Journal of Neuroscience Methods最新文献

{"title":"Improved brain effective connectivity modelling by dynamic Bayesian networks","authors":"Ilkay Ulusoy,&nbsp;Salih Geduk","doi":"10.1016/j.jneumeth.2024.110211","DOIUrl":"10.1016/j.jneumeth.2024.110211","url":null,"abstract":"<div><h3>Background:</h3><p>If brain effective connectivity network modelling (ECN) could be accurately achieved, early diagnosis of neurodegenerative diseases would be possible. It has been observed in the literature that Dynamic Bayesian Network (DBN) based methods are more successful than others. However, DBNs have not been applied easily and tested much due to computational complexity problems in structure learning.</p></div><div><h3>New method:</h3><p>This study introduces an advanced method for modelling brain ECNs using improved discrete DBN (Improved- dDBN) which addresses the computational challenges previously limiting DBN application, offering solutions that enable accurate and fast structure modelling.</p></div><div><h3>Results:</h3><p>The practical data and prior sizes needed for the convergence to the globally correct network structure are proved to be much smaller than the theoretical ones using simulated dDBN data. Besides, Hill Climbing is shown to converge to the true structure at a reasonable iteration step size when the appropriate data and prior sizes are used. Finally, importance of data quantization methods are analysed.</p></div><div><h3>Comparison with existing methods:</h3><p>The Improved-dDBN method performs better and robust, when compared to the existing methods for realistic scenarios such as varying graph complexity, various input conditions, noise cases and non-stationary connections. The data used in these tests is the simulated fMRI BOLD time series proposed in the literature.</p></div><div><h3>Conclusions:</h3><p>Improved-dDBN is a good candidate to be used on real datasets to accelerate developments in brain ECN modelling and neuroscience. Appropriate data and prior sizes can be identified based on the approach proposed in this study for global and fast convergence.</p></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"409 ","pages":"Article 110211"},"PeriodicalIF":2.7,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141537905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"NeuroHealth guardian: A novel hybrid approach for precision brain stroke prediction and healthcare analytics","authors":"Umar Islam ,&nbsp;Gulzar Mehmood ,&nbsp;Abdullah A. Al-Atawi ,&nbsp;Faheem Khan ,&nbsp;Hathal Salamah Alwageed ,&nbsp;Lucia Cascone","doi":"10.1016/j.jneumeth.2024.110210","DOIUrl":"10.1016/j.jneumeth.2024.110210","url":null,"abstract":"<div><p>Stroke is a severe illness, that requires early stroke detection and intervention, as this would help prevent the worsening of the condition. The research is done to solve stroke prediction problem, which may be divided into a number of sub-problems such as an individual's predisposition to develop stroke. To attain this objective, a multiturn dataset consisting of various health features, such as age, gender, hypertension, and glucose levels, takes a central role. A multiple approach was put forward concentrating on integrating the machine learning techniques, such as Logistic Regression, Naive Bayes, K-Nearest Neighbors, and Support Vector Machine (SV), together to develop an ensemble machine called Neuro-Health Guardian. The hypothesis \"Neuro-Health Guardian Model\" integrates these algorithms into one, purported to make stroke prediction more accurate. The topic dives into each instance of preparation of data for analysis, data visualization techniques, selection of the right model, training, testing, ensembling, evaluation, and prediction. The models are validated with error rate accounted from their accuracy, precision, recall, F1 score, and finally confusion matrices for a look. The study's result is showing that the ensemble model that combines the multiple algorithms has the edge over them and this is evidently by the fact that it can predict stroke rises. Additionally, accuracy, precision, recall, and F1 scores are measured in all models and the comparison is done to provide a clear comparison of the models' performance. In short, the article presented the formation of the ongoing stroke prediction that revealed the ensemble model as a good anticipation. Precise stroke predisposition forecasting can assist in early intervention thereby preventing stroke-related deaths, and limiting disability burden by stroke. The conclusions that have come out of this study offer a great action item for the development of predictive models related to stroke prevention and treatment.