Cerebellar white-matter changes in cannabis users
with and without schizophrenia
N. Solowij1,2*, M. Yu ¨cel3,4, C. Respondek1, S. Whittle3, E. Lindsay3, C. Pantelis3and D. I. Lubman4,5
1School of Psychology, University of Wollongong, Australia
2Schizophrenia Research Institute, Sydney, Australia
3Melbourne Neuropsychiatry Centre, University of Melbourne, Australia
4Orygen Youth Health Research Centre, University of Melbourne, Australia
5Turning Point Alcohol and Drug Centre, Eastern Health and Monash University, Melbourne, Australia
Background. The cerebellum is rich in cannabinoid receptors and implicated in the neuropathology of schizophrenia.
Long-term cannabis use is associated with functional and structural brain changes similar to those evident in schizo-
phrenia, yet its impact on cerebellar structure has not been determined. We examined cerebellar grey and white
matter in cannabis users with and without schizophrenia.
Method. Seventeen patients with schizophrenia and 31 healthy controls were recruited; 48% of the healthy group
and 47% of the patients were long-term heavy cannabis users (mean 19.7 and 17.9 years near daily use respectively).
Cerebellar measures were extracted from structural 3-T magnetic resonance imaging (MRI) scans using semi-
automated methods, and examined using analysis of covariance (ANCOVA) and correlational analyses.
Results. Cerebellar white-matter volume was reduced in cannabis users with and without schizophrenia compared
to healthy non-users, by 29.7% and 23.9% respectively, and by 17.7% in patients without cannabis use. Healthy
cannabis users did not differ in white-matter volume from either of the schizophrenia groups. There were no group
differences in cerebellar grey matter or total volumes. Total cerebellar volume decreased as a function of duration of
cannabis use in the healthy users. Psychotic symptoms and illness duration correlated with cerebellar measures
differentially between patients with and without cannabis use.
Conclusions. Long-term heavy cannabis use in healthy individuals is associated with smaller cerebellar white-matter
volume similar to that observed in schizophrenia. Reduced volumes were even more pronounced in patients with
schizophrenia who use cannabis. Cannabis use may alter the course of brain maturational processes associated with
Received 28 May 2010; Revised 16 December 2010; Accepted 7 March 2011; First published online 5 April 2011
Key words: Cannabis, cerebellum, schizophrenia, structural magnetic resonance imaging.
Cerebellar dysfunction has been proposed to explain
the heterogeneity of cognitive-affective deficits and
symptoms observed in schizophrenia (Schmahmann,
1991; Andreasen & Pierson, 2008). Consistent with this
notion, studies have reported reduced total cerebellar
or vermian volume in established schizophrenia
(Ichimiya et al. 2001; Loeber et al. 2001; Ho et al. 2004;
Picard et al. 2008), during the early stages of psychosis
(Okugawa et al. 2007; Charalambides et al. 2009),
and also longitudinally with the onset of psychosis
(Pantelis et al. 2003; Borgwardt et al. 2008). The cer-
ebellum is rich in cannabinoid receptors (Ashton et al.
2004) and deficits in cerebellar-dependent functions
such as internal self-paced timing (O’Leary et al. 2003),
classical eyeblink conditioning (Skosnik et al. 2008)
and oculomotor function (Huestegge et al. 2009) have
been demonstrated in humans following acute or
chronic cannabis use. These cerebellar-mediated pro-
cesses are aberrant in schizophrenia (Picard et al. 2008)
and long-term heavy cannabis use in general can lead
to cognitive deficits that are similar to those evident
in schizophrenia (Solowij & Michie, 2007). We have
previously reported preliminary data suggestive of
smaller cerebellar volumes in cannabis users (Ward
et al. 2002). More recently, we reported bilaterally re-
duced hippocampal and amygdala volumes in long-
term heavy cannabis users compared with non-user
controls (Yu ¨cel et al. 2008), with hippocampal re-
duction (12%) of a magnitude similar to that seen in
schizophrenia (Wright et al. 2000; Velakoulis et al.
* Address for correspondence: Dr N. Solowij, School of Psychology,
University of Wollongong, Wollongong, NSW 2522, Australia.
