1
|
Silva AB, Littlejohn KT, Liu JR, Moses DA, Chang EF. The speech neuroprosthesis. Nat Rev Neurosci 2024:10.1038/s41583-024-00819-9. [PMID: 38745103 DOI: 10.1038/s41583-024-00819-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/12/2024] [Indexed: 05/16/2024]
Abstract
Loss of speech after paralysis is devastating, but circumventing motor-pathway injury by directly decoding speech from intact cortical activity has the potential to restore natural communication and self-expression. Recent discoveries have defined how key features of speech production are facilitated by the coordinated activity of vocal-tract articulatory and motor-planning cortical representations. In this Review, we highlight such progress and how it has led to successful speech decoding, first in individuals implanted with intracranial electrodes for clinical epilepsy monitoring and subsequently in individuals with paralysis as part of early feasibility clinical trials to restore speech. We discuss high-spatiotemporal-resolution neural interfaces and the adaptation of state-of-the-art speech computational algorithms that have driven rapid and substantial progress in decoding neural activity into text, audible speech, and facial movements. Although restoring natural speech is a long-term goal, speech neuroprostheses already have performance levels that surpass communication rates offered by current assistive-communication technology. Given this accelerated rate of progress in the field, we propose key evaluation metrics for speed and accuracy, among others, to help standardize across studies. We finish by highlighting several directions to more fully explore the multidimensional feature space of speech and language, which will continue to accelerate progress towards a clinically viable speech neuroprosthesis.
Collapse
Affiliation(s)
- Alexander B Silva
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA
| | - Kaylo T Littlejohn
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, USA
| | - Jessie R Liu
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA
| | - David A Moses
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA.
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA.
| |
Collapse
|
2
|
Roelofs A. Wernicke's functional neuroanatomy model of language turns 150: what became of its psychological reflex arcs? Brain Struct Funct 2024:10.1007/s00429-024-02785-5. [PMID: 38581582 DOI: 10.1007/s00429-024-02785-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 03/05/2024] [Indexed: 04/08/2024]
Abstract
Wernicke (Der aphasische Symptomencomplex: Eine psychologische Studie auf anatomischer Basis. Cohn und Weigert, Breslau. https://wellcomecollection.org/works/dwv5w9rw , 1874) proposed a model of the functional neuroanatomy of spoken word repetition, production, and comprehension. At the heart of this epoch-making model are psychological reflex arcs underpinned by fiber tracts connecting sensory to motor areas. Here, I evaluate the central assumption of psychological reflex arcs in light of what we have learned about language in the brain during the past 150 years. I first describe Wernicke's 1874 model and the evidence he presented for it. Next, I discuss his updates of the model published in 1886 and posthumously in 1906. Although the model had an enormous immediate impact, it lost influence after the First World War. Unresolved issues included the anatomical underpinnings of the psychological reflex arcs, the role of auditory images in word production, and the sufficiency of psychological reflex arcs, which was questioned by Wundt (Grundzüge der physiologischen Psychologie. Engelmann, Leipzig. http://vlp.mpiwg-berlin.mpg.de/references?id=lit46 , 1874; Grundzüge der physiologischen Psychologie (Vol. 1, 5th ed.). Engelmann, Leipzig. http://vlp.mpiwg-berlin.mpg.de/references?id=lit806 , 1902). After a long dormant period, Wernicke's model was revived by Geschwind (Science 170:940-944. https://doi.org/10.1126/science.170.3961.940 , 1970; Selected papers on language and the brain. Reidel, Dordrecht, 1974), who proposed a version of it that differed in several important respects from Wernicke's original. Finally, I describe how new evidence from modern research has led to a novel view on language in the brain, supplementing contemporary equivalents of psychological reflex arcs by other mechanisms such as attentional control and assuming different neuroanatomical underpinnings. In support of this novel view, I report new analyses of patient data and computer simulations using the WEAVER++/ARC model (Roelofs 2014, 2022) that incorporates attentional control and integrates the new evidence.
