Analyze neural, physiological, and behavioral time-series data.
- Time-Frequency Analysis: Compute short-time Fourier or continuous wavelet transforms and time-varying coherence between signals
- Multi-Resolution Analysis: Separate signal components with wavelet-based or data-adaptive multiresolution analysis techniques
- Signal Analyzer App: Visualize, process, and analyze signal data interactively
- Feature Extraction: Automatically extract deep features from time-series data using a wavelet scattering framework
- Signal Labeling: Label signals automatically and interactively, and visualize labeled signals, with the Signal Labeler app
- Deep Learning: Apply LSTM networks and CNNs with time-frequency analysis for signal classification and prediction tasks
Analyze images, volumes, and videos at the neuron, brain, and subject scales.
- Volumetric Data Visualization: View labeled volumetric data interactively with the Volume Viewer app
- Volumetric Data Processing: Process volumetric data with over 70 3D image processing functions
- Neuroimaging Data: Read, write, and explore NIfTI files
- Big Image Data: Represent and process images that are too large to fit in memory, including labeled and multiple resolution image data
- Image Labeling: Interactively label image-based data with the Image Labeler and Video Labeler apps
- Deep Learning: Apply 2D and 3D CNN models for object detection and semantic segmentation and LSTM models for video classification
Create, train, and run predictive models for neuroscience data.
- Deep Learning Experiments: Compare networks trained under various conditions with the Experiment Manager app
- Framework Interoperability: Import and export deep learning models from and to other frameworks via the ONNX model format
- Deep Learning Customization: Build custom training loops and custom layers more easily with automatic differentiation
- Machine Learning: Discover clusters and noise in data with the DBSCAN algorithm
- Multidimensional Visualization: Visualize high-dimensional data using t-SNE
Create, share, and scale data analyses.
- Unlimited Parallel Computing: MATLAB Parallel Server supports unlimited scaling for every user on campus
- Thread-Based Parallelism: Achieve greater speedups on multi-core machines by eliminating data copies
- Live Editor: Create rich documents combining code, text, figures, interactive controls, animations, and more
- Cloud Computing: Configure MATLAB enabled cloud instances on Amazon Web Services (AWS) using the MathWorks Cloud Center
- Remote Data: Access remote data on cloud storage systems like Amazon S3, Azure Storage Blobs, and Hadoop HDFS
Process live signals for brain recordings, behavioral control systems, and BCIs.
- Stateflow: Graphically design state machine logic for behavioral control systems, runnable in MATLAB or Simulink
- MATLAB Coder: Translate over 1900 MATLAB functions to ANSI C or C++ code for faster performance and real-time applications
- HDL Coder: Target FPGA hardware for video processing and closed-loop experiments using high-level MATLAB or Simulink programming
- Multithreading: Call MATLAB asynchronously from user-created threads using the C++ engine API
- Performance: Run existing MATLAB code over two times faster