</p></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"409 ","pages":"Article 110210"},"PeriodicalIF":2.7,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141537906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Systematic Online Living Evidence Summary of experimental Alzheimer’s disease research","authors":"","doi":"10.1016/j.jneumeth.2024.110209","DOIUrl":"10.1016/j.jneumeth.2024.110209","url":null,"abstract":"<div><h3>Background</h3><p>Despite extensive investment, the development of effective treatments for Alzheimer's disease (AD) has been largely unsuccessful. To improve translation, it is crucial to ensure the quality and reproducibility of foundational evidence generated from laboratory models. Systematic reviews play a key role in providing an unbiased overview of the evidence, assessing rigour and reporting, and identifying factors that influence reproducibility. However, the sheer pace of evidence generation is prohibitive to evidence synthesis and assessment.</p></div><div><h3>New method</h3><p>To address these challenges, we have developed AD-SOLES, an integrated workflow of automated tools that collect, curate, and visualise the totality of evidence from in vivo experiments.</p></div><div><h3>Results</h3><p>AD-SOLES is a publicly accessible interactive dashboard aiming to surface and expose data from in vivo experiments. It summarises the latest evidence, tracks reporting quality and transparency, and allows research users to easily locate evidence relevant to their specific research question.</p></div><div><h3>Comparison with existing methods</h3><p>Using automated screening methodologies within AD-SOLES, systematic reviews can begin at an accelerated starting point compared to traditional approaches. Furthermore, through text-mining approaches within the full-text of publications, users can identify research of interest using specific models, outcomes, or interventions without relying on details in the title and/or abstract.</p></div><div><h3>Conclusions</h3><p>By automating the collection, curation, and visualisation of evidence from in vivo experiments, AD-SOLES addresses the challenges posed by the rapid pace of evidence generation. AD-SOLES aims to offer guidance for research improvement, reduce research waste, highlight knowledge gaps, and support informed decision making for researchers, funders, patients, and the public.</p></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"409 ","pages":"Article 110209"},"PeriodicalIF":2.7,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0165027024001547/pdfft?md5=2f105b3aaaee3d5e9f7dd7706921261c&pid=1-s2.0-S0165027024001547-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141534642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dementia rhythms: Unveiling the EEG dynamics for MCI detection through spectral and synchrony neuromarkers","authors":"Mesut Şeker,&nbsp;Mehmet Siraç Özerdem","doi":"10.1016/j.jneumeth.2024.110216","DOIUrl":"10.1016/j.jneumeth.2024.110216","url":null,"abstract":"<div><h3>Background</h3><p>Neurological disorders arise primarily from the dysfunction of brain cells, leading to various impairments. Electroencephalography (EEG) stands out as the most popular method in the discovery of neuromarkers indicating neurological disorders. The proposed study investigates the effectiveness of spectral and synchrony neuromarkers derived from resting state EEG in the detection of Mild Cognitive Impairment (MCI) with controls.</p></div><div><h3>New methods</h3><p>The dataset is composed of 10 MCI and 10 HC groups. Spectral features and synchrony measures are utilized to detect slowing patterns in MCI. Efficient neuro-markers are classified by 25 classification algorithm. Independent samples t-test and Pearson’s Correlation Coefficients are applied to reveal group differences for spectral markers, and repeated measures ANOVA is tested for wPLI-based markers.</p></div><div><h3>Results</h3><p>Lower peak amplitudes are prominent in MCI participants for high frequencies indicating slower physiological behavior of the demented EEG. The MCI and HC groups are correctly classified with 95 % acc. using peak amplitudes of beta band with LGBM classifier. Higher wPLI values are calculated for HC participants in high frequencies. The alpha wPLI values achieve a classification accuracy of 99 % using the LGBM algorithm for MCI detection.</p></div><div><h3>Comparison with existing methods</h3><p>The neuro-markers including peak amplitudes, frequencies, and wPLIs with advanced machine learning techniques showcases the innovative nature of this research.</p></div><div><h3>Conclusion</h3><p>The findings suggest that peak amplitudes and wPLI in high frequency bands derived from resting state EEG are effective neuromarkers for detection of MCI. Spectral and synchrony neuro-markers hold great promise for accurate MCI detection.