Pub Date : 2024-09-06DOI: 10.3389/fnins.2024.1378498
Robin M. Voigt, Bichun Ouyang, Ali Keshavarzian
IntroductionAlzheimer’s disease (AD) prevalence has increased in the last century which can be attributed to increased lifespan, but environment is also important. Exposure to artificial light at night is one environmental factor that may influence AD.MethodsThis study evaluated the relationship between outdoor nighttime light exposure and AD prevalence in the United States using satellite acquired outdoor nighttime light intensity and Medicare data.ResultsHigher outdoor nighttime light was associated with higher prevalence of AD. While atrial fibrillation, diabetes, hyperlipidemia, hypertension, and stroke were associated more strongly with AD prevalence than nighttime light intensity, nighttime light was more strongly associated with AD prevalence than alcohol abuse, chronic kidney disease, depression, heart failure, and obesity. Startlingly, nighttime light exposure more strongly associated with AD prevalence in those under the age of 65 than any other disease factor examined.DiscussionThese data suggest light exposure at night may influence AD, but additional studies are needed.
{"title":"Outdoor nighttime light exposure (light pollution) is associated with Alzheimer’s disease","authors":"Robin M. Voigt, Bichun Ouyang, Ali Keshavarzian","doi":"10.3389/fnins.2024.1378498","DOIUrl":"https://doi.org/10.3389/fnins.2024.1378498","url":null,"abstract":"IntroductionAlzheimer’s disease (AD) prevalence has increased in the last century which can be attributed to increased lifespan, but environment is also important. Exposure to artificial light at night is one environmental factor that may influence AD.MethodsThis study evaluated the relationship between outdoor nighttime light exposure and AD prevalence in the United States using satellite acquired outdoor nighttime light intensity and Medicare data.ResultsHigher outdoor nighttime light was associated with higher prevalence of AD. While atrial fibrillation, diabetes, hyperlipidemia, hypertension, and stroke were associated more strongly with AD prevalence than nighttime light intensity, nighttime light was more strongly associated with AD prevalence than alcohol abuse, chronic kidney disease, depression, heart failure, and obesity. Startlingly, nighttime light exposure more strongly associated with AD prevalence in those under the age of 65 than any other disease factor examined.DiscussionThese data suggest light exposure at night may influence AD, but additional studies are needed.","PeriodicalId":12639,"journal":{"name":"Frontiers in Neuroscience","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.3389/fnins.2024.1434508
Shawn Fletcher Sorrells
Once we are born, the number and location of nerve cells in most parts of the brain remain unchanged. These types of structural changes are therefore a significant form of flexibility for the neural circuits where they occur. In humans, the postnatal birth of neurons is limited; however, neurons do continue to migrate into some brain regions throughout infancy and even into adolescence. In human infants, multiple migratory pathways deliver interneurons to destinations across the frontal and temporal lobe cortex. Shorter-range migration of excitatory neurons also appears to continue during adolescence, particularly near the amygdala paralaminar nucleus, a region that follows a delayed trajectory of growth from infancy to adulthood. The significance of the timing for when different brain regions recruit new neurons through these methods is unknown; however, both processes of protracted migration and maturation are prominent in humans. Mechanisms like these that reconfigure neuronal circuits are a substrate for critical periods of plasticity and could contribute to distinctive circuit functionality in human brains.