Collapse
Affiliation(s)
- Ardi Roelofs
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognition, Radboud University, Thomas van Aquinostraat 4, 6525 GD, Nijmegen, The Netherlands.
| |
Collapse
|
3
|
Levy DF, Entrup JL, Schneck SM, Onuscheck CF, Rahman M, Kasdan A, Casilio M, Willey E, Davis LT, de Riesthal M, Kirshner HS, Wilson SM. Multivariate lesion symptom mapping for predicting trajectories of recovery from aphasia. Brain Commun 2024; 6:fcae024. [PMID: 38370445 PMCID: PMC10873140 DOI: 10.1093/braincomms/fcae024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 12/05/2023] [Accepted: 01/30/2024] [Indexed: 02/20/2024] Open
Abstract
Individuals with post-stroke aphasia tend to recover their language to some extent; however, it remains challenging to reliably predict the nature and extent of recovery that will occur in the long term. The aim of this study was to quantitatively predict language outcomes in the first year of recovery from aphasia across multiple domains of language and at multiple timepoints post-stroke. We recruited 217 patients with aphasia following acute left hemisphere ischaemic or haemorrhagic stroke and evaluated their speech and language function using the Quick Aphasia Battery acutely and then acquired longitudinal follow-up data at up to three timepoints post-stroke: 1 month (n = 102), 3 months (n = 98) and 1 year (n = 74). We used support vector regression to predict language outcomes at each timepoint using acute clinical imaging data, demographic variables and initial aphasia severity as input. We found that ∼60% of the variance in long-term (1 year) aphasia severity could be predicted using these models, with detailed information about lesion location importantly contributing to these predictions. Predictions at the 1- and 3-month timepoints were somewhat less accurate based on lesion location alone, but reached comparable accuracy to predictions at the 1-year timepoint when initial aphasia severity was included in the models. Specific subdomains of language besides overall severity were predicted with varying but often similar degrees of accuracy. Our findings demonstrate the feasibility of using support vector regression models with leave-one-out cross-validation to make personalized predictions about long-term recovery from aphasia and provide a valuable neuroanatomical baseline upon which to build future models incorporating information beyond neuroanatomical and demographic predictors.
Collapse
Affiliation(s)
- Deborah F Levy
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Jillian L Entrup
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Sarah M Schneck
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Caitlin F Onuscheck
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Maysaa Rahman
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Anna Kasdan
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Marianne Casilio
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Emma Willey
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - L Taylor Davis
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Michael de Riesthal
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Howard S Kirshner
- Vanderbilt Stroke and Cerebrovascular Center, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Stephen M Wilson
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- School of Health and Rehabilitation Sciences, University of Queensland, Brisbane, QLD 4072, Australia
| |
Collapse
|
4
|
Lakhani DA, Sabsevitz DS, Chaichana KL, Quiñones-Hinojosa A, Middlebrooks EH. Current State of Functional MRI in the Presurgical Planning of Brain Tumors. Radiol Imaging Cancer 2023; 5:e230078. [PMID: 37861422 DOI: 10.1148/rycan.230078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2023]
Abstract
Surgical resection of brain tumors is challenging because of the delicate balance between maximizing tumor removal and preserving vital brain functions. Functional MRI (fMRI) offers noninvasive preoperative mapping of widely distributed brain areas and is increasingly used in presurgical functional mapping. However, its impact on survival and functional outcomes is still not well-supported by evidence. Task-based fMRI (tb-fMRI) maps blood oxygen level-dependent (BOLD) signal changes during specific tasks, while resting-state fMRI (rs-fMRI) examines spontaneous brain activity. rs-fMRI may be useful for patients who cannot perform tasks, but its reliability is affected by tumor-induced changes, challenges in data processing, and noise. Validation studies comparing fMRI with direct cortical stimulation (DCS) show variable concordance, particularly for cognitive functions such as language; however, concordance for tb-fMRI is generally greater than that for rs-fMRI. Preoperative fMRI, in combination with MRI tractography and intraoperative DCS, may result in improved survival and extent of resection and reduced functional deficits. fMRI has the potential to guide surgical planning and help identify targets for intraoperative mapping, but there is currently limited prospective evidence of its impact on patient outcomes. This review describes the current state of fMRI for preoperative assessment in patients undergoing brain tumor resection. Keywords: MR-Functional Imaging, CNS, Brain/Brain Stem, Anatomy, Oncology, Functional MRI, Functional Anatomy, Task-based, Resting State, Surgical Planning, Brain Tumor © RSNA, 2023.
