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Background: Despite the current shift towards permissive cannabis policies, few studies have investigated the pleasurable effects users seek. Here we investigate the effects of cannabis on listening to music - a rewarding activity that frequently occurs in the context of recreational cannabis use. We additionally tested how these effects are influenced by cannabidiol (CBD), which may offset cannabis-related harms. Methods: Across three sessions, sixteen cannabis users inhaled cannabis with CBD, cannabis without CBD, and placebo. We compared their response to music relative to control excerpts of scrambled sound during functional Magnetic Resonance Imaging (fMRI) within regions identified in a meta-analysis of music-evoked reward and emotion. All results were False Discovery Rate corrected (p<0.05). Results: Compared to placebo, cannabis without CBD dampened response to music in bilateral auditory cortex (right: p=0.005, left: p=0.008), right hippocampus/parahippocampal gyrus (p=0.025), right amygdala (p=0.025) and right ventral striatum (p=0.033). Across all sessions, the effects of music in this ventral striatal region correlated with pleasure ratings (p=0.002) and increased functional connectivity with auditory cortex (right: p=0.000, left: p=0.000), supporting its involvement in music reward. Functional connectivity between right ventral striatum and auditory cortex was increased by CBD (right: p=0.003, left: p=0.030), and cannabis with CBD did not differ from placebo on any fMRI measures. Both types of cannabis increased ratings of wanting to listen to music (p<0.002) and enhanced sound perception (p<0.001). Conclusions: Cannabis dampens the effects of music in brain regions sensitive to reward and emotion. These effects were offset by a key cannabis constituent, cannabidol.
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Received: May 4, 2017; Revised: August 16, 2017; Accepted: August 30, 2017
© The Author 2017. Published by Oxford University Press on behalf of CINP.
International Journal of Neuropsychopharmacology (2017) 00(00): 1–12
Advance Access Publication: September 2, 2017
Regular Research Article
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  
Cannabis Dampens the Effects of Music in Brain
Regions Sensitive to Reward and Emotion
Tom P.Freeman, Rebecca A.Pope, Matthew B.Wall, James A.Bisby,
MaartjeLuijten, ChandniHindocha, ClaireMokrysz, WillLawn, AbigailMoss,
Michael A.P.Bloomeld, Celia J.A.Morgan, David J.Nutt, H. ValerieCurran
Clinical Psychopharmacology Unit, University College London, United Kingdom (Dr Freeman, Dr Pope,
Dr Wall, Ms Hindocha, Dr Mokrysz, Dr Lawn, Ms Moss, Prof Morgan, and Prof Curran); National Addiction
Centre, King’s College London, United Kingdom (Dr Freeman); Imanova Centre for Imaging Sciences, Imperial
College London, Hammersmith Hospital, London, United Kingdom (Dr Wall); Neuropsychopharmacology
Unit, Division of Brain Sciences, Imperial College London, London, United Kingdom (Dr Wall and Prof Nutt);
Institute of Cognitive Neuroscience, University College London, United Kingdom (Dr Bisby); Behavioural
Science Institute, Radboud University, Nijmegen, The Netherlands (Dr Luijten); Psychiatric Imaging Group,
Medical Research Council Clinical Sciences Centre, Hammersmith Hospital, London, United Kingdom (Dr
Bloomeld); Division of Psychiatry, University College London, United Kingdom (Dr Bloomeld); Department of
Psychology, University of Exeter, United Kingdom (Prof Morgan).
Correspondence: Tom Freeman, PhD, National Addiction Centre, King’s College London, UK (
Background: Despite the current shift towards permissive cannabis policies, few studies have investigated the pleasurable
effects users seek. Here, we investigate the effects of cannabis on listening to music, a rewarding activity that frequently
occurs in the context of recreational cannabis use. We additionally tested how these effects are inuenced by cannabidiol,
which may offset cannabis-related harms.
Methods: Across 3 sessions, 16 cannabis users inhaled cannabis with cannabidiol, cannabis without cannabidiol, and placebo.
We compared their response to music relative to control excerpts of scrambled sound during functional Magnetic Resonance
Imaging within regions identied in a meta-analysis of music-evoked reward and emotion. All results were False Discovery
Rate corrected (P < .05).
Results: Compared with placebo, cannabis without cannabidiol dampened response to music in bilateral auditory cortex
(right: P = .005, left: P = .008), right hippocampus/parahippocampal gyrus (P = .025), right amygdala (P = .025), and right ventral
striatum (P = .033). Across all sessions, the effects of music in this ventral striatal region correlated with pleasure ratings
(P = .002) and increased functional connectivity with auditory cortex (right: P < .001, left: P < .001), supporting its involvement
in music reward. Functional connectivity between right ventral striatum and auditory cortex was increased by cannabidiol
(right: P = .003, left: P = .030), and cannabis with cannabidiol did not differ from placebo on any functional Magnetic Resonance
Imaging measures. Both types of cannabis increased ratings of wanting to listen to music (P < .002) and enhanced sound
perception (P < .001).
Conclusions: Cannabis dampens the effects of music in brain regions sensitive to reward and emotion. These effects were
offset by a key cannabis constituent, cannabidol.
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2 | International Journal of Neuropsychopharmacology, 2017
Keywords: cannabis, music, reward, pleasure, emotion
The main psychoactive constituent of cannabis, THC (delta-
9-tetrahydrocannabinol), produces subjective effects such as
feeling “stoned” and can impair memory and elicit transient
psychotic-like symptoms (Curran etal., 2016). Certain types of
cannabis also contain cannabidiol (CBD), which can have oppo-
site effects of THC on a range of functional neuroimaging tasks
(Bhattacharyya etal., 2010; Batalla et al., 2014). Moreover, CBD
has been found to offset harmful effects of THC (e.g., memory
impairment and psychotic-like symptoms) without inuencing
subjective intoxication (Curran etal., 2016; Englund etal., 2017).
Cannabis containing high THC and little if any CBD is becoming
increasingly prevalent (Hardwick and King 2008; ElSohly et al.,
2016) and has been linked to greater mental health and addic-
tion problems compared with less potent varieties of cannabis
(Di Forti etal., 2015; Freeman and Winstock 2015).
Despite the changes currently occurring in cannabis legisla-
tion worldwide, including legalization of use for medicine and
pleasure (Room 2014), few studies have attempted to document
the effects that recreational users seek (Curran etal., 2016). The
limited evidence of positive effects tends to have arisen inciden-
tally in studies investigating cannabis-related harms. For exam-
ple, THC has been reported to increase phonological uency
(Curran etal., 2002), a measure of divergent thinking, especially
among people with low trait creativity (Schafer etal., 2012).
Cannabis has a strong historical link to music and is associated
with several distinct styles, including jazz, reggae, and rock (Booth
2004). Cannabis is reported to enhance appreciation of music (Tart
1970; Green etal., 2003), and its use is consistently high among
people who attend music festivals and nightclubs (Lim etal., 2008;
Van Havere etal., 2011; Palamar etal., 2015). This association may
be partly attributable to shared effects on reward circuitry between
drug and nondrug rewards (Berridge and Kringelbach 2015). Music
recruits key regions in the reward network, including ventral stria-
tum, mediodorsal thalamus, anterior insula, orbitofrontal cortex,
amygdala, and hippocampus (Koelsch 2014).
Many of these reward-related brain regions are character-
ized by a high density of Cannabinoid Type-1 Receptors (CB1Rs)
(Curran etal., 2016). THC is a partial agonist of CB1Rs and may
inuence response to music by interfering with endogenous
CB1R ligands such as anandamide (Thieme etal., 2014), which
plays a causal role in consummatory response to reward (Mahler
et al., 2007). Ahuman neuroimaging study found that THC (a
partial CB1R agonist) dampened the effects of monetary reward
feedback across a widespread network, including temporal and
orbitofrontal cortices, while leaving reward anticipation intact
(van Hell et al., 2012). By contrast, 7-day administration of a
CB1R antagonist was found to diminish response to food reward
in ventral striatum and orbitofrontal cortex (Horder etal., 2010).
Additionally, THC causes modest, regionally selective
increased dopamine release in limbic striatum (Bossong et al.,
2015). Such effects might enhance the rewarding experience
of music, which can also elicit dopamine release in ventral
striatum (Salimpoor et al., 2011) as well as enhancing activa-
tion and connectivity between mesolimbic brain regions (Blood
and Zatorre 2001; Menon and Levitin 2005; Koelsch et al., 2006;
Salimpoor et al., 2011; Trost et al., 2012). Functional connectivity
between ventral striatum and auditory cortex during listening
also predicts the rewarding experience of music (Salimpoor et
al., 2013; Zatorre and Salimpoor 2013; Martínez-Molina et al.,
Here, we conducted the rst controlled experimental study on
the interactive effects of cannabis and music. Based on previous
ndings that cannabis and music activate and increase connec-
tivity between common regions in the reward network, whereas
a CB1R antagonist dampened neural response to reward (Horder
et al., 2010), and observational data linking cannabis use and
music, we hypothesized that cannabis would increase haemo-
dynamic response to music in brain regions sensitive to reward
and emotion (Koelsch 2014) as well as subjective ratings (want-
ing to listen to music, pleasure of listening). Given that CBD and
THC can have opposing neural effects (Bhattacharyya et al.,
2010; Batalla etal., 2014) and CBD can attenuate THC harms
(Curran etal., 2016; Englund etal., 2017), we predicted that these
effects would be partially offset by CBD.
Design and Participants
A randomized, double-blind, crossover design compared can-
nabis with CBD (Cann+CBD), cannabis without CBD (Cann-CBD)
and matched placebo in 16 cannabis users. Experimental ses-
sions were separated by at least 1 week (>3 times the elimina-
tion half-life of THC) to minimize carryover effects (D’Souza
etal., 2004; Hindocha etal., 2015). In addition to the music task
described here, participants completed additional assessments
that are reported elsewhere (Lawn etal., 2016). Inclusion criteria
were uency in English, right-handedness, age between 18 and
70years, and self-reported current cannabis use (≥4 times in the
last year, ≤3 times/wk, ability to smoke a whole joint to oneself).
