Week-to-Week Fluctuations in Risky Decision Making Track Heroin Use in Treatment-Seeking Opioid Users

Anna B Konova, Silvia Lopez-Guzman, Adelya Urmanche, John Messinger, Soteri Polydorou, Stephen Ross, Kenway Louie, John Rotrosen, Paul W Glimcher

Research output: Contribution to journalMeeting Abstract

Abstract

Background: The degree to which opioid replacement
therapy (e.g., methadone), the gold standard in opioid
addiction management, is effective at reducing illicit opioid
use depends on how well titrated it is for the current needs of
an individual. However, good proximal predictors of when
an individual is at risk for relapse—and therefore in need of
additional behavioral and/or pharmacological intervention—
are currently lacking. Here, we use standard computationally
driven neuroeconomic measurements to decompose the risk
taking behavior of opioid users undergoing opioid replacement
therapy, as a way to identify behavioral markers that
might predict illicit opioid use.
Methods: We had individuals starting opioid replacement
therapy (i.e., who were within 4 weeks of treatment
initiation) perform simple and easy-to-automate monetary
decision making tasks weekly (and then every other week)
over several months of treatment. We established when our
subjects returned to illicit opioid (or any drug) use by both
self-report and randomly administered (at least 1/week)
urine toxicology tests. A matched sample of drug-free
community controls also completed the decision making
tasks. These subjects both served as a baseline control group
as well as allowed us to assess the test-retest reliability of our
measurements. A subset of subjects from both groups also
completed the tasks while we acquired functional magnetic
resonance imaging (MRI) data at two time points: once at the
beginning of the treatment and again 8-12 weeks later. The
measurements we used are based on a standard neuroeconomic
model that decomposes the behavior of each subject
into two parameters: “risk attitude” and “ambiguity attitude”,
indexing how sensitive that subject is to known and
unknown risks, respectively. We computed these parameters
for each subject at each study session, and using generalized
linear mixed models, we examined how fluctuations in these
parameters related retrospectively and prospectively to illicit
opioid use events.
Results: We find a high degree of test-retest reliability across
the study sessions for both parameters. Attesting to the
distinct aspects of risky decision making captured by these
parameters, we find that only sudden increases in an opioiddependent
subject’s willingness to take risks in our task
correlated with, and in some cases preceded, illicit opioid
use. But importantly, we find both parameters are not
stationary in the opioid-dependent subjects: both parameters
fluctuate as individuals approach and recover from opioid
use events in a way not seen in controls. Both risk and
ambiguity tolerance increases surrounding opioid use, albeit
at different rates.
Conclusions: These data suggest that risk attitudes, which
can be quickly and easily measured by our behavioral tasks,
might be suitable behavioral markers—and perhaps even
predictors—of relapse in opioid addiction. Our ongoing
work seeks to examine the neurobiological basis of this
relationship between risky decision making and drug use.
Based on previous findings in health with these tasks, we
anticipate a common neural mechanism of the risk and
ambiguity parameters to include activation in regions that
form the brain’s valuation network (striatum, ventromedial
prefrontal cortex), and distinct mechanisms to include
activation in the insular cortex (for risk attitudes) and
amygdala (for ambiguity attitudes).
Original languageEnglish (US)
Pages (from-to)S289-S454
JournalNeuropsychopharmacology
Volume41
Issue numberS1
StatePublished - Dec 6 2016

