Introduction:
It is reported that approximately 70% of US adults are alcohol consumers, and more than 5% of adults are considered to have Alcohol Use Disorder (AUD). Although studies have shown that people with AUD usually do not tolerate abstinence well, fewer studies have investigated the moderate-to-heavy drinkers' response to abstinence. In this functional magnetic resonance imaging (fMRI) study, we examine abstinence-induced changes in the dynamics of functional brain network states among moderate-to-heavy drinkers when presented with alcohol cues.
Materials and Methods:
Our sample consists of 39 moderate-to-heavy drinkers with an average age of 41 years, and no history of AUD. Each participant completed two sessions of task fMRI, during which they were presented with alcohol image stimuli. Prior to one scan participants consumed alcohol as usual (typical drinking), and prior to the other scan participants abstained from any alcohol consumption for three consecutive days (abstinence). The fMRI data were preprocessed and signals for 58 regions were extracted for each subject. Our analysis focused on the regions belonging to three distinct networks: the salience (SN), default mode (DMN) and somatomotor networks (SMN). These networks are known to be associated with attention, self-focus, and sensory-motor function, respectively. Next, the extracted signals were fed to a Hidden Semi Markov Model (HSMM) for studying dynamic brain functional connectivity. In the HSMM framework, we assume that an individual’s time series data can be described via a series of repeating brain states, where each state is characterized by a connectivity structure. We fit the modeling framework (with 5 states) on our study participants to obtain group level estimates of the connectivity structure of the brain network states occupied by the participants during their scans. We then explored differences in state occupancy time, state sojourn time and state transition probabilities between the two study sessions (typical drinking vs. abstinence).

RESULTS:

Figure 1.a illustrates the connectivity matrix of the five states. In the abstinence drinking condition, participants spent significantly less total time in state 4 (P=0.02) compared to the typical drinking condition. In addition, the distribution of sojourn times indicates that participants spent more continuous time in state 4 during the abstinence condition than during the typical drinking condition (figure 1.b). This phenomenon is also evident in the state sequence of the subjects, as shown in figure 1.c. Participants in the typical drinking condition spent multiple short blocks of time in state 4 (yellow) compared to those in the abstinence drinking condition. Finally, the transition matrix for the abstinence drinking condition displays a lower probability of transitioning from states 1, 2, 3, and 5 to state 4 as compared to the typical drinking condition (figure 1.d).


CONCLUSIONS:

Based on our study's findings, individuals who abstain from alcohol spend less time in state 4 and exhibit a reduced tendency to transition from other states to state 4. This state may serve as a mediating stage between less connected states (states 2 and 3) and highly connected states (states 1 and 5). The absence of this state could result in the subnetwork of the brain associated with attention and self-focus lacking a moderately connected network. This state should be the focus of future research for a potential association with AUD.

ACKNOWLEDGEMENTS:This research was supported by the National Institutes of Alcohol Abuse and
Alcoholism of the National Institutes of Health under Award Number P50 AA026117.

REFERENCES:

Shappell H, Caffo BS, Pekar JJ, Lindquist MA. Improved state change estimation in dynamic functional connectivity using hidden semi-Markov models. Neuroimage. 2019 May 1;191:243-257. doi: 10.1016/j.neuroimage.2019.02.013. Epub 2019 Feb 10. PMID: 30753927; PMCID: PMC6504179.