1. Imaging the loss of free will in the addicted brain: implications for internet addictions
Anissa Abi-Dargham MD
Professor of Psychiatry,  
Vice Chair of Research
Associate Dean for Clinical and Translational Research
Department of Psychiatry
Stony Brook University
Professor Emerita, Columbia University
New York
Here, please introduce yourself, briefly discussing your background and the company you are representing.

2. Disclosures
Paid Editorial duties: Neuropsychopharmacology and Biological Psychiatry
Member of NPAS study section
Consultant: System 1 Biosciences, Biostorm Sciences
Honoraria for lectures: Otsuka
Advisory Boards: Roche, Sunovion, Otsuka

3. OUTLINE Brain Circuitry relevant to addictions PET Imaging methodology
Alcohol use disorders
Cocaine use disorders
Cannabis
Non dopaminergic effects
Implications for internet gaming

4. OUTLINE Brain Circuitry relevant to addictions PET Imaging methodology
Alcohol use disorders
Cocaine use disorders
Cannabis
Non dopaminergic effects
Implications for internet gaming

5. Glutamate
GABA
Dopamine

6. SM-FC
DLPFC
OFC
Glutamate
GABA
Dopamine

7. SM-FC
DLPFC
Striatum
OFC
Glutamate
GABA
Dopamine

8. SM-FC
DLPFC
Striatum
Pallidum
OFC
Glutamate
GABA
Dopamine

9. SM-FC
DLPFC
Thalamus
Striatum
Pallidum
OFC
Glutamate
GABA
Dopamine

10. SM-FC
DLPFC
Thalamus
Striatum
Pallidum
OFC
Glutamate
GABA
Dopamine

11. DLPFC OFC SM-FC Thalamus Striatum Pallidum VHipp Glutamate Dopamine
GABA
Dopamine

12. DLPFC OFC SM-FC Thalamus Striatum Pallidum VHipp DA Glutamate Dopamine
GABA
Dopamine

13. DLPFC OFC SM-FC Thalamus Striatum Pallidum VHipp DA Glutamate Dopamine
GABA
Dopamine

14. DLPFC OFC SM-FC Thalamus Striatum Pallidum VHipp DA Glutamate Dopamine
GABA
Dopamine

15. DLPFC OFC SM-FC Thalamus Striatum Pallidum VHipp DA
Nigrostriatal
sensorimotor
Nigrostriatal
associative
Thalamus
Striatum
Pallidum
mesolimbic
VHipp
OFC DA
mesocortical
Dopaminergic pathways

16. DLPFC SM-FC Thalamus D1 Striatum D2 Pallidum DA Glutamate OFC GABA
O’Donnnell, SCZ bull, 2011
SM-FC
DLPFC
Thalamus D1 D2
Striatum
OFC
Pallidum
Schultz et al DA
Glutamate
GABA

17. OUTLINE Brain Circuitry relevant to addictions PET Imaging methodology
Alcohol use disorders
Cocaine use disorders
Cannabis
Non dopaminergic effects
Implications for internet gaming

18. PET Neuroreceptor Imaging
Cyclotron
Radiotracer
PET scanning
11C BP
Input function
Modeling Analysis
MRI / PET Registration

19. Imaging the striatal dopaminergic synapse
Presynaptic
Tyrosine hydroxylase
[18F]f-DOPA: synthesis and presynaptic storage
(activity of Aromatic L-amino acid decarboxylase
AADC)
AADC
VMAT
VMAT2 radiotracers: [11C]DTBZ
MAO
COMT
D2 receptor
DAT radiotracer: [123I]BCIT, [11C]PE2I
DAT
Dopamine levels
Rate of radioactivity accumulation or trapping of fdopa in the terminal, assumed to be mostly fdopamine stored in vesicles. Trapping is modeled with compartment model, for irreversible ligands, which measures Kin,
D2 receptor
D2 receptor
Postsynaptic STR medium Spiny neuron 19