Collapse
Affiliation(s)
- Dhairya A Lakhani
- From the Department of Radiology, West Virginia University, Morgantown, WV (D.A.L.); and Departments of Psychiatry and Psychology (D.S.S.), Neurosurgery (K.L.C., A.Q.H., E.H.M.), and Radiology (E.H.M.), Mayo Clinic Florida, 4500 San Pablo Rd, Jacksonville, FL 32224
| | - David S Sabsevitz
- From the Department of Radiology, West Virginia University, Morgantown, WV (D.A.L.); and Departments of Psychiatry and Psychology (D.S.S.), Neurosurgery (K.L.C., A.Q.H., E.H.M.), and Radiology (E.H.M.), Mayo Clinic Florida, 4500 San Pablo Rd, Jacksonville, FL 32224
| | - Kaisorn L Chaichana
- From the Department of Radiology, West Virginia University, Morgantown, WV (D.A.L.); and Departments of Psychiatry and Psychology (D.S.S.), Neurosurgery (K.L.C., A.Q.H., E.H.M.), and Radiology (E.H.M.), Mayo Clinic Florida, 4500 San Pablo Rd, Jacksonville, FL 32224
| | - Alfredo Quiñones-Hinojosa
- From the Department of Radiology, West Virginia University, Morgantown, WV (D.A.L.); and Departments of Psychiatry and Psychology (D.S.S.), Neurosurgery (K.L.C., A.Q.H., E.H.M.), and Radiology (E.H.M.), Mayo Clinic Florida, 4500 San Pablo Rd, Jacksonville, FL 32224
| | - Erik H Middlebrooks
- From the Department of Radiology, West Virginia University, Morgantown, WV (D.A.L.); and Departments of Psychiatry and Psychology (D.S.S.), Neurosurgery (K.L.C., A.Q.H., E.H.M.), and Radiology (E.H.M.), Mayo Clinic Florida, 4500 San Pablo Rd, Jacksonville, FL 32224
| |
Collapse
|
5
|
Thomas G, McMahon KL, Finch E, Copland DA. Interindividual variability and consistency of language mapping paradigms for presurgical use. BRAIN AND LANGUAGE 2023; 243:105299. [PMID: 37413742 DOI: 10.1016/j.bandl.2023.105299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 04/08/2023] [Accepted: 06/21/2023] [Indexed: 07/08/2023]
Abstract
Most functional MRI studies of language processing have focussed on group-level inference, but for clinical use, the aim is to predict outcomes at an individual patient level. This requires being able to identify atypical activation and understand how differences relate to language outcomes. A language mapping paradigm that selectively activates left hemisphere language regions in healthy individuals allows atypical activation in a patient to be more easily identified. We investigated the interindividual variability and consistency of language activation in 12 healthy participants using three tasks-verb generation, responsive naming, and sentence comprehension-for future presurgical use. Responsive naming produced the most consistent left-lateralised activation across participants in frontal and temporal regions that postsurgical voxel-based lesion-symptom mapping studies suggest are most critical for language outcomes. Studies with a long-term clinical aim of predicting language outcomes in neurosurgical patients and stroke patients should first establish paradigm validity at an individual level in healthy participants.
Collapse
Affiliation(s)
- Georgia Thomas
- School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, Australia; Queensland Aphasia Research Centre, School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, Australia.
| | - Katie L McMahon
- School of Clinical Sciences, Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, Australia; Herston Imaging Research Facility, The University of Queensland, Brisbane, Australia
| | - Emma Finch
- School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, Australia; Research and Innovation, West Moreton Health, Ipswich, Australia; Speech Pathology Department, Princess Alexandra Hospital, Brisbane, Australia
| | - David A Copland
- School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, Australia; Queensland Aphasia Research Centre, School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, Australia; Surgical Treatment and Rehabilitation Service (STARS) Education and Research Alliance, The University of Queensland and Metro North Health, Queensland, Australia
| |
Collapse
|
6
|
Willett FR, Kunz EM, Fan C, Avansino DT, Wilson GH, Choi EY, Kamdar F, Glasser MF, Hochberg LR, Druckmann S, Shenoy KV, Henderson JM. A high-performance speech neuroprosthesis. Nature 2023; 620:1031-1036. [PMID: 37612500 PMCID: PMC10468393 DOI: 10.1038/s41586-023-06377-x] [Citation(s) in RCA: 35] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Accepted: 06/27/2023] [Indexed: 08/25/2023]
Abstract
Speech brain-computer interfaces (BCIs) have the potential to restore rapid communication to people with paralysis by decoding neural activity evoked by attempted speech into text1,2 or sound3,4. Early demonstrations, although promising, have not yet achieved accuracies sufficiently high for communication of unconstrained sentences from a large vocabulary1-7. Here we demonstrate a speech-to-text BCI that records spiking activity from intracortical microelectrode arrays. Enabled by these high-resolution recordings, our study participant-who can no longer speak intelligibly owing to amyotrophic lateral sclerosis-achieved a 9.1% word error rate on a 50-word vocabulary (2.7 times fewer errors than the previous state-of-the-art speech BCI2) and a 23.8% word error rate on a 125,000-word vocabulary (the first successful demonstration, to our knowledge, of large-vocabulary decoding). Our participant's attempted speech was decoded at 62 words per minute, which is 3.4 times as fast as the previous record8 and begins to approach the speed of natural conversation (160 words per minute9). Finally, we highlight two aspects of the neural code for speech that are encouraging for speech BCIs: spatially intermixed tuning to speech articulators that makes accurate decoding possible from only a small region of cortex, and a detailed articulatory representation of phonemes that persists years after paralysis. These results show a feasible path forward for restoring rapid communication to people with paralysis who can no longer speak.