Psychological Medicine (2011), 41, 2349–2359.
f Cambridge University Press 2011
2006). Moreover, smaller left hippocampal volume in
mulative exposure to cannabis and also with cannabis
exposure-related subclinical psychotic symptoms in
these otherwise healthy adults. The accumulating
evidence suggests that cannabis use may lead to the
development of cognitive deficits, psychotic symp-
toms and specific regional brain alterations. No
studies have examined the effects of cannabis use on
cerebellar structural integrity in adult long-term heavy
cannabis users with or without schizophrenia.
In this study we examined the effects of very long-
term and heavy cannabis use on cerebellar structure in
a sample of patients with chronic schizophrenia and
also in otherwise healthy individuals. We hypothe-
sized that cannabis use would be associated with re-
duced cerebellar volume compared to non-use, and
that this reduction would be greater in schizophrenia
patients with co-morbid cannabis use. If confirmed,
the finding would suggest that heavy cannabis use is
not only harmful to the human brain but also es-
pecially harmful to already vulnerable individuals,
such as those with psychotic illnesses.
Participants, substance use and symptom measures
Right-handed males were recruited from the general
community, by referral from psychiatrists or through
the Australian Schizophrenia Research Bank (ASRB),
to form the following comparison groups: otherwise
healthy long-term heavy cannabis users (THC; n=15);
healthy non-user controls (CON; n=16); cannabis
users with schizophrenia (SZ+THC; n=8) and non-
users with schizophrenia (SZ–THC; n=9). The SZ–
THC group was recruited to match the clinical and
demographic characteristics of the SZ+THC group.
Clinical and demographic characteristics and sub-
stance use were assessed by structured interview, and
drug use was confirmed by urinalysis. Cannabis users
with and without schizophrenia had similar levels of
current use and very extensive cannabis use histories
(near daily use for 9–32 years). Cannabis use had
generally preceded the onset of schizophrenia by sev-
eral years. No participant had used any other illicit
substance regularly (i.e. f10 lifetime episodes) and
alcohol use was limited to <24 standard drinks per
week. Overall, there was a significant difference be-
tween groups in alcohol use (standard drinks/day;
x2=9.12, p=0.028) and tobacco use (cigarettes/day;
x2=25.06, p < 0.001). This was due to the healthy
control group using significantly less tobacco than any
other group (p < 0.057–0.001) and the SZ–THC group
using less alcohol than either of the non-schizophrenia
groups (p=0.005 and 0.02). Alcohol and tobacco use
were included as covariates in the analyses. All groups
were matched on age (range 21–60 years), pre-morbid
IQ (National Adult Reading Test) and years of edu-
cation. Demographic, clinical and substance use
characteristics are provided in Table 1.
The Structured Clinical Interview for DSM-IV Axis I
Disorders (SCID) was used to screen for any psychi-
atric disorders among healthy participants, and to
confirm a schizophrenia diagnosis. All patients were
stabilized on atypical antipsychotic medication (ex-
cept for one currently antipsychotic free in the SZ–
THC group). Estimated chlorpromazine equivalent
doses did not differ between SZ+THC and SZ–THC
(median 200 mg in each group; p=0.54). The duration
of illness (years since diagnosis) was longer in the
SZ–THC group compared with SZ+THC (t=2.14,
p=0.049), but there was no difference in the duration
of the prodrome (p=0.37) or the total number of
hospitalizations (p=0.48). Psychotic symptoms were
assessed using the Scales for the Assessment of
Positive and Negative Symptoms (SAPS and SANS;
Andreasen, 1983). Patients had significantly higher
SAPS and SANS composite scores than healthy parti-
cipants (Table 1), and SZ+THC had non-significantly
higher symptom scores than SZ–THC (SAPS: p>0.2;
SANS: p>0.09). Healthy cannabis users had signifi-
cantly higher SAPS and SANS scores than healthy
non-users (SAPS: z=3.57, p<0.001; SANS: z=3.66,
p<0.001). Depressive symptoms, assessed by the
Hamilton Depression Rating Scale (HAMD) and
Global Assessment of Functioning (GAF), also differed
between the four groups (Table 1). HAMD scores were
significantly higher in THC (t=2.60, p=0.013) and in
SZ+THC (t=2.33, p=0.024) compared to CON, and
GAF scores were lower in both schizophrenia groups
compared to both THC (SZ+THC: t=5.53, p<0.001;
SZ–THC: t=5.21, p < 0.001) and CON (SZ+THC:
t=7.63, p<0.001; SZ–THC: t=7.39, p<0.001) and in
THC compared to CON (t=2.45, p=0.018).