Cite this

Konova, A. B., Lopez-Guzman, S., Urmanche, A., Messinger, J., Polydorou, S., Ross, S., ... Glimcher, P. W. (2016). Week-to-Week Fluctuations in Risky Decision Making Track Heroin Use in Treatment-Seeking Opioid Users. Neuropsychopharmacology, 41(S1), S289-S454.
Konova, Anna B ; Lopez-Guzman, Silvia ; Urmanche, Adelya ; Messinger, John ; Polydorou, Soteri ; Ross, Stephen ; Louie, Kenway ; Rotrosen, John ; Glimcher, Paul W. / Week-to-Week Fluctuations in Risky Decision Making Track Heroin Use in Treatment-Seeking Opioid Users. In: Neuropsychopharmacology. 2016 ; Vol. 41, No. S1. pp. S289-S454.
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abstract = "Background: The degree to which opioid replacementtherapy (e.g., methadone), the gold standard in opioidaddiction management, is effective at reducing illicit opioiduse depends on how well titrated it is for the current needs ofan individual. However, good proximal predictors of whenan individual is at risk for relapse—and therefore in need ofadditional behavioral and/or pharmacological intervention—are currently lacking. Here, we use standard computationallydriven neuroeconomic measurements to decompose the risktaking behavior of opioid users undergoing opioid replacementtherapy, as a way to identify behavioral markers thatmight predict illicit opioid use.Methods: We had individuals starting opioid replacementtherapy (i.e., who were within 4 weeks of treatmentinitiation) perform simple and easy-to-automate monetarydecision making tasks weekly (and then every other week)over several months of treatment. We established when oursubjects returned to illicit opioid (or any drug) use by bothself-report and randomly administered (at least 1/week)urine toxicology tests. A matched sample of drug-freecommunity controls also completed the decision makingtasks. These subjects both served as a baseline control groupas well as allowed us to assess the test-retest reliability of ourmeasurements. A subset of subjects from both groups alsocompleted the tasks while we acquired functional magneticresonance imaging (MRI) data at two time points: once at thebeginning of the treatment and again 8-12 weeks later. Themeasurements we used are based on a standard neuroeconomicmodel that decomposes the behavior of each subjectinto two parameters: “risk attitude” and “ambiguity attitude”,indexing how sensitive that subject is to known andunknown risks, respectively. We computed these parametersfor each subject at each study session, and using generalizedlinear mixed models, we examined how fluctuations in theseparameters related retrospectively and prospectively to illicitopioid use events.Results: We find a high degree of test-retest reliability acrossthe study sessions for both parameters. Attesting to thedistinct aspects of risky decision making captured by theseparameters, we find that only sudden increases in an opioiddependentsubject’s willingness to take risks in our taskcorrelated with, and in some cases preceded, illicit opioiduse. But importantly, we find both parameters are notstationary in the opioid-dependent subjects: both parametersfluctuate as individuals approach and recover from opioiduse events in a way not seen in controls. Both risk andambiguity tolerance increases surrounding opioid use, albeitat different rates.Conclusions: These data suggest that risk attitudes, whichcan be quickly and easily measured by our behavioral tasks,might be suitable behavioral markers—and perhaps evenpredictors—of relapse in opioid addiction. Our ongoingwork seeks to examine the neurobiological basis of thisrelationship between risky decision making and drug use.Based on previous findings in health with these tasks, weanticipate a common neural mechanism of the risk andambiguity parameters to include activation in regions thatform the brain’s valuation network (striatum, ventromedialprefrontal cortex), and distinct mechanisms to includeactivation in the insular cortex (for risk attitudes) andamygdala (for ambiguity attitudes).",
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Konova, AB, Lopez-Guzman, S, Urmanche, A, Messinger, J, Polydorou, S, Ross, S, Louie, K, Rotrosen, J & Glimcher, PW 2016, 'Week-to-Week Fluctuations in Risky Decision Making Track Heroin Use in Treatment-Seeking Opioid Users', Neuropsychopharmacology, vol. 41, no. S1, pp. S289-S454.

Week-to-Week Fluctuations in Risky Decision Making Track Heroin Use in Treatment-Seeking Opioid Users. / Konova, Anna B; Lopez-Guzman, Silvia; Urmanche, Adelya; Messinger, John; Polydorou, Soteri; Ross, Stephen; Louie, Kenway; Rotrosen, John; Glimcher, Paul W.

In: Neuropsychopharmacology, Vol. 41, No. S1, 06.12.2016, p. S289-S454.

Research output: Contribution to journalMeeting Abstract

TY - JOUR

T1 - Week-to-Week Fluctuations in Risky Decision Making Track Heroin Use in Treatment-Seeking Opioid Users

