Pub Date : 2024-08-06DOI: 10.1101/2024.08.05.24311520
Ali Azargoonjahromi, Hamide Nasiri, Fatemeh Abutalebian
Resting-state EEG records brain activity when awake but not engaged in tasks, analyzing frequency bands linked to cognitive states. Recent studies on Alzheimer's disease (AD) and frontotemporal dementia (FTD) have found a link between EEG activity, MMSE scores, and age, though some findings are conflicting. This study aimed to explore EEG regional differences among AD and FTD, thereby improving diagnostic strategies. We analyzed EEG recordings from 88 participants in OpenNeuro Dataset ds004504, collected at AHEPA General Hospital using a Nihon Kohden 2100 EEG device. The study used preprocessed recordings, classification algorithms, and cognitive function assessments (MMSE) to identify significant predictors and correlations between EEG measures and cognitive variables. The study revealed that cognitive function, age, and brain activity show distinct relationships in AD and FTD. In AD, MMSE scores significantly predicted brain activity in regions like C3, C4, T4, and Fz, with better cognitive performance linked to higher EEG power in frontal and temporal areas. Conversely, age had a major influence on brain activity in FTD, particularly in regions like C3, P3, O1, and O2, while MMSE scores did not significantly predict brain activity. In FTD, higher EEG power in regions like P3, P4, Cz, and Pz correlated with lower cognitive function. Thus, the findings suggest that EEG biomarkers can enhance diagnostic strategies by highlighting different patterns of brain activity related to cognitive function and age in AD and FTD.
静息状态脑电图记录清醒但未参与任务时的大脑活动，分析与认知状态相关的频段。最近对阿尔茨海默病（AD）和额颞叶痴呆（FTD）的研究发现，脑电图活动、MMSE评分和年龄之间存在联系，但有些研究结果相互矛盾。本研究旨在探索 AD 和 FTD 的脑电图区域差异，从而改进诊断策略。我们分析了 OpenNeuro 数据集 ds004504 中 88 名参与者的脑电图记录，这些记录是在 AHEPA 综合医院使用 Nihon Kohden 2100 脑电图设备收集的。研究使用预处理记录、分类算法和认知功能评估（MMSE）来确定脑电图测量与认知变量之间的重要预测因素和相关性。研究显示，认知功能、年龄和大脑活动在 AD 和 FTD 中显示出不同的关系。在注意力缺失症患者中，MMSE评分可显著预测C3、C4、T4和Fz等区域的大脑活动，认知能力越好，额叶和颞叶区域的脑电图功率越高。相反，年龄对 FTD 患者的大脑活动有很大影响，尤其是在 C3、P3、O1 和 O2 等区域，而 MMSE 分数对大脑活动的预测作用并不明显。在 FTD 患者中，P3、P4、Cz 和 Pz 等区域较高的脑电图功率与较低的认知功能相关。因此，研究结果表明，脑电图生物标记物可以突出显示 AD 和 FTD 中与认知功能和年龄相关的大脑活动的不同模式，从而加强诊断策略。
{"title":"Resting-State EEG Reveals Regional Brain Activity Correlates in Alzheimer's and Frontotemporal Dementia","authors":"Ali Azargoonjahromi, Hamide Nasiri, Fatemeh Abutalebian","doi":"10.1101/2024.08.05.24311520","DOIUrl":"https://doi.org/10.1101/2024.08.05.24311520","url":null,"abstract":"Resting-state EEG records brain activity when awake but not engaged in tasks, analyzing frequency bands linked to cognitive states. Recent studies on Alzheimer's disease (AD) and frontotemporal dementia (FTD) have found a link between EEG activity, MMSE scores, and age, though some findings are conflicting. This study aimed to explore EEG regional differences among AD and FTD, thereby improving diagnostic strategies. We analyzed EEG recordings from 88 participants in OpenNeuro Dataset ds004504, collected at AHEPA General Hospital using a Nihon Kohden 2100 EEG device. The study used preprocessed recordings, classification algorithms, and cognitive function assessments (MMSE) to identify significant predictors and correlations between EEG measures and cognitive variables. The study revealed that cognitive function, age, and brain activity show distinct relationships in AD and FTD. In AD, MMSE scores significantly predicted brain activity in regions like C3, C4, T4, and Fz, with better cognitive performance linked to higher EEG power in frontal and temporal areas. Conversely, age had a major influence on brain activity in FTD, particularly in regions like C3, P3, O1, and O2, while MMSE scores did not significantly predict brain activity. In FTD, higher EEG power in regions like P3, P4, Cz, and Pz correlated with lower cognitive function. Thus, the findings suggest that EEG biomarkers can enhance diagnostic strategies by highlighting different patterns of brain activity related to cognitive function and age in AD and FTD.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141934526","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 : 2024-08-06DOI: 10.1101/2024.08.04.24311473
Palak Patel, Mark A. Bernard, Arjun V. Masurkar
Anxiety is a neuropsychiatric symptom (NPS) of Alzheimer disease (AD) patients which has been studied primarily in prospective and retrospective studies of clinically diagnosed AD. However, this can be confounded by other primary etiologies. Moreover, anxiety has not been comprehensively studied in autopsy-confirmed AD cases across subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia stages. We conducted a retrospective longitudinal analysis of 212 participants with autopsy-confirmed AD, followed from 1986-2013 at the NYU Alzheimer Disease Research Center with staging via the Global Deterioration Scale and NPS assessed via BEHAVE-AD. We found that anxiety varied uniquely with stage and was the most common NPS in SCD and MCI (35-40% prevalence). ApoE4 carriage associated with a higher rate of anxiety only at mild dementia. Anxiety in SCD associated with cerebral amyloid angiopathy and arteriosclerosis on brain autopsy, but there were no such associations with concomitant neuropathology at MCI and mild dementia. Anxiety associated with increased progression rate (~2.5-fold) from SCD to MCI/dementia stages, but not from MCI to dementia. These results suggest an important relationship between anxiety and AD, especially at the preclinical stage. This warrants further study of anxiety as a possible modifiable factor of disease experience and course.
