Controlled retrieval relies on directed interactions between semantic control regions and visual cortex: MEG evidence from oscillatory dynamics
Bibliographic record
Abstract
Abstract To navigate the world, we store knowledge about relationships between concepts and retrieve this information flexibly to suit our goals. The semantic control network, comprising left inferior frontal gyrus (IFG) and posterior middle temporal gyrus (pMTG), is thought to orchestrate this flexible retrieval by modulating sensory inputs. However, interactions between semantic control and input regions are not sufficiently understood. Moreover, pMTG’s well-formed structural connections to IFG and visual cortex suggest it as a candidate region to integrate control and input processes. We used magnetoencephalography to investigate oscillatory dynamics during semantic decisions to pairs of words, when participants (both sexes) did or did not know the type of semantic relation between them. IFG showed increases and decreases in oscillatory activity to prior task knowledge, while pMTG only showed positive task knowledge effects. Furthermore, IFG provided sustained feedback to pMTG when task goals were known, while in the absence of goals this feedback was delayed until receiving bottom-up input from the second word. This goal-dependent feedback coincided with an earlier onset of feedforward signalling from visual cortex to pMTG, indicating rapid retrieval of task-relevant features. This pattern supports a model of semantic cognition in which pMTG integrates top-down control from IFG with bottom-up input from visual cortex to activate task-relevant semantic representations. Our findings elucidate the separate roles of anterior and posterior components of the semantic control network and reveal the spectro-temporal cascade of interactions between semantic and visual regions that underlie our ability to flexibly adapt cognition to the current goals. Significance Statement Using magnetoencephalography, we characterize the spectro-temporal dynamics that underlie our ability to flexibly adapt semantic cognition to the current context and goals. We find that semantic goals increase oscillatory activity in IFG and pMTG, and ultimately facilitate visual processing. Effective connectivity analyses reveal more sustained feedback from IFG to pMTG, and more rapid feedforward signalling from visual cortex to pMTG, resulting in rapid retrieval when semantic goals are known. Crucially, our findings suggest differential roles for the two semantic control regions: while IFG controls goal-dependent retrieval, pMTG integrates top-down information from IFG with bottom-up visual input.
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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".