Walder-Christensen, K. | bioRxiv Science

bioRxiv2026

A widespread internal brain state for fentanyl withdrawal

Opioid addiction is characterized by escalating drug use, driven in part by negative reinforcement from withdrawal, but the neural processes linking withdrawal to increased drug-taking remain poorly understood. Here, we use multisite local field potential recordings and interpretable machine learning to identify large-scale brain networks engaged by repeated opioid exposure and withdrawal. After discovering that repeated fentanyl exposure induces a progressively ramping network of widespread high beta and low gamma oscillations, we then identified a distinct brain network that selectively encodes the emergence and severity of opioid withdrawal. This network, termed EN-Withdrawal, is characterized by regional gamma oscillations and widely synchronized delta/theta oscillations. Its activity patterns predict the emergence of spontaneous and naloxone-precipitated withdrawal across multiple independent cohorts, generalizing across mice, sex, opioids, and dosing regimens, while persisting over multiple days of withdrawal. Using a novel, data-driven severity index, we find that network activity scales with individual behavioral severity without simply reflecting ongoing somatic behaviors or general aversion, suggesting that EN-Withdrawal underlies a withdrawal-induced internal state. Strikingly, network activity predicts the escalation of fentanyl self-administration on a mouse-by-mouse basis in experienced, but not drug-naive, animals. These findings reveal a neurophysiological substrate of the negative reinforcement cycle of addiction that shapes individual vulnerability.

neuroscience↗

bioRxiv2024

Sleep-wake states are encoded across emotion-regulation regions of the mouse brain

Emotional dysregulation is highly comorbid with sleep disturbances. Sleep is comprised of unique physiological states that are reflected by conserved brain oscillations. Though the role of these state-dependent oscillations in cognitive function has been well established, less is known regarding the nature of state-dependent oscillations across brain regions that strongly contribute to emotional function. To characterize these dynamics, we recorded local field potentials simultaneously from multiple cortical and subcortical regions implicated in sleep and emotion-regulation and characterize widespread patterns of spectral power and synchrony between brain regions during sleep/wake states. First, we showed that these brain regions encode sleep state, albeit to various degrees of accuracy. We then identified network-based classifiers of sleep based on the combination of features from all recorded brain regions. Spectral power and synchrony from brain networks allowed for automatic, accurate and rapid discrimination of wake, non-REM sleep (NREM) and rapid eye movement (REM) sleep. When we examined the impact of commonly prescribed sleep promoting medications on neural dynamics across these regions, we found disparate alterations to both cortical and subcortical activity across all three states. Finally, a we found that a stress manipulation that disrupts circadian rhythm produced increased sleep fragmentation without altering the underlying average brain dynamics across sleep-wake states. Thus, we characterized state dependent brain dynamics across regions canonically associated with emotions. Significance StatementSleep and emotion regulation are known to be intertwined at the level of behavior and in neuropsychiatric illnesses. Here, we examined how brain regions involved in emotion regulation encode wake and sleep states by performing multi-site electrophysiological recordings in mice. We developed sleep-wake state classifiers that rapidly labeled sleep-wake states from brain activity alone. We then identified how commonly prescribed sleep-inducing medications have unique impacts on brain activity throughout these emotion-regulation regions. Finally, we explored the impact of circadian rhythm disruption on sleep architecture and brain activity. Together, these data shed light on how brain regions which regulate emotion behave during sleep so that one day, treatments to improve both sleep and emotional well-being may be developed.

neuroscience↗