Plasticity in neuromagnetic cortical responses suggests enhanced auditory object representation
Bibliographic record
Abstract
BACKGROUND: Auditory perceptual learning persistently modifies neural networks in the central nervous system. Central auditory processing comprises a hierarchy of sound analysis and integration, which transforms an acoustical signal into a meaningful object for perception. Based on latencies and source locations of auditory evoked responses, we investigated which stage of central processing undergoes neuroplastic changes when gaining auditory experience during passive listening and active perceptual training. Young healthy volunteers participated in a five-day training program to identify two pre-voiced versions of the stop-consonant syllable 'ba', which is an unusual speech sound to English listeners. Magnetoencephalographic (MEG) brain responses were recorded during two pre-training and one post-training sessions. Underlying cortical sources were localized, and the temporal dynamics of auditory evoked responses were analyzed. RESULTS: After both passive listening and active training, the amplitude of the P2m wave with latency of 200 ms increased considerably. By this latency, the integration of stimulus features into an auditory object for further conscious perception is considered to be complete. Therefore the P2m changes were discussed in the light of auditory object representation. Moreover, P2m sources were localized in anterior auditory association cortex, which is part of the antero-ventral pathway for object identification. The amplitude of the earlier N1m wave, which is related to processing of sensory information, did not change over the time course of the study. CONCLUSION: The P2m amplitude increase and its persistence over time constitute a neuroplastic change. The P2m gain likely reflects enhanced object representation after stimulus experience and training, which enables listeners to improve their ability for scrutinizing fine differences in pre-voicing time. Different trajectories of brain and behaviour changes suggest that the preceding effect of a P2m increase relates to brain processes, which are necessary precursors of perceptual learning. Cautious discussion is required when interpreting the finding of a P2 amplitude increase between recordings before and after training and learning.
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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) | 0.005 | 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".