Biology subjects

Dwiel, L.

Publications and source records attributed to Dwiel, L..

5 recordsLinked to original sources

bioRxiv2025

Lysergic acid diethylamide pretreatment prolongs brain-stimulation induced neural activity

A leading theory for how psychedelics are able to produce robust clinical improvement and preclinical behavioral changes is that psychedelics act through neuroplastic mechanisms to induce lasting structural and functional alterations in neural circuits. However, psychedelics produce these effects across wide swaths of the brain. Based on our prior work, we hypothesized that engaging a specific brain circuit with focal brain stimulation during the window of enhanced plasticity produced by psychedelics would lead to more persistent alterations in the activity of that circuit. To test this, we administered either saline (SAL) or lysergic acid diethylamide (LSD) to rats 24 hours prior to electrical stimulation targeting the rat medial prefrontal cortex (mPFC). Brain activity was recorded before, during, and after stimulation using depth electrodes implanted in four bilateral frontostriatal regions. To assess changes in neural activity, we trained general logistic classifiers to distinguish between time points (e.g., pre-stimulation vs. post-stimulation) and then compared model performances across groups (e.g., LSD vs. SAL). As such, model performance represents the degree of difference between the two neural states (pre vs. post), and a significant difference between groups indicates a larger change in brain activity in one group. We found that LSD pretreatment, compared to SAL, resulted in larger and longer-lasting changes in brain activity following stimulation. Immunohistochemistry revealed that stimulation led to the activation of the mTOR signaling pathway, and the combination of LSD and stimulation led to alterations in perineuronal net (PNN) integrity. Regardless of pretreatment, brain activity states recorded during stimulation did not capture the brain state that persisted in the minutes or days that followed. This work has important implications for understanding the general effects of brain stimulation and provides strong support for the development of psychedelic-assisted brain stimulation approaches. By increasing the durability of brain stimulation-induced changes in activity, this approach could lead to a reduction in relapse rates, which currently limit the impact of non-invasive stimulation treatments.

neuroscience↗

bioRxiv2024

Chronic intermittent alcohol yields sex-specific disruptions in cortical-striatal-limbic oscillations

BackgroundWhile the neurobiology of alcohol use disorder (AUD) has been extensively researched, the vast majority of these studies included only male organisms. However, there are significant sex differences in both the causes and consequences of alcohol misuse and dependence, suggesting sex-specific neurobiological mechanisms. The current study used a rodent model to determine whether chronic alcohol exposure impacts sex-specific neural circuits, and whether these changes contribute to the development of alcohol misuse. MethodsMale and female Sprague-Dawley rats were trained to self-administer 10% alcohol before implanting bilateral electrodes into the infralimbic medial prefrontal cortex (IL), nucleus accumbens shell (NAcSh), and central nucleus of the amygdala (CeA). Half of the rats were then exposed to four weeks of chronic intermittent alcohol (CIA) vapor (14 hours on/10 hours off). During acute withdrawal (6-8 after the vapor turns off), local field potentials (LFPs) were recorded from the IL, NAcSh, and CeA during 30-minute self-administration sessions. Using an unbiased machine learning approach, we built predictive models to determine whether/which LFP features could distinguish CIA-exposed from control rats in each sex, as well as if any of these LFP features correlated with rates of alcohol self-administration. ResultsFemale rats self-administered more alcohol in general compared to males, but only males exposed to CIA showed increased alcohol intake during acute withdrawal. LFPs predicted CIA exposure in both sexes better than chance estimates, but models built on IL and NAcSh oscillations performed the best in males, while models built on IL and CeA LFPs performed best in females. High {gamma} LFPs recorded in the NAcSh correlated with rates of alcohol self-administration in males exposed to CIA, while only left-right NAcSh {beta} coherence correlated with drinking in control females. ConclusionsThese data provide support for the hypothesis that the neural circuits driving alcohol dependence development are sex-specific, and that high frequency oscillations in the NAcSh may be related to the increased drinking observed in males exposed to CIA. Overall, these data add to our understanding of the neurobiological underpinnings behind the sex differences observed in AUD and offer promising biomarkers for future therapeutic research.