{"title":"Which neurodevelopmental processes continue in humans after birth?","authors":"Shawn Fletcher Sorrells","doi":"10.3389/fnins.2024.1434508","DOIUrl":"https://doi.org/10.3389/fnins.2024.1434508","url":null,"abstract":"Once we are born, the number and location of nerve cells in most parts of the brain remain unchanged. These types of structural changes are therefore a significant form of flexibility for the neural circuits where they occur. In humans, the postnatal birth of neurons is limited; however, neurons do continue to migrate into some brain regions throughout infancy and even into adolescence. In human infants, multiple migratory pathways deliver interneurons to destinations across the frontal and temporal lobe cortex. Shorter-range migration of excitatory neurons also appears to continue during adolescence, particularly near the amygdala paralaminar nucleus, a region that follows a delayed trajectory of growth from infancy to adulthood. The significance of the timing for when different brain regions recruit new neurons through these methods is unknown; however, both processes of protracted migration and maturation are prominent in humans. Mechanisms like these that reconfigure neuronal circuits are a substrate for critical periods of plasticity and could contribute to distinctive circuit functionality in human brains.","PeriodicalId":12639,"journal":{"name":"Frontiers in Neuroscience","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.3389/fnins.2024.1465701
Jessica M. Carpenter, Sarah N. Hughes, Nikolay M. Filipov
Gulf War Illness (GWI) affects nearly 30% of veterans from the 1990–1991 Gulf War (GW) and is a multi-symptom illness with many neurological effects attributed to in-theater wartime chemical overexposures. Brain-focused studies have revealed persistent structural and functional alterations in veterans with GWI, including reduced volumes, connectivity, and signaling that correlate with poor cognitive and motor performance. GWI symptomology components have been recapitulated in rodent models as behavioral, neurochemical, and neuroinflammatory aberrations. However, preclinical structural imaging studies remain limited. This study aimed to characterize the progression of brain structural alterations over the course of 12 months in two established preclinical models of GWI. In the PB/PM model, male C57BL/6 J mice (8–9 weeks) received daily exposure to the nerve agent prophylactic pyridostigmine bromide (PB) and the pyrethroid insecticide permethrin (PM) for 10 days. In the PB/DEET/CORT/DFP model, mice received daily exposure to PB and the insect repellent DEET (days 1–14) and corticosterone (CORT; days 7–14). On day 15, mice received a single injection of the sarin surrogate diisopropylfluorophosphate (DFP). Using a Varian 7 T Bore MRI System, structural (sagittal T2-weighted) scans were performed at 6-, 9-, and 12-months post GWI exposures. Regions of interest, including total brain, ventricles, cortex, hippocampus, cerebellum, and brainstem were delineated in the open source Aedes Toolbox in MATLAB, followed by brain volumetric and cortical thickness analyses in ImageJ. Limited behavioral testing 1 month after the last MRI was also performed. The results of this study compare similarities and distinctions between these exposure paradigms and aid in the understanding of GWI pathogenesis. Major similarities among the models include relative ventricular enlargement and reductions in hippocampal volumes with age. Key differences in the PB/DEET/CORT/DFP model included reduced brainstem volumes and an early and persistent loss of total brain volume, while the PB/PM model produced reductions in cortical thickness with age. Behaviorally, at 13 months, motor function was largely preserved in both models. However, the GWI mice in the PB/DEET/CORT/DFP model exhibited an elevation in anxiety-like behavior.
{"title":"Longitudinal evaluation of structural brain alterations in two established mouse models of Gulf War Illness","authors":"Jessica M. Carpenter, Sarah N. Hughes, Nikolay M. Filipov","doi":"10.3389/fnins.2024.1465701","DOIUrl":"https://doi.org/10.3389/fnins.2024.1465701","url":null,"abstract":"Gulf War Illness (GWI) affects nearly 30% of veterans from the 1990–1991 Gulf War (GW) and is a multi-symptom illness with many neurological effects attributed to in-theater wartime chemical overexposures. Brain-focused studies have revealed persistent structural and functional alterations in veterans with GWI, including reduced volumes, connectivity, and signaling that correlate with poor cognitive and motor performance. GWI symptomology components have been recapitulated in rodent models as behavioral, neurochemical, and