</p></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"409 ","pages":"Article 110216"},"PeriodicalIF":2.7,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141534644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of emotional states on tinnitus sound therapy efficacy based on ECG signals and emotion recognition model","authors":"Ancheng Fang ,&nbsp;Ping Zhong ,&nbsp;Fan Pan ,&nbsp;Yongkang Li ,&nbsp;Peiyu He","doi":"10.1016/j.jneumeth.2024.110213","DOIUrl":"10.1016/j.jneumeth.2024.110213","url":null,"abstract":"<div><h3>Background</h3><p>Diagnosis and severity assessment of tinnitus are mostly based on the patient's descriptions and subjective questionnaires, which lacks objective means of diagnosis and assessment bases, the accuracy of which fluctuates with the clarity of the patient's description. This complicates the timely modification of treatment strategies or therapeutic music to improve treatment efficacy.</p></div><div><h3>New method</h3><p>We employed a novel random convolutional kernel-based method for electrocardiogram (ECG) signal analysis to identify patients' emotional states during Music Tinnitus Sound Therapy (Music-TST) sessions. Then analyzed correlations between emotional changes in different treatment phase and Tinnitus Handicap Inventory (THI) score differences to determine the impact of emotions on tinnitus treatment efficacy.</p></div><div><h3>Results</h3><p>This study revealed a significant correlation between patients' emotion changes during Music-TST and the therapy's effectiveness. Changes in arousal and dominance dimension, were strongly linked to THI variations. These findings highlight the substantial impact of emotional responses on sound therapy's efficacy, offering a new perspective for understanding and optimizing tinnitus treatment.</p></div><div><h3>Comparison with existing methods</h3><p>Compared to existing methods, we proposed an objective indicator to assess the progress of sound therapy, the indicator could also be used to provide feedback to optimize sound therapy music.</p></div><div><h3>Conclusions</h3><p>This study revealed the critical role of emotion changes in tinnitus sound therapy. By integrating objective ECG-based emotion analysis with traditional subjective scale like THI, we present an innovative approach to assess and potentially optimize therapy effectiveness. This finding could lead to more personalized and effective treatment strategies for tinnitus sound therapy.</p></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"409 ","pages":"Article 110213"},"PeriodicalIF":2.7,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141534645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combining blood pressure variability and heart rate variability to analyze the autonomic nervous function of rotenone induced Parkinson’s rat model","authors":"Nan Yang ,&nbsp;Tao Tan ,&nbsp;Jiarong Wei ,&nbsp;Xudong Gao ,&nbsp;Menghan Wang ,&nbsp;Ruijiao Li ,&nbsp;Chen Wang ,&nbsp;Miaoqing Lei ,&nbsp;Heshun Hu ,&nbsp;Mengke Wang ,&nbsp;Yifan Feng ,&nbsp;Peiqi Chen ,&nbsp;Yilin Liu ,&nbsp;Junlin Mu ,&nbsp;Zongya Zhao ,&nbsp;Yi Yu","doi":"10.1016/j.jneumeth.2024.110217","DOIUrl":"10.1016/j.jneumeth.2024.110217","url":null,"abstract":"<div><h3>Background</h3><p>Parkinson's patients have significant autonomic dysfunction, early detect the disorder is a major challenge. To assess the autonomic function in the rat model of rotenone induced Parkinson's disease (PD), Blood pressure and ECG signal acquisition are very important.</p></div><div><h3>New method</h3><p>We used telemetry to record the electrocardiogram and blood pressure signals from awake rats, with linear and nonlinear analysis techniques calculate the heart rate variability (HRV) and blood pressure variability (BPV). we applied nonlinear analysis methods like sample entropy and detrended fluctuation analysis to analyze blood pressure signals. Particularly, this is the first attempt to apply nonlinear analysis to the blood pressure evaluate in rotenone induced PD model rat.</p></div><div><h3>Results</h3><p>HRV in the time and frequency domains indicated sympathetic-parasympathetic imbalance in PD model rats. Linear BPV analysis didn’t reflect changes in vascular function and blood pressure regulation in PD model rats. Nonlinear analysis revealed differences in BPV, with lower sample entropy results and increased detrended fluctuation analysis results in the PD group rats.</p><p>Comparison with existing methods and Conclusions: our experiments demonstrate the ability to evaluate autonomic dysfunction in models of Parkinson's disease by combining the analysis of BPV with HRV, consistent with autonomic impairment in PD patients. Nonlinear analysis by blood pressure signal may help in early detection of the PD. It indicates that the fluctuation of blood pressure in the rats in the rotenone model group tends to be regular and predictable, contributes to understand the PD pathophysiological mechanisms and to find strategies for early diagnosis.