DHA Status Associated with Cognitive Performance and Differential Patterns of Brain Activation in School Age Children
Bibliographic record
Abstract
We assessed the associations between DHA intake (food frequency questionnaire) and DHA status [red blood cell (RBC)‐DHA/docosapentaenoic acid (DPA, n‐6) ratio] with cognitive performance [Kaufman Assessment Battery for Children (KABC‐III)] and brain functioning [measured by functional magnetic resonance imaging (fMRI)] in healthy children ~6 years of age (n=62). fMRI scanning of an n‐back numbers task was conducted, consisting of control and 1‐back task conditions (96 × 96 oblique axial EPI, 3mm thickness, no gap, TR/TE = 3000/30ms). Using Behavior Partial Least Squares (bPLS), the task‐specific correlation matrix between behavior and brain activity was computed and then decomposed using singular value decomposition. This yielded condition related brain network activation patterns, which were used to assess the association between DHA status and brain functioning. Median (interquartile range) DHA intake and RBC‐DHA/DPA were 76 (40–127) mg/d and 8.9 (6.0–12), respectively. DHA intake was positively correlated with: RBC‐DHA/DPA ( r =0.62, p<0.0001), KABC indicators of short‐term memory (Sequential; r =0.29, p=0.03) and general mental processing ability (Mental Performance Index; r =0.34, p=0.018); RBC‐DHA/DPA was positively correlated with the KABC Sequential ( r =0.26, p=0.042). The bPLS analysis ( n =34 with acceptably low head motion) produced 2 latent variables (LV), which represent underlying condition related brain network activation patterns. LV 1 showed activations in the Right (R) superior frontal, R middle temporal, Left (L) middle frontal gyri and the R insula with concomitant deactivations in the R cerebellum (lobules VI and IX) and the R lateral occipital gyrus that were negatively correlated with RBC‐DHA/DPA for both the control [ r (95% confidence interval (CI) = −0.39 (−0.66, −0.05)] and 1‐back [ r (95% CI) = −0.36 (−0.67, −0.12)] conditions. Therefore, activations were more activated with lower RBC‐DHA/DPA, while deactivations were more deactivated with higher RBC‐DHA/DPA. LV 2 showed activations in the R superior temporal gyrus and R anterior cingulate with concomitant deactivations in the R hippocampus, L fusiform, and bilateral precuneus and post‐central gyri that were negatively correlated with the control condition [r (95% CI) = −0.46 (−0.71, −0.17)] and positively correlated with the 1‐back condition [r (95% CI) = 0.43 (0.06, 0.70)]. Therefore, activations were more activated with lower RBC‐DHA/DPA in the control condition, while the same activations were more activated with higher RBC‐DHA/DPA in the 1‐back condition. Similarly, deactivated regions showed more deactivation with higher RBC‐DHA/DPA in the control condition and more deactivation with lower RBC‐DHA/DPA in the 1‐back condition. In sum, DHA intake was positively associated with some aspects of cognitive performance; DHA status was positively associated with some aspects of cognitive performance as well as differential brain activation patterns. Support or Funding Information Funded by Nestec, S.A.
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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 | 0.001 | 0.001 |
| 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".