for six of eight patients. Complete agreement between pre- and postoperative fMRI studies and direct brain mapping results was observed for only three of eight patients. CONCLUSION With the paradigms and analysis thresholds used in this study, language fMRI data obtained with naming or verb generation tasks, before and after surgery, were imperfectly correlated with intraoperative brain mapping results. A better correlation could be obtained by combining the fMRI tasks. The overall results of this study demonstrated that language fMRI could not be used to make critical surgical decisions in the absence of direct brain mapping. Other acquisition protocols are required for evaluation of the potential role of language fMRI in the accurate detection of essential cortical language areas.
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Canario, Edgar, Donna Chen, and Bharat Biswal. "A review of resting-state fMRI and its use to examine psychiatric disorders." Psychoradiology 1, no. 1 (March 2021): 42–53. http://dx.doi.org/10.1093/psyrad/kkab003.

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Abstract Resting-state fMRI (rs-fMRI) has emerged as an alternative method to study brain function in human and animal models. In humans, it has been widely used to study psychiatric disorders including schizophrenia, bipolar disorder, autism spectrum disorders, and attention deficit hyperactivity disorders. In this review, rs-fMRI and its advantages over task based fMRI, its currently used analysis methods, and its application in psychiatric disorders using different analysis methods are discussed. Finally, several limitations and challenges of rs-fMRI applications are also discussed.
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Giussani, Carlo, Frank-Emmanuel Roux, Jeffrey Ojemann, Erik Pietro Sganzerla, David Pirillo, and Costanza Papagno. "Is Preoperative Functional Magnetic Resonance Imaging Reliable for Language Areas Mapping in Brain Tumor Surgery? Review of Language Functional Magnetic Resonance Imaging and Direct Cortical Stimulation Correlation Studies." Neurosurgery 66, no. 1 (January 1, 2010): 113–20. http://dx.doi.org/10.1227/01.neu.0000360392.15450.c9.

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Abstract OBJECTIVE Language functional magnetic resonance imaging (fMRI) has been used extensively in the past decade for both clinical and research purposes. Its integration in the preoperative imaging assessment of brain lesions involving eloquent areas is progressively more diffused in neurosurgical practice. Nevertheless, the reliability of language fMRI is unclear. To understand the reliability of preoperative language fMRI in patients operated on for brain tumors, the surgical studies that compared language fMRI with direct cortical stimulation (DCS) were reviewed. METHODS Articles comparing language fMRI with DCS of language areas were reviewed with attention to the lesion pathology, the magnetic field, the language tasks used pre- and intraoperatively, and the validation modalities adopted to establish the reliability of language fMRI. We tried to explore the effectiveness of language fMRI in gliomas. RESULTS Nine language brain mapping studies compared the findings of fMRI with those of DCS. The studies are not homogeneous for tumor types, magnetic fields, pre- and intraoperative language tasks, intraoperative matching criteria, and results. Sensitivity and specificity were calculated in 5 studies (respectively ranging from 59% to 100% and from 0% to 97%). CONCLUSION The contradictory results of these studies do not allow consideration of language fMRI as an alternative tool to DCS in brain lesions located in language areas, especially in gliomas because of the pattern of growth of these tumors. However, language fMRI conducted with high magnet fields is a promising brain mapping tool that must be validated by DCS in methodological robust studies.
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Wiens, Charmaine, Bradley G. Goodyear, Ankur Goel, Paolo Federico, Walter Hader, and Mayank Goyal. "Presurgical Language fMRI and Postsurgical Deficits: A Single Centre Experience." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 40, no. 6 (November 2013): 819–23. http://dx.doi.org/10.1017/s031716710001595x.

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Background:In this study, we conducted a retrospective investigation of our initial single-centre experience with the clinical use of functional magnetic resonance imaging (fMRI) of hemisphere dominance for language processing (i.e., language lateralization). We demonstrated its association with surgical outcome and its potential impact on surgical planning and patient management.Methods:Fifty-two cases were reviewed, covering the period from July 2007 to July 2010. Clinical fMRI reports were examined to determine the hemisphere dominance for language processing. Neurological reports were examined to determine if new language deficits were present post-surgery. Neurosurgeon notes were also reviewed to determine if fMRI had an impact on surgical planning.Results:Of the cases reviewed, 49 (94%) generated conclusive fMRI. Eleven (22%) patients exhibited fMRI language lateralization contralateral to pathology; zero of nine of these patients that had surgery experienced post-surgical deficits. Twenty-two (44%) patients exhibited fMRI language lateralization ipsilateral to pathology; three of 13 of these patients that had surgery experienced post-surgical deficits. Sixteen (34%) patients exhibited bilateral lateralization of language; five of 13 of these patients that had surgery experienced post-surgery deficits. Several post-fMRI reports indicated that fMRI results had an impact on surgical planning.Conclusions:Our results suggest that fMRI demonstrations of language processing within the hemisphere ipsilateral to pathology (either ipsilateral alone or bilateral) is associated with a greater risk for post-surgical language deficits, and in these cases, fMRI results should be taken into consideration for pre-surgical planning.
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Enzinger, Christian, Daniela Pinter, Maria A. Rocca, John De Luca, Jaume Sastre-Garriga, Bertrand Audoin, and Massimo Filippi. "Longitudinal fMRI studies: Exploring brain plasticity and repair in MS." Multiple Sclerosis Journal 22, no. 3 (December 18, 2015): 269–78. http://dx.doi.org/10.1177/1352458515619781.

