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de Zwart B, Ruis C. An update on tests used for intraoperative monitoring of cognition during awake craniotomy. Acta Neurochir (Wien) 2024; 166:204. [PMID: 38713405 PMCID: PMC11076349 DOI: 10.1007/s00701-024-06062-6] [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] [Received: 12/28/2023] [Accepted: 04/02/2024] [Indexed: 05/08/2024]
Abstract
PURPOSE Mapping higher-order cognitive functions during awake brain surgery is important for cognitive preservation which is related to postoperative quality of life. A systematic review from 2018 about neuropsychological tests used during awake craniotomy made clear that until 2017 language was most often monitored and that the other cognitive domains were underexposed (Ruis, J Clin Exp Neuropsychol 40(10):1081-1104, 218). The field of awake craniotomy and cognitive monitoring is however developing rapidly. The aim of the current review is therefore, to investigate whether there is a change in the field towards incorporation of new tests and more complete mapping of (higher-order) cognitive functions. METHODS We replicated the systematic search of the study from 2018 in PubMed and Embase from February 2017 to November 2023, yielding 5130 potentially relevant articles. We used the artificial machine learning tool ASReview for screening and included 272 papers that gave a detailed description of the neuropsychological tests used during awake craniotomy. RESULTS Comparable to the previous study of 2018, the majority of studies (90.4%) reported tests for assessing language functions (Ruis, J Clin Exp Neuropsychol 40(10):1081-1104, 218). Nevertheless, an increasing number of studies now also describe tests for monitoring visuospatial functions, social cognition, and executive functions. CONCLUSIONS Language remains the most extensively tested cognitive domain. However, a broader range of tests are now implemented during awake craniotomy and there are (new developed) tests which received more attention. The rapid development in the field is reflected in the included studies in this review. Nevertheless, for some cognitive domains (e.g., executive functions and memory), there is still a need for developing tests that can be used during awake surgery.
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Affiliation(s)
- Beleke de Zwart
- Experimental Psychology, Helmholtz Institution, Utrecht University, Utrecht, The Netherlands.
| | - Carla Ruis
- Experimental Psychology, Helmholtz Institution, Utrecht University, Utrecht, The Netherlands
- Department of Neurology and Neurosurgery, University Medical Center Utrecht, Utrecht, The Netherlands
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Gruenwald J, Sieghartsleitner S, Kapeller C, Scharinger J, Kamada K, Brunner P, Guger C. Characterization of High-Gamma Activity in Electrocorticographic Signals. Front Neurosci 2023; 17:1206120. [PMID: 37609450 PMCID: PMC10440607 DOI: 10.3389/fnins.2023.1206120] [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: 04/14/2023] [Accepted: 07/10/2023] [Indexed: 08/24/2023] Open
Abstract
Introduction Electrocorticographic (ECoG) high-gamma activity (HGA) is a widely recognized and robust neural correlate of cognition and behavior. However, fundamental signal properties of HGA, such as the high-gamma frequency band or temporal dynamics of HGA, have never been systematically characterized. As a result, HGA estimators are often poorly adjusted, such that they miss valuable physiological information. Methods To address these issues, we conducted a thorough qualitative and quantitative characterization of HGA in ECoG signals. Our study is based on ECoG signals recorded from 18 epilepsy patients while performing motor control, listening, and visual perception tasks. In this study, we first categorize HGA into HGA types based on the cognitive/behavioral task. For each HGA type, we then systematically quantify three fundamental signal properties of HGA: the high-gamma frequency band, the HGA bandwidth, and the temporal dynamics of HGA. Results The high-gamma frequency band strongly varies across subjects and across cognitive/behavioral tasks. In addition, HGA time courses have lowpass character, with transients limited to 10 Hz. The task-related rise time and duration of these HGA time courses depend on the individual subject and cognitive/behavioral task. Task-related HGA amplitudes are comparable across the investigated tasks. Discussion This study is of high practical relevance because it provides a systematic basis for optimizing experiment design, ECoG acquisition and processing, and HGA estimation. Our results reveal previously unknown characteristics of HGA, the physiological principles of which need to be investigated in further studies.
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Affiliation(s)
- Johannes Gruenwald
- g.tec medical engineering GmbH, Schiedlberg, Austria
- Institute of Computational Perception, Johannes Kepler University, Linz, Austria
| | - Sebastian Sieghartsleitner
- g.tec medical engineering GmbH, Schiedlberg, Austria
- Institute of Computational Perception, Johannes Kepler University, Linz, Austria
| | | | - Josef Scharinger
- Institute of Computational Perception, Johannes Kepler University, Linz, Austria
| | - Kyousuke Kamada
- Department for Neurosurgery, Asahikawa Medical University, Asahikawa, Japan
- Hokashin Group Megumino Hospital, Sapporo, Japan
| | - Peter Brunner
- National Center for Adaptive Neurotechnologies, Albany, NY, United States
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO, United States
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Xie T, Wu Z, Schalk G, Tong Y, Vato A, Raviv N, Guo Q, Ye H, Sheng X, Zhu X, Brunner P, Chen L. Automated intraoperative central sulcus localization and somatotopic mapping using median nerve stimulation. J Neural Eng 2022; 19. [PMID: 35785769 PMCID: PMC9534515 DOI: 10.1088/1741-2552/ac7dfd] [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: 02/18/2022] [Accepted: 07/04/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Accurate identification of functional cortical regions is essential in neurological resection. The central sulcus (CS) is an important landmark that delineates functional cortical regions. Median nerve stimulation (MNS) is a standard procedure to identify the position of the CS intraoperatively. In this paper, we introduce an automated procedure that uses MNS to rapidly localize the CS and create functional somatotopic maps. APPROACH We recorded electrocorticographic signals from 13 patients who underwent MNS in the course of an awake craniotomy. We analyzed these signals to develop an automated procedure that determines the location of the CS and that also produces functional somatotopic maps. MAIN RESULTS The comparison between our automated method and visual inspection performed by the neurosurgeon shows that our procedure has a high sensitivity (89%) in identifying the CS. Further, we found substantial concordance between the functional somatotopic maps generated by our method and passive functional mapping (92% sensitivity). SIGNIFICANCE Our automated MNS-based method can rapidly localize the CS and create functional somatotopic maps without imposing additional burden on the clinical procedure. With additional development and validation, our method may lead to a diagnostic tool that guides neurosurgeon and reduces postoperative morbidity in patients undergoing resective brain surgery.