All protocols were approved by the University of
Wollongong and South Eastern Sydney and Illawarra
Area Health Service Human Research Ethics Com-
mittee and the study was performed according to ap-
proved guidelines and regulations. After complete
description of the study to the participants, written
informed consent was obtained. Patients were deemed
to have the capacity to provide informed consent.
Magnetic resonance imaging (MRI) procedures and
MRI data were obtained using a Phillips Intera 3-Tesla
scanner at the Symbion Clinical Research Imaging
2350N. Solowij et al.
Centre, Prince of Wales Medical Research Institute,
Sydney, Australia. A three-dimensional volumetric
spoiled gradient recalled (SPGR) sequence generated
180 contiguous coronal slices. Imaging parameters
were: echo time (TE)=2.9 ms; repetition time (TR)=
6.4 ms; flip angle=8x; matrix size 256r256; 1 mm3
Cerebellar volumes were delineated using semi-
automated methods adapted from a parcellation tech-
nique developed in our laboratory (Yu ¨cel et al. 2001).
In brief, a cerebellar template was initially created
from the original Montreal Neurological Institute
(MNI) Colin27 MRI brain image using a manual
tracing method. The original MNI image was then
warped and registered onto each target brain using
168 parameters of the Automated Image Registration
(AIR) 5.25 package. Using these warp parameters, the
cerebellum template from the MNI brain was then
registered to each target brain to create a cerebellar
mask. Each mask was algebraically multiplied with
the target brains to produce a cerebellum grey-
scale image. To avoid susceptibility to partial volum-
ing and inhomogeneity effects, grey and white tissue
volumes of the whole cerebellum were obtained by
Table 1. Demographic, clinical, drug use and MRI volumetric measures
Years of education
SAPS composite score
SANS composite score
Duration of illness (years)
Age at diagnosis (years)
Years of regular usea
– 17.9 (6.5),
Age started regular usea
Current use (days/month)b
Current use (cones/month)b
(past 10 years)b
Alcohol (standard drinks/week)
Intracranial cavity (mm3)c
Whole brain volume (mm3)
Total cerebellar volume (mm3)c
Cerebellar grey matter (mm3)c
Cerebellar white matter (mm3)c
MRI, Magnetic resonance imaging; SAPS, Scale for the Assessment of Positive Symptoms; SANS, Scale for the Assessment of
Negative Symptoms; GAF, Global Assessment of Functioning; HAMD, Hamilton Depression Rating Scale.
Values given as mean (standard deviation) or median [range].
aRegular use was defined as at least twice a month.
bCannabis users had used at this level for the majority of their drug-using careers; a ‘cone’ is the small funnel into which
cannabis is packed to consume through a water pipe in a single inhalation. Without the loss of sidestream smoke, the quantity of
tetrahydrocannabinol (THC) delivered by this method is estimated as equating three cones to one cigarette-sized joint. Thus, the
cannabis users with and without schizophrenia smoked the equivalent of 213 joints per month, or approximately seven joints
per day. Estimates of lifetime dose beyond 10 years in these very long-term users became skewed and unreliable, hence the 10-
year estimate was used in correlational analyses.
cTotal, grey and white-matter volumes represent means corrected for intracranial cavity and adjusted for differences in
alcohol and tobacco use across samples.
Cannabis, schizophrenia and cerebellar alterations2351
algebraically multiplying the binary cerebellar mask
for each image with segmented grey and white tissue
matter images of the whole brain extracted using the
FSL Functional Automated Segmentation Tool (Zhang
et al. 2001). Reliability analyses were conducted be-
tween manual tracing methods and the current semi-
automated method for 10 randomly selected brains
and obtained intraclass coefficient correlations of 0.98
for grey matter and 0.99 for white matter. Cerebellar
data were normalized for variation in total intracranial
volume between all individuals using a covariance
method described by Free et al. (1995).
