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Can we use brain function to predict the course of cannabis use towards dependence?
Results from a prospective neuroimaging studie
Janna Cousijn
‐ lab, University of Amsterdam, The Netherlands
Amsterdam Institute for Addiction Research, AMC, The Netherlands
Learn about learning, 2013
Outline
• General introduction
• (Neuro)cognitive predictors of future cannabis use
and problem severity
• Discussion
INTRODUCTION PREDICTORS DISCUSSION
Outline
• General introduction
• (Neuro)cognitive predictors of future cannabis use
and problem severity
• Discussion
INTRODUCTION PREDICTORS DISCUSSION
Transition
Sporadic drug use
INTRODUCTION PREDICTORS DISCUSSION
Why do only some individuals become addicted?
• Chronic relapsing disorder characterized by compulsive drug taking
• Imbalance between approach‐oriented motivational system and regulatory executive system
Dual‐process theories of addiction(Evans & Coventry, 2006; Strack & Deutch, 2006: Wiers & Stacy, 2006)
GO
I should STOP
Sensitized and conditioned responses to cues
INTRODUCTION PREDICTORS DISCUSSION
Cannabis addiction? YES!
National Drug Monitor 2009
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Year
Num
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Primary Secondary
Treatment demands increase
INTRODUCTION PREDICTORS DISCUSSION
Outline
• General introduction
• (Neuro)cognitive predictors of future cannabis use
and problem severity
• Discussion
INTRODUCTION PREDICTORS DISCUSSION
INTRODUCTION PREDICTORS DISCUSSION
Addicts and healthy individuals differ in many aspect
Substance use
Genetics
Brain function
Social environment
Potential predictors of addiction
Control
Motivation
Joint roken = belonend
Control
Motivation
Joint zien extreem sterkt verlangen (craving)automatische aandachtautomatische toenadering
CUE
Control
Motivation
Disbalans verslaving
CUE
Control
Motivation
INTRODUCTION PREDICTORS DISCUSSION
Motivation
Cognitive control
• Working‐memory
• Decision making
• Cue‐reactivity
• Attentional bias fast allocation, sustained attention
• Approach bias fast approach responses
• Cue‐induced craving
Can we use neurocognitive processes to predict cannabis use trajectories?
Design
• Heavy cannabis users (n = 33, 18‐25 y)
– Use: > 10 days/month, > 2 year, no treatment
• Controls (n = 42)
INTRODUCTION PREDICTORS DISCUSSION
T 1 T 26 months
T 33 year
‐brain structure‐decision making‐working memory‐cue‐reactivity‐cannabis use‐problems
‐cannabis use‐problems
‐brain structure‐decision making‐working memory‐cue‐reactivity‐cannabis use‐problems
Design
• Heavy cannabis users (n = 33, 18‐25 y)
– Use: > 10 days/month, > 2 year, no treatment
• Controls (n = 42)
INTRODUCTION PREDICTORS DISCUSSION
T 1 T 26 months
T 33 year
‐brain structure‐decision making‐working memory‐cue‐reactivity‐cannabis use‐problems
‐cannabis use‐problems
‐brain structure‐decision making‐working memory‐cue‐reactivity‐cannabis use‐problems
Approach bias
• Relatively automatic tendency to approach rather than avoid
• Possible predictor of drug abuse / dependence?
INTRODUCTION PREDICTORS DISCUSSION
bias = RT avoid – RT approach
Approach‐Avoidance Task(original Rinck & Becker, J Behav Ther Exp Psychiatry 2007)
• Arm flexion and extension: pulling and pushing a joystick
• Irrelevant feature task: respond to format of the picture
• Heavy drinkers faster to approach alcohol (Wiers et al. 2009)
INTRODUCTION PREDICTORS DISCUSSION
• Heavy cannabis users are
faster in approaching
cannabis compared to
controls
• Approach‐bias predicts
escalation of cannabis use
after 6 months
INTRODUCTION PREDICTORS DISCUSSION
• Move a manikin towards or away from cannabis (blocked design)
• Regular cannabis users are faster
in approaching cannabis compared
to controls (Mogg et al. 2006)
• Cannabis approach (neutral avoid) vs.
cannabis avoid (neutral approach)
Stimulus‐Response Compatibility Task (SRC)‐fMRI
INTRODUCTION PREDICTORS DISCUSSION
• No group differences for cannabis approach vs. avoid activity
• Within cannabis users positive correlation lifetime use:
4.0
2.3x = - 2 y = 12 z = 6
INTRODUCTION PREDICTORS DISCUSSION
• DLPFC and ACC predict problem severity after six months
3.5
2.3x = 34 y = 38 z = 32
Monetary decision‐making task
Iowa Gambling task fMRI
INTRODUCTION PREDICTORS DISCUSSION
• Win > loss evaluation in right insula, right caudate and right VLPFC was positively associated with weekly cannabis use
• Disadvantageous > advantageous decisions in frontal pole and middle and superior temporal gyrus was positively associated with change in weekly cannabis use
INTRODUCTION PREDICTORS DISCUSSION
• Working‐memory task (blocked design)
• 3 levels: 0‐back, 1‐back, 2‐back
N‐Back task fMRI
INTRODUCTION PREDICTORS DISCUSSION
0-back 1-back 2-back
AA
YA
ZX
B1-back target
2-back target
0-back target
• Tensor‐ICA analysis (FSL; Beckmann & Smith 2005)
• Individual differences in working‐memory network function predicts escalation in cannabis use after 6 months
INTRODUCTION PREDICTORS DISCUSSION
Integrated model of cannabis use
INTRODUCTION PREDICTORS DISCUSSION
• Both working‐memory network function, the approach‐bias, IGT activations, and craving uniquely explain variance in future cannabis use.
Outline
• General introduction
• (Neuro)cognitive predictors of future cannabis use
and problem severity
• Discussion
INTRODUCTION PREDICTORS DISCUSSION
• Can we use brain function to predict cannabis use? YES
Brain activity: working‐memory, decision‐making
Behavior: Approach‐bias, craving
•Identify individuals at‐risk for the development of a cannabis use disorder
•fMRI assessments add value
•Targeted interventions:
– Approach‐bias retraining (Wiers et al. 2010, 2011)
– Working‐memory training
INTRODUCTION PREDICTORS DISCUSSION
Questions?Dr. Janna Cousijn
Dr. Anneke Goudriaan
Prof. Richard Ridderinkhof
Prof. Reinout Wiers
Prof. Wim van den Brink
Prof. Dick Veltman
INTRODUCTION PREDICTORS DISCUSSION