{"title":"Prevalence, risk factors, and impact of anxiety in early Alzheimer disease: a retrospective study of an autopsy-confirmed cohort","authors":"Palak Patel, Mark A. Bernard, Arjun V. Masurkar","doi":"10.1101/2024.08.04.24311473","DOIUrl":"https://doi.org/10.1101/2024.08.04.24311473","url":null,"abstract":"Anxiety is a neuropsychiatric symptom (NPS) of Alzheimer disease (AD) patients which has been studied primarily in prospective and retrospective studies of clinically diagnosed AD. However, this can be confounded by other primary etiologies. Moreover, anxiety has not been comprehensively studied in autopsy-confirmed AD cases across subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia stages. We conducted a retrospective longitudinal analysis of 212 participants with autopsy-confirmed AD, followed from 1986-2013 at the NYU Alzheimer Disease Research Center with staging via the Global Deterioration Scale and NPS assessed via BEHAVE-AD. We found that anxiety varied uniquely with stage and was the most common NPS in SCD and MCI (35-40% prevalence). ApoE4 carriage associated with a higher rate of anxiety only at mild dementia. Anxiety in SCD associated with cerebral amyloid angiopathy and arteriosclerosis on brain autopsy, but there were no such associations with concomitant neuropathology at MCI and mild dementia. Anxiety associated with increased progression rate (~2.5-fold) from SCD to MCI/dementia stages, but not from MCI to dementia. These results suggest an important relationship between anxiety and AD, especially at the preclinical stage. This warrants further study of anxiety as a possible modifiable factor of disease experience and course.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141934507","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}
Objective: Youth male athletes show changes in resting-state causal brain connectivity following subacute concussion; however, little is known about how concussion alters causal brain connectivity in female youth. In this study, we compared resting-state causal brain connectivity in healthy and subconcussed females. Materials and methods: Data from 11 concussed and 15 healthy control female athletes were included in this study. Five minutes of resting state eyes-closed EEG data were collected from all participants. SCAT5 data were also collected from all concussed participants. Causal connectivity was calculated from EEG source data. Network topology was evaluated using the degree assortativity coefficient, a summary statistic describing network structure of information flow between source locations. Results: There were three main results: 1) a qualitative difference in the spatial pattern of the most active connections, marked by posterior connectivity shifting in the concussed group, 2) an increase in the magnitude of connectivity in the concussed group, and 3) no significant difference in degree assortativity between the concussed and control groups. Conclusion: Causal connectivity changes following concussion in females do not follow the same trends reported in males. These findings suggest a potential sex difference in injury response and may have implications for recovery.