Collapse
Affiliation(s)
- Francis R Willett
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA.
| | - Erin M Kunz
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Chaofei Fan
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Donald T Avansino
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
| | - Guy H Wilson
- Department of Neuroscience, Stanford University, Stanford, CA, USA
| | - Eun Young Choi
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - Foram Kamdar
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - Matthew F Glasser
- Department of Neuroscience, Washington University in St. Louis, St. Louis, MO, USA
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Leigh R Hochberg
- VA RR&D Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Providence VA Medical Center, Providence, RI, USA
- School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI, USA
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Shaul Druckmann
- Department of Neurobiology, Stanford University, Stanford, CA, USA
| | - Krishna V Shenoy
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Neurobiology, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Bio-X Program, Stanford University, Stanford, CA, USA
| | - Jaimie M Henderson
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| |
Collapse
|
7
|
McCarty MJ, Murphy E, Scherschligt X, Woolnough O, Morse CW, Snyder K, Mahon BZ, Tandon N. Intraoperative cortical localization of music and language reveals signatures of structural complexity in posterior temporal cortex. iScience 2023; 26:107223. [PMID: 37485361 PMCID: PMC10362292 DOI: 10.1016/j.isci.2023.107223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 06/01/2023] [Accepted: 06/22/2023] [Indexed: 07/25/2023] Open
Abstract
Language and music involve the productive combination of basic units into structures. It remains unclear whether brain regions sensitive to linguistic and musical structure are co-localized. We report an intraoperative awake craniotomy in which a left-hemispheric language-dominant professional musician underwent cortical stimulation mapping (CSM) and electrocorticography of music and language perception and production during repetition tasks. Musical sequences were melodic or amelodic, and differed in algorithmic compressibility (Lempel-Ziv complexity). Auditory recordings of sentences differed in syntactic complexity (single vs. multiple phrasal embeddings). CSM of posterior superior temporal gyrus (pSTG) disrupted music perception and production, along with speech production. pSTG and posterior middle temporal gyrus (pMTG) activated for language and music (broadband gamma; 70-150 Hz). pMTG activity was modulated by musical complexity, while pSTG activity was modulated by syntactic complexity. This points to shared resources for music and language comprehension, but distinct neural signatures for the processing of domain-specific structural features.
