Caltech’s Computation and Neural Systems (CNS) program enables undergraduates to study the brain through the lens of computation, biology, and engineering. These project ideas reflect cutting-edge research in neural decoding, modeling, brain-computer interfaces, and machine learning.
Brain-Computer Interface for Motor Control Using EEG Signals
Modeling Spiking Neural Networks for Pattern Recognition
Simulating Visual Cortex Behavior with Deep Convolutional Networks
Neural Decoding of Sensory Input Using Statistical Models
Design of Adaptive Neuroprosthetics Using Reinforcement Learning
Computational Modeling of Working Memory Circuits
AI-Based Emotion Recognition from Neural Signal Patterns
Real-Time Signal Processing Pipeline for Neural Data
Analysis of Functional MRI Data for Brain Connectivity Mapping
Hybrid Models of Symbolic and Sub-symbolic Cognitive Processing
Development of Neural Network Models to Predict Decision Making
Neuromorphic Hardware Design for Low-Power Inference
Modeling Plasticity in Hippocampal Learning Circuits
Data-Driven Prediction of Neural Disorders Using ML Classifiers
Designing Closed-Loop Feedback Systems in Brain-Machine Interfaces
Collexa helps Caltech CNS students with neural data analysis, signal processing, simulation tools, and integrating ML into neuroscience research workflows.
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