{"title":"Resting-state causal brain connectivity in youth female athletes suggest sex-related differences following subacute concussion.","authors":"Julianne McLeod, Sahar Sattari, Dionissios T. Hristopulos, Karun Thanjavur, Naznin Virji-Babul","doi":"10.1101/2024.08.04.24311356","DOIUrl":"https://doi.org/10.1101/2024.08.04.24311356","url":null,"abstract":"Objective: Youth male athletes show changes in resting-state causal brain connectivity following subacute concussion; however, little is known about how concussion alters causal brain connectivity in female youth. In this study, we compared resting-state causal brain connectivity in healthy and subconcussed females. Materials and methods: Data from 11 concussed and 15 healthy control female athletes were included in this study. Five minutes of resting state eyes-closed EEG data were collected from all participants. SCAT5 data were also collected from all concussed participants. Causal connectivity was calculated from EEG source data. Network topology was evaluated using the degree assortativity coefficient, a summary statistic describing network structure of information flow between source locations.\u0000Results: There were three main results: 1) a qualitative difference in the spatial pattern of the most active connections, marked by posterior connectivity shifting in the concussed group, 2) an increase in the magnitude of connectivity in the concussed group, and 3) no significant difference in degree assortativity between the concussed and control groups.\u0000Conclusion: Causal connectivity changes following concussion in females do not follow the same trends reported in males. These findings suggest a potential sex difference in injury response and may have implications for recovery.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141934505","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 : 2024-08-05DOI: 10.1101/2024.08.04.24311483
Qiang Yu, Richard A Kwiatek, Perter Del Fante, Anya Bonner, Vince D Calhoun, Grant A Bateman, Takashi Yamamura, Zack Y Shan
Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex and debilitating illness with an unknown pathogenesis. Although post-infectious (PI-ME/CFS) and gradual onset ME/CFS (GO-ME/CFS) manifest similar symptoms, it has long been suspected that different disease processes underlie them. However, the lack of biological evidence has left this question unanswered. In this study, we recruited PI-ME/CFS and GO-ME/CFS patients based on consensus diagnoses made by two experienced clinicians and compared their diffusion MRI features with those of rigorously matched healthy controls (HCs) with sedentary lifestyles. PI-ME/CFS patients showed significantly higher axial diffusivities (ADs) in several association and projection fibres compared to HCs. Higher AD values in PI-ME/CFS were significantly related to worse physical summary scores. In contrast, GO-ME/CFS patients exhibited significantly decreased ADs in the corpus callosum. Lower AD values in GO-ME/CFS patients were significantly associated with lower mental summary scores in commissural and projection fibres. Distinct patterns of AD alterations in PI-ME/CFS and GO-ME/CFS provide neurophysiological evidence of different disease processes and highlight the heterogeneities of ME/CFS. These results also help explain inconsistent findings in previous ME/CFS studies and guide future intervention design.
{"title":"Opposite white matter abnormalities in post-infectious vs. gradual onset chronic fatigue syndrome revealed by diffusion MRI","authors":"Qiang Yu, Richard A Kwiatek, Perter Del Fante, Anya Bonner, Vince D Calhoun, Grant A Bateman, Takashi Yamamura, Zack Y Shan","doi":"10.1101/2024.08.04.24311483","DOIUrl":"https://doi.org/10.1101/2024.08.04.24311483","url":null,"abstract":"Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex and debilitating illness with an unknown pathogenesis. Although post-infectious (PI-ME/CFS) and gradual onset ME/CFS (GO-ME/CFS) manifest similar symptoms, it has long been suspected that different disease processes underlie them. However, the lack of biological evidence has left this question unanswered. In this study, we recruited PI-ME/CFS and GO-ME/CFS patients based on consensus diagnoses made by two experienced clinicians and compared their diffusion MRI features with those of rigorously matched healthy controls (HCs) with sedentary lifestyles. PI-ME/CFS patients showed significantly higher axial diffusivities (ADs) in several association and projection fibres compared to HCs. Higher AD values in PI-ME/CFS were significantly related to worse physical summary scores. In contrast, GO-ME/CFS patients exhibited significantly decreased ADs in the corpus callosum. Lower AD values in GO-ME/CFS patients were significantly associated with lower mental summary scores in commissural and projection fibres. Distinct patterns of AD alterations in PI-ME/CFS and GO-ME/CFS provide neurophysiological evidence of different disease processes and highlight the heterogeneities of ME/CFS. These results also help explain inconsistent findings in previous ME/CFS studies and guide future intervention design.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141934508","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 : 2024-08-05DOI: 10.1101/2024.08.05.24311482
Tengfei Li, Jie Chen, Bingxin Zhao, Hui Chen, Changzheng Yuan, Gwenn A. Garden, Kelly S. Giovanello, Guorong Wu, Hongtu Zhu
Recent studies have shed light on the complex nonlinear changes in brain functions across the lifespan, demonstrating the variability in the individual cognitive and neural development during aging. This variability is influenced by factors such as sex, age, genetics, and modifiable health risk factors (MHRFs), which collectively shape unique patterns of brain functional connectivities (FCs) across different regions. However, their joint effects and underlying mechanisms remain unclear. We conduct a comprehensive analysis to jointly examine the association of common risk factors with brain functional measures, using data from 36,630 UK Biobank participants aged 44-81. Participants were assessed for age, sex, Apolipoprotein E (APOE) genotypes, ten common MHRFs, and brain FCs measured via resting-state functional magnetic resonance imaging. Using the fine-grained HCP-MMP parcellation and Ji-12 network atlases, we identified 91 associations with network functional connectivity (NFC) and 102 associations with network edge strength (NES) measures. Hypertension, BMI, and education emerged as the top three influential factors across networks. Notably, a negative interaction between sex and APOE4 genotype was observed, with male APOE4 carriers showing greater reductions in NFC between the cingulo-opercular (CON) and posterior multimodal (PMN) networks. Additionally, a negative age-BMI interaction on NES between the visual and dorsal attention (DAN) networks suggested that higher BMI accelerates the decline in visual-DAN connectivity. A positive age-hypertension interaction between the frontoparietal (FPN) and default mode (DMN) networks indicated a more rapid decrease in functional segregation associated with hypertension. We also identified sex-education interactions, showing more pronounced positive effects on CON-FPN networks in females and PMN-DMN networks in males. Further interactions involving sex and other MHRFs, such as smoking, alcohol consumption, diabetes, and BMI, revealed that smoking, alcohol, and BMI had more detrimental effects in males, while diabetes had a more pronounced negative impact in females within specific networks. These findings underscore the necessity of jointly considering sex, age, genetic factors, and MHRFs to accurately delineate the multifactorial alterations in the FCs during brain aging.
