Changes in Computational Markers of Decision-Making are Proximally Tied to Heroin Use in Opioid Users Followed Longitudinally Through the First Months of Treatment

Anna Konova, Silvia Lopez-Guzman, Adelya Urmanche, Stephen Ross, Kenway Louie, John Rotrosen, Paul Glimcher

Resultado de la investigación: Contribución a RevistaResumen en Conferencia

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Resumen

Antecedentes: Las muertes por sobredosis de opiáceos se han cuadruplicado en la última década y ahora son la principal causa de muerte accidental en los EE.UU. La recaída en el consumo de opiáceos (heroína y analgésicos) durante el tratamiento de abstinencia o de reemplazo de opiáceos aumenta significativamente el riesgo de sobredosis. Por lo tanto, la identificación de los factores predictores de recaída y, en última instancia, la prevención de la recaída, en individuos que se abstengan y/o busquen tratamiento es de vital importancia. Aquí probamos la hipótesis de que los marcadores computacionales de la toma de decisiones están próximos al consumo de heroína en los individuos que buscan tratamiento para su adicción a los opiáceos. Concretamente, planteamos la hipótesis de que el valor de las perspectivas de riesgo aumenta cuando estas personas son más vulnerables a volver a consumir heroína, y que la base neurobiológica de esta vulnerabilidad implicaría el sistema de valoración del cerebro compuesto por el córtex prefrontal estriado y ventromedial (VMPFC). Métodos: 79 usuarios crónicos de opiáceos fueron estudiados en serie durante los primeros 7 meses de iniciar el tratamiento de reemplazo de opiáceos (1-15 sesiones de estudio/sujeto; media = 6, DE = 3,9). En cada sesión, caracterizamos la toma de decisiones individuales y documentamos cualquier retorno al consumo de heroína mediante autoinforme y pruebas toxicológicas de orina aleatorias (semanales). Para derivar los marcadores computacionales de la toma de decisiones utilizamos una tarea validada susceptible de ser modelada neuroeconómicamente. En la tarea completada en cada sesión, los sujetos eligieron repetidamente entre cierta ganancia de dinero real y la oportunidad de jugar a la lotería. Las loterías diferían en la posible ganancia monetaria y en la probabilidad de experimentar esa ganancia. En algunos ensayos, la probabilidad de ganar la lotería era conocida (prospectos riesgosos), en otros, la probabilidad era sólo parcialmente conocida (prospectos ambiguos). Este diseño general nos permitió realizar análisis con desfase temporal para predecir el consumo de heroína en la próxima sesión a partir de la toma de decisiones sobre el comportamiento de la sesión actual a través de la regresión logística de efectos mixtos. Un subconjunto de la cohorte más grande (n=12, estudio en curso) también completó una sesión de fMRI multibanda donde realizaron la misma tarea de toma de decisiones y exploraciones de estado de reposo para aislar el mecanismo neural del proceso de decisión involucrado. Resultados: De un total de 605 sesiones, 288 (47%) fueron positivas a la heroína. Sólo un aumento en un parámetro de decisión de tolerancia a la ambigüedad fue significativamente predictivo del uso prospectivo de heroína en la escala de tiempo examinada[t(577)=3,39, p<0,001], lo que respalda nuestra hipótesis de que el valor de estas perspectivas (más riesgosas) aumenta cuando los individuos son más vulnerables. Los datos preliminares de fMRI revelaron actividad en el estrato y VMPFC codificaron el valor de los prospectos ambiguos en una base de prueba por prueba, aumentando a medida que aumentaba su valor subjetivo. La actividad en estas regiones a su vez se correlacionó con la conectividad entre ellas en reposo, lo que sugiere que la actividad coordinada en el sistema de valoración del cerebro podría subyacer tanto en el comportamiento observado en la toma de decisiones como en la vulnerabilidad al consumo de heroína. Conclusiones: El seguimiento del tratamiento y los esfuerzos de intervención dirigidos a los procesos de toma de decisiones para las perspectivas de riesgo (y por lo tanto el sistema de valoración) pueden ayudar a reducir la incidencia de recaída en una población de alto riesgo de muerte por sobredosis.
Idioma originalEnglish (US)
Páginas (desde-hasta)S279
PublicaciónNeuropsychopharmacology
Volumen43
N.ºS1
DOI
EstadoPublished - nov 1 2017

