Simultaneous EEG and MEG recordings reveal vocal pitch elicited cortical gamma oscillations in young and older adults
Bibliographic record
Abstract
The frequency-following response with origin in the auditory brainstem represents the pitch contour of voice and can be recorded with electrodes from the scalp. MEG studies also revealed a cortical contribution to the high gamma oscillations at the fundamental frequency (f0) of a vowel stimulus. Therefore, studying the cortical component of the frequency-following response could provide insights into how pitch information is encoded at the cortical level. Comparing how aging affects the different responses may help to uncover the neural mechanisms underlying speech understanding deficits in older age. We simultaneously recorded EEG and MEG responses to the syllable /ba/. MEG beamformer analysis localized sources in bilateral auditory cortices and the midbrain. Time-frequency analysis showed a faithful representation of the pitch contour between 106 Hz and 138 Hz in the cortical activity. A cross-correlation revealed a latency of 20 ms. Furthermore, stimulus onsets elicited cortical 40-Hz responses. Both the 40-Hz and the f0 response amplitudes increased in older age and were larger in the right hemisphere. The effects of aging and laterality of the f0 response were evident in the MEG only, suggesting that both effects were characteristics of the cortical response. After comparing f0 and N1 responses in EEG and MEG, we estimated that approximately one-third of the scalp-recorded f0 response could be cortical in origin. We attributed the significance of the cortical f0 response to the precise timing of cortical neurons that serve as a time-sensitive code for pitch.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".