{"title":"The Interaction Effects of Age, Sex, APOE and Common Health Risk Factors on Human Brain Functions","authors":"Tengfei Li, Jie Chen, Bingxin Zhao, Hui Chen, Changzheng Yuan, Gwenn A. Garden, Kelly S. Giovanello, Guorong Wu, Hongtu Zhu","doi":"10.1101/2024.08.05.24311482","DOIUrl":"https://doi.org/10.1101/2024.08.05.24311482","url":null,"abstract":"Recent studies have shed light on the complex nonlinear changes in brain functions across the lifespan, demonstrating the variability in the individual cognitive and neural development during aging. This variability is influenced by factors such as sex, age, genetics, and modifiable health risk factors (MHRFs), which collectively shape unique patterns of brain functional connectivities (FCs) across different regions. However, their joint effects and underlying mechanisms remain unclear. We conduct a comprehensive analysis to jointly examine the association of common risk factors with brain functional measures, using data from 36,630 UK Biobank participants aged 44-81. Participants were assessed for age, sex, Apolipoprotein E (APOE) genotypes, ten common MHRFs, and brain FCs measured via resting-state functional magnetic resonance imaging. Using the fine-grained HCP-MMP parcellation and Ji-12 network atlases, we identified 91 associations with network functional connectivity (NFC) and 102 associations with network edge strength (NES) measures. Hypertension, BMI, and education emerged as the top three influential factors across networks. Notably, a negative interaction between sex and APOE4 genotype was observed, with male APOE4 carriers showing greater reductions in NFC between the cingulo-opercular (CON) and posterior multimodal (PMN) networks. Additionally, a negative age-BMI interaction on NES between the visual and dorsal attention (DAN) networks suggested that higher BMI accelerates the decline in visual-DAN connectivity. A positive age-hypertension interaction between the frontoparietal (FPN) and default mode (DMN) networks indicated a more rapid decrease in functional segregation associated with hypertension. We also identified sex-education interactions, showing more pronounced positive effects on CON-FPN networks in females and PMN-DMN networks in males. Further interactions involving sex and other MHRFs, such as smoking, alcohol consumption, diabetes, and BMI, revealed that smoking, alcohol, and BMI had more detrimental effects in males, while diabetes had a more pronounced negative impact in females within specific networks. These findings underscore the necessity of jointly considering sex, age, genetic factors, and MHRFs to accurately delineate the multifactorial alterations in the FCs during brain aging.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141968903","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 : 2024-08-05DOI: 10.1101/2024.08.04.24311471
Aditya Vedantam, Mahmudur Rahman, Sakib Salam, Anjishnu Banerjee, Kajana Satkunendrarajah, Matthew D Budde, Timothy B Meier
Introduction Diagnosis of degenerative cervical myelopathy (DCM) is primarily based on clinical evaluation and evidence of cervical spinal cord compression on conventional MRI. However, delays in diagnosis are common in DCM and there is a need for additional objective assessments of spinal cord structure and function. Serum proteins are increasingly being used as biomarkers for neurological disorders and are promising targets for biomarker discovery in DCM. The objective of this study was to profile serum protein biomarkers in DCM and determine if serum proteins can aid diagnosis and prognosis in DCM. Methods Patients with a clinical diagnosis of DCM and scheduled to undergo decompressive surgery were prospectively enrolled from July 2022 to August 2023. Serum was obtained prior to surgery and at 3 months after surgery. Serum neuronal and inflammatory proteins were quantified using ultrasensitive single-molecular array technology. Serum biomarker concentrations were compared between DCM patients and age- and sex-matched healthy controls. Robust logistic regression was used to determine the panel of serum biomarkers that best differentiated DCM and controls. Serum biomarkers were also related to pre- and post-surgical functional measurements using linear regression. Results Twenty DCM patients (median age 70 years, 10 females) and 10 healthy controls (median age 65 years, 5 females) were enrolled. Pre-surgical NfL (30.2 vs 11.2 pg/ml, p=0.01) and IL-6 (2.9 vs 1.2, p=0.003) was significantly higher in DCM patients compared to controls. Pre-surgical NfL, IL-6 and BDNF best differentiated DCM and controls (p<0.001). At 3 months after surgery, significant increase in serum BDNF (p=0.001), AB-42 (p=0.042) and TNFa (p=0.007) were noted. Pre-surgical serum NfL was significantly associated improvement in pinch strength after surgery (p<0.05). Inflammatory biomarkers were linked to improvement in the neck pain-related disability and upper limb function assessed by the QuickDASH. Conclusion A pre-surgical serum panel of NfL, IL-6 and BDNF may aid in the diagnosis of DCM. Serum NfL is elevated in DCM and is associated with improvement in post-surgical objective measures of upper limb function. Pre-surgical serum neuronal and inflammatory biomarkers predict early post-surgical functional outcomes in DCM.