Data were examined for outliers and normality. The
primary measures for analysis (i.e. cerebellar volumes,
cannabis use measures) were normally distributed
and group differences investigated using analysis of
covariance (ANCOVA), with alcohol and tobacco use
as covariates. Planned contrasts (least significant dif-
ference) examined differences between cannabis users
and controls within the healthy (THC versus CON) and
schizophrenia samples (SZ+THC versus SZ – THC),
and also between healthy cannabis users and users
and non-users with schizophrenia (THC versus SZ+
THC and THC versus SZ – THC). Relationships be-
tween cerebellar volumes and cannabis use measures
or psychological symptoms were examined using
two-tailed Pearson product-moment correlations for
normally distributed data, or Spearman rank order
correlations for skewed data (e.g. SAPS, SANS scores).
volumes are reported in Table 1 and depicted in Figs 1
and 2. ANCOVA with current levels of alcohol and
tobacco use as covariates determined a significant
overall difference between the four groups in white-
matter volume [F(3, 38)=4.23, p=0.011], but groups
did not differ in grey matter [F(3, 38)=0.55, p=0.65] or
total cerebellar volume [F(3, 42)=1.68, p=0.19].
Whole-brain white-matter volume did not differ be-
tween groups [F(3, 42)=0.58, p=0.63] and its inclusion
as a covariate in the analysis of cerebellar white-matter
volume did not alter the significant overall group
difference [F(3, 37)=3.70, p=0.02]. Similarly, whole-
brain grey-matter and total volume did not differ
significantly between groups [F(3, 42)=2.20, p=0.10;
inclusion as covariates in respective analyses of cer-
ebellar grey-matter and total cerebellar volume did
not alter the lack of overall group differences found for
those measures [cerebellar grey matter: F(3, 37)=0.53,
p=0.66; cerebellar total volume: F(3, 41)=0.85,
p=0.47]. These results indicate the specificity of group
differences to cerebellar white-matter volume.
Pairwise comparisons revealed that the THC group
had a 23.9% smaller white-matter volume than CON
(t=3.04, p < 0.004) with a large effect size [Cohen’s
d=1.32, 95% confidence interval (CI) 0.41–2.1]. White-
matter volume was also significantly smaller relative
to CON in the schizophrenia groups: by 29.7%
in SZ+THC (t=3.30, p=0.002, Cohen’s d=1.63, 95%
CI 0.50–2.48) and by 17.7% in SZ – THC (t=2.13,
p=0.037, Cohen’s d=1.0, 95% CI 0.01–1.84). SZ+THC
and SZ – THC did not differ in white-matter volume
(p=0.20), yet the difference between these groups
showed a medium effect size (Cohen’s d=0.64, 95%
CI –0.39 to 1.61). The THC group did not differ in
white-matter volume from either of the schizophrenia
White-matter differences between THC and CON and
SZ+THC and CON remained significant when life-
time estimates of exposure to alcohol and tobacco
were controlled (THC versus CON: t=2.28, p=0.029;
SZ+THC versus CON: t=2.43, p=0.02), but the dif-
ference between SZ – THC and CON was no longer
significant (p=0.09). GAF did not correlate with cer-
ebellar volumetric measures (p> 0.13), but the HAMD
score correlated inversely with both white-matter (p=
0.058) and total cerebellar volume (p=0.01), but not
grey matter (p=0.60) in the entire sample. Controlling
for HAMD in the analysis retained the significant
group differences for white matter (THC versus CON:
t=2.73, p=0.01; SZ+THC versus CON: t=2.96,
p=0.005; SZ – THC versus CON: t=1.94, p=0.06).
SZ – THC:p=0.45).
Fig. 1. Cerebellar total ( ), grey-matter ( ) and white-matter
(%) volumes by group (corrected for intracranial cavity).
2352N. Solowij et al.
An overall interactionbetween schizophrenia
diagnosis and cannabis use status did not reach sig-
nificance for white-matter volume [F(1, 38)=1.15,
p=0.29], but the main effect of cannabis use (regard-
less of diagnosis) was highly significant [F(1, 38)=
7.76, p=0.008]. The main effect of diagnosis (schizo-
phrenia versus healthy sample regardless of cannabis
use) was also significant [F(1, 38)=4.31, p=0.045].
Total cerebellar volume correlated marginally and
inversely with the duration of regular cannabis use in
healthy cannabis users (r=–0.49, p=0.06). Age also
correlated inversely with total cerebellar volume in
this subgroup (r=–0.53, p=0.04), but not in any
other subgroup nor in the overall combined sample
(r=–0.19, p=0.20). Partial correlations in THC alone
showed that neither age nor duration of cannabis use
remained significantly correlated with total volume
after controlling for the other, suggesting that both
increasing age and duration of exposure to cannabis
may be related to smaller cerebellar volume. Despite
the association between duration of use and total cer-
ebellar volume in healthy users, no such relationship
was apparent in the SZ+THC group (p > 0.70). Age
also correlated inversely with white-matter volume in
the overall combined sample (r=–0.40, p=0.007), with
a trend in healthy controls (r=–0.50, p=0.07) but
not in the other subgroups. The groups did not
differ in age and the differences between groups in
white-matter volume remained significant after con-
trolling for the effect of age [F(3, 36)=3.14, p=0.037].
