Marek, Tervo-Clemmens et al. (2022) suggest that we need much larger sample sizes to investigate associations between common variability in brain structure or function and cognition or psychiatric symptomatology. That is true under the assumption that such associations, for complex, multifactorial cognitive or psychiatric phenotypes, and characteristics accessible with existing imaging methods, exist.
Unfortunately, the evidence provided seems to suggest the absence of such effects. In their article, Figure 2 shows overlap only for the distribution of effects, with peaks virtually at zero for three major studies, but no evidence for overlap of localized effects; Supplementary Figure 17 shows near-perfect correlation for average connectivity, but not for connectivity in relation to complex phenotypes. In Linke et al. (2021), we showed evidence that similar clinical presentations can emerge from disparate changes in brain connectivity, suggesting substantial diversity in the presentation of the underlying biological substrate, even for the same behavioral measurements.
It is possible that the aspects of human behavior that we consider relevant, and which guide our cognitive and clinical phenotyping, do not manifest themselves as measurable entities using available brain imaging methods. Merely increasing sample size with such phenotypes can only ensure statistically significant results for trivial, negligible effects, which may still fail to replicate. More investment on the development of techniques to probe yet unexplored aspects of the brain tissue, in vivo, and non-invasively, are more likely to be fruitful, without prejudice to the collection of large samples. The same holds for cognitive and clinical phenotypes, which need to be reliable, even if only indirectly mapped into aspects of human behavior.
- Linke, J. O. et al. Shared and anxiety-specific pediatric psychopathology dimensions manifest distributed neural correlates. Biol Psychiatry. 2021 Mar 15;89(6):579-587.
- Marek, S. et al. Reproducible brain-wide association studies require thousands of individuals. Nature. 2022 Mar;603(7902):654-660.
Anderson M. Winkler, Daniel S. Pine, Julia O. Linke