neuroscience↗

bioRxiv2022

Psychedelics enhance the effects of brain stimulation in rodents

BackgroundPsychedelic drugs have resurged in neuroscience and psychiatry with promising success in psychedelic-assisted therapy for the treatment of anxiety, depression, and addiction. At the cellular level, psychedelic drugs elicit neuroplastic processes 24 hours after administration, priming neural circuits for change. The acute effects of psychedelic drugs are well characterized with functional imaging and neural oscillations showing an increase in the entropy of spontaneous cortical activity. HypothesesWe hypothesized that cortical-striatal oscillations recorded in rats would confirm the effects of psychedelic drugs. We also hypothesized that brain stimulation delivered 24 hours after LSD administration would lead to different effects than brain stimulation alone. MethodsWe recorded local field potential (LFP) oscillations from rats following lysergic acid diethylamide (LSD) or saline administration and determined if exposure to these treatments altered the effect of a targeted intervention (brain stimulation) 24 hours later. ResultsWe confirmed acutely decreased low frequency power across the brain when rats are given LSD. We also demonstrated these altered states return to baseline after 24 hours. Brain stimulation applied in the previously reported window of heightened neuroplasticity produced distinct shifts in brain state compared to brain stimulation applied 24 hours after saline. ConclusionsDespite the acute effects of LSD disappearing after 24 hours, there are still latent effects that interact with brain stimulation to create larger and distinct changes in brain activity compared to brain stimulation alone. Our proof-of-concept findings are the first to suggest that psychedelic drugs could work in combination with brain stimulation to achieve enhanced effects on brain activity and future work will assess impacts on stimulation induced changes in behavior.

neuroscience↗

bioRxiv2018

An unbiased decoding of ventral striatal oscillations in a rat model of binge eating: Finding the balance between model complexity and performance.

The ventral striatum (VS) is a central node within a distributed network that controls appetitive behavior, and neuromodulation of the VS has demonstrated therapeutic potential for appetitive disorders. Local field potential (LFP) oscillations recorded from deep brain stimulation electrodes within the VS are a pragmatic source of neural systems-level information about appetitive behavior that could be used in responsive neuromodulation systems. Here, we recorded LFPs from the bilateral nucleus accumbens core and shell (subregions of the VS) during limited access to palatable food across varying conditions of hunger and food palatability in male rats. We used standard statistical methods (logistic regression) as well as the machine learning algorithm lasso to predict aspects of feeding behavior using VS LFPs. These models were able to predict the amount of food eaten, the increase in consumption following food deprivation, and the type of food eaten. Further, we were able to predict whether the initiation of feeding was imminent up to 42.5 seconds before feeding began and classify current behavior as either feeding or not-feeding. In classifying this behavior, we found an optimal balance between model complexity and performance with models using 3 LFP features primarily from the alpha and high gamma frequencies. As shown here, unbiased methods can identify systems-level neural activity linked to symptoms of mental illness with potential application to the development and personalization of novel treatments.\n\nAuthor SummaryAs neuropsychiatry begins to leverage the power of computational methods to understand disease states and to develop better therapies, it is vital that we acknowledge the trade-offs between model complexity and performance. We show that computational methods can elucidate a neural signature of feeding behavior and show how these methods could be used to discover neural patterns related to other behaviors and used as therapeutic targets. Further, our results helps to contextualize both the limitations and potential of applying computational methods to neuropsychiatry by showing how changing the data being used to train predictive models (e.g., population vs. individual data) can have a large impact on how model performance generalizes across time, internal states and individuals.

neuroscience↗

bioRxiv2018

Machine learning based classification of deep brain stimulation outcomes in a rat model of binge eating using ventral striatal oscillations.

Neuromodulation-based interventions continue to be evaluated across an array of appetitive disorders but broader implementation of these approaches remains limited due to variable treatment outcomes. We hypothesize that individual variation in treatment outcomes may be linked to differences in the networks underlying these disorders. Here, Sprague-Dawley rats received deep brain stimulation separately within each nucleus accumbens (NAc) sub-region (core and shell) using a within-animal crossover design in a rat model of binge eating. Significant reductions in binge size were observed with stimulation of either target but with significant variation in effectiveness across individuals. When features of local field potentials (LFPs) recorded from the NAc were used as predictors of the pre-defined stimulation outcomes (response or non-response) from each rat using a machine-learning approach (lasso), stimulation outcomes could be predicted with greater accuracy than expected by chance (effect sizes: core = 1.13, shell = 1.05). Further, these LFP features could be used to identify the best stimulation target for each animal (core vs. shell) with an effect size = 0.96. These data suggest that individual differences in underlying network activity may contribute to the variable outcomes of circuit based interventions and that measures of network activity have the potential to individually guide the selection of an optimal stimulation target and improve overall treatment response rates.

neuroscience↗