Adolescent cannabis use and brain systems supporting adult working memory encoding, maintenance, and retrieval

Abstract

Given prior reports of adverse effects of cannabis use on working memory, an executive function with a protracted developmental course during adolescence, we examined associations between developmental patterns of cannabis use and adult working memory (WM) processes. Seventy-five adults with longitudinal assessments of cannabis use (60 with reported use, 15 with no reported use) and prenatal drug exposure assessment completed a spatial WM task during fMRI at age 28. All subjects passed a multi-drug urine screen on the day of testing and denied recreational drug use in the past week. A fast event-related design with partial trials was used to separate the BOLD response associated with encoding, maintenance, and retrieval periods of the WM task. Behavioral results showed that subjects who began using cannabis earlier in adolescence had longer reaction times (RT) than those with later initiation. Cannabis age of onset was further associated with reduced posterior parietal cortex (PPC) encoding BOLD activation, which significantly mediated age of onset WM RT associations. However, cannabis age of onset brain-behavior associations did not differ between groups with a single reported use and those with repeated use, suggesting age of onset effects may reflect substance use risk characteristics rather than a developmentally-timed cannabis exposure effect. Within repeated cannabis users, greater levels of total cannabis use were associated with performance-related increases in dorsolateral prefrontal cortex (DLPFC) activation during maintenance. This pattern of significant results remained unchanged with inclusion of demographic and prenatal measures as covariates. Surprisingly, however, at the group level, cannabis users generally performed better than participants who reported never using cannabis (faster RT, higher accuracy). We extend previous investigations by identifying that WM associations with cannabis age of onset may be primary to PPC stimulus encoding activity, while the amount of cannabis use is associated with DLPFC maintenance processes. Poorer performance of participants who reported never using cannabis and the consistency of cannabis age of onset associations across single and repeated users limit interpretation of direct developmental effects of cannabis on WM in adulthood.

Keywords: Cannabis; Development; Executive function; Functional MRI; Substance use; Working memory.

Fig. 1.

Working Memory Task. Three cues (yellow circles) were presented sequentially (300 ms presentation, 200 ms ISI) in one of eight possible locations (2 row X 4 column grid).

Fig. 2.

Behavioral Effects of Cannabis Age of Onset and Total Cannabis Use on Working Memory Performance. N.S. Non-significant, + p < .10, **p < .01. EXP, cannabis experimenters; REP, repeated cannabis users. Model estimates were back transformed from log (reaction time) and logit (accuracy) space for ease of interpretation. Visualized estimates are from intercept onlybaseline models. (A), Cannabis age of onsetwas not a significant predictor of WM accuracy (baseline: z = 1.30, p = .193; full model: z = 0.52, p = .601), but had a significant, negative relationship with WM RT (C; baseline: t = −2.99, p = .003; full model: t = −3.11, p = .002). In contrast, total cannabis use (log) was not a significant predictor of working memory RT (D; baseline: t = 0.88, p = .381; full model: t = 1.40, p = .162) but had a near significant, negative relationship with WM accuracy in the baseline model (B; z = −1.93, p = .054). However, this effect was no longer significant after adjusting for prenatal cannabis exposure (z = −1.41, p = .159).

Fig. 3.

Performance Differences in Usage Groups. NU, non-user; EXP, cannabis experimenters; REP, repeated cannabis users. N.S., Non-significant, + p < .10, *p < .05. Visualized estimates are from intercept only baseline models. There was a trend (baseline: z = 1.95, p = .052) for a combined cannabis group (EXP + REP) to have higher WM accuracy than subjects that reported not using cannabis (NU). Additionally, a combined cannabis group (EXP + REP) had significantly lower RT (baseline: t = −2.34, p = .019). In contrast, usage groups (REP vs. EXP) did not significantly differ on WM accuracy (baseline: z = −1.19, p = .237) or RT (baseline: t = 0.36 p = .719).

Fig. 4.

Clusters of Omnibus Activation Differences as a Function of Cannabis Age of Onset in the Right Posterior Parietal Cortex (cluster A, top; cluster b, bottom. **p < .01 (corrected); (A,C) Mean cluster time course with reference markers of cue (grey), delay (white), and target (black). Model was run with a continuous age of onset function and data are median split for visualization only. (B,D) Epoch activation differences as a function of cannabis age of onset.

Fig. 5.

Clusters of Omnibus Activation Differences as a Function of Total Cannabis Use in Right (top) and Left (bottom) Dorsolateral Prefrontal Cortex (DLPFC). Left DLPFC cluster is represented as L-DLPFC (A) in tables. (A,C) Mean cluster time course with reference markers for cue (grey), delay (white), and target (black). Model was run with a continuous total cannabis use (log) function and data are median split for visualization only. (B,D) Epoch activation differences as a function of total cannabis use (log).

Fig. 6.

Brain Behavior Relationships for R-Posterior Parietal Cortex (A) (R-PPC(A)) and R-Dorsolateral Prefrontal Cortex (R-DLPFC). + p < .10, *p < .05, **p < .01.(A) Cue epoch activation in the R-PPC (A) was a significant predictor of WM RT (β = −.358, t (55)) = −2.75, p= .024, corrected. (B) Top panel, R-PPC (A) cue epoch activation significantly mediates the relationship between cannabis age of onset and reaction time (baseline: average indirect pathway, β= −.153, 95% C.I., −.307: −.043, p = .003; full model: β= −.140, 95% C.I., −.342: −.008, p = .029). Bottom Panel, R-PPC (A) cue epoch activation significantly mediates the relationship between cannabis age of onset and reaction time in the REP only group while covarying total cannabis use (average indirect pathway, β= −.189, 95% C.I., −.415: −.026, p = .017). (C), Delay epoch activation in R-DLPFC had a negative trend with working memory accuracy (O.R. = .978, z = −2.16, p = .093, corrected).

Fig. 7.

*p < .05. Usage groups (NU, non-user; EXP, cannabis experimenters; REP, repeated cannabis users) BOLD activation in performance-related fMRI regions from cannabis age of onset (A; R-PPC (A) cue epoch) and total cannabis use (B; R-DLPFC delay epoch) analyses.