Resting state functional connectivity in addiction: Lessons learned and a road ahead

Abstract

Despite intensive scientific investigation and public health imperatives, drug addiction treatment outcomes have not significantly improved in more than 50 years. Non-invasive brain imaging has, over the past several decades, contributed important new insights into the neuroplastic adaptations that result from chronic drug intake, but additional experimental approaches and neurobiological hypotheses are needed to better capture the totality of the motivational, affective, cognitive, genetic and pharmacological complexities of the disease. Recent advances in assessing network dynamics through resting-state functional connectivity (rsFC) may allow for such systems-level assessments. In this review, we first summarize the nascent addiction-related rsFC literature and suggest that in using this tool, circuit connectivity may inform specific neurobiological substrates underlying psychological dysfunctions associated with reward, affective and cognitive processing often observed in drug addicts. Using nicotine addiction as an exemplar, we subsequently provide a heuristic framework to guide future research by linking recent findings from intrinsic network connectivity studies with those interrogating nicotine's neuropharmacological actions. Emerging evidence supports a critical role for the insula in nicotine addiction. Likewise, the anterior insula, potentially together with the anterior cingulate cortex, appears to pivotally influence the dynamics between large-scale brain networks subserving internal (default-mode network) and external (executive control network) information processing. We suggest that a better understanding of how the insula modulates the interaction between these networks is critical for elucidating both the cognitive impairments often associated with withdrawal and the performance-enhancing effects of nicotine administration. Such an understanding may be usefully applied in the design and development of novel smoking cessation treatments.

Figure 1

(A) Summary of regions showing reduced rsFC strength with MCL seed regions in cocaine-users relative to matched non-using controls (Reproduced from Gu et al., 2010). (B) Difference map illustrating reduced rsFC between an amygdala seed and medial PFC/rostral ACC regions in cocaine-users relative to matched non-using controls (Reproduced from Gu et al., 2010). (C) Top right displays a difference map showing stronger interhemispheric connectivity between lateral PFC regions among non-using controls relative to cocaine-users. Bottom right shows self-reported cognitive failures as a function of reduced lateral PFC interhemispheric connectivity (reproduced from Kelly et al., 2011).

Figure 2

State and trait components of nicotine addiction. (A) Two of the seven resting state networks that showed enhanced connectivity under nicotine relative to placebo administration in minimally deprived (~4.5hrs) smokers. Left image shows enhanced rsFC between a dorsal ACC (dACC) seed (blue oval) and a region encompassing the superior parietal lobe and post-central gyrus. Right image shows enhanced rsFC between a mid cingulate cortex (MCC) seed and a region encompassing the post-central gyrus and inferior parietal lobe. (B) Negative correlation between scores on the Fagerström Test for Nicotine Dependence (FTND) and rsFC strength in smokers between the right striatum (blue) and a dACC seed in minimally deprived (grey triangles) and nicotine sated (red diamonds) conditions. (Reproduced from Hong et al., 2009).

Figure 3

Two components derived from a spatial Independent Components Analysis of BOLD activity during performance of a speeded flanker task. (A) A “task positive” component that includes the dorsal ACC and supplementary motor area (pictured in red/yellow) as well as the anterior insula and dorsal premotor area (not pictured), showing a pattern of activation consistent with engagement of these regions in performance monitoring. (B) A “task negative” component that includes the PCC (pictured in blue/green), precuneus and retrosplenial cortex (not pictured) showing task-related deactivation consistent with the identification of these regions as part of the default-mode network. (C) Activity in the “task negative” component shows a linear increase in activity preceding response errors (Reproduced from Eichele et al., 2008).

Figure 4

Nicotine’s impact on default-mode functioning. (A) Nicotine enhanced deactivation in DMN regions (PCC, dmPFC) in minimally deprived (~3 hrs) smokers under nicotine (relative to placebo) administration during a spatial attention task. (B) Nicotine-induced deactivation in the PCC correlates with reduced reaction time (difference values reflect Nicotine - Placebo). (Reproduced from Hahn et al., 2007). (C) Nicotine (relative to pre-nicotine baseline) reduced activity in DMN regions (vmPFC, PCC, precuneus) of non-smokers (Reproduced from Tanabe et al., 2011). (D) Example time-courses of DMN (blue) and ECN (red) activity during the resting state under nicotine and placebo conditions in two abstinent (~12 hrs) smokers. Top graphs illustrate enhanced negative coupling between the DMN and ECN following nicotine in an individual reporting decreased withdrawal symptoms following nicotine replacement. Bottom graphs show little change in DMN-ECN coupling following nicotine administration in an individual reporting no change in withdrawal symptoms (Reproduced from Cole et al 2010).

Figure 5

Increased activity in DMN regions in response to cues. (A) BOLD activation in DMN regions (PCC, precuneus) to heroin-related versus neutral cues in opioid-dependent individuals (Reproduced from Wang et al., 2010). (B,C). Heroin-related cues increase BOLD activation in DMN regions (vmPFC, hippocampus) and the insula immediately prior to and after a methadone dose in opioid-dependent individuals (Reproduced from Langelben et al. 2008).

Figure 6

Insula involvement in nicotine addiction and attentional processes. (A) Greater gray matter density in smokers (n=48) relative to matched controls in the left insula. (Reproduced from Zhang et al., 2010) (B) Increased insula activity to smoking-related versus neutral cues is positively correlated with attention to smoking-cues in an affective Stroop task. (Reproduced from Janes et al., 2010). (C). Difference map and bar graph illustrating enhanced BOLD deactivations in the insula under nicotine relative to placebo conditions during a sustained attention task (RVIP) but not a sensorimotor control task in minimally deprived (~3 hrs) smokers. (Reproduced from Lawrence et al., 2002).

Figure 7

A proposed model of activity within and between the DMN, executive control network (ECN) and salience network (SN) under nicotine abstinence (A) and following acute nicotine administration (B). Arrow thickness between and within networks reflects the hypothesized strength of interactions between networks. The thick arrow between the insula and endogenously relevant interoceptive events in (A) reflects an influx of such events during nicotine abstinence. Similarly, thick arrows between the dACC and ECN and their conceptual outputs in (B) reflects an enhanced capacity to engage in task execution and performance monitoring following nicotine administration.