Allothetic and Idiothetic Spatial Cues Control the Multiplexed Theta Phase Coding of Place Cells

Information Science, Computer Science, Artificial Intelligence, Medicine, Neurology, Life Sciences, Biophysics,
place cells   theta oscillation   phase coding   spatial learning   hippocampus   animal experiment   virtual reality  

New Advances in Hippocampal Spatiotemporal Coding—Multiplexed Theta Phase Coding and the Regulation by External vs. Self-Motion Cues —Review of the latest Nature Neuroscience paper: “allothetic and idiothetic spatial cues control the multiplexed theta phase coding of place cells” 1. Academic Background & Motivations Spatial navigation and memory ha...

Temporal Integration in Human Auditory Cortex is Predominantly Yoked to Absolute Time

Information Science, Artificial Intelligence, Medicine, Neurology, Life Sciences, Biophysics,
Auditory cortex   Temporal integration   Speech structure   Neural computation   Electrophysiology   Time-yoked   Structure-yoked  

Temporal Integration Mechanisms in the Human Auditory Cortex: Neural Computation Is Predominantly Tied to Absolute Time In recent years, the mechanisms of temporal integration in the brain during the processing of sound structure—especially in speech and music comprehension—have attracted widespread attention in neuroscience. Sound signals, such as...

Recurrent Pattern Completion Drives the Neocortical Representation of Sensory Inference

Information Science, Artificial Intelligence, Medicine, Neurology, Life Sciences, Cell Biology, Biochemistry, Biophysics,
neocortex   pattern completion   sensory inference   illusory contours   visual cortex   neural coding  

Academic Background: Exploring Perceptual Inference and Neural Mechanisms In everyday life, our sensory systems often encounter incomplete or ambiguous information. For instance, when objects are occluded, the brain relies on prior experience and expectations to infer the whole. This inferential ability is not only a core function of the human visu...

Analysis of Learned Feature Similarities to Diagnostic Criteria in Deep Learning-Based 12-Lead ECG Classification

Information Science, Artificial Intelligence, Medicine, Medical Imaging, Cardiovascular System,
deep learning   ECG   explainable AI   feature attribution   atrial fibrillation   left bundle branch block   biosignal processing  

Interpretability Research of Deep Learning in Automated ECG Diagnosis —— Progress Overview Based on Explainable AI 1. Academic Background and Problem Statement Electrocardiogram (ECG) is an important physiological signal acquisition method for clinical diagnosis of heart diseases, with a history of over a hundred years. In recent years, with the ra...

MASA-TCN: Multi-Anchor Space-Aware Temporal Convolutional Neural Networks for Continuous and Discrete EEG Emotion Recognition

Information Science, Computer Science, Artificial Intelligence, Medicine, Psychiatry, Neurology, Clinical Psychology, Medical Imaging,
EEG signals   emotion recognition   temporal convolutional neural network   space-aware   continuous regression   discrete classification   multi-anchor fusion  

A Breakthrough in EEG Emotion Recognition: The Proposal and Experimental Analysis of the MASA-TCN Unified Model Academic Background and Research Motivation Human emotion recognition has long been a popular research direction in neuroscience, artificial intelligence, and human-computer interaction. Automatic identification of individual emotional st...

Deep Representation Learning with Sample Generation and Augmented Attention Module for Imbalanced ECG Classification

Information Science, Computer Science, Artificial Intelligence, Medicine, Medical Laboratory Science, Cardiovascular System, Life Sciences, Bioengineering,
arrhythmia detection   beat classification   imbalanced learning   deep representation learning   remote health monitoring   augmented attention module   data resampling  

Innovative Application of Deep Representation Learning in Imbalanced ECG Classification —— Academic News Report on “Deep Representation Learning with Sample Generation and Augmented Attention Module for Imbalanced ECG Classification” 1. Academic Background and Research Motivation Cardiac health monitoring holds a pivotal place in modern healthcare,...

Estimation and Conformity Evaluation of Multi-Class Counterfactual Explanations for Chronic Disease Prevention

Information Science, Artificial Intelligence, Medicine, Respiratory System, Environmental and Public Health, Cardiovascular System,
chronic disease prevention   counterfactual explanations   conformal predictions   explainable AI   cardiovascular risk   feature selection  

1. Academic Background and Research Motivation In recent years, Artificial Intelligence (AI) has made tremendous progress in healthcare. From initial uses in assisted diagnosis and risk prediction to the recommendation of personalized intervention plans, AI has become a critical tool for improving the quality and efficiency of medical services. How...