We did not collect data on participants’ typical method of admin-
istering cannabis. However, previous data from the UK suggest
that the majority (~76%) of cannabis users typically smoke can-
nabis together with tobacco in joints, and only a small minority
(~4%) use a vaporizer as their most common route (Hindocha
etal., 2016). Exclusion criteria were self-reported frequent and/
Signicance Statement
Here, we report that cannabis administration decreased response to music in several brain regions linked to reward and
emotion. These included right ventral striatum, which showed increased functional connectivity with auditory cortex
and correlated with pleasure ratings during musical listening, consistent with its critical role in reward processing.
These effects were offset when cannabis contained cannabidiol, a key cannabinoid that has been found to reduce some
harmful effects of cannabis.
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Freeman et al. | 3
or severe adverse reactions to cannabis, current use of illicit
drugs other than cannabis more than twice per month, cur-
rent alcohol use >4d/wk, signicant physical health problems,
color blindness, current treatment for a psychiatric disorder,
current/history of psychosis, and current/history of psychosis
in an immediate family member. This study was approved by
the UCL ethics committee, and all participants provided written
informed consent.
Following telephone screening, eligible participants completed
a baseline session consisting of task training (outside of the MRI
scanner), video training for drug administration, drug history
(Freeman etal., 2012), and problematic cannabis use on Severity
of Dependence Scale (Gossop etal., 1995). The Beck Depression
Inventory-II (Beck et al., 1996) and Temporal Experiences of
Pleasure (Gard etal., 2006) were also administered. Each experi-
mental session began with a urinary drug screen to verify recent
use reported by Timeline Follow-back (Sobell and Sobell 1992).
Next, 11-point (0–10) Numerical Rating Scales were adminis-
tered ~0 minutes before drug inhalation (Pre-Drug), ~5 minutes
after rst drug administration (Post-Drug), and ~90 minutes
after rst drug administration (Post-Scan). The Numerical
Rating Scales “Want to Listen to Music” and “Enhanced Sound
Perception” were administered at all 3 of these time points; “Feel
Drug Effect,” “Like Drug Effect,” and “Want More Drug” were
administered only after drug administration (Post-Drug and
Post-Scan). Heart rate and systolic and diastolic blood pressure
were also recorded at the same 3 time points (Pre-Drug, Post-
Drug, Post-Scan).
Drug Administration
Cannabis was obtained from Bedrocan, The Netherlands and
used within 6 months of purchase. It was stored on site in
foil-sealed pouches at -20ºC and then at ambient temperature
prior to drug administration. Each dose was vaporized using a
Volcano Medic Vaporizer (Storz and Bickel) at 210ºC in 2 sequen-
tially administered balloons to minimize residual cannabinoids
(Lawn etal., 2016). Participants inhaled at their own pace (each
inhalation held for 8 seconds, enforced by the experimenter
using a stopwatch) until the balloon was empty, which lasted ~5
minutes for both balloons. All participants complied with this
administration protocol. Bedrobinol (12% THC, <1% CBD), Bediol
(6% THC, 7.5% CBD), and placebo cannabis were used to load
doses of 8mg THC + 10mg CBD (Cann+CBD), 8mg THC (Cann-
CBD), and placebo (Lawn etal., 2016). Placebo cannabis had a
comparable terpene prole to the 2 active forms of cannabis,
ensuring it was matched for smell. The same physical quantity
of cannabis/placebo (133.4mg) was administered across each
of the 3 sessions. This dose of THC has produced effects on
brain and behavior in studies with similar vaporizer protocols
(Bossong etal., 2009; Hindocha etal., 2015; Mokrysz etal., 2016)
and is roughly equivalent to one-quarter of a standard UK joint
(Freeman etal., 2014).
Music Task (Menon and Levitin 2005)
Six 21-second excerpts of standard instrumental classical
music were taken from compact disc recordings, adapted from
a previous study (Menon and Levitin 2005). Six scrambled ver-
sions were created by randomly drawing 250- to 350-millisec-
ond variable-sized sections from each piece and concatenating
them with a 30-millisecond linear cross-fade between excerpts
(Menon and Levitin 2005). Scrambled excerpts retain the same
distribution of pitch and loudness and the same spectral infor-
mation as normal music. However, they lack temporal structure
and are rated as less pleasurable than normal excerpts (Menon
and Levitin 2005).
To deliver clear audio during scanning, clips were adapted
to improve volume constancy during sections of low volume.
Output volume was adapted for each participant in the scanner
before the task commenced. Normal/scrambled excerpts were
delivered using PsychoPy (Version 1.79.01) through MR compat-
ible sensimetric earphones (
model-s14/) in a standard blocked fMRI design. The 12 normal/
scrambled excerpts were presented in a pseudo-randomized
order across the 3 test sessions. Each 21-second excerpt was fol-
lowed by a 1-second interstimulus interval. Next, participants
rated the pleasantness of each excerpt using a 2-nger response
pad beneath their right hand (xed time of 8 seconds). The
numerical rating scale was anchored from 0 (not at all pleasant)
to 10 (very pleasant). This was followed by 12 seconds of pas-
sive xation (rest). The total task time was 8 minutes 24 seconds,
plus a 5-second end-buffer period.
fMRI Data Acquisition
Imaging data were collected using a Siemens TIM Avanto 1.5T
scanner, using a 32-channel receive-only head coil, at the
Birkbeck-UCL Centre for Neuroimaging, London. An automated
shim procedure was applied to minimize possible magnetic eld
homogeneities. Functional imaging used a multiband (accelera-
tion factor = 4) gradient-echo T2*-weighted echo-planar imag-
ing (EPI) sequence with 40 slices per volume (TR = 1000 ms;
TE = 55ms; in-plane matrix = 64 x 64; 3mm isotropic voxels; ip
angle = 75°; bandwidth = 1474 Hz/pixel; 509 volumes). The rst 8
scans were treated as “dummy” scans and discarded to avoid
T1-equilibrium effects. All scanning parameters were selected
to optimize the quality of the BOLD signal while maintaining
a sufcient number of slices to acquire whole-brain data. To
co-register the fMRI data into standard space, we also acquired
a MPRAGE structural sequence (TR = 2730 ms; TE = 3.57 ms;
matrix = 176 x 256 x 256; 1-mm isotropic voxels; ip angle = 7°;
bandwidth = 190 Hz/pixel; parallel imaging acceleration fac-
tor = 2), and a B0 eld map image (64 axial slices; TR = 1170 ms;
TE1 = 10.0 ms; TE2 = 14.76 ms; in-plane matrix = 64 x 64; 3 x 3 x
2mm voxels; ip angle = 90°; bandwidth = 260 Hz/pixel) to enable
distortion correction of the functional data.
fMRI Data Analysis
Preprocessing and data analysis were performed using
Statistical Parametric Mapping (SPM8; http://www.l.ion.ucl. Standard preprocessing procedures
consisted of bias correction of EPI images to control for within-
volume signal intensity differences, realignment/unwarping
to correct for interscan movements, correction for differences
in slice acquisition timing, and normalization of the images to
an EPI template specic to our sequence and scanner that was
aligned to the T1 MNI template. Finally, the normalized func-
tional images were spatially smoothed with an isotropic 8-mm
FWHM Gaussian kernel.
At the rst level, the normal and scrambled epochs were
each modelled as a 21-second boxcar convolved with the canon-
ical hemodynamic response function combined with time and
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4 | International Journal of Neuropsychopharmacology, 2017
dispersion derivatives to create the contrast music>scrambled,
as previously used with this task (Menon and Levitin 2005).
The interstimulus interval, rating, and passive xation (rest)
were also modelled. Each subject’s movement parameters were
included as confounds. Low-frequency noise was removed with
a high-pass lter (cut-off frequency 1/128 Hz). Parameter esti-
mates pertaining to the height of the hemodynamic response
function for each regressor of interest were then calculated for
At the second level, the contrast music>scrambled was
entered into a within-subject ANOVA model with a single fac-
tor of drug (Cann+CBD, Cann-CBD, placebo). Within this ANOVA
model, we used t contrasts to investigate music>scrambled and
the reverse contrast (scrambled>music) across all scans. Drug
effects on music>scrambled were conducted using t contrasts
within this ANOVA model. To aid interpretation of signi-
cant drug effects (which could reect changes in response to
music, scrambled, or both), separate parameter estimates were
extracted from these coordinates for the contrasts music>rest
and scrambled>rest using the MarsBaR region of interest tool-
box; these were analyzed using repeated-measures ANOVA
Psychophysiological interaction (PPI) analysis was per-
formed to assess task-related functional connectivity (O’Reilly
etal., 2012) using seed regions identied by drug effects. We
extracted the representative time-course from voxels in the
seed region (6-mm radius sphere) using the rst eigenvari-
ate calculated from singular value composition. This time
course (physiological) was entered into a General Linear Model
together with the contrast music>scrambled (psychological)
and their interaction (PPI). Motion parameters were included in
rst-level models as nuisance regressors. The PPI regressor was
analyzed using a within-subject ANOVA. We used t contrasts
to investigate PPI effects across all scans and to compare drug
A False Discovery Rate correction (P < .05) was applied to all
fMRI analyses. Regions of interest were dened from a previ-
ous meta-analysis of music-evoked reward and emotion (see
Figure1 and supplementary Table1 in Koelsch 2014) using the
MarsBaR toolbox. Firstly, each of the structures identied in the
meta-analysis was converted into a single sphere. Coordinates
were converted to MNI using the Yale BioImage Suite (Lacadie
etal., 2008). Sphere radius was estimated from the cluster size
reported in the meta-analysis. Where clusters contained mul-
tiple structures, size was determined using the cluster mean.
Subthreshold clusters were assigned a default size of 200mm3.
Each of these spheres was combined into a single mask that
was applied to second-level analysis. This mask (41 240mm3)
included bilateral hippocampal formation, bilateral amygdala,
bilateral auditory cortex, right ventral striatum, left caudate
nucleus, presupplementary motor area, frontomedian cortex,
rostral cingulate zone, pre-genual and middle cingulate cortex,
medial and laterial orbitofrontal cortex, right anterior insula,
mediodorsal thalamus, and superior parietal lobule.
