Pub Date : 2023-12-01DOI: 10.26599/BSA.2023.9050021
Hao-nan Li, Zhiqiang Cui, Yong Liu
Objective: To investigate the clinical efficacy of minimally invasive subpial tonsillectomy (MIST) in the treatment of Chiari malformation (type I) with syringomyelia. Method A total of 209 Chiari malformation (type I) patients with syringomyelia were studied. The patients were grouped based on the syrinx diameter changes: complete disappearance group (48 patients), obvious shrinkage group (147 patients), and non-obvious shrinkage group (14 patients). The Chicago Chiari Outcome Scale (CCOS) was used to compare clinical data of the three groups of patients before treatment. The correlations between disease duration and syrinx diameter changes as well as post-treatment clinical symptoms were analyzed. The related factors of efficacy were analyzed. Results: Age and disease duration were the oldest/longest in the non-obvious shrinkage group, and the youngest/shortest in the complete disappearance group (P < 0.05). The maximum diameter reduction of syrinx was the greatest in the complete disappearance group, and the smallest in the non-obvious shrinkage group (P < 0.05). The proportions of patients with hypoesthesia, limb weakness, and muscle atrophy were the largest in the non-obvious shrinkage group, and the smallest in the complete disappearance group (P < 0.05). The CCOS score were the highest in the complete disappearance group, and the lowest in the non-obvious shrinkage group (P < 0.05). There were statistically significant (P < 0.05) negative correlations between disease duration and maximum diameter reduction of syrinx, CCOS pain score, CCOS non-pain score, CCOS functionality score, and CCOS complication score, disease duration and hypoesthesia, limb weakness, muscle atrophy, and sleep apnea. Result of multivariate stepwise regression analysis indicated that age, disease duration, and preoperative syrinx diameter were the risk factors for efficacy (P < 0.05). Conclusion: For patients with Chiari malformation complicated by syringomyelia, the longer the disease duration, the more difficult it is to achieve syrinx reduction and improve the clinical symptoms. “Minimally invasive subpial tonsillectomy (MIST) and cisterna magna reconstruction” is an improved surgical approach to treat Chiari malformation (cerebellar tonsil herniation). It has the advantages of small incision, less postoperative reaction, and fewer complications, and it emphasizes the reshaping and repair of cerebellar tonsils, reconstruction of cisterna magna, and restoration of cerebrospinal fluid circulation.
{"title":"Clinical Efficacy of Minimally Invasive Subpial Tonsillectomy (MIST) for Treatment of Chiari Malformation (Type I) with Syringomyelia","authors":"Hao-nan Li, Zhiqiang Cui, Yong Liu","doi":"10.26599/BSA.2023.9050021","DOIUrl":"https://doi.org/10.26599/BSA.2023.9050021","url":null,"abstract":"Objective: To investigate the clinical efficacy of minimally invasive subpial tonsillectomy (MIST) in the treatment of Chiari malformation (type I) with syringomyelia. Method A total of 209 Chiari malformation (type I) patients with syringomyelia were studied. The patients were grouped based on the syrinx diameter changes: complete disappearance group (48 patients), obvious shrinkage group (147 patients), and non-obvious shrinkage group (14 patients). The Chicago Chiari Outcome Scale (CCOS) was used to compare clinical data of the three groups of patients before treatment. The correlations between disease duration and syrinx diameter changes as well as post-treatment clinical symptoms were analyzed. The related factors of efficacy were analyzed. Results: Age and disease duration were the oldest/longest in the non-obvious shrinkage group, and the youngest/shortest in the complete disappearance group (P < 0.05). The maximum diameter reduction of syrinx was the greatest in the complete disappearance group, and the smallest in the non-obvious shrinkage group (P < 0.05). The proportions of patients with hypoesthesia, limb weakness, and muscle atrophy were the largest in the non-obvious shrinkage group, and the smallest in the complete disappearance group (P < 0.05). The CCOS score were the highest in the complete disappearance group, and the lowest in the non-obvious shrinkage group (P < 0.05). There were statistically significant (P < 0.05) negative correlations between disease duration and maximum diameter reduction of syrinx, CCOS pain score, CCOS non-pain score, CCOS functionality score, and CCOS complication score, disease duration and hypoesthesia, limb weakness, muscle atrophy, and sleep apnea. Result of multivariate stepwise regression analysis indicated that age, disease duration, and preoperative syrinx diameter were the risk factors for efficacy (P < 0.05). Conclusion: For patients with Chiari malformation complicated by syringomyelia, the longer the disease duration, the more difficult it is to achieve syrinx reduction and improve the clinical symptoms. “Minimally invasive subpial tonsillectomy (MIST) and cisterna magna reconstruction” is an improved surgical approach to treat Chiari malformation (cerebellar tonsil herniation). It has the advantages of small incision, less postoperative reaction, and fewer complications, and it emphasizes the reshaping and repair of cerebellar tonsils, reconstruction of cisterna magna, and restoration of cerebrospinal fluid circulation.","PeriodicalId":402599,"journal":{"name":"Brain Science Advances","volume":"725 ","pages":"310 - 321"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139022776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.26599/BSA.2023.9050020
