標(biāo)題: Titlebook: Brain Network Dysfunction in Neuropsychiatric Illness; Methods, Application Vaibhav A. Diwadkar,Simon B. Eickhoff Book 2021 Springer Nature [打印本頁(yè)] 作者: 代表 時(shí)間: 2025-3-21 17:04
書目名稱Brain Network Dysfunction in Neuropsychiatric Illness影響因子(影響力)
書目名稱Brain Network Dysfunction in Neuropsychiatric Illness影響因子(影響力)學(xué)科排名
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書目名稱Brain Network Dysfunction in Neuropsychiatric Illness網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Brain Network Dysfunction in Neuropsychiatric Illness被引頻次
書目名稱Brain Network Dysfunction in Neuropsychiatric Illness被引頻次學(xué)科排名
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書目名稱Brain Network Dysfunction in Neuropsychiatric Illness年度引用學(xué)科排名
書目名稱Brain Network Dysfunction in Neuropsychiatric Illness讀者反饋
書目名稱Brain Network Dysfunction in Neuropsychiatric Illness讀者反饋學(xué)科排名
作者: 上流社會(huì) 時(shí)間: 2025-3-21 22:52
fMRI: Blood Oxygen Level-Dependent Contrast and Its Value for Understanding Functional Brain Networkgh-resolution, and high-speed assessment of human brain activation and connectivity. Because clinical MRI scanners equipped with fMRI capability are ubiquitous throughout the world – with at least one in most hospitals – its use has grown rapidly since its inception in the early 1990s. Over the year作者: Postmenopause 時(shí)間: 2025-3-22 02:31
Review of Resting-State Functional Connectivity Methods and Application in Clinical Populationsstinct regions whose interactions are both functionally segregated and integrated across the whole brain. Functional connections integrate multiple brain systems to produce unique networks attending to the different cognitive and sensory demands of the body. Detection and quantification of functiona作者: CLASH 時(shí)間: 2025-3-22 08:24 作者: ANNUL 時(shí)間: 2025-3-22 12:00 作者: white-matter 時(shí)間: 2025-3-22 15:32
Data Mining in the Era of Big Data: The BrainMap Database as a Resource for Characterizing Brain Netrature. This chapter provides a review of meta-analysis techniques available via the BrainMap Project, including activation likelihood estimation (ALE), independent component analysis (ICA), and clustering. Prior work emphasizing clinical utility of these meta-analytic methods are discussed.作者: HUMID 時(shí)間: 2025-3-22 19:46 作者: 一夫一妻制 時(shí)間: 2025-3-22 22:49 作者: Ringworm 時(shí)間: 2025-3-23 01:54
Resting-State Functional Network Disturbances in Schizophreniances of functional resting-state brain networks in this illness are widely investigated. For example, dysconnectivity among brain networks have been revealed by regions of interest-based analysis, independent component analysis, graph theory-based analysis, and dynamic connectivity analysis. In addi作者: 臭了生氣 時(shí)間: 2025-3-23 05:53 作者: Herbivorous 時(shí)間: 2025-3-23 10:51 作者: 菊花 時(shí)間: 2025-3-23 16:57
Functional Resting-State Network Disturbances in Bipolar Disorder findings highlight abnormal functional connectivity patterns within and between several brain networks including default mode, control, and saliency networks. Local and large-scale connectivity changes in these networks as well as modulation of cortico-striato-thalamic, reward-related, and sensorim作者: 符合你規(guī)定 時(shí)間: 2025-3-23 18:06 作者: expdient 時(shí)間: 2025-3-23 23:53 作者: Alcove 時(shí)間: 2025-3-24 04:24
Understanding the Network Bases of ADHD: An Overview of the fMRI Evidencebrain networks. This chapter provides a critical overview of the available functional MRI (fMRI) studies on the brain networks in ADHD across the lifespan, with a particular focus on evidence from resting state fMRI (R-fMRI) studies. It is concluded that, whereas some results seem to be fairly consi作者: enumaerate 時(shí)間: 2025-3-24 08:44 作者: atopic-rhinitis 時(shí)間: 2025-3-24 13:29 作者: Project 時(shí)間: 2025-3-24 15:27
,Brain Network Dysconnection in Neuropsychiatric Disorders: The Practice of “Normal Science”,s. Because psychiatric conditions are ultimately conditions of behavior, the brain is . generative biological system for these aberrations. And because the brain is biology’s ultimate functional network, understanding brain network dysfunction becomes a logical mechanistic bridge for discovering neu作者: insomnia 時(shí)間: 2025-3-24 22:08
fMRI: Blood Oxygen Level-Dependent Contrast and Its Value for Understanding Functional Brain Networkrldwide has become uniformly high. While fMRI is still not making significant clinical inroads, it is well poised to do so in the very near future..This chapter is all about BOLD contrast and the neuronal information that has been able to be derived from it. The depth and accuracy by which the inter作者: Priapism 時(shí)間: 2025-3-24 23:51
