The Use of Therapeutic Music Training to Remediate Cognitive Impairment Following an Acquired Brain Injury: The Theoretical Basis and a Case Study
Bibliographic record
Abstract
Cognitive impairment is the most common sequelae following an acquired brain injury (ABI) and can have profound impact on the life and rehabilitation potential for the individual. The literature demonstrates that music training results in a musician's increased cognitive control, attention, and executive functioning when compared to non-musicians. Therapeutic Music Training (TMT) is a music therapy model which uses the learning to play an instrument, specifically the piano, to engage and place demands on cognitive networks in order to remediate and improve these processes following an acquired brain injury. The underlying theory for the efficacy of TMT as a cognitive rehabilitation intervention is grounded in the literature of cognition, neuroplasticity, and of the increased attention and cognitive control of musicians. This single-subject case study is an investigation into the potential cognitive benefit of TMT and can be used to inform a future more rigorous study. The participant was an adult male diagnosed with cognitive impairment as a result of a severe brain injury following an automobile accident. Pre- and post-tests used standardized neuropsychological measures of attention: Trail Making A and B, Digit Symbol, and the Brown- Peterson Task. The treatment period was twelve months. The results of Trail Making Test reveal improved attention with a large decrease in test time on both Trail Making A (-26.88 s) and Trail Making B (-20.33 s) when compared to normative data on Trail Making A (-0.96 s) and Trail Making B (-3.86 s). Digit Symbol results did not reveal any gains and indicated a reduction (-2) in free recall of symbols. The results of the Brown-Peterson Task reveal improved attention with large increases in the correct number of responses in the 18-s delay (+6) and the 36-s delay (+7) when compared with normative data for the 18-s delay (+0.44) and the 36-s delay (-0.1). There is sparse literature regarding music based cognitive rehabilitation and a gap in the literature between experimental research and clinical work. The purpose of this paper is to present the theory for Therapeutic Music Training (TMT) and to provide a pilot case study investigating the potential efficacy of TMT to remediate cognitive impairment following an ABI.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.002 |
| 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".