Research Articles
Brain Imaging Data Analysis Workflows: A Comprehensive Guide from Foundations to AI
This article provides a comprehensive guide to modern brain imaging data analysis workflows, tailored for researchers, scientists, and drug development professionals.
Advanced Artifact Removal in Neurotechnology: From Foundational Principles to Cutting-Edge AI Applications
This comprehensive review examines state-of-the-art artifact removal techniques in neurotechnology signal processing, addressing the critical challenge of distinguishing genuine neural signals from contamination across EEG, ECoG, and intracortical recordings.
Brain-Computer Interfaces in 2025: From Foundational Principles to Clinical Applications and Future Trends
This article provides a comprehensive overview of the current state of Brain-Computer Interface (BCI) technology, tailored for researchers, scientists, and drug development professionals.
Ensuring fMRI Preprocessing Pipeline Reliability: A Guide for Reproducible Research and Clinical Translation
Functional magnetic resonance imaging (fMRI) is a cornerstone of modern neuroscience and is increasingly used to inform drug development and clinical diagnostics.
Deep Brain Stimulation Parameter Optimization: From Foundational Principles to AI-Driven Future
This article provides a comprehensive analysis of deep brain stimulation (DBS) parameter settings, addressing the critical needs of researchers and clinical scientists.
Precision Neuromodulation: Optimizing TMS Protocols with Neuroimaging and AI for Clinical Translation
This article synthesizes the latest advancements in transcranial magnetic stimulation (TMS) protocol optimization, a critical endeavor for enhancing the efficacy and reliability of this non-invasive neuromodulation therapy.
Neural Population Dynamics Optimization: A Brain-Inspired Metaheuristic for Advanced Drug Development
This article explores the Neural Population Dynamics Optimization Algorithm (NPDOA), a novel brain-inspired meta-heuristic, and its transformative potential for researchers and professionals in drug development.
Optimizing EEG Channel Selection for Brain-Computer Interfaces: Strategies for Enhanced Accuracy and Practical Application
This article provides a comprehensive analysis of Electroencephalogram (EEG) channel selection methods for Brain-Computer Interface (BCI) systems, a critical step for improving computational efficiency and user comfort.
Deep Learning in EEG Analysis: A Comprehensive Review of Classification Methods and Clinical Applications
This article provides a comprehensive overview of deep learning methodologies for electroencephalography (EEG) signal classification, tailored for researchers, scientists, and drug development professionals.
Spiking Neural Networks: The Next Frontier in Brain-Inspired Computing for Biomedical Research
Spiking Neural Networks (SNNs), the third generation of neural networks, offer a paradigm shift from traditional artificial neural networks (ANNs) by mimicking the brain's efficient, event-driven communication.