neuroinflammatory aberrations. However, preclinical structural imaging studies remain limited. This study aimed to characterize the progression of brain structural alterations over the course of 12 months in two established preclinical models of GWI. In the PB/PM model, male C57BL/6 J mice (8–9 weeks) received daily exposure to the nerve agent prophylactic pyridostigmine bromide (PB) and the pyrethroid insecticide permethrin (PM) for 10 days. In the PB/DEET/CORT/DFP model, mice received daily exposure to PB and the insect repellent DEET (days 1–14) and corticosterone (CORT; days 7–14). On day 15, mice received a single injection of the sarin surrogate diisopropylfluorophosphate (DFP). Using a Varian 7 T Bore MRI System, structural (sagittal T2-weighted) scans were performed at 6-, 9-, and 12-months post GWI exposures. Regions of interest, including total brain, ventricles, cortex, hippocampus, cerebellum, and brainstem were delineated in the open source Aedes Toolbox in MATLAB, followed by brain volumetric and cortical thickness analyses in ImageJ. Limited behavioral testing 1 month after the last MRI was also performed. The results of this study compare similarities and distinctions between these exposure paradigms and aid in the understanding of GWI pathogenesis. Major similarities among the models include relative ventricular enlargement and reductions in hippocampal volumes with age. Key differences in the PB/DEET/CORT/DFP model included reduced brainstem volumes and an early and persistent loss of total brain volume, while the PB/PM model produced reductions in cortical thickness with age. Behaviorally, at 13 months, motor function was largely preserved in both models. However, the GWI mice in the PB/DEET/CORT/DFP model exhibited an elevation in anxiety-like behavior.","PeriodicalId":12639,"journal":{"name":"Frontiers in Neuroscience","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.3389/fnins.2024.1428666
Jun-Zhi Zhou, Jie Deng, De-Xing Luo, Jing-Wen Mai, Jia-Yan Wu, Yu-Juan Duan, Bo Dong, Wen-Jun Xin, Ting Xu, Jia-You Wei
IntroductionIt is well known that there are significant differences in the prevalence of chronic pain between males and females. Human and animal imaging studies have shown that chronic pain profoundly alters the structure and function of brain regions. However, there is limited research on the sex-specific mechanisms underlying the brain plasticity and adaptive changes associated with chronic pain. In this article, we conducted a multimodal study to evaluate how nerve injury-induced chronic pain affects the brain.MethodsMale and female Sprague-Dawley (SD) rats with spared nerve injury (SNI) model underwent resting-state functional magnetic resonance imaging (rs-fMRI) (male sham group: <jats:italic>n</jats:italic> = 18; male SNI group: <jats:italic>n</jats:italic> = 18; female sham group: <jats:italic>n</jats:italic> = 20; female SNI group: <jats:italic>n</jats:italic> = 18) and magnetic resonance diffusion tensor imaging (DTI) (male sham group: <jats:italic>n</jats:italic> = 23; male SNI group: <jats:italic>n</jats:italic> = 21; female sham group: <jats:italic>n</jats:italic> = 20; female SNI group: <jats:italic>n</jats:italic> = 21) scanning. ICA method, Fractional amplitude of low-frequency fluctuations (fALFF), immunofluorescence staining, and graph theory analysis was utilized to extract the rs-fMRI changes of brain regions of each group.ResultsUsing SNI model, which promotes long-lasting mechanical allodynia, we found that neuropathic pain deeply modified the intrinsic organization of the brain functional network in male and female rats (main effect of operation: <jats:italic>F</jats:italic> = 298.449, <jats:italic>P</jats:italic> < 0.001). 64 independent components (ICs) in the brain were divided and assigned to 16 systems. In male rats, we observed significant alterations in the microstructure of the hippocampal cornu ammonis 1 and cornu ammonis 2 (CA1/CA2) region, as indicated by increased mean diffusivity (MD) (CA1_L: <jats:italic>P</jats:italic> = 0.02; CA1_R: <jats:italic>P</jats:italic> = 0.031; CA2_L: <jats:italic>P</jats:italic> = 0.035; CA2_R: <jats:italic>P</jats:italic> = 0.015) and radial diffusivity (RD) (CA1_L: <jats:italic>P</jats:italic> = 0.028; CA1_R: <jats:italic>P</jats:italic> = 0.033; CA2_L: <jats:italic>P</jats:italic> = 0.037; CA2_R: <jats:italic>P</jats:italic> = 0.038) values, along with enhanced activating transcription factor 3 (ATF3) expression. Conversely, in female rats, we found significant increases in the fractional amplitude of low frequency fluctuations (fALFF) value within the hippocampal dentate gyrus (DG) (<jats:italic>F</jats:italic> = 5.419, <jats:italic>P</jats:italic> = 0.023), accompanied by elevated c-Fos signal (<jats:italic>F</jats:italic> = 6.269, <jats:italic>P</jats:italic> = 0.031). Furthermore, graph theory analysis revealed notable differences in the small-world network of the hippocampal system in female rats, characterized by reduced small-world attributes and increased inter-no