Behavioral Data Analysis
SPSS version 21 was used to analyze all behavioral data and
parameter estimates extracted posthoc using MarsBaR. Outliers
(>3 times IQR) were winsorized within each session and time
point. Histograms were used to investigate normality, and
square root or log transformations were applied where appro-
priate. Trait measures (BDI, Temporal Experiences of Pleasure,
SDS, and drug history) were missing for one participant. Missing
data from experimental sessions (0.69% of Numerical Rating
Scale data, 0.69% of cardiovascular data) were imputed with the
mean for that session and time point to retain each participant
in the repeated-measures analysis. Repeated-measures ANOVA
models were used for all data collected on the 3 experimental
sessions, including within-subject factors of drug (Cann+CBD,
Cann-CBD, placebo) and time (Pre-Drug, Post-Drug, Post-Scan)
or (Post-Drug, Post-Scan) and additional factors where appro-
priate. Posthoc pairwise tests were Bonferroni-corrected locally
within each ANOVA model. Additional repeated-measures
ANOVA models were used to aid interpretation of interactions
where appropriate. The Greenhouse-Geisser correction was
applied where assumptions of sphericity were violated, with
degrees of freedom rounded to the nearest integer. To reduce
type Iand type II error rates, correlations with fMRI data were
collapsed across each of the sessions using mixed effects mod-
els, with a Bonferroni-adjusted α threshold. These accounted for
xed effects of drug and session order, with a random intercept
of participant and maximum likelihood estimation. Equivalent
mixed effects models were used to assess possible confound-
ing by cardiovascular measures, cannabis use, and session order.
Seventeen participants completed the study. One participant
was excluded due to excessive head movement on one session
(exceeding thresholds for both translation [>6mm] and rotation
[>6º]) and was replaced, leaving a nal sample of 16. Demographic
and drug use data are shown in Table 1. The following num-
ber of participants completed each treatment order: Placebo,
Cann+CBD, Cann-CBD: n = 3; Placebo, Cann-CBD, Cann+CBD:
n = 2; Cann+CBD, Placebo, Cann-CBD: n = 3; Cann+CBD, Cann-
CBD, Placebo: n = 3; Cann-CBD, Placebo, Cann+CBD: n = 2; Cann-
CBD, Cann+CBD, Placebo: n = 3.
Behavioral Results
Subjective Effects
Subjective effects are shown in Figure2 . A main effect of drug
(F1,22 = 107.659, P < .001, ηp
2 = 0.878) emerged for Feel Drug Effect,
reecting increased scores following Cann+CBD (P < .001) and
Cann-CBD (P < .001) compared with placebo, but no differences
between Cann+CBD and Cann-CBD (P = 1.000). There was also
a main effect of time, indicating that scores decreased from
Post-Drug to Post-Scan (F1,15 = 19.057, P < .001, ηp
2 = 0.560), but
there was no evidence for an interaction between drug and
time (F2, 30 = 0.796, P = .461, ηp
2 = 0.050). Like Drug Effect showed
a similar prole of results. There was a main effect of drug
(F2,30 = 44.371, P < .001, ηp
2 = 0.747), reecting increased scores fol-
lowing Cann+CBD (P < .001) and Cann-CBD (P < .001) compared
with placebo but no difference between Cann + CBD and Cann-
CBD (P = 1.000). There was also a main effect of time, indicating
that scores decreased from Post-Drug to Post-Scan (F1,15 = 19.454,
P < .001, ηp
2 = 0.565). Again, there was no evidence for an inter-
action between drug and time (F2,30 = 0.589, P = .561, ηp
2 = 0.038).
For Want More Drug, there was no evidence for any effects or
interactions: drug by time (F2,30 = 2.462, P = .102, ηp
2 = 0.141), drug
(F2,30 = 1.329, P = .280, ηp
2 = 0.081), or Time (F1,15 = 0.388, P = .543,
2 = 0.025).
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Freeman et al. | 5
Cardiovascular Effects
Cardiovascular effects are shown in Figure 2. For heart rate
(BPM), a drug by time interaction emerged (F2,28 = 18.243, P < .001,
2 = 0.549) as well as main effects of both drug (F2,30 = 13.999,
P < .001, ηp
2 = 0.483) and time (F2,30 = 45.977, P < .001, ηp
2 = 0.754).
Heart rate increased from Pre-Drug to Post-Drug following
Cann+CBD (P < .001) and Cann-CBD (P < .001) but not placebo
(P = .456). It then decreased from Post-Drug to Post-Scan for
both Cann+CBD (P < .001) and Cann-CBD (P < .001) but did not
change on placebo (P = 1.000). When comparing the 2 types of
cannabis alone, there were no differences between the effects of
Cann+CBD and Cann-CBD on heart rate across the 3 time points
(drug by time interaction: F2,30 = 0.123, P = .885, ηp
2 = 0.008; main
effect of drug: F1,15 = 0.090, P = .768, ηp
2 = 0.006, main effect of time:
F2,30 = 87.391, P < .001, ηp
2 = 0.854). For systolic blood pressure, a
main effect of drug was found (F2,30 = 6.297, P = .005, ηp
2 = 0.296).
This reected increased blood pressure for both Cann+CBD
(P = .030) and Cann-CBD (P = .006), compared with placebo, but
no differences between Cann+CBD and Cann-CBD (P = 1.000).
There was no evidence for an interaction between drug and
Figure1. Subjective effects. Both types of cannabis increased ratings for (A) Feel Drug Effect and (B) Like Drug Effect but did not inuence (C) Want More Drug.
Cann + CBD, cannabis with cannabidiol (CBD); Cann-CBD, cannabis without CBD. ***P < .001.
Figure2. Cardiovascular effects. Both types of cannabis increased (A) heart rate and (B) systolic blood pressure. (C) Diastolic blood pressure increased from Pre- to Post-
Drug following cannabis without cannabidiol (CBD), but not following cannabis with CBD; Cann + CBD, cannabis with CBD; Cann-CBD, cannabis without CBD; *P < .05,
***P < .001; Difference between cannabis types.
Figure3. Subjective music ratings. (A) Both types of cannabis increased ratings of Want to Listen to Music. (B) Both types of cannabis increased scores for Enhanced
Sound Perception and this increase was greater for cannabis with cannabidiol (CBD). (C) Neither type of cannabis inuenced the pleasure of listening to music or
scrambled sound clips. Cann + CBD, cannabis with CBD; Cann-CBD, cannabis without CBD. ***P < .001; Difference between cannabis types.
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6 | International Journal of Neuropsychopharmacology, 2017
time (F4,60 = 0.953, P = .440, ηp
2 = 0.060) or a main effect of time
(F2,30 = 2.641, P = .088, ηp
2 = 0.150). For diastolic blood pressure,
an interaction between drug and time was found (F4,60 = 3.217,
P = .019, ηp
2 = 0.177) and a main effect of time (F2,30 = 7.702, P = .002,
2 = 0.339) but not drug (F2,30 = 2.975, P = .066, ηp
2 = 0.165). Diastolic
blood pressure increased from Pre-Drug to Post-Drug for Cann-
CBD (P < .001) but not Cann+CBD (P = .233) or placebo (P = 1.000).
It then increased from Post-Drug to Post-Scan following placebo
(P = .030) but not Cann-CBD (P = 1.000) or Cann+CBD (P = 1.000).
Subjective Music Ratings
Subjective music ratings are shown in Figure 3. For Want to
Listen to Music, we found a drug by time interaction (F4,60 = 5.256,
P = .001, ηp
2 = 0.259) and main effects of drug (F2,30 = 5.664, P = .008,
2 = 0.274) and time (F1,22 = 6.300, P = .012, ηp
2 = 0.296). Scores
increased from Pre-Drug to Post-Drug following Cann+CBD
(P < .001) and Cann-CBD (P = .002) but not placebo (P = 1.000).
Scores then decreased from Post-Drug to Post-Scan on Cann+CBD
(P = .028), but these tests did not reach signicance for Cann-
CBD (P = .553) or placebo (P = .199). However, analysis of all three
drug conditions suggested that the decrease in Want to Listen
to Music from Post-Drug to Post-Scan was equivalent across
the 3 sessions (drug by time interaction: F1,21 = 1.130, P = .321,
2 = 0.070; main effect of drug: F2,30 = 9.158, P = .001, ηp
2 = 0.379,
main effect of time: F1,15 = 7.164, P = .017, ηp
2 = 0.323). Moreover,
when comparing the 2 types of cannabis alone, there were no
differences between the effects of Cann+CBD and Cann-CBD on
Want to Listen to Music across the 3 time points (drug by time
interaction: F2,30 = 0.804, P = .457, ηp
2 = 0.051; main effect of drug:
F1,15 = 3.590, P = .078, ηp
2 = 0.193, main effect of time: F2,30 = 8.251,
P = .001, ηp
2 = 0.355).
For Enhanced Sound Perception, Pre-Drug scores were
removed from analysis due to oor effects on each session. Mean
(SD) values were 0.25 (0.45) on placebo, 0.00 (0.00) on Cann+CBD,
and 0.00 (0.00) on Cann-CBD. Analysis of variance was there-
fore restricted to 2 time points (Post-Drug, Post-Scan). Amain
effect of drug (F2,30
= 44.810, P < .001, ηp
= 0.749) reected increased
scores from placebo following Cann+CBD (P < .001) and Cann-
CBD (P < .001) and higher scores following Cann+CBD compared
with Cann-CBD (P = .015). There was no evidence for an interac-
tion between drug and time (F2,30
= 2.056, P = .146, ηp
= 0.121) or a
main effect of time (F1,15
= 1.248, P = .281, ηp
= 0.077). Finally, we
analyzed trial-by-trial pleasure ratings, recorded immediately
after listening to classical music and scrambled sound excerpts
during MRI scanning. There was a main effect of excerpt
= 133.860, P < .001, ηp
= 0.899), indicating that music was rated
as more pleasant than scrambled sound. However, there was no
evidence for a main effect of drug (F2,30
= 1.205, P = .314, ηp
= 0.074)
or a drug by excerpt interaction (F2,30
= 1.221, P = .309, ηp
= 0.075).
