Revisiting the assessment of inter-individual differences in fMRI activations-behavior relationships

Characterizing inter-individual differences is critical to realize neuroimaging full potential, but can hardly be achieved without accurately assessing the statistical dependencies between inter-individual differences in behavior and inter-individual differences in neural activity. In this manuscript, we consider two hypotheses: 1) BOLD signal scales linearly with behavioral variables across individuals and 2) BOLD signal encodes behavioral variables on a similar scale across individuals. We formally show that these two hypotheses induce opposite brain-behavior correlational results in group-level analyses, illustrating the importance of explicitly testing interindividual brain-behavior scaling before engaging in the study of functional inter-individual differences. To further evidence the relevance of this framework, we illustrate its practical consequences for model-based fMRI using computational simulations, and demonstrate its empirical robustness in four fMRI studies investigating values coding in the prefrontal cortex. This may constitute an important step forward in our conceptualization, analysis and interpretation of inter-individual differences in cognitive neurosciences. INTRODUCTION: “There is very little difference between one man and another; but what little there is, is very important. " They are two complementary goals in cognitive neuroscience: understanding the average – typical brain by linking its structure and functions with cognition and behavior, and understanding how individuals differ from each-others from the normal to the pathological ranges. With respect to these two quests, inter-individual differences in brainbehavior relationships are fundamentally important either because they constitute a statistical challenge to understand the typical brain, or because they represent the very object of interest (Braver et al., 2010; Gabrieli et al., 2015). Task-related functional neuroimaging (fMRI) constitutes a tool of choice to investigate the neurobiological underpinnings of cognition. Initially confined to the mapping of the typical brain, fMRI is increasingly used to investigate the neural bases of differential cognition. Individual brain activations are linked to external heterogeneity factors, such as the diagnostic criterion for some pathology, psychosocio-economic measures -i.e. “traits”-, or to behavioral measures recorded during the experiment – i.e. “task performance” (Figure.1.A and 1.B). Significant associations are then William James (1897). The Importance of Individuals, In The Will to Believe and Other Essays in Popular Philosophy interpreted in term of individual neural resource mobilized to complete the task – sometimes with opposite post-hoc rationalization. It is paradigmatic in the example of executive control literature, linking activations in the frontal regions and individual performance: positive associations are typically interpreted as an effective increase in cognitive control mobilization, whereas negative associations are interpreted as an increase in neural efficiency. This represents a critical failure of the current interindividual difference framework (Poldrack, 2015; Yarkoni and Braver, 2010). In the present paper, we suggest that these inconsistencies are possible because the hypotheses concerning the inter-individual relative scaling of brain signal (typically Blood Oxygen Level Dependent signal, BOLD) with behavior are not explicitly stated and tested. We therefore present the scaling issue and evidence its impact on interindividual fMRI results by intuitively and mathematically demonstrating that two simple and equally plausible scaling hypotheses can produce opposite results and conclusions. Using computational simulations, we show how the scaling issue can percolate in model-based fMRI, and we provide a priori principle to process model-based variables. Finally, in order to prove the interest of our framework and validate its robustness, we assess -and replicate in four imaging datasetsthe statistical law describing the relationship between inter-individual differences in prefrontal BOLD signal peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (which was not . http://dx.doi. org/10.1101/036772 doi: bioRxiv preprint first posted online Jan. 18, 2016;