一般口演
神経回路操作 / 画像法と可視化など
Neural Circuit Manipulation / Imaging and Visualization
座長：山下 宙人（国際電気通信基礎技術研究所） |
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| 2022年6月30日 10:00～10:15 沖縄コンベンションセンター 会議場B2 第5会場
1O05m2-01
ヒト一次運動野に対するシン磁場刺激
A brand-new transcranial static magnetic field stimulation (triple tSMS) of human motor cortex
*芝田 純也(1,2)、美馬 達哉(3)、大西 秀明(1,2)
1. 新潟医療福祉大学 理学療法学科、2. 新潟医療福祉大学 運動機能医科学研究所、3. 立命館大学大学院 先端総合学術研究科
*Sumiya Shibata(1,2), Tatsuya Mima(3), Hideaki Onishi(1,2)
1. Department of Physical Therapy, Niigata University of Health and Welfare, Niigata, Japan, 2. Institute for Human Movement and Medical Sciences (HIMMS), Niigata University of Health and Welfare, Niigata, Japan, 3. The Graduate School of Core Ethics and Frontier Sciences, Ritsumeikan University, Kyoto, Japan
Keyword: transcranial static magnetic field stimulation (tSMS), non-invasive brain stimulation, deep brain stimulation
Transcranial static magnetic field stimulation (tSMS) is a new type of non-invasive brain stimulation. Using static magnetic fields produced by a small and strong neodymium (NdFeB) magnet placed on the scalp, tSMS can reduce the cortical excitability just below the magnet as well as modulate functions in the remote area from the magnet via brain-wide network. Unlike other non-invasive brain stimulation methods associated with induced electric currents such as repetitive transcranial magnetic stimulation (rTMS) and transcranial electric stimulation (tES), tSMS never provokes seizures or tingling sensations. Thus, tSMS is a promising neuromodulatory technique with safety, ease-of-operation, and low cost.
The disadvantage of a current tSMS system is that it cannot stimulate deep brain areas effectively. Since magnetic fields decrease with the distance from a magnet, a current tSMS cannot produce sufficient magnetic fields in deep brain areas to modulate brain functions. Deep brain areas such as basal ganglia and hippocampus are involved in many neurological and psychiatric diseases. The neuromodulation of the deep brain areas can be effective for the treatment of the brain diseases. Thus, overcoming this disadvantage can expand the possibility of its clinical use.
We designed and fabricated a brand-new tSMS system, triple tSMS, with three NdFeB magnets disposed in contiguity with each other. The system would produce an effective level of magnetic field strength in deep brain areas by summing up the magnetic fields produced by each magnet. The measurement of the magnetic field profile in the air produced by the triple tSMS system showed it could produce the magnetic field sufficient for neuromodulation up to 80 mm depth which was 30 mm deeper than a current tSMS.
Here, we performed a stimulation experiment in 17 healthy young subjects to confirm the functionality of the triple tSMS. The triple tSMS was applied over the representational field of the right first dorsal interosseous (FDI) muscle (the left M1) for 20 min. We found a significant decrease of the motor evoked potential (MEP) of the right FDI elicited by TMS over the left M1 after the intervention. The triple tSMS was capable of inhibiting brain functions of its target like a current tSMS system. These findings suggested that the triple tSMS could be used for non-invasive deep brain stimulation. | | 2022年6月30日 10:15～10:30 沖縄コンベンションセンター 会議場B2 第5会場
1O05m2-02
全脳レイヤーfMRIコネクティビティを目指して：機能的レイヤーコネクトミクスの方法論的進歩
Towards whole-brain layer-fMRI connectivity: methodological advancements for functional layer connectomics
*小磯 堅秀(1,2)、Sebastian Dresbach(1)、Christopher J Wiggins(3)、Omer Faruk Gulban(1,4)、宮脇 陽一(2,5)、Benedikt A Poser(1)、Renzo Huber(1)
2. 電気通信大学大学院情報理工学研究科、5. 電気通信大学脳・医工学研究センター
*Kenshu Koiso(1,2), Sebastian Dresbach(1), Christopher J Wiggins(3), Omer Faruk Gulban(1,4), Yoichi Miyawaki(2,5), Benedikt A Poser(1), Renzo Huber(1)
1. Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands, 2. Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo, Japan, 3. Scannexus, Maastricht, Netherlands, 4. Brain Innovation, Maastricht, Netherlands, 5. Center for Neuroscience and Biomedical Engineering, The University of Electro-Communications, Tokyo, Japan
Keyword: layer, fMRI, connectivity , whole-brain
