Monotic Versus Dichotic Multiple-Stimulus Auditory Steady State Responses in Young Children
Bibliographic record
Abstract
In Brief In their recent study on infant multiple auditory steady state responses (ASSR), the authors found that ASSR amplitudes unexpectedly decreased when switching from 1-ear stimulation to 2-ear stimulation, a result not present in adults. In addition, residual EEG noise levels increased in the 2-ear condition. In the present study, to determine whether to use 1-ear or 2-ear multiple ASSR Protocols clinically, the authors tested a new group of 19 young children to determine whether these unexpected findings could be replicated. ASSR amplitude and EEG noise were compared for 1-ear (4 stimuli) versus 2-ear (8 stimuli) multiple stimuli presented at 60 dBHL. Results indicated a small but significant decrease in amplitudes going from 1-ear (40.1 nV) to 2-ear (37.9 nV) multiple stimuli. EEG noise was not significantly different between the 2 conditions. Despite small amplitude decreases, the 2-ear stimulus condition was more efficient for infants and young children with normal hearing. In the present study, to determine whether to use one-ear or twoear multiple auditory steady state response protocols clinically, a group of 19 young children were tested to determine whether the unexpected findings (lower ASSR amplitudes and higher EEG noise for dichotic versus monotic conditions) of the previous study conducted by Hatton and Stapells (2011) could be replicated. Results indicated a small but significant decrease in amplitudes going from one-ear to two-ear multiple stimuli, with no significant change in EEG noise. Nevertheless, the two-ear stimulus condition was more efficient.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".