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Silva AB, Liu JR, Metzger SL, Bhaya-Grossman I, Dougherty ME, Seaton MP, Littlejohn KT, Tu-Chan A, Ganguly K, Moses DA, Chang EF. A bilingual speech neuroprosthesis driven by cortical articulatory representations shared between languages. Nat Biomed Eng 2024:10.1038/s41551-024-01207-5. [PMID: 38769157 DOI: 10.1038/s41551-024-01207-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 04/01/2024] [Indexed: 05/22/2024]
Abstract
Advancements in decoding speech from brain activity have focused on decoding a single language. Hence, the extent to which bilingual speech production relies on unique or shared cortical activity across languages has remained unclear. Here, we leveraged electrocorticography, along with deep-learning and statistical natural-language models of English and Spanish, to record and decode activity from speech-motor cortex of a Spanish-English bilingual with vocal-tract and limb paralysis into sentences in either language. This was achieved without requiring the participant to manually specify the target language. Decoding models relied on shared vocal-tract articulatory representations across languages, which allowed us to build a syllable classifier that generalized across a shared set of English and Spanish syllables. Transfer learning expedited training of the bilingual decoder by enabling neural data recorded in one language to improve decoding in the other language. Overall, our findings suggest shared cortical articulatory representations that persist after paralysis and enable the decoding of multiple languages without the need to train separate language-specific decoders.
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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
- University of California, Berkeley - University of California, San Francisco Graduate Program in Bioengineering, 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
- University of California, Berkeley - University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA, USA
| | - Sean L Metzger
- 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
- University of California, Berkeley - University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA, USA
| | - Ilina Bhaya-Grossman
- 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
- University of California, Berkeley - University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA, USA
| | - Maximilian E Dougherty
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Margaret P Seaton
- Department of Neurological Surgery, 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
| | - Adelyn Tu-Chan
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Karunesh Ganguly
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, 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.
- University of California, Berkeley - University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA, USA.
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Pasquini L, Jenabi M, Graham M, Peck KK, Schöder H, Holodny AI, Krebs S. Tumors Affect the Metabolic Connectivity of the Human Brain Measured by 18F-FDG PET. Clin Nucl Med 2024:00003072-990000000-01095. [PMID: 38693648 DOI: 10.1097/rlu.0000000000005227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2024]
Abstract
PURPOSE 18F-FDG PET captures the relationship between glucose metabolism and synaptic activity, allowing for modeling brain function through metabolic connectivity. We investigated tumor-induced modifications of brain metabolic connectivity. PATIENTS AND METHODS Forty-three patients with left hemispheric tumors and 18F-FDG PET/MRI were retrospectively recruited. We included 37 healthy controls (HCs) from the database CERMEP-IDB-MRXFDG. We analyzed the whole brain and right versus left hemispheres connectivity in patients and HC, frontal versus temporal tumors, active tumors versus radiation necrosis, and patients with high Karnofsky performance score (KPS = 100) versus low KPS (KPS < 70). Results were compared with 2-sided t test (P < 0.05). RESULTS Twenty high-grade glioma, 4 low-grade glioma, and 19 metastases were included. The patients' whole-brain network displayed lower connectivity metrics compared with HC (P < 0.001), except assortativity and betweenness centrality (P = 0.001). The patients' left hemispheres showed decreased similarity, and lower connectivity metrics compared with the right (P < 0.01), with the exception of betweenness centrality (P = 0.002). HC did not show significant hemispheric differences. Frontal tumors showed higher connectivity metrics (P < 0.001) than temporal tumors, but lower betweenness centrality (P = 4.5-7). Patients with high KPS showed higher distance local efficiency (P = 0.01), rich club coefficient (P = 0.0048), clustering coefficient (P = 0.00032), betweenness centrality (P = 0.008), and similarity (P = 0.0027) compared with low KPS. Patients with active tumor(s) (14/43) demonstrated significantly lower connectivity metrics compared with necroses. CONCLUSIONS Tumors cause reorganization of metabolic brain networks, characterized by formation of new connections and decreased centrality. Patients with frontal tumors retained a more efficient, centralized, and segregated network than patients with temporal tumors. Stronger metabolic connectivity was associated with higher KPS.