{"title":"Serum protein biomarkers for degenerative cervical myelopathy: a prospective pilot study","authors":"Aditya Vedantam, Mahmudur Rahman, Sakib Salam, Anjishnu Banerjee, Kajana Satkunendrarajah, Matthew D Budde, Timothy B Meier","doi":"10.1101/2024.08.04.24311471","DOIUrl":"https://doi.org/10.1101/2024.08.04.24311471","url":null,"abstract":"Introduction\u0000Diagnosis of degenerative cervical myelopathy (DCM) is primarily based on clinical evaluation and evidence of cervical spinal cord compression on conventional MRI. However, delays in diagnosis are common in DCM and there is a need for additional objective assessments of spinal cord structure and function. Serum proteins are increasingly being used as biomarkers for neurological disorders and are promising targets for biomarker discovery in DCM. The objective of this study was to profile serum protein biomarkers in DCM and determine if serum proteins can aid diagnosis and prognosis in DCM. Methods\u0000Patients with a clinical diagnosis of DCM and scheduled to undergo decompressive surgery were prospectively enrolled from July 2022 to August 2023. Serum was obtained prior to surgery and at 3 months after surgery. Serum neuronal and inflammatory proteins were quantified using ultrasensitive single-molecular array technology. Serum biomarker concentrations were compared between DCM patients and age- and sex-matched healthy controls. Robust logistic regression was used to determine the panel of serum biomarkers that best differentiated DCM and controls. Serum biomarkers were also related to pre- and post-surgical functional measurements using linear regression. Results\u0000Twenty DCM patients (median age 70 years, 10 females) and 10 healthy controls (median age 65 years, 5 females) were enrolled. Pre-surgical NfL (30.2 vs 11.2 pg/ml, p=0.01) and IL-6 (2.9 vs 1.2, p=0.003) was significantly higher in DCM patients compared to controls. Pre-surgical NfL, IL-6 and BDNF best differentiated DCM and controls (p<0.001). At 3 months after surgery, significant increase in serum BDNF (p=0.001), AB-42 (p=0.042) and TNFa (p=0.007) were noted. Pre-surgical serum NfL was significantly associated improvement in pinch strength after surgery (p<0.05). Inflammatory biomarkers were linked to improvement in the neck pain-related disability and upper limb function assessed by the QuickDASH. Conclusion\u0000A pre-surgical serum panel of NfL, IL-6 and BDNF may aid in the diagnosis of DCM. Serum NfL is elevated in DCM and is associated with improvement in post-surgical objective measures of upper limb function. Pre-surgical serum neuronal and inflammatory biomarkers predict early post-surgical functional outcomes in DCM.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141934449","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 : 2024-08-03DOI: 10.1101/2024.08.02.24311397
Afolabi Salami Alausa, Jose M Sanchez-Bornot, Abdoreza Asadpour, Paula L McClean, KongFatt Wong-Lin
Making accurate diagnosis of Alzheimer's disease (AD) is crucial for effective treatment and management. Although deep learning has been applied to AD classification, it is typically performed at group level, the data used are not sufficiently heterogeneous and comprehensive, and decision confidence is not evaluated at individual (single patient) level. This paper proposed a more practical deep learning approach that not only detects AD stages of individuals, but also provides its corresponding confidence estimation. In particular, in addition to a convolutional neural network (CNN), we incorporated a softmax confidence metric based on the network's output activity to evaluate its classification confidence. Further, we applied this approach to a heterogeneous and comprehensive data that comprised cognitive and functional assessments, tau-PET and MRI neuroimaging, medical/family history, demographic, and APoE genotype. Importantly, we utilised leave-one-out cross-validation to train the CNN and classify an individual's healthy control, mild cognitive impairment or AD state, while concurrently estimating each output decision's confidence. We showed that, over different confidence softmax temperature values, CNN could attain classification accuracies at 83-85% for the three classes while having robust confidence scores of 78-83%. Further improvement in confidence breakdown was achieved using the optimal temperature value in confidence evaluation, with higher confidence scores for correct than error decisions. Overall, the computed classification confidence of an individual may aid clinicians and other stakeholders in understanding the reliability of the model's decision outcome and offer better trust. The implication of this work may extend to other classification applications, in which the confidence level of a single deep learning-based decision can be evaluated.