20. Imaging synaptic Dopamine
D2 radiotracer
Dopamine
Amphetamine Challenge
Baseline
This is a schematic representation of dopamine synapse (dopamine in red), which stores in vesicles in the presynaptic nerve terminal. The yellow indicates the radioactive tracer for D2 receptors. The purple represents D2 receptors and the green, dopamine transporters.
The image on the left is a schematic representation of a baseline scan of the binding of radiotracer of D2 receptors before amphetamine challenge, and the one on the right represents a second scan showing the radiotracer after amphetamine challenge. The difference between the 2 scans is a decrease in binding of the radiotracer, related to the magnitude of dopamine release.
More dopamine will compete with the radiotracer for binding to the D2 receptor and will displace the radiotracer, resulting in a lower radioactive signal. The amount of displacement indicates the amount of dopamine released after amphetamine challenge.
Reference
Laruelle M et al. Single photon emission computerized tomography imaging of amphetamine-induced dopamine release in drug-free schizophrenic subjects. Proc Natl Acad Sci USA. 1996;93:

21. Correlation between microdialysis and radiotracer displacement
Laruelle et al, SYNAPSE 25:1–14 (1997)

22. Imaging synaptic Dopamine
D2 radiotracer
Dopamine
Alpha-methyl-para-tyrosine
Baseline
This is a schematic representation of dopamine synapse (dopamine in red), which stores in vesicles in the presynaptic nerve terminal. The yellow indicates the radioactive tracer for D2 receptors. The purple represents D2 receptors and the green, dopamine transporters.
The image on the left is a schematic representation of a baseline scan of the binding of radiotracer of D2 receptors before amphetamine challenge, and the one on the right represents a second scan showing the radiotracer after amphetamine challenge. The difference between the 2 scans is a decrease in binding of the radiotracer, related to the magnitude of dopamine release.
More dopamine will compete with the radiotracer for binding to the D2 receptor and will displace the radiotracer, resulting in a lower radioactive signal. The amount of displacement indicates the amount of dopamine released after amphetamine challenge.
Reference
Laruelle M et al. Single photon emission computerized tomography imaging of amphetamine-induced dopamine release in drug-free schizophrenic subjects. Proc Natl Acad Sci USA. 1996;93:

23. D2/3 PET imaging [11C]raclopride [11C]Fallypride / [11C]PHNO
For nearly half a century, since the initial formulation of the dopamine hypothesis, intense research efforts have focused on the role of dopaminergic systems in the pathophysiology and treatment of schizophrenia.1 In its earliest form, the dopamine hypothesis of schizophrenia proposed that the psychotic, also known as “positive,” symptoms were associated with a hyperactivity of dopaminergic transmission.
Initially, evidence to support the dopaminergic hypothesis was primarily pharmacologic, based almost entirely on observations of the opposing pharmacologic activities of dopamine antagonists and agonists. Specifically, it was noted that
antipsychotic drugs acted as dopamine receptor antagonists, and
dopamine agonists, such as amphetamine, induced a psychotic state with symptoms similar to those seen in patients with schizophrenia.
In the early 1980s, this initial pharmacologic evidence for the dopamine hypothesis received additional support from innovative brain-imaging techniques, such as positron emission tomography (PET) and single photon emission computerized tomography (SPECT). For the first time, PET and SPECT techniques allowed researchers to actually measure indices of dopaminergic activity in the living brain.2 Over the past 20 years, continuing improvements in these neuroimaging tools have permitted investigators to correlate various measured neuroreceptor parameters with clinical symptomatology in both drug-free and drug-naïve patients with schizophrenia.
This slide presentation, which is based largely on brain imaging work by researchers at the Division of Division of Functional Brain Mapping, New York State Psychiatric Institute, has 2 goals:
to examine how evidence derived from recent neuroimaging studies can be used to re-examine, and possibly reformulate, the dopamine hypothesis, and
to establish a scientific foundation for the use of antipsychotic medications in schizophrenia.
References
1. Laruelle M, Kegeles LS, Abi-Dargham A. Glutamate, dopamine, and schizophrenia. Ann NY Acad Sci. 2003;1003: ; 2. Laruelle M. Imaging dopamine transmission in schizophrenia: Review and meta-analysis. Q J Nucl Med. 1998;42:
[11C]FLB457
COLUMBIA
TRANSLATIONAL
NEUROSCIENCE
INITIATIVE
COLUMBIA UNIVERSITY
MEDICAL CENTER

24. FUNCTIONALSUBDIVISIONS OF STRIATUM
Post
PUT CA
LIMBIC
ASSOCIATIVE
SENSORIMOTOR
PRECOMMISSURAL
(ANTERIOR)
POSTCOMMISSURAL
(POSTERIOR)

