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Effects of cannabidiol on brain excitation and inhibition systems; a randomised placebo-controlled single dose trial during magnetic resonance spectroscopy in adults with and without autism spectrum disorder


Abstract and Figures

There is increasing interest in the use of cannabis and its major non-intoxicating component cannabidiol (CBD) as a treatment for mental health and neurodevelopmental disorders, such as autism spectrum disorder (ASD). However, before launching large-scale clinical trials, better understanding of the effects of CBD on brain would be desirable. Preclinical evidence suggests that one aspect of the polypharmacy of CBD is that it modulates brain excitatory glutamate and inhibitory γ-aminobutyric acid (GABA) levels, including in brain regions linked to ASD, such as the basal ganglia (BG) and the dorsomedial prefrontal cortex (DMPFC). However, differences in glutamate and GABA pathways in ASD mean that the response to CBD in people with and without ASD may be not be the same. To test whether CBD ‘shifts’ glutamate and GABA levels; and examine differences in ASD, we used magnetic resonance spectroscopy (MRS) to measure glutamate (Glx = glutamate + glutamine) and GABA+ (GABA + macromolecules) levels in 34 healthy men (17 neurotypicals, 17 ASD). Data acquisition commenced 2 h (peak plasma levels) after a single oral dose of 600 mg CBD or placebo. Test sessions were at least 13 days apart. Across groups, CBD increased subcortical, but decreased cortical, Glx. Across regions, CBD increased GABA+ in controls, but decreased GABA+ in ASD; the group difference in change in GABA + in the DMPFC was significant. Thus, CBD modulates glutamate-GABA systems, but prefrontal-GABA systems respond differently in ASD. Our results do not speak to the efficacy of CBD. Future studies should examine the effects of chronic administration on brain and behaviour, and whether acute brain changes predict longer-term response.
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Effects of cannabidiol on brain excitation and inhibition
systems; a randomised placebo-controlled single dose trial
during magnetic resonance spectroscopy in adults with and
without autism spectrum disorder
Charlotte Marie Pretzsch
, Jan Freyberg
, Bogdan Voinescu
, David Lythgoe
, Jamie Horder
, Maria Andreina Mendez
Robert Wichers
, Laura Ajram
, Glynis Ivin
, Martin Heasman
, Richard A. E. Edden
, Steven Williams
, Declan G. M. Murphy
Eileen Daly
and Gráinne M. McAlonan
There is increasing interest in the use of cannabis and its major non-intoxicating component cannabidiol (CBD) as a treatment for
mental health and neurodevelopmental disorders, such as autism spectrum disorder (ASD). However, before launching large-scale
clinical trials, a better understanding of the effects of CBD on brain would be desirable. Preclinical evidence suggests that one
aspect of the polypharmacy of CBD is that it modulates brain excitatory glutamate and inhibitory γ-aminobutyric acid (GABA) levels,
including in brain regions linked to ASD, such as the basal ganglia (BG) and the dorsomedial prefrontal cortex (DMPFC). However,
differences in glutamate and GABA pathways in ASD mean that the response to CBD in people with and without ASD may be not
be the same. To test whether CBD shiftsglutamate and GABA levels; and to examine potential differences in this response in ASD,
we used magnetic resonance spectroscopy (MRS) to measure glutamate (Glx =glutamate +glutamine) and GABA+(GABA +
macromolecules) levels in 34 healthy men (17 neurotypicals, 17 ASD). Data acquisition commenced 2 h (peak plasma levels) after a
single oral dose of 600 mg CBD or placebo. Test sessions were at least 13 days apart. Across groups, CBD increased subcortical, but
decreased cortical, Glx. Across regions, CBD increased GABA+in controls, but decreased GABA+in ASD; the group difference in
change in GABA +in the DMPFC was signicant. Thus, CBD modulates glutamate-GABA systems, but prefrontal-GABA systems
respond differently in ASD. Our results do not speak to the efcacy of CBD. Future studies should examine the effects of chronic
administration on brain and behaviour, and whether acute brain changes predict longer-term response.
Neuropsychopharmacology (2019) 0:18;
Autism spectrum disorder (ASD) affects up to 1 in 59 individuals
[1]. Of those affected, 70% also have co-occurring conditions such
as epilepsy [2], and mood and anxiety disorders [3]. This incurs a
high cost to the individual and society: on average the lifespan of
individuals with ASD is reduced by 20 years [4]. Given the lack of
effective pharmacological treatments, researchers have therefore
begun to explore alternative options. These include cannabis and
its major non-intoxicating component cannabidiol (CBD), which is
derived from the cannabis sativa plant [5].
CBD has already been trialled in several disorders. For instance,
preliminary evidence suggests that CBD may improve spasticity
[6], pain, sleep disturbances [7], and mobility [8] in multiple
sclerosis (MS); and alleviate anxiety symptoms in social phobia [9].
Moreover, alongside anecdotal accounts and case series reports of
benets from medical marijuana in ASD [10], there is evidence
that CBD: (i) reduces seizure frequency in two epilepsy syndromes
associated with autistic symptoms: Dravet Syndrome and
LennoxGastaut syndrome [1113]; and (ii) improves ASD-like
social decits in a mouse model of Dravet Syndrome [14]. This
suggests that CBD may be worth further investigation in
idiopathic ASD. However, before embarking on large-scale clinical
trials, a better understanding of how CBD acts on the human
brain, and especially in ASD, would be desirable.
CBD has multiple targets, but one aspect of its polypharmacy
may be to help regulate excitatory glutamate (E) and inhibitory γ-
aminobutyric acid (GABA) (I) transmission, which may inuence
the activity of excitatory and inhibitory signalling pathways: For
example, CBD facilitates glutamate and GABA neurotransmission
across the brain through agonism at the transient receptor
potential vanilloid type 1 (TRPV1) receptor [15,16]. Moreover, CBD
may increase GABAergic transmission by antagonism at the G
protein-coupled receptor 55 (GPR55), and especially in the basal
ganglia [14] (BG). In contrast, CBD is thought to be an agonist at
prefrontal 5-HT1A receptors, where it suppresses glutamate and
GABA transmission [17,18]. In sum, CBD may act on targets
Received: 18 September 2018 Revised: 14 January 2019 Accepted: 19 January 2019
Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, Kings College London, London, UK;
Department of
Neuroimaging Sciences, Institute of Psychiatry, Psychology & Neuroscience, Kings College London, London, UK;
South London and Maudsley NHS Foundation Trust Pharmacy,
London, UK and
Russel H Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institutions, Baltimore, MD, USA
Correspondence: Gráinne M. McAlonan (
These authors contributed equally: Declan G. M. Murphy, Eileen Daly, Gráinne M. McAlonan
©The Author(s) 2019
throughout the brain, but especially in the BG and the prefrontal
cortex. These actions of CBD upon glutamate-GABA pathways may
be especially important in ASD, where post mortem, genetic, and
in vivo proton magnetic resonance spectroscopy (MRS) studies
have shown abnormalities in both prefrontal and BG glutamate
and GABA pathways [1921]; both regions have also been
repeatedly linked to ASD core symptoms [21,22]. Thus, CBD
could well impact on prefrontal and BG Glx and GABA levels in
ASD, but not necessarily in the same manner as in unaffected
individuals (with intact glutamate-GABA systems). However, no-
one has investigated this directly.
Therefore, in this study, we tested the hypotheses that CBD
impacts on human in vivo glutamate and GABA levels in the BG
and dorsomedial prefrontal cortex (DMPFC); but that the response
is atypical in ASD. To achieve this, we compared MRS measures of
glutamate and GABA in men with and without ASD following a
single oral dose of 600 mg CBD or a matched placebo (at least
2 weeks apart) in a randomised double-blind, cross-over design.
This research was conducted in accordance with the Declaration
of Helsinki, at the Institute of Psychiatry, Psychology, and
Neuroscience (IoPPN) at De Crespigny Park, SE5 8AF, London,
UK (August 2016 to August 2018). The Medicines and Health
Research Authority (MHRA) in the UK conrmed the study design
was not a Clinical Trial and ethical approval for this study was
provided by the Kings College London Research Ethics Commit-
tee, study reference HR15/162744. All participants provided
written informed consent. Every participant took part in all
aspects of this case-control study.
This placebo-controlled, randomised, double-blind, repeated-
measures, cross-over case-control study was conducted as part of
a larger investigation into the role of phytocannabinoids in ASD; (identier: NCT03537950, entry name: HR15-
162744). Placebo (PLC) or CBD was allocated in a pseudo-
randomised order, so that approximately half in each group
attended a placebo visit before CBD; and half attended a CBD visit
before placebo. The randomisation was implemented by Prof
McAlonan using Participants and
researchers directing the study were blind to the assignment.
Participants attended for two visits. To allow for drug wash-out,
visits were separated each by a minimum of 13 days, with all
attempts made to keep between-visit time consistent across all
visits and participants. Moreover, the acquisition of data from both
groups was mostly overlapping during the same period. On each
visit, urine samples were taken to screen for illicit substances (a full
list is included below). Subsequently, participants underwent a
brief health check, received a liquid oral dose of the pharmaco-
logical probe (600 mg of CBD; in line with previous single dose
studies of CBD adults (e.g. [23]) or a matched placebo, both
provided by GW Research Ltd, Cambridge, UK), and a second brief
health check to test for potential acute adverse reactions/side
effects. Participants underwent scanning timed to coincide with
peak plasma (2 h) concentration. After the scan, participants
received a third health check to ensure they had experienced no
ill-effects and were t to leave the department.
