Clinical applications of neurolinguistics in neurosurgery

Peng Wang, Zehao Zhao, Linghao Bu, Nijiati Kudulaiti, Qiao Shan, Yuyao Zhou, N. U. Farrukh Hameed, Yangming Zhu, Lei Jin, Jie Zhang, Junfeng Lu, Jinsong Wu

PDF(2096 KB)
PDF(2096 KB)
Front. Med. ›› 2021, Vol. 15 ›› Issue (4) : 562-574. DOI: 10.1007/s11684-020-0771-z
REVIEW
REVIEW

Clinical applications of neurolinguistics in neurosurgery

Author information +
History +

Abstract

The protection of language function is one of the major challenges of brain surgery. Over the past century, neurosurgeons have attempted to seek the optimal strategy for the preoperative and intraoperative identification of language-related brain regions. Neurosurgeons have investigated the neural mechanism of language, developed neurolinguistics theory, and provided unique evidence to further understand the neural basis of language functions by using intraoperative cortical and subcortical electrical stimulation. With the emergence of modern neuroscience techniques and dramatic advances in language models over the last 25 years, novel language mapping methods have been applied in the neurosurgical practice to help neurosurgeons protect the brain and reduce morbidity. The rapid advancements in brain--computer interface have provided the perfect platform for the combination of neurosurgery and neurolinguistics. In this review, the history of neurolinguistics models, advancements in modern technology, role of neurosurgery in language mapping, and modern language mapping methods (including noninvasive neuroimaging techniques and invasive cortical electroencephalogram) are presented.

Keywords

neurolinguistics / language mapping / dual pathway model / neurosurgery

Cite this article

Download citation ▾
Peng Wang, Zehao Zhao, Linghao Bu, Nijiati Kudulaiti, Qiao Shan, Yuyao Zhou, N. U. Farrukh Hameed, Yangming Zhu, Lei Jin, Jie Zhang, Junfeng Lu, Jinsong Wu. Clinical applications of neurolinguistics in neurosurgery. Front. Med., 2021, 15(4): 562‒574 https://doi.org/10.1007/s11684-020-0771-z