</p></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"409 ","pages":"Article 110217"},"PeriodicalIF":2.7,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141534643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A deep-learning-based threshold-free method for automated analysis of rodent behavior in the forced swim test and tail suspension test","authors":"Xuechun Meng ,&nbsp;Yang Xia ,&nbsp;Mingqing Liu ,&nbsp;Yuxing Ning ,&nbsp;Hongqi Li ,&nbsp;Ling Liu ,&nbsp;Ji Liu","doi":"10.1016/j.jneumeth.2024.110212","DOIUrl":"10.1016/j.jneumeth.2024.110212","url":null,"abstract":"<div><h3>Background</h3><p>The forced swim test (FST) and tail suspension test (TST) are widely used to assess depressive-like behaviors in animals. Immobility time is used as an important parameter in both FST and TST. Traditional methods for analyzing FST and TST rely on manually setting the threshold for immobility, which is time-consuming and subjective.</p></div><div><h3>New method</h3><p>We proposed a threshold-free method for automated analysis of mice in these tests using a Dual-Stream Activity Analysis Network (DSAAN). Specifically, this network extracted spatial information of mice using a limited number of video frames and combined it with temporal information extracted from differential feature maps to determine the mouse’s state. To do so, we developed the Mouse FSTST dataset, which consisted of annotated video recordings of FST and TST.</p></div><div><h3>Results</h3><p>By using DSAAN methods, we identify immobility states at accuracies of 92.51 % and 88.70 % for the TST and FST, respectively. The predicted immobility time from DSAAN is nicely correlated with a manual score, which indicates the reliability of the proposed method. Importantly, the DSAAN achieved over 80 % accuracy for both FST and TST by utilizing only 94 annotated images, suggesting that even a very limited training dataset can yield good performance in our model.</p></div><div><h3>Comparison with existing method(s)</h3><p>Compared with DBscorer and EthoVision XT, our method exhibits the highest Pearson correlation coefficient with manual annotation results on the Mouse FSTST dataset.</p></div><div><h3>Conclusions</h3><p>We established a powerful tool for analyzing depressive-like behavior independent of threshold, which is capable of freeing users from time-consuming manual analysis.</p></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"409 ","pages":"Article 110212"},"PeriodicalIF":2.7,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141498246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modified histological staining for the identification of arterial and venous segments of brain microvessels","authors":"Luping Xue ,&nbsp;Wei Ouyang ,&nbsp;Xiaoru Qi ,&nbsp;Xiao Zhang ,&nbsp;Baodong Li ,&nbsp;Xiangjian Zhang ,&nbsp;Lili Cui","doi":"10.1016/j.jneumeth.2024.110214","DOIUrl":"10.1016/j.jneumeth.2024.110214","url":null,"abstract":"<div><h3>Background</h3><p>This study aimed to develop a modified histochemical staining technique to successfully identify arterial and venous segments of brain microvessels.</p></div><div><h3>New method</h3><p>Gelatin/red ink-alkaline phosphatase-oil red O (GIAO) staining was developed from the traditional gelatin–ink perfusion method. Oil red Chinese ink for brush writing and painting mixed with gelatin was used to label cerebral vascular lumens. Subsequently, alkaline phosphatase staining was used to label endothelial cells on the arterial segments of cerebral microvessels. Thereafter, the red ink color in vessel lumens was highlighted with oil red O staining.</p></div><div><h3>Results</h3><p>The arterial segments of the brain microvessels exhibited red lumens surrounded by dark blue walls, while the venous segments were bright red following GIAO staining. Meanwhile, the nerve fiber bundles were stained brownish-yellow, and the nuclei appeared light green under light microscope. After cerebral infarction, we used GIAO staining to determine angiogenesis features and detected notable vein proliferation inside the infarct core. Moreover, GIAO staining in conjunction with hematoxylin staining was performed to assess the infiltration of foamy macrophages.</p></div><div><h3>Comparison with existing method</h3><p>Red Chinese ink enabled subsequent multiple color staining on brain section. Oil red O was introduced to improved the resolution and contrast between arterial and venous segments of microvessels.</p></div><div><h3>Conclusion</h3><p>With excellent resolution, GIAO staining effectively distinguished arterial and venous segments of microvessels in both normal and ischemic brain tissue. GIAO staining, as described in the present study, will be useful for histological investigations of microvascular bed alterations in a variety of brain disorders.