Potential participants were excluded if they had a comorbid major
psychiatric or medical disorder affecting brain development (e.g.
schizophrenia or epilepsy), a history of head/brain injury, a genetic
disorder associated with ASD (e.g. tuberous sclerosis or Fragile X
syndrome), or an IQ below 70. We also excluded participants who
were reliant on receiving regular medication known to directly
modulate glutamate and GABA systems. However, we included
participants on other medications which are commonly prescribed
in ASD: one person with ASD who took a single dose of Ritalin on
the morning of each study visit, and one person with ASD who
took a single dose of sertraline on the morning of each study visit.
We asked participants to abstain from using cannabis and/or other
illicit substances in the month prior to scanning, and from drinking
alcohol on the day prior to testing. We also carried out Urine Drug
Screening on each test day. Data from individuals who screened
positive for these substances were excluded. Thus, we initially
retained data from 34 subjects (neurotypical control n=17, ASD
n=17) (see Table 1for demographics); this sample size was
sufcient to detect a 10% E-I shift (where shiftmeans a change in
a component of the Glx-GABA metabolite pool) at a power of 0.8
and a signicance level of α=0.05, based on a power analysis
using previous ndings in the department [19]. All participants
had an IQ over 70. All participants in the ASD group had a clinical
diagnosis of ASD made according to ICD10 research criteria
[2426], and severity of symptoms was conrmed using standar-
dised research diagnostic instruments (Autism Diagnostic Obser-
vation Schedule, ADOS; and Autism Diagnostic Interview-Revised,
Imaging data acquisition
All imaging data were acquired on a 3T GE Excite II magnetic
resonance imaging (MRI) scanner (GE Medical Systems, Milwau-
kee, WI, USA). The scanning protocol included a structural MRI
scan acquired using a 3D inversion recovery prepared fast spoiled
gradient recalled (IR-FSPGR) sequence (slice thickness =1.1 mm,
spatial positions =124, ip angle =20°, eld of view (FoV) =280
mm, echo time (TE) =2.844 ms, repetition time (TR) =7.068 ms,
inversion time =450 ms, matrix =256 × 256). This structural scan
was conducted to obtain information used during the preproces-
sing of the spectroscopy scan. The scanning protocol further
included a spectroscopy scan based on the MEshcher-GArwood
Point RESolved Spectroscopy (MEGA-PRESS) sequence [27]. We
acquired data (44 averages) from two voxels: the rst was
positioned in the BG (echo time (TE) =68 ms, repetition time (TR)
=1800 ms, voxel size =35*30*25 mm
This voxel was placed with the anterior border initially abutting
the anterior portion of the left lentiform nucleus, and as medial as
possible, to avoid the ventricles as much as possible. Thus, taking
Table 1. Participant demographics for all subjects are reported including standard deviations (except for N)
Demographic measure TD ASD F(dof) p-value
N(M/F) 17 (17/0) 17 (17/0)
Age in years 28.47 (6.55) 31.29 (9.94) F(1) =0.956 p=0.335
Days between visits 34.82 (24.99) 36.44 (20.53) F(1) =0.041 p=0.841
FSIQ 124.59 (12.7) 111.35 (18.80) F(1) =5.781 p=0.022
Signicant between-group differences are highlighted in bold
ASD autism spectrum disorder, F(dof) F statistic and degrees of freedom, Ffemale, FSIQ full scale intelligence quotient, Mmale, N, participant number, TD
typically developing individuals
Effects of cannabidiol on brain excitation and inhibition systems; a. . .
CM Pretzsch et al.
Neuropsychopharmacology (2019) 0:1 – 8
into account slight inter-individual anatomical differences, this
voxel was on average composed as follows: the white matter
(WM), primarily included the internal capsule and part of the
corpus callosum. The grey matter (GM), included the BG [~55%],
the thalamus [~25%] and the insula [~20%].
The second voxel was positioned in the DMPFC (TE =68 ms,
TR =2000 ms, voxel size =25*40*30 mm
). This voxel was placed
in the midline, avoiding the corpus callosum. Resultantly, given
inter-individual variance, this voxel was composed as follows: the
WM included the corpus callosum and cingulum; while the GM
included the anterior part of the cingulate gyrus.
Representative voxel positions are shown in Fig. 1.
Urine test
To evaluate presence or absence of illicit substances that could
confound potential effects of the pharmacological probes tested
in this study, we performed liquid chromatography-mass spectro-
metry (LC-MS) analysis on urine samples provided by each
participant before the drug administration. Participants that
showed positive results for any of the drugs tested, including
Amphetamines (Amphetamine, Methamphetamine, MDMA/
Ecstasy), Benzodiazepines, Cannabis, Cocaine (as benzoylecgo-
nine), Methadone and its metabolite EDDP, and Opioids
(6-Monoacetylmorphine, Morphine, Codeine, Dihydrocodeine),
were excluded from the analysis, resulting in the exclusion
of four subjects (two controls, two ASD) from the original sample.
Data processing
Structural data processing. T1-weighted structural MRI volumes
were inspected manually to ensure adequate signal-to-noise ratio
(SNR) and absence of motion artefacts. Subsequently, structural
volumes were normalised to Montreal Neurological Institute (MNI)
space, and segmented into GM, WM, and CSF, to obtain
percentage measures of tissue composition in each individual
MRS voxel, using positional coordinates embedded in the raw
spectra data les.
MRS data processing. MRS data were pre-processed using in-
house scripts adapted from FID-A [28], which prepared the data
for reading into the main processing software. This included
conversion of data to the required le format, combination of
receiver channels, removal of badaverages (>4 standard devia-
tions), frequency drift correction (alignment of averages), separa-
tion and visualisation of the edit on/off spectra, and their
subtraction to generate the difference spectrum. Each spectrum
was manually inspected to ensure adequate SNR, as well as the
absence of artefacts [26,28]. Representative example spectra are
displayed in Fig. 1.
MRS data were then processed using LCModel v6.3-1 L software
(Stephen Provencher Incorporated, Oakville, Canada). LCModel
uses a linear combination of model spectra derived from
metabolite solutions in vitro to analyse the major resonances of
in vivo spectra. For this analysis, we used a basis set (mega-press-
3T-1) to determine the concentrations of GABA+(which
comprises GABA plus macromolecules), glutamine, glutamate,
glutathione (GSH), N-acetyl-aspartate (NAA), N-acetyl-
aspartylglutamate (NAAG), NAA +NAAG, Glx (Glu +Gln), and
GSH +Glu +Gln in each voxel; however, for this analysis, we
focused solely on GABA+and Glx.
In MRS, partial volume effects (different proportions of GM, WM,
and CSF in the MRS voxels) are a potential confound, especially
given previously reported volumetric differences between autistic
and neurotypical individuals [29]. To account for partial volume
effects, we therefore corrected all metabolites for GM, WM, and
CSF percentages. Assuming that CSF only contains negligible
quantities of the metabolites of interest, the calculations were as
follows: LCModel assumes a voxel is 100% WM with a water
concentration (WCONC) of 35880 mM and corrects each metabo-
lite value (where F stands for fraction) using the factor:
). To correct for
the value of water concentration being used in the processing
through LCModel, we divided values by an individual correction
factor (35880), arriving at (1.207*F
Fig. 1 Magnetic resonance spectroscopy (MRS) representative voxel placement and example spectra. aMRS voxel of interest (outlined in
white) in the basal ganglia and the dorsomedial prefrontal cortex. bExample spectroscopy spectra from each voxel. Glx glutamate +
glutamine, GABA +γ-aminobutyric acid +macromolecules, NAA N-acetyl-aspartate, p.p.m parts per million
Effects of cannabidiol on brain excitation and inhibition systems; a. . .
CM Pretzsch et al.
Neuropsychopharmacology (2019) 0:1 – 8
Therefore, in summary, the corrected metabolite values were
obtained by multiplying the raw metabolite values by this
correction. Since we did not measure relaxation times for tissue
water and metabolites, these were not corrected forwith the
exception of assuming the tissue water relaxation time (T
ms) [30].
To further ensure the robustness of our ndings, we excluded
all measurements of GABA+and Glx (Glx =glutamate +gluta-
mine) where the LCModel Cramér-Rao lower bound (CRLB)
estimates exceeded 15% from further analysis (LCModel manual,
Stephen Provencher Incorporated, Oakville, Canada). This resulted
in the exclusion of a total of eleven data points from six ASD
participants from the original sample. The spread across voxels
and conditions (placebo/CBD) was as follows: 1: BG Glx
& Glx
& Glx
& Glx
; 5 (also excluded due to positive
drug screening): DMPFC GABA +
& Glx
; 6: DMPFC Glx
Statistical analysis
Demographic measures (age, IQ) and baseline levels of Glx and
GABA+in each region of interest were compared using a one-way
ANOVA (signicance level p< 0.05).