References

[1]
Tremblay P, Dick AS. Broca and Wernicke are dead, or moving past the classic model of language neurobiology. Brain Lang 2016; 162: 60–71
CrossRef Pubmed Google scholar
[2]
Ueno T, Saito S, Rogers TT, Lambon Ralph MA. Lichtheim 2: synthesizing aphasia and the neural basis of language in a neurocomputational model of the dual dorsal-ventral language pathways. Neuron 2011; 72(2): 385–396
CrossRef Pubmed Google scholar
[3]
Poeppel D, Emmorey K, Hickok G, Pylkkänen L. Towards a new neurobiology of language. J Neurosci 2012; 32(41): 14125–14131
CrossRef Pubmed Google scholar
[4]
Hickok G, Poeppel D. The cortical organization of speech processing. Nat Rev Neurosci 2007; 8(5): 393–402
CrossRef Pubmed Google scholar
[5]
Catani M, Jones DK, Ffytche DH. Perisylvian language networks of the human brain. Ann Neurol 2005; 57(1): 8–16
CrossRef Pubmed Google scholar
[6]
Chang EF, Raygor KP, Berger MS. Contemporary model of language organization: an overview for neurosurgeons. J Neurosurg 2015; 122(2): 250–261
CrossRef Pubmed Google scholar
[7]
Zhang N, Xia M, Qiu T, Wang X, Lin CP, Guo Q, Lu J, Wu Q, Zhuang D, Yu Z, Gong F, Farrukh Hameed NU, He Y, Wu J, Zhou L. Reorganization of cerebro-cerebellar circuit in patients with left hemispheric gliomas involving language network: a combined structural and resting-state functional MRI study. Hum Brain Mapp 2018; 39(12): 4802–4819
CrossRef Pubmed Google scholar
[8]
Yagmurlu K, Middlebrooks EH, Tanriover N, Rhoton AL Jr. Fiber tracts of the dorsal language stream in the human brain. J Neurosurg 2016; 124(5): 1396–1405
CrossRef Pubmed Google scholar
[9]
Fernandez-Miranda JC, Pathak S, Schneider W. High-definition fiber tractography and language. J Neurosurg 2010; 113(1): 156––158
CrossRef Pubmed Google scholar
[10]
Fernández-Miranda JC, Rhoton AL Jr, Alvarez-Linera J, Kakizawa Y, Choi C, de Oliveira EP. Three-dimensional microsurgical and tractographic anatomy of the white matter of the human brain. Neurosurgery 2008; 62(6 Suppl 3): 989–1028
CrossRef Pubmed Google scholar
[11]
Fernandez-Miranda JC, Pathak S, Engh J, Jarbo K, Verstynen T, Yeh FC, Wang Y, Mintz A, Boada F, Schneider W, Friedlander R. High-definition fiber tractography of the human brain: neuroanatomical validation and neurosurgical applications. Neurosurgery 2012; 71(2): 430–453
CrossRef Pubmed Google scholar
[12]
Levelt WJ, Roelofs A, Meyer AS. A theory of lexical access in speech production. Behav Brain Sci 1999; 22(1): 1–38
CrossRef Pubmed Google scholar
[13]
Indefrey P, Levelt WJ. The spatial and temporal signatures of word production components. Cognition 2004; 92(1-2): 101–144
CrossRef Pubmed Google scholar
[14]
Indefrey P. The spatial and temporal signatures of word production components: a critical update. Front Psychol 2011; 2: 255
CrossRef Pubmed Google scholar
[15]
Mandonnet E, Gatignol P, Duffau H. Evidence for an occipito-temporal tract underlying visual recognition in picture naming. Clin Neurol Neurosurg 2009; 111(7): 601–605
CrossRef Pubmed Google scholar
[16]
Vogel AC, Petersen SE, Schlaggar BL. The VWFA: it’s not just for words anymore. Front Hum Neurosci 2014; 8: 88
CrossRef Pubmed Google scholar
[17]
Breshears JD, Molinaro AM, Chang EF. A probabilistic map of the human ventral sensorimotor cortex using electrical stimulation. J Neurosurg 2015; 123(2): 340–349
CrossRef Pubmed Google scholar
[18]
Penfield W, Roberts L. Speech and brain mechanisms. New Jersey: Princeton University Press,1959
[19]
