National Institute on Drug Abuse

Previous work showed that rats that were exposed to a high-fat, low-carbohydrate/protein ketogenic diet (KD) exhibited elevated blood alcohol levels following alcohol exposure compared with rats fed regular chow. Additionally, the administration of a KD prior to alcohol exposure (i.e., a history of KD) reduced alcohol consumption in alcohol-dependent rats that were no longer on the diet. In the present study, we investigated the mechanisms by which a KD alters alcohol metabolism and tested whether ongoing KD exposure reduces alcohol consumption in rats. We hypothesized that chronic KD exposure alters hepatic alcohol-metabolizing enzymes, slows alcohol metabolism, and reduces alcohol self-administration in alcohol-dependent rats. We found that male and female rats maintained on a KD had higher blood alcohol levels, lower hepatic alcohol dehydrogenase 1 protein levels, and a higher nicotinamide adenine dinucleotide [NAD+]/[NADH] ratio in the liver cytoplasm compared with chow-fed control rats. Furthermore, KD-fed rats demonstrated lower brain glucose uptake relative to chow-fed control rats. In a model of alcohol dependence, the KD reduced alcohol consumption in male, but not female, rats compared with chow-fed rats. These findings suggest that a KD alters brain energetics and alcohol metabolism, which may contribute to reduced alcohol consumption in male rats.

Dynamic resting-state brain activity provides insight into intrinsic neural function and holds promise for predicting individual responses to cognitive demands and pharmacological interventions. This research could ultimately guide medication selection, yet links between network dynamics and medication effects on cognitive function require further validation. Here, we examined whether dynamic activity of an attentional network at rest relates to task-evoked brain activation on the Multi Source Interference Task (MSIT) following administration of methylphenidate (20 mg) and haloperidol (2 mg), which have opposing effects on attention and catecholaminergic function. Fifty-nine healthy adults completed resting-state and task-based fMRI on three separate days on which they received methylphenidate, haloperidol, or placebo in a double-blind placebo-controlled design. Coactivation pattern analysis determined time spent in the dorsal attention network (DAN) under placebo at rest. Linear mixed-effects modeling assessing the relationship between MSIT task activation under drug and time spent in DAN at rest under placebo and MSIT task activation under drug identified a significant interaction in the dorsolateral prefrontal cortex (dlPFC; p < 0.001). Post-hoc analyses indicated that more time in the DAN at rest under placebo was associated with decreased MSIT dlPFC activation under methylphenidate and increased dlPFC activation under haloperidol. Findings demonstrate that resting dynamics of an attentional network are linked to task-related brain responses under different drug conditions within a region implicated in attentional control and sensitive to catecholaminergic variance. Resting-state dynamics may predict pharmacological modulation of goal-directed cognition, highlighting the potential clinical utility of resting-state dynamics in predicting medication response and supporting individualized treatment.

Cortical circuits produce time-varying patterns of population and single neuron activity that play a fundamental role in perceptual and behavioral processes. However, the functional contributions of individual neuron activity to population dynamics and behavior remain unclear. Here we addressed this issue focusing on the mouse gustatory cortex (GC) and using a taste mixture-based decision-making task, high-density electrophysiology, and computational modeling. GC population dynamics represented stimuli linearly during taste sampling and choices categorically before decisions. Single neurons were classified by their linear and categorical activity patterns, revealing subpopulations encoding sensory, perceptual, and decisional variables. To test their functional role, we built a recurrent neural network model of GC. Model perturbations showed linear and categorical neurons were essential for driving normal population dynamics and behavioral performance, whereas many units with other activity patterns could be silenced without consequence. These results have implications that extend beyond GC, and demonstrate the role of linear and categorical coding neurons in cortical dynamics and behavior during perceptual decision-making.

