Effects of LSD and music on brain activity

Full text

LSD modulates music-induced imagery via
changes in parahippocampal connectivity
Mendel Kaelen
a,
n
, Leor Roseman
a,b
, Joshua Kahan
c
,
Andre Santos-Ribeiro
a
, Csaba Orban
a
, Romy Lorenz
b
,
Frederick S. Barrett
d
, Mark Bolstridge
a
, Tim Williams
e
,
Luke Williams
a
, Matthew B. Wall
a,f,g
, Amanda Feilding
h
,
Suresh Muthukumaraswamy
i
, David J. Nutt
a
,
Robin Carhart-Harris
a
a
Centre for Neuropsychopharmacology, Division of Brain Sciences, Faculty of Medicine,
Imperial College London, London W12, UK
b
The Computational, Cognitive and Clinical Neuroimaging Laboratory, The Centre for Neuroscience,
Division of Brain Sciences, Imperial College London, London W12, UK
c
Sobell Department of Motor Neuroscience & Movement Disorders, Institute of Neurology,
University College London, Queen Square, London WC1N 3BG, UK
d
Behavioral Pharmacology Research Unit, Johns Hopkins School of Medicine, Baltimore, MD 21224, USA
e
Academic Unit of Psychiatry, University of Bristol, Bristol BS8 2BN, UK
f
Imanova Centre for Imaging Sciences, Hammersmith Hospital, London W12, UK
g
Clinical Psychopharmacology Unit, University College London, London UK
h
The Beckley Foundation, Beckley Park, Oxford OX3 9SY, UK
i
Schools of Pharmacy and Psychology, University of Auckland, Auckland 1142, New Zealand
Received 10 November 2015; received in revised form 15 February 2016; accepted 24 March 2016
KEYWORDS
Effective connectiv-
ity;
LSD;
Mental imagery;
Music;
Parahippocampus;
Psychedelic
Abstract
Psychedelic drugs such as lysergic acid diethylamide (LSD) were used extensively in psychiatry
in the past and their therapeutic potential is beginning to be re-examined today. Psychedelic
psychotherapy typically involves a patient lying with their eyes-closed during peak drug effects,
while listening to music and being supervised by trained psychotherapists. In this context, music
is considered to be a key element in the therapeutic model; working in synergy with the drug to
evoke therapeutically meaningful thoughts, emotions and imagery. The underlying mechanisms
involved in this process have, however, never been formally investigated. Here we studied the
interaction between LSD and music-listening on eyes-closed imagery by means of a placebo-
controlled, functional magnetic resonance imaging (fMRI) study. Twelve healthy volunteers
received intravenously administered LSD (75 mg) and, on a separate occasion, placebo, before
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http://dx.doi.org/10.1016/j.euroneuro.2016.03.018
0924-977X/&2016 Elsevier B.V. and ECNP. All rights reserved.
n
Correspondence to: Imperial College London, Burlington Danes Building, Hammersmith Campus, 160 Du Cane Road, London W12, UK.
E-mail address: m.kaelen@imperial.ac.uk (M. Kaelen).
European Neuropsychopharmacology (2016) 26, 1099–1109

being scanned under eyes-closed resting conditions with and without music-listening. The
parahippocampal cortex (PHC) has previously been linked with (1) music-evoked emotion,
(2) the action of psychedelics, and (3) mental imagery. Imaging analyses therefore focused on
changes in the connectivity profile of this particular structure. Results revealed increased PHC–
visual cortex (VC) functional connectivity and PHC to VC information flow in the interaction
between music and LSD. This latter result correlated positively with ratings of enhanced eyes-
closed visual imagery, including imagery of an autobiographical nature. These findings suggest a
plausible mechanism by which LSD works in combination with music listening to enhance certain
subjective experiences that may be useful in a therapeutic context.
&2016 Elsevier B.V. and ECNP. All rights reserved.
1. Introduction
Humans have chosen to alter their consciousness via psy-
chedelic drugs for millennia, and often in combination with
music (Nettl, 1956). In the 1950s and 1960s, psychedelic
drugs such as lysergic acid diethylamide (LSD) were used in
psychotherapy, and modern clinical trials are re-examining
their therapeutic potential (Bogenschutz et al., 2015;
Gasser et al., 2014;Grob et al., 2011;Johnson et al.,
2014). Since the inception of psychedelic-assisted psy-
chotherapy, music-listening has been considered an impor-
tant component in the therapeutic model (Bonny and
Pahnke, 1972). It is believed that music acts synergistically
with the drug to enhance emotionality, mental imagery, and
access to personal memories (Bonny and Pahnke, 1972;
Grof, 1980;Kaelen et al., 2015).
