Research Articles
Implementing EEGNet for Brain-Computer Interfaces: A Comprehensive Guide for Neuroscience Researchers and Clinical Application Developers
This article provides a detailed, practical guide to implementing EEGNet, a compact convolutional neural network architecture specifically designed for electroencephalogram (EEG)-based brain-computer interfaces (BCIs).
Digital Twin Cognition: A Framework for Biomimetic Benchmarking in Neuroscience and Drug Development
This article explores the transformative potential of digital twin technology for creating biomimetic benchmarks in neuroscience.
Configuring Strong and Weak Scaling Benchmarks: A Complete Guide for Biomedical Researchers
This guide provides researchers, scientists, and drug development professionals with a comprehensive framework for configuring, executing, and analyzing strong and weak scaling benchmarks in high-performance computing (HPC) environments.
Best Practices for Neural Decoding with Machine Learning: A Guide for Biomedical Researchers
This article provides a comprehensive guide for researchers and scientists on implementing machine learning for neural decoding.
A Practical Guide to Evolutionary Algorithms for Neuron Model Fitting in Drug Development
This article provides a comprehensive guide for researchers and drug development professionals on implementing evolutionary algorithms (EAs) for optimizing neuron model parameters.
HPC Benchmarking for Neuronal Networks: A Comprehensive Guide for Biomedical Research
This article provides a comprehensive guide for researchers and drug development professionals on conducting high-performance computing (HPC) benchmarking experiments for neuronal networks.
Implementing NeuroBench Algorithm Track: A Complete Guide for Neuromorphic Computing Research
This comprehensive guide provides researchers and scientists with practical knowledge for implementing the NeuroBench algorithm track, a standardized framework for benchmarking neuromorphic computing algorithms.
A Modular Workflow for Performance Benchmarking of Neuronal Network Simulations
This article explores the critical role of standardized, modular benchmarking workflows in advancing computational neuroscience and drug discovery.
A 2025 Guide to Benchmarking Machine Learning Algorithms for Drug Discovery
This article provides researchers, scientists, and drug development professionals with a comprehensive framework for benchmarking machine learning training algorithms.
Benchmarking Predictive Coding Networks: New Tools and Benchmarks for Scalable, Biologically-Plausible AI in Drug Discovery
This article explores the latest advancements in benchmarking Predictive Coding Networks (PCNs), a class of biologically-plausible neural networks.