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Functional magnetic resonance imaging (fMRI) has greatly advanced our understanding of cerebral functional changes occurring in patients with multiple sclerosis (MS). However, most of our knowledge regarding brain plasticity and repair in MS as evidenced by fMRI has been extrapolated from cross-sectional studies across different phenotypes of the disease. This topical review provides an overview of this research, but also highlights limitations of existing fMRI studies with cross-sectional design. We then review the few existing longitudinal fMRI studies and discuss the feasibility and constraints of serial fMRI in individuals with MS. We further emphasize the potential to track fMRI changes in evolving disease and the insights this may give in terms of mechanisms of adaptation and repair, focusing on serial fMRI to monitor response to disease-modifying therapies or rehabilitation interventions. Finally, we offer recommendations for designing future research studies to overcome previous methodological shortcomings.
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Agarwal, Shruti, Kirk M. Welker, David F. Black, Jason T. Little, David R. DeLone, Steven A. Messina, Theodore J. Passe, Chetan Bettegowda, and Jay J. Pillai. "Detection and Mitigation of Neurovascular Uncoupling in Brain Gliomas." Cancers 15, no. 18 (September 8, 2023): 4473. http://dx.doi.org/10.3390/cancers15184473.

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Functional magnetic resonance imaging (fMRI) with blood oxygen level-dependent (BOLD) technique is useful for preoperative mapping of brain functional networks in tumor patients, providing reliable in vivo detection of eloquent cortex to help reduce the risk of postsurgical morbidity. BOLD task-based fMRI (tb-fMRI) is the most often used noninvasive method that can reliably map cortical networks, including those associated with sensorimotor, language, and visual functions. BOLD resting-state fMRI (rs-fMRI) is emerging as a promising ancillary tool for visualization of diverse functional networks. Although fMRI is a powerful tool that can be used as an adjunct for brain tumor surgery planning, it has some constraints that should be taken into consideration for proper clinical interpretation. BOLD fMRI interpretation may be limited by neurovascular uncoupling (NVU) induced by brain tumors. Cerebrovascular reactivity (CVR) mapping obtained using breath-hold methods is an effective method for evaluating NVU potential.
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Weiner, Kevin S., Rory Sayres, Joakim Vinberg, and Kalanit Grill-Spector. "fMRI-Adaptation and Category Selectivity in Human Ventral Temporal Cortex: Regional Differences Across Time Scales." Journal of Neurophysiology 103, no. 6 (June 2010): 3349–65. http://dx.doi.org/10.1152/jn.01108.2009.

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Repeating object images produces stimulus-specific repetition suppression referred to as functional magnetic resonance imaging-adaptation (fMRI-A) in ventral temporal cortex (VTC). However, the effects of stimulus repetition on functional selectivity are largely unknown. We investigated the effects of short-lagged (SL, immediate) and long-lagged (LL, many intervening stimuli) repetitions on category selectivity in VTC using high-resolution fMRI. We asked whether repetition produces scaling or sharpening of fMRI responses both within category-selective regions as well as in the distributed response pattern across VTC. Results illustrate that repetition effects across time scales vary quantitatively along an anterior-posterior axis and qualitatively along a lateral-medial axis. In lateral VTC, both SL and LL repetitions produce proportional fMRI-A with no change in either selectivity or distributed responses as predicted by a scaling model. Further, there is larger fMRI-A in anterior subregions irrespective of category selectivity. Medial VTC exhibits similar scaling effects during SL repetitions. However, for LL repetitions, both the selectivity and distributed pattern of responses vary with category in medial VTC as predicted by a sharpening model. Specifically, there is larger fMRI-A for nonpreferred categories compared with the preferred category, and category selectivity does not predict fMRI-A across the pattern of distributed response. Finally, simulations indicate that different neural mechanisms likely underlie fMRI-A in medial compared to lateral VTC. These results have important implications for future fMRI-A experiments because they suggest that fMRI-A does not reflect a universal neural mechanism and that results of fMRI-A experiments will likely be paradigm independent in lateral VTC but paradigm dependent in medial VTC.
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Peters, Judith C., Joel Reithler, Teresa Schuhmann, Tom de Graaf, Kâmil Uludağ, Rainer Goebel, and Alexander T. Sack. "On the feasibility of concurrent human TMS-EEG-fMRI measurements." Journal of Neurophysiology 109, no. 4 (February 15, 2013): 1214–27. http://dx.doi.org/10.1152/jn.00071.2012.

