Quick Navigation
Topics
Quantum Simulation
Quantum Chemistry
Quantum Machine Learning
Entanglement Theory Quantum Correlations
Magnetoencephalography: From SQUIDs to neuroscience. Neuroimage 20th anniversary special edition.
PubMed
Authors: Hari R, Salmelin R
Year
2012
Paper ID
12185
Status
Peer-reviewed
Abstract Read
~2 min
Abstract Words
138
Citations
N/A
Abstract
Magnetoencephalography (MEG), with its direct view to the cortex through the magnetically transparent skull, has developed from its conception in physics laboratories to a powerful tool of basic and clinical neuroscience. MEG provides millisecond time resolution and allows real-time tracking of brain activation sequences during sensory processing, motor planning and action, cognition, language perception and production, social interaction, and various brain disorders. Current-day neuromagnetometers house hundreds of SQUIDs, superconducting quantum interference devices, to pick up signals generated by concerted action of cortical neurons. Complementary MEG measures of neuronal involvement include evoked responses, modulation of cortical rhythms, properties of the on-going neural activity, and interareal connectivity. Future MEG breakthroughs in understanding brain dynamics are expected through advanced signal analysis and combined use of MEG with hemodynamic imaging (fMRI). Methodological development progresses most efficiently when linked with insightful neuroscientific questions.
Why This Paper Matters
- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
- It adds a 2012 reference point for readers tracking recent quantum research.
- Magnetoencephalography (MEG), with its direct view to the cortex through the magnetically transparent skull, has developed from its conception in physics laboratories to a...
Paper Tools
Become a member to use research tools
Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.
Publisher Share
Cite This Paper
Copy URL
Compare
Copy DOI Add to Reading List
Category Correction Request
Category Correction Request
Help us improve classification quality by proposing a better category. Every request is reviewed by an admin.
Sign in to submit a category correction request for this paper.
Log In to SubmitReferences & Citation Signals
Community Reactions
Quick sentiment from readers on this paper.
Score:
0
Likes: 0
Dislikes: 0
Sign in to react to this paper.
Discussion & Reviews (Moderated)
Average Rating: 0.0 / 5 (0 ratings)
No written reviews yet.