Next, we calculated a pleasure rating score (music>scrambled)
equivalent to our fMRI contrast of interest to provide compa-
rable metrics for brain and behavior. Mean (SD) pleasure rating
scores were 5.16 (2.27) for Cann+CBD, 4.78 (2.03) for Cann-CBD,
and 5.53 (1.99) for placebo. Analysis of these scores provided no
evidence for an effect of drug (F2,30
= 1.221, P = .309, ηp
= 0.075).
fMRI Results
Main Effect ofTask
All fMRI analyses were conducted among regions of inter-
est selected from a meta-analysis of previous studies (Koelsch
2014). Across all sessions, listening to music elicited activation
in bilateral amygdala, bilateral striatum, left hippocampus, and
left cingulate gyrus (see Table2). For completion, we also exam-
ined the reverse contrast (scrambled>music), which revealed
activation in bilateral auditory cortex (see Table2).
Drug Effects
Response to music>scrambled was greater on placebo com-
pared with Cann-CBD in bilateral auditory cortex, right hip-
pocampus/parahippocampal gyrus, right ventral striatum, and
right amygdala (see Table2 and Figure4). There was no evidence
for any differences when comparing Cann+CBD with placebo or
Cann+CBD with Cann-CBD.
To aid interpretation of these ndings (which may have been
driven by drug effects on music, scrambled sound, or both), we
extracted parameter estimates from each of the clusters iden-
tied in this drug effect (Table 2, bottom panel) for separate
contrasts of music>rest and scrambled>rest. ANOVA revealed
an interaction between drug (placebo, Cann-CBD) and contrast
(music>rest, scrambled>rest) (F1,15
= 37.851, P < .001, ηp
= 0.716).
This interaction indicated that relative to placebo, Cann-CBD
decreased parameter estimates for music>rest (P = .009, mean
difference -0.195, standard error 0.065). However, there was no
evidence for drug effects on scrambled>rest (P = .130, mean dif-
ference 0.103, standard error 0.064). There were no other ndings
involving drug (drug by contrast by region interaction: F4,60
= 0.687,
P = .604, ηp
= 0.044; drug by region interaction: F4,60
= 0.919, P = .459,
= 0.058; main effect of drug: F1,15
= 0.585, P = .456, ηp
= 0.038).
This suggests that Cann-CBD dampened response to music to a
similar extent across each of these regions (right auditory cor-
tex, left auditory cortex, right hippocampus/parahippocampal
gyrus, right ventral striatum, and right amygdala) while having
negligible effects on response to scrambled sound.
Brain-Behavior Correlations
Next, we sought to examine correlations between brain
(music>scrambled, extracted from the 5 clusters shown in
Table1. Demographic and Drug Use Data
frequency SD
Age 26.25 7.35
Gender (male/female) 8/8 -
Days of cannabis use per month 8.06 5.48
Years of cannabis use 8.94 7.02
Days since last cannabis use 19.25 45.28
Days to smoke 3.5g cannabis 25.88 33.73
Severity of dependence scale (cannabis) 1.13 1.26
Alcohol use (yes/no) 16/0 -
Days of alcohol use per month 10.81 4.86
Number of UK alcohol units (8g) per
5.93 2.08
Current tobacco use (yes/no) 15/1 -
Days of tobacco use per month 11.30 10.27
Cigarettes per day 3.63 3.62
Current MDMA use <twice a month (yes/
6/10 -
Current cocaine use <twice a month (yes/
3/13 -
Current ketamine use <twice a month
2/14 -
Beck Depression Inventory-II 3.38 3.12
Temporal experiences of pleasure
42.06 4.85
Temporal experiences of pleasure
43.50 5.61
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Freeman et al. | 7
the bottom panel of Table 2) and behavior (pleasure ratings
for music>scrambled, Post-Drug Want to Listen to Music and
Enhanced Sound Perception). Data were combined across
all sessions to minimize type I and type II error using mixed
effects models, resulting in a total of 15 correlations. One cor-
relation reached statistical signicance. This showed a positive
Table 2. MNI Coordinates for the Contrasts Music>Scrambled (Main Effect of Task, Top Panel) and Scrambled>Music (Main Effect of Task, Middle
Panel) across All Sessions. The bottom panel shows brain regions in which participants’ response to music>scrambled was dampened follow-
ing cannabis without CBD compared with placebo; +: additional peak within cluster. All P values are thresholded at P < .05 (FDR-corrected for
multiple comparisons)
x y Z mm3
Main effect of task (music>scrambled)
L Caudate -12 6 6 540 4.45 .006
L Amygdala -15 -3 -15 486 4.32 .006
L Hippocampus -18 -12 -18 + 3.59 .027
R Caudate/thalamus 9 3 6 594 3.91 .014
R Pallidum 15 -3 -6 54 3.33 .031
L Cingulate gyrus -6 -15 42 27 3.16 .035
R Amygdala 18 -3 -18 54 2.99 .040
Main effect of task (scrambled>music)
R Planum temporale 60 -12 3 3834 6.61 <.001
R Planum temporale 54 -24 6 + 6.54 <.001
L Planum temporale -48 -33 9 2511 6.16 <.001
L Heschls gyrus -42 -24 3 + 5.26 <.001
Drug effect (placebo>cannabis without CBD)
R Superior temporal gyrus 51 -27 6 2484 4.51 .005
R Planum temporale 60 -12 3 + 3.55 .016
R Planum temporale/heschls gyrus 42 -18 0 + 3.15 .026
L Planum temporale -42 -33 9 972 4.04 .008
R Hippocampus/parahippocampal gyrus 33 -18 -24 81 3.23 .025
R Amygdala 27 3 -27 27 3.19 .025
R Ventral striatum 15 15 -12 54 2.90 .033
Figure4. Cannabis without cannabidiol (CBD) dampened brain response to music across several regions sensitive to music-evoked reward and emotion. (A) Bilateral
auditory cortex activation clusters visualized on the cortical surface of a standard template (MNI152). (B) Aventral view of the same template showing right-hemi-
sphere amygdala and hippocampal clusters. (C) Axial slice views of the same contrast showing amygdala, hippocampal, ventral striatal (top row), and auditory cortex
(bottom row) activation clusters. All activation maps thresholded at P < .05 (FDR corrected for multiple comparisons). A, anterior; L, left hemisphere; P, posterior; R, right
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8 | International Journal of Neuropsychopharmacology, 2017
relationship between pleasure ratings and response to music
in right ventral striatum (F1,34
= 11.447, P = .002; Figure 5). The
same relationship was found using a Pearson correlation analy-
sis across all scans (r = 0.463, P = .001). This correlation did not
contain any outlying values (all data points were <3 times the
interquartile range). However, there was still evidence for a cor-
relation after excluding the 2 data points showing the highest
and lowest right ventral striatum response to music (mixed
effects model: F1,41
= 4.438, P = .041; Pearson correlation analysis
r = 0.318, P = .032).
Functional Connectivity
Previous research has shown that the rewarding experience of
music is predicted by increased functional connectivity between
right ventral striatum and auditory cortex (Salimpoor etal., 2013;
Zatorre and Salimpoor 2013; Martínez-Molina etal., 2016). To test
this, we conducted PPI analyses. These analyses were conducted
posthoc, informed by our ndings that Cann-CBD blunted partic-
ipants’ response to music in right ventral striatum and auditory
cortex. Within-subjects ANOVA revealed that across all sessions,
the right ventral striatum region (15, 15, -12) identied in our
analysis showed a robust increase in functional connectivity with
bilateral auditory cortex (and to a lesser extent, right caudate)
during music relative to scrambled sound (Table3). For comple-
tion, we conducted the reverse contrast. However, we found no
evidence for any regions showing reduced connectivity with this
region during music relative scrambled sound. Next, we exam-
ined drug effects using t contrasts. Compared with Cann-CBD,
greater functional connectivity occurred on Cann+CBD between
right ventral striatum and bilateral auditory cortex (Table 3;
Figure6). We also conducted a PPI analysis using an auditory cor-
tex seed (right superior temporal gyrus 51, -27, 6). However, this
PPI analysis did not identify any regions that showed increases
in functional connectivity with the seed region.
Possible Confounding
Cardiovascular Drug Effects
We conducted correlations between all Post-Drug cardiovascu-
lar measures (heart rate, systolic and diastolic blood pressure)
and the 9 clusters showing evidence of drug effects (see Tables
2 and 3) across all sessions (total 27 correlations). We found no
evidence for any association between cardiovascular and fMRI
data (all P > .05).
We also explored correlations between levels of cannabis of use
and our main ndings. These were conducted between (1) years
of cannabis use, (2) days of cannabis use per month and the 9
clusters showing evidence of drug effects (Tables 2 and 3), Want
to Listen to Music (Post-Drug), Enhanced Sound Perception (Post-
Drug), and pleasure rating scores. Of the 24 correlations, we found
Table 3. Functional Connectivity Analysis. MNI coordinates showing increased functional connectivity with right ventral striatum for
music>scrambled across all sessions (main effect, top panel). Functional connectivity between right ventral striatum and auditory cortex
increased on cannabis with CBD compared with cannabis without CBD (drug effect, bottom panel); +Additional peak within cluster. All P values
are thresholded at P < .05 (False Discovery Rate-corrected for multiple comparisons)
X y z mm3ZP
Main effect
R Planum temporale 60 -12 6 5319 6.43 <.001
R Heschls gyrus/planum polare 48 -12 0 + 6.42 <.001
R Planum temporale 48 -27 9 + 6.26 <.001
L Heschls gyrus -42 -24 12 3429 6.31 <.001
L Planum temporale -42 -30 6 + 6.27 <.001
L Planum temporale -33 -33 15 + 5.48 <.001
R Caudate 9 15 9 54 2.42 .037
Drug effect (cannabis with CBD>cannabis without CBD)
R Heschls gyrus 42 -18 9 1620 4.63 .003
L Hippocampus -30 -18 -21 81 3.64 .009
L Heschls gyrus -36 -27 9 54 3.08 .030
L Heschls gyrus -45 -24 15 27 3.05 .031
Figure 5. Correlation between brain and behavior. (A) Axial slice of right ventral striatal region of interest, identied from voxelwise analysis. (B) Sagittal slice of the
same region. (C) Across all scans, activation in right ventral striatum for the contrast music>scrambled correlated positively with pleasure ratings.