{"title":"Sex differences in functional and structural alterations of hippocampus region in chronic pain: a DTI and resting-state fMRI study","authors":"Jun-Zhi Zhou, Jie Deng, De-Xing Luo, Jing-Wen Mai, Jia-Yan Wu, Yu-Juan Duan, Bo Dong, Wen-Jun Xin, Ting Xu, Jia-You Wei","doi":"10.3389/fnins.2024.1428666","DOIUrl":"https://doi.org/10.3389/fnins.2024.1428666","url":null,"abstract":"IntroductionIt is well known that there are significant differences in the prevalence of chronic pain between males and females. Human and animal imaging studies have shown that chronic pain profoundly alters the structure and function of brain regions. However, there is limited research on the sex-specific mechanisms underlying the brain plasticity and adaptive changes associated with chronic pain. In this article, we conducted a multimodal study to evaluate how nerve injury-induced chronic pain affects the brain.MethodsMale and female Sprague-Dawley (SD) rats with spared nerve injury (SNI) model underwent resting-state functional magnetic resonance imaging (rs-fMRI) (male sham group: <jats:italic>n</jats:italic> = 18; male SNI group: <jats:italic>n</jats:italic> = 18; female sham group: <jats:italic>n</jats:italic> = 20; female SNI group: <jats:italic>n</jats:italic> = 18) and magnetic resonance diffusion tensor imaging (DTI) (male sham group: <jats:italic>n</jats:italic> = 23; male SNI group: <jats:italic>n</jats:italic> = 21; female sham group: <jats:italic>n</jats:italic> = 20; female SNI group: <jats:italic>n</jats:italic> = 21) scanning. ICA method, Fractional amplitude of low-frequency fluctuations (fALFF), immunofluorescence staining, and graph theory analysis was utilized to extract the rs-fMRI changes of brain regions of each group.ResultsUsing SNI model, which promotes long-lasting mechanical allodynia, we found that neuropathic pain deeply modified the intrinsic organization of the brain functional network in male and female rats (main effect of operation: <jats:italic>F</jats:italic> = 298.449, <jats:italic>P</jats:italic> &lt; 0.001). 64 independent components (ICs) in the brain were divided and assigned to 16 systems. In male rats, we observed significant alterations in the microstructure of the hippocampal cornu ammonis 1 and cornu ammonis 2 (CA1/CA2) region, as indicated by increased mean diffusivity (MD) (CA1_L: <jats:italic>P</jats:italic> = 0.02; CA1_R: <jats:italic>P</jats:italic> = 0.031; CA2_L: <jats:italic>P</jats:italic> = 0.035; CA2_R: <jats:italic>P</jats:italic> = 0.015) and radial diffusivity (RD) (CA1_L: <jats:italic>P</jats:italic> = 0.028; CA1_R: <jats:italic>P</jats:italic> = 0.033; CA2_L: <jats:italic>P</jats:italic> = 0.037; CA2_R: <jats:italic>P</jats:italic> = 0.038) values, along with enhanced activating transcription factor 3 (ATF3) expression. Conversely, in female rats, we found significant increases in the fractional amplitude of low frequency fluctuations (fALFF) value within the hippocampal dentate gyrus (DG) (<jats:italic>F</jats:italic> = 5.419, <jats:italic>P</jats:italic> = 0.023), accompanied by elevated c-Fos signal (<jats:italic>F</jats:italic> = 6.269, <jats:italic>P</jats:italic> = 0.031). Furthermore, graph theory analysis revealed notable differences in the small-world network of the hippocampal system in female rats, characterized by reduced small-world attributes and increased inter-no","PeriodicalId":12639,"journal":{"name":"Frontiers in Neuroscience","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-05DOI: 10.3389/fnins.2024.1463038
Jie Jin, Guangying Pei, Zhenxiang Ji, Xinze Liu, Tianyi Yan, Wei Li, Dingjie Suo
Ultrasound is a mechanical wave that can non-invasively penetrate the skull to deep brain regions to activate neurons. Transcranial focused ultrasound neuromodulation is a promising approach, with the advantages of noninvasiveness, high-resolution, and deep penetration, which developed rapidly over the past years. However, conventional transcranial ultrasound’s spatial resolution is low-precision which hinders its use in precision neuromodulation. Here we focus on methods that could increase the spatial resolution, gain modulation efficiency at the focal spot, and potential mechanisms of ultrasound neuromodulation. In this paper, we summarize strategies to enhance the precision of ultrasound stimulation, which could potentially improve the ultrasound neuromodulation technic.