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Simultaneously combining the complementary assets of EEG, functional MRI (fMRI), and transcranial magnetic stimulation (TMS) within one experimental session provides synergetic results, offering insights into brain function that go beyond the scope of each method when used in isolation. The steady increase of concurrent EEG-fMRI, TMS-EEG, and TMS-fMRI studies further underlines the added value of such multimodal imaging approaches. Whereas concurrent EEG-fMRI enables monitoring of brain-wide network dynamics with high temporal and spatial resolution, the combination with TMS provides insights in causal interactions within these networks. Thus the simultaneous use of all three methods would allow studying fast, spatially accurate, and distributed causal interactions in the perturbed system and its functional relevance for intact behavior. Concurrent EEG-fMRI, TMS-EEG, and TMS-fMRI experiments are already technically challenging, and the three-way combination of TMS-EEG-fMRI might yield additional difficulties in terms of hardware strain or signal quality. The present study explored the feasibility of concurrent TMS-EEG-fMRI studies by performing safety and quality assurance tests based on phantom and human data combining existing commercially available hardware. Results revealed that combined TMS-EEG-fMRI measurements were technically feasible, safe in terms of induced temperature changes, allowed functional MRI acquisition with comparable image quality as during concurrent EEG-fMRI or TMS-fMRI, and provided artifact-free EEG before and from 300 ms after TMS pulse application. Based on these empirical findings, we discuss the conceptual benefits of this novel complementary approach to investigate the working human brain and list a number of precautions and caveats to be heeded when setting up such multimodal imaging facilities with current hardware.
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Kim, Jaehee. "Statistical analysis issues for fMRI data." Journal of the Korean Data And Information Science Sociaty 29, no. 6 (November 30, 2018): 1353–63. http://dx.doi.org/10.7465/jkdi.2018.29.6.1353.

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Noh, Ju Hyeon, and Hee-Deok Yang. "Alzheimer progression classification using fMRI data." Korean Institute of Smart Media 13, no. 4 (April 30, 2024): 86–93. http://dx.doi.org/10.30693/smj.2024.13.4.86.

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The development of functional magnetic resonance imaging (fMRI) has significantly contributed to mapping brain functions and understanding brain networks during rest. This paper proposes a CNN-LSTM-based classification model to classify the progression stages of Alzheimer's disease. Firstly, four preprocessing steps are performed to remove noise from the fMRI data before feature extraction. Secondly, the U-Net architecture is utilized to extract spatial features once preprocessing is completed. Thirdly, the extracted spatial features undergo LSTM processing to extract temporal features, ultimately leading to classification. Experiments were conducted by adjusting the temporal dimension of the data. Using 5-fold cross-validation, an average accuracy of 96.4% was achieved, indicating that the proposed method has high potential for identifying the progression of Alzheimer's disease by analyzing fMRI data.
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Vogt, Nina. "fMRI goes individual." Nature Methods 12, no. 12 (December 2015): 1112. http://dx.doi.org/10.1038/nmeth.3677.

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NARUSE, Shoji. "Functional MRI(fMRI)." Japanese Journal of Rehabilitation Medicine 35, no. 6 (1998): 405–11. http://dx.doi.org/10.2490/jjrm1963.35.405.

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Tang, Cheuk Ying, and Ramachandran Ramani. "fMRI and Anesthesia." International Anesthesiology Clinics 54, no. 1 (2016): 129–42. http://dx.doi.org/10.1097/aia.0000000000000081.

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Caria, Andrea, Ranganatha Sitaram, and Niels Birbaumer. "Real-Time fMRI." Neuroscientist 18, no. 5 (June 7, 2011): 487–501. http://dx.doi.org/10.1177/1073858411407205.

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Guerra-Carrillo, Belén, Allyson P. Mackey, and Silvia A. Bunge. "Resting-State fMRI." Neuroscientist 20, no. 5 (February 21, 2014): 522–33. http://dx.doi.org/10.1177/1073858414524442.

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Broerse, A., F. W. Cornelissen, and J. A. den Boer. "fMRI of inhibition." Schizophrenia Research 41, no. 1 (January 2000): 136. http://dx.doi.org/10.1016/s0920-9964(00)90631-5.

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Ritter, Petra, and Arno Villringer. "Simultaneous EEG–fMRI." Neuroscience & Biobehavioral Reviews 30, no. 6 (January 2006): 823–38. http://dx.doi.org/10.1016/j.neubiorev.2006.06.008.

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Hadjikhani, Nouchine. "fMRI made clear." Trends in Neurosciences 25, no. 9 (September 2002): 485–86. http://dx.doi.org/10.1016/s0166-2236(02)02196-3.

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Larsson, Jonas, Samuel G. Solomon, and Adam Kohn. "fMRI adaptation revisited." Cortex 80 (July 2016): 154–60. http://dx.doi.org/10.1016/j.cortex.2015.10.026.

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