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Juliano, A.

Publications and source records attributed to Juliano, A..

2 recordsLinked to original sources

Associations between amygdala connectivity and experienced discrimination in children

Discrimination is a chronic stressor linked to adverse health outcomes, particularly in racial and ethnic minorities. Understanding associations between early discrimination and the brain in childhood may help identify mechanisms through which discrimination impacts future health. Data from 4512 children (ages 9-11) and a subsample of Black, Indigenous, and People of Color (BIPOC; N = 1567) from the Adolescent Brain and Cognitive Development (ABCD) Study(R) was used to create linear mixed-effects models that evaluated associations between Perceived Discrimination (PD) and amygdala resting-state fMRI connectivity (AC) to the salience network (SN), default mode network (DMN), and thalamus. PD was measured using the youth self-reported PD Scale. Results indicated that greater PD significantly predicted greater AC to the right thalamus in our full sample. In secondary analyses, environmental and behavioral factors were evaluated as potential moderators for associations significant at least at a trend level in both our full sample and BIPOC subsample. In our BIPOC subsample, traumatic events experienced moderated the relationship between PD and AC to the anterior cingulate cortex (ACC; SN), such that greater traumatic experiences predicted stronger positive associations between PD and this connection. Results suggest PD impacts neural connections in early life, highlighting the need to consider the impact of discrimination on risk for psychopathology.

neuroscience↗

The ABCD Stop Signal Data: Response to Bissett et al.

This paper responds to a recent critique by Bissett and colleagues (Bissett et al., eLife, In Press) of the fMRI Stop task being used in the Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study(R)). The critique focuses primarily on a design feature of the task that the authors contend lead to a violation of race model assumptions (i.e., that the Go and Stop processes are fully independent) which are relevant to the calculation of the Stop Signal Reaction Time, a measure of the inhibition process. Bissett and colleagues also raise a number of secondary concerns. In this response we note that satisfying race model assumptions is a pernicious challenge for Stop task designs but also that the race model is quite robust against violations of its assumptions. Most importantly, while Bissett et al. raise conceptual concerns with the task we focus here on analyses of both the performance and the neuroimaging data and we conclude that the concerns appear to have minimal impact on the neuroimaging data (the validity of which do not rely on race model assumptions) and have far less of an impact on the performance data than the critique suggests. We note that Bissett et al. did not apply any performance-based exclusions to the data they analyzed, that a number of the trial coding errors that they flagged were already identified and corrected in the ABCD annual data releases, that a number of the secondary concerns reflect sensible design decisions and, indeed, that their own computational modeling of the ABCD Stop task suggests the problems they identify have just a modest impact on the rank ordering of individual differences in subject performance. In this paper, we list some adjustments that have been made to the task and some new flags that are now added to the annual, curated data releases. We stress that the ABCD data are fully available to the scientific community who are empowered to apply whatever inclusion and exclusion criteria they deem appropriate for their analyses and we conclude that the ABCD Stop task yields valuable data that researchers can use to track adolescent neurodevelopment.

neuroscience↗