</p></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"409 ","pages":"Article 110214"},"PeriodicalIF":2.7,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141498247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimation of complete mutual information exploiting nonlinear magnitude-phase dependence: Application to spatial FNC for complex-valued fMRI data","authors":"Wei-Xing Li ,&nbsp;Qiu-Hua Lin ,&nbsp;Chao-Ying Zhang ,&nbsp;Yue Han ,&nbsp;Huan-Jie Li ,&nbsp;Vince D. Calhoun","doi":"10.1016/j.jneumeth.2024.110207","DOIUrl":"10.1016/j.jneumeth.2024.110207","url":null,"abstract":"<div><h3>Background</h3><p>Real-valued mutual information (MI) has been used in spatial functional network connectivity (FNC) to measure high-order and nonlinear dependence between spatial maps extracted from magnitude-only functional magnetic resonance imaging (fMRI). However, real-valued MI cannot fully capture the group differences in spatial FNC from complex-valued fMRI data with magnitude and phase dependence.</p></div><div><h3>Methods</h3><p>We propose a complete complex-valued MI method according to the chain rule of MI. We fully exploit the dependence among magnitudes and phases of two complex-valued signals using second and fourth-order joint entropies, and propose to use a Gaussian copula transformation with a lower bound property to avoid inaccurate estimation of joint probability density function when computing the joint entropies.</p></div><div><h3>Results</h3><p>The proposed method achieves more accurate MI estimates than the two histogram-based (normal and symbolic approaches) and kernel density estimation methods for simulated signals, and enhances group differences in spatial functional network connectivity for experimental complex-valued fMRI data.</p></div><div><h3>Comparison with existing methods</h3><p>Compared with the simplified complex-valued MI and real-valued MI, the proposed method yields higher MI estimation accuracy, leading to 17.4 % and 145.5 % wider MI ranges, and more significant connectivity differences between healthy controls and schizophrenia patients. A unique connection between executive control network (EC) and right frontal parietal areas, and three additional connections mainly related to EC are detected than the simplified complex-valued MI.</p></div><div><h3>Conclusions</h3><p>With capability in quantifying MI fully and accurately, the proposed complex-valued MI is promising in providing qualified FNC biomarkers for identifying mental disorders such as schizophrenia.</p></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"409 ","pages":"Article 110207"},"PeriodicalIF":2.7,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141468701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated Short-TE and Hadamard-edited Multi-Sequence (ISTHMUS) for advanced MRS","authors":"Steve C.N. Hui ,&nbsp;Saipavitra Murali-Manohar ,&nbsp;Helge J. Zöllner ,&nbsp;Kathleen E. Hupfeld ,&nbsp;Christopher W. Davies-Jenkins ,&nbsp;Aaron T. Gudmundson ,&nbsp;Yulu Song ,&nbsp;Vivek Yedavalli ,&nbsp;Jessica L. Wisnowski ,&nbsp;Borjan Gagoski ,&nbsp;Georg Oeltzschner ,&nbsp;Richard A.E. Edden","doi":"10.1016/j.jneumeth.2024.110206","DOIUrl":"10.1016/j.jneumeth.2024.110206","url":null,"abstract":"<div><h3>Background</h3><p>To examine data quality and reproducibility using ISTHMUS, which has been implemented as the standardized MR spectroscopy sequence for the multi-site Healthy Brain and Child Development (HBCD) study.</p></div><div><h3>Methods</h3><p>ISTHMUS is the consecutive acquisition of short-TE PRESS (32 transients) and long-TE HERCULES (224 transients) data with dual-TE water reference scans. Voxels were positioned in the centrum semiovale, dorsal anterior cingulate cortex, posterior cingulate cortex and bilateral thalamus regions. After acquisition, ISTHMUS data were separated into the PRESS and HERCULES portions for analysis and modeled separately using Osprey. In vivo experiments were performed in 10 healthy volunteers (6 female; 29.5±6.6 years). Each volunteer underwent two scans on the same day. Differences in metabolite measurements were examined. T₂ correction based on the dual-TE water integrals were compared with: 1) T₂ correction based on the default white matter and gray matter T₂ reference values in Osprey and 2) shorter WM and GM T₂ values from recent literature.</p></div><div><h3>Results</h3><p>No significant difference in linewidth was observed between PRESS and HERCULES. Bilateral thalamus spectra had produced significantly higher (p&lt;0.001) linewidth compared to the other three regions. Linewidth measurements were similar between scans, with scan-to-scan differences under 1 Hz for most subjects. Paired t-tests indicated a significant difference only in PRESS NAAG between the two thalamus scans (p=0.002). T₂ correction based on shorter T₂ values showed better agreement to the dual-TE water integral ratio.</p></div><div><h3>Conclusions</h3><p>ISTHMUS facilitated data acquisition and post-processing and reduced operator workload to eliminate potential human error.</p></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"409 ","pages":"Article 110206"},"PeriodicalIF":2.7,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141468702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}