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Freeman et al. | 9
no evidence for any associations (all P > .05) apart from a trend
negative correlation between years of cannabis use and functional
connectivity between right ventral striatum and left hippocampus
(F1,48 = 4.984, P = .030). However, this did not reach signicance at a
Bonferroni-corrected threshold (α = 0.0021). Moreover, the effect of
drug remained signicant in this model (F1,48 = 7.455, P = .002).
Order Effects
Because the same music and scrambled sound excerpts were
presented across each of the 3 sessions, we investigated pos-
sible order effects. For all fMRI results showing drug effects, the
effect of drug remained signicant, and there was no evidence
for an effect of session order (all P > .05). There was no evidence
for effects of drug or session order for pleasure rating scores
(all P > .05). Analysis of Want to Listen to Music (Post-Drug) and
Enhanced Sound Perception (Post-Drug) scores showed effects
of drug (both P < .001) but not session (both P > .05).
To our knowledge, this is the rst controlled experiment inves-
tigating the interactive effects of cannabis and music. Cannabis
dampened response to music in several regions implicated in
music-evoked reward and emotion (Koelsch 2014): bilateral audi-
tory cortex, right amygdala, right hippocampus/parahippocam-
pal gyrus, and right ventral striatum. Across all scans we found
a positive correlation between response to music in this ventral
striatal region and the pleasure of listening to the same sound
clips, consistent with several studies implicating the ventral stri-
atum in musical pleasure (Blood and Zatorre 2001; Koelsch et al.,
2006; Salimpoor et al., 2011; Trost et al., 2012). The same ventral
striatal region showed increased task-related functional connec-
tivity with bilateral auditory cortex, an effect that has previously
been shown to predict musical reward value (Salimpoor et al.,
2013; Zatorre and Salimpoor 2013; Martínez-Molina et al., 2016).
These ndings were contrary to our prediction that cannabis
would increase the rewarding effects of music, which can acti-
vate and increase connectivity within mesolimbic brain regions
(Blood and Zatorre 2001; Menon and Levitin 2005; Koelsch et al.,
2006; Salimpoor et al., 2011; Trost et al., 2012) and, in common
with THC, may increase striatal dopamine release (Salimpoor et
al., 2011; Bossong et al., 2015). Moreover, observational data sug-
gests that cannabis is frequently used in the context of music
and may enhance its effects (Tart 1970; Green et al., 2003; Lim et
al., 2008; Van Havere et al., 2011; Palamar et al., 2015).
One possible explanation for our ndings is that THC inter-
fered with the endocannabinoid system, which plays a critical
role in reward processing (Parsons and Hurd 2015). For example,
acute THC may deplete the CB1R ligand anandamide (Thieme
etal., 2014), which increases consummatory response to reward
in the nucleus accumbens shell (Mahler etal., 2007). Disruption
of the endocannabinoid system could explain why neural
response to reward was previously dampened by 7-day admin-
istration of a CB1R antagonist (Horder etal., 2010) as well as a
single dose of the partial CB1R agonist THC (van Hell etal., 2012).
It should also be noted that our ndings of dampened response
to music occurred in the context of increased wanting to listen
to music. These ndings are broadly consistent with previous
ndings that THC may have dissociable effects on anticipatory
(“wanting”) and consummatory (“liking”) components of reward
(van Hell et al., 2012; Jansma et al., 2013), although our task
lacked a neural index of reward anticipation.
Cannabis with CBD did not differ from placebo on any fMRI
measures. Furthermore, it resulted in greater task-related func-
tional connectivity between ventral striatum and auditory
cortex compared with cannabis without CBD. These ndings
suggest that CBD was able to offset some effects of THC, consist-
ent with previous research (Curran etal., 2016; Englund et al.,
2017) and evidence that THC and CBD can have opposite neu-
ral effects (Bhattacharyya etal., 2010; Batalla etal., 2014). For
example, activation in right superior temporal gyrus (a region
identied in our study) during word listening relative to rest was
previously found to be decreased by THC but increased by CBD
(Winton-Brown etal., 2011). Moreover, CBD may increase con-
centrations of anandamide (Bisogno etal., 2001; Leweke etal.,
2012). We found some evidence that CBD interacted with THC
on additional measures. Taken together, CBD appeared to par-
tially offset some negative effects of THC (increase in diastolic
blood pressure, decreased response to music) while preserv-
ing or potentiating desirable ones (enhanced sound perception,
Figure 6. Functional connectivity analysis. (A) Seed region in right ventral striatum. (B) This seed region showed increased task-related functional connectivity with
bilateral auditory cortex following cannabis with cannabidiol (CBD) compared with cannabis without CBD (C). Axial slices depicting the same data in bilateral auditory
cortex and additional left hippocampal cluster. All activation maps visualized on MNI152 and thresholded at P < .05 (FDR corrected for multiple comparisons). L, left
hemisphere; R, right hemisphere.
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10 | International Journal of Neuropsychopharmacology, 2017
functional connectivity with ventral striatum during musical
In terms of clinical implications, the effects of acute can-
nabis administration here are similar to previous ndings in
people with depression, who also show a blunted response to
music in ventral striatum as well as medial orbitofrontal cortex
(Osuch etal., 2009). In this respect, acute cannabis administra-
tion may transiently mimic the diminished response to reward
characteristic of some mental health disorders. The impact of
chronic cannabis administration remains unclear. However, a
4-year prospective study found that increased cannabis use
was associated with subsequent reductions in ventral striatal
response to reward anticipation (Martz etal., 2016). It there-
fore is possible that effects of cannabis on reward processing
may contribute to an increased risk of developing depression
(Zhang etal., 2013; Lev-Ran etal., 2014) as well as other disor-
ders characterized by reward dysfunction such as addiction and
psychosis (Radua etal., 2015; Luijten etal., 2017). Moreover, our
ndings support the potential utility of CBD in reducing can-
nabis harms while maintaining the positive effects users seek
(Englund etal., 2017).
Strengths of this study include its controlled experimen-
tal design, comparison of cannabis with and without CBD (but
matched for THC), a music task previously validated using fMRI
(Menon and Levitin 2005), and regions of interest informed by
meta-analysis (Koelsch, 2014). Our sample size was equivalent
or larger than previous studies with comparable designs (van
Hell et al., 2012; Jansma et al., 2013) and neuroimaging music
studies of music (mean n = 14.5 across 22 studies (Koelsch
2014)). We used a xed set of classical music excerpts, com-
mensurate with previous use of this task (Menon and Levitin,
2005) and many other studies (Koelsch, 2014). Advantages of
this approach include the absence of lyrics (which would inu-
ence neural response due to speech) and ease of comparison
with existing data. Although participants rated classical sound
clips as highly pleasant (~7.5 of 10), results may have differed if
preferred music was preselected by participants (Osuch et al.,
2009). Drug order was not completely balanced in this study,
and the same sound clips were presented on each of the 3 ses-
sions. However, we found no evidence that session order inu-
enced our results. We screened for personal/family history of
psychosis and current treatment for a psychiatric disorder,
but not for lifetime history of other mental health problems.
Additionally, our sample were cannabis users, which may have
prolonged cannabinoid clearance between sessions. However,
we found minimal evidence for associations between cannabis
use and fMRI ndings, and their response to cannabinoids may
be more representative of typical use than healthy volunteers
who never use cannabis.
In conclusion, cannabis dampened the effects of music in
bilateral auditory cortex, right hippocampus/parahippocampal
gyrus, right amygdala, and right ventral striatum. During musi-
cal listening, this ventral striatal region correlated with pleas-
ure ratings and showed increased functional connectivity with
auditory cortex. By contrast, cannabis containing cannabidiol
did not inuence the effects of music in brain regions sensitive
to reward and emotion.
T.P.F.was funded by the UK Medical Research Council and a Senior
Academic Fellowship from the Society for the Study of Addiction.
This study was funded by Drug Science/Channel 4 television.
These data were presented in preliminary form at the CINP
World Congress in Seoul, South Korea, the BAP Summer Meeting
in Brighton, UK, and the ECNP Workshop for Junior Scientists
in Nice, France. We are grateful to Marty Sereno, Joseph Devlin,
and the Birkbeck-UCL Centre for Neuroimaging team for their
Statement of Interest
H.V.C.is a member of UK MRC boards and Drug Science. D.J.N.is
an advisor to the British National Formulary, MRC, GMC,
Department of Health; President of European Brain Council; Past
President of British Neuroscience Association and European
College of Neuropsychopharmacology, Chair of Drug Science
(UK); Member of International Centre for Science in Drug Policy;
advisor to Swedish government on drug, alcohol, and tobacco
research; editor of the Journal of Psychopharmacology; mem-
ber of advisory boards of Lundbeck, MSD, Nalpharm, Orexigen,
Shire, MSD; has received speaking honoraria (in addition to
above) from BMS/Otsuka, GSK, Lilly, Janssen, Servier, AZ, and
Pzer; is a member of the Lundbeck International Neuroscience
Foundation; has received grants or clinical trial payments from
P1vital, MRC, NHS, Lundbeck, RB; has share options in P1vital;
has been an expert witness in a number of legal cases relat-
ing to psychotropic drugs; and has edited/written 27 books,
some purchased by pharma companies. C.J.A.M.has consulted
for Janssen and GlaxoSmithKline and received compensation.
M.B.W. is employed by Imanova Ltd., a private company that
performs contract research work for the pharmaceutical indus-
try. The other authors declare no potential conicts of interest.
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... The final sample comprised 30 papers including 31 studies, of which 26 were non-acute (Tables 1a and 1b) and five were acute (Tables 2a and 2b). Two (Freeman et al., 2018;Lawn et al., 2016) had participants from the same sample, but as they used different tasks, we included both. Total number of participants were 5546 in the questionnaire studies, 401 in the non-acute behavioural studies, 712 in the non-acute neuroimaging studies, and 48 in the acute studies. ...
