Regional Excitatory–Inhibitory Balance Relates to Self-Reference Effect on Recollection via the Precuneus/Posterior Cingulate Cortex–Medial Prefrontal Cortex Connectivity
Bibliographic record
Abstract
Self-related representation can enhance perception and memory—a phenomenon known as the self-referential effect (SRE). While SRE has been linked to the activation of the default mode network (DMN), including the precuneus/posterior cingulate cortex (Pcu/PCC) and the medial prefrontal cortex (mPFC), the underlying neurochemical processes of DMN activations remain unclear. The balance of excitation and inhibition (E/I balance) within brain circuits is crucial for cognition and may play a role in the SRE. We examine whether the ratio of glutamate/glutamine (Glx) to γ-aminobutyric acid (GABA) concentrations, measured by 1 H-magnetic resonance spectroscopy ( 1 H-MRS) as a proxy measure for E/I balance, is associated with DMN neural processes involved in self-referential encoding. Fifty-four healthy participants aged 7–35 (25 female) underwent MRS to measure levels of Glx and GABA in Pcu/PCC and completed an fMRI scan during an encoding task that involved self-referential and semantic judgments. We found that the self-related condition led to better subsequent memory and greater activation in the Pcu/PCC compared with the semantic condition. Activations in the Pcu/PCC were positively correlated with the Glx/GABA+ ratio. Task-dependent functional connectivity analysis revealed that connectivity between the Pcu/PCC and medial prefrontal cortex (mPFC) was positively associated with both the Glx/GABA+ ratio and the SRE effect on recollection accuracy. Furthermore, mediation analysis showed that a higher Glx/GABA+ ratio correlated with better SRE on memory recollection through increased Pcu/PCC–mPFC connectivity. Our study provides valuable insights into how neurochemical activity is associated with self-related cognition via functional connectivity of large-scale brain networks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".