Yue Dong, Sen Tian
Background: Brain-computer interfaces (BCIs) have gained considerable attention for their potential in assisting individuals who have motor impairments with communication and rehabilitation. Among BCIs, steady-state visual evoked potential (SSVEP)-based systems have demonstrated high efficiency in interactive applications. However, ergonomic design challenges have limited their practical implementation in industrial settings. Issues such as visual and mental fatigue caused by flickering stimuli and the time-consuming preparation process hinder user adoption of such systems. Methods: To evaluate these BCI solutions, we introduced an open database comprising Electroencephalogram (EEG) data collected from 59 healthy volunteers using ergonomically designed semi-dry electrodes and grid stimuli. The database was acquired without electromagnetic shielding, and the preparation time for each participant was <5 min. A 40-target SSVEP speller system with cues was used in the experiment. Results: We validate the database by temporal and spectral analyzing methods. To further investigate the database, filter bank canonical correlation analysis (FBCCA), ensemble task-related component analysis (e-TRCA) and multi-stimulus task-related component analysis (msTRCA) were used for classification. The database can be downloaded from the following link: https://drive.google.com/drive/folders/1TXuxU863nZoniZRgNWZy0PRuL8lhBuP4?usp=sharing. Conclusions: This research contributes to enhancing the use of SSVEP-based BCIs in practical settings by addressing user experience and system design challenges. The proposed user-friendly visual stimuli and ergonomic electrode design improve comfort and usability. The open dataset serves as a valuable resource for future studies, enabling the development of robust and efficient SSVEP- BCI systems suitable for industrial applications.
{"title":"A large database towards user-friendly SSVEP-based BCI","authors":"Yue Dong, Sen Tian","doi":"10.26599/BSA.2023.9050020","DOIUrl":"https://doi.org/10.26599/BSA.2023.9050020","url":null,"abstract":"Background: Brain-computer interfaces (BCIs) have gained considerable attention for their potential in assisting individuals who have motor impairments with communication and rehabilitation. Among BCIs, steady-state visual evoked potential (SSVEP)-based systems have demonstrated high efficiency in interactive applications. However, ergonomic design challenges have limited their practical implementation in industrial settings. Issues such as visual and mental fatigue caused by flickering stimuli and the time-consuming preparation process hinder user adoption of such systems. Methods: To evaluate these BCI solutions, we introduced an open database comprising Electroencephalogram (EEG) data collected from 59 healthy volunteers using ergonomically designed semi-dry electrodes and grid stimuli. The database was acquired without electromagnetic shielding, and the preparation time for each participant was <5 min. A 40-target SSVEP speller system with cues was used in the experiment. Results: We validate the database by temporal and spectral analyzing methods. To further investigate the database, filter bank canonical correlation analysis (FBCCA), ensemble task-related component analysis (e-TRCA) and multi-stimulus task-related component analysis (msTRCA) were used for classification. The database can be downloaded from the following link: https://drive.google.com/drive/folders/1TXuxU863nZoniZRgNWZy0PRuL8lhBuP4?usp=sharing. Conclusions: This research contributes to enhancing the use of SSVEP-based BCIs in practical settings by addressing user experience and system design challenges. The proposed user-friendly visual stimuli and ergonomic electrode design improve comfort and usability. The open dataset serves as a valuable resource for future studies, enabling the development of robust and efficient SSVEP- BCI systems suitable for industrial applications.","PeriodicalId":402599,"journal":{"name":"Brain Science Advances","volume":"171 1","pages":"297 - 309"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139015307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.26599/BSA.2023.9050025
Despina Tsolisou
Over the last decades, infantile brain networks have received increased scientific attention due to the elevated need to understand better the maturational processes of the human brain and the early forms of neural abnormalities. Electroencephalography (EEG) is becoming a popular tool for the investigation of functional connectivity (FC) of the immature brain, as it is easily applied in awake, non-sedated infants. However, there are still no universally accepted standards regarding the preprocessing and processing analyses which address the peculiarities of infantile EEG data, resulting in comparability difficulties between different studies. Nevertheless, during the last few years, there is a growing effort in overcoming these issues, with the creation of age-appropriate pipelines. Although FC in infants has been mostly measured via linear metrics and particularly coherence analysis, non-linear methods, such as cross-frequency-coupling (CFC), may be more valuable for the investigation of network communication and early network development. Additionally, graph theory analysis often accompanies linear and non-linear FC computation offering a more comprehensive understanding of the infantile network architecture. The current review attempts to gather the basic information on the preprocessing and processing techniques that are usually employed by infantile FC studies, while providing guidelines for future studies.
