The progressive digging task: A naturalistic assay of effort-based food motivation in mice [0.03%]
渐进性挖掘任务——小鼠基于努力的觅食动机自然行为检测指标
Karla Mendez Vasquez,Jacob Calle,Milo Duch et al.
Karla Mendez Vasquez et al.
Background: The progressive ratio (PR) task is a widely used measure of effort-based food motivation, but it relies on operant conditioning rather than natural behaviors. ...
Frequency-enhanced fiber orientation distribution super-resolution network with application on Alzheimer's disease [0.03%]
基于频率增强的纤维导向分布超分辨率网络在阿尔茨海默病中的应用研究
Xinyi Xie,Jingxin Meng,Yuanjun Wang
Xinyi Xie
Background: Diffusion MRI enables noninvasive assessment of white matter microstructure, but the accuracy of fiber orientation distribution (FOD) reconstruction remains limited by inter-voxel incoherence and insufficient ...
LSHMMformer: An Intelligent detection model of depression based on multi-modal fusion [0.03%]
基于多模态融合的智能抑郁症检测模型LSHMMformer
Yuntao Shi,Tian Gan,Jie Li et al.
Yuntao Shi et al.
Background: Depression is a serious mental health issue, which has become an undeniable threat to mental well-being. Against this background, research on automatic depression detection based on deep learning (DL) can help...
Computational modelling of Parkinson's disease: A multiscale approach with deep brain stimulation and stochastic noise [0.03%]
基于深部脑刺激和随机噪声的帕金森病多尺度计算模型
A Herrera,M Chowdhury,H Shaheen
A Herrera
Multiscale modelling presents a multifaceted perspective into understanding the mechanisms of the brain and how neurodegenerative disorders like Parkinson's disease (PD) manifest and evolve over time. In this study, we propose a novel co-si...
Alzheimer's disease staging using enhanced inception-ResNet-V2 and improved XceptionNet models for 3D MRI classification and segmentation [0.03%]
基于增强的Inception-ResNet-V2和改进的XceptionNet模型的阿尔茨海默病淀粉样蛋白病变期别的深度学习方法
V Srilakshmi,Prasad Devarasetty,V Lakshmi Chetana et al.
V Srilakshmi et al.
Background: Neurologists have a significant challenge due to the progressive nature of Alzheimer's disease (AD) and its severe effects on cognitive function. Recent advances in neuroimage analysis have opened the door to ...
Dynamic source domain selection: An adaptive EEG transfer learning framework for mitigating negative transfer [0.03%]
动态源领域选择：一种适应性EEG迁移学习框架以缓解负面迁移
Xinhui Zhou,Li Wang,Lin Zhang et al.
Xinhui Zhou et al.
Background: Electroencephalography (EEG) is widely used in brain-computer interfaces (BCIs). Current transfer learning (TL) methods often merge multiple source domains, underutilizing diverse information and risking negat...
EEG-AI: An agentic system for AI-assisted semi-automated EEG preprocessing and artifact removal [0.03%]
EEG-AI：一种用于AI辅助半自动脑电图预处理和伪迹移除的自主系统
Abdelrahman Abdou,Martin Ivanov,Sarmed Shaya et al.
Abdelrahman Abdou et al.
Background: EEG is widely used to identify neural markers, personalize treatments, and evaluate interventions. However, low signal-to-noise ratio and mixing of artifactual distorted interpretation. Traditional preprocessi...
A scalable EEG-based spatial neglect detection system in augmented reality for stroke patients [0.03%]
一种基于EEG的可在卒中患者中使用的增强现实技术Spatial Neglect检测系统
Jennifer Mak,Richard Gall,Golnaz Haddadshargh et al.
Jennifer Mak et al.
Background: Spatial neglect is a common visuospatial attention disorder following a stroke. To overcome weaknesses associated with classic pen-and-paper tests used in some clinical settings, we developed AREEN: an AR-guid...
Comparison of dimensionality reduction and feature selection for cognitive task decoding using functional connectivity [0.03%]
基于功能连接的认知任务解码的降维与特征选择方法比较
Corey J Richier,Kyle A Baacke,Sarah M Olshan et al.
Corey J Richier et al.
Background: Advances in functional magnetic resonance imaging (fMRI) have led to the ability to study the brain across many contexts. However, the large number of features generated by functional connectivity approaches m...
Comparison of place field detection methods and their effect on place field stability and drift in mouse dCA1 [0.03%]
小鼠dCA1区位场检测方法的比较及其对位场稳定性和漂移的影响
Vladislav Ivantaev,Alireza Chenani,Alessio Attardo et al.
Vladislav Ivantaev et al.
Background: Hippocampal place cells (PCs) undergo representational drift, i.e., a gradual change in their place fields despite unaltered behavior. While Ca2 + imaging enables long-term tracking of PC populations, distinct...