{"title":"Alzheimer's Disease Classification Confidence of Individuals using Deep Learning on Heterogeneous Data","authors":"Afolabi Salami Alausa, Jose M Sanchez-Bornot, Abdoreza Asadpour, Paula L McClean, KongFatt Wong-Lin","doi":"10.1101/2024.08.02.24311397","DOIUrl":"https://doi.org/10.1101/2024.08.02.24311397","url":null,"abstract":"Making accurate diagnosis of Alzheimer's disease (AD) is crucial for effective treatment and management. Although deep learning has been applied to AD classification, it is typically performed at group level, the data used are not sufficiently heterogeneous and comprehensive, and decision confidence is not evaluated at individual (single patient) level. This paper proposed a more practical deep learning approach that not only detects AD stages of individuals, but also provides its corresponding confidence estimation. In particular, in addition to a convolutional neural network (CNN), we incorporated a softmax confidence metric based on the network's output activity to evaluate its classification confidence. Further, we applied this approach to a heterogeneous and comprehensive data that comprised cognitive and functional assessments, tau-PET and MRI neuroimaging, medical/family history, demographic, and APoE genotype. Importantly, we utilised leave-one-out cross-validation to train the CNN and classify an individual's healthy control, mild cognitive impairment or AD state, while concurrently estimating each output decision's confidence. We showed that, over different confidence softmax temperature values, CNN could attain classification accuracies at 83-85% for the three classes while having robust confidence scores of 78-83%. Further improvement in confidence breakdown was achieved using the optimal temperature value in confidence evaluation, with higher confidence scores for correct than error decisions. Overall, the computed classification confidence of an individual may aid clinicians and other stakeholders in understanding the reliability of the model's decision outcome and offer better trust. The implication of this work may extend to other classification applications, in which the confidence level of a single deep learning-based decision can be evaluated.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141934509","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 : 2024-08-02DOI: 10.1101/2024.08.01.24311334
PengPeng Niu, Rui Zhang, Shuo Li, YuSheng Li
Objective: Through the utilization of the data specifically related to early-onset ischemic stroke, we aimed to investigate the causal effects of migraine and its subtypes on the risk of early-onset ischemic stroke using the two-sample Mendelian randomization method. Methods: Genetic instrumental variables were acquired from two sources with the largest sample sizes available. Summary data for early-onset ischemic stroke was acquired from a study encompassing individuals aged 18 to 59 years, comprising 16,730 cases and 599,237 non-stroke controls. The random-effects inverse variance weighted method was used as the primary analysis approach. Results: The Mendelian randomization analysis revealed no association between overall migraine and migraine without aura with the risk of early-onset ischemic stroke. However, migraine with aura showed a suggestive association with an elevated risk of early-onset ischemic stroke, with odds ratios of 1.114 (95% confidence interval = 1.005 to 1.236, p-value = 0.040) and 1.062 (95% confidence interval = 1.002 to 1.126, p-value = 0.042) based on instruments from two independent sources. The odds ratio was 1.074 (95% confidence interval = 1.022 to 1.130, p-value = 0.005) based on instruments from both two sources. No evidence of heterogeneity or horizontal pleiotropy was found. Furthermore, a positive genetic correlation was found between migraine with aura and early-onset ischemic stroke (genetic correlation = 0.208, 95% confidence interval = 0.038 to 0.377, p-value = 0.016). By contrast, migraine with aura was not related to ischemic stroke of all adults. Conclusion: This study provides evidence of a causal relationship between migraine with aura and the risk of early-onset ischemic stroke.
