Temporal specialization of the neural memory system: common and distinct neural correlates of recent and remote memory retrieval [0.03%]
神经记忆系统的时序特化：近期和远期记忆提取共有的及不同的脑机制
Rudolf Krug,Marko Rajkovic,Marco Caviezel et al.
Rudolf Krug et al.
Introduction: Associative memory (AM) is the most basic and common memory form. It constitutes the foundation of the declarative memory system, including all semantic and episodic memory processes. However, despite numero...
AI improves consistency in regional brain volumes measured in ultra-low-field MRI and 3T MRI [0.03%]
人工智能改善了极低场MRI和3T MRI下脑区体积测量的一致性
Kh Tohidul Islam,Shenjun Zhong,Parisa Zakavi et al.
Kh Tohidul Islam et al.
This study compares volumetric measurements of various brain regions using different magnetic resonance imaging (MRI) modalities and deep learning models, specifically 3T MRI, ultra-low field (ULF) MRI at 64mT, and AI-enhanced ULF MRI using...
Efficient Fourier base fitting on masked or incomplete structured data [0.03%]
有效傅里叶基拟合方法及其在结构数据上的应用
Fariba Karimi,Esra Neufeld,Arya Fallahi et al.
Fariba Karimi et al.
Introduction: Fourier base fitting for masked or incomplete structured data holds significant importance, for example in biomedical image data processing. However, data incompleteness destroys the simple unitary form of t...
Imaging joy with generalized slice dithered enhanced resolution and SWAT reconstruction: 3T high spatial-temporal resolution fMRI [0.03%]
利用广义分片抖动增强分辨率和SWAT重建的高空间-时间分辨力3T功能磁共振成像测量愉快感
Jennifer D Townsend,Angela Martina Muller,Zanib Naeem et al.
Jennifer D Townsend et al.
To facilitate high spatial-temporal resolution fMRI (≦1mm3) at more broadly available field strengths (3T) and to better understand the neural underpinnings of joy, we used SE-based generalized Slice Dithered Enhanced Resolution (gSLIDER)....
Benchmarking machine learning models in lesion-symptom mapping for predicting language outcomes in stroke survivors [0.03%]
机器学习模型在病变-症状映射中的基准测试，用于预测卒中幸存者的语言结果
Deepa Tilwani,Christian O&#x;Reilly,Nicholas Riccardi et al.
Deepa Tilwani et al.
Several decades of research have investigated the neural connections between stroke-induced brain damage and language difficulties. Typically, lesion-symptom mapping (LSM) studies that address this connection have relied on mass univariate ...
Low-intensity transcranial focused ultrasound of the amygdala modulates neural activation during emotion processing [0.03%]
低强度聚焦超声波作用于杏仁核可调节情绪加工过程中的神经激活状态
Kathryn C Jenkins,Katherine Koning,Arman Mehzad et al.
Kathryn C Jenkins et al.
Introduction: Low-intensity focused ultrasound (LIFU) is a form of neuromodulation that offers increased depth of penetrance and improved spatial resolution over other non-invasive techniques, allowing for modulation of o...
Neuroimaging correlates of psychological resilience: an Open Science systematic review and meta-analysis [0.03%]
心理韧性相关的神经影像标志：开放科学系统综述和元分析
Allison Kuehn,Maegan L Calvert,G Andrew James
Allison Kuehn
Introduction: While risk factors have been identified for numerous psychiatric disorders, many individuals exposed to these risk factors do not develop psychopathology. A growing neuroimaging literature has sought to find...
Denoising very low-field magnetic resonance images using native noise modeling [0.03%]
利用固有噪声模型对极低场磁共振图像进行降噪
Tonny Ssentamu,Alvin Kimbowa,Ronald Omoding et al.
Tonny Ssentamu et al.
Low-field MRI is gaining interest, especially in low-resource settings, due to its low cost, portability, small footprint, and low power consumption. However, it suffers from significant noise, limiting its clinical utility. This study intr...
A deep neural network for adaptive spatial smoothing of task fMRI data [0.03%]
一种自适应空间平滑的任务性fMRI数据深度神经网络方法
Zhengshi Yang,Xiaowei Zhuang,Mark J Lowe et al.
Zhengshi Yang et al.
Over the past decade, functional magnetic resonance imaging (fMRI) has emerged as a widely adopted in vivo imaging technique for examining neural activity in the brain. A common preprocessing step in fMRI analysis is spatial smoothing, whic...
Modeling functional connectivity with learning and memory in a mouse model of Alzheimer's disease [0.03%]
阿尔茨海默病小鼠模型中学习记忆功能连接的构建研究
Lindsay Fadel,Elizabeth Hipskind,Steen E Pedersen et al.
Lindsay Fadel et al.
Introduction: Functional connectivity (FC) is a metric of how different brain regions interact with each other. Although there have been some studies correlating learning and memory with FC, there have not yet been, to da...