Neuroscientists seek to understand brain structure and function at every physical scale: from molecules to neurons to whole brains. From brain mapping (macroscale) to cellular neuroscience (microscale), typical experimental studies follow similar workflows. These begin with collecting data (signals, images, timing events) from many individual trials and subjects, followed by raw data processing, and analysis of complex data sets to identify statistically meaningful patterns. To guide their hypotheses, scientists create increasingly sophisticated models to predict the principles of brain function.

For neuroscientists tackling these challenges, MATLAB® helps at every step. It can coordinate experiments, process noisy signals, wrangle complex data, and build and simulate detailed models of brain circuits. MATLAB uses fast, robust implementations of proven algorithms from signal processing, computer vision, machine learning, and other fields. MATLAB enables neuroscientists to manage their growing data volumes and to access research computing resources for large-scale analyses and simulations.

Neuroscientists are increasingly collaborating across the globe. They are creating, sharing, and using MATLAB community toolboxes and apps for neuroscience. And they are working with industry, building upon MATLAB enabled products designed for neuroscience research.


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Approaches such as MRI, EEG, and PET/SPECT reveal anatomy and function at the scale of the whole brain.

Approaches such as microscopy and electrophysiology are used to study brain activity and structure at the scale of individual neurons and synapses.

Various approaches are used to monitor the sensory inputs and output actions of experimental subjects.

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Machine Learning and Computer Vision for Biological Imaging Applications

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Vijay Iyer, Ph.D., Neuroscience Community Liaison

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