{"title":"Migraine and Early-onset Ischemic Stroke: A Mendelian Randomization Study","authors":"PengPeng Niu, Rui Zhang, Shuo Li, YuSheng Li","doi":"10.1101/2024.08.01.24311334","DOIUrl":"https://doi.org/10.1101/2024.08.01.24311334","url":null,"abstract":"Objective: Through the utilization of the data specifically related to early-onset ischemic stroke, we aimed to investigate the causal effects of migraine and its subtypes on the risk of early-onset ischemic stroke using the two-sample Mendelian randomization method.\u0000Methods: Genetic instrumental variables were acquired from two sources with the largest sample sizes available. Summary data for early-onset ischemic stroke was acquired from a study encompassing individuals aged 18 to 59 years, comprising 16,730 cases and 599,237 non-stroke controls. The random-effects inverse variance weighted method was used as the primary analysis approach.\u0000Results: The Mendelian randomization analysis revealed no association between overall migraine and migraine without aura with the risk of early-onset ischemic stroke. However, migraine with aura showed a suggestive association with an elevated risk of early-onset ischemic stroke, with odds ratios of 1.114 (95% confidence interval = 1.005 to 1.236, p-value = 0.040) and 1.062 (95% confidence interval = 1.002 to 1.126, p-value = 0.042) based on instruments from two independent sources. The odds ratio was 1.074 (95% confidence interval = 1.022 to 1.130, p-value = 0.005) based on instruments from both two sources. No evidence of heterogeneity or horizontal pleiotropy was found. Furthermore, a positive genetic correlation was found between migraine with aura and early-onset ischemic stroke (genetic correlation = 0.208, 95% confidence interval = 0.038 to 0.377, p-value = 0.016). By contrast, migraine with aura was not related to ischemic stroke of all adults. Conclusion: This study provides evidence of a causal relationship between migraine with aura and the risk of early-onset ischemic stroke.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141884980","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 : 2024-08-02DOI: 10.1101/2024.07.31.24311276
Taylor G Hobbs, Charles Greenspon, Ceci Verbaarschot, Giacomo Valle, Michael Boninger, Sliman J Bensmaia, Robert A Gaunt
Objective. Intracortical microstimulation (ICMS) of human somatosensory cortex evokes tactile percepts that people describe as originating from their own body, but are not always described as feeling natural. It remains unclear whether stimulation parameters such as amplitude, frequency, and spatiotemporal patterns across electrodes can be chosen to increase the naturalness of these artificial tactile percepts. Approach. In this study, we investigated whether biomimetic stimulation patterns — ICMS patterns that reproduce essential features of natural neural activity — increased the perceived naturalness of ICMS-evoked sensations compared to a non-biomimetic pattern in three people with cervical spinal cord injuries. All participants had electrode arrays implanted in their somatosensory cortices. Rather than qualitatively asking which pattern felt more natural, participants directly compared natural residual percepts, delivered by mechanical indentation on a sensate region of their hand, to artificial percepts evoked by ICMS and were asked whether linear non-biomimetic or biomimetic stimulation felt most like the mechanical indentation. Main Results. We show that simple biomimetic ICMS, which modulated the stimulation amplitude on a single electrode, was perceived as being more like a mechanical indentation reference on 32% of the electrodes. We also tested an advanced biomimetic stimulation scheme that captured more of the spatiotemporal dynamics of cortical activity using co-modulated stimulation amplitudes and frequencies across four electrodes. Here, ICMS felt more like the mechanical reference for 75% of the electrode groups. Finally, biomimetic stimulation required less stimulus charge than their non-biomimetic counterparts. Significance. We conclude that ICMS encoding schemes that mimic naturally occurring neural spatiotemporal activation patterns in somatosensory cortex feel more like an actual touch than non-biomimetic encoding schemes. This also suggests that using key elements of neuronal activity can be a useful conceptual guide to constrain the large stimulus parameter space when designing future stimulation strategies.
{"title":"Biomimetic stimulation patterns drive natural artificial touch percepts using intracortical microstimulation in humans","authors":"Taylor G Hobbs, Charles Greenspon, Ceci Verbaarschot, Giacomo Valle, Michael Boninger, Sliman J Bensmaia, Robert A Gaunt","doi":"10.1101/2024.07.31.24311276","DOIUrl":"https://doi.org/10.1101/2024.07.31.24311276","url":null,"abstract":"Objective. Intracortical microstimulation (ICMS) of human somatosensory cortex evokes tactile percepts that people describe as originating from their own body, but are not always described as feeling natural. It remains unclear whether stimulation parameters such as amplitude, frequency, and spatiotemporal patterns across electrodes can be chosen to increase the naturalness of these artificial tactile percepts. Approach. In this study, we investigated whether biomimetic stimulation patterns — ICMS patterns that reproduce essential features of natural neural activity — increased the perceived naturalness of ICMS-evoked sensations compared to a non-biomimetic pattern in three people with cervical spinal cord injuries. All participants had electrode arrays implanted in their somatosensory cortices. Rather than qualitatively asking which pattern felt more natural, participants directly compared natural residual percepts, delivered by mechanical indentation on a sensate