No other cannabis use measures correlated with any
measure of cerebellar volume in either THC or
SZ+THC or the combined cannabis-using sample.
The SAPS composite score correlated positively
with white matter in the SZ+THC group (Spearman’s
r=0.72, p=0.022) but inversely with total volume in
the SZ–THC group (Spearman’s r=–0.70, p=0.018).
No associations between SAPS composite scores and
cerebellar volumes were evident in the healthy can-
nabis users, and SANS composite scores did not
correlate with cerebellar volumes in any group. The
duration of illness correlated significantly and in-
versely with total cerebellar volume in the SZ – THC
group only (r=–0.71, p=0.032), with a trend apparent
also for grey matter (r=–0.69, p=0.06). No trends
in this direction were apparent in SZ+THC (total:
p=0.31; grey matter: p=0.90). After controlling for
differences in duration of illness, a trend towards
a difference between SZ+THC and SZ – THC in
white-matter volume emerged [F(1, 11)=3.25, p=0.09]
(smaller in SZ+THC) but there were no differences
in grey matter (p=0.51) or total volume (p=0.26). In
the SZ–THC group, there were also trends towards
smaller total cerebellar volume (r=0.62, p=0.078)
and smaller grey-matter volume (r=0.69, p=0.058) the
earlier the age at onset of illness, with no such
Cerebellar white-matter volume (mm3)
Fig. 2. Cerebellar white-matter volume by group (corrected for intracranial cavity and adjusted for differences in alcohol
and tobacco use).
Cannabis, schizophrenia and cerebellar alterations2353
association in SZ+THC (total: p=0.86; grey matter:
p=0.51). Given these bidirectional differences be-
tween SZ+THC and SZ – THC, we performed a sub-
sequent analysis in which clinically relevant variables
(duration of illness, SAPS, SANS, GAF and HAMD
scores, and alcohol and tobacco use measures) were
included as covariates in the analysis, and a significant
difference in white matter emerged between these
schizophrenia groups [F(1, 7)=7.33, p=0.03].
The primary finding of this study is of significantly
smaller cerebellar white-matter volume in cannabis
users compared to non-users, with the greatest
reduction relative to healthy controls evident in
schizophrenia patients with co-morbid cannabis use.
White-matter volume was 23.9% smaller in healthy
cannabis users and 29.7% smaller in schizophrenia
patients who used cannabis. Our analyses indicate
that cannabis use and schizophrenia are both inde-
pendently associated with smaller cerebellar white-
matter volume; schizophrenia patients who did not
use cannabis also showed a 17.7% reduction in white
matter relative to healthy controls. However, the re-
sults suggest that cannabis use may confer a relatively
greater adverse effect on cerebellar white matter than
schizophrenia. Effect size analyses also indicated that
the largest effect observed (i.e. the greatest reduction
in cerebellar volume relative to healthy controls) was
when cannabis use was co-morbid with schizo-
phrenia. To our knowledge, this is the first report
anomalies in association with cannabis use in chronic
schizophrenia patients and in otherwise healthy
adults. As a cross-sectional investigation, however,
it cannot be determined whether these anomalies
resulted from or preceded cannabis use.
Integration with other studies of brain structure
in cannabis users
Our findings accord in general with three recent
studies that indicate brain structural alterations in
cannabis-using first-episode psychosis patients and,
more specifically, with growing observations of white-
matter anomalies in otherwise healthy cannabis users.
In first-episode psychosis patients, decreased grey-
matter volumes of the anterior cingulate (Szeszko et al.
2007), right posterior cingulate cortex and left hippo-
campus (Bangalore et al. 2008) were reported among
those who used cannabis compared to their non-using
counterparts and to healthy controls. Trends towards
smaller left and right cerebellar volumes were also
apparent (Bangalore et al. 2008). Rais et al. (2008)
reported more pronounced total cerebral grey-matter
volume reduction over 5 years in first-episode schizo-
phrenia patients who used cannabis compared to
those who did not (2.67%) and also compared to
healthy controls (5.09%), with greater lateral and third
ventricle enlargements. The results were suggested to
explain some of the detrimental effects of cannabis use
in schizophrenia patients.
