Frontiers in Systems Neuroscience最新文献_第2页

Editorial: Rising stars in systems neuroscience: 2022 社论：系统神经科学的新星：2022 年

IF 3 4区医学

Frontiers in Systems Neuroscience Pub Date : 2024-05-14 DOI: 10.3389/fnsys.2024.1414351

Mazyar Fallah, Juhee Haam, Ada Ledonne

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Editorial: Horizons in Systems Neuroscience 2022 社论：2022 年系统神经科学的前景

IF 3 4区医学

Frontiers in Systems Neuroscience Pub Date : 2024-05-09 DOI: 10.3389/fnsys.2024.1415569

Wen-Jun Gao, Olivia Gosseries, Preston Garraghty, Mathew Diamond, M. Sanchez-Vives

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A hybrid boundary element-finite element approach for solving the EEG forward problem in brain modeling 解决脑建模中脑电图前向问题的边界元-有限元混合方法

IF 3 4区医学

Frontiers in Systems Neuroscience Pub Date : 2024-05-03 DOI: 10.3389/fnsys.2024.1327674

Nasireh Dayarian, Ali Khadem

{"title":"A hybrid boundary element-finite element approach for solving the EEG forward problem in brain modeling","authors":"Nasireh Dayarian, Ali Khadem","doi":"10.3389/fnsys.2024.1327674","DOIUrl":"https://doi.org/10.3389/fnsys.2024.1327674","url":null,"abstract":"This article introduces a hybrid BE-FE method for solving the EEG forward problem, leveraging the strengths of both the Boundary Element Method (BEM) and Finite Element Method (FEM). FEM accurately models complex and anisotropic tissue properties for realistic head geometries, while BEM excels in handling isotropic tissue regions and dipolar sources efficiently. The proposed hybrid method divides regions into homogeneous boundary element (BE) regions that include sources and heterogeneous anisotropic finite element (FE) regions. So, BEM models the brain, including dipole sources, and FEM models other head layers. Validation includes inhomogeneous isotropic/anisotropic three- and four-layer spherical head models, and a four-layer MRI-based realistic head model. Results for six dipole eccentricities and two orientations are computed using BEM, FEM, and hybrid BE-FE method. Statistical analysis, comparing error criteria of RDM and MAG, reveals notable improvements using the hybrid FE-BE method. In the spherical head model, the hybrid BE-FE method compared with FEM demonstrates enhancements of at least 1.05 and 38.31% in RDM and MAG criteria, respectively. Notably, in the anisotropic four-layer head model, improvements reach a maximum of 88.3% for RDM and 93.27% for MAG over FEM. Moreover, in the anisotropic four-layer realistic head model, the proposed hybrid method exhibits 55.4% improvement in RDM and 89.3% improvement in MAG compared to FEM. These findings underscore the proposed method is a promising approach for solving the realistic EEG forward problems, advancing neuroimaging techniques and enhancing understanding of brain function.","PeriodicalId":12649,"journal":{"name":"Frontiers in Systems Neuroscience","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140836323","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}

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Exploring Flip Flop memories and beyond: training Recurrent Neural Networks with key insights 探索翻转记忆及其他：训练循环神经网络的重要启示

IF 3 4区医学

Frontiers in Systems Neuroscience Pub Date : 2024-03-27 DOI: 10.3389/fnsys.2024.1269190

Cecilia Jarne

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Contributions of narrow- and broad-spiking prefrontal and parietal neurons on working memory tasks 窄尖峰和宽尖峰前额叶和顶叶神经元对工作记忆任务的贡献

IF 3 4区医学

Frontiers in Systems Neuroscience Pub Date : 2024-03-21 DOI: 10.3389/fnsys.2024.1365622

Rana Mozumder, Sophia Chung, Sihai Li, Christos Constantinidis

{"title":"Contributions of narrow- and broad-spiking prefrontal and parietal neurons on working memory tasks","authors":"Rana Mozumder, Sophia Chung, Sihai Li, Christos Constantinidis","doi":"10.3389/fnsys.2024.1365622","DOIUrl":"https://doi.org/10.3389/fnsys.2024.1365622","url":null,"abstract":"Neurons that generate persistent activity in the primate dorsolateral prefrontal and posterior parietal cortex have been shown to be predictive of behavior in working memory tasks, though subtle differences between them have been observed in how information is represented. The role of different neuron types in each of these areas has not been investigated at depth. We thus compared the activity of neurons classified as narrow-spiking, putative interneurons, and broad-spiking, putative pyramidal neurons, recorded from the dorsolateral prefrontal and posterior parietal cortex of male monkeys, to analyze their role in the maintenance of working memory. Our results demonstrate that narrow-spiking neurons are active during a range of tasks and generate persistent activity during the delay period over which stimuli need to be maintained in memory. Furthermore, the activity of narrow-spiking neurons was predictive of the subject’s recall no less than that of broad-spiking neurons, which are exclusively projection neurons in the cortex. Our results show that putative interneurons play an active role during the maintenance of working memory and shed light onto the fundamental neural circuits that determine subjects’ memories and judgments.","PeriodicalId":12649,"journal":{"name":"Frontiers in Systems Neuroscience","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140197430","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}

引用次数: 0

Explainable machine learning radiomics model for Primary Progressive Aphasia classification 用于原发性进行性失语症分类的可解释机器学习放射组学模型

