The noise in our brain: a systematic review and meta-analysis of neuroimaging and signal-detection studies on source monitoring in psychosis

Abstract

Noisy thoughts or perceptions are characteristics of psychosis (PSY) and, they are deeply related to source monitoring (SM) — the ability to discriminate the origin of internal/external experiences. This MOOSE, PRISMA-compliant meta-analysis compared SM performances in PSY compared to healthy controls (HC) focusing on signal-to-noise discrimination in order to: i) test whether neuroimaging procedures (fMRI/EEG) might be a group-specific source of noise for SM; ii) compare error- and accuracy-based indexes; iii) to meta-analyze signal-detection measures (i.e., discrimination index and response bias); iv) to determine the best index capturing SM deficits in psychosis. We conducted a 3-level meta-analysis for each aim to estimate pooled effect-sizes (Cohen's d). SM type, source discrimination and stimulus modality were used as meta-regressors. Heterogeneity (I2), publication bias (Egger's test) and multiple comparisons (Bonferroni correction) were considered. Sixteen neuroimaging, 44 error/accuracy-based behavioral and 7 signal-detection trials were included (2297 PSY, age range = 18.78–52.6; 1745 HC, age range = 21.1–53.3). The noise generated by neuroimaging procedures slightly influenced error, but not accuracy. Accuracy-based (d = -0.83), but not error-based, indexes showed significant and large SM impairments in PSY compared to HC. Overall SM performance differences between PSY and HC were larger in discrimination index (d = -0.65) and accuracy (d = -0.61), followed by response bias (d = −0.59, ns) and error-based (d = 0.35) indexes. Although both accuracy and discrimination indexes differentiate patients with PSY from HC, discrimination index is more reliable and may better capture the bi-directional nature of the internal/external source confusion.