Dataset Information

Machine Learning Based Classification of Deep Brain Stimulation Outcomes in a Rat Model of Binge Eating Using Ventral Striatal Oscillations.

ABSTRACT: 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 to classify the pre-defined stimulation outcomes (response or non-response) from each rat using a machine-learning approach (lasso), stimulation outcomes could be classified 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 relate to the variable outcomes of circuit based interventions, and measures of network activity could have the potential to individually guide the selection of an optimal stimulation target to improve overall treatment response rates.

SUBMITTER: Doucette WT

PROVIDER: S-EPMC6085408 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Machine Learning Based Classification of Deep Brain Stimulation Outcomes in a Rat Model of Binge Eating Using Ventral Striatal Oscillations.

Doucette Wilder T WT Dwiel Lucas L Boyce Jared E JE Simon Amanda A AA Khokhar Jibran Y JY Green Alan I AI

Frontiers in psychiatry 20180803

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 ...[more]

PMID: 30123143

Similar Datasets

Project description:ObjectiveAlthough several effective behavioral treatments for binge-eating disorder (BED) exist, there are racial disparities in treatment access, with African-Americans and/or Black individuals having some of the lowest rates of access to care. Little is known about the experience and treatment of binge eating (BE) and BED among Black women.MethodThis systematic review, conducted according to PRISMA guidelines, synthesizes information related to BE and BED in Black women.ResultsA total of N = 38 studies met our eligibility criteria. We did not identify any systematic risk of bias across studies. The majority of included studies used cross-sectional survey methodology, and relied on interview (EDE) and self-report measures (particularly the Binge Eating Scale, BES) for the assessment of BE. Outcomes were inconsistently measured across trials, and there are limited data on the results of evidence-based treatments for BE/BED in Black women.DiscussionAlthough Black women have similar or higher rates of BE than White women, most research on BE and BED has focused on White women, with Black individuals underrepresented in clinical trials. Future research should examine evidence-based treatments to prevent and treat BED in this population.ObjetivoAunque existen varios tratamientos conductuales que son efectivos para el Trastorno de Atracones (BED, por sus siglas en inglés), existen disparidades raciales en el acceso a tratamiento, con individuos Afroamericanos y/o personas de color teniendo algunas de las tasas más bajas de acceso al cuidado de la salud. Se sabe muy poco acerca de la experiencia y tratamiento del comer en atracones (BE, por sus siglas en inglés) y BED entre mujeres afroamericanas y/o de color. MÉTODO: Esta revisión sistemática, realizada bajo lineamientos de las guías PRISMA, sintetiza información relacionada con BE y BED en mujeres afroamericanas y/o de color.ResultadosUn total de N = 38 estudios cumplieron con nuestros criterios de elegibilidad. No identificamos ningún riesgo sistemático de sesgo entre los estudios. La mayoría de los estudios incluidos utilizaron una metodología de encuesta transversal y se basaron en la entrevista (EDE) y las medidas de autoinforme (en particular, la Binge Eating Scale, BES) para la evaluación de BE. Los resultados se midieron de manera inconsistente entre los ensayos, y hay datos limitados sobre los resultados de los tratamientos basados en la evidencia para BE/BED en mujeres afroamericanas y/o de color. DISCUSIÓN: Aunque las mujeres afroamericanas y/o de color tienen tasas similares o más altas de BE que las mujeres blancas, la mayoría de las investigaciones sobre BE y BED se han centrado en las mujeres blancas, con individuos afroamericanos y/o de color subrepresentados en ensayos clínicos. La investigación futura debería examinar los tratamientos basados en la evidencia para prevenir y tratar el BED en esta población.

Dataset Information

Machine Learning Based Classification of Deep Brain Stimulation Outcomes in a Rat Model of Binge Eating Using Ventral Striatal Oscillations.

Publications

Machine Learning Based Classification of Deep Brain Stimulation Outcomes in a Rat Model of Binge Eating Using Ventral Striatal Oscillations.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets