Disrupting selective persistent activity with electrical stimulation impairs human working memory
Bibliographic record
Abstract
Working memory (WM) enables the temporary maintenance and manipulation of information, supporting flexible, goal-directed behavior. While converging evidence suggests that the hippocampus contributes to WM storage, its causal role in WM remains unclear. Here, we combined simultaneous intracranial single-neuron recordings in the hippocampus and several cortical areas with focal electrical stimulation in the human hippocampus to test the causal necessity of hippocampal activity for WM. Thirty patients with implanted hybrid depth electrodes performed a WM task with images as memoranda. Electrical stimulation (2 s, 50 Hz, 1 mA) was delivered to the hippocampus during the maintenance period on a subset of trials. Behaviorally, stimulation impaired WM performance, reducing accuracy and increasing response times. Neuronally, stimulation reduced memoranda-selective persistent activity in hippocampus and ventral temporal cortex (VTC), thereby disrupting content-specific neural representations. The extent of neural disruption was correlated trial-by-trial with impaired WM-related behavior, establishing a causal link between disrupted neural activity and impaired WM. At the population level, stimulation shifted neural trajectories farther from attractor states, consistent with degraded mnemonic fidelity. Together, these data provide causal evidence that persistent activity of individual neurons in hippocampus and VTC supports WM maintenance in humans. Our results demonstrate that perturbing hippocampal dynamics disrupts both single-neuron coding and population-level attractor stability, linking cellular mechanisms to behavior and highlighting hippocampal contributions to WM maintenance.
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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 | 0.000 |
| 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".