Citar esto

Konova, Anna ; Lopez-Guzman, Silvia ; Urmanche, Adelya ; Ross, Stephen ; Louie, Kenway ; Rotrosen, John ; Glimcher, Paul. / Changes in Computational Markers of Decision-Making are Proximally Tied to Heroin Use in Opioid Users Followed Longitudinally Through the First Months of Treatment. En: Neuropsychopharmacology. 2017 ; Vol. 43, N.º S1. pp. S279.
@article{fc1014e076c546378cc966cafb7fdb5c,
title = "Changes in Computational Markers of Decision-Making are Proximally Tied to Heroin Use in Opioid Users Followed Longitudinally Through the First Months of Treatment",
abstract = "Background: Opioid overdose deaths have increased four-fold in the last decade and are now the leading cause of accidental death in the U.S. Relapse to opioid (heroin and painkiller) use during abstinence or opioid replacement treatment significantly increases the risk for overdose. Identifying predictors of relapse, and ultimately preventing relapse, in abstaining and/or treatment-seeking individuals is thus of critical importance. Here we tested the hypothesis that computational markers of decision-making are proximately tied to heroin use in individuals seeking treatment for their opioid addiction. We specifically hypothesized that the value of risky prospects is enhanced when these individuals are most vulnerable to return to heroin use, and that the neurobiological basis of this vulnerability would involve the brain’s valuation system comprised of the striatum and ventromedial prefrontal cortex (VMPFC). Methods: 79 chronic opioid users were serially studied over the first 7 months of initiating opioid replacement treatment (1-15 study sessions/subject; mean=6, SD=3.9). At each session, we characterized individual decision-making and documented any return to heroin use by self-report and random (weekly) urine toxicology tests. To derive computational markers of decision-making we used a validated task amenable to neuroeconomic modeling. In the task completed at each session, subjects repeatedly chose between certain gain of real money and a chance to play a lottery. Lotteries differed in possible monetary gain and in the probability of experiencing that gain. In some trials, the probability of winning the lottery was known (risky prospects), in others, the probability was only partially known (ambiguous prospects). This overall design allowed us to perform time-lagged analyses predicting heroin use next session from decision-making behavior on the current session via mixed-effects logistic regression. A subset of the larger cohort (n=12, study ongoing) also completed a multi-band fMRI session where they performed the same decision-making task and resting-state scans to isolate the neural mechanism of the decision process involved. Results: Of 605 total sessions, 288 (47{\%}) were heroin positive. Only an increase in an ambiguity tolerance decision parameter was significantly predictive of prospective heroin use at the timescale examined [t(577)=3.39, p<0.001], supporting our hypothesis that the value of these (more risky) prospects is enhanced when individuals are most vulnerable. The preliminary fMRI data revealed activity in the striatum and VMPFC encoded the value of the ambiguous prospects on a trial-by-trial basis, increasing as their subjective value increased. Activity in these regions in turn correlated with connectivity between them at rest, together suggesting that coordinated activity in the brain’s valuation system might underlie both the observed decision-making behavior and heroin use vulnerability. Conclusions: Treatment monitoring and intervention efforts aimed at decision processes for risky prospects (and thus the valuation system) may help reduce incidence of relapse in a population at high risk for overdose death.",
author = "Anna Konova and Silvia Lopez-Guzman and Adelya Urmanche and Stephen Ross and Kenway Louie and John Rotrosen and Paul Glimcher",
year = "2017",
month = "11",
day = "1",
doi = "10.1038/npp.2017.264",
language = "English (US)",
volume = "43",
pages = "S279",
journal = "Neuropsychopharmacology",
issn = "0893-133X",
publisher = "Nature Publishing Group",
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Changes in Computational Markers of Decision-Making are Proximally Tied to Heroin Use in Opioid Users Followed Longitudinally Through the First Months of Treatment. / Konova, Anna; Lopez-Guzman, Silvia; Urmanche, Adelya; Ross, Stephen; Louie, Kenway; Rotrosen, John; Glimcher, Paul.

En: Neuropsychopharmacology, Vol. 43, N.º S1, 01.11.2017, p. S279.

Resultado de la investigación: Contribución a RevistaResumen en Conferencia

TY - JOUR

T1 - Changes in Computational Markers of Decision-Making are Proximally Tied to Heroin Use in Opioid Users Followed Longitudinally Through the First Months of Treatment