In a recent study of otherwise healthy cannabis-
using adolescents (28-day abstinent), Medina et al.
(2010) reported larger cerebellar inferior posterior
vermis volumes relative to controls and these were
associated with poorer executive function. However,
we are not able to compare our findings directly with
this latter study as we did not parcellate the vermis,
Medina et al. (2010) were unable to parcellate white
matter from grey matter (given their lower resolution
MRI protocols), there are large age differences be-
tween the samples, and we also included chronic
schizophrenia patients. In a previous study, Medina
et al. (2007) found an association between whole-brain
white-matter volume and depressive symptoms on the
HAMD in cannabis-using adolescents. A similar re-
lationship with cerebellar white-matter volume was
revealed in the overall combined sample of this study,
but white-matter volume remained significantly re-
duced in cannabis users after controlling for HAMD
scores, which were not in the clinically significant
range. Whole-brain white-matter volume did not
differ between groups in our study, and differences in
cerebellar white-matter volume were retained after
controlling for whole-brain white-matter volume,
Pathology in white-matter structural integrity has
recently been reported in diffusion tensor imaging
(DTI) studies of young adult (Arnone et al. 2008; Allin
et al. 2009) and adolescent (Ashtari et al. 2009) cannabis
users in the corpus callosum and various fronto-
temporal, occipitofrontal and posterior connections
that develop during adolescence. It is suggested that
cannabis use, particularly during adolescence, may
affect the trajectory of normal brain maturation
resulting in white-matter aberrations.
White-matter changes may reflect an altered
trajectory of normal development or premature
In our sample, regular cannabis use commenced
around age 19–20, but initiation to cannabis use
occurred a year or two prior to regular use, and some
participants commenced regular use as early as age
12–13. Neurodevelopmental processes such as myeli-
nation, dendritic proliferation and synaptogenesis
in the cerebellum are thought to occur through
2354 N. Solowij et al.
Cerebellar grey matter has been shown to decrease
whereas white matter increases between the ages of 15
and 19 in healthy adolescents (Parker et al. 2008). The
cerebellum reaches maturity late, with changes occur-
ring through the late 20s and early 30s, akin to the late
development of prefrontal cortex. There is evidence
that the developing brain may be particularly sensitive
to the effects of drugs and substance abuse, resulting
in aberrant brain developmental processes (Lubman
et al. 2007). Whether the reduction in white matter that
we report in cannabis users with and without schizo-
phrenia may be interpreted in this manner requires
further prospective research.
Smaller white-matter volume might also reflect
premature ageing. Cerebellar white-matter volume
gradually declines between the ages of 18 and 99 and
more rapidly than grey matter (Andersen et al. 2003;
Pieperhoff et al. 2008). Total cerebellar volume in the
healthy cannabis users of our study decreased with
the duration of regular cannabis use, and with age,
which may give credence to premature ageing effects
in association with cannabis use. Because white-matter
volume did not correlate with any specific measure
of cannabis use, the findings cannot be interpreted
as dose related. It remains possible that smaller cer-
ebellar white-matter volume preceded cannabis use
and may somehow be related to a propensity or pre-
disposition to use cannabis. Longitudinal studies
are required before these results could be interpreted
as a true reduction, implying change from a baseline
adolescenceand young adulthood.
Potential mechanisms by which cannabis may
impact white matter
Credence to our interpretation that cannabis use
interferes with white-matter development is given by
evidence that chronic exposure to cannabinoids alters
genes involved in neuronal growth and myelination
(Grigorenko et al. 2002), genes that are also known to
be altered in chronic schizophrenia (Hakak et al. 2001).