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Affiliation(s)
| | | | | | - Kyung K Peck
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center
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Pasquini L, Peck KK, Jenabi M, Holodny A. Functional MRI in Neuro-Oncology: State of the Art and Future Directions. Radiology 2023; 308:e222028. [PMID: 37668519 PMCID: PMC10546288 DOI: 10.1148/radiol.222028] [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: 08/10/2022] [Revised: 05/15/2023] [Accepted: 05/26/2023] [Indexed: 09/06/2023]
Abstract
Since its discovery in the early 1990s, functional MRI (fMRI) has been used to study human brain function. One well-established application of fMRI in the clinical setting is the neurosurgical planning of patients with brain tumors near eloquent cortical areas. Clinical fMRI aims to preoperatively identify eloquent cortices that serve essential functions in daily life, such as hand movement and language. The primary goal of neurosurgery is to maximize tumor resection while sparing eloquent cortices adjacent to the tumor. When a lesion presents in the vicinity of an eloquent cortex, surgeons may use fMRI to plan their best surgical approach by determining the proximity of the lesion to regions of activation, providing guidance for awake brain surgery and intraoperative brain mapping. The acquisition of fMRI requires patient preparation prior to imaging, determination of functional paradigms, monitoring of patient performance, and both processing and analysis of images. Interpretation of fMRI maps requires a strong understanding of functional neuroanatomy and familiarity with the technical limitations frequently present in brain tumor imaging, including neurovascular uncoupling, patient compliance, and data analysis. This review discusses clinical fMRI in neuro-oncology, relevant ongoing research topics, and prospective future developments in this exciting discipline.
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Affiliation(s)
- Luca Pasquini
- From the Neuroradiology Service, Department of Radiology (L.P.,
K.K.P., M.J., A.H.), Department of Medical Physics (K.K.P.), and Brain Tumor
Center (A.H.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York,
NY 10065; Neuroradiology Unit, NESMOS Department, Sant'Andrea Hospital,
La Sapienza University, Rome, Italy (L.P.); Department of Radiology, Weill
Medical College of Cornell University, New York, NY (A.H.); and Department of
Neuroscience, Weill Cornell Medicine Graduate School of Medical Sciences, New
York, NY (A.H.)
| | - Kyung K. Peck
- From the Neuroradiology Service, Department of Radiology (L.P.,
K.K.P., M.J., A.H.), Department of Medical Physics (K.K.P.), and Brain Tumor
Center (A.H.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York,
NY 10065; Neuroradiology Unit, NESMOS Department, Sant'Andrea Hospital,
La Sapienza University, Rome, Italy (L.P.); Department of Radiology, Weill
Medical College of Cornell University, New York, NY (A.H.); and Department of
Neuroscience, Weill Cornell Medicine Graduate School of Medical Sciences, New
York, NY (A.H.)
| | - Mehrnaz Jenabi
- From the Neuroradiology Service, Department of Radiology (L.P.,
K.K.P., M.J., A.H.), Department of Medical Physics (K.K.P.), and Brain Tumor
Center (A.H.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York,
NY 10065; Neuroradiology Unit, NESMOS Department, Sant'Andrea Hospital,
La Sapienza University, Rome, Italy (L.P.); Department of Radiology, Weill
Medical College of Cornell University, New York, NY (A.H.); and Department of
Neuroscience, Weill Cornell Medicine Graduate School of Medical Sciences, New
York, NY (A.H.)
| | - Andrei Holodny
- From the Neuroradiology Service, Department of Radiology (L.P.,
K.K.P., M.J., A.H.), Department of Medical Physics (K.K.P.), and Brain Tumor
Center (A.H.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York,
NY 10065; Neuroradiology Unit, NESMOS Department, Sant'Andrea Hospital,
La Sapienza University, Rome, Italy (L.P.); Department of Radiology, Weill
Medical College of Cornell University, New York, NY (A.H.); and Department of
Neuroscience, Weill Cornell Medicine Graduate School of Medical Sciences, New
York, NY (A.H.)