{"title":"Transcranial focused ultrasound precise neuromodulation: a review of focal size regulation, treatment efficiency and mechanisms","authors":"Jie Jin, Guangying Pei, Zhenxiang Ji, Xinze Liu, Tianyi Yan, Wei Li, Dingjie Suo","doi":"10.3389/fnins.2024.1463038","DOIUrl":"https://doi.org/10.3389/fnins.2024.1463038","url":null,"abstract":"Ultrasound is a mechanical wave that can non-invasively penetrate the skull to deep brain regions to activate neurons. Transcranial focused ultrasound neuromodulation is a promising approach, with the advantages of noninvasiveness, high-resolution, and deep penetration, which developed rapidly over the past years. However, conventional transcranial ultrasound’s spatial resolution is low-precision which hinders its use in precision neuromodulation. Here we focus on methods that could increase the spatial resolution, gain modulation efficiency at the focal spot, and potential mechanisms of ultrasound neuromodulation. In this paper, we summarize strategies to enhance the precision of ultrasound stimulation, which could potentially improve the ultrasound neuromodulation technic.","PeriodicalId":12639,"journal":{"name":"Frontiers in Neuroscience","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-04DOI: 10.3389/fnins.2024.1400444
Yan Su, Yong Liu, Yan Xiao, Jiaqi Ma, Dezhao Li
Music is an archaic form of emotional expression and arousal that can induce strong emotional experiences in listeners, which has important research and practical value in related fields such as emotion regulation. Among the various emotion recognition methods, the music-evoked emotion recognition method utilizing EEG signals provides real-time and direct brain response data, playing a crucial role in elucidating the neural mechanisms underlying music-induced emotions. Artificial intelligence technology has greatly facilitated the research on the recognition of music-evoked EEG emotions. AI algorithms have ushered in a new era for the extraction of characteristic frequency signals and the identification of novel feature signals. The robust computational capabilities of AI have provided fresh perspectives for the development of innovative quantitative models of emotions, tailored to various emotion recognition paradigms. The discourse surrounding AI algorithms in the context of emotional classification models is gaining momentum, with their applications in music therapy, neuroscience, and social activities increasingly coming under the spotlight. Through an in-depth analysis of the complete process of emotion recognition induced by music through electroencephalography (EEG) signals, we have systematically elucidated the influence of AI on pertinent research issues. This analysis offers a trove of innovative approaches that could pave the way for future research endeavors.
{"title":"A review of artificial intelligence methods enabled music-evoked EEG emotion recognition and their applications","authors":"Yan Su, Yong Liu, Yan Xiao, Jiaqi Ma, Dezhao Li","doi":"10.3389/fnins.2024.1400444","DOIUrl":"https://doi.org/10.3389/fnins.2024.1400444","url":null,"abstract":"Music is an archaic form of emotional expression and arousal that can induce strong emotional experiences in listeners, which has important research and practical value in related fields such as emotion regulation. Among the various emotion recognition methods, the music-evoked emotion recognition method utilizing EEG signals provides real-time and direct brain response data, playing a crucial role in elucidating the neural mechanisms underlying music-induced emotions. Artificial intelligence technology has greatly facilitated the research on the recognition of music-evoked EEG emotions. AI algorithms have ushered in a new era for the extraction of characteristic frequency signals and the identification of novel feature signals. The robust computational capabilities of AI have provided fresh perspectives for the development of innovative quantitative models of emotions, tailored to various emotion recognition paradigms. The discourse surrounding AI algorithms in the context of emotional classification models is gaining momentum, with their applications in music therapy, neuroscience, and social activities increasingly coming under the spotlight. Through an in-depth analysis of the complete process of emotion recognition induced by music through electroencephalography (EEG) signals, we have systematically elucidated the influence of AI on pertinent research issues. This analysis offers a trove of innovative approaches that could pave the way for future research endeavors.","PeriodicalId":12639,"journal":{"name":"Frontiers in Neuroscience","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-04DOI: 10.3389/fnins.2024.1457623
Hui Chen, Xiangyang Wang, Yang Xiao, Beixian Wu, Zhuo Wang, Yao Liu, Peiyi Wang, Chunjie Chen, Xinyu Wu
IntroductionWearable exoskeletons assist individuals with mobility impairments, enhancing their gait and quality of life. This study presents the iP3T model, designed to optimize gait phase prediction through the fusion of multimodal time-series data.MethodsThe iP3T model integrates data from stretch sensors, inertial measurement units (IMUs), and surface electromyography (sEMG) to capture comprehensive biomechanical and neuromuscular signals. The model's architecture leverages transformer-based attention mechanisms to prioritize crucial data points. A series of experiments were conducted on a treadmill with five participants to validate the model's performance.ResultsThe iP3T model consistently outperformed traditional single-modality approaches. In the post-stance phase, the model achieved an RMSE of 1.073 and an R2 of 0.985. The integration of multimodal data enhanced prediction accuracy and reduced metabolic cost during assisted treadmill walking.DiscussionThe study highlights the critical role of each sensor type in providing a holistic understanding of the gait cycle. The attention mechanisms within the iP3T model contribute to its interpretability, allowing for effective optimization of sensor configurations and ultimately improving mobility and quality of life for individuals with gait impairments.
