ReviewResting state functional connectivity in addiction: Lessons learned and a road ahead
Highlights
► Review addiction-related resting state functional connectivity (rsFC) literature. ► Propose a framework to guide future research of rsFC in nicotine addiction. ► Nicotine and withdrawal alter FC of large-scale intrinsic connectivity networks. ► Insula/dACC salience network plays critical role in craving and network switching. ► Shifts in network dynamics underlie cognitive effects of nicotine and withdrawal.
Introduction
Drug addiction is a multifaceted neuropsychiatric disorder characterized by the compulsive seeking and taking of a drug, despite the high likelihood of negative consequences. Addiction is notable for the complex, and still only partially understood, interactions between neurobiological, environmental, pharmacological, and genetic components. Multiple theories regarding the underlying mechanisms of addiction have been proposed (e.g., Everitt and Robbins, 2005, Goldstein and Volkow, 2002, Koob and Le Moal, 2008, Koob and Volkow, 2010, Redish, 2004, Wise, 2008), and although originally generated mostly from rodent studies, many, but not all, of these neurobiological mechanisms appear well conserved in non-human primates and, where studied, in humans. However, despite tremendous advances over the past several decades, translating preclinical findings of the molecular and cellular neuroadaptations following chronic drug intake has not as yet significantly improved clinical outcomes. As drug abuse is a uniquely human disease, it would seem that a better understanding of the profound disruption of motivational, affective and cognitive processes following, and/or predisposing individuals to drug use is critical to expedite treatment development.
While neuroimaging cognitive-subtraction task paradigms have been essential for delineating the acute effects of addictive drugs and the long-term consequences of use within circumscribed brain areas (e.g., Bickel et al., 2007, Breiter et al., 1997, Diekhof et al., 2008, Kumari et al., 2003, Stein et al., 1998), additional, complementary insight will most likely be obtained by considering alterations in circuit-level interactions between brain regions (Koob and Volkow, 2010). The last decade has witnessed an explosion in the study of functional connectivity using fMRI, largely because it allows for the exploration of large-scale networks and their interactions, thus moving towards a systems-level understanding of brain functioning (Bressler and Menon, 2010, van den Heuvel and Hulshoff Pol, 2010). By extension, resting-state functional connectivity (rsFC) may allow for the identification of neural circuitry dysfunction underlying various neuropsychiatric disorders (Fox and Greicius, 2010). Among its advantages as a potential characterization and diagnostic tool are that: 1) identified rsFC circuit-alterations are less likely to be confounded by subtle differences in specific task-based experimental paradigms; 2) networks so identified appear to be consistent across time within and between individuals (Chen et al., 2008); 3) such networks appear to reflect the entirety of the cognitive elements necessary for task processing (Smith et al., 2009); and 4) relative to task-based fMRI methods, data collection is relatively quick and straight-forward — a useful quality when assessing patient populations with variable constraints on attentional, executive, and motor control. There are, however, certain methodological issues associated with rsFC-based techniques, a few of which will be briefly discussed at points throughout the review. Nonetheless, this emerging neuroimaging tool has provided researchers with additional insights and spurred novel theories about the underlying neural substrates of various neuropsychiatric disorders (e.g., Menon, 2011).
Circuits synchronized “at rest” are constrained to known, direct or polysynaptic anatomically interconnected regions (Damoiseaux and Greicius, 2009, Greicius et al., 2009, Honey et al., 2009), thus constituting plausible functional networks. Critically, the strength of these networks “at rest” predicts both behavioral performance and subsequent activation of the same brain areas during task performance (e.g., Hampson et al., 2006, Kelly et al., 2008, Kim et al., 2009, Seeley et al., 2007, Tambini et al., 2010). Further, there is growing evidence that alterations in rsFC strength can potentially be used to assess various neuropsychiatric disease trajectories, and where available treatment outcomes, including: Alzheimer's disease (Greicius et al., 2004, Lustig et al., 2003, Rombouts et al., 2005, Wang et al., 2006), autism (Kennedy et al., 2006), depression (Anand et al., 2005), multiple sclerosis (Lowe et al., 2002), and attention deficit/hyperactive disorder (ADHD; Tian et al., 2006). Emerging evidence further suggests a genetic linkage between rsFC networks and various behavioral phenotypes (Glahn et al., 2010, Meyer-Lindenberg, 2009), raising promise that functional connectivity may serve as a systems-level biomarker to identify individual differences in and provide differential disease diagnoses for various neuropsychiatric disorders. Despite such promise, it is only in the last few years that rsFC has begun to be considered as a characterization and potentially diagnostic tool.
To date, rsFC has been applied in only a handful of drug addiction-related studies and the current review begins with an overview of those findings. As expected in an emerging field, many of these studies have been somewhat exploratory in nature, leading to conflicting findings. Applications of this tool in addiction research may therefore benefit from experimental approaches grounded by stronger a priori theoretical models. To this end, throughout the review we relate extant addiction-related rsFC findings to a larger corpus of neuroimaging research from healthy controls and other neuropsychiatric conditions. In the latter half of the review we continue this theme and in greater detail link recent findings from network connectivity and nicotine-related neuroimaging studies to develop a heuristic framework yielding empirically testable hypotheses regarding the effects of both nicotine abstinence and drug administration on brain and behavior.
Section snippets
Addiction-related rsFC studies
The earliest addiction-related rsFC study reported marked reductions in connectivity within the primary visual and motor cortices after cocaine administration to addicted individuals, presumably reflecting changes in coherent neuronal firing patterns (Li et al., 2000). Subsequently, using a functional connectivity analysis on [15O] PET data, Daglish et al. (2003) identified two networks during opiate craving, one including anterior cingulate cortex (ACC) and temporal cortex and a second
Nicotine and large-scale networks
Nicotine's performance-enhancing properties manifest in multiple cognitive domains, particularly when considering abstinent smokers (Heishman et al., 1994, Heishman et al., 2010, Newhouse et al., 2004). Previous neuroimaging studies exploring such nicotinic or cholinergic effects have often done so in the context of cognitive task paradigms, providing information regarding pharmacological actions generally within specific brain regions (for review, see Bentley et al., 2011). rsFC studies may
Insula, network switching and interoception
The brain is inundated with a continuous flow of information arising from exogenous and endogenous sources, necessitating control mechanisms to identify, and in turn act upon, the currently most salient stimuli. A distinct network, composed of insula and ACC nodes, has been suggested to play a critical and causal role in the initiation, maintenance, and adjustment of attentional control (Bressler and Menon, 2010, Dosenbach et al., 2006, Dosenbach et al., 2007, Dosenbach et al., 2008, Menon and
A network model of nicotine addiction
Drawing upon the above literature, we propose a model that integrates contemporary understanding of intrinsic network dynamics with evidence of alterations within and between these networks as a function of nicotine abstinence and administration, cue reactivity and/or drug urges. We hypothesize that during acute abstinence, the insula monitors salient interoceptive states, thus marking the presence of endogenous, withdrawal-related somatic, affective, and/or motivational events. The insula in
Acknowledgments
This work was supported by the National Institute on Drug Abuse, Intramural Research Program, NIH/DHHS.
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