Despite long-term rising national rates of opioid-involved overdose deaths, little is known about the risks for US adults with work disability. A prospective cohort study was performed with a nationally representative sample of adults, ages 20-61years, from the 2008 American Community Survey (N = 2,403,000) followed through 2019 for overdose death involving opioids. Rates of fatal opioid overdose were calculated for adults with and without workdisability followed by adjusted overdose hazards from stepwise Cox models controlling for age, sex, and race/ethnicity; marital status, education, residence, and region; and adding employment and income. Adjusted opioid overdose hazards of disability status were also stratified by age groups, sex, race/ethnicity, and by hearing, visual, cognitive, mobility, self-care, independent living skills, and unspecified impairments. Approximately 4% had work disability. Annual fatal opioid overdose rates per 100,000 persons were 44.1 (95%CI = 40.1-48.3) for adults with workdisability and 9.4 (95%CI = 9.1-9.8) for those without workdisability. After controlling for age, sex, and race/ethnicity, the adjusted hazards of opioid overdose with disability were 5.92 (95%CI = 5.34-6.56), decreasing to 3.52 (95%CI = 3.14-3.93) after further controlling for marital status, residence, and education, and decreasing to 1.82 (95%CI = 1.62-2.05) after further controlling for employment and income, compared to adults without disability. In fully adjusted models, the association of workdisability with opioid overdose was stronger for females (2.44, 95%CI = 2.03-2.93) than for males (1.40, 95%CI = 1.20-1.64), older (1.93, 95%CI = 1.65-2.26) than younger (1.31, 95%CI = 1.07-1.61) adults, and Hispanic (2.80, 95%CI = 1.69-4.63) than White non-Hispanic (1.75, 95%CI = 1.54-1.99) adults. Relative to US adults without work disability, adults with work disability were at increased risk of fatal opioid overdose, including especially women, older adults, and Hispanic adults. New clinical and health policy initiatives may be needed to help protect US adults with work disability from the risks of fatal opioid overdose.

Although the recent proliferation of telemental health care has transformed the delivery of outpatient mental health care for many individuals in the US, little is known about how outpatients are distributed across telehealth, hybrid, and in-person care. To characterize the national distribution of sociodemographic and clinical outpatient mental health groups across telehealth, hybrid, and in-person mental health care. This was a cross-sectional analysis of all telehealth, hybrid, and all in-person mental health care by adults (aged ≥18 years) in the 2021-2022 Medical Expenditure Panel Survey (n = 4720). Data were analyzed from January to August 2025. Average annual percentages of adult mental health outpatients who used all telemental health care, hybrid, and all in-person mental health care were calculated overall and stratified by sociodemographic and clinical characteristics. Differences in percentages using each modality were evaluated by sociodemographic and clinical strata adjusted for age, sex, and distress level (Kessler-6 scale). Type of mental health treatment used (telemental health, hybrid, or in-person). The analysis involved 4720 participants (2235 aged 18-44 years; 3007 female). Approximate one-fourth (27.8%; 95% CI, 25.7-29.8) of mental health outpatients received all telemental health care, 21.5% (95% CI, 19.8-23.1) received hybrid care, and 50.6% (95% CI, 48.2-53.1) received all in-person care. The percentage of patients receiving all telemental health care was higher for younger (aged 18-44 years; 31.7%; 95% CI, 29.0-34.3) than middle age (aged 45-64 years; 24.2%; 95% CI, 21.1-27.4) or older (aged ≥65 years; 19.4%; 95% CI, 16.1-22.7) adults, high school (23.1% 95% CI, 20.4-25.8) and college (34.5%; 95% CI, 31.5-37.5) graduates than those without a high school diploma (19.9%; 95% CI, 13.7-26.1), patients with incomes >400% federal poverty level (33.8%; 95% CI, 30.9-36.7) than lower (range, 20.6% to 23.7%), private (30.8%; 95% CI, 28.5-33.1) than public (20.2%; 95% CI, 17.4-23.0) insurance, and urban (29.2%; 95% CI, 27.0-31.3) than rural (14.0%; 95% CI, 8.6-19.3) residence. Compared to patients receiving medication alone (15.4%; 95% CI, 12.5-18.3), those receiving psychotherapy with (25.9%; 95% CI, 23.2-28.6) or without (41.6%; 95% CI, 38.0-45.2) medication were more likely to use all telemental health. Patients with less than moderate distress (29.2%; 95% CI, 26.1-32.3) were also more likely than those with serious distress (21.2%; 95% CI, 16.7-25.6) to use all telemental health. In adjusted analyses, patients treated by mental health counselors (10.9%; 95% CI, 7.0-14.7) or social workers (8.4%; 95% CI, 4.1-12.7) were also more likely to receive all telemental health than were patients treated by other mental health clinicians. The findings of this cross-sectional study indicate that telehealth has become a common means of receiving outpatient mental health care in the US, especially for resourced patients with less serious psychological distress who receive psychotherapy from mental health specialists.