To test the primary hypothesis that CBD impacts on E-I balance
in our two brain regions of interest (BG and DMPFC), differences in
mean metabolite concentrations were calculated using two 2 ×
2 × 2 mixed-model ANOVAs with group (neurotypicals, ASD) as
between-subject factor, voxel (BG, DMPFC) and drug (PLC, CBD) as
within-subject factors, and the respective metabolite (Glx, GABA+)
as the dependent variable. Our planned comparisons tested a
priori predictions that CBD would impact upon Glx and GABA+;
and that there would be differences in the response of
participants with and without ASD. With the caveat that
Bonferroni testing can be overly conservative, for completeness
however, we also report a Bonferroni corrected p-value alongside
any signicant (uncorrected) results.
However, this repeated-measures approach is impacted by
missing data (one missing/poor quality data point from either
voxel during either placebo or drug condition results in data from
that individual being omitted); also there is a possibility that our
results were inuenced by the different T1-weighting in the
cortical and subcortical voxels. Therefore, following this overall
analysis we conducted secondary post hoc two-by-two mixed-
model ANOVAs with group (neurotypicals, ASD) as a between-
subject factor, and drug (PLC, CBD) as a within-subject factor for
each metabolite in each region separately and examined any
group difference in the change in each using as much of the
available data as possible. Thus, for Glx measures in both BG and
DMPFC, ASD n=13, neurotypicals n=17; for GABA+measures in
the DMPFC, ASD n=11, neurotypicals n=17; and for GABA+
measures in BG, ASD n=16, neurotypicals n=17.
All analyses were performed using SPSS 24.00 software (SPSS,
Chicago, IL, USA). Graphs displaying results were produced using
GraphPad Prism version 7 for Mac, GraphPad Software, La Jolla,
Groups did not differ signicantly in age (F(1) =0.956, p=0.335);
but, as is commonly reported, individuals with ASD had a slightly
lower IQ than neurotypical controls, and this difference was
signicant (F(1) =5.781, p=0.022) (as summarised in Table 1).
Therefore, to be sure that our ndings were not inuenced by IQ,
we investigated the relationship between drug-induced shifts
(CBD-PLC) in metabolite levels (Glx and GABA+) and IQ. As
expected, there were no signicant correlations across the whole
group (r< 0.095, p> 0.350), in ASD alone (r<0.008, p> 0.698)
nor in the neurotypicals alone (r< 0.068, p> 0.235), suggesting
that the difference in IQ did not inuence the results. No
participant experienced any subjective or objective ill-effects/
harm following administration of the study drug.
Tissue composition and data quality
Tissue percentage (not excluding omitted spectra) differed
between groups for BG PLC GM (F(1) =7.307, p=0.011) and for
BG PLC WM (F(1) =9.345, p=0.004), but not for other tissues or
drug conditions (as summarised in Table 2). This is unsurprising, as
previous studies have suggested morphological differences in the
BG in autistic compared to neurotypical individuals [31]. In our
statistical analysis we corrected all metabolite values accordingly.
To ensure that the [H]MRS data quality was equal between
groups, we compared CRLB estimates for each metabolite (Glx,
GABA+) in each voxel (excluding omitted spectra), using a one-
way ANOVA. As expected, we found no signicant differences (all
F(1) 4.102, all p0.052) (as summarised in Table 3).
In extended MRS studies, there is often a risk of drift, where the
metabolite estimates on the same scanner change over long
Table 2. Absolute values (and standard deviations) for percentages of grey and white matter and cerebrospinal uid in the voxels of interest
Voxel Drug Tissue TD ASD F(dof) p-value
BG PLC GM 42.53% (3.03%) 45.43% (3.21%) F(1) =7.307 p=0.011
WM 50.47% (3.39%) 46.54% (4.08%) F(1) =9.345 p=0.004
CSF 6.92% (1.33%) 7.95% (1.95%) F(1) =3.222 p=0.082
CBD GM 43.24% (3.54%) 45.07% (3.64%) F(1) =2.157 p=0.152
WM 49.20% (4.66%) 47.29% (4.32%) F(1) =1.482 p=0.233
CSF 7.46% (2.16%) 7.56% (1.93%) F(1) =0.19 p=0.890
DMPFC PLC GM 52.93% (2.21%) 52.38% (3.49%) F(1) =0.299 p=0.589
WM 27.24% (3.36%) 28.11% (3.65%) F(1) =0.527 p=0.473
CSF 19.73% (4.05%) 19.41% (2.57%) F(1) =0.076 p=0.784
CBD GM 52.69% (2.86%) 52.84% (3.69%) F(1) =0.017 p=0.898
WM 27.32% (3.54%) 27.41% (4.14%) F(1) =0.004 p=0.947
CSF 19.89% (3.72%) 19.63% (2.53%) F(1) =0.048 p=0.827
Signicant between-group differences are highlighted in bold
ASD autism spectrum disorder, BG basal ganglia, CBD cannabidiol, CSF cerebrospinal uid, DMPFC dorsomedial prefrontal cortex, F(dof) F statistic and degrees
of freedom, GM grey matter, PLC placebo, TD typically developing individuals, WM white matter
Effects of cannabidiol on brain excitation and inhibition systems; a. . .
CM Pretzsch et al.
Neuropsychopharmacology (2019) 0:1 – 8
periods of time. For this reason, we compared the duration
between scans (days between PLC and CBD scan) across the two
groups. There was no signicant difference in duration between
visits (F(1) =0.041, p=0.841) in controls (34.82 ± 24.99) and ASD
(36.44 ± 20.53) (see Table 1). Furthermore, scan date for each drug
condition (PLC, CBD) was not correlated with the value of any
metabolite at that drug condition (all Pearsonsr0.299, all p
0.115), conrming that data acquisition was stable over time.
Metabolite differences
Glx (glutamate+glutamine). There were no signicant between-
group differences in baseline Glx in the BG (F(1) =0.000, p=0.993,
n=29) or in the DMPFC (F(1) =0.196, p=0.661, n=32). There
was however a signicant voxel × drug interaction effect
(F(1,21) =5.235, p
=0.033, partial eta squared (η
in both groups, CBD increased Glx in the BG and decreased Glx in
the DMPFC (as depicted in Fig. 2). This effect did not survive
stringent Bonferroni-correction. Nonetheless, p
=0.126 indi-
cates at least an 87% likelihood that the observed effect was real.
Results of post hoc testing within each voxel separately were
consistent with these ndings, albeit at trend level. In the BG, CBD
increased Glx in both groups (F(1,24) =3.593, p
=0.070, η
0.130); in the DMPFC, CBD decreased Glx in both groups
(F(1,26) =4.030, p
=0.055, η
=0.134). Thus, differences in
the acquisition parameters for each region were unlikely to
explain the overall results. Moreover, post-hoc within-subject
comparisons of Glx changes (CBD-PLC) showed that there was no
group-difference in Glx responsivity to CBD in the BG (F(1) =0.602,
=0.445) nor in the DMPFC (F(1) =0.006, p
conrming that Glx in adults with and without ASD responded to
CBD in the same way.
GABA+. There were no signicant between-group differences in
baseline GABA+in the BG (F(1) =0.000, p
=0.987, n=33) or
in the DMPFC (F(1) =0.408, p
=0.528, n=30). There was
however a signicant group × drug interaction in both brain
regions (F(1,22) =13.506, p
=0.001, η
=0.380). CBD
increased GABA+in the control group and decreased GABA+in
autistic individuals. This effect survived Bonferroni-correction
=0.004). These ndings are displayed in Fig. 2.
Post hoc testing in each voxel separately indicated that this
result was largely driven by changes in the DMPFC, where there
was a signicant group × drug interaction effect (F(1,23) =4.864,
=0.038, η
=0.175); and the group difference in CBD-
induced change in GABA+was signicant in the DMPFC (F(1) =
6.510, p
=0.017), but not in the BG.
Post hoc within-subject analyses of GABA+changes (CBD-PLC)
also conrmed a signicant group difference in the DMPFC (F1) =
4.864, p
=0.038), and but not the BG. This effect did not
survive stringent Bonferroni-correction (p
=0.14), but there was
at least a 86% chance (p
=0.14) it was real.
Finally, given that we excluded ASD participants, but not
neurotypicals, on the basis of low CRLB estimates, we also reran
our analysis including CRLB measures as a covariate and this did
Table 3. Absolute values (and standard deviations) for Cramér-Rao Lower Bound estimates for each metabolite in each voxel
Voxel Drug Metabolite TD ASD N(TD, ASD) F(dof) p-value
BG PLC GABA+4.56 (0.66) 4.82 (0.81) 17, 17 F(1) =1.095 p=0.303
Glx 7.50 (2.09) 7.56 (2.25) 17, 16 F(1) =0.007 p=0.935
CBD GABA+4.59 (0.62) 4.25 (1.43) 17, 16 F(1) =0.782 p=0.383
Glx 7.82 (3.00) 6.75 (2.48) 17, 16 F(1) =1.236 p=0.275
DMPFC PLC GABA+6.47 (0.87) 7.38 (2.06) 17, 16 F(1) =2.751 p=0.107
Glx 5.68 (0.73) 5.88 (1.02) 17, 16 F(1) =0.416 p=0.524
CBD GABA+6.29 (0.85) 7.69 (2.69) 17, 13 F(1) =4.102 p=0.052
Glx 6.24 (1.95) 6.31 (1.55) 17, 13 F(1) =0.12 p=0.913
ASD autism spectrum disorder, BG basal ganglia, CBD cannabidiol, DMPFC dorsomedial prefrontal cortex, F(dof) F statistic and degrees of freedom, GABA +
g-aminobutyric acid +macromolecule, Glx glutamate +glutamine, Nnumber of individuals, PLC placebo, TD typically developing individuals
Fig. 2 Glx (glutamate +glutamine) (14 neurotypicals, 9 autistic individuals) (a) and GABA+(γ-aminobutyric acid +macromolecules) (16
neurotypicals, 8 autistic individuals) (b) in the basal ganglia and the dorsomedial prefrontal cortex for both groups in both drug conditions.