{"title":"iP3T: an interpretable multimodal time-series model for enhanced gait phase prediction in wearable exoskeletons","authors":"Hui Chen, Xiangyang Wang, Yang Xiao, Beixian Wu, Zhuo Wang, Yao Liu, Peiyi Wang, Chunjie Chen, Xinyu Wu","doi":"10.3389/fnins.2024.1457623","DOIUrl":"https://doi.org/10.3389/fnins.2024.1457623","url":null,"abstract":"IntroductionWearable exoskeletons assist individuals with mobility impairments, enhancing their gait and quality of life. This study presents the iP3T model, designed to optimize gait phase prediction through the fusion of multimodal time-series data.MethodsThe iP3T model integrates data from stretch sensors, inertial measurement units (IMUs), and surface electromyography (sEMG) to capture comprehensive biomechanical and neuromuscular signals. The model's architecture leverages transformer-based attention mechanisms to prioritize crucial data points. A series of experiments were conducted on a treadmill with five participants to validate the model's performance.ResultsThe iP3T model consistently outperformed traditional single-modality approaches. In the post-stance phase, the model achieved an RMSE of 1.073 and an R<jats:sup>2</jats:sup> of 0.985. The integration of multimodal data enhanced prediction accuracy and reduced metabolic cost during assisted treadmill walking.DiscussionThe study highlights the critical role of each sensor type in providing a holistic understanding of the gait cycle. The attention mechanisms within the iP3T model contribute to its interpretability, allowing for effective optimization of sensor configurations and ultimately improving mobility and quality of life for individuals with gait impairments.","PeriodicalId":12639,"journal":{"name":"Frontiers in Neuroscience","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-04DOI: 10.3389/fnins.2024.1440000
Ahmed Hasssan, Jian Meng, Anupreetham Anupreetham, Jae-sun Seo
Spiking neural networks (SNNs) have received increasing attention due to their high biological plausibility and energy efficiency. The binary spike-based information propagation enables efficient sparse computation in event-based and static computer vision applications. However, the weight precision and especially the membrane potential precision remain as high-precision values (e.g., 32 bits) in state-of-the-art SNN algorithms. Each neuron in an SNN stores the membrane potential over time and typically updates its value in every time step. Such frequent read/write operations of high-precision membrane potential incur storage and memory access overhead in SNNs, which undermines the SNNs' compatibility with resource-constrained hardware. To resolve this inefficiency, prior works have explored the time step reduction and low-precision representation of membrane potential at a limited scale and reported significant accuracy drops. Furthermore, while recent advances in on-device AI present pruning and quantization optimization with different architectures and datasets, simultaneous pruning with quantization is highly under-explored in SNNs. In this work, we present SpQuant-SNN, a fully-quantized spiking neural network with ultra-low precision weights, membrane potential, and high spatial-channel sparsity, enabling the end-to-end low precision with significantly reduced operations on SNN. First, we propose an integer-only quantization scheme for the membrane potential with a stacked surrogate gradient function, a simple-yet-effective method that enables the smooth learning process of quantized SNN training. Second, we implement spatial-channel pruning with membrane potential prior, toward reducing the layer-wise computational complexity, and floating-point operations (FLOPs) in SNNs. Finally, to further improve the accuracy of low-precision and sparse SNN, we propose a self-adaptive learnable potential threshold for SNN training. Equipped with high biological adaptiveness, minimal computations, and memory utilization, SpQuant-SNN achieves state-of-the-art performance across multiple SNN models for both event-based and static image datasets, including both image classification and object detection tasks. The proposed SpQuant-SNN achieved up to 13× memory reduction and >4.7× FLOPs reduction with < 1.8% accuracy degradation for both classification and object detection tasks, compared to the SOTA baseline.
