Simultaneous EEG and fMRI Reveals a Causally Connected Subcortical-Cortical Network during Reward Anticipation
Bibliographic record
Abstract
Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have been used to study the neural correlates of reward anticipation, but the interrelation of EEG and fMRI measures remains unknown. The goal of the present study was to investigate this relationship in response to a well established reward anticipation paradigm using simultaneous EEG-fMRI recording in healthy human subjects. Analysis of causal interactions between the thalamus (THAL), ventral-striatum (VS), and supplementary motor area (SMA), using both mediator analysis and dynamic causal modeling, revealed that (1) THAL fMRI blood oxygenation level-dependent (BOLD) activity is mediating intermodal correlations between the EEG contingent negative variation (CNV) signal and the fMRI BOLD signal in SMA and VS, (2) the underlying causal connectivity network consists of top-down regulation from SMA to VS and SMA to THAL along with an excitatory information flow through a THAL→VS→SMA route during reward anticipation, and (3) the EEG CNV signal is best predicted by a combination of THAL fMRI BOLD response and strength of top-down regulation from SMA to VS and SMA to THAL. Collectively, these findings represent a likely neurobiological mechanism mapping a primarily subcortical process, i.e., reward anticipation, onto a cortical signature.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".