Glx (a) and GABA+(b) concentration represents the ratio of the Glx and GABA+metabolite resonance area to the unsuppressed water
resonance area, respectively. Dotted lines connect group means, which are indicated by black horizontal bars. Error bars represent standard
deviations. ASD autism spectrum disorder, BG basal ganglia, CBD cannabidiol, DMPFC dorsomedial prefrontal cortex, PLC placebo, TD typically
developed controls; * indicates a signicance level at p0.05; *** indicates a signicance level at p0.001
Effects of cannabidiol on brain excitation and inhibition systems; a. . .
CM Pretzsch et al.
Neuropsychopharmacology (2019) 0:1 – 8
not materially alter the ndings. Thus, GABA+in adults with and
without ASD responded to CBD in opposite directions, and
especially in the cortex.
We note that secondary analyses conrmed that CBD did not
alter the levels of other metabolites within the spectrum; namely
we observed no signicant group and drug main effects, and no
group × drug interaction effects for GSH, NAA, NAAG, NAA +
NAAG, and GSH +Glx.
Here we report that acute (single dose) CBD shiftslevels of the
brains primary excitatory and inhibitory neurotransmitters in
adults with and without ASD. In both groups, CBD increased Glx in
the BG voxel and decreased it in the DMPFC voxel. In contrast,
CBD had opposite effects on GABA+in each group. Specically,
both in prefrontal and subcortical regions, CBD increased GABA+
in the controls but decreased GABA+in ASD. Moreover, in line
with some [19,21], but not all previous MRS studies of glutamate
and GABA in ASD [21,32] in the BG and DMPFC voxel, there were
no differences in baseline metabolite levels. Thus, our study
suggests that excitatory (E) glutamate response mechanisms to
CBD are comparable regardless of diagnosis; whereas inhibitory (I)
GABA response pathways are altered in ASD.
Effect of CBD on Glx
The region including and surrounding the BG is richly innervated
by a web of excitatory pyramidal neurons alongside GABAergic
inhibitory projection neurons and glia cells [33]. The increase in
Glx triggered by CBD in both groups could therefore have resulted
from CBD binding to neuronal TRPV1 receptors. Subsequent
activation of pyramidal neurons [15] may potentially have
contributed to the altered Glx metabolite levels in the BG
captured by MRS. Cannabinoid activation of TRPV1 receptors on
microglia could also theoretically upregulate microglial activity
and migration, leading to extracellular vesicular shedding and
augmentation of Glx levels [34]. However, this is speculative, given
the rapid desensitisation of TRPV1 receptors after activation [35].
In the DMPFC, glutamatergic pyramidal neurons predominate,
with relatively fewer GABAergic interneurons (ratio ~4.7:1) [17].
Here, CBD reduced Glx in each group. One possible explanation
for this is that CBD suppressed the activity of prefrontal
glutamatergic neurons via their 5-HT
receptors [17,18], thereby
reducing Glx levels. Preliminary evidence has linked impaired
TRPV1 signalling to the ASD risk gene SHANK3, and 5-HT
anomalies, including 5-HT
receptor dysfunction, to ASD [36].
Despite this, we found no group difference in Glx response to
CBD. This implies that glutamate targets of CBD in the BG and
DMPFC in idiopathic ASD are no different from those in
Effect of CBD on GABA+
In contrast, CBD increased GABA+levels in the BG and DMPFC
voxel in neurotypicals, but decreased GABA+levels in the BG and
(markedly so) in the DMPFC voxel of autistic adults. The causes of
group differences in GABA+response are unknown. However, it
may be partially explained by ASD-related alterations in CBD
targets. For example, the expression of the CBD interneuron
GPR55 receptor is reduced in the cortex in the valproic rat model
of ASD [37]. Another explanation could be more general
disruption to GABA pathways in ASD. For instance, a reduction
in the activity of the rate-limiting GABA synthesising enzyme
glutamic acid decarboxylase (GAD) [38], and genetic anomalies in
GABA receptors [39] have been reported in ASD. Since MRS
GABA+is thought to reect metabolic (intracellular) and
extracellular GABA+levels, rather than GABAergic synaptic
transmission [40,41], further studies are required to back-
translate our results into preclinical models to dissect exactly
what underpins the atypical cortical and sub-cortical GABA+
response to CBD in ASD; and what is the impact on excitatory and
inhibitory system activity. For example, Kaplan and colleagues
have reported that CBD appears to restore GABAergic neuro-
transmission in an animal model of Dravet syndrome [14]. Despite
the limitations of resolution using MRS, the present ndings,
together with our previous nding of atypical prefrontal GABA
responsivity to the glutamate-GABA acting drug riluzole, clearly
point to an alteration in the dynamics of GABA, but not glutamate,
systems in ASD. This observation may not only have aetiological
relevance, but also add to the evidence that the GABA system may
be a tractable treatment target in ASD [42,43].
Cortico-striatal systems (in ASD)
The CBD-induced shift in cortical and subcortical Glx and GABA+
levels may inuence excitation and inhibition, although MRS does
not tell us directly about excitation or inhibition at the level of the
synapse. Nevertheless, this shift in metabolites could potentially
have widespread implications for brain function and behaviour.
This is because the BG (and the thalamus and insula) and DMPFC
form part of a circuit that is heavily dependent on glutamatergic
excitation and GABAergic inhibition and supports and regulates a
range of cognitive processes. In brief, in the neurotypical brain, the
BG receive input from the (insular) cortex, brainstem, and
thalamus. Cortical input is predominantly excitatory [44], but BG
output nuclei act via a direct monosynaptic GABAergic and an
indirect polysynaptic glutamatergic pathway [45]. Projection
neurons from the output nuclei provide GABAergic tonic
inhibition to thalamocortical and brainstem neurons to complete
aloop[45,46]. In ASD, however, neuroimaging studies have
revealed reduced WM integrityespecially in prefrontal tracts [47],
and abnormal functional integrationof the BG and the DMPFC.
This is thought to partly explain why multiple processes
dependent upon cortico-striatal loop integrity, such as socio-
emotional, motor, and reward processing, are altered in ASD [48,
49]. Our results suggest that the structural and functional
differences previously reported in MRI studies of cortical-
subcortical systems in ASD extend to atypical E-I response to
pharmacological challenge.
The corollary of our observations is that because CBD shifts
glutamate and GABA+, it may affect glutamatergic excitation and
GABAergic inhibition, and thereby impact on brain function. We
did not directly test this here, but some support for this
proposition comes from a recent report that CBD increases
prefrontostriatal functional connectivity in neurotypical controls
[50]. However, our results predict that the direction of a functional
response to CBD may be distinct in autistic individuals, and this
warrants further investigation.
Our results reinforce the fact that we cannot expect the
actions of a drug tested in a typically developing population to
be replicated in people with neurodevelopmental conditions.
For example, we have previously reported a link between
disrupted functional connectivity and an atypical MRS GABA+
response to pharmacological E-I challenge through riluzole in
ASD but not in controls [19]. However, unlike CBD, riluzole
increased prefrontal GABA+in ASD. Together with our current
ndings, this suggests that GABA+can be shifted bi-
directionally in cortical-subcortical systems in adults with ASD.
This is encouraging, as we can now begin to build a repertoire of
drugs that elicit a biological response in ASD. This tactic will be
critical given the heterogeneity of the autism spectrum, where a
one-drug-ts-allapproach is unlikely to succeed. Thus, our next
steps will be to examine whether acute drug response allows us
to (i) identify more pharmacologically homogeneous sub-groups
within ASD; and (ii) predict clinical responsiveness to
sustained treatment.
Effects of cannabidiol on brain excitation and inhibition systems; a. . .
CM Pretzsch et al.
Neuropsychopharmacology (2019) 0:1 – 8
We acknowledge that our study has important limitations. First,
here we measured MRS bulk amounts of Glx and GABA+in the
chosen voxels of interest. This did not allow us to reliably discern
the specic contributions of different compounds (glutamate and
glutamine) contributing to the Glx signal. Moreover, at 3T, we
were limited to draw inferences about intra-cellular and extra-
cellular metabolite levels from our ndings. Future studies with
higher resolutions and magnetic eld strengths are required to
address these questions.
Second, we only included adult male subjects with an IQ above
70, and with no epilepsy or comorbid psychiatric conditions. This
step was taken to ensure the homogeneity of our study sample
and to make sure that observed effects were related to ASD rather
than a comorbidity of ASD. However, this also limits our ability to
extend our ndings to the general ASD population, which is
characterised by heterogeneity and the presence of psychiatric
and neurological comorbidities. Future studies should attempt to
replicate our ndings in larger and more diverse population
samples, and especially include women.
Third, our participant sample was relatively small. This can be
attributed to our strict recruitment criteria (e.g. no use of illicit
substances in the month leading up to and during the study). It is
also inuenced by difculties inherent in time-intensive repeated-
measures studies involving drug administration, e.g. high drop-out
rates. Finally, also contributing to the modest sample size were our
rigorous data quality criteria, e.g. exclusion of scans based on head
motion, known to be a difculty in ASD. That said, our sample size
was comparable (or bigger than) previous MRS studies in ASD [19,
21]. Moreover, each individual in our study had two scans and
thus acted as their own controlto reduce inter-subject variability
and to increase statistical power.
Fourth, in this study we only investigated the impact of acute
CBD administration on brain. We cannot extrapolate from the
effects of a single dose to the impact of repeated administrations,
e.g. as a therapeutic option in ASD, for several reasons. For
instance, chronic CBD administration may result in a steady state,
wherein the brain system plasticity equilibrates to the presence of
CBD. Future studies should thus investigate the impact of long-
term treatment with CBD on brain and behaviour.
In summary, we report that CBD can shiftlevels of Glx and
GABA+. These metabolites contribute to the regulation of
excitatory and inhibitory neurotransmission in both the typical
and the autistic brain. However, our study also demonstrated that
the atypical (autistic) brain reacts differently to CBD challenge of
GABA+. Our ndings that the GABAergic system is distinct in ASD,
but can be shifted, is relevant both to our understanding of causal
mechanisms and to the discovery of treatment targets in ASD.
Additional studies will be required to (i) identify the neural basis of
the response to acute CBD challenge, including potential
pharmacologically homogeneous sub-groups within the autistic
spectrum; (ii) examine potential functional consequences of CBD
challenge in terms of inhibition, brain network activity, cognition,
and behaviour; and (iii) investigate whether an acute response to
CBD could predict the effects of sustained treatment in ASD.
This study was an Investigator Initiated Study (G.M.) which received funding and
product from GW Research Ltd (Cambridge, UK). GW Research Ltd (Cambridge, UK)
had no role in the data collection or analysis of results, nor in the decision to publish.
The authors also acknowledge infrastructure and training support from the National
Institute for Health Research (NIHR) Mental Health Biomedical Research Centre (BRC)
at South London and Maudsley NHS Foundation Trust and Kings College London.
The views expressed are those of the authors and not necessarily those of the NHS,
the NIHR or the Department of Health, U.K. Additional sources of support included
the Sackler Institute for Translational Neurodevelopment at Kings College London,
Autistica, the Medical Research Council (MRC) Centre grant (MR/N026063/1) and EU-
AIMS (European Autism Interventions)/EU AIMS-2-TRIALS, a European Innovative
Medicines Initiative Joint Undertaking under Grant Agreements No. 115300 and
777394, the resources of which are composed of nancial contributions from the
European Unions Seventh Framework Programme (Grant FP7/20072013). RAEE
receives salary support from NIH R01 MH106564 and U54 HD079123. The remaining
authors have nothing to disclose. Finally, the authors sincerely thank all the
Supplementary Information accompanies this paper at (
Publishers note: Springer Nature remains neutral with regard to jurisdictional claims
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Effects of cannabidiol on brain excitation and inhibition systems; a. . .
CM Pretzsch et al.
Neuropsychopharmacology (2019) 0:1 – 8
... Three eligible papers [80][81][82] were found according to the purpose of the present study. ...
... All three studies used a randomized double-blind, cross-over design. Two studies [80,81] acquired data following a single oral dose of 600 mg CBD or a matched placebo while one study utilized CBDV [82] (see Table 1). ...
... Two studies compared MRS measures of glutamate and GABA [81] and Glx (glutamate + glutamine) and GABA+ (GABA+ macromolecules) [82] levels in the BG and DMPFC in men with and without ASD. ...
... 47 Independent work shows that CBD modulates Glx in basal ganglia and prefrontal cortex across ASD and neurotypical individuals. 48 Altogether, these findings suggest that CBD may have effects on glutamate and blood flow in humans, two pathophysiological features strongly implicated in psychosis onset. However, whether CBD can normalise glutamatergic dysfunction (or its relationship with blood flow) in CHR patients is yet to be examined. ...
... 47 Outside of the hippocampus, CBD has been shown to increase Glx in basal ganglia but reduce Glx in prefrontal cortex across ASD and neurotypical individuals. 48 Preclinical studies demonstrate that CBD can increase prefrontal glutamate in rodent depression models, 59 although attenuated glutamate release from hippocampal synaptosomes has been observed in cocaine-induced seizure models. 60 CBD may also act on excitation-inhibition balance via the GABAergic system. ...
... 61 In humans, CBD increases GABA in basal ganglia and prefrontal cortex in controls, but decreases GABA in these regions in ASD individuals. 48 Overall, previous work points to effects of CBD on the glutamate system but the regions implicated and the direction of effects are somewhat mixed, potentially due to species-specific differences, the differential populations examined in humans and other methodological factors. Our results therefore extend the limited body of existing literature (so far conducted in people with established psychosis, ASD and neurotypical controls) by showing that CBD may also modulate hippocampal glutamate in people at risk of psychosis, and in a direction indicative of normalisation. ...
Full-text available
Background Preclinical and human data suggest that the onset of psychosis involves hippocampal glutamatergic dysfunction, driving hyperactivity/hyperperfusion in a hippocampal-midbrain-striatal circuit. Whether glutamatergic dysfunction is related to cerebral perfusion in patients at Clinical High Risk (CHR) for psychosis, and whether cannabidiol (CBD) has ameliorative effects on glutamate or its relationship with blood flow remains unknown. Methods Using a double-blind, parallel-group design, 33 CHR patients were randomised to 600mg CBD or placebo; 19 healthy controls did not receive any drug. Proton magnetic resonance spectroscopy was used to measure glutamate concentrations in left hippocampus. We examined differences relating to CHR status (controls vs placebo), effects of CBD (placebo vs CBD) and linear between-group effects, such that placebo>CBD>controls or controls>CBD>placebo. We also examined group x glutamate x cerebral perfusion (measured using arterial spin labelling) interactions. Results Compared to controls, CHR-placebo patients had significantly lower hippocampal glutamate (p=.015) and a significant linear relationship was observed across groups, such that glutamate was highest in controls, lowest in CHR-placebo and intermediate in patients under CBD (p=.031). There was also a significant interaction between group (controls vs CHR-placebo), hippocampal glutamate and perfusion in the putamen and insula (p FWE =.012), driven by a strong positive correlation in the CHR-placebo group vs a negative correlation in controls. Conclusions Our findings suggest that hippocampal glutamate is lower in CHR patients and may be partially normalised by CBD treatment. Furthermore, we provide the first in vivo evidence of an abnormal relationship between hippocampal glutamate and resting perfusion in the striatum and insula in these patients.
... Last, the rest of the studies investigated the effects of CBD on obsessive-compulsive disorder [73], severe behavioral problems [91], autism spectrum disorder (ASD) [61,62], and behavioral and cardiovascular effects [71]. Efron et al. conducted a study to determine whether it was feasible to investigate the effects of CBD in children with intellectual disability and severe behavioral problems and their families; while the study was not powered to discern the effects of CBD, the trial was feasible [91]. ...
... Kayser et al. determined that either THC or CBD had little impact on obsessivecompulsive disorder symptoms and smaller reductions in anxiety, whereas THC increased heart rate, blood pressure, and intoxication compared with CBD and placebo [73]. One of the two ASD studies did not show the efficacy of CBD on ASD, but that CBD can alter the glutamate and GABAergic levels [62]; another study showed that CBD can alter the fractional amplitude of low-frequency fluctuations and functional connectivity in/between brain regions in adults with ASD [61]. Neurological diseases or movement disorders were another commonly studied topic found during this review (n = 11) and included Parkinson's disease (PD) [80,82], Huntington's disease [69,70], multiple sclerosis [49], brain function [51], chronic pain [59,78], neural oscillations [76], and neurogenic disorders [65]. ...
Background: Legislative changes have fueled the global availability of cannabis and cannabis-derived compounds, such as cannabidiol. Little is known about the effectiveness and safety of cannabidiol for treating health conditions other than seizure disorders. Objective: A systematic review of the literature was performed to investigate other health conditions, characteristics of the studied populations, and the effectiveness of cannabidiol in randomized clinical trials. Methods: Seven publication databases were searched from February to March 2021. The inclusion criteria for studies were: (1) utilized a randomized clinical trial design; (2) published in a peer-reviewed journal or thesis/dissertation; (3) published in English; (4) investigated either prescription (i.e., Epidiolex) or non-prescription CBD that was derived from the Cannabis sativa plant with < 3% ∆9-tetrahydrocannabinol; and (5) reported at least one outcome. This review excluded seizure-related disorders as several previous reviews have been done on this topic; it also excluded published protocols, other systematic reviews, or meta-analyses of randomized clinical trials that investigated cannabidiol. Independent reviewing, risk of bias assessment, and data abstraction were performed by two authors. Results: Fifty-eight studies from eight countries were included in this review. Twenty-seven studies (47%) were conducted in healthy populations, 14% were restricted to male individuals (n = 8), and 72% had sample sizes of fewer than 40 participants. Doses of cannabidiol used in these studies ranged from 400 µg to 6000 mg. The effect of cannabidiol on mental health was the most studied topic (53%), which focused mainly on anxiety, psychosis, schizophrenia, and substance use disorders. The remaining studies investigated neurological conditions (19%) and a myriad of other health conditions or outcomes. While cannabidiol appears to be anxiolytic, its effectiveness for other conditions was highly variable. Conclusions: This review highlights the inconsistencies of cannabidiol as a treatment for non-seizure-related health conditions or outcomes. Studies incorporating larger sample sizes in more diverse populations are encouraged. While cannabidiol was generally safe and well tolerated even in high doses among the included studies, clearer dosing guidelines and increased regulation of cannabidiol products are also needed.