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Pasquini L, Jenabi M, Yildirim O, Silveira P, Peck KK, Holodny AI. Brain Functional Connectivity in Low- and High-Grade Gliomas: Differences in Network Dynamics Associated with Tumor Grade and Location. Cancers (Basel) 2022; 14:cancers14143327. [PMID: 35884387 PMCID: PMC9324249 DOI: 10.3390/cancers14143327] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 07/06/2022] [Accepted: 07/07/2022] [Indexed: 12/27/2022] Open
Abstract
Brain tumors lead to modifications of brain networks. Graph theory plays an important role in clarifying the principles of brain connectivity. Our objective was to investigate network modifications related to tumor grade and location using resting-state functional magnetic resonance imaging (fMRI) and graph theory. We retrospectively studied 30 low-grade (LGG), 30 high-grade (HGG) left-hemispheric glioma patients and 20 healthy controls (HC) with rs-fMRI. Tumor location was labeled as: frontal, temporal, parietal, insular or occipital. We collected patients’ clinical data from records. We analyzed whole-brain and hemispheric networks in all patients and HC. Subsequently, we studied lobar networks in subgroups of patients divided by tumor location. Seven graph-theoretical metrics were calculated (FDR p < 0.05). Connectograms were computed for significant nodes. The two-tailed Student t-test or Mann−Whitney U-test (p < 0.05) were used to compare graph metrics and clinical data. The hemispheric network analysis showed increased ipsilateral connectivity for LGG (global efficiency p = 0.03) and decreased contralateral connectivity for HGG (degree/cost p = 0.028). Frontal and temporal tumors showed bilateral modifications; parietal and insular tumors showed only local effects. Temporal tumors led to a bilateral decrease in all graph metrics. Tumor grade and location influence the pattern of network reorganization. LGG may show more favorable network changes than HGG, reflecting fewer clinical deficits.
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Affiliation(s)
- Luca Pasquini
- Neuroradiology Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (M.J.); (O.Y.); (K.K.P.); (A.I.H.)
- Neuroradiology Unit, NESMOS Department, Sant’Andrea Hospital, La Sapienza University, 00189 Rome, Italy
- Correspondence:
| | - Mehrnaz Jenabi
- Neuroradiology Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (M.J.); (O.Y.); (K.K.P.); (A.I.H.)
| | - Onur Yildirim
- Neuroradiology Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (M.J.); (O.Y.); (K.K.P.); (A.I.H.)
| | - Patrick Silveira
- Molecular Imaging and Therapy Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA;
| | - Kyung K. Peck
- Neuroradiology Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (M.J.); (O.Y.); (K.K.P.); (A.I.H.)
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Andrei I. Holodny
- Neuroradiology Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (M.J.); (O.Y.); (K.K.P.); (A.I.H.)
- Brain Tumor Center, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
- Department of Radiology, Weill Medical College of Cornell University, New York, NY 10065, USA
- Department of Neuroscience, Weill-Cornell Graduate School of the Medical Sciences, New York, NY 10065, USA
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Bottino F, Lucignani M, Pasquini L, Mastrogiovanni M, Gazzellini S, Ritrovato M, Longo D, Figà-Talamanca L, Rossi Espagnet MC, Napolitano A. Spatial Stability of Functional Networks: A Measure to Assess the Robustness of Graph-Theoretical Metrics to Spatial Errors Related to Brain Parcellation. Front Neurosci 2022; 15:736524. [PMID: 35250432 PMCID: PMC8894326 DOI: 10.3389/fnins.2021.736524] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 12/28/2021] [Indexed: 12/12/2022] Open
Abstract
There is growing interest in studying human brain connectivity and in modelling the brain functional structure as a network. Brain network creation requires parcellation of the cerebral cortex to define nodes. Parcellation might be affected by possible errors due to inter- and intra-subject variability as a consequence of brain structural and physiological characteristics and shape variations related to ageing and diseases, acquisition noise, and misregistration. These errors could induce a knock-on effect on network measure variability. The aim of this study was to investigate spatial stability, a measure of functional connectivity variations induced by parcellation errors. We simulated parcellation variability with random small spatial changes and evaluated its effects on twenty-seven graph-theoretical measures. The study included subjects from three public online datasets. Two brain parcellations were performed using FreeSurfer with geometric atlases. Starting from these, 100 new parcellations were created by increasing the area of 30% of parcels, reducing the area of neighbour parcels, with a rearrangement of vertices. fMRI data were filtered with linear regression, CompCor, and motion correction. Adjacency matrices were constructed with 0.1, 0.2, 0.3, and 0.4 thresholds. Differences in spatial stability between datasets, atlases, and threshold were evaluated. The higher spatial stability resulted for Characteristic-path-length, Density, Transitivity, and Closeness-centrality, and the lower spatial stability resulted for Bonacich and Katz. Multivariate analysis showed a significant effect of atlas, datasets, and thresholds. Katz and Bonacich centrality, which was subject to larger variations, can be considered an unconventional graph measure, poorly implemented in the clinical field and not yet investigated for reliability assessment. Spatial stability (SS) is affected by threshold, and it decreases with increasing threshold for several measures. Moreover, SS seems to depend on atlas choice and scanning parameters. Our study highlights the importance of paying close attention to possible parcellation-related spatial errors, which may affect the reliability of functional connectivity measures.