region of their hand, to artificial percepts evoked by ICMS and were asked whether linear non-biomimetic or biomimetic stimulation felt most like the mechanical indentation. Main Results. We show that simple biomimetic ICMS, which modulated the stimulation amplitude on a single electrode, was perceived as being more like a mechanical indentation reference on 32% of the electrodes. We also tested an advanced biomimetic stimulation scheme that captured more of the spatiotemporal dynamics of cortical activity using co-modulated stimulation amplitudes and frequencies across four electrodes. Here, ICMS felt more like the mechanical reference for 75% of the electrode groups. Finally, biomimetic stimulation required less stimulus charge than their non-biomimetic counterparts. Significance. We conclude that ICMS encoding schemes that mimic naturally occurring neural spatiotemporal activation patterns in somatosensory cortex feel more like an actual touch than non-biomimetic encoding schemes. This also suggests that using key elements of neuronal activity can be a useful conceptual guide to constrain the large stimulus parameter space when designing future stimulation strategies.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141934450","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 : 2024-08-02DOI: 10.1101/2024.08.01.24311354
Anouk van der Heide, Maaike Wessel, Danae Papadopetraki, Dirk E.M. Geurts, Teije H. van Prooije, Frank Gommans, Bastiaan R. Bloem, Michiel F. Dirkx, Rick C. Helmich
Objective: Parkinson's disease (PD) resting tremor is thought to be initiated in the basal ganglia and amplified in the cerebello-thalamo-cortical circuit. Since stress worsens tremor, the noradrenergic system may play a role in amplifying tremor. We tested if and how propranolol, a non-selective beta-adrenergic receptor antagonist, reduces PD tremor, and whether or not this effect is specific to stressful conditions. Methods: In a cross-over, double-blind intervention study, participants with PD resting tremor received propranolol (40mg, single dose) or placebo (counter-balanced) on two different days. During both days, we assessed tremor severity (with accelerometry) and tremor-related brain activity (with functional Magnetic Resonance Imaging; fMRI), as well as heart rate and pupil diameter, while subjects performed a stressful cognitive load task that has been linked to the noradrenergic system. We tested for effects of drug (propranolol vs. placebo) and stress (cognitive load vs. rest) on tremor power and tremor-related brain activity. Results: We included 27 PD patients with clear resting tremor. Tremor power significantly increased during cognitive load vs. rest (F(1,19)=13.8; p=.001; ηp2=0.42) and decreased by propranolol vs. placebo (F(1,19)=6.4; p=.02; ηp2=0.25), but there was no interaction. We observed task-related brain activity in a stress-sensitive cognitive control network, and tremor power-related activity in the cerebello-thalamo-cortical circuit. Propranolol significantly reduced tremor-related activity in the motor cortex compared to placebo (F(1,21)=5.3; p=.03; ηp2=0.20), irrespective of cognitive load. Interpretation: Our findings indicate that the noradrenergic system has a general, context-independent role in amplifying PD tremor at the level of the primary motor cortex.
{"title":"Propranolol reduces Parkinson's tremor and inhibits tremor-related activity in the motor cortex: a placebo-controlled crossover trial","authors":"Anouk van der Heide, Maaike Wessel, Danae Papadopetraki, Dirk E.M. Geurts, Teije H. van Prooije, Frank Gommans, Bastiaan R. Bloem, Michiel F. Dirkx, Rick C. Helmich","doi":"10.1101/2024.08.01.24311354","DOIUrl":"https://doi.org/10.1101/2024.08.01.24311354","url":null,"abstract":"Objective: Parkinson's disease (PD) resting tremor is thought to be initiated in the basal ganglia and amplified in the cerebello-thalamo-cortical circuit. Since stress worsens tremor, the noradrenergic system may play a role in amplifying tremor. We tested if and how propranolol, a non-selective beta-adrenergic receptor antagonist, reduces PD tremor, and whether or not this effect is specific to stressful conditions.\u0000Methods: In a cross-over, double-blind intervention study, participants with PD resting tremor received propranolol (40mg, single dose) or placebo (counter-balanced) on two different days. During both days, we assessed tremor severity (with accelerometry) and tremor-related brain activity (with functional Magnetic Resonance Imaging; fMRI), as well as heart rate and pupil diameter, while subjects performed a stressful cognitive load task that has been linked to the noradrenergic system. We tested for effects of drug (propranolol vs. placebo) and stress (cognitive load vs. rest) on tremor power and tremor-related brain activity.\u0000Results: We included 27 PD patients with clear resting tremor. Tremor power significantly increased during cognitive load vs. rest (F(1,19)=13.8; p=.001; ηp<sup>2</sup>=0.42) and decreased by propranolol vs. placebo (F(1,19)=6.4; p=.02; ηp<sup>2</sup>=0.25), but there was no interaction. We observed task-related brain activity in a stress-sensitive cognitive control network, and tremor power-related activity in the cerebello-thalamo-cortical circuit. Propranolol significantly reduced tremor-related activity in the motor cortex compared to placebo (F(1,21)=5.3; p=.03; ηp<sup>2</sup>=0.20), irrespective of cognitive load.\u0000Interpretation: Our findings indicate that the noradrenergic system has a general, context-independent role in amplifying PD tremor at the level of the primary motor cortex.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141884979","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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