AU - Konova, Anna B

AU - Lopez-Guzman, Silvia

AU - Urmanche, Adelya

AU - Messinger, John

AU - Polydorou, Soteri

AU - Ross, Stephen

AU - Louie, Kenway

AU - Rotrosen, John

AU - Glimcher, Paul W

PY - 2016/12/6

Y1 - 2016/12/6

N2 - Background: The degree to which opioid replacementtherapy (e.g., methadone), the gold standard in opioidaddiction management, is effective at reducing illicit opioiduse depends on how well titrated it is for the current needs ofan individual. However, good proximal predictors of whenan individual is at risk for relapse—and therefore in need ofadditional behavioral and/or pharmacological intervention—are currently lacking. Here, we use standard computationallydriven neuroeconomic measurements to decompose the risktaking behavior of opioid users undergoing opioid replacementtherapy, as a way to identify behavioral markers thatmight predict illicit opioid use.Methods: We had individuals starting opioid replacementtherapy (i.e., who were within 4 weeks of treatmentinitiation) perform simple and easy-to-automate monetarydecision making tasks weekly (and then every other week)over several months of treatment. We established when oursubjects returned to illicit opioid (or any drug) use by bothself-report and randomly administered (at least 1/week)urine toxicology tests. A matched sample of drug-freecommunity controls also completed the decision makingtasks. These subjects both served as a baseline control groupas well as allowed us to assess the test-retest reliability of ourmeasurements. A subset of subjects from both groups alsocompleted the tasks while we acquired functional magneticresonance imaging (MRI) data at two time points: once at thebeginning of the treatment and again 8-12 weeks later. Themeasurements we used are based on a standard neuroeconomicmodel that decomposes the behavior of each subjectinto two parameters: “risk attitude” and “ambiguity attitude”,indexing how sensitive that subject is to known andunknown risks, respectively. We computed these parametersfor each subject at each study session, and using generalizedlinear mixed models, we examined how fluctuations in theseparameters related retrospectively and prospectively to illicitopioid use events.Results: We find a high degree of test-retest reliability acrossthe study sessions for both parameters. Attesting to thedistinct aspects of risky decision making captured by theseparameters, we find that only sudden increases in an opioiddependentsubject’s willingness to take risks in our taskcorrelated with, and in some cases preceded, illicit opioiduse. But importantly, we find both parameters are notstationary in the opioid-dependent subjects: both parametersfluctuate as individuals approach and recover from opioiduse events in a way not seen in controls. Both risk andambiguity tolerance increases surrounding opioid use, albeitat different rates.Conclusions: These data suggest that risk attitudes, whichcan be quickly and easily measured by our behavioral tasks,might be suitable behavioral markers—and perhaps evenpredictors—of relapse in opioid addiction. Our ongoingwork seeks to examine the neurobiological basis of thisrelationship between risky decision making and drug use.Based on previous findings in health with these tasks, weanticipate a common neural mechanism of the risk andambiguity parameters to include activation in regions thatform the brain’s valuation network (striatum, ventromedialprefrontal cortex), and distinct mechanisms to includeactivation in the insular cortex (for risk attitudes) andamygdala (for ambiguity attitudes).

AB - Background: The degree to which opioid replacementtherapy (e.g., methadone), the gold standard in opioidaddiction management, is effective at reducing illicit opioiduse depends on how well titrated it is for the current needs ofan individual. However, good proximal predictors of whenan individual is at risk for relapse—and therefore in need ofadditional behavioral and/or pharmacological intervention—are currently lacking. Here, we use standard computationallydriven neuroeconomic measurements to decompose the risktaking behavior of opioid users undergoing opioid replacementtherapy, as a way to identify behavioral markers thatmight predict illicit opioid use.Methods: We had individuals starting opioid replacementtherapy (i.e., who were within 4 weeks of treatmentinitiation) perform simple and easy-to-automate monetarydecision making tasks weekly (and then every other week)over several months of treatment. We established when oursubjects returned to illicit opioid (or any drug) use by bothself-report and randomly administered (at least 1/week)urine toxicology tests. A matched sample of drug-freecommunity controls also completed the decision makingtasks. These subjects both served as a baseline control groupas well as allowed us to assess the test-retest reliability of ourmeasurements. A subset of subjects from both groups alsocompleted the tasks while we acquired functional magneticresonance imaging (MRI) data at two time points: once at thebeginning of the treatment and again 8-12 weeks later. Themeasurements we used are based on a standard neuroeconomicmodel that decomposes the behavior of each subjectinto two parameters: “risk attitude” and “ambiguity attitude”,indexing how sensitive that subject is to known andunknown risks, respectively. We computed these parametersfor each subject at each study session, and using generalizedlinear mixed models, we examined how fluctuations in theseparameters related retrospectively and prospectively to illicitopioid use events.Results: We find a high degree of test-retest reliability acrossthe study sessions for both parameters. Attesting to thedistinct aspects of risky decision making captured by theseparameters, we find that only sudden increases in an opioiddependentsubject’s willingness to take risks in our taskcorrelated with, and in some cases preceded, illicit opioiduse. But importantly, we find both parameters are notstationary in the opioid-dependent subjects: both parametersfluctuate as individuals approach and recover from opioiduse events in a way not seen in controls. Both risk andambiguity tolerance increases surrounding opioid use, albeitat different rates.Conclusions: These data suggest that risk attitudes, whichcan be quickly and easily measured by our behavioral tasks,might be suitable behavioral markers—and perhaps evenpredictors—of relapse in opioid addiction. Our ongoingwork seeks to examine the neurobiological basis of thisrelationship between risky decision making and drug use.Based on previous findings in health with these tasks, weanticipate a common neural mechanism of the risk andambiguity parameters to include activation in regions thatform the brain’s valuation network (striatum, ventromedialprefrontal cortex), and distinct mechanisms to includeactivation in the insular cortex (for risk attitudes) andamygdala (for ambiguity attitudes).

M3 - Meeting Abstract

VL - 41

SP - S289-S454

JO - Neuropsychopharmacology

JF - Neuropsychopharmacology

SN - 0893-133X

IS - S1

ER -

Konova AB, Lopez-Guzman S, Urmanche A, Messinger J, Polydorou S, Ross S et al. Week-to-Week Fluctuations in Risky Decision Making Track Heroin Use in Treatment-Seeking Opioid Users. Neuropsychopharmacology. 2016 Dec 6;41(S1):S289-S454.