Latest Features
Explore the latest MATLAB features relevant for neuroscience
Neurosignals and Biosignals
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
Related Products: Deep Learning Toolbox, Signal Processing Toolbox, Wavelet Toolbox
Neuroimaging, Microscopy, and Ethology
Analyze images, volumes, and videos at the neuron, brain, and subject scales.
- Neuroimaging and Microscopy Data: Access image slices and volumes from 3-D NIfTI and TIFF files
- Volumetric Data: View labeled volumetric data interactively with the Volume Viewer app, extract image slices, including at oblique angles, and apply over 70 process 3-D image processing functions
- Big Image Data: Represent and process images that are too large to fit in memory, including labeled and multiple resolution image data
- Image Labeling: Apply and view labels to image data via ROI objects and the interactive 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
Related Products: Computer Vision Toolbox, Image Processing Toolbox, Deep Learning Toolbox, Wavelet Toolbox
Machine Learning and Deep Learning
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
Related Products: Deep Learning Toolbox, Parallel Computing Toolbox, Statistics and Machine Learning Toolbox
Neural Data Science
Create, share, and scale data analyses.
- Graphics: Flexible data distribution plots such as swarm and box charts
- Graphics: Export graphics for use in scientific publications
- Live Editor: Create rich documents combining code, text, figures, interactive controls, animations, and more
- Unlimited Parallel Computing: MATLAB Parallel Server supports unlimited scaling for every user on campus
- Cloud Computing: Apply your campus license to run and scale MATLAB in the cloud, including connections to remote data sources such as Amazon S3 and Hadoop HDFS
Experiment Control
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 3000 MATLAB and toolbox 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
Related Products: Data Acquisition Toolbox, MATLAB Coder, Stateflow, Simulink Real-Time