IF 3 4区医学

Frontiers in Systems Neuroscience Pub Date : 2024-02-26 DOI: 10.3389/fnsys.2024.1324437

Benedetta Tafuri, Roberto De Blasi, Salvatore Nigro, Giancarlo Logroscino

{"title":"Explainable machine learning radiomics model for Primary Progressive Aphasia classification","authors":"Benedetta Tafuri, Roberto De Blasi, Salvatore Nigro, Giancarlo Logroscino","doi":"10.3389/fnsys.2024.1324437","DOIUrl":"https://doi.org/10.3389/fnsys.2024.1324437","url":null,"abstract":"<sec><title>Introduction</title>Primary Progressive Aphasia (PPA) is a neurodegenerative disease characterized by linguistic impairment. The two main clinical subtypes are semantic (svPPA) and non-fluent/agrammatic (nfvPPA) variants. Diagnosing and classifying PPA patients represents a complex challenge that requires the integration of multimodal information, including clinical, biological, and radiological features. Structural neuroimaging can play a crucial role in aiding the differential diagnosis of PPA and constructing diagnostic support systems.</sec><sec><title>Methods</title>In this study, we conducted a white matter texture analysis on T1-weighted images, including 56 patients with PPA (31 svPPA and 25 nfvPPA), and 53 age- and sex-matched controls. We trained a tree-based algorithm over combined clinical/radiomics measures and used Shapley Additive Explanations (SHAP) model to extract the greater impactful measures in distinguishing svPPA and nfvPPA patients from controls and each other.</sec><sec><title>Results</title>Radiomics-integrated classification models demonstrated an accuracy of 95% in distinguishing svPPA patients from controls and of 93.7% in distinguishing svPPA from nfvPPA. An accuracy of 93.7% was observed in differentiating nfvPPA patients from controls. Moreover, Shapley values showed the strong involvement of the white matter near left entorhinal cortex in patients classification models.</sec><sec><title>Discussion</title>Our study provides new evidence for the usefulness of radiomics features in classifying patients with svPPA and nfvPPA, demonstrating the effectiveness of an explainable machine learning approach in extracting the most impactful features for assessing PPA.</sec>","PeriodicalId":12649,"journal":{"name":"Frontiers in Systems Neuroscience","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140152874","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}

引用次数: 0

Updating perspectives on spinal cord function: motor coordination, timing, relational processing, and memory below the brain 更新脊髓功能视角：大脑下方的运动协调、计时、关系处理和记忆

IF 3 4区医学

Frontiers in Systems Neuroscience Pub Date : 2024-02-20 DOI: 10.3389/fnsys.2024.1184597

James W. Grau, Kelsey E. Hudson, David T. Johnston, Sienna R. Partipilo

{"title":"Updating perspectives on spinal cord function: motor coordination, timing, relational processing, and memory below the brain","authors":"James W. Grau, Kelsey E. Hudson, David T. Johnston, Sienna R. Partipilo","doi":"10.3389/fnsys.2024.1184597","DOIUrl":"https://doi.org/10.3389/fnsys.2024.1184597","url":null,"abstract":"Those studying neural systems within the brain have historically assumed that lower-level processes in the spinal cord act in a mechanical manner, to relay afferent signals and execute motor commands. From this view, abstracting temporal and environmental relations is the province of the brain. Here we review work conducted over the last 50 years that challenges this perspective, demonstrating that mechanisms within the spinal cord can organize coordinated behavior (stepping), induce a lasting change in how pain (nociceptive) signals are processed, abstract stimulus–stimulus (Pavlovian) and response-outcome (instrumental) relations, and infer whether stimuli occur in a random or regular manner. The mechanisms that underlie these processes depend upon signal pathways (e.g., NMDA receptor mediated plasticity) analogous to those implicated in brain-dependent learning and memory. New data show that spinal cord injury (SCI) can enable plasticity within the spinal cord by reducing the inhibitory effect of GABA. It is suggested that the signals relayed to the brain may contain information about environmental relations and that spinal cord systems can coordinate action in response to descending signals from the brain. We further suggest that the study of stimulus processing, learning, memory, and cognitive-like processing in the spinal cord can inform our views of brain function, providing an attractive model system. Most importantly, the work has revealed new avenues of treatment for those that have suffered a SCI.","PeriodicalId":12649,"journal":{"name":"Frontiers in Systems Neuroscience","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139920853","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}

引用次数: 0

Editorial: Sleep and circadian rhythms in plasticity and memory, volume II 社论：可塑性和记忆中的睡眠与昼夜节律》第 II 卷

IF 3 4区医学

Frontiers in Systems Neuroscience Pub Date : 2024-02-05 DOI: 10.3389/fnsys.2024.1351714

J. Gerstner, H. Craig Heller, S. Aton

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Editorial: Sleep and circadian rhythms in plasticity and memory, volume II 社论：可塑性和记忆中的睡眠与昼夜节律》第 II 卷

IF 3 4区医学

Frontiers in Systems Neuroscience Pub Date : 2024-02-05 DOI: 10.3389/fnsys.2024.1351714

J. Gerstner, H. Craig Heller, S. Aton

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Editorial: Distributed networks: new outlooks on cerebellar function, volume II 社论：分布式网络：小脑功能新展望》第二卷

IF 3 4区医学

Frontiers in Systems Neuroscience Pub Date : 2024-02-01 DOI: 10.3389/fnsys.2024.1362963

Richard Apps, Jimena Frontera, Lisa Mapelli, Thomas Watson

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