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Affiliation(s)
- Francesca Bottino
- Medical Physics Department, Bambino Gesù Children’s Hospital IRCCS, Rome, Italy
| | - Martina Lucignani
- Medical Physics Department, Bambino Gesù Children’s Hospital IRCCS, Rome, Italy
| | - Luca Pasquini
- Neuroradiology Unit, NESMOS Department, Sant’Andrea Hospital, La Sapienza University, Rome, Italy
- Neuroradiology Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | | | - Simone Gazzellini
- Neuroscience and Neurorehabilitation Department, Bambino Gesù Children’s Hospital – IRCCS, Rome, Italy
| | - Matteo Ritrovato
- Health Technology and Safety Research Unit, Bambino Gesù Children’s Hospital – IRCCS, Rome, Italy
| | - Daniela Longo
- Neuroradiology Unit, Imaging Department, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy
| | - Lorenzo Figà-Talamanca
- Neuroradiology Unit, Imaging Department, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy
| | - Maria Camilla Rossi Espagnet
- Neuroradiology Unit, Imaging Department, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy
- NESMOS, Neuroradiology Department, S. Andrea Hospital Sapienza Rome University, Rome, Italy
| | - Antonio Napolitano
- Medical Physics Department, Bambino Gesù Children’s Hospital IRCCS, Rome, Italy
- *Correspondence: Antonio Napolitano,
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Pasquini L, Di Napoli A, Rossi-Espagnet MC, Visconti E, Napolitano A, Romano A, Bozzao A, Peck KK, Holodny AI. Understanding Language Reorganization With Neuroimaging: How Language Adapts to Different Focal Lesions and Insights Into Clinical Applications. Front Hum Neurosci 2022; 16:747215. [PMID: 35250510 PMCID: PMC8895248 DOI: 10.3389/fnhum.2022.747215] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 01/18/2022] [Indexed: 12/13/2022] Open
Abstract
When the language-dominant hemisphere is damaged by a focal lesion, the brain may reorganize the language network through functional and structural changes known as adaptive plasticity. Adaptive plasticity is documented for triggers including ischemic, tumoral, and epileptic focal lesions, with effects in clinical practice. Many questions remain regarding language plasticity. Different lesions may induce different patterns of reorganization depending on pathologic features, location in the brain, and timing of onset. Neuroimaging provides insights into language plasticity due to its non-invasiveness, ability to image the whole brain, and large-scale implementation. This review provides an overview of language plasticity on MRI with insights for patient care. First, we describe the structural and functional language network as depicted by neuroimaging. Second, we explore language reorganization triggered by stroke, brain tumors, and epileptic lesions and analyze applications in clinical diagnosis and treatment planning. By comparing different focal lesions, we investigate determinants of language plasticity including lesion location and timing of onset, longitudinal evolution of reorganization, and the relationship between structural and functional changes.
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Affiliation(s)
- Luca Pasquini
- Neuroradiology Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
- Neuroradiology Unit, NESMOS Department, Sant’Andrea Hospital, La Sapienza University, Rome, Italy
| | - Alberto Di Napoli
- Neuroradiology Unit, NESMOS Department, Sant’Andrea Hospital, La Sapienza University, Rome, Italy
- Radiology Department, Castelli Hospital, Rome, Italy
- IRCCS Fondazione Santa Lucia, Rome, Italy
| | | | - Emiliano Visconti
- Neuroradiology Unit, Cesena Surgery and Trauma Department, M. Bufalini Hospital, AUSL Romagna, Cesena, Italy
| | - Antonio Napolitano
- Medical Physics Department, Bambino Gesù Children’s Hospital, Rome, Italy
| | - Andrea Romano
- Neuroradiology Unit, NESMOS Department, Sant’Andrea Hospital, La Sapienza University, Rome, Italy
| | - Alessandro Bozzao
- Neuroradiology Unit, NESMOS Department, Sant’Andrea Hospital, La Sapienza University, Rome, Italy
| | - Kyung K. Peck
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Andrei I. Holodny
- Neuroradiology Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, United States
- Department of Neuroscience, Weill-Cornell Graduate School of the Medical Sciences, New York, NY, United States
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