Dronkers NF, Plaisant O, Iba-Zizen MT, Cabanis EA. Paul Broca’s historic cases: high resolution MR imaging of the brains of Leborgne and Lelong. Brain 2007; 130(5): 1432–1441
CrossRef Pubmed Google scholar
[20]
Ojemann GA, Whitaker HA. Language localization and variability. Brain Lang 1978; 6(2): 239–260
CrossRef Pubmed Google scholar
[21]
Penfield W, Boldrey E. Somatic motor and sensory representation in the cerebral cortex of man as studied by electrical stimulation. Brain 1937; 60(4): 389–443
CrossRef Google scholar
[22]
Whitaker HA, Ojemann GA. Graded localisation of naming from electrical stimulation mapping of left cerebral cortex. Nature 1977; 270(5632): 50–51
CrossRef Pubmed Google scholar
[23]
Ojemann G, Ojemann J, Lettich E, Berger M. Cortical language localization in left, dominant hemisphere. An electrical stimulation mapping investigation in 117 patients. J Neurosurg 1989; 71(3): 316–326
CrossRef Pubmed Google scholar
[24]
Berger MS, Ojemann GA. Intraoperative brain mapping techniques in neuro-oncology. Stereotact Funct Neurosurg 1992; 58(1-4): 153–161
CrossRef Pubmed Google scholar
[25]
Sanai N, Mirzadeh Z, Berger MS. Functional outcome after language mapping for glioma resection. N Engl J Med 2008; 358(1): 18–27
CrossRef Pubmed Google scholar
[26]
Tate MC, Herbet G, Moritz-Gasser S, Tate JE, Duffau H. Probabilistic map of critical functional regions of the human cerebral cortex: Broca’s area revisited. Brain 2014; 137(10): 2773–2782
CrossRef Pubmed Google scholar
[27]
Wu J, Lu J, Zhang H, Zhang J, Yao C, Zhuang D, Qiu T, Guo Q, Hu X, Mao Y, Zhou L. Direct evidence from intraoperative electrocortical stimulation indicates shared and distinct speech production center between Chinese and English languages. Hum Brain Mapp 2015; 36(12): 4972–4985
CrossRef Pubmed Google scholar
[28]
Duffau H, Capelle L, Sichez N, Denvil D, Lopes M, Sichez JP, Bitar A, Fohanno D. Intraoperative mapping of the subcortical language pathways using direct stimulations. An anatomo-functional study. Brain 2002; 125(1): 199–214
CrossRef Pubmed Google scholar
[29]
Cheung C, Chang EF. Real-time, time-frequency mapping of event-related cortical activation. J Neural Eng 2012; 9(4): 046018
CrossRef Pubmed Google scholar
[30]
Dym RJ, Burns J, Freeman K, Lipton ML. Is functional MR imaging assessment of hemispheric language dominance as good as the Wada test?: a meta-analysis. Radiology 2011; 261(2): 446–455
CrossRef Pubmed Google scholar
[31]
Bauer PR, Reitsma JB, Houweling BM, Ferrier CH, Ramsey NF. Can fMRI safely replace the Wada test for preoperative assessment of language lateralisation? A meta-analysis and systematic review. J Neurol Neurosurg Psychiatry 2014; 85(5): 581–588
CrossRef Pubmed Google scholar
[32]
Doucet GE, Pustina D, Skidmore C, Sharan A, Sperling MR, Tracy JI. Resting-state functional connectivity predicts the strength of hemispheric lateralization for language processing in temporal lobe epilepsy and normals. Hum Brain Mapp 2015; 36(1): 288–303
CrossRef Pubmed Google scholar
[33]
DeSalvo MN, Tanaka N, Douw L, Leveroni CL, Buchbinder BR, Greve DN, Stufflebeam SM. Resting-state functional MR imaging for determining language laterality in intractable epilepsy. Radiology 2016; 281(1): 264–269
CrossRef Pubmed Google scholar
[34]
Smitha KA, Arun KM, Rajesh PG, Thomas B, Radhakrishnan A, Sarma PS, Kesavadas C. Resting fMRI as an alternative for task-based fMRI for language lateralization in temporal lobe epilepsy patients: a study using independent component analysis. Neuroradiology 2019; 61(7): 803–810
CrossRef Pubmed Google scholar
[35]