... 57 In addition, there is evidence that CBD also activates 5-HT1A/2A/3A serotonergic and vanilloid receptors, antagonizes alpha-1 adrenergic and μ-opioid receptors, and inhibits synaptic uptake of noradrenaline, dopamine, serotonin, and gammaaminobutyric acid (GABA). [58][59][60][61] Other studies indicate that it affects mitochondrial activities, including calcium influx. ...
... Wykazano, że aktywacja ECS i podawanie CBD przywraca deficyty społeczne [16]. Pojedyncze doustne podanie 600 mg CBD 34 mężczyznom (17 neurotypowym i 17 z ASD) zwiększyło przedczołową aktywność hamującego neuroprzekaźnika, kwasu gamma-aminomasłowego (GABA) u neurotypowych i zmniejszyło aktywność GABA u osób z ASD [28]. Co więcej, stwierdzono, że dzieci z ASD mają niższy obwodowy poziom endokannabinoidów [29,30]. ...
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Introduction and objective: Therapy with the use of "medical marijuana" is becoming more and more popular with patients, who often perceive it as a more natural and safe form of treatment. It is also more and more boldly considered by physicians in the pediatric population, especially when standard methods of pharmacotherapy prove insufficient. The following review focuses on the possibilities of using cannabis preparations in children with drug-resistant epilepsy, autism spectrum disorders and spasticity. It also draws attention to the possible side effects and risks of unjustified use of medical marijuana. State of knowledge: In the pediatric population, high efficacy and a favorable safety profile have been proven so far in the treatment of epileptic seizures associated with Lennox-Gastaut syndrome and Dravet syndrome, and for the treatment of epileptic seizures in tuberous sclerosis complex, (TSC) . Although the therapy has been approved only for the above-mentioned indications, high hopes are also placed on the use of cannabinoids to treat the symptoms of other diseases and disorders, including spasticity and autism spectrum disorders. Conclusions: The research carried out so far gives hope for the possibility of using medical marijuana in other indications as well, as its use correlates with the reduction of i.a. symptoms of spasticity or autism spectrum disorders. At the same time, further studies are needed to assess the balance of benefits and potential risks of the therapy. Since recreational cannabis use in youth is known to be associated with serious adverse events, and medical cannabis use has a relatively strong placebo effect, decisions about its use should always be made carefully and based on scientific evidence.
... CBD has a broad range of pharmacological mechanisms. For example, CBD has been demonstrated to affect proxy measures of glutamate and GABA in typically developing and autistic adults [16]. CBD may also act within dopaminergic, serotoninergic and endocannabinoid systems [17]. ...
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Cannabidiol (CBD) has shown promise in treating psychiatric disorders, including cannabis use disorder – a major public health burden with no approved pharmacotherapies. However, the mechanisms through which CBD acts are poorly understood. One potential mechanism of CBD is increasing levels of anandamide, which has been implicated in psychiatric disorders including depression and cannabis use disorder. However, there is a lack of placebo-controlled human trials investigating this in psychiatric disorders. We therefore assessed whether CBD affects plasma anandamide levels compared to placebo, within a randomised clinical trial of CBD for the treatment of cannabis use disorder. Individuals meeting criteria for cannabis use disorder and attempting cannabis cessation were randomised to 28-day administration with placebo (n = 23), 400 mg CBD/day (n = 24) or 800 mg CBD/day (n = 23). We estimated the effects of each CBD dose compared to placebo on anandamide levels from baseline to day 28. Analyses were conducted both unadjusted and adjusted for cannabis use during the trial to account for effects of cannabis on the endocannabinoid system. We also investigated whether changes in plasma anandamide levels were associated with clinical outcomes relevant for cannabis use disorder (cannabis use, withdrawal, anxiety, depression). There was an effect of 800 mg CBD compared to placebo on anandamide levels from baseline to day 28 after adjusting for cannabis use. Pairwise comparisons indicated that anandamide levels unexpectedly reduced from baseline to day 28 in the placebo group (−0.048, 95% CI [−0.089, −0.007]), but did not change in the 800 mg CBD group (0.005, 95% CI [−0.036, 0.047]). There was no evidence for an effect of 400 mg CBD compared to placebo. Changes in anandamide levels were not associated with clinical outcomes. In conclusion, this study found preliminary evidence that 28-day treatment with CBD modulates anandamide levels in individuals with cannabis use disorder at doses of 800 mg/day but not 400 mg/day compared to placebo.
... Similarly, altered excitation-inhibition (e.g. glutamatergic-GABAergic) systems are thought to be a central element in the neurobiology of autism [20,[73][74][75][76]; and may therefore also underpin a broad range of functions other than adaptive behaviour. In fact, this prior work, together with the known interaction between different behavioural domains/cognitive functions (and the spatial overlap in the associated neuroanatomical profiles we detected), suggest that it is unlikely that genetically determined mechanisms underpinning differences in neurodevelopment are specific to adaptive outcome in autism. ...
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Individuals with autism spectrum disorder (henceforth referred to as autism) display significant variation in clinical outcome. For instance, across age, some individuals’ adaptive skills naturally improve or remain stable, while others’ decrease. To pave the way for ‘precision-medicine’ approaches, it is crucial to identify the cross-sectional and, given the developmental nature of autism, longitudinal neurobiological (including neuroanatomical and linked genetic) correlates of this variation. We conducted a longitudinal follow-up study of 333 individuals (161 autistic and 172 neurotypical individuals, aged 6–30 years), with two assessment time points separated by ~12–24 months. We collected behavioural (Vineland Adaptive Behaviour Scale-II, VABS-II) and neuroanatomical (structural magnetic resonance imaging) data. Autistic participants were grouped into clinically meaningful “Increasers”, “No-changers”, and “Decreasers” in adaptive behaviour (based on VABS-II scores). We compared each clinical subgroup’s neuroanatomy (surface area and cortical thickness at T1, ∆T (intra-individual change) and T2) to that of the neurotypicals. Next, we explored the neuroanatomical differences’ potential genomic associates using the Allen Human Brain Atlas. Clinical subgroups had distinct neuroanatomical profiles in surface area and cortical thickness at baseline, neuroanatomical development, and follow-up. These profiles were enriched for genes previously associated with autism and for genes previously linked to neurobiological pathways implicated in autism (e.g. excitation-inhibition systems). Our findings suggest that distinct clinical outcomes (i.e. intra-individual change in clinical profiles) linked to autism core symptoms are associated with atypical cross-sectional and longitudinal, i.e. developmental, neurobiological profiles. If validated, our findings may advance the development of interventions, e.g. targeting mechanisms linked to relatively poorer outcomes.
... Also, alterations in the expression of CB1r and other ECS components, as well as in their functionality, have been described in ASD patients (Karhson et al., 2018;Smith et al., 2017) and in several ASD animal models (reviewed by Zamberletti et al., 2017). Finally, recent clinical and preclinical studies supported the efficacy of pharmacological modulators of ECS as therapeutic approaches to ASD symptoms ( Bar-Lev Schleider et al., 2019;Jung et al., 2012;Pretzsch et al., 2019). ...
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Mice and rats emit ultrasonic vocalizations (USVs), which may express their arousal and emotional states, to communicate with each other. There is continued scientific effort to better understand the functions of USVs as a central element of the rodent behavioral repertoire. However, studying USVs is not only important because of their ethological relevance, but also because they are widely applied as a behavioral readout in various fields of biomedical research. In mice and rats, a large number of experimental models of brain disorders exist and studying the emission of USVs in these models can provide valuable information about the health status of the animals and the effectiveness of possible interventions, both environmental and pharmacological. This review (i) provides an updated overview of the contexts, in which ultrasonic calling behavior of mice and rats has particularly high translational value, and gives (ii) some examples of novel approaches and tools used for the analysis of USVs in mice and rats, combining qualitative and quantitative methods. The relevance of age and sex differences as well as the importance of longitudinal evaluations of calling and non‐calling behavior is also discussed. Finally, the importance of assessing the communicative impact of USVs in the receiver, i.e., through playback studies, is highlighted.
Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders whose symptoms include impaired communication and social interaction, stereotypies, and varying levels of intellectual disability. Together with these symptoms are co-occurring psychiatric or neurological conditions, often with hyperactivity and attention disorders, anxiety, depression, and epilepsy. So far, no effective treatment for ASD is available, possibly because its neurobiological basis and heterogeneous nature are not clearly understood. Clinical and preclinical trials support the involvement of the endocannabinoid system in the patho-physiology of ASD. Cannabidiol (CBD), the main nonpsychotomimetic compound of the cannabis plant, interacts with the endocannabinoid system and has significant therapeutic potential in treating several psychiatric disorders and manifestations of ASD. After this article, readers are expected to have a broad understanding of current scientific evidence and perspectives on the use of CBD in cases of ASD. [ Psychiatr Ann . 2023;53(6):247–251.]