在过去的几十年里，由于需要更好地了解人类大脑的成熟过程和早期神经异常的形式，婴幼儿大脑网络受到了越来越多的科学关注。脑电图（EEG）正成为研究未成熟大脑功能连接（FC）的流行工具，因为它很容易应用于清醒、无镇静的婴儿。然而，针对婴儿脑电图数据的特殊性，在预处理和处理分析方面仍然没有公认的标准，导致不同研究之间难以进行比较。尽管如此，在过去几年中，随着适龄管道的建立，人们在克服这些问题方面做出了越来越多的努力。虽然婴儿的脑功能大多是通过线性指标，特别是相干性分析来测量的，但非线性方法，如交叉频率耦合（CFC），可能对研究网络通信和早期网络发展更有价值。此外，图论分析通常与线性和非线性 FC 计算同时进行，从而更全面地了解婴儿网络结构。本综述试图收集有关婴儿 FC 研究通常采用的预处理和处理技术的基本信息，同时为今后的研究提供指导。
{"title":"EEG connectivity analysis in infants: A Beginner’s Guide on Preprocessing and Processing Techniques","authors":"Despina Tsolisou","doi":"10.26599/BSA.2023.9050025","DOIUrl":"https://doi.org/10.26599/BSA.2023.9050025","url":null,"abstract":"Over the last decades, infantile brain networks have received increased scientific attention due to the elevated need to understand better the maturational processes of the human brain and the early forms of neural abnormalities. Electroencephalography (EEG) is becoming a popular tool for the investigation of functional connectivity (FC) of the immature brain, as it is easily applied in awake, non-sedated infants. However, there are still no universally accepted standards regarding the preprocessing and processing analyses which address the peculiarities of infantile EEG data, resulting in comparability difficulties between different studies. Nevertheless, during the last few years, there is a growing effort in overcoming these issues, with the creation of age-appropriate pipelines. Although FC in infants has been mostly measured via linear metrics and particularly coherence analysis, non-linear methods, such as cross-frequency-coupling (CFC), may be more valuable for the investigation of network communication and early network development. Additionally, graph theory analysis often accompanies linear and non-linear FC computation offering a more comprehensive understanding of the infantile network architecture. The current review attempts to gather the basic information on the preprocessing and processing techniques that are usually employed by infantile FC studies, while providing guidelines for future studies.","PeriodicalId":402599,"journal":{"name":"Brain Science Advances","volume":"195 ","pages":"242 - 274"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139020626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.26599/bsa.2023.9050019
Hong Li, Junjie Wang
The personality–brain association mechanism has been a topic of interest in the field of neuroscience. Usually, the previous research strategy was to first group the population based on different personality traits, and then explore the brain mechanisms corresponding to different personality groups. At present, a “brain‐first” research strategy, which uses data‐driven approaches instead of personality traits to first group the population, has been adopted to further enhance study objectivity. Here, we used a data‐driven approach following the “brain‐first” research strategy to deeply mine the resting‐state brain functional magnetic resonance imaging data of 119 healthy participants, classified subjects into different groups based on brain image characteristics, and used the Sixteen Personality Factor Questionnaire to explain the variabilities of resting‐state brain characteristics between different groups. Finally, we have identified 3 personality–brain connections, including the privateness–left frontoparietal network, liveliness–sensory–motor network, and vigilance–sensory–motor network. Furthermore, we conclude that the above‐mentioned three personality factors are based on brain neural activity, independent of the subjective experience of the personality scale creator, and have stronger explanatory power of brain imaging features.
{"title":"Personality&ndash;brain connection: Based on resting‐state functional magnetic resonance imaging data‐driven exploration","authors":"Hong Li, Junjie Wang","doi":"10.26599/bsa.2023.9050019","DOIUrl":"https://doi.org/10.26599/bsa.2023.9050019","url":null,"abstract":"The personality–brain association mechanism has been a topic of interest in the field of neuroscience. Usually, the previous research strategy was to first group the population based on different personality traits, and then explore the brain mechanisms corresponding to different personality groups. At present, a “brain‐first” research strategy, which uses data‐driven approaches instead of personality traits to first group the population, has been adopted to further enhance study objectivity. Here, we used a data‐driven approach following the “brain‐first” research strategy to deeply mine the resting‐state brain functional magnetic resonance imaging data of 119 healthy participants, classified subjects into different groups based on brain image characteristics, and used the Sixteen Personality Factor Questionnaire to explain the variabilities of resting‐state brain characteristics between different groups. Finally, we have identified 3 personality–brain connections, including the privateness–left frontoparietal network, liveliness–sensory–motor network, and vigilance–sensory–motor network. Furthermore, we conclude that the above‐mentioned three personality factors are based on brain neural activity, independent of the subjective experience of the personality scale creator, and have stronger explanatory power of brain imaging features.","PeriodicalId":402599,"journal":{"name":"Brain Science Advances","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135349472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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