{"title":"SpQuant-SNN: ultra-low precision membrane potential with sparse activations unlock the potential of on-device spiking neural networks applications","authors":"Ahmed Hasssan, Jian Meng, Anupreetham Anupreetham, Jae-sun Seo","doi":"10.3389/fnins.2024.1440000","DOIUrl":"https://doi.org/10.3389/fnins.2024.1440000","url":null,"abstract":"Spiking neural networks (SNNs) have received increasing attention due to their high biological plausibility and energy efficiency. The binary spike-based information propagation enables efficient sparse computation in event-based and static computer vision applications. However, the weight precision and especially the membrane potential precision remain as high-precision values (e.g., 32 bits) in state-of-the-art SNN algorithms. Each neuron in an SNN stores the membrane potential over time and typically updates its value in every time step. Such frequent read/write operations of high-precision membrane potential incur storage and memory access overhead in SNNs, which undermines the SNNs' compatibility with resource-constrained hardware. To resolve this inefficiency, prior works have explored the time step reduction and low-precision representation of membrane potential at a limited scale and reported significant accuracy drops. Furthermore, while recent advances in on-device AI present pruning and quantization optimization with different architectures and datasets, simultaneous pruning with quantization is highly under-explored in SNNs. In this work, we present <jats:italic>SpQuant-SNN</jats:italic>, a fully-quantized spiking neural network with <jats:italic>ultra-low precision weights, membrane potential, and high spatial-channel sparsity</jats:italic>, enabling the end-to-end low precision with significantly reduced operations on SNN. First, we propose an integer-only quantization scheme for the membrane potential with a stacked surrogate gradient function, a simple-yet-effective method that enables the smooth learning process of quantized SNN training. Second, we implement spatial-channel pruning with membrane potential prior, toward reducing the layer-wise computational complexity, and floating-point operations (FLOPs) in SNNs. Finally, to further improve the accuracy of low-precision and sparse SNN, we propose a self-adaptive learnable potential threshold for SNN training. Equipped with high biological adaptiveness, minimal computations, and memory utilization, SpQuant-SNN achieves state-of-the-art performance across multiple SNN models for both event-based and static image datasets, including both image classification and object detection tasks. The proposed SpQuant-SNN achieved up to 13× memory reduction and &gt;4.7× FLOPs reduction with &lt; 1.8% accuracy degradation for both classification and object detection tasks, compared to the SOTA baseline.","PeriodicalId":12639,"journal":{"name":"Frontiers in Neuroscience","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hedgehog signaling is a highly conserved pathway that plays pivotal roles in morphogenesis, tumorigenesis, osteogenesis, and wound healing. Previous investigations in patients with Gorlin syndrome found low harm avoidance traits, and increased volumes in the cerebrum, cerebellum, and cerebral ventricles, suggesting the association between brain morphology and the constitutive hyperactivation of hedgehog signaling, while the changes of regional brain volumes in upregulated hedgehog signaling pathway remains unclear so far. Herein, we investigated comprehensive brain regional volumes using quantitative structural brain MRI, and identified increased volumes of amygdala, striatum, and pallidum on the global segmentation, and increased volumes of the lateral and medial parts of the central nucleus of the amygdala on the detail segmentation in Ptch heterozygous deletion mice. Our data may enhance comprehension of the association between brain morphogenic changes and hyperactivity in hedgehog signaling.
{"title":"Brain morphological analysis in mice with hyperactivation of the hedgehog signaling pathway","authors":"Tadashi Shiohama, Hideki Uchikawa, Nobuhiro Nitta, Tomozumi Takatani, Shingo Matsuda, Alpen Ortug, Emi Takahashi, Daisuke Sawada, Eiji Shimizu, Katsunori Fujii, Ichio Aoki, Hiromichi Hamada","doi":"10.3389/fnins.2024.1449673","DOIUrl":"https://doi.org/10.3389/fnins.2024.1449673","url":null,"abstract":"Hedgehog signaling is a highly conserved pathway that plays pivotal roles in morphogenesis, tumorigenesis, osteogenesis, and wound healing. Previous investigations in patients with Gorlin syndrome found low harm avoidance traits, and increased volumes in the cerebrum, cerebellum, and cerebral ventricles, suggesting the association between brain morphology and the constitutive hyperactivation of hedgehog signaling, while the changes of regional brain volumes in upregulated hedgehog signaling pathway remains unclear so far. Herein, we investigated comprehensive brain regional volumes using quantitative structural brain MRI, and identified increased volumes of amygdala, striatum, and pallidum on the global segmentation, and increased volumes of the lateral and medial parts of the central nucleus of the amygdala on the detail segmentation in <jats:italic>Ptch</jats:italic> heterozygous deletion mice. Our data may enhance comprehension of the association between brain morphogenic changes and hyperactivity in hedgehog signaling.","PeriodicalId":12639,"journal":{"name":"Frontiers in Neuroscience","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-03DOI: 10.3389/fnins.2024.1397991