... However, follow-up analyses within individual regions of interest did not reach statistical significance after correcting for multiple comparisons. Finally, Freeman et al. (2018) found that THC dampened the response to music in several brain areas associated with music listening and pleasure, including auditory cortex and ventral striatum. Moreover, functional connectivity between these two areas was higher during a THC with CBD condition, compared to a THC only condition. ...
... The results of Lawn et al. (2016) suggested an acute amotivational effect of cannabis at low probability of reward, consistent with previous research (Cherek et al., 2002). However, acute cannabis did not affect liking of food (de Bruijn et al., 2017) or pleasure ratings of music (Freeman et al., 2018). This was surprising, given the vast amount of historical, anecdotal, and preclinical scientific evidence suggesting that that cannabis augments the pleasurable effects of a variety of rewards (see Solinas et al., 2008 for a review). ...
Cannabis use has historically been thought to cause amotivation, but the relationship between cannabis and apathy, anhedonia, and reward processing remains poorly characterised. In this systematic review, we evaluated whether cannabis exposure acutely and/or non-acutely was associated with altered reward processing using questionnaire, behavioural, or functional neuroimaging measures. Questionnaire studies demonstrated greater anhedonia in adolescent cannabis users, and some indication of greater apathy in young adult cannabis users. Behavioural studies yielded some evidence of reduced reward learning in adolescent cannabis users, though there were too few studies in this category for reliable conclusions. Finally, longitudinal and acute functional neuroimaging studies showed an association between cannabis and blunted neural responses to reward, which did not emerge consistently in cross-sectional studies. The current results suggest that cannabis use is associated with specific impairments in reward and motivation. Future large-scale, longitudinal studies which use multiple behavioural and neuroimaging measures of reward processing may further clarify the impact of cannabis use on motivational and reward processes, and neural networks.
... Research suggests that enjoyment of listening to music is greater when under the effects of cannabis with CBD relative to cannabis containing trace or no CBD (Freeman et al., 2018b). This has been attributed to CBD modulating the dampening effects of THC on brain regions sensitive to reward and emotion. ...
... This has been attributed to CBD modulating the dampening effects of THC on brain regions sensitive to reward and emotion. Consequently for an enjoyable experience in shishatype bars and to offset some reported negative effects of THC, such as an increase in diastolic blood pressure and decreased response to music, while preserving or potentiating desirable effects, such as enhanced sound perception, cannabis with notable levels of CBD is recommended for use in shisha-type bars (Freeman et al., 2018b). Set and setting are highly influential on the subjective experiences of cannabis users and shishatype bars and regulations thereof should account for this to minimise potential harms and increase positive, and ideally therapeutic, outcomes (Hartogsohn, 2017). ...
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Background: Despite rescheduling of cannabis to Schedule 2 and amendments to the law permitting legal availability of cannabis for the treatment of medical conditions, access to cannabis for medical use remains challenging for patients in the United Kingdom (UK). Recreational use is widespread despite laws stating users can be sentenced to prison for up to 5 years for possession. Objective: The aim of the study was to develop a model for a legal cannabis market in the UK building upon the results of a preceding study in which a UK population sample determined that pharmacies are the most suitable primary legal vendor of cannabis as opposed to regulated shops or the black market. Methods: An online survey was developed using Qualtrics software and advertised via the Multidisciplinary Association for Psychedelic Studies' Facebook, Twitter and Instagram social media accounts and monthly newsletter. Results: Three hundred and ninety seven individuals, a majority having used cannabis at least once, consented to participate in the study. The participants concluded that there is enough evidence for cannabis to be prescribed to treat a range of medical conditions. In addition to pharmacies providing cannabis to patients with a prescription, a majority of participants supported cannabis being sold in pharmacies for harm reduction purposes and allowing access to medicinal cannabis in cases where supporting evidence is insufficient to merit a prescription. Participants supported greater integration between dispensing pharmacies and mental health services. Overall, the participants did not oppose a consultation or screening for potential cannabis users prior to obtaining access from licensed vendors. UK participants were supportive of the concept of a cannabis card, which users can present to licensed vendors such as pharmacies, with specific recommendations (such as strains relevant to a patient's medical condition) being coded into the card. A majority of participants supported the existence of shisha-type bars for the purchase and onsite consumption of cannabis and determined that such vendors should not be part of a pharmacy chain of stores or regulated by pharmacy regulators. The participants generally preferred that laws regarding public consumption are in line with existing smoking legislation. Participants determined that it should be legally permitted to grow cannabis at home for personal medical and non-medical purposes but not to sell for profit. Conclusion: The results are suggestive of a regulatory system that medical and non-medical cannabis users can use which aims to maximise therapeutic applications, minimise harms and respect individual liberty.
... For example, when administered capsules containing standardized cannabis extracts, subjects exposed to a pure tone deviance task demonstrated a significant negative correlation between mismatch negativity amplitudes and the plasma concentration of the THC metabolite 11-OH-THC 47 . In addition, using a standardized cannabis inhalation protocol, subjects demonstrated reduced auditory cortex activity in response to music stimuli compared to controls 48 . Similar findings of reduced auditory cortex activation in response to neutral words read as auditory stimuli were seen in subjects administered THC capsules as well 49 . ...
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Alterations in cannabinoid CB1 receptor (CB1R) are implicated in various psychiatric disorders. CB1R participates in both depolarization induced suppression of inhibition (DSI) and depolarization induced suppression of excitation (DSE), suggesting its involvement in regulating excitatory and inhibitory (E/I) balance. Prior studies examining neuronal cell type specific CB1R distribution have been conducted near exclusively within rodents. Identification of these distribution patterns within the human and non-human primate cortex is essential to increase our insight into its function. Using co-labeling immunohistochemistry and fluorescent microscopy, we examined CB1R protein levels within excitatory and inhibitory boutons of male human and non-human primate prefrontal cortex and auditory cortices, regions involved in the behavioral effects of exogenous cannabinoid exposures. We found that CB1R was present in both bouton populations within all brain regions examined in both species. Significantly higher CB1R levels were found within inhibitory than within excitatory boutons across all regions in both species, although the cell type by brain region interactions differed between the two species. Our results support the importance of conducting more in-depth CB1R examinations to understand how cell type and brain region dependent differences contribute to regional E/I balance regulation, and how aberrations in CB1R distribution may contribute to pathology.
... Such studies could potentially monitor directly how acute THC intoxication affects ventral-dorsal striatal activation as a function of cannabis use history and further clarify the contributory roles of striatal dopaminergic and glutamatergic neurotransmission to excessive cannabis use and habit formation. The latter is of particular relevance, as a number of acute THC studies have shown that a single dose of THC attenuates the striatal response to rewards such as monetary incentives, cannabis marketing, and music (56)(57)(58) suggesting that THC-induced increments in striatal dopamine reduce salience and attentional processing of concurrent rewards (56). Acute THC challenge studies therefore would not only contribute to a fundamental understanding of ventral-dorsal striatal activation with increasing cannabis use, but also provide important pharmacological insights on how shifts in striatal balance can be prevented or controlled in order to avoid progression to compulsive cannabis use. ...
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Currently, the assessment of the neurobehavioral consequences of repeated cannabis use is restricted to studies in which brain function of chronic cannabis users is compared to that of non-cannabis using controls. The assumption of such studies is that changes in brain function of chronic users are caused by repeated and prolonged exposure to acute cannabis intoxication. However, differences in brain function between chronic cannabis users and non-users might also arise from confounding factors such as polydrug use, alcohol use, withdrawal, economic status, or lifestyle conditions. We propose a methodology that highlights the relevance of acute Δ9-tetrahydrocannabinol (THC) dosing studies for a direct assessment of neuroadaptations in chronic cannabis users. The approach includes quantification of neurochemical, receptor, and functional brain network changes in response to an acute cannabis challenge, as well as stratification of cannabis using groups ranging from occasional to cannabis-dependent individuals. The methodology allows for an evaluation of THC induced neuroadaptive and neurocognitive changes across cannabis use history, that can inform neurobiological models on reward driven, compulsive cannabis use.
... The authors speculated that this attenuated response to a reward may have been caused by delta-9tetrahydrocannabinol's effects on regions such as the ventral striatum and amygdala, although they were unable to speculate on whether dopamine levels in these areas were involved in the participant's response. Instead, the endocannabinoid system in those regions may instead be affected by cannabis use (Freeman et al., 2018). ...
Value-based decision-making is thought to play an important role in drug dependency. Achieving elevated levels of euphoria or ameliorating dysphoria/pain may motivate goal-directed drug consumption in both drug-naïve and long-time users. In other words, drugs become viewed as the preferred means of attaining a desired internal state. The bias towards choosing drugs may affect one’s cognition. Observed biases in learning, attention and memory systems within the brain gradually focus one’s cognitive functions towards drugs and related cues to the exclusion of other stimuli. In this narrative review, the effects of drug use on learning, attention and memory are discussed with a particular focus on changes across brain-wide functional networks and the subsequent impact on behaviour. These cognitive changes are then incorporated into the cycle of addiction, an established model outlining the transition from casual drug use to chronic dependency. If drug use results in the elevated salience of drugs and their cues, the studies highlighted in this review strongly suggest that this salience biases cognitive systems towards the motivated pursuit of addictive drugs. This bias is observed throughout the cycle of addiction, possibly contributing to the persistent hold that addictive drugs have over the dependent. Taken together, the excessive valuation of drugs as the preferred means of achieving a desired internal state affects more than just decision-making, but also learning, attentional and mnemonic systems. This eventually narrows the focus of one’s thoughts towards the pursuit and consumption of addictive drugs.
... THC and cannabis produce several effects on the brain which may account for the increased risk of psychopathology and psychotic symptoms (15)(16)(17). These include effects on the striatum which integrates sensorimotor, cognitive, motivational and emotional information to mediate reward and decision-making processes (7,(18)(19)(20). However, the precise mechanisms through which THC exposure causes psychotic symptoms have yet to be fully elucidated. ...