Junck L, Hervey-Jumper SL, Sagher O. Resection of gliomas around language areas: can fMRI contribute? Neurology 2015; 84(6): 550–551
CrossRef Pubmed Google scholar
[36]
Kuchcinski G, Mellerio C, Pallud J, Dezamis E, Turc G, Rigaux-Viodé O, Malherbe C, Roca P, Leclerc X, Varlet P, Chrétien F, Devaux B, Meder JF, Oppenheim C. Three-tesla functional MR language mapping: comparison with direct cortical stimulation in gliomas. Neurology 2015; 84(6): 560–568
CrossRef Pubmed Google scholar
[37]
Pillai JJ, Zacá D. Clinical utility of cerebrovascular reactivity mapping in patients with low grade gliomas. World J Clin Oncol 2011; 2(12): 397–403
CrossRef Pubmed Google scholar
[38]
Hou BL, Bradbury M, Peck KK, Petrovich NM, Gutin PH, Holodny AI. Effect of brain tumor neovasculature defined by rCBV on BOLD fMRI activation volume in the primary motor cortex. Neuroimage 2006; 32(2): 489–497
CrossRef Pubmed Google scholar
[39]
Krüger G, Kastrup A, Glover GH. Neuroimaging at 1.5 T and 3.0 T: comparison of oxygenation-sensitive magnetic resonance imaging. Magn Reson Med 2001; 45(4): 595–604
CrossRef Pubmed Google scholar
[40]
Bizzi A, Blasi V, Falini A, Ferroli P, Cadioli M, Danesi U, Aquino D, Marras C, Caldiroli D, Broggi G. Presurgical functional MR imaging of language and motor functions: validation with intraoperative electrocortical mapping. Radiology 2008; 248(2): 579–589
CrossRef Pubmed Google scholar
[41]
Roux FE, Boulanouar K, Lotterie JA, Mejdoubi M, LeSage JP, Berry I. Language functional magnetic resonance imaging in preoperative assessment of language areas: correlation with direct cortical stimulation. Neurosurgery 2003; 52(6): 1335–1347
CrossRef Pubmed Google scholar
[42]
Ruohonen J, Karhu J. Navigated transcranial magnetic stimulation. Neurophysiol Clin 2010; 40(1): 7–17
CrossRef Pubmed Google scholar
[43]
Kombos T, Picht T, Derdilopoulos A, Suess O. Impact of intraoperative neurophysiological monitoring on surgery of high-grade gliomas. J Clin Neurophysiol 2009; 26(6): 422–425
CrossRef Pubmed Google scholar
[44]
Pascual-Leone A, Walsh V, Rothwell J. Transcranial magnetic stimulation in cognitive neuroscience—virtual lesion, chronometry, and functional connectivity. Curr Opin Neurobiol 2000; 10(2): 232–237
CrossRef Pubmed Google scholar
[45]
Pascual-Leone A, Gates JR, Dhuna A. Induction of speech arrest and counting errors with rapid-rate transcranial magnetic stimulation. Neurology 1991; 41(5): 697–702
CrossRef Pubmed Google scholar
[46]
Epstein CM, Lah JJ, Meador K, Weissman JD, Gaitan LE, Dihenia B. Optimum stimulus parameters for lateralized suppression of speech with magnetic brain stimulation. Neurology 1996; 47(6): 1590–1593
CrossRef Pubmed Google scholar
[47]
Lioumis P, Zhdanov A, Mäkelä N, Lehtinen H, Wilenius J, Neuvonen T, Hannula H, Deletis V, Picht T, Mäkelä JP. A novel approach for documenting naming errors induced by navigated transcranial magnetic stimulation. J Neurosci Methods 2012; 204(2): 349–354
CrossRef Pubmed Google scholar
[48]
Picht T, Krieg SM, Sollmann N, Rösler J, Niraula B, Neuvonen T, Savolainen P, Lioumis P, Mäkelä JP, Deletis V, Meyer B, Vajkoczy P, Ringel F. A comparison of language mapping by preoperative navigated transcranial magnetic stimulation and direct cortical stimulation during awake surgery. Neurosurgery 2013; 72(5): 808–819
CrossRef Pubmed Google scholar
[49]
Ille S, Sollmann N, Hauck T, Maurer S, Tanigawa N, Obermueller T, Negwer C, Droese D, Zimmer C, Meyer B, Ringel F, Krieg SM. Combined noninvasive language mapping by navigated transcranial magnetic stimulation and functional MRI and its comparison with direct cortical stimulation. J Neurosurg 2015; 123(1): 212–225
