Baseline task performance predicts mini-mental state examination improvement after individuals with dementia practice an N-back task with bilateral transcranial direct current stimulation
Bibliographic record
Abstract
INTRODUCTION: This research explores the relationship between baseline performance in dementia patients and its impact on the effectiveness of transcranial direct current stimulation (tDCS) for improving executive function. Past research suggests that those participants who are more impaired at baseline will be those who then demonstrate the greatest improvements with tDCS. In addition, we examined if bilateral or unilateral stimulation would be more effective for improving the general level of cognition of these participants. MATERIALS AND METHODS: The study involved 24 participants, with 18 diagnosed with Alzheimer's disease (AD) and 6 with Frontotemporal Dementia (FTD). These participants engaged in three rounds of N-back task training sessions, each separated by two months. The sessions included three types of stimulation: 4mA unilateral stimulation targeting the left Dorsolateral Prefrontal Cortex (DLPFC), 4mA bilateral stimulation targeting both the left and right DPFC, and sham stimulation. Additionally, a control group of elderly individuals without dementia was used to establish a benchmark for the normal average response time (RT) of the administered N-Back task. Evaluations, comprising of the N-Back task and the Mini-Mental State Examination (MMSE), were conducted before stimulation, at the final session, and two weeks post-stimulation in all rounds. RESULTS: Participants were retrospectively allocated into those whose baseline N-Back response times (RTs) were found on average to be within the normal range versus those who performed more slowly than the normal range. For the group that performed within the normal range, no significant improvement was observed on the N-Back task after a series of sessions involving active tDCS. In contrast, the participants with slower than normal RTs at baseline demonstrated improvement both on the N-Back task (faster times) and the MMSE (higher scores) after receiving active tDCS, although accompanying improvement on the MMSE task was restricted to the condition where participants received bilateral tDCS. CONCLUSION: This study replicates a pervasive finding in the tDCS literature: participants who perform worse at baseline often demonstrate the greatest improvements with tDCS. Furthermore, these results have clinical implications, in that tDCS may be most beneficial in individuals when clear deficits or impairments are present. Attempts to treat less severe participants might fail to show improvement with tDCS. Ultimately, baseline condition should be routinely considered when evaluating tDCS results.
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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 | 0.002 |
| 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 | 0.001 |
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".