Abnormal resting state FMRI activity predicts processing speed deficits in first-episode psychosis

Abstract

Little is known regarding the neuropsychological significance of resting state functional magnetic resonance imaging (rs-fMRI) activity early in the course of psychosis. Moreover, no studies have used different approaches for analysis of rs-fMRI activity and examined gray matter thickness in the same cohort. In this study, 41 patients experiencing a first-episode of psychosis (including N=17 who were antipsychotic drug-naive at the time of scanning) and 41 individually age- and sex-matched healthy volunteers completed rs-fMRI and structural MRI exams and neuropsychological assessments. We computed correlation matrices for 266 regions-of-interest across the brain to assess global connectivity. In addition, independent component analysis (ICA) was used to assess group differences in the expression of rs-fMRI activity within 20 predefined publicly available templates. Patients demonstrated lower overall rs-fMRI global connectivity compared with healthy volunteers without associated group differences in gray matter thickness assessed within the same regions-of-interest used in this analysis. Similarly, ICA revealed worse rs-fMRI expression scores across all 20 networks in patients compared with healthy volunteers, with posthoc analyses revealing significant (p<0.05; corrected) abnormalities within the caudate nucleus and planum temporale. Worse processing speed correlated significantly with overall lower global connectivity using the region-of-interest approach and lower expression scores within the planum temporale using ICA. Our findings implicate dysfunction in rs-fMRI activity in first-episode psychosis prior to extensive antipsychotic treatment using different analytic approaches (in the absence of concomitant gray matter structural differences) that predict processing speed.

Figure 1

Region-based cortical thickness approach. The 266 nodes that were used as resting state functional magnetic resonance imaging seeds are illustrated in panel a. The nodes were then projected into Freesurfer space aligning them with vertices from the gray–white interface. The vertices with the corresponding gray matter ribbon are illustrated in the left hemisphere in panel b. Regions-of-interest and their corresponding gray–white matter interface are provided in panel c. The gray–white matter interface, color-coded with corresponding thickness is illustrated in panel d. Lighter colors denote thicker gray matter regions above that area such that gray matter is defined as the distance between the interface and the pial surface. The region-level calculation of thickness is an average of the regions in panel c over the values in panel d. This is illustrated in the left hemisphere but was done similarly in the right hemisphere.

Figure 2

Average connectivity strength in patients and healthy volunteers. Red lines denote patients, and black lines denote healthy volunteers. SEMs are provided for each node. Regions are presented based on their connectivity strength rank order in healthy volunteers.

Figure 3

Independent component analysis expression scores in patients and healthy volunteers. *p<0.05; **p<0.01; ***p<0.005; ****p<0.001.

Figure 4

Illustration of significant (p<0.05; FWE-corrected) voxelwise analyses of independent components 16 and 19. Green and yellow indicate strongly correlating and anti-correlating regions respectively. (a) Salience network, blue indicates group differences in planum temporale, (c) Somatosensory network, blue indicates group differences in caudate nucleus, (b) and (d) are post hoc analyses in the corresponding blue region.