Aberrant inhibitory processing in the somatosensory cortices of cannabis-users
Bibliographic record
Abstract
BACKGROUND: ) receptors. THC is known to inhibit presynaptic neurotransmission and has been repeatedly linked to acute decrements in cognitive function across multiple domains. Previous electrophysiological studies of sensory gating have shown specific deficits in inhibitory processing in cannabis-users, but to date these findings have been limited to the auditory cortices, and the degree to which these aberrations extend to other brain regions remains largely unknown. METHODS: We used magnetoencephalography (MEG) and a paired-pulse somatosensory stimulation paradigm to probe inhibitory processing in 29 cannabis-users (i.e. at least four times per month) and 41 demographically matched non-user controls. MEG responses to each stimulation were imaged in both the oscillatory and time domain, and voxel time-series data were extracted to quantify the dynamics of sensory gating, oscillatory gamma activity, evoked responses, and spontaneous neural activity. RESULTS: We observed robust somatosensory responses following both stimulations, which were used to compute sensory gating ratios. Cannabis-users exhibited significantly impaired gating relative to non-users in somatosensory cortices, as well as decreased spontaneous neural activity. In contrast, oscillatory gamma activity did not appear to be affected by cannabis use. CONCLUSIONS: We observed impaired gating of redundant somatosensory information and altered spontaneous activity in the same cortical tissue in cannabis-users compared to non-users. These data suggest that cannabis use is associated with a decline in the brain's ability to properly filter repetitive information and impairments in cortical inhibitory processing.
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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) | 0.003 | 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".