results from a prospective neuroimaging studie · genetics brain function social environment...
Post on 09-Oct-2020
1 Views
Preview:
TRANSCRIPT
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
j.cousijn@gmail.com
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
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Year
Num
ber
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
top related