An abundance of cannabinoid receptors in the de-
veloping nervous system, and particularly on neural
fibre tracts in white-matter progenitor cell regions,
suggests that the endocannabinoid system is involved
in regulating the structural and functional maturation
of the nervous system, including a demonstrated
role in neurogenesis, glial cell formation, neuronal
migration, axonal elongation and myelin formation
(Berghuis et al. 2007; Fride, 2008). Oligodendrocytes
receptors and oligodendrocyte dysfunction is also
implicated in schizophrenia (Tkachev et al. 2003).
regular exposure during adolescence and early adult-
hood might suppress oligodendrocyte function, re-
sulting in decreased myelination. Furthermore, recent
research showing that tetrahydrocannabinol (THC)
accumulates primarily in neurons but that trans-
formation to its metabolite THC-COOH depends on
the presence of glia suggests that the adverse effects of
cannabinoids on the brain may occur through a com-
bination of pathways involving cannabinoid receptor
activation, accumulation of cannabinoids and their
metabolites, and upregulation of neuro-inflammatory
cytokines (Monnet-Tschudi et al. 2008). Notably, some
cytokines (e.g. interleukin-1) promote demyelination
of neuronal axons and cannabinoids have been shown
to modulate this system (Molina-Holgado et al.
2003), which may be dysfunctional following chronic
exposure to cannabis.
Links with development of psychosis
Alterations in white matter may also underlie the
propensity of cannabis to cause psychosis (Allin et al.
2009). A recent study found evidence of a different
pattern of white-matter development in adolescents
and young adults at high risk for psychosis and that
aberrant white-matter integrity was predictive of func-
tional outcome (Karlsgodt et al. 2009). Another study
found a trend towards reduced white matter in the
right posterior lobe of the cerebellum in a prodromal
group who went on to develop psychosis compared to
their counterparts who did not develop psychosis,
yet both groups showed increases in cerebellar white-
matter volume over a 12- to 18-month follow-up
period, with concomitant decreases in total cerebellar
volume and grey matter (Walterfang et al. 2008).
The authors discussed these findings in terms of pro-
gressive changes occurring in the cerebellum in an
at-risk mental state, regardless of subsequent devel-
opment of psychosis. The mean age of our healthy
cannabis-using sample was near 40 years, making it
unlikely that they were in a prodromal state at the time
of our assessments and unlikely that these individuals
would develop psychosis if they had not done so thus
far in their almost 20-year history of heavy cannabis
use. However, they had developed changes in the
brain, in cerebellar white matter (this study) and in
hippocampal and amygdala volumes (Yu ¨cel et al.
2008), and also subclinical positive and negative psy-
chotic symptoms and memory deficits (Yu ¨cel et al.
2008), similar to those evident in schizophrenia.
Together these features resemble an at-risk mental
state, which we surmise to be associated with their
very long-term and heavy cannabis use.
Cannabis, schizophrenia and cerebellar alterations2355
White-matter anomalies and phenomenological
differences between chronic schizophrenia patients
with and without cannabis use
In accord with previous studies of white-matter
anomalies in schizophrenia (Davis et al. 2003), we
found smaller cerebellar white matter in our schizo-
phrenia sample. The largest effect size relative to
healthy non-user controls was observed in the SZ+
THC group (the smallest white-matter volume of
all groups studied), suggesting a greater impact of
cannabis in this clinical population. Furthermore,
phenomenological differences were observed between
the SZ+THC and SZ – THC groups. Cannabis users
with schizophrenia had non-significantly greater posi-
tive and negative symptom scores than schizophrenia
non-users, and the groups differed in the associations
between symptomatic or illness-related measures and
cerebellar measures. Smaller cerebellar grey matter
has been reported in association with longer duration
of illness in schizophrenia (Premkumar et al. 2008). In
our study, smaller total cerebellar volume correlated
with increased duration of established schizophrenia
only in the patients who did not use cannabis (SZ –
THC). In SZ–THC, greater positive symptoms were
also associated with smaller total cerebellar volumes.
By contrast, positive symptoms in SZ+THC were
associated with larger white-matter volume. This is
difficult to reconcile with the smaller white matter
observed in this cannabis-using group, which was
significantly smaller relative to patients without
cannabis use when duration of illness and symptoms
were covaried in the analysis. These results in general
suggest differing pathophysiological processes and
functional outcomes in schizophrenia with and with-
out co-morbid cannabis use. Cannabis use may alter
the course of brain changes in schizophrenia. Alterna-
tively, people with schizophrenia who use cannabis
may differ in phenomenological traits and/or geno-
types that confer differing vulnerabilities. The small
sample sizes of our study dictate a need for repli-
cation, but credence to our findings is given by other
evidence that the cerebellum is associated with posi-
tive psychotic symptoms (Levitt et al. 1999; Whalley
et al. 2007; Picard et al. 2008). The elevated positive and
negative psychotic symptoms in the healthy cannabis
users of our study were not associated with cerebellar
volume measures. We previously reported an associ-
ation in this same cohort between subclinical positive
psychotic symptoms and reduced left hippocampal
volume (Yu ¨cel et al. 2008). Differing relationships be-
tween cannabis use indices (e.g. duration of use) and
cerebellar volumetric measures in healthy cannabis
users compared to users with schizophrenia also
suggest potential differences in pathophysiological
processes associated with cannabis use in the two
Limitations and conclusions
Our findings must be interpreted with caution given
the small sample sizes and replication is required.
