Functional Connectivity Substrates for tDCS Response in Minimally Conscious State Patients
Bibliographic record
Abstract
Transcranial direct current stimulation (tDCS) is a non-invasive technique recently employed in disorders of consciousness, and determining a transitory recovery of signs of consciousness in almost half of minimally conscious state (MCS) patients. Although the rising evidences about its possible role in the treatment of many neurological and psychiatric conditions exist, no evidences exist about brain functional connectivity substrates underlying tDCS response. We retrospectively evaluated resting state functional Magnetic Resonance Imaging (fMRI) of 16 sub-acute and chronic MCS patients (6 tDCS responders) who successively received a single left dorsolateral prefrontal cortex (DLPFC) tDCS in a double-blind randomized cross-over trial. A seed-based approach for regions of left extrinsic control network (ECN) and default-mode network (DMN) was performed. tDCS responders showed an increased left intra-network connectivity for regions co-activated with left DLPFC, and significantly with left inferior frontal gyrus. Non-responders (NR) MCS patients showed an increased connectivity between left DLPFC and midline cortical structures, including anterior cingulate cortex and precuneus. Our findings suggest that a prior high connectivity with regions belonging to ECN can facilitate transitory recovery of consciousness in a subgroup of MCS patients that underwent tDCS treatment. Therefore, resting state-fMRI could be very valuable in detecting the neuronal conditions necessary for tDCS to improve behavior in MCS.
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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) | 0.001 | 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".