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Cannabidiol (CBD) is a non-intoxicating phytochemical from Cannabis sativa that is increasingly used to manage pain. The potential for CBD to ameliorate dimensional behavior symptoms occurring in multiple psychiatric disorders was suggested, including social interaction impairments. To test this hypothesis, adult male BTBRT+Itpr3tf/J (BTBR) mice, a model of idiopathic autism exhibiting social preference deficits and restrictive repetitive behaviors, were acutely treated with vehicle or 0.1, 1, or 10 mg/kg CBD. Social interaction preference was assessed 50 min after treatment, followed by social novelty preference at 60 min, marble burying at 75 min and social dominance at 120 min. CBD (10 mg/kg) enhanced BTBR social interaction but not social novelty preference, marble burying or dominance, with serum levels = 29 ± 11 ng/mg at 3 h post-injection. Next, acute 10 mg/kg CBD was compared to vehicle treatment in male serotonin transporter (SERT) knock-out mice, since SERT deficiency is an autism risk factor, and in their wildtype background strain controls C57BL/6J mice. CBD treatment generally enhanced social interaction preference and attenuated social novelty preference, yet neither marble burying nor dominance was affected. These findings show acute treatment with as little as 10 mg/kg purified CBD can enhance social interaction preference in male mice that are otherwise socially deficient.
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Problem/condition: Autism spectrum disorder (ASD). Period covered: 2014. Description of system: The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance system that provides estimates of the prevalence of autism spectrum disorder (ASD) among children aged 8 years whose parents or guardians reside within 11 ADDM sites in the United States (Arizona, Arkansas, Colorado, Georgia, Maryland, Minnesota, Missouri, New Jersey, North Carolina, Tennessee, and Wisconsin). ADDM surveillance is conducted in two phases. The first phase involves review and abstraction of comprehensive evaluations that were completed by professional service providers in the community. Staff completing record review and abstraction receive extensive training and supervision and are evaluated according to strict reliability standards to certify effective initial training, identify ongoing training needs, and ensure adherence to the prescribed methodology. Record review and abstraction occurs in a variety of data sources ranging from general pediatric health clinics to specialized programs serving children with developmental disabilities. In addition, most of the ADDM sites also review records for children who have received special education services in public schools. In the second phase of the study, all abstracted information is reviewed systematically by experienced clinicians to determine ASD case status. A child is considered to meet the surveillance case definition for ASD if he or she displays behaviors, as described on one or more comprehensive evaluations completed by community-based professional providers, consistent with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) diagnostic criteria for autistic disorder; pervasive developmental disorder-not otherwise specified (PDD-NOS, including atypical autism); or Asperger disorder. This report provides updated ASD prevalence estimates for children aged 8 years during the 2014 surveillance year, on the basis of DSM-IV-TR criteria, and describes characteristics of the population of children with ASD. In 2013, the American Psychiatric Association published the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), which made considerable changes to ASD diagnostic criteria. The change in ASD diagnostic criteria might influence ADDM ASD prevalence estimates; therefore, most (85%) of the records used to determine prevalence estimates based on DSM-IV-TR criteria underwent additional review under a newly operationalized surveillance case definition for ASD consistent with the DSM-5 diagnostic criteria. Children meeting this new surveillance case definition could qualify on the basis of one or both of the following criteria, as documented in abstracted comprehensive evaluations: 1) behaviors consistent with the DSM-5 diagnostic features; and/or 2) an ASD diagnosis, whether based on DSM-IV-TR or DSM-5 diagnostic criteria. Stratified comparisons of the number of children meeting either of these two case definitions also are reported. Results: For 2014, the overall prevalence of ASD among the 11 ADDM sites was 16.8 per 1,000 (one in 59) children aged 8 years. Overall ASD prevalence estimates varied among sites, from 13.1-29.3 per 1,000 children aged 8 years. ASD prevalence estimates also varied by sex and race/ethnicity. Males were four times more likely than females to be identified with ASD. Prevalence estimates were higher for non-Hispanic white (henceforth, white) children compared with non-Hispanic black (henceforth, black) children, and both groups were more likely to be identified with ASD compared with Hispanic children. Among the nine sites with sufficient data on intellectual ability, 31% of children with ASD were classified in the range of intellectual disability (intelligence quotient [IQ] <70), 25% were in the borderline range (IQ 71-85), and 44% had IQ scores in the average to above average range (i.e., IQ >85). The distribution of intellectual ability varied by sex and race/ethnicity. Although mention of developmental concerns by age 36 months was documented for 85% of children with ASD, only 42% had a comprehensive evaluation on record by age 36 months. The median age of earliest known ASD diagnosis was 52 months and did not differ significantly by sex or race/ethnicity. For the targeted comparison of DSM-IV-TR and DSM-5 results, the number and characteristics of children meeting the newly operationalized DSM-5 case definition for ASD were similar to those meeting the DSM-IV-TR case definition, with DSM-IV-TR case counts exceeding DSM-5 counts by less than 5% and approximately 86% overlap between the two case definitions (kappa = 0.85). Interpretation: Findings from the ADDM Network, on the basis of 2014 data reported from 11 sites, provide updated population-based estimates of the prevalence of ASD among children aged 8 years in multiple communities in the United States. The overall ASD prevalence estimate of 16.8 per 1,000 children aged 8 years in 2014 is higher than previously reported estimates from the ADDM Network. Because the ADDM sites do not provide a representative sample of the entire United States, the combined prevalence estimates presented in this report cannot be generalized to all children aged 8 years in the United States. Consistent with reports from previous ADDM surveillance years, findings from 2014 were marked by variation in ASD prevalence when stratified by geographic area, sex, and level of intellectual ability. Differences in prevalence estimates between black and white children have diminished in most sites, but remained notable for Hispanic children. For 2014, results from application of the DSM-IV-TR and DSM-5 case definitions were similar, overall and when stratified by sex, race/ethnicity, DSM-IV-TR diagnostic subtype, or level of intellectual ability. Public health action: Beginning with surveillance year 2016, the DSM-5 case definition will serve as the basis for ADDM estimates of ASD prevalence in future surveillance reports. Although the DSM-IV-TR case definition will eventually be phased out, it will be applied in a limited geographic area to offer additional data for comparison. Future analyses will examine trends in the continued use of DSM-IV-TR diagnoses, such as autistic disorder, PDD-NOS, and Asperger disorder in health and education records, documentation of symptoms consistent with DSM-5 terminology, and how these trends might influence estimates of ASD prevalence over time. The latest findings from the ADDM Network provide evidence that the prevalence of ASD is higher than previously reported estimates and continues to vary among certain racial/ethnic groups and communities. With prevalence of ASD ranging from 13.1 to 29.3 per 1,000 children aged 8 years in different communities throughout the United States, the need for behavioral, educational, residential, and occupational services remains high, as does the need for increased research on both genetic and nongenetic risk factors for ASD.
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Currently, there are no effective pharmacologic treatments for the core symptoms of autism spectrum disorder (ASD). There is, nevertheless, potential for progress. For example, recent evidence suggests that the excitatory (E) glutamate and inhibitory (I) GABA systems may be altered in ASD. However, no prior studies of ASD have examined the ‘responsivity’ of the E–I system to pharmacologic challenge; or whether E–I modulation alters abnormalities in functional connectivity of brain regions implicated in the disorder. Therefore, we used magnetic resonance spectroscopy ([1H]MRS) to measure prefrontal E–I flux in response to the glutamate and GABA acting drug riluzole in adult men with and without ASD. We compared the change in prefrontal ‘Inhibitory Index’—the GABA fraction within the pool of glutamate plus GABA metabolites—post riluzole challenge; and the impact of riluzole on differences in resting-state functional connectivity. Despite no baseline differences in E–I balance, there was a significant group difference in response to pharmacologic challenge. Riluzole increased the prefrontal cortex inhibitory index in ASD but decreased it in controls. There was also a significant group difference in prefrontal functional connectivity at baseline, which was abolished by riluzole within the ASD group. Our results also show, for we believe the first time in ASD, that E–I flux can be ‘shifted’ with a pharmacologic challenge, but that responsivity is significantly different from controls. Further, our initial evidence suggests that abnormalities in functional connectivity can be ‘normalised’ by targeting E–I, even in adults.
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The capsaicin receptor TRPV1 has been widely characterized in the sensory system as a key component of pain and inflammation. A large amount of evidence shows that TRPV1 is also functional in the brain although its role is still debated. Here we report that TRPV1 is highly expressed in microglial cells rather than neurons of the anterior cingulate cortex and other brain areas. We found that stimulation of microglial TRPV1 controls cortical microglia activation per se and indirectly enhances glutamatergic transmission in neurons by promoting extracellular microglial microvesicles shedding. Conversely, in the cortex of mice suffering from neuropathic pain, TRPV1 is also present in neurons affecting their intrinsic electrical properties and synaptic strength. Altogether, these findings identify brain TRPV1 as potential detector of harmful stimuli and a key player of microglia to neuron communication.
