The Diagnostic Value of Children's Responses to Cross-Examination Questioning.

In response to a widespread belief within the legal system that cross-examination is instrumental in uncovering the truth, we examined the effect of cross-examination questioning on the reports of children who had-and had not-been coached to lie. A group of children, aged 6-11 years (N = 65), played three computer games with one of their parents. For half of the pairs, the parents-who acted as confederates-coached their children to make lies of commission concerning the occurrence of two target activities. For the remaining pairs, these two target activities actually occurred, and there was no coaching. Immediately afterwards, children were interviewed about the two activities. Those who-correctly or incorrectly-reported that both activities occurred were retained for the final sample (n = 56); these children were then interviewed again with both neutral questions and cross-examination-style challenges. Neither style of questioning elicited responses that discriminated between liars and truth-tellers: although the accuracy of children who were lying increased in response to cross-examination questions, the accuracy of truth-telling children saw a corresponding decrease. When asked neutral questions, children's responses tended to be consistent with their earlier responses, whether or not those responses were lies. These findings raise important questions about the function that cross-examination might serve in trials involving child witnesses. Copyright © 2016 John Wiley & Sons, Ltd.

Robust data-driven segmentation of pulsatile cerebral vessels using functional magnetic resonance imaging.

Functional magnetic resonance imaging (fMRI) captures rich physiological and neuronal information that can offer insights into neurofluid dynamics, vascular health, and waste clearance function. The availability of cerebral vessel segmentation could facilitate fluid dynamics research in fMRI. However, without magnetic resonance angiography scans, cerebral vessel segmentation is challenging and time-consuming. This study leverages cardiac-induced pulsatile fMRI signal to develop a data-driven, automatic segmentation of large cerebral arteries and the superior sagittal sinus (SSS). The method was validated in a local dataset by comparing it to ground truth cerebral artery and SSS segmentations. Using the Human Connectome Project (HCP) aging dataset, the method's reproducibility was tested on 422 participants aged 36 to 100 years, each with four repeated fMRI scans. The method demonstrated high reproducibility, with an intraclass correlation coefficient > 0.7 in both cerebral artery and SSS segmentation volumes. This study demonstrates that the large cerebral arteries and SSS can be reproducibly and automatically segmented in fMRI datasets, facilitating the investigation of fluid dynamics in these regions.