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Affiliation(s)
- Tao Xie
- Department of Neurosurgery, Washington University School of Medicine in Saint Louis, 660 S. Euclid Avenue, St Louis, Missouri, 63110-1010, UNITED STATES
| | - Zehan Wu
- Dept. of Neurosurgery, Huashan Hospital Fudan University, 12 Wulumuqi Middle Rd, Shanghai, 200040, CHINA
| | - Gerwin Schalk
- National Center for Adaptive Neurotechnologies, 113 Holland Avenue, Albany, New York, 12208, UNITED STATES
| | - Yusheng Tong
- Dept. of Neurosurgery, Huashan Hospital Fudan University, 12 Wulumuqi Middle Rd, Shanghai, 200040, CHINA
| | - Alessandro Vato
- National Center for Adaptive Neurotechnologies, 113 Holland Avenue, Albany, New York, 12208, UNITED STATES
| | - Nataly Raviv
- National Center for Adaptive Neurotechnologies, 113 Holland Avenue, Albany, New York, 12208, UNITED STATES
| | - Qinglong Guo
- Dept. of Neurosurgery, Huashan Hospital Fudan University, 12 Wulumuqi Middle Rd, Shanghai, 200040, CHINA
| | - Huanpeng Ye
- State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, CHINA
| | - Xinjun Sheng
- State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, CHINA
| | - Xiangyang Zhu
- State Key Laboratory of Mechanical System and Vibration , Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, CHINA
| | - Peter Brunner
- Department of Neurosurgery, Washington University School of Medicine in Saint Louis, 660 S. Euclid Avenue, St Louis, Missouri, 63110-1010, UNITED STATES
| | - Liang Chen
- Dept. of Neurosurgery, Huashan Hospital Fudan University, 12 Wulumuqi Middle Rd, Shanghai, 200040, CHINA
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Neshige S, Kobayashi K, Matsuhashi M, Hitomi T, Shimotake A, Kikuchi T, Yoshida K, Kunieda T, Matsumoto R, Miyamoto S, Takahashi R, Maruyama H, Ikeda A. A rational, multispectral mapping algorithm for primary motor cortex: A primary step before cortical stimulation. Epilepsia 2019; 60:547-559. [PMID: 30790267 DOI: 10.1111/epi.14669] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Revised: 01/20/2019] [Accepted: 01/21/2019] [Indexed: 12/11/2022]
Abstract
OBJECTIVE For future artificial intelligence-based brain mapping, development of a rational and safe scoring system for a brain motor mapping algorithm using electrocorticography (ECoG score), which contains various spectral, purely intrinsic brain activities, is necessary for either before or in the absence of electrical cortical stimulation (ECS). METHODS We evaluated 1114 electrodes of 10 consecutive focal epilepsy patients who underwent subdural electrode implantation before epilepsy surgery at Kyoto University Hospital during 2011-2017. Data from ECoG-based mapping (bandpass filter of 0.016-300/600 Hz) to define the primary motor area (M1) localization were used to create an ECoG score (range = 0-4) by assigning 1 point each for the occurrence of ECoG components: very slow movement-related cortical potentials (<0.5-1.0 Hz), event-related synchronization (76-100 Hz or 100-200 Hz), and event-related desynchronization (8-12 Hz or 12-24 Hz). The ECoG score was assessed by calculating the sensitivity, specificity, and cutoff values of the score for localization concordance with M1 defined using only ECS as a reference. RESULTS With an area under the receiver operating characteristic curve (AUC) of 0.76, cutoffs of scores of 4 and 1 showed high specificity (94%) and sensitivity (98%) in concordance with ECS-based mapping, respectively. The ECoG score for mapping M1 of the upper limb achieved greater accuracy (AUC = 0.85) compared to that of the face (AUC = 0.64). SIGNIFICANCE The ECoG score proposed in the present study is rational, simple, and useful to define M1, and it is spatially concordant with ECS. Although ECS is still widely employed for presurgical examination, our proposed application of the ECoG score may be suitable for future brain M1 mapping, and possibly beyond M1 mapping, independently of ECS.
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Affiliation(s)
- Shuichiro Neshige
- Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto, Japan.,Department of Clinical Neuroscience and Therapeutics, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, Japan
| | - Katsuya Kobayashi
- Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Masao Matsuhashi
- Department of Epilepsy, Movement Disorders, and Physiology, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Takefumi Hitomi
- Department of Clinical Laboratory Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Akihiro Shimotake
- Department of Epilepsy, Movement Disorders, and Physiology, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Takayuki Kikuchi
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Kazumichi Yoshida
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Takeharu Kunieda
- Department of Neurosurgery, Ehime University Graduate School of Medicine, Noon, Japan
| | - Riki Matsumoto
- Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Susumu Miyamoto
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Ryosuke Takahashi
- Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Hirofumi Maruyama
- Department of Clinical Neuroscience and Therapeutics, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, Japan
| | - Akio Ikeda
- Department of Epilepsy, Movement Disorders, and Physiology, Kyoto University Graduate School of Medicine, Kyoto, Japan
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