However, our samples were unique in terms of their
extensive cannabis use histories (5–7 joints per day on
average for o10 years; mean 18–20 years use) and
absence of significant other drug use, neurological or
other psychiatric confounds. Furthermore, the large
effect sizes observed indicate that the results are ro-
bust and reproducible. As this was a cross-sectional
study, it is not possible to determine whether smaller
cerebellar white-matter volume may have preceded
cannabis use and somehow be related to a propensity
or predisposition to use cannabis. However, total
cerebellar volume in the cannabis users of this study
decreased with the duration of cannabis use, suggest-
ing that our findings could be conjectured as sequelae
to this long-term heavy exposure to the drug. The po-
tential effect of long-term treatment with antipsychotic
medications in the patient samples is unknown and
may also interact with exposure to cannabis. In this
study we only examined grey-matter, white-matter
and total cerebellar volume, and not the vermis, and
MRI cannot differentiate between cerebellar white
matter and the deep output nuclei buried within,
which would have been included in our white-matter
volume estimates. Further studies parcellating the
cerebellum into subregions, replication studies with
larger samples, and longitudinal studies are required
to better understand and interpret the complex effects
of cannabis on the cerebellum that have been sug-
gested in this study, in both healthy cannabis users
and people with schizophrenia who also use cannabis.
In conclusion, this research adds to the growing
body of evidence that cannabis use may alter brain
structure and function, and demonstrates adverse
effects associated with long-term heavy cannabis use
on cerebellar structural integrity. Cerebellar white-
matter volume was smaller in cannabis users than in
non-users and a greater reduction relative to healthy
non-users was observed in cannabis users with
schizophrenia. These findings may be explained by
aberrant neurodevelopmental processes associated
with cannabis exposure in adolescence or young adult-
hood, but may also reflect premature ageing effects.
White-matter pathology has been suggested to play
a primary role in the cognitive deficits observed in
schizophrenia, which are thought to arise due to faulty
circuits (Wexler et al. 2009). As white matter is
an anatomical substrate for connectivity, similar
2356 N. Solowij et al.
functional connectivity disturbances may underlie the
cognitive deficits observed in long-term heavy canna-
bis users. Differing associations between cerebellar
measures and psychotic symptoms and duration of
illness in users versus non-users with schizophrenia
suggest different functional consequences of cannabis
use in relation to disease processes within the dis-
order. White-matter loss may underlie the propensity
for cannabis use to cause psychosis in vulnerable
individuals and contribute to a poorer course of illness
in patients who use.
This research was supported by grants from the Clive
and Vera Ramaciotti Foundation, the Schizophrenia
Research Institute utilizing infrastructure funding
from NSW Health, the National Health and Medical
Research Council of Australia (Grant 459111) and the
University of Wollongong. The study was also sup-
ported by the Australian Schizophrenia Research
Bank (ASRB), which is supported by the National
Health and Medical Research Council of Australia,
the Pratt Foundation, Ramsay Health Care, the
Viertel Charitable Foundation and the Schizophrenia
Research Institute. Dr Yu ¨cel is supported by a
National Health and Medical Research Council
Clinical Career Development Award (Grant 509345).
Dr Whittle is supported by an Australian Research
Dr Lubman is supported by the Colonial Foundation.
Scans were performed at the Symbion Clinical
Research Imaging Centre, Prince of Wales Medical
Dr R. Shnier. Neuroimaging analysis was facilitated
by the Neuropsychiatry Imaging Laboratory managed
by B. Soulsby at the Melbourne Neuropsychiatry
Centre and supported by Neurosciences Victoria.
Portionsof this work
14th Annual Meeting of the Organization for Human
Brain Mapping, Melbourne, June 2008.
were presented atthe
Declaration of Interest
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