Alpha Band Oscillations in the Limbic Pallidum Track Future Alcohol Use
DOI: Pending DOI
Synopsis
Treating alcohol use disorder (AUD) remains challenging, with high relapse rates even after extended periods of abstinence. The limbic pallidum (LP) is a key structure in motivated behavior and has been proposed as a neuromodulatory target for AUD treatment. In this study, a sensing-enabled DBS system was placed in the LP of a patient with severe AUD, and local field potentials were collected during routine clinic visits. Prominent neural oscillations were identified in the canonical alpha to low beta frequency range, localized to the right ventral LP. Relative power within this range correlated strongly with drinks consumed in the 3 days following the recording session. These findings indicate that neural LP oscillations in the alpha band may act as a biomarker for future alcohol use.
Background
Current treatment options for alcohol use disorder (AUD) have limited efficacy, with roughly 40–60% of treated patients relapsing within 6 months of abstinence.¹ Combined with the severe societal and economic burden of AUD, this has driven substantial research into the underlying neural circuit dysfunctions.² The limbic pallidum (LP) is a central node within the circuits implicated in AUD pathophysiology and has emerged as a promising therapeutic neuromodulation target for AUD.³
Findings from monkey and human studies align with rodent research on the LP's role in reward and aversion processing.⁴,⁵,⁶,⁷,⁸,⁹,¹⁰,¹¹,¹² Preclinical evidence demonstrates that GABAergic LP neurons encode rewards and drive approach behaviors, and that the LP is critical for drug seeking and relapse in various substance use disorders and essential for resumption of drug seeking after abstinence.³,¹³ Conversely, glutamatergic LP neurons encode aversive outcomes and drive avoidance responses.³
The Percept DBS neurostimulator (Medtronic Inc.) allows for recording of local field potentials (LFPs) from implanted structures and has been used to study the neural basis of pathological behaviors in Parkinson’s disease, obsessive compulsive disorder, depression, and addiction.¹⁴,¹⁵,¹⁶,¹⁷ Additionally, symptom-driven titrations and electrophysiological biomarkers reactive to drug cues have been used to personalize treatment targeting in opioid use disorder and AUD.¹⁸,¹⁹,²⁰,²¹,²² We hypothesized that LP neural activity would be associated with alcohol-related behaviors like consumption and craving.
Methods
A male in his 50s with severe AUD and advanced compensated liver disease was implanted with Sensight DBS electrodes (Medtronic Inc.) into the LP (anterior GPi – globus pallidus internal segment). The electrodes were localized using the LeadDBS software.²³ The subject was followed with weekly phone visits to ensure safety and accurate alcohol use reporting. Additionally, monthly in-person visits occurred during which stimulation was turned off and LFPs were recorded for 10-20 min, totaling 16 recording sessions.
LFPs were recorded in bipolar configuration between three unique pairs of contacts (0-2, 1-3, etc.) in each lead. LFPs between adjacent contacts (0-1, 1-2, etc.) were computed from the raw recordings for in-depth localization. LFPs were divided into 3-second epochs and passed to MATLAB’s periodogram function to compute the power spectral density (PSD). The PSDs were then averaged for each recording session. Periodic spectral power was separated from the aperiodic component of the PSDs with a modified fitting of one over frequency algorithm.²⁴,²⁵ To compare frequency band power, relative periodic power (RPP) was calculated by integrating the periodic PSD over specific frequency ranges (e.g., alpha: 8-12 Hz). The observed prominent oscillations occurred within the 7-15 Hz range, peaking in the alpha band. Given this observed range extends beyond the canonical alpha band and given the evidence that cortical and subcortical oscillations do not always align perfectly²⁶,²⁷,²⁸, we refer to the observed LP alpha band activity as the frequency band of interest (FBOI).