1
The main aim of the
present study was to investigate the brain mechanisms
underlying the effects of LSD and music on mental imagery.
The characteristic subjective effects of LSD and other
psychedelics such as psilocybin are thought to depend on
agonist actions at the serotonin 2A receptor (Glennon
et al., 1984;Vollenweider et al., 1998). The serotonin 2A
receptor is expressed on “excitatory”deep layer pyramidal
cells, as well as on a smaller proportion of “inhibitory”
interneurons (Andrade, 2011;Celada et al., 2013). Its
activation depolarises the cell membrane of the host
neuron, increasing its likelihood of firing (Aghajanian and
Marek, 1999). Although expressed throughout the neo-
cortex (Pazosetal.,1987), the serotonin 2A receptor is
especially highly expressed in high-level association cor-
tices, including the anterior cingulate cortex (ACC), pos-
terior cingulate cortex (PCC) and insula, but also in the
visual cortex (VC) and, to a lesser extent, the entorhinal
cortex (Erritzoe et al., 2009;Ettrup et al., 2014;Pazos
et al., 1987). Not surprisingly, functional neuroimaging
studies revealed altered activity in these brain regions
during serotonin 2A receptor agonist-induced psychedelic
states (Carhart-Harris et al., 2012a;Muthukumaraswamy
et al., 2013;Riba et al., 2002;Vollenweider et al., 1997).
Of particular interest to the present study are the effects
of psychedelics and music-listening on activity in the
parahippocampal cortex (PHC). The PHC is an important
hub within the medial temporal lobe (MTL) (Burwell, 2000;
Eichenbaum and Lipton, 2008), and it's acute functioning is
appreciably altered by psychedelics as determined by fMRI
(Kometer et al., 2015;Tagliazucchi et al., 2014), depth EEG
(Monroe et al., 1957;Schwarz et al., 1956) and PET
(Vollenweider et al., 1997). Furthermore, attenuation of
the subjective and behavioural effects of LSD were observed
after resection of the MTLs in humans (Serafetinides, 1965)
and chimpanzees (Ramey and O'Doherty, 1960).
Activation of the PHC is found during spatial navigation
(Aguirre and D’Esposito, 1999;Epstein, 2008), imagining
scenes (Spreng et al., 2009), emotional arousal (LaBar and
Cabeza, 2006;Smith et al., 2004) and personal memory
recall (Fink et al., 1996). Importantly, the PHC is also
implicated in music-evoked emotion (Baumgartner et al.,
2006;Gosselin et al., 2006;Koelsch, 2014) and music-evoked
personal memories (Janata, 2009). Damage to the PHC can
result in impaired music-evoked emotion (Gosselin et al.,
2006) and visual deficits (Harding et al., 2002;Hensley-Judge
et al., 2013), whereas direct stimulation of the PHC can
producevisualhallucinationsofscenes(Mégevand et al.,
2014), autobiographical memories (Vignal et al., 2007)and
dream-like states (Bancaud et al., 1994;Barbeau et al.,
2005;Bartolomei et al., 2004), accompanied by enhanced
coupling between the PHC and the VC (Barbeau et al., 2005).
These insights motivated the present hypothesis that LSD,
in combination with music-listening, modulates PHC func-
tional connectivity. This hypothesis was tested using func-
tional magnetic resonance imaging (fMRI) and a balanced-
order, placebo-controlled design. Participants completed
ratings of eye-closed visual imagery and spontaneous auto-
biographical memory recollection. Acute changes in PHC
functional connectivity informed a subsequent Dynamic
Causal Modelling (DCM) analysis that assessed how music
and LSD interact to change the direction of information flow
between the PHC and the VC (i.e. effective connectivity).
1
By the late 1960s there existed, broadly speaking, two schools of thoughts around the therapeutic use of psychedelics –and these differed
in the significance they attributed to music. In the United States, higher dosages of psychedelics were administered, with the goal to
facilitate a peak- or mystical-type experience to promote long lasting change in personality traits and behaviour. Here, music was typically
played for the entire duration of the drug effects, with intermittent periods of silence. In Europe, psycholytic therapy became more widely
practiced. This method involved more frequent administration of lower dosages of a psychedelic, and with more interaction between
therapist and patient. Music was played for to help with relaxation, or to support intermittent periods of introspection.
M. Kaelen et al.1100

2. Experimental procedures
2.1. Approvals
This study was approved by the National Research Ethics
Service (NRES) committee London –West London and was
conducted in accordance with the revised declaration of
Helsinki (2000), the International Committee on Harmonisa-
tion Good Clinical Practice guidelines and National Health
Service (NHS) Research Governance Framework. Imperial
College London sponsored the research which was con-
ducted under a Home Office license for research with
schedule I drugs.
