Altered Central Integration of Dual Somatosensory Input After Cervical Spine Manipulation
Bibliographic record
Abstract
OBJECTIVE: The aim of the current study was to investigate changes in the intrinsic inhibitory interactions within the somatosensory system subsequent to a session of spinal manipulation of dysfunctional cervical joints. METHOD: Dual peripheral nerve stimulation somatosensory evoked potential (SEP) ratio technique was used in 13 subjects with a history of reoccurring neck stiffness and/or neck pain but no acute symptoms at the time of the study. Somatosensory evoked potentials were recorded after median and ulnar nerve stimulation at the wrist (1 millisecond square wave pulse, 2.47 Hz, 1 x motor threshold). The SEP ratios were calculated for the N9, N11, N13, P14-18, N20-P25, and P22-N30 peak complexes from SEP amplitudes obtained from simultaneous median and ulnar (MU) stimulation divided by the arithmetic sum of SEPs obtained from individual stimulation of the median (M) and ulnar (U) nerves. RESULTS: There was a significant decrease in the MU/M + U ratio for the cortical P22-N30 SEP component after chiropractic manipulation of the cervical spine. The P22-N30 cortical ratio change appears to be due to an increased ability to suppress the dual input as there was also a significant decrease in the amplitude of the MU recordings for the same cortical SEP peak (P22-N30) after the manipulations. No changes were observed after a control intervention. CONCLUSION: This study suggests that cervical spine manipulation may alter cortical integration of dual somatosensory input. These findings may help to elucidate the mechanisms responsible for the effective relief of pain and restoration of functional ability documented after spinal manipulation treatment.
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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) | 0.002 | 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".