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Scan for outdated or missing drivers - takes under a minuteDriver Scan →Repair Windows errors before they cause bigger problemsFix Now →fMRI and EEG measure different things, so neither is universally better. fMRI detects blood-oxygen changes linked indirectly to neural activity and can map brain-wide patterns in detail. EEG records electrical potentials at the scalp, providing much faster timing but less precise information about where activity originates. What a method can decode depends on the question, the signals collected, and how the decoder is trained and tested—not on a simple ranking of “accuracy.”
What fMRI and EEG actually measure
fMRI measures a delayed blood-flow response
Functional MRI commonly analyzes the blood-oxygen-level-dependent (BOLD) response. It is an indirect hemodynamic correlate of neural activity: the scanner detects changes in blood oxygenation associated with activity, rather than reading thoughts or recording neurons firing directly. Because this response unfolds more slowly than neural electrical activity, fMRI is better suited to patterns associated with a task or stimulus than to tracking the precise timing of individual neural events.
EEG records electrical potentials at the scalp
Electroencephalography (EEG) measures voltage differences at electrodes placed on the scalp. These electrical signals are associated with neural activity and can change on millisecond timescales. But the signal reaching the scalp has spread through tissue, making it difficult to determine exactly where within the brain it originated.
How the main brain-imaging methods compare
No single functional neuroimaging technique answers every research question. The most useful comparison is what each method measures, and which practical and scientific trade-offs matter for the task.
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| Method | Signal measured | Spatial information | Timing | Practical trade-offs |
|---|---|---|---|---|
| fMRI | BOLD changes, an indirect hemodynamic correlate of neural activity | Detailed, whole-brain patterns; approximately 1–3 mm in an educational comparison | Limited by the slower hemodynamic response | Scanner-bound; movement is constrained |
| EEG | Electrical potentials at the scalp associated with neural activity | Limited spatial specificity; approximately 1–3 cm in an educational comparison | Millisecond-scale timing | Portable compared with MRI, but scalp signals make localization difficult |
| MEG | Magnetic fields associated with neural currents | Better localization than EEG in many settings | Millisecond-scale timing | Requires specialized instrumentation and a controlled environment |
| fNIRS | Hemodynamic changes measured using near-infrared light | Samples superficial cortex; limited depth | Limited by its hemodynamic signal | Portable and wearable compared with MRI; vulnerable to scalp and sensor-coupling effects |
| PET | Radiotracer uptake associated with metabolism or blood flow | Answers metabolic questions | Not a millisecond-scale measure of neural activity | Uses ionizing radiation and has constraints on repeat measurement |
The approximate spatial figures in this table come from a 2026 educational comparison by the Society for functional Near Infrared Spectroscopy; they are system-dependent and are not a universal head-to-head measure. Resolution and performance vary with equipment and protocol.
What fMRI decoding has demonstrated—and what it has not
A 2023 Nature Neuroscience study by Tang, LeBel, Jain and colleagues reported a non-invasive fMRI decoder that produced intelligible word sequences recovering the meaning of perceived speech, imagined speech, and silent videos. This was a specific research protocol involving participant-specific training. The authors report that the core results included three participants, making the work a proof-of-concept demonstration rather than population-level validation.
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The authors state that “subject cooperation is required both to train and to apply the decoder.” The result does not establish universal decoding of arbitrary thoughts, nor effortless or covert access to a person’s mind. It shows that a decoder can infer aspects of meaning under the study’s conditions from measured brain activity.
Can EEG read thoughts like fMRI?
Neither EEG nor fMRI literally reads thoughts. A decoder maps measured signals to a defined output—such as which image category a participant saw or the meaning of material presented under a controlled protocol. Its results depend on the task, training data, participant, stimulus design, and evaluation method.
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A 2024 NeurIPS paper illustrates why accuracy figures need context: in a follow-up experiment using randomly arranged images, EEG classification reached at most 7.0% accuracy against a 2.5% chance level. Those numbers describe that particular task and dataset. They are not an overall measure of EEG’s ability to decode thoughts, and they do not form a direct accuracy contest with the fMRI semantic-decoding study.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Which method is more accurate?
Ask “accurate for what?” fMRI can be useful when the priority is detailed, brain-wide spatial patterns. EEG is useful when the timing of neural activity matters. MEG combines fast timing with better localization than EEG in many settings, while fNIRS offers a more portable way to sample hemodynamic changes near the cortical surface. PET can address questions about metabolism, with radiation and repeat-measurement constraints.
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- For spatial mapping across the brain, consider fMRI, while accounting for its indirect, slow signal and scanner constraints.
- For fast changes in electrical brain activity, consider EEG; do not mistake temporal precision for precise localization.
- For fast timing with better localization than EEG in many settings, MEG may fit, if specialized equipment and a controlled environment are available.
- For portable measurement of superficial cortical hemodynamic changes, fNIRS may fit, with limited depth and sensitivity to scalp and coupling effects.
- For metabolic questions, PET may be appropriate when its use of a radiotracer and limits on repeat measurement are acceptable.
Decoding percentages should only be compared when the participants, stimuli, training setup, chance baseline, and scoring metric are genuinely comparable. A result from one task cannot establish that a modality is generally more accurate than another.
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