1282Causal inference in multi-cohort studies using the target trial approach

Focus of Presentation Utilising data from multiple cohorts to address causal questions in health research has become increasingly widespread due to a number of advantages. These include improved precision of estimates, in particular to investigate effect heterogeneity as well as rare events and exposures, and the ability to examine the replicability of findings. However, undertaking causal inference in multi-cohort studies also faces several challenges, which makes clear causal thinking even more important than in single-cohort studies. We propose the use of the “target trial” framework for the conduct of causal inference in multi-cohort studies. Findings Using two case studies, the first considering the effect of maternal mental health on emotional reactivity and the second examining the influence of exposure to adversity on inflammatory outcomes in childhood, we describe and demonstrate how the target trial approach enables clear definition of the target estimand and systematic consideration of sources of bias. Considering the target trial as the reference point allows the identification of potential biases within each study, so that analysis can be planned to reduce them. Furthermore, the interpretation of findings is assisted by an understanding of the unavoidable biases that may be compounded when pooling data from multiple cohorts, or that may explain discrepant findings across cohorts. Conclusions/Implications Use of the target trial framework in multi-cohort studies helps strengthen causal inferences through improved analysis design and clarity in the interpretation of findings. Key messages The target trial framework, already well-established for casual inference in single-cohort studies, is recommended for the conduct of causal inference in multi-cohort studies.

Statistical inference of body representation in the macaque brain

The sense of one’s own body is a pillar of self-consciousness and could be investigated by inducing human illusions of artificial objects as part of the self. Here, we present a nonhuman primate version of a rubber-hand illusion that allowed us to determine its computational and neuronal mechanisms. We implemented a video-based system in a reaching task in monkeys and combined a casual inference model to establish an objective and quantitative signature for the monkey’s body representation. Similar to humans, monkeys were more likely to perceive an external object as part of the self when the dynamics (spatial disparity) and the features (shape and structure) of visual (V) input was closer to proprioceptive (P) signals. Neural signals in the monkey’s premotor cortex reflected the strength of illusion and the likelihood of misattributing the illusory hand to oneself, thus, revealing a cortical representation of body ownership.