Collapse
Affiliation(s)
- Meredith J. McCarty
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Elliot Murphy
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Xavier Scherschligt
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Oscar Woolnough
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Cale W. Morse
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Kathryn Snyder
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Bradford Z. Mahon
- Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Nitin Tandon
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Memorial Hermann Hospital, Texas Medical Center, Houston, TX 77030, USA
| |
Collapse
|
8
|
Shalom M, Mehkri Y, Sharaf R, Reilly T, Gendreau J. Letter: Planning Brain Tumor Resection Using a Probabilistic Atlas of Cortical and Subcortical Structures Critical for Functional Processing: A Proof of Concept. Oper Neurosurg (Hagerstown) 2023; 24:e244-e245. [PMID: 36715971 DOI: 10.1227/ons.0000000000000596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 10/27/2022] [Indexed: 01/31/2023] Open
Affiliation(s)
- Moshe Shalom
- Tel Aviv University, Sackler Faculty of Medicine, Tel Aviv, Israel
| | - Yusuf Mehkri
- College of Medicine, University of Florida, Gainesville, FL, USA
| | - Ramy Sharaf
- College of Medicine, University of Florida, Gainesville, FL, USA
| | - Thomas Reilly
- College of Medicine, University of Florida, Gainesville, FL, USA
| | - Julian Gendreau
- Department of Biomedical Engineering, Johns Hopkins Whiting School of Engineering, Baltimore, MD, USA
| |
Collapse
|
9
|
Sarubbo S, Venturini M, Avesani P, Duffau H. In Reply: Planning Brain Tumor Resection Using a Probabilistic Atlas of Cortical and Subcortical Structures Critical for Functional Processing: A Proof of Concept. Oper Neurosurg (Hagerstown) 2023; 24:e246-e247. [PMID: 36716037 DOI: 10.1227/ons.0000000000000597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 10/27/2022] [Indexed: 01/31/2023] Open
Affiliation(s)
- Silvio Sarubbo
- Department of Neurosurgery, Azienda Provinciale peri Servizi Sanitari (APSS), "S. Chiara" Hospital, Trento, Italy
| | - Martina Venturini
- Department of Neurosurgery, Azienda Provinciale peri Servizi Sanitari (APSS), "S. Chiara" Hospital, Trento, Italy
| | - Paolo Avesani
- Neuroinformatic Laboratory, Bruno Kessler Foundation, Trento Italy
| | - Hugues Duffau
- Department of Neurosurgery, Gui de Chauliac Hospital, University of Montpellier, France
- Institute of Functional Genomics, University of Montpellier, Montpellier, France
| |
Collapse
|
10
|
Silva AB, Liu JR, Zhao L, Levy DF, Scott TL, Chang EF. A Neurosurgical Functional Dissection of the Middle Precentral Gyrus during Speech Production. J Neurosci 2022; 42:8416-8426. [PMID: 36351829 PMCID: PMC9665919 DOI: 10.1523/jneurosci.1614-22.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 08/30/2022] [Indexed: 11/17/2022] Open
Abstract
Classical models have traditionally focused on the left posterior inferior frontal gyrus (Broca's area) as a key region for motor planning of speech production. However, converging evidence suggests that it is not critical for either speech motor planning or execution. Alternative cortical areas supporting high-level speech motor planning have yet to be defined. In this review, we focus on the precentral gyrus, whose role in speech production is often thought to be limited to lower-level articulatory muscle control. In particular, we highlight neurosurgical investigations that have shed light on a cortical region anatomically located near the midpoint of the precentral gyrus, hence called the middle precentral gyrus (midPrCG). The midPrCG is functionally located between dorsal hand and ventral orofacial cortical representations and exhibits unique sensorimotor and multisensory functions relevant for speech processing. This includes motor control of the larynx, auditory processing, as well as a role in reading and writing. Furthermore, direct electrical stimulation of midPrCG can evoke complex movements, such as vocalization, and selective injury can cause deficits in verbal fluency, such as pure apraxia of speech. Based on these findings, we propose that midPrCG is essential to phonological-motoric aspects of speech production, especially syllabic-level speech sequencing, a role traditionally ascribed to Broca's area. The midPrCG is a cortical brain area that should be included in contemporary models of speech production with a unique role in speech motor planning and execution.
Collapse
Affiliation(s)
- Alexander B Silva
- Department of Neurological Surgery, University of California, San Francisco, California, 94158
- Weill Institute for Neurosciences, University of California, San Francisco, California, 94158
- Medical Scientist Training Program, University of California, San Francisco, California, 94158
- Graduate Program in Bioengineering, University of California, Berkeley, California 94720, & University of California, San Francisco, California, 94158
| | - Jessie R Liu
- Department of Neurological Surgery, University of California, San Francisco, California, 94158
- Weill Institute for Neurosciences, University of California, San Francisco, California, 94158
- Graduate Program in Bioengineering, University of California, Berkeley, California 94720, & University of California, San Francisco, California, 94158
| | - Lingyun Zhao
- Department of Neurological Surgery, University of California, San Francisco, California, 94158
- Weill Institute for Neurosciences, University of California, San Francisco, California, 94158
| | - Deborah F Levy
- Department of Neurological Surgery, University of California, San Francisco, California, 94158
- Weill Institute for Neurosciences, University of California, San Francisco, California, 94158
| | - Terri L Scott
- Department of Neurological Surgery, University of California, San Francisco, California, 94158
- Weill Institute for Neurosciences, University of California, San Francisco, California, 94158
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, California, 94158
- Weill Institute for Neurosciences, University of California, San Francisco, California, 94158
- Graduate Program in Bioengineering, University of California, Berkeley, California 94720, & University of California, San Francisco, California, 94158
| |
Collapse
|