2.2. Participants
Twenty participants (16 males and 4 females) were
recruited, carefully screened for physical and mental health
and provided written informed consent before participa-
tion. The screening for physical health included electro-
cardiogram (ECG), routine blood tests, and urine test for
recent drug use and pregnancy. A psychiatric assessment
was conducted and participants provided full disclosure of
their drug use history. Key exclusion criteria included: being
younger than 21 years of age, having a personal history of
diagnosed psychiatric illness, an immediate family history of
a psychotic disorder, an absence of previous experience
with a classic psychedelic drug (e.g. LSD, mescaline,
psilocybin or dimethyltryptamine (DMT), drug use within
6 weeks of the first scanning day, a persistent adverse
reaction to a psychedelic drug, pregnancy, problematic
alcohol-use (i.e. 440 units consumed per week), and/or a
medically significant condition rendering them unsuitable
for the study.
2.3. Study setting and overview
Screening took place at Imperial's clinical research facility
at the Hammersmith hospital campus. All study days were
performed at Cardiff University Brain Research Imaging
Centre (CUBRIC). Eligible participants attended two study
days that were separated by at least 14 days. LSD was
received on one of the study days, and placebo on the other.
The order of receipt of LSD was balanced across partici-
pants, and they were kept blind to this order but the
researchers were not.
On scanning days, volunteers arrived at the study centre
at 8:00 am, were given a detailed brief about the study day
schedule, gave a urine test for recent drug-use and preg-
nancy, and carried out a breathalyser test for recent
alcohol-use. A cannula was inserted into a vein in the
antecubital fossa by a medical doctor and secured. Partici-
pants were encouraged to close their eyes and relax in a
reclined position while the drug was administered. All
participants received 75 mg of LSD, administered intrave-
nously via a 10 ml solution infused over a two minute
period, followed by an infusion of saline. Dosing was
followed by an acclimatisation period of approximately
60 min, in which (for at least some of the time) participants
were encouraged to relax and lie with their eyes closed
inside a mock MRI scanner. This functioned to prepare the
participants for the subsequent (potentially anxiogenic
(Studerus et al., 2012)) MRI scanning experience.
Participants reported noticing subjective drug effects
between 5 and 15 min post-dosing, and these approached
peak intensity between 60 and 90 min post-dosing. The
duration of a subsequent plateau of drug effects varied
among individuals but was generally maintained for approxi-
mately four hours post-dosing. BOLD MRI scanning started
approximately 120 min post-dosing, and lasted for approxi-
mately 60 min. This included a structural scan, arterial spin
labelling (ASL) fMRI, and BOLD fMRI. After the MRI scanning,
magnetoencephalography (MEG) scanning was performed
but these findings will be reported elsewhere. Once the
subjective effects of LSD had sufficiently subsided, the
study psychiatrist assessed the participant's suitability for
discharge.
3. Experimental design
Each fMRI scanning session involved three eyes-closed
resting state scans, each lasting seven minutes. After each
seven minute scan, visual analogue scale (VAS) ratings were
performed in the scanner via a response-box. The music-
listening scan always occurred after the first resting state
(no music) scan and before a final resting-state scan (no
music). The music itself was triggered by the first TR, and
listened to via MRI compatible headphones (MR Confon).
Two seven-minute long excerpts (A and B) were selected
from the album Yearning, by ambient artist Robert Rich and
classical Indian musician Lisa Moskow. Pre-study assessments
confirmed the two excerpts to be balanced for their
emotional potency. Each participant listened to both sti-
muli, in a balanced order across conditions. Volume-
maximisation and broadband compression was carried out
using Ableton live 9 software.
Prior to each scan, participants were instructed via a
display screen to close their eyes and relax. Prior to the
music scan, the music volume was adjusted to a level that
was “as loud as possible, without being unpleasant”and
then maintained for each condition. When the music ended,
participants were instructed to open their eyes and rate the
degree of simple visual imagery (i.e. “with my eyes closed I
saw colours or geometric patterns”) and complex visual
imagery (i.e. “with my eyes closed I saw complex visual
imagery”) they experienced. Complex imagery was pre-
defined as: static or dynamic images of objects or entities
(e.g. plants, buildings, people or animals) and complex
scenes. Items were completed on a continuous visual
analogue scale from 0 (“not at all”)to20(“extremely
intense”). Soon after the MRI scanning session was com-
plete, participants rated some further VAS items that
assessed their subjective experience during scanning. The
VAS item “I saw scenes from my past”was selected for
special consideration because of personal memory recollec-
tion being consistently associated with PHC functioning
(Fink et al., 1996;Spreng et al., 2009), as well as a prior
hypothesis inspired by previous