Results
Average PSDs were calculated from 16 recording sessions and split into aperiodic and periodic components. Prominent oscillatory activity in the 7-15 Hz range that peaks in the alpha band (11-12 Hz) was recorded in the right hemisphere LP from the most ventral contacts (8-9) of the DBS electrodes (Fig 1a, b). Hereafter, we denote the 7-15 Hz frequency range as the frequency band of interest (FBOI), given that it extends beyond the 8-12 Hz canonical alpha band, as previously described in the methods section. The prominent FBOI periodic peak observed between contact pair 8-9 was not observed in recordings from any contacts on the left, or more dorsal contact pairs on the right (e.g., 9-10 or 9-11), but was observed between contact pairs 8-10 and 8-11. This suggests specificity of the activity to contact 8.
To connect this oscillatory activity to the pathological behaviors of AUD, we examined the correlation between periodic power in various frequency bands and drinking behavior – measured as the number of drinks, before, after, and around each recording session. We also investigated the correlation between the aperiodic fit parameters and drinking behavior. For all 16 sessions and all contact pairs, the RPP was integrated for each of the canonical frequency bands as well as the FBOI to determine the strength of oscillatory activity. The Spearman correlation coefficient between the resulting RPPs and the number of drinks consumed in the 1, 3, 5, and 7 days before, after, and around each recording session were computed. The strongest and most significant correlation was observed between the FBOI RPP and the number of drinks consumed in the 3 days following the recording session (Fig 1c, Spearman’s ρ = 0.8935, Šidák’s multiple comparison test p = 0.0002). Significant correlations were only observed for the FBOI and its subcomponent – canonical alpha band – in contact pair 8-9. FBOI and alpha band RPP were more correlated with drinking post-recording session compared to pre-recording session (Fig 1d). Other time windows analyzed as well as aperiodic fit parameters did not exhibit significant correlations. Moreover, the same analyses for other sequential contact pairs did not reveal any meaningful correlations. Of note, the FBOI RPP did not show significant correlation with depression (MADRS) and anxiety (HAM-A) scores.
Using the K-means method (Fig 1e, k = 2) for automatic clustering of the FBOI RPP and number of drinks 3 days post-recording session resulted in groups that aligned with heavy drinking (n = 7) and no/light drinking (n = 9) as defined by the National Institute on Alcohol Abuse and Alcoholism (heavy drinking for men: >5 drinks in 1 day or >15 drinks in 1 week) when considering the full week of drinking behavior following the recording sessions. Therefore, we separated the recording sessions based on these no/light and heavy drinking definitions and found the FBOI periodic power between contacts 8 and 9 was significantly greater in heavy drinking sessions compared to no/light drinking sessions (Fig 1f, p = 0.0005). Alpha band periodic power was also significantly different between contacts 8 and 9 when comparing these clustered recording sessions (Fig 1f, p = 0.0214). No other significant differences in RPP were observed across any frequency band or contact pair between the two session groups. Similarly, aperiodic fitting parameters did not differ significantly between groups.
Discussion
In this exploratory study, we present a possible neural biomarker predictive of alcohol use. A key aspect of our finding is the signal’s anatomical specificity. The increased FBOI periodic activity was most strongly observed between contact pair 8-9, and the activity was localized to contact 8, which was in the ventral pallidum, ventral to the anterior GPi. Recently, a similar contact-level localization in the Nucleus accumbens was shown for opioid use disorder.²² Together, these results suggest that distinct subregions in the basal ganglia contain electrophysiological indicators of future substance use, reinforcing the value of defined biomarkers in closed-loop neuromodulation.
Most recordings were obtained with negative breathalyzer results, and FBOI RPP correlated more strongly with future drinking than with past drinking, suggesting that the observed increase in FBOI periodic power is not simply due to acute alcohol effects or short-term neurophysiological adaptations to recent exposure. If either were driving the signal, stronger correlation with pre-recording or peri-recording consumption would be expected.
Given the inherently subjective nature of craving, identifying reliable electrophysiological biomarkers for AUD remains an important goal. Larger and more diverse patient cohorts will be needed to further evaluate LP periodic activity in the alpha band and other frequency bands as potential biomarkers for craving, and to establish whether a causal relationship exists between the identified LP oscillatory activity and pathological behaviors in substance use disorder.
Disclosures
This work was supported by the NIH (AA030505) and the Weill Institute of Neuroscience at UCSF.
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