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Autism spectrum disorder (ASD) is a common neurodevelopmental disorder with cognitive, motor and emotional symptoms. The thalamus and basal ganglia form circuits with the cortex supporting all three of these behavioral domains. Abnormalities in the structure of sub-cortical regions may suggest atypical development of these networks, with implications for understanding the neural basis of ASD symptoms. Findings from previous volumetric studies have been inconsistent. Here, using advanced surface-based methodology, we investigated localized differences in shape and surface area in the basal ganglia and thalamus in ASD, using T1-weighted anatomical images from the Autism Brain Imaging Data Exchange (373 male participants aged 7-35years with ASD and 384 typically developing; TD). We modeled effects of diagnosis, age and their interaction on volume, shape and surface area. In participants with ASD, we found expanded surface area in the right posterior thalamus corresponding to the pulvinar nucleus; and a mo
Tetrahydrocannabinol (THC) and Cannabidiol (CBD) are two substances from cannabis sativa that have beenimplicated in the treatment of mental and neurological disorders. We concentrated on a previously validated neuroimaging phenotype, fronto-striatal connectivity across different striatal seeds, because of this loop's relevance to executive functioning, decision making, salience generation and motivation and its link to various neuropsychiatric conditions. Therefore, we studied the effect of THC and CBD on fronto-striatal circuitry by a seed-voxel connectivity approach using seeds from the caudate and the putamen. We conducted a cross-over pharmaco-fMRI study in 16 healthy male volunteers with placebo, 10 mg oral THC and 600 mg oral CBD. Resting state was measured in a 3 T scanner. CBD lead to an increase of fronto-striatal connectivity in comparison to placebo. In contrast to our expectation that THC and CBD show opposing effects, THC versus placebo did not show any significant effects, probably due to insufficient concentration of THC during scanning. The effect of CBD on enhancing fronto-striatal connectivity is of interest because it might be a neural correlate of its anti-psychotic effect in patients.
Background: Patients with Lennox-Gastaut syndrome, a rare, severe form of epileptic encephalopathy, are frequently treatment resistant to available medications. No controlled studies have investigated the use of cannabidiol for patients with seizures associated with Lennox-Gastaut syndrome. We therefore assessed the efficacy and safety of cannabidiol as an add-on anticonvulsant therapy in this population of patients. Methods: In this randomised, double-blind, placebo-controlled trial done at 24 clinical sites in the USA, the Netherlands, and Poland, we investigated the efficacy of cannabidiol as add-on therapy for drop seizures in patients with treatment-resistant Lennox-Gastaut syndrome. Eligible patients (aged 2-55 years) had Lennox-Gastaut syndrome, including a history of slow (<3 Hz) spike-and-wave patterns on electroencephalogram, evidence of more than one type of generalised seizure for at least 6 months, at least two drop seizures per week during the 4-week baseline period, and had not responded to treatment with at least two antiepileptic drugs. Patients were randomly assigned (1:1) using an interactive voice response system, stratified by age group, to receive 20 mg/kg oral cannabidiol daily or matched placebo for 14 weeks. All patients, caregivers, investigators, and individuals assessing data were masked to group assignment. The primary endpoint was percentage change from baseline in monthly frequency of drop seizures during the treatment period, analysed in all patients who received at least one dose of study drug and had post-baseline efficacy data. All randomly assigned patients were included in the safety analyses. This study is registered with, number NCT02224690. Findings: Between April 28, 2015, and Oct 15, 2015, we randomly assigned 171 patients to receive cannabidiol (n=86) or placebo (n=85). 14 patients in the cannabidiol group and one in the placebo group discontinued study treatment; all randomly assigned patients received at least one dose of study treatment and had post-baseline efficacy data. The median percentage reduction in monthly drop seizure frequency from baseline was 43·9% (IQR -69·6 to -1·9) in the cannibidiol group and 21·8% (IQR -45·7 to 1·7) in the placebo group. The estimated median difference between the treatment groups was -17·21 (95% CI -30·32 to -4·09; p=0·0135) during the 14-week treatment period. Adverse events occurred in 74 (86%) of 86 patients in the cannabidiol group and 59 (69%) of 85 patients in the placebo group; most were mild or moderate. The most common adverse events were diarrhoea, somnolence, pyrexia, decreased appetite, and vomiting. 12 (14%) patients in the cannabidiol group and one (1%) patient in the placebo group withdrew from the study because of adverse events. One patient (1%) died in the cannabidiol group, but this was considered unrelated to treatment. Interpretation: Add-on cannabidiol is efficacious for the treatment of patients with drop seizures associated with Lennox-Gastaut syndrome and is generally well tolerated. The long-term efficacy and safety of cannabidiol is currently being assessed in the open-label extension of this trial. Funding: GW Pharmaceuticals.
Significance Medicinal cannabis use is booming despite limited preclinical evidence and mechanistic insight. Recent clinical trials of cannabidiol (CBD) in Dravet syndrome (DS) support its clinical efficacy for reduction of seizure frequency and invite study of its benefits for additional DS symptoms. We demonstrate here that treatment with CBD is beneficial for seizure frequency, duration, and severity and for autistic-like social deficits in a mouse model of DS. CBD rescue of DS symptoms is associated with increased inhibitory neurotransmission, potentially mediated by antagonism of the lipid-activated G protein-coupled receptor GPR55. These studies lend critical support for treatment of seizures in DS with CBD, extend the scope of CBD treatment to autistic-like behaviors, and provide initial mechanistic insights into CBD’s therapeutic actions.
Despite its controversial nature, the use of medical marijuana and cannabis-derived medicinal products grows more popular with each passing year. As of November 2016, over 40 states have passed legislation regarding the use of either medical marijuana or cannabidiol products. Many providers have started encountering patients experimenting with cannabis products for a wide range of conditions. While the debate continues regarding these agents for both medicinal and recreational use in the general population, special consideration needs to be made for pediatric use. This review will deliver the history of marijuana use and legislation in the United States in addition to the currently available medical literature to equip pediatric health care providers with resources to provide patients and their parents the best recommendation for safe and appropriate use of cannabis-containing compounds.
Background The Dravet syndrome is a complex childhood epilepsy disorder that is associated with drug-resistant seizures and a high mortality rate. We studied cannabidiol for the treatment of drug-resistant seizures in the Dravet syndrome. Methods In this double-blind, placebo-controlled trial, we randomly assigned 120 children and young adults with the Dravet syndrome and drug-resistant seizures to receive either cannabidiol oral solution at a dose of 20 mg per kilogram of body weight per day or placebo, in addition to standard antiepileptic treatment. The primary end point was the change in convulsive-seizure frequency over a 14-week treatment period, as compared with a 4-week baseline period. Results The median frequency of convulsive seizures per month decreased from 12.4 to 5.9 with cannabidiol, as compared with a decrease from 14.9 to 14.1 with placebo (adjusted median difference between the cannabidiol group and the placebo group in change in seizure frequency, −22.8 percentage points; 95% confidence interval [CI], −41.1 to −5.4; P=0.01). The percentage of patients who had at least a 50% reduction in convulsive-seizure frequency was 43% with cannabidiol and 27% with placebo (odds ratio, 2.00; 95% CI, 0.93 to 4.30; P=0.08). The patient’s overall condition improved by at least one category on the seven-category Caregiver Global Impression of Change scale in 62% of the cannabidiol group as compared with 34% of the placebo group (P=0.02). The frequency of total seizures of all types was significantly reduced with cannabidiol (P=0.03), but there was no significant reduction in nonconvulsive seizures. The percentage of patients who became seizure-free was 5% with cannabidiol and 0% with placebo (P=0.08). Adverse events that occurred more frequently in the cannabidiol group than in the placebo group included diarrhea, vomiting, fatigue, pyrexia, somnolence, and abnormal results on liver-function tests. There were more withdrawals from the trial in the cannabidiol group. Conclusions Among patients with the Dravet syndrome, cannabidiol resulted in a greater reduction in convulsive-seizure frequency than placebo and was associated with higher rates of adverse events. (Funded by GW Pharmaceuticals; number, NCT02091375.)
Purpose: To introduce a new toolkit for simulation and processing of magnetic resonance spectroscopy (MRS) data, and to demonstrate some of its novel features. Methods: The FID appliance (FID-A) is an open-source, MATLAB-based software toolkit for simulation and processing of MRS data. The software is designed specifically for processing data with multiple dimensions (eg, multiple radiofrequency channels, averages, spectral editing dimensions). It is equipped with functions for importing data in the formats of most major MRI vendors (eg, Siemens, Philips, GE, Agilent) and for exporting data into the formats of several common processing software packages (eg, LCModel, jMRUI, Tarquin). This paper introduces the FID-A software toolkit and uses examples to demonstrate its novel features, namely 1) the use of a spectral registration algorithm to carry out useful processing routines automatically, 2) automatic detection and removal of motion-corrupted scans, and 3) the ability to perform several major aspects of the MRS computational workflow from a single piece of software. This latter feature is illustrated through both high-level processing of in vivo GABA-edited MEGA-PRESS MRS data, as well as detailed quantum mechanical simulations to generate an accurate LCModel basis set for analysis of the same data. Results: All of the described processing steps resulted in a marked improvement in spectral quality compared with unprocessed data. Fitting of MEGA-PRESS data using a customized basis set resulted in improved fitting accuracy compared with a generic MEGA-PRESS basis set. Conclusions: The FID-A software toolkit enables high-level processing of MRS data and accurate simulation of in vivo MRS experiments. Magn Reson Med, 2015. © 2015 Wiley Periodicals, Inc.