Academic Articles & Research Papers

The influence of catch trials on the consolidation of motor memory in force field adaptation tasks

In computational neuroscience it is generally accepted that human motor memory contains neural representations of the physics of the musculoskeletal system and the objects in the environment. These representations are called internal models...

Editorial: 2021 WHO classification of pediatric brain tumors: a final wedding between morphology and molecular biology?

The Genetic Architecture of Murine Glutathione Transferases.

Glutathione S-transferase (GST) genes play a protective role against oxidative stress and may influence disease risk and drug pharmacokinetics. In this study, massive multiscalar trait profiling across a large population of mice derived fro...

A Novel Depression Rehabilitation Game Framework Using VR Based on Neurofeedback

At present,depression is treated with antidepressant drugs and assisted with psychotherapy and physical therapy,and these expensive and time-consuming treatment methods often end prematurely and result in a prolonged course without effectiv...

QG-WRN: A Quantum-Enhanced Graph Convolutional Wide Residual Network for ASD Diagnosis via Neuroimaging Sensing Technology

The pathological mechanism of autism spectrum disorder (ASD) exhibits dual heterogeneity: abnormal local energy metabolism and brain-wide high-order topological failure. To synergistically characterize these complex signals captured by adva...

A Fully Adapted Headstage With Custom Electrode Arrays Designed for Electrophysiological Experiments

Electrophysiological recordings lead amongst the techniques that aim to investigate the dynamics of neural activity sampled from large neural ensembles. However, the financial costs associated with the state-of-the-art technology used to ma...

A recurrent neural network framework for flexible and adaptive decision making based on sequence learning.

The brain makes flexible and adaptive responses in a complicated and ever-changing environment for an organism's survival. To achieve this, the brain needs to understand the contingencies between its sensory inputs, actions, and rewards. Th...

Zonula occludens-1 at the ischemic blood–brain barrier: mechanisms of disruption, functional significance, and experimental modulation.

Natural language processing in Alzheimer's disease research: Systematic review of methods, data, and efficacy

Abstract INTRODUCTION Alzheimer's disease (AD) prevalence is increasing, with no current cure. Natural language processing (NLP) offers the potential for non‐invasive diagnostics, social burden assessment, and research advancements in AD. M...

Connectionist Approaches to Natural Language Processing

Preface, N. Sharkey and R. Reilly connectionist natural language processing semantics, M.D. Dyer, et al distributed symbol discovery through symbol recirculation - toward natural language processing in distributed connectionist networks, R....

Analyzing Brain Tumor Classification Techniques: A Comprehensive Survey

Classification of brain tumour is critical in medical image analysis and diagnosis as it aids in determining the affinity of cases to select treatment paths. This feature underscores the importance of accurate classification of brain tumour...

Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain)

Neural networks models for NLP are typically implemented without the explicit encoding of language rules and yet they are able to break one performance record after another. This has generated a lot of research interest in interpreting the ...

Brains and algorithms partially converge in natural language processing

Deep learning algorithms trained to predict masked words from large amount of text have recently been shown to generate activations similar to those of the human brain. However, what drives this similarity remains currently unknown. Here, w...

Diminished Auditory Responses during NREM Sleep Correlate with the Hierarchy of Language Processing.

Natural sleep provides a powerful model system for studying the neuronal correlates of awareness and state changes in the human brain. To quantitatively map the nature of sleep-induced modulations in sensory responses we presented participa...

A Semantic Hybrid Temporal Approach for Detecting Driver Mental Fatigue

Driver mental fatigue is considered a major factor affecting driver behavior that may result in fatal accidents. Several approaches are addressed in the literature to detect fatigue behavior in a timely manner through either physiological o...

Link Predictions with Bi-Level Routing Attention

Background/Objectives: Knowledge Graphs (KGs) are often incomplete, which can significantly impact the performance of downstream applications. Manual completion of KGs is time-consuming and costly, emphasizing the importance of developing a...

Neural evidence for progressive decline of visual face recognition ability in Alzheimer's disease.

An Overview of the Attention Mechanisms in Computer Vision

Abstract Deep convolutional neural network (CNN) plays an important role in the field of computer vision and image processing. In order to further improve the performance of CNN, scholars have conducted a series of new explorations, such as...

Hyperspectral imaging and machine learning in brain tumor surgery: Current evidence, clinical applications, and future directions.

A hybrid CNN-BiLSTM network with additive attention for automated four-stage classification of Alzheimer's disease from brain MRI.