Review of Resting-State Functional Connectivity Methods and Application in Clinical Populations review the neurophysiological basis of resting-state functional connectivity and give a synopsis of the most established resting-state analysis techniques. We also summarize relevant findings from an array of clinical populations including neuropsychological disorders to emphasize the versatility o作者: 性學(xué)院 時(shí)間: 2025-3-25 04:00
Directed Interregional Brain Interactionsterconnected neuronal populations in the central nervous system, or neurocognitive networks, as uniquely organized to perform specific cognitive functions. Simply put, specific cognitive functions are executed by uniquely configured neurocognitive networks. Following graph theory, neurocognitive net作者: Distribution 時(shí)間: 2025-3-25 11:13
dMRI: Diffusion Magnetic Resonance Imaging as a Window onto Structural Brain Networks and White Matton an understanding of dMRI signal mechanisms and appropriate signal processing and modeling for this purpose. It first?discusses basic diffusion MRI acquisition principles and diffusion contrast and the constraints the acquisition places on the modeling of diffusion. It then?sets out the diffusion 作者: HPA533 時(shí)間: 2025-3-25 14:25 作者: Deject 時(shí)間: 2025-3-25 16:20 作者: Leaven 時(shí)間: 2025-3-25 23:06
An Overview of Resting State Functional Connectivity Studies of Major Depressive Disorderrs being emphasized as areas of particular significance for future work. In summary, I describe the considerable progress that has been made, outlining the many challenges but also successful attempts to make progress toward the goal of identifying replicable and generalizable markers of major depre作者: 死亡率 時(shí)間: 2025-3-26 00:42 作者: Minuet 時(shí)間: 2025-3-26 07:54 作者: Hot-Flash 時(shí)間: 2025-3-26 11:01 作者: Parley 時(shí)間: 2025-3-26 12:40 作者: nitric-oxide 時(shí)間: 2025-3-26 18:43
https://doi.org/10.1007/978-3-030-13743-4rldwide has become uniformly high. While fMRI is still not making significant clinical inroads, it is well poised to do so in the very near future..This chapter is all about BOLD contrast and the neuronal information that has been able to be derived from it. The depth and accuracy by which the inter作者: 鳴叫 時(shí)間: 2025-3-27 00:53
Maria Virvou,Efthimios Alepis,Lakhmi C. Jain review the neurophysiological basis of resting-state functional connectivity and give a synopsis of the most established resting-state analysis techniques. We also summarize relevant findings from an array of clinical populations including neuropsychological disorders to emphasize the versatility o作者: conquer 時(shí)間: 2025-3-27 03:27
Rania Saidi,Waad Bouaguel,Nadia Essoussiterconnected neuronal populations in the central nervous system, or neurocognitive networks, as uniquely organized to perform specific cognitive functions. Simply put, specific cognitive functions are executed by uniquely configured neurocognitive networks. Following graph theory, neurocognitive net作者: 外面 時(shí)間: 2025-3-27 06:40
Studies in Computational Intelligenceon an understanding of dMRI signal mechanisms and appropriate signal processing and modeling for this purpose. It first?discusses basic diffusion MRI acquisition principles and diffusion contrast and the constraints the acquisition places on the modeling of diffusion. It then?sets out the diffusion 作者: ORBIT 時(shí)間: 2025-3-27 12:00
Xiaowei Huang,Gaojie Jin,Wenjie Ruanhis chapter provides a brief overview of suitable analysis approaches and a selective overview of brain network findings in high-risk subjects for psychosis. Finally, we suggest necessary developments for future research to approach a brain network-driven stratification of individual risk propensity作者: DEAF 時(shí)間: 2025-3-27 15:11
Xiaowei Huang,Gaojie Jin,Wenjie Ruanill be critical to overcome these challenges. However, there are also concerns about the use of “resting states” for fMRI data acquisition, and better controlled natural stimulation may be a preferable alternative.作者: obligation 時(shí)間: 2025-3-27 18:52 作者: Jocose 時(shí)間: 2025-3-27 23:19
Xiaowei Huang,Gaojie Jin,Wenjie Ruanneurofunctional deficits – linked to emotional processing – associated with BD. Overall, morpho-functional and connectivity evidence points towards the hypothesis that BD is a brain disorder characterized by deficits in selective brain networks, which may ultimately explain the specific clinical and作者: 運(yùn)動(dòng)的我 時(shí)間: 2025-3-28 04:41 作者: Meditate 時(shí)間: 2025-3-28 06:53 作者: 弓箭 時(shí)間: 2025-3-28 14:07 作者: 沉著 時(shí)間: 2025-3-28 16:45 作者: 排他 時(shí)間: 2025-3-28 20:14
works interactions in specific neuropsychiatric disorders.Ex.Brain network function and dysfunction is the dominant model for understanding how the brain gives rise to normal and abnormal behavior. Moreover, neuropsychiatric illnesses continue to resist attempts to reveal an understanding of their b作者: 脾氣暴躁的人 時(shí)間: 2025-3-29 00:16 作者: 環(huán)形 時(shí)間: 2025-3-29 05:23
