EEG and MEG: relevance to neuroscience.
By F. H. Lopes da Silva. Neuron, 2013
828 citations recorded by the source corpus.
Subfields: Cognitive Neuroscience
View Paper: https://www.semanticscholar.org/paper/2230aa1127b836c11b3b7acfe3dd2574adbceab5
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cognitive Neuroscience
- Christoph Kayser
- Joachim Gross
- Stefano Panzeri
- György Buzsáki
- Ganesh R. Naik
- Jakob H. Macke
- Jessica Fortier-Lavallée
- R. Zatorre
Citations in the corpus
- Neural population coding: combining insights from microscopic and mass signals (2015, background): “Measures of mass activity at high temporal resolution (LFP, ECoG, EEG, MEG) cannot resolve individual neurons (and sometimes even brain regions), but capture temporal activity patterns that are coordinated across multiple neurons [108].”
- Progress in Brain Computer Interface: Challenges and Opportunities (2019, background): “The neuronal signals attenuate through some layers of tissues having complex geometry and diverse electrical properties; however, the magnetic permeability in the cerebrospinal fluid, skull, and skin, is consistent [79].”
- Hippocampal sharp wave‐ripple: A cognitive biomarker for episodic memory and planning (2015, background): “…planning; epilepsy; learning INTRODUCTION Since the early days of human neurophysiology, scientists have been fascinated by the variety of mesoscopic events that can be recorded from the scalp as EEG and directly from within the brain as local field potential (LFP; cf., Lopes da Silva, 2013).”
- Simultaneous invasive and non-invasive recordings in humans: A novel Rosetta stone for deciphering brain activity (2024, unknown): “Thus, the complement of EEG and MEG can capture multiple sources of neuronal activity from outside of the brain (Lopes da Silva, 2013).”
- Information-based rhythmic transcranial magnetic stimulation to accelerate learning during auditory working memory training: a proof-of-concept study (2024, background): “…frequencies reflect fundamental elements of brain function: delta (0.5 – 3 Hz), theta (4 – 8 Hz), alpha (8 – 12 Hz), beta (12 – 30 Hz), gamma (30 – 150 Hz) frequency bands are commonly observed in both domain-general and domain-specific cognitive states (Basar et al., 2001; Lopes da Silva, 2013).”