25. OUTLINE Brain Circuitry relevant to addictions PET Imaging methodology
Alcohol use disorders
Cocaine use disorders
Cannabis
Implications for internet gaming

26. Volkow, M.D., Koob, Ph.D.McLellan, N Engl J Med 2016

27. Alcohol dependence is associated with reduced amphetamine-stimulated dopamine release (Martinez et al. Biol Psychiatry 2005) 5 10 15 20 25 *
Healthy Control
Alcohol Dependent
[11C]raclopride displacement (∆V3”)
VENTRAL
STRIATUM
LST
AST
SMST
STR

28. Reductions in D2-R in all Striatal Subregions in Alcohol Dependence*
Baseline [11C]raclopride V3”
Healthy Control
Alcohol Dependent
11.2% 14.6% % %
p = p = p = p = 0.001

29. Amphetamine effect on [11C]FLB 457 BPND
Healthy Controls n=20
Alcohol dependence
N=20
paired t test, * p ≤ 0.01
† p ≤ 0.05
Narendran et al, Am J Psych, In Press

30. DA release is decreased in cocaine dependence predominantly in VST
Martinez et al., AJP 2007, 164:

31. Cannabis cohort I [11C]raclopride/ iv amphetamine
Length of abstinence before PET: 2 weeks - 3 months
Cannabis users:
Mean age of onset (AOO): 18.3 ± 2 y
Mean duration of use: 8.6 ± 7 y
Severity of use (last year): 517± 465 estimated puffs per month
(joints/blunts/bongs)
No history of psychosis
No other significant drug use, no nicotine
517± 465 estimated puffs per month
The number of "puffs" was estimated as in Gray et al. [30], where 1 pipe equals 5 puffs, 1 "joint" equals 10 puffs, 1 "bong" or "bowl" equals 12 puffs, and 1 "blunt" (very large joint, cannabis “cigar”) equals 20 puffs.
Urban et al, Biol Psychiatry, 2012

32. Cannabis cohort I - DA release* *
* : p=0.1, for total AST: p=0.16
Urban et al, Biol Psychiatry, 2012

33. Cannabis cohort I: DA release by age of onset*
*: p = 0.04 when compared to age matched controls, AST: 0.07

34. Cannabis cohort I: age of onset

35. Cannabis cohort II Length of abstinence before PET: 4 days
[11C]PHNO: D2/3 agonist radiotracer, larger signal
No history of psychosis
No other drug use, no nicotine
Van de Giessen et al, Molecular Psychiatry, 2017

36. Cannabis cohort II: DemographicsHC
(N = 12) CD
(N = 11) p
Age
28.3 ± 3.3
28.6 ± 5.1
0.840
Sex (F/M)
4/8
4/7
1.000
Ethnicity (C/AA/Hisp/mixed)
2/6/3/1
2/6/2/1
SES of Participant
40.6 ± 13.4
33.8 ± 10.3
0.192
SES of Parent
43.5 ± 10
41.9 ± 7.3
0.672
Nicotine use
0.000
There were no significant demographic differences between the twogroups. Mean age was between 28 and 29 in both groups. They were well-matched on age, sex, ethinicity, SES of parents and participants and there were no smokers in either group
Independent samples t tests for continuous variables, fisher’s exact for categorical
Ethnicity variable was dichotomized to AA vs. nonAA for between group tests
Van de Giessen et al, Molecular Psychiatry, 2017

37. Cannabis cohort II: results
50%
40%
30%
20%
10% 0%
Displacement [11C]-(+)-PHNO
***
***
***
FILL IN OPEN CIRCLES AND EXAGGERATE MARKERS
Figure: Displacement of [11C]-(+)-PHNO in the striatum and its subregions
STR = full striatum, AST = associative striatum, SMST = sensorimotor striatum, LST = limbic striatum, HC = healthy controls, CD = cannabis dependent subjects. ***p<0.001 CD HC
LST
SMST
AST
STR
Van de Giessen et al, Molecular Psychiatry, 2017

38. Cannabis cohort II: results
Functional impact
Blunted dopamine release capacity in the associative striatum was associated with higher negative symptoms (A) and inattention symptoms (B) in cannabis users and poor probabilistic category learning (C) and working memory (D) in all subjects. Adj HR = adjusted hit rate, PC learning = probabilistic category learning; **p < 0.01, *p < β = standardized β.
In light of deficits in dopamine in this group, and association of dopamine with
Van de Giessen et al, Molecular Psychiatry, 2017