Functional Resting-State Network Disturbances in Bipolar Disordernetworks. Local and large-scale connectivity changes in these networks as well as modulation of cortico-striato-thalamic, reward-related, and sensorimotor circuits might depend on patients’ symptomatology. Further studies should clarify specific associations between clinical dimensions and functional network properties.作者: CRAB 時(shí)間: 2025-3-29 10:29 作者: cathartic 時(shí)間: 2025-3-29 12:33
Some Important Background Material,disturbances are associated with patient’s symptoms. Future studies may develop new understanding of how these functional brain disturbances translate into clinical practice, and help inform disease diagnosis.作者: 準(zhǔn)則 時(shí)間: 2025-3-29 17:43
Networks-Mediated Spreading of Pathology in Neurodegenerative Diseases and metabolic dysregulation, structural atrophy). Finally, we show that, by characterizing each patient’s multifactorial brain changes in response to potential therapeutic inputs, robust predictions of treatment response can be obtained, potentially accelerating the finding of effective disease-modifying agents at the individual level.作者: 烤架 時(shí)間: 2025-3-29 20:07 作者: 值得尊敬 時(shí)間: 2025-3-30 03:24
Network Modulation in Neuropsychiatric Disorders Using the Virtual Brainpy and intervention can be tested. With a focus on major depressive disorder (MDD), we highlight the rationale for using this computational approach in psychiatric disorders to characterize disease mechanisms and map these characterizations to treatment predictions.作者: chapel 時(shí)間: 2025-3-30 04:34 作者: chemical-peel 時(shí)間: 2025-3-30 09:13
https://doi.org/10.1007/978-1-4302-6766-9py and intervention can be tested. With a focus on major depressive disorder (MDD), we highlight the rationale for using this computational approach in psychiatric disorders to characterize disease mechanisms and map these characterizations to treatment predictions.作者: Lacunar-Stroke 時(shí)間: 2025-3-30 13:03 作者: 會(huì)犯錯(cuò)誤 時(shí)間: 2025-3-30 17:52 作者: Confirm 時(shí)間: 2025-3-31 00:16
Vaibhav A. Diwadkar,Simon B. EickhoffCombines and synthesizes expertise from neuroimaging and psychiatry.Discusses applications of neuroimaging to reveal dysfunctional brain networks interactions in specific neuropsychiatric disorders.Ex作者: Sputum 時(shí)間: 2025-3-31 01:29
http://image.papertrans.cn/b/image/190218.jpg作者: Hay-Fever 時(shí)間: 2025-3-31 07:58
Intelligent Systems Reference Libraryends of neurodevelopment and neurodegeneration, thus implying that they cannot be “cured.” Though psychiatric nosology is relatively tractable and characterized by high reliability, the etiology of neuropsychiatric conditions is considered anything but. Unlike some other medical conditions, their ge作者: 議程 時(shí)間: 2025-3-31 12:08
https://doi.org/10.1007/978-3-030-13743-4gh-resolution, and high-speed assessment of human brain activation and connectivity. Because clinical MRI scanners equipped with fMRI capability are ubiquitous throughout the world – with at least one in most hospitals – its use has grown rapidly since its inception in the early 1990s. Over the year作者: BIAS 時(shí)間: 2025-3-31 14:06
Maria Virvou,Efthimios Alepis,Lakhmi C. Jainstinct regions whose interactions are both functionally segregated and integrated across the whole brain. Functional connections integrate multiple brain systems to produce unique networks attending to the different cognitive and sensory demands of the body. Detection and quantification of functiona作者: 喪失 時(shí)間: 2025-3-31 19:05
Rania Saidi,Waad Bouaguel,Nadia Essoussiehavior of brain networks is revealed by the relative timing of coordinated brain areas during cognitive task performance (Bressler and Kelso 2016). Coordination of brain areas has been demonstrated by function-related phase synchrony of the EEG, MEG, iEEG, ECoG, or LFP at a fast timescale in the 1–作者: 頭腦冷靜 時(shí)間: 2025-4-1 01:35
Studies in Computational Intelligence diffusion-weighted MR signal has sensitivity to micrometer-scale tissue properties averaged over the imaging voxel size, for example, intra-cellular and extra-cellular volumes and the 3D orientations of axonal bundles. It derives its contrast from sensitivity to the bulk displacement of water throu作者: IRS 時(shí)間: 2025-4-1 02:32 作者: intuition 時(shí)間: 2025-4-1 06:24
https://doi.org/10.1007/978-1-4302-6766-9mprove treatment results. We describe a novel approach to customizing interventions, The Virtual Brian (TVB), which combines individual patient brain structure and connectivity with high-performance computing to develop in silico platforms of brain function on which personalized strategies for thera作者: coalition 時(shí)間: 2025-4-1 12:56