Laminar-specific fMRI allows neuroscientists to address research questions of directional functional connectivity within and across brain areas. While recent sequence developments allow improvements in coverage and mitigations of venous biases, previous attempts of whole-brain connectome datasets turned out to be too artifact-dominated to be neuroscientifically applicable. Here we aimed to acquire a new and improved sequence and a relatively large open dataset of whole-brain laminar connectivity. Scans were performed on a 7T scanner. For layer-fMRI scanning without venous biases, a blood volume sensitive vascular space occupancy (VASO) (Lu 2003) sequence was used. The MAGEC VASO approach was used to maintain the VASO T1-weighting across long echo trains (Huber 2020). First, to find an improved sequence/reconstruction framework over previous works, nine ‘two-hour sessions’ of eight participants were performed. The final parameters that we used are: resolution = 0.842mm iso, TR = 5.1s (alternating 5.1s/5.2s), 3D-EPI (Poser 2010), GRAPPA 3x2, two segments and 3D-CAIPI 1 (Poser 2013, Stirnberg 2021). This sequence is available via SIEMENS’ C2P ‘app store’ Teamplay. The details of parameters are accessible on https://layerfmri.page.link/WBprotocol. Then, these newly improved scan/reconstruction parameters were used for eight ‘two-hour sessions’ in the main single participant while the subject was watching an identical Human Connectome Project (HCP) movie 51 times in total. All the movie-watching scan data are openly available on https://openneuro.org/datasets/ds003216. To investigate replicability of connectivity networks activation, we performed Independent Component Analysis (ICA). Then, we picked the parieto-frontal network component and performed General Linear Models (GLM) with the picked component on session-averaged functional time series independently on four sessions. Results showed that the spatial and temporal artifacts were successfully reduced by segmentation and shorter TRs over previous work in the visible levels. When analyzing each session’s data separately, we observed consistent layer signatures, demonstrating high reliability. The open dataset provided here will be useful for benchmarking developing laminar preprocessing strategies. Furthermore, with the large number of runs provided of the same 14 min movie clips, this dataset will be helpful for a comprehensive characterization of the reproducibility layer-fMRI connectivity results. | | 2022年6月30日 10:30～10:45 沖縄コンベンションセンター 会議場B2 第5会場
1O05m2-03
Determining the Correlation between Subjective Well-Being and EEG Alpha Asymmetry under Different Environmental Conditions
*Betty Wutzl(1), Kenji Leibnitz(2,1), Masayuki Murata(1,2)
1. Graduate School of Information Science and Technology, Osaka University, Suita, Japan, 2. Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology, and Osaka University, Suita, Japan
Keyword: Subjective Well-Being, EEG, Frontal alpha asymmetry
Introduction: Well-being is perceived differently from person to person, and it is our goal to determine a quantitative measure for it. Using electroencephalography (EEG), a correlation between frontal alpha asymmetry and subjective well-being (SWB) could be found (Urry et al. 2004; Xu et al. 2018). Unlike previous work, we focus on SWB as a dynamic measure which changes over time with temperature and humidity.
Methods: The temperature of the experimental room was set to one of three conditions (22°C, 24°C, or 26°C), and the humidity to one of four conditions (40, 60, 75, or 80 percent). An EEG headset (Emotiv EPOC+) was placed on the subject’s head, and we recorded brain waves for five minutes. SWB was provided by the subject every minute on a scale from 1 (worst) to 10 (best). The EEG data were analyzed using EEGLAB (Delorme and Makeig 2004) following HAPPE (The Harvard Automated Processing Pipeline for Electroencephalography) (Gabard-Durnam et al. 2018) for preprocessing. Furthermore, we used the MARA (Multiple Artifact Rejection Algorithm) plugin (Winkler et al. 2011; Winkler et al. 2014) and the FAA toolbox by Michael Tesar (Tesar, 2016). We computed an alpha asymmetry value foreach sensor pair and each minute (SWB value in the middle of the minute) of the experiment . Then we determined a correlation between those two values and tested for statistical relevance with a null model.
Results: We included 30 subjects (16 male, one left-handed, age 23.4 ± 3.3 years). We found statistically-significant correlations for 16 sensor pairs at a p-value of 0.05 (10 inter- and 6 intra-hemispheric). Considering a p-value of 0.01, just the connection between AF3 and AF4 remained statistically significant.