39. Cannabis cohorts I vs II30 25 20 15 10 5
Cannabis use (days/month)
∆BPND in AST (s.d. units relative to controls) -4 -3 -2 -1 1 2 3 4
EXAGGERATE MARKER SIZES
Reconcile results with our earlier study Urban (2012), in which no group differences in striatal ∆BPND was found.
To compare between the current study and the earlier study, taking into account the globally different magnitude of ∆BPND between [11C]raclopride and [11C]-(+)-PHNO, the distance of AST ∆BPND in CD subjects relative to the mean ∆BPND of the HC subjects in each study is expressed in standard deviation units. Here, cannabis use frequency in days per month is plotted against this normalized ∆BPND to demonstrate the relationship between severity of use and amphetamine-induced DA release (R2 = 0.21).
Blue circles () are CD subjects from this study.
Red diamonds () are CD subjects from Urban et al.
∆BPND = 0 represents the HC mean from each study.

40. DLPFC OFC SM-FC Thalamus Striatum Pallidum VHipp DA
Loss of dopamine function in chronic addictions

41. OUTLINE Brain Circuitry relevant to addictions PET Imaging methodology
Alcohol use disorders
Cocaine use disorders
Cannabis
Non dopaminergic effects
Implications for internet gaming

42. MRS studies in alcoholism: focus on GABA and glutamate
A hypothesized mechanism in acute alcohol withdrawal is an imbalance between glutamatergic and GABAergic neurotransmission, which theoretically increases the risk for alcohol withdrawal-related seizures.
Lower glutamate and increased glutamine concentrations in the bilateral ACC in current or past AUD (predate AUD onset, or persist during abstinence). Thoma, NPP 2011
Abstinent AD : higher glutamate concentration in NAcc/VS and ACC, correlated with craving, suggesting that higher glutamate concentrations in early abstinence may predict relapse. Bauer NPP 2013
High brain glutamate concentration in human ACC and rodent mPFC during acute withdrawal. Hermann Biol Psych 2012
Acute ethanol effects during a 1-hour intravenous alcohol administration: GABA decreased 12 % within minutes, while NAA levels decreased gradually by 8 % Gomez, Biol Psych Glutamate decreased (p= 0.019), so possibly the elevations seen with chronic exposure reflect adaptations to ethanol’s acute effects.

43. OUTLINE Brain Circuitry relevant to addictions PET Imaging methodology
Alcohol use disorders
Cocaine use disorders
Cannabis
Non dopaminergic effects
Implications for internet gaming

44. Synaptic/circuitry remodeling
Acute binge:
Chronic stage
Low dopamine
Altered glutamate
Synaptic/circuitry remodeling
High Dopamine
Low Glutamate
Low GABA?
Volkow, M.D., Koob, Ph.D.McLellan, N Engl J Med 2016

45. Summary
There are well know and global alterations in neurobiology and circuitry of brains of substance use disorders patients
The behavioral cycles are similar across all addictions, making it likely that similar brain systems are involved across different addictions
Internet gaming has received less attention and less research: a few studies have shown some indication of low dopamine indices, abnormal connectivity, abnormal metabolism, even potentially MRS changes, but samples are small, suggesting spurious findings, and methods are often non transparent
More research is needed considering the effects are worse in the young developing brain

46. Contributors Many thanks to patients and families who volunteered
Marc Laruelle MD, Mark Slifstein PhD, Roberto Gil, MD Larry Kegeles, MD, PhD, Gordon Frankle MD, Raj Narendran MD, Judy Thompson PhD, Nina Urban MD, Isabelle Boileau PhD, Peter Talbot MD, Jesper Ekelund MD, David Erritzoe MD, Ning Ning Guo PhD, Mette Sinkberj, PhD, Elsmarieke Van de Giessen MD PhD, Olivier Guillin MD, Ragy Girgis, MD, Guillermo Horga, MD Jared Van Snellenberg, PhD, Cliff Cassidy, PhD, Diana Martinez MD, Osama Mawlawi PhD, Jodi Weinstein, MD, Dah-Ren Hwang PhD, Yuying Hwang PhD, Henry Huang PhD, Xiaoyan Xu PhD, Liz Hackett, Najate Ojeil, Greg Perlman PhD
Funding: NIMH, NIDA, BBRF, NIAAA
Many thanks to patients and families who volunteered