CrossRef Pubmed Google scholar
[50]
Tarapore PE, Findlay AM, Honma SM, Mizuiri D, Houde JF, Berger MS, Nagarajan SS. Language mapping with navigated repetitive TMS: proof of technique and validation. Neuroimage 2013; 82: 260–272
CrossRef Pubmed Google scholar
[51]
Lefaucheur JP. Stroke recovery can be enhanced by using repetitive transcranial magnetic stimulation (rTMS). Neurophysiol Clin 2006; 36(3): 105–115
CrossRef Pubmed Google scholar
[52]
Kapur N. Paradoxical functional facilitation in brain-behaviour research. A critical review. Brain 1996; 119(5): 1775–1790
CrossRef Pubmed Google scholar
[53]
Glasser MF, Rilling JK. DTI tractography of the human brain’s language pathways. Cereb Cortex 2008; 18(11): 2471–2482
CrossRef Pubmed Google scholar
[54]
Saur D, Kreher BW, Schnell S, Kümmerer D, Kellmeyer P, Vry MS, Umarova R, Musso M, Glauche V, Abel S, Huber W, Rijntjes M, Hennig J, Weiller C. Ventral and dorsal pathways for language. Proc Natl Acad Sci USA 2008; 105(46): 18035–18040
CrossRef Pubmed Google scholar
[55]
Wakana S, Caprihan A, Panzenboeck MM, Fallon JH, Perry M, Gollub RL, Hua K, Zhang J, Jiang H, Dubey P, Blitz A, van Zijl P, Mori S. Reproducibility of quantitative tractography methods applied to cerebral white matter. Neuroimage 2007; 36(3): 630–644
CrossRef Pubmed Google scholar
[56]
Catani M, Thiebaut de Schotten M. A diffusion tensor imaging tractography atlas for virtual in vivo dissections. Cortex 2008; 44(8): 1105–1132
CrossRef Pubmed Google scholar
[57]
Martino J, De Witt Hamer PC, Berger MS, Lawton MT, Arnold CM, de Lucas EM, Duffau H. Analysis of the subcomponents and cortical terminations of the perisylvian superior longitudinal fasciculus: a fiber dissection and DTI tractography study. Brain Struct Funct 2013; 218(1): 105–121
CrossRef Pubmed Google scholar
[58]
Wu JS, Zhou LF, Hong XN, Mao Y, Du GH. Role of diffusion tensor imaging in neuronavigation surgery of brain tumors involving pyramidal tracts. Chin J Surg (Zhonghua Wai Ke Za Zhi) 2003; 41(9): 662–666(in Chinese)
Pubmed
[59]
Zhu FP, Wu JS, Yao CJ, Lang LQ, Xu G, Zhang J, Sun S, Mao Y, Zhou LF. Diffusion tensor imaging correlates with subcortical stimulation for intraoperative pyramidal tract mapping: a preliminary study. Chin J Neurosurg (Zhonghua Shen Jing Wai Ke Za Zhi) 2010; 26(9): 795–799(in Chinese)
CrossRef Google scholar
[60]
Zhu FP, Wu JS, Yao CJ, Lang LQ, Xu G, Mao Y. Intraoperative neurophysiological monitoring in low-field MRI environment. Chin J Neurosurg (Zhonghua Shen Jing Wai Ke Za Zhi) 2010; 26(4): 303–305(in Chinese)
CrossRef Google scholar
[61]
Yuan Z. Combining independent component analysis and Granger causality to investigate brain network dynamics with fNIRS measurements. Biomed Opt Express 2013; 4(11): 2629–2643
CrossRef Pubmed Google scholar
[62]
Watanabe E, Maki A, Kawaguchi F, Takashiro K, Yamashita Y, Koizumi H, Mayanagi Y. Non-invasive assessment of language dominance with near-infrared spectroscopic mapping. Neurosci Lett 1998; 256(1): 49–52
CrossRef Pubmed Google scholar
[63]
Kennan RP, Kim D, Maki A, Koizumi H, Constable RT. Non-invasive assessment of language lateralization by transcranial near infrared optical topography and functional MRI. Hum Brain Mapp 2002; 16(3): 183–189
CrossRef Pubmed Google scholar
[64]
Watson NF, Dodrill C, Farrell D, Holmes MD, Miller JW. Determination of language dominance with near-infrared spectroscopy: comparison with the intracarotid amobarbital procedure. Seizure 2004; 13(6): 399–402
