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Brain Imaging

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...

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Spectral methods for functional brain imaging.

David Kleinfeld, Partha P Mitra

Cold Spring Harbor Protocols

|March 5, 2014

Summary

This summary is machine-generated.

Signal processing techniques help analyze complex dynamic functional imaging data. These methods simplify spatiotemporal structures and separate useful signals from noise for better insights.

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Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Published on: June 30, 2018

Area of Science:

Neuroimaging
Biomedical Engineering
Data Science

Background:

Dynamic functional imaging generates large, complex datasets with significant spatial and temporal characteristics.
Analyzing these datasets requires advanced methods to extract meaningful information.

Purpose of the Study:

To introduce signal processing techniques for analyzing functional imaging data.
To enable the separation of signal from noise in complex spatiotemporal data.

Main Methods:

Signal processing algorithms.
Spatiotemporal data analysis.
Noise reduction techniques.

Main Results:

Distillation of underlying spatiotemporal structure.
Effective separation of signal and noise components.

Conclusions:

Signal processing is crucial for interpreting complex functional imaging data.
These techniques enhance the ability to identify true neural activity amidst noise.