Lifang Huang, Mao Liu, Jiahui Tang, Zhenxiang Gong, Zehui Li, Yuan Yang, Min Zhang
BackgroundThe aldehyde dehydrogenase 2 (ALDH2) rs671 (A) allele has been implicated in neurodegeneration, potentially through oxidative and inflammatory pathways. The study aims to investigate the effects of the ALDH2 rs671 (A) allele and high sensitivity C-reactive protein (hs-CRP) on the clinical phenotypes of amyotrophic lateral sclerosis (ALS) in male and female patients.MethodsClinical data and ALDH2 rs671 genotype of 143 ALS patients, including 85 males and 58 females, were collected from January 2018 to December 2022. All patients underwent assessment using the Chinese version of the Edinburgh Cognitive and Behavioral ALS Screen (ECAS). Complete blood count and metabolic profiles were measured. Clinical and laboratory parameters were compared between carriers and non-carriers of the rs671 (A) allele in males and females, respectively. The significant parameters and rs671 (A) Allele were included in multivariate linear regression models to identify potential contributors to motor and cognitive impairment. Mediation analysis was employed to evaluate any mediation effects.ResultsMale patients carrying rs671 (A) allele exhibited higher levels of hs-CRP than non-carriers (1.70 mg/L vs. 0.50 mg/L, p = 0.006). The rs671 (A) allele was identified as an independent risk factor for faster disease progression only in male patients (β = 0.274, 95% CI = 0.048−0.499, p = 0.018). The effect of the rs671 (A) allele on the executive function in male patients was fully mediated by hs-CRP (Indirect effect = −1.790, 95% CI = −4.555−−0.225). No effects of the rs671 (A) allele or hs-CRP were observed in female ALS patients. The effects of the ALDH2 rs671 (A) allele and the mediating role of hs-CRP in male patients remained significant in the sensitivity analyses.ConclusionThe ALDH2 rs671 (A) allele contributed to faster disease progression and hs-CRP mediated cognitive impairment in male ALS patients.
{"title":"The role of ALDH2 rs671 polymorphism and C-reactive protein in the phenotypes of male ALS patients","authors":"Lifang Huang, Mao Liu, Jiahui Tang, Zhenxiang Gong, Zehui Li, Yuan Yang, Min Zhang","doi":"10.3389/fnins.2024.1397991","DOIUrl":"https://doi.org/10.3389/fnins.2024.1397991","url":null,"abstract":"BackgroundThe aldehyde dehydrogenase 2 (<jats:italic>ALDH2</jats:italic>) rs671 (A) allele has been implicated in neurodegeneration, potentially through oxidative and inflammatory pathways. The study aims to investigate the effects of the <jats:italic>ALDH2</jats:italic> rs671 (A) allele and high sensitivity C-reactive protein (hs-CRP) on the clinical phenotypes of amyotrophic lateral sclerosis (ALS) in male and female patients.MethodsClinical data and <jats:italic>ALDH2</jats:italic> rs671 genotype of 143 ALS patients, including 85 males and 58 females, were collected from January 2018 to December 2022. All patients underwent assessment using the Chinese version of the Edinburgh Cognitive and Behavioral ALS Screen (ECAS). Complete blood count and metabolic profiles were measured. Clinical and laboratory parameters were compared between carriers and non-carriers of the rs671 (A) allele in males and females, respectively. The significant parameters and rs671 (A) Allele were included in multivariate linear regression models to identify potential contributors to motor and cognitive impairment. Mediation analysis was employed to evaluate any mediation effects.ResultsMale patients carrying rs671 (A) allele exhibited higher levels of hs-CRP than non-carriers (1.70 mg/L vs. 0.50 mg/L, <jats:italic>p</jats:italic> = 0.006). The rs671 (A) allele was identified as an independent risk factor for faster disease progression only in male patients (β = 0.274, 95% CI = 0.048−0.499, <jats:italic>p</jats:italic> = 0.018). The effect of the rs671 (A) allele on the executive function in male patients was fully mediated by hs-CRP (Indirect effect = −1.790, 95% CI = −4.555−−0.225). No effects of the rs671 (A) allele or hs-CRP were observed in female ALS patients. The effects of the <jats:italic>ALDH2</jats:italic> rs671 (A) allele and the mediating role of hs-CRP in male patients remained significant in the sensitivity analyses.ConclusionThe <jats:italic>ALDH2</jats:italic> rs671 (A) allele contributed to faster disease progression and hs-CRP mediated cognitive impairment in male ALS patients.","PeriodicalId":12639,"journal":{"name":"Frontiers in Neuroscience","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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