CrossRef Pubmed Google scholar
[65]
Peña M, Maki A, Kovacić D, Dehaene-Lambertz G, Koizumi H, Bouquet F, Mehler J. Sounds and silence: an optical topography study of language recognition at birth. Proc Natl Acad Sci USA 2003; 100(20): 11702–11705
CrossRef Pubmed Google scholar
[66]
Kotilahti K, Nissilä I, Näsi T, Lipiäinen L, Noponen T, Meriläinen P, Huotilainen M, Fellman V. Hemodynamic responses to speech and music in newborn infants. Hum Brain Mapp 2010; 31(4): 595–603
Pubmed
[67]
Qiu T, Hameed NUF, Peng Y, Wang S, Wu J, Zhou L. Functional near-infrared spectroscopy for intraoperative brain mapping. Neurophotonics 2019; 6(4): 045010
CrossRef Pubmed Google scholar
[68]
Lee CY, Liu YN, Tsai JL. The time course of contextual effects on visual word recognition. Front Psychol 2012; 3: 285
CrossRef Pubmed Google scholar
[69]
Beres AM. Time is of the essence: a review of electroencephalography (EEG) and event-related brain potentials (ERPs) in language research. Appl Psychophysiol Biofeedback 2017; 42(4): 247–255
CrossRef Pubmed Google scholar
[70]
Boudewyn MA, Long DL, Swaab TY. Graded expectations: predictive processing and the adjustment of expectations during spoken language comprehension. Cogn Affect Behav Neurosci 2015; 15(3): 607–624
CrossRef Pubmed Google scholar
[71]
Nieuwland MS. Do ‘early’ brain responses reveal word form prediction during language comprehension? A critical review. Neurosci Biobehav Rev 2019; 96: 367–400
CrossRef Pubmed Google scholar
[72]
Hagoort P, Wassenaar M, Brown CM. Syntax-related ERP-effects in Dutch. Brain Res Cogn Brain Res 2003; 16(1): 38–50
CrossRef Pubmed Google scholar
[73]
Brouwer H, Hoeks JC. A time and place for language comprehension: mapping the N400 and the P600 to a minimal cortical network. Front Hum Neurosci 2013; 7: 758
CrossRef Pubmed Google scholar
[74]
Farwell LA, Donchin E. Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. Electroencephalogr Clin Neurophysiol 1988; 70(6): 510–523
CrossRef Pubmed Google scholar
[75]
Krusienski DJ, Sellers EW, McFarland DJ, Vaughan TM, Wolpaw JR. Toward enhanced P300 speller performance. J Neurosci Methods 2008; 167(1): 15–21
CrossRef Pubmed Google scholar
[76]
Serby H, Yom-Tov E, Inbar GF. An improved P300-based brain-computer interface. IEEE Trans Neural Syst Rehabil Eng 2005; 13(1): 89–98
CrossRef Pubmed Google scholar
[77]
Zhang H, Guan C, Wang C. Asynchronous P300-based brain-computer interfaces: a computational approach with statistical models. IEEE Trans Biomed Eng 2008; 55(6): 1754–1763
CrossRef Pubmed Google scholar
[78]
See JJ, Lew TW, Kwek TK, Chin KJ, Wong MF, Liew QY, Lim SH, Ho HS, Chan Y, Loke GP, Yeo VS. Anaesthetic management of awake craniotomy for tumour resection. Ann Acad Med Singap 2007; 36(5): 319–325
Pubmed
[79]
Piccioni F, Fanzio M. Management of anesthesia in awake craniotomy. Minerva Anestesiol 2008; 74(7-8): 393–408
Pubmed
[80]
Bilotta F, Rosa G. ‘Anesthesia’ for awake neurosurgery. Curr Opin Anaesthesiol 2009; 22(5): 560–565
CrossRef Pubmed Google scholar
[81]
Hansen E, Seemann M, Zech N, Doenitz C, Luerding R, Brawanski A. Awake craniotomies without any sedation: the awake-awake-awake technique. Acta Neurochir (Wien) 2013; 155(8): 1417–1424
CrossRef Pubmed Google scholar
[82]
Dilmen OK, Akcil EF, Oguz A, Vehid H, Tunali Y. Comparison of conscious sedation and asleep-awake-asleep techniques for awake craniotomy. J Clin Neurosci 2017; 35: 30–34
CrossRef Pubmed Google scholar
[83]