AU - Konova, Anna

AU - Lopez-Guzman, Silvia

AU - Urmanche, Adelya

AU - Ross, Stephen

AU - Louie, Kenway

AU - Rotrosen, John

AU - Glimcher, Paul

PY - 2017/11/1

Y1 - 2017/11/1

N2 - Background: Opioid overdose deaths have increased four-fold in the last decade and are now the leading cause of accidental death in the U.S. Relapse to opioid (heroin and painkiller) use during abstinence or opioid replacement treatment significantly increases the risk for overdose. Identifying predictors of relapse, and ultimately preventing relapse, in abstaining and/or treatment-seeking individuals is thus of critical importance. Here we tested the hypothesis that computational markers of decision-making are proximately tied to heroin use in individuals seeking treatment for their opioid addiction. We specifically hypothesized that the value of risky prospects is enhanced when these individuals are most vulnerable to return to heroin use, and that the neurobiological basis of this vulnerability would involve the brain’s valuation system comprised of the striatum and ventromedial prefrontal cortex (VMPFC). Methods: 79 chronic opioid users were serially studied over the first 7 months of initiating opioid replacement treatment (1-15 study sessions/subject; mean=6, SD=3.9). At each session, we characterized individual decision-making and documented any return to heroin use by self-report and random (weekly) urine toxicology tests. To derive computational markers of decision-making we used a validated task amenable to neuroeconomic modeling. In the task completed at each session, subjects repeatedly chose between certain gain of real money and a chance to play a lottery. Lotteries differed in possible monetary gain and in the probability of experiencing that gain. In some trials, the probability of winning the lottery was known (risky prospects), in others, the probability was only partially known (ambiguous prospects). This overall design allowed us to perform time-lagged analyses predicting heroin use next session from decision-making behavior on the current session via mixed-effects logistic regression. A subset of the larger cohort (n=12, study ongoing) also completed a multi-band fMRI session where they performed the same decision-making task and resting-state scans to isolate the neural mechanism of the decision process involved. Results: Of 605 total sessions, 288 (47%) were heroin positive. Only an increase in an ambiguity tolerance decision parameter was significantly predictive of prospective heroin use at the timescale examined [t(577)=3.39, p<0.001], supporting our hypothesis that the value of these (more risky) prospects is enhanced when individuals are most vulnerable. The preliminary fMRI data revealed activity in the striatum and VMPFC encoded the value of the ambiguous prospects on a trial-by-trial basis, increasing as their subjective value increased. Activity in these regions in turn correlated with connectivity between them at rest, together suggesting that coordinated activity in the brain’s valuation system might underlie both the observed decision-making behavior and heroin use vulnerability. Conclusions: Treatment monitoring and intervention efforts aimed at decision processes for risky prospects (and thus the valuation system) may help reduce incidence of relapse in a population at high risk for overdose death.

AB - Background: Opioid overdose deaths have increased four-fold in the last decade and are now the leading cause of accidental death in the U.S. Relapse to opioid (heroin and painkiller) use during abstinence or opioid replacement treatment significantly increases the risk for overdose. Identifying predictors of relapse, and ultimately preventing relapse, in abstaining and/or treatment-seeking individuals is thus of critical importance. Here we tested the hypothesis that computational markers of decision-making are proximately tied to heroin use in individuals seeking treatment for their opioid addiction. We specifically hypothesized that the value of risky prospects is enhanced when these individuals are most vulnerable to return to heroin use, and that the neurobiological basis of this vulnerability would involve the brain’s valuation system comprised of the striatum and ventromedial prefrontal cortex (VMPFC). Methods: 79 chronic opioid users were serially studied over the first 7 months of initiating opioid replacement treatment (1-15 study sessions/subject; mean=6, SD=3.9). At each session, we characterized individual decision-making and documented any return to heroin use by self-report and random (weekly) urine toxicology tests. To derive computational markers of decision-making we used a validated task amenable to neuroeconomic modeling. In the task completed at each session, subjects repeatedly chose between certain gain of real money and a chance to play a lottery. Lotteries differed in possible monetary gain and in the probability of experiencing that gain. In some trials, the probability of winning the lottery was known (risky prospects), in others, the probability was only partially known (ambiguous prospects). This overall design allowed us to perform time-lagged analyses predicting heroin use next session from decision-making behavior on the current session via mixed-effects logistic regression. A subset of the larger cohort (n=12, study ongoing) also completed a multi-band fMRI session where they performed the same decision-making task and resting-state scans to isolate the neural mechanism of the decision process involved. Results: Of 605 total sessions, 288 (47%) were heroin positive. Only an increase in an ambiguity tolerance decision parameter was significantly predictive of prospective heroin use at the timescale examined [t(577)=3.39, p<0.001], supporting our hypothesis that the value of these (more risky) prospects is enhanced when individuals are most vulnerable. The preliminary fMRI data revealed activity in the striatum and VMPFC encoded the value of the ambiguous prospects on a trial-by-trial basis, increasing as their subjective value increased. Activity in these regions in turn correlated with connectivity between them at rest, together suggesting that coordinated activity in the brain’s valuation system might underlie both the observed decision-making behavior and heroin use vulnerability. Conclusions: Treatment monitoring and intervention efforts aimed at decision processes for risky prospects (and thus the valuation system) may help reduce incidence of relapse in a population at high risk for overdose death.

U2 - 10.1038/npp.2017.264

DO - 10.1038/npp.2017.264

M3 - Meeting Abstract

VL - 43

SP - S279

JO - Neuropsychopharmacology

JF - Neuropsychopharmacology

SN - 0893-133X

IS - S1

ER -