Common and Unique Neural Activations in Autobiographical, Episodic, and Semantic Retrieval
Bibliographic record
Abstract
This study sought to explore the neural correlates that underlie autobiographical, episodic, and semantic memory. Autobiographical memory was defined as the conscious recollection of personally relevant events, episodic memory as the recall of stimuli presented in the laboratory, and semantic memory as the retrieval of factual information and general knowledge about the world. Our objective was to delineate common neural activations, reflecting a functional overlap, and unique neural activations, reflecting functional dissociation of these memory processes. We conducted an event-related functional magnetic resonance imaging study in which we utilized the same pictorial stimuli but manipulated retrieval demands to extract autobiographical, episodic, or semantic memories. The results show a functional overlap of the three types of memory retrieval in the inferior frontal gyrus, the middle frontal gyrus, the caudate nucleus, the thalamus, and the lingual gyrus. All memory conditions yielded activation of the left medial-temporal lobe; however, we found a functional dissociation within this region. The anterior and superior areas were active in episodic and semantic retrieval, whereas more posterior and inferior areas were active in autobiographical retrieval. Unique activations for each memory type were also delineated, including medial frontal increases for autobiographical, right middle frontal increases for episodic, and right inferior temporal increases for semantic retrieval. These findings suggest a common neural network underlying all declarative memory retrieval, as well as unique neural contributions reflecting the specific properties of retrieved memories.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".