Meng L, McDonagh DL, Berger MS, Gelb AW. Anesthesia for awake craniotomy: a how-to guide for the occasional practitioner. Can J Anaesth 2017; 64(5): 517–529
CrossRef Pubmed Google scholar
[84]
Jin L, Wu JS, Chen GB, Zhou LF. Unforgettable ups and downs of acupuncture anesthesia in China. World Neurosurg 2017; 102: 623–631
CrossRef Pubmed Google scholar
[85]
Wang Y, Fifer MS, Flinker A, Korzeniewska A, Cervenka MC, Anderson WS, Boatman-Reich DF, Crone NE. Spatial-temporal functional mapping of language at the bedside with electrocorticography. Neurology 2016; 86(13): 1181–1189
CrossRef Pubmed Google scholar
[86]
Arya R, Horn PS, Crone NE. ECoG high-gamma modulation versus electrical stimulation for presurgical language mapping. Epilepsy Behav 2018; 79: 26–33
CrossRef Pubmed Google scholar
[87]
Bouchard KE, Mesgarani N, Johnson K, Chang EF. Functional organization of human sensorimotor cortex for speech articulation. Nature 2013; 495(7441): 327–332
CrossRef Pubmed Google scholar
[88]
Dichter BK, Breshears JD, Leonard MK, Chang EF. The control of vocal pitch in human laryngeal motor cortex. Cell 2018; 174(1): 21–31.e29
CrossRef Pubmed Google scholar
[89]
Chang EF, Rieger JW, Johnson K, Berger MS, Barbaro NM, Knight RT. Categorical speech representation in human superior temporal gyrus. Nat Neurosci 2010; 13(11): 1428–1432
CrossRef Pubmed Google scholar
[90]
Mesgarani N, Chang EF. Selective cortical representation of attended speaker in multi-talker speech perception. Nature 2012; 485(7397): 233–236
CrossRef Pubmed Google scholar
[91]
Mesgarani N, Cheung C, Johnson K, Chang EF. Phonetic feature encoding in human superior temporal gyrus. Science 2014; 343(6174): 1006–1010
CrossRef Pubmed Google scholar
[92]
Tang C, Hamilton LS, Chang EF. Intonational speech prosody encoding in the human auditory cortex. Science 2017; 357(6353): 797–801
CrossRef Pubmed Google scholar
[93]
Colin Phillips KLS. Language and the Brain. McGraw-Hill Publishers, 2005
[94]
Anumanchipalli GK, Chartier J, Chang EF. Speech synthesis from neural decoding of spoken sentences. Nature 2019; 568(7753): 493–498
CrossRef Pubmed Google scholar
[95]
Collins FS. Reengineering translational science: the time is right. Sci Transl Med 2011; 3(90): 90cm17
CrossRef Pubmed Google scholar
[96]
Chiong W, Leonard MK, Chang EF. Neurosurgical patients as human research subjects: ethical considerations in intracranial electrophysiology research. Neurosurgery 2018; 83(1): 29–37
CrossRef Pubmed Google scholar

Acknowledgements

This work was supported by Shanghai Shenkang Hospital Development Center (No. SHDC12018114); Shanghai Rising-Star Program (No. 19QA1401700); Shanghai Young Talents Program (No. 2017YQ014); Shanghai Municipal Science and Technology Major Project (No. 2018SHZDZX01) and ZJLab; National Natural Science Foundation of China (No. 81701289).

Compliance with ethics guidelines

Peng Wang, Zehao Zhao, Linghao Bu, Nijiati Kudulaiti, Qiao Shan, Yuyao Zhou, N. U. Farrukh Hameed, Yangming Zhu, Lei Jin, Jie Zhang, Junfeng Lu, and Jinsong Wu declare that they have no financial conflicts of interest. This manuscript is a review article and does not involve a research protocol requiring approval by a relevant institutional review board or ethics committee.

Electronic Supplementary Material

Supplementary material is available in the online version of this article at https://doi.org/10.1007/s11684-020-0771-z and is accessible for authorized users.

RIGHTS & PERMISSIONS

2021 Higher Education Press
AI Summary AI Mindmap
PDF(2096 KB)

Accesses

Citations

Detail

Sections
Recommended

/