Curious to dive deeper?
[Read the full paper: doi.org/10.1101/2025...
Curious to dive deeper?
[Read the full paper: doi.org/10.1101/2025...
Focusing on this task, we uncovered both converging and diverging predictive network patterns across models.
Focusing on this task, we uncovered both converging and diverging predictive network patterns across models.
That is, while we can predict who performs well at a later timepoint, it’s much harder to predict how much they improve over time – except for one task.
That is, while we can predict who performs well at a later timepoint, it’s much harder to predict how much they improve over time – except for one task.
These results suggest that stable individual differences in baseline FC carry more predictive weight than short-term changes over time
These results suggest that stable individual differences in baseline FC carry more predictive weight than short-term changes over time
Why might that be?
Could it just be a matter of measurement reliability?
Baseline FC: mean ICC = 0.56
FC change: mean ICC = 0.24
Why might that be?
Could it just be a matter of measurement reliability?
Baseline FC: mean ICC = 0.56
FC change: mean ICC = 0.24
Models trained on baseline FC to predict baseline cognition generalized better when tested on Year 2 FC and cognition.
This suggests that brain–cognition relationships strengthen over time.
Models trained on baseline FC to predict baseline cognition generalized better when tested on Year 2 FC and cognition.
This suggests that brain–cognition relationships strengthen over time.
We also observed notable individual differences in FC change, especially in somatomotor, visual, and medial prefrontal cortex
We also observed notable individual differences in FC change, especially in somatomotor, visual, and medial prefrontal cortex
At the same time, we observed substantial variation in how much cognition changed across individuals.
At the same time, we observed substantial variation in how much cognition changed across individuals.
We hypothesize that cross-sectional and longitudinal estimates may diverge, echoing classical Simpson’s paradox.
See below:
We hypothesize that cross-sectional and longitudinal estimates may diverge, echoing classical Simpson’s paradox.
See below: