ACTUAL STATUS IN BRAIN MAPPING
Keywords:
BRAIN MAPPINGAbstract
In this editorial, authors have performed an analysis of the current status of brain mapping taking into consideration both general and particular data. Our aim was to provide the basic concepts to each of the aforementioned investigations and finally look at the present perspective on some of the wide-recognized brain mapping projects.
References
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18. Benjamin CFA, Dhingra I, Li AX, et al. Presurgical language fMRI: Technical practices in epilepsy surgical planning. Hum Brain Mapp 2018; 39(10): 4032-4042.
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22. Deverdun J, van Dokkum LEH, Le Bars E, et al. Language reorganization after resection of low-grade gliomas: an fMRI task-based connectivity study. Brain Imaging Behav 2020; 14(5): 1779-1791.
23. Yordanova YN, Cochereau J, Duffau H, Herbet G. Combining resting state functional MRI with intraoperative cortical stimulation to map the mentalizing network. Neuroimage 2019; 186: 628-636.
24. Parisot S, Darlix A, Baumann C, et al. A Probabilistic Atlas of Diffuse WHO Grade II Glioma Loca-tions in the Brain. PLoS One 2016; 11(1): e0144200 / doi: 10.1371/journal.pone.0144200.
2. Nieuwenhuys R, Broere CA, Cerliani L. A new myeloarchitectonic map of the human neocortex based on data from the Vogt-Vogt school. Brain Struct Funct 2015; 220(5): 2551-2573.
3. Shams Z, Norris DG, Marques JP. A comparison of in vivo MRI based cortical myelin mapping using T1w/T2w and R1 mapping at 3T. PLoS One 2019; 14(7): e0218089 / doi: 10.1371/journal.pone. 0218089.
4. Glasser MF, Van Essen DC. Mapping human cortical areas in vivo based on myelin content as revealed by T1- and T2-weighted MRI. J Neurosci 2011; 31(32): 11597-11616.
5. Shafee R, Buckner RL, Fischl B. Gray matter myelination of 1,555 human brains using partial volume corrected MRI images. Neuroimage 2015; 105: 473-485.
6. Agarwal S, Sair HI, Gujar S, Pillai JJ. Language Mapping With fMRI: Current Standards and Repro-ducibility. Top Magn Reson Imaging 2019; 28(4): 225-233.
7. Gaut G, Turner B, Lu ZL, Li X, Cunningham WA, Steyvers M. Predicting Task and Subject Differ-ences with Functional Connectivity and Blood-Oxygen-Level-Dependent Variability. Brain Connect 2019; 9(6): 451-463.
8. Cook MJ, Gardner AJ, Wojtowicz M, Williams WH, Iverson GL, Stanwell P. Task-related functional magnetic resonance imaging activations in patients with acute and subacute mild traumatic brain injury: A coordinate-based meta-analysis. Neuroimage Clin 2020; 25: 102129 / doi: 10.1016/ j.nicl. 2019. 102129.
9. Valente G, Kaas AL, Formisano E, Goebel R. Optimizing fMRI experimental design for MVPA-based BCI control: Combining the strengths of block and event-related designs. Neuroimage 2019; 186: 369-381.
10. Silva MA, See AP, Essayed WI, Golby AJ, Tie Y. Challenges and techniques for presurgical brain mapping with functional MRI. Neuroimage Clin 2017; 17: 794-803.
11. Maknojia S, Churchill NW, Schweizer TA, Graham SJ. Resting State fMRI: Going Through the Motions. Front Neurosci 2019; 13: 825 / doi: 10.3389/fnins.2019.00825
12. Wise RG, Ide K, Poulin MJ, Tracey I. Resting fluctuations in arterial carbon dioxide induce significant low frequency variations in BOLD signal. Neuroimage 2004; 21(4): 1652-1664.
13. Eickhoff SB, Thirion B, Varoquaux G, Bzdok D. Connectivity-based parcellation: Critique and impli-cations. Hum Brain Mapp 2015; 36(12): 4771-4792.
14. Melhem ER, Mori S, Mukundan G, Kraut MA, Pomper MG, van Zijl PC. Diffusion tensor MR imag-ing of the brain and white matter tractography. AJR Am J Roentgenol 2002; 178(1): 3-16.
15. Kollias S. Parcelation of the White Matter Using DTI: Insights into the Functional Connectivity of the Brain. The Neuroradiology Journal 2009; 22(1): 74-84.
16. Hart MG, Price SJ, Suckling J. Connectome analysis for pre-operative brain mapping in neurosurgery. Br J Neurosurg 2016; 30(5): 506-517.
17. Huang Q, Zhang R, Hu X, et al. Disturbed small-world networks and neurocognitive function in frontal lobe low-grade glioma patients. PLoS One 2014; 9(4): e94095 / doi: 10.1371/journal. pone. 0094095.
18. Benjamin CFA, Dhingra I, Li AX, et al. Presurgical language fMRI: Technical practices in epilepsy surgical planning. Hum Brain Mapp 2018; 39(10): 4032-4042.
19. Black DF, Vachha B, Mian A, et al. American Society of Functional Neuroradiology-Recommended fMRI Paradigm Algorithms for Presurgical Language Assessment. AJNR Am J Neuroradiol 2017; 38(10): E65-E73.
20. Sidhu MK, Stretton J, Winston GP, et al. Memory fMRI predicts verbal memory decline after anterior temporal lobe resection. Neurology 2014; 84(15): 1512-1519.
21. Buck S, Bastos F, Baldeweg T, Vargha-Khadem F. A Functional MRI Paradigm Suitable for Language and Memory Mapping in Pediatric Temporal Lobe Epilepsy. Front Neurol 2020; 10: 1384 / doi: 10.3389/fneur.2019.01384.
22. Deverdun J, van Dokkum LEH, Le Bars E, et al. Language reorganization after resection of low-grade gliomas: an fMRI task-based connectivity study. Brain Imaging Behav 2020; 14(5): 1779-1791.
23. Yordanova YN, Cochereau J, Duffau H, Herbet G. Combining resting state functional MRI with intraoperative cortical stimulation to map the mentalizing network. Neuroimage 2019; 186: 628-636.
24. Parisot S, Darlix A, Baumann C, et al. A Probabilistic Atlas of Diffuse WHO Grade II Glioma Loca-tions in the Brain. PLoS One 2016; 11(1): e0144200 / doi: 10.1371/journal.pone.0144200.
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2021-06-30
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