Background Cannabis and its main psychoactive component, Δ⁹-tetrahydrocannabinol (THC), can elicit transient psychotic symptoms. A key candidate biological mechanism of how THC induces psychotic symptoms is the modulation of glutamate in the brain. We sought to investigate the effects of acute THC administration on striatal glutamate levels and its relationship to the induction of psychotic symptoms. Methods We used proton magnetic resonance spectroscopy to measure glutamate levels in the striatum in 20 healthy participants after THC (15 mg, oral) and matched placebo administration in a randomized, double-blind, placebo-controlled design. Psychotic symptoms were measured using the Psychotomimetic States Inventory. Results We found that THC administration did not significantly change glutamate (glutamate plus glutamine relative to creatine) concentration in the striatum (p = .58; scaled Jeffreys-Zellner-Siow Bayes factor = 4.29). THC increased psychotic symptoms, but the severity of these symptoms was not correlated with striatal glutamate levels. Conclusions These findings suggest that oral administration of 15 mg of THC does not result in altered striatal glutamate levels. Further work is needed to clarify the effects of THC on striatal glutamate.
... NATURE REVIEwS | NeuroscieNce such as monetary incentives, cannabis marketing and music [93][94][95] , suggesting that THC-induced increments in striatal dopamine reduce salience and attentional processing of concurrent rewards 94 . THC-induced changes in response latency during tasks involving attentional salience processing were shown to be related to modulations in prefrontal and striatal activation that result in decreased mesocorticolimbic functional connectivity 32,96 . ...
Acute cannabis intoxication may induce neurocognitive impairment and is a possible cause of human error, injury and psychological distress. One of the major concerns raised about increasing cannabis legalization and the therapeutic use of cannabis is that it will increase cannabis‐related harm. However, the impairing effect of cannabis during intoxication varies among individuals and may not occur in all users. There is evidence that the neurocognitive response to acute cannabis exposure is driven by changes in the activity of the mesocorticolimbic and salience networks, can be exacerbated or mitigated by biological and pharmacological factors, varies with product formulations and frequency of use and can differ between recreational and therapeutic use. It is argued that these determinants of the cannabis-induced neurocognitive state should be taken into account when defining and evaluating levels of cannabis impairment in the legal arena, when prescribing cannabis in therapeutic settings and when informing society about the safe and responsible use of cannabis. Acute cannabis exposure modulates numerous aspects of neurocognitive function; however, the effects experienced by individuals are highly variable. Ramaekers and colleagues here review the neural basis of cannabis-induced neurocognitive changes and response variability, and consider the legal, therapeutic and societal implications.
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Rationale Greater availability of cannabis in the USA has raised concerns about adverse effects of the drug, including possible amotivational states. Lack of motivation may be assessed by examining acute effects of cannabinoids on reward processing. Objectives This study examined single doses of delta-9-tetrahydrocannabinol (∆9-THC; 7.5, 15 mg oral) in healthy adults using a version of the monetary incentive delay (MID) task adapted for electroencephalography (EEG; e-MID) in a within-subjects, double blind design. Methods Two phases of reward processing were examined: anticipation, which occurs with presentation of cues that indicate upcoming reward, punishment, or neutral conditions, and outcome, which occurs with feedback indicating hits or misses. During anticipation, we measured two event-related potential (ERP) components: the P300, which measures attention and motivation, and the LPP, which measures affective processing. During outcome processing, we measured P300 and LPP, as well as the RewP, which measures outcome evaluation. Results We found that ∆9-THC modulated outcome processing, but not reward anticipation. Specifically, both doses of ∆9-THC (7.5 and 15 mg) reduced RewP amplitudes after outcome feedback (hits and misses) relative to placebo. ∆9-THC (15 mg) also reduced P300 and LPP amplitudes following hits compared to misses, relative to both placebo and 7.5 mg ∆9-THC. Conclusions These findings suggest that ∆9-THC dampens responses to both reward and loss feedback, which may reflect an “amotivational” state. Future studies are needed to determine generalizability of this effect, such as its pharmacological specificity and its specificity to monetary vs other types of reward.
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Background Cannabidiol (CBD) and Δ ⁹ -tetrahydrocannabinol (THC) are the two major constituents of cannabis with contrasting mechanisms of action. THC is the major psychoactive, addiction-promoting, and psychotomimetic compound, while CBD may have opposite effects. The brain effects of these drugs alone and in combination are poorly understood. In particular, the striatum is implicated in the pathophysiology of several psychiatric disorders, but it is unclear how THC and CBD influence striato-cortical connectivity. Aims To examine effects of THC, CBD, and THC + CBD on functional connectivity of striatal sub-divisions (associative, limbic and sensorimotor). Method Resting-state functional Magnetic Resonance Imaging (fMRI) was used across two within-subjects, placebo-controlled, double-blind studies, with a unified analysis approach. Results Study 1 ( N = 17; inhaled cannabis containing 8 mg THC, 8 mg THC + 10 mg CBD or placebo) showed strong disruptive effects of both THC and THC + CBD on connectivity in the associative and sensorimotor networks, but a specific effect of THC in the limbic striatum network which was not present in the THC + CBD condition. In Study 2 ( N = 23, oral 600 mg CBD, placebo), CBD increased connectivity in the associative network, but produced only relatively minor disruptions in the limbic and sensorimotor networks. Outcomes THC strongly disrupts striato-cortical networks, but this effect is mitigated by co-administration of CBD in the limbic striatum network. Oral CBD administered has a more complex effect profile of relative increases and decreases in connectivity. The insula emerges as a key region affected by cannabinoid-induced changes in functional connectivity, with potential implications for understanding cannabis-related disorders, and the development of cannabinoid therapeutics.
Purpose of review: This comprehensive review discusses the adverse effects known today about marijuana, for either medical or recreational use. It reviews the role of cannabis in the treatment of chronic pain, cognitive and neurological adverse effects, special cases and addiction. Recent findings: Cannabinoids work through the endocannabinoids system and inhibit the release of GABA and glutamate in the brain, impact neuromodulation, as well as dopamine, acetylcholine and norepinephrine release. They affect reward, learning and pain. The use of cannabis is increasing nationally and world-wide for both recreational and medicinal purposes, however, there is relatively only low quality evidence to the efficacy and adverse effects of this. Cannabis and its derivatives may be used for treatment of chronic pain. They are via CB1 receptors that are thought to modulate nociceptive signals in the brain. CB2 receptors in the DRG likely affect pain integration in the afferent pathways, and peripherally CB2 also affects noradrenergic pathways influencing pain. A large proportion of users may see more than 50% of chronic pain alleviation compared with placebo. Cannabis affects cognition, most notably executive function, memory and attention, and may deteriorate the boundary between emotional and executive processing. Cannabis impairs memory in the short run, which become more significant with chronic use, and may also be accompanied by poorer effort, slower processing and impacted attention. It is generally believed that long-term use and earlier age are risk factor for neurocognitive deficits; neuroimaging studies have shown reduced hippocampal volume and density. Executive functions and memory are worse in adolescent users versus adults. Cannabis addiction is different and likely less common than other addictive substances, but up to 10% of users meet criteria for lifetime cannabis dependence. Addiction patterns may be linked to genetic and epigenetic differences. It is still unclear whether abstinence reverses patterns of addiction, and more research is required into this topic. Summary: Cannabis use has become more abundant for both medical and recreational use. It carries likely benefits in the form of analgesia, anti-emesis and improved appetite in chronic patients. The evidence reviewing adverse effects of this use are still limited, however, exiting data points to a clear link with neurocognitive deterioration, backed by loss of brain volume and density. Addiction is likely complex and variable, and no good data exists to support treatment at this point. It is becoming clear that use in earlier ages carries a higher risk for long-term deficits. As with any other drug, these risks should be considered alongside benefits prior to a decision on cannabis use.
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Importance: Disrupted reward processing, mainly driven by striatal dysfunction, is a key characteristic of addictive behaviors. However, functional magnetic resonance imaging (fMRI) studies have reported conflicting results, with both hypoactivations and hyperactivations during anticipation and outcome notification of monetary rewards in addiction. Objective: To determine the nature and direction of reward-processing disruptions during anticipation and outcome notification of monetary rewards in individuals with addiction using image-based meta-analyses of fMRI studies. Data sources: Relevant publications were identified searching PubMed (inclusion until March 2015) using the following terms: reward, fMRI, substance use, cocaine, cannabis, opiates, alcohol, nicotine, smokers, gambling, gamblers, gaming, and gamers. Authors of included articles were contacted to obtain statistical fMRI maps. Study selection: Inclusion criteria: reward task involving monetary reward anticipation and/or outcome; participants showing addictive behaviors; and healthy control group. Exclusion criteria: participants aged younger than 18 years; recreational substance use or gambling; participants at risk for addictive behaviors; and studies using the same patient data as other included studies. Data extraction and synthesis: Study procedures were conducted in accordance with the Meta-analysis of Observational Studies in Epidemiology guidelines. Using Seed-based d Mapping software, meta-analyses were performed using random-effect nonparametric statistics with group whole brain T-maps from individual studies as input. Analyses were performed across all addictions and for substance and gambling addictions separately. Main outcomes and measures: Group differences (individuals with addiction vs control individuals) in reward-related brain activation during reward anticipation and outcome using fMRI (planned before data collection). Results: Twenty-five studies were included in the meta-analysis, representing 643 individuals with addictive behaviors and 609 healthy control individuals. During reward anticipation, individuals with substance and gambling addictions showed decreased striatal activation compared with healthy control individuals. During reward outcome, individuals with substance addiction showed increased activation in the ventral striatum, whereas individuals with gambling addiction showed decreased activation in the dorsal striatum compared with healthy control individuals. Conclusions and relevance: Striatal hypoactivation in individuals with addiction during reward anticipation and in individuals with gambling addiction during reward outcome is in line with the reward-deficiency theory of addiction. However, the combination of hypoactivation during reward anticipation and hyperactivation during reward outcome in the striatum of individuals with substance addiction may be explained using learning-deficit theory.
