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. 2018 Apr:194:70-77.
doi: 10.1016/j.schres.2017.07.029. Epub 2017 Aug 18.

Understanding marijuana's effects on functional connectivity of the default mode network in patients with schizophrenia and co-occurring cannabis use disorder: A pilot investigation

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Understanding marijuana's effects on functional connectivity of the default mode network in patients with schizophrenia and co-occurring cannabis use disorder: A pilot investigation

Susan Whitfield-Gabrieli et al. Schizophr Res. 2018 Apr.

Abstract

Nearly half of patients with schizophrenia (SCZ) have co-occurring cannabis use disorder (CUD), which has been associated with decreased treatment efficacy, increased risk of psychotic relapse, and poor global functioning. While reports on the effects of cannabis on cognitive performance in patients with SCZ have been mixed, study of brain networks related to executive function may clarify the relationship between cannabis use and cognition in these dual-diagnosis patients. In the present pilot study, patients with SCZ and CUD (n=12) and healthy controls (n=12) completed two functional magnetic resonance imaging (fMRI) resting scans. Prior to the second scan, patients smoked a 3.6% tetrahydrocannabinol (THC) cannabis cigarette or ingested a 15mg delta-9-tetrahydrocannabinol (THC) pill. We used resting-state functional connectivity to examine the default mode network (DMN) during both scans, as connectivity/activity within this network is negatively correlated with connectivity of the network involved in executive control and shows reduced activity during task performance in normal individuals. At baseline, relative to controls, patients exhibited DMN hyperconnectivity that correlated with positive symptom severity, and reduced anticorrelation between the DMN and the executive control network (ECN). Cannabinoid administration reduced DMN hyperconnectivity and increased DMN-ECN anticorrelation. Moreover, the magnitude of anticorrelation in the controls, and in the patients after cannabinoid administration, positively correlated with WM performance. The finding that DMN brain connectivity is plastic may have implications for future pharmacotherapeutic development, as treatment efficacy could be assessed through the ability of therapies to normalize underlying circuit-level dysfunction.

Keywords: Cannabis use disorder; Default mode network; Resting state functional connectivity; Schizophrenia; fMRI.

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Figures

Fig. 1.
Fig. 1.
Smoking apparatus and plasma THC levels. (a) Smoking apparatus consisting of a transparent chamber into which joint was inserted. Patients smoked a placebo or active cannabis cigarette immediately prior to scanning (note: photo taken of member of research team, not study participant). (b) Plasma THC levels in the patient group showed significant increases immediately prior to scanning as compared to baseline (p<0.05). Immediately prior to WM assessment, approximately 30 minutes post scanning, plasma THC levels were somewhat higher (p = 0.053 as compared to baseline), but showed a significant decline from immediately post-intervention resting scan (p<0.05).
Fig. 2.
Fig. 2.
Functional connectivity of the DMN at baseline (T1) in control participants (left column), patients with SCZ and CUD (middle column), and between group comparison (patients > controls) (right column). (a) Positive connectivity of the DMN (MPFC seed) revealing DMN hyperconnectivity in patients with SCZ and co-occurring CUD relative to controls (L medial view). (b) Brain regions significantly anticorrelated with the MPFC seed showing significantly greater MPFC-DLPFC anticorrelation in controls relative to patients (R lateral view). Connectivity values, quantified as z scores, are shown in the right-hand column.
Fig. 3.
Fig. 3.
DMN connectivity in the patients with SCZ and CUD associated with PANSS positive symptom score. Connectivity between (a) the MPFC seed and (b) Precuneus significantly correlated with PANSS total symptom score in the patient group at baseline T1. The x-axis indicates PANSS positive symptoms score and the y-axis shows strength of MPFC-Precuneus connectivity, quantified as z scores (p = 0.04, r= 0.65).
Fig. 4.
Fig. 4.
Change in DMN connectivity in control participants (left column), patients with SCZ and CUD (middle column) from T1 to T2 (expressed as T2-T1), and between group comparison at T2 (patients > controls) (right column). (a) Within group contrast showing no significant within group change in healthy controls (T2-T1; paired t-test), reduction in DMN hyperconnectivity in patients (T2-T1, paired t-test), and ongoing but attenuated hyperconnectivity in patients relative to controls (between group contrast). (b) Within group contrast showed no significant change in DMN-DLPFC anticorrelation found in healthy controls (T2-T1; paired t-test), a significant increase in MPFC-DLPFC anticorrelation subsequent to cannabinoid administration (T2-T1; paired t-test) and no significant difference in strength of MPFC-to-DLPFC anticorrelation (controls vs. patients at T2). All results shown were significant at whole brain p<0.001 cluster level, FDR-corrected.
Fig. 5.
Fig. 5.
MPFC-DLPFC anticorrelation association with WM performance. The strength of anticorrelation between (a) the MPFC seed and (b) the right DLPFC significantly correlated (p<0.05) with WM performance (p<0.05) in the control group at (c) the initial T1 scan session, (d) the control group at T2, and (e) the patient group at T2 following cannabinoid administration. The x-axis indicates performance on the WAIS-III Letter Number Sequencing Test, and the y-axis shows strength of MPFC-DLPFC anticorrelation quantified as z scores.

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