Conclusion: Our results show a positive linear correlation between the frontal (AF3, AF4) alpha asymmetry and the SWB, even when it is dynamically computed on a one-minute scale and for varied environmental conditions. Alpha asymmetry computed for different pairs of sensors, proved to be also statistically significant, however, with a higher p-value. These results show that it is not necessary to consider the whole brain, but it is sufficient to focus on the connection of specific areas, when trying to determine SWB. | | 2022年6月30日 10:45～11:00 沖縄コンベンションセンター 会議場B2 第5会場
1O05m2-04
白質病変が健常高齢者の皮質表面解析に及ぼす影響と改善のための新手法
The adverse effects of white matter lesions on cortical surface analysis in the healthy aged adults: A method proposed for improvement
*大井 由貴(1)、廣瀬 正和(1)、東口 大樹(3)、吉永 健二(2,3)、赤坂 太(5)、岡田 知久(5)、麻生 俊彦(4)、高橋 良輔(1)、林 拓也(4)、花川 隆(2,3)
1. 京都大学大学院医学研究科臨床神経学教室、2. 京都大学大学院医学研究科脳統合イメージング教室、3. 国立精神・神経医療研究センター 脳病態統合イメージングセンター、4. 理化学研究所生命機能科学研究センター脳コネクトミクスイメージング研究チーム、5. 京都大学大学院医学研究科脳機能総合研究センター
*Yuki Oi(1), Masakazu Hirose(1), Hiroki Togo(3), Kenji Yoshinaga(2,3), Thai Akasaka(5), Tomohisa Okada(5), Toshihiko Aso (4), Ryosuke Takahashi(1), Takuya Hayashi(4), Takashi Hanakawa(2,3)
1. Department of Neurology, Kyoto University Graduate School of Medicine, 2. Integrated Neuroanatomy and Neuroimaging, Kyoto University Graduate School of Medicine, 3. Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, 4. Laboratory for Brain Connectomics Imaging at RIKEN Center for Biosystems Dynamics Research, 5. Human Brain Research Center, Kyoto University Graduate School of Medicine
Keyword: age-related WML, Human Connectome Project, machine learning, cortical surface analysis
Recent advancement in brain MRI techniques like in the Human Connectome Project (HCP) has enabled a deep understanding of the cortical and subcortical structure, function, and connectivity. The usefulness of this HCP-style approach was proven in healthy young adults but yet to be fully tested in elderly adults, who often accompany age-related changes including asymptomatic subcortical white matter lesions (WMLs). The purpose of this study is to quantify the analysis errors of cortical surface estimation due to WMLs in the middle to advanced aged subjects, and compare the number of errors between before and after adopting a new correction method based on the automated prediction of WML. We used structural MRI data (T1-weighted images and T2-weighted FLAIR) obtained from 44 individuals who did not report any previous neuropsychiatric disorders (mean age of 64.4 years old (s.d. =11), ranging from 41 to 83 years, 29 males). We manually delineated WML as lesion masks in all the participants and used them to train a machine-learning algorithm for classifying WML, BIANCA (Brain Intensity AbNormality Classification Algorithm) in FSL (Functional magnetic resonance imaging Software Library) and optimized the classification threshold by leave-one-out cross-validation. Manually defined or BIANCA-predicted WML masks were fed into the HCP pipeline to re-estimate cortical surfaces. The products of the cortical surface analysis were compared between those with the manually defined WMLs (manual method), machine-predicted WMLs (BIANCA method), and without WMLs (control method). The numbers of the cortical surface errors were counted by two expert neuroradiologists ( T.A. and T.O.) and compared between the three methods. Advanced aged subjects (≧ 65 years old, N=26) had a larger total volume of WML and number of associated cortical surface errors than the others (<65 years old, N=18). The ratio of WML to white matter was significantly correlated with the number of errors in the control method. The number of errors was significantly reduced in both the manual and BIANCA methods by 60-80% compared to the control. No significant differences were found between BIANCA and manual methods. These findings indicate that the advanced aged adults may have significant numbers of WMLs, which potentially degrades cortical surface and metrics such as cortical thickness and myelin. Our results also demonstrated the potential usefulness of the combined approach of the machine-predicted WML and automated cortical surface estimation for improving the accuracy of cortical surfaces. Future studies should investigate the usefulness of the automated surface error correction method in a large-population study to understand mechanisms of aging and age-related neurodegeneration. | |
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