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Preclinical research demonstrates that cannabinoids have differing effects in adolescent and adult animals. Whether these findings translate to humans has not yet been investigated. Here we believe we conducted the first study to compare the acute effects of cannabis in human adolescent (n=20; 16–17 years old) and adult (n=20; 24–28 years old) male cannabis users, in a placebo-controlled, double-blind cross-over design. After inhaling vaporized active or placebo cannabis, participants completed tasks assessing spatial working memory, episodic memory and response inhibition, alongside measures of blood pressure and heart rate, psychotomimetic symptoms and subjective drug effects (for example, ‘stoned’, ‘want to have cannabis’). Results showed that on active cannabis, adolescents felt less stoned and reported fewer psychotomimetic symptoms than adults. Further, adults but not adolescents were more anxious and less alert during the active cannabis session (both pre- and post-drug administration). Following cannabis, cognitive impairment (reaction time on spatial working memory and prose recall following a delay) was greater in adults than adolescents. By contrast, cannabis impaired response inhibition accuracy in adolescents but not in adults. Moreover, following drug administration, the adolescents did not show satiety; instead they wanted more cannabis regardless of whether they had taken active or placebo cannabis, while the opposite was seen for adults. These contrasting profiles of adolescent resilience (blunted subjective, memory, physiological and psychotomimetic effects) and vulnerability (lack of satiety, impaired inhibitory processes) show some degree of translation from preclinical findings, and may contribute to escalated cannabis use by human adolescents.
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Although music is ubiquitous in human societies, there are some people for whom music holds no reward value despite normal perceptual ability and preserved reward-related responses in other domains. The study of these individuals with specific musical anhedonia may be crucial to understand better the neural correlates underlying musical reward. Previous neuroimaging studies have shown that musically induced pleasure may arise from the interaction between auditory cortical networks and mesolimbic reward networks. If such interaction is critical for music-induced pleasure to emerge, then those individuals who do not experience it should show alterations in the cortical-mesolimbic response. In the current study, we addressed this question using fMRI in three groups of 15 participants, each with different sensitivity to music reward. We demonstrate that the music anhedonic participants showed selective reduction of activity for music in the nucleus accumbens (NAcc), but normal activation levels for a monetary gambling task. Furthermore, this group also exhibited decreased functional connectivity between the right auditory cortex and ventral striatum (including the NAcc). In contrast, individuals with greater than average response to music showed enhanced connectivity between these structures. Thus, our results suggest that specific musical anhedonia may be associated with a reduction in the interplay between the auditory cortex and the subcortical reward network, indicating a pivotal role of this interaction for the enjoyment of music.
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RationaleAnecdotally, both acute and chronic cannabis use have been associated with apathy, amotivation, and other reward processing deficits. To date, empirical support for these effects is limited, and no previous studies have assessed both acute effects of Δ-9-tetrahydrocannabinol (THC) and cannabidiol (CBD), as well as associations with cannabis dependence. Objectives The objectives of this study were (1) to examine acute effects of cannabis with CBD (Cann + CBD) and without CBD (Cann-CBD) on effort-related decision-making and (2) to examine associations between cannabis dependence, effort-related decision-making and reward learning. Methods In study 1, 17 participants each received three acute vaporized treatments, namely Cann-CBD (8 mg THC), Cann + CBD (8 mg THC + 10 mg CBD) and matched placebo, followed by a 50 % dose top-up 1.5 h later, and completed the Effort Expenditure for Rewards Task (EEfRT). In study 2, 20 cannabis-dependent participants were compared with 20 non-dependent, drug-using control participants on the EEfRT and the Probabilistic Reward Task (PRT) in a non-intoxicated state. ResultsCann-CBD reduced the likelihood of high-effort choices relative to placebo (p = 0.042) and increased sensitivity to expected value compared to both placebo (p = 0.014) and Cann + CBD (p = 0.006). The cannabis-dependent and control groups did not differ on the EEfRT. However, the cannabis-dependent group exhibited a weaker response bias than the control group on the PRT (p = 0.007). Conclusions Cannabis acutely induced a transient amotivational state and CBD influenced the effects of THC on expected value. In contrast, cannabis dependence was associated with preserved motivation alongside impaired reward learning, although confounding factors, including depression, cannot be disregarded. This is the first well powered, fully controlled study to objectively demonstrate the acute amotivational effects of THC.
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Cannabis and tobacco are common drugs of abuse worldwide and are often used in combination through various routes of administration (ROAs). Here, we aimed to provide an overview of how cannabis and tobacco routes varied across countries and assess the impact of tobacco-based ROAs on motivation to use less cannabis, and less tobacco, in different models. A cross-sectional online survey (Global Drugs Survey 2014) was completed by 33,687 respondents (mean age = 27.9; % female = 25.9) who smoked cannabis at least once in the last 12 months. Most common ROA, frequency of cannabis/tobacco use, and questions about motivation to use less cannabis/ tobacco were recorded. Tobacco-based ROA were used by 65.6% of respondents. These were most common in Europe (77.2–90.9%) and Australasia (20.7–51.6%) and uncommon in the Americas (4.4–16.0%). Vaporizer use was most common in Canada (13.2%) and the United States (11.2%). Using a non-tobacco ROA was associated with a 10.7% increase in odds for " desire to use less " tobacco (OR: 1.107, 95% CI: 1.003, 1.221), 80.6% increase in odds for " like help to use less tobacco " (OR: 1.806, 95% CI: 1.556, 2.095), and a 103.9% increase in the odds for " planning to seek help to use less tobacco " (OR: 2.039, 95% CI: 1.638, 2.539), in comparison to using a tobacco-based ROA. Associations between ROA and intentions to use less cannabis were inconsistent. Results support considerable global variation in cannabis and tobacco ROA. Tobacco routes are common, especially " joints with tobacco, " especially in Europe, but not in the Americas. Non-tobacco-based routes are associated with increased motivation to change tobacco use. Interventions addressing tobacco and cannabis need to accommodate this finding and encourage non-tobacco routes.
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In an increasing number of states and countries, cannabis now stands poised to join alcohol and tobacco as a legal drug. Quantifying the relative adverse and beneficial effects of cannabis and its constituent cannabinoids should therefore be prioritized. Whereas newspaper headlines have focused on links between cannabis and psychosis, less attention has been paid to the much more common problem of cannabis addiction. Certain cognitive changes have also been attributed to cannabis use, although their causality and longevity are fiercely debated. Identifying why some individuals are more vulnerable than others to the adverse effects of cannabis is now of paramount importance to public health. Here, we review the current state of knowledge about such vulnerability factors, the variations in types of cannabis, and the relationship between these and cognition and addiction.
Cannabis use and related problems are on the rise globally alongside an increase in the potency of cannabis sold on both black and legal markets. Additionally, there has been a shift towards abandoning prohibition for a less punitive and more permissive legal stance on cannabis, such as decriminalisation and legalisation. It is therefore crucial that we explore new and innovative ways to reduce harm. Research has found cannabis with high concentrations of its main active ingredient, δ-9-tetrahydrocannabinol (THC), to be more harmful (in terms of causing the main risks associated with cannabis use, such as addiction, psychosis, and cognitive impairment) than cannabis with lower concentrations of THC. By contrast, cannabidiol, which is a non-intoxicating and potentially therapeutic component of cannabis, has been found to reduce the negative effects of cannabis use. Here, we briefly review findings from studies investigating various types of cannabis and discuss how future research can help to better understand and reduce the risks of cannabis use.
Importance Marijuana use may alter ventral striatal response to reward, which might heighten susceptibility to substance use disorder. Longitudinal research is needed to determine the effects of marijuana use on neural function involved in reward response. Objective To determine whether marijuana use among young adults prospectively affects nucleus accumbens (NAcc) activation during reward anticipation. Design, Setting, and Participants One hundred eight young adults were recruited from the Michigan Longitudinal Study, an ongoing study of youth at high risk for substance use disorder and a contrast sample of control families. Participants underwent 3 consecutive functional magnetic resonance imaging scans at approximate ages of 20 (time 1), 22 (time 2), and 24 (time 3) years. Self-report data on marijuana and other drug use occasions were collected annually since age 11 years. Main Outcomes and Measures Cross-lagged models were used to test the association of marijuana use with neural response in the NAcc to reward anticipation during a monetary incentive delay task controlling for sex, age, other substance use, and family history of substance use disorder. Results Of 108 participants, 39 (36.1%) were female and mean (SD) age at baseline was 20.1 (1.4) years. Greater marijuana use was associated with later blunted activation in the NAcc during reward anticipation (time 1 to time 2: β = −0.26, P = .04; time 2 to time 3: β = −0.25, P = .01). When the cross-lagged model was tested with the inclusion of previous and concurrent cigarette use, the effect of marijuana use from time 2 to time 3 remained significant (β = −0.29; P = .005) and the effect of cigarette use was nonsignificant. Conclusions and Relevance The findings of this study indicate that marijuana use is associated with decreased neural response in the NAcc during the anticipation of nondrug rewards. Over time, marijuana use may alter anticipatory reward processing in the NAcc, which may increase the risk for continued drug use and later addiction.
Background: Marijuana is the most widely used illicit drug in the United States and all over the world. Reports indicate that the potency of cannabis preparation has been increasing. This report examines the concentration of cannabinoids in illicit cannabis products seized by the U.S. Drug Enforcement Administration over the last 2 decades, with particular emphasis on Δ(9)-tetrahydrocannabinol and cannabidiol. Methods: Samples in this report were received over time from materials confiscated by the Drug Enforcement Administration and processed for analysis using a validated gas chromatography with flame ionization detector method. Results: Between January 1, 1995, and December 31, 2014, 38,681 samples of cannabis preparations were received and analyzed. The data showed that although the number of marijuana samples seized over the last 4 years has declined, the number of sinsemilla samples has increased. Overall, the potency of illicit cannabis plant material has consistently increased over time since 1995 from ~4% in 1995 to ~12% in 2014. The cannabidiol content has decreased on average from ~.28% in 2001 to <.15% in 2014, resulting in a change in the ratio of Δ(9)-tetrahydrocannabinol to cannabidiol from 14 times in 1995 to ~80 times in 2014. Conclusions: There is a shift in the production of illicit cannabis plant material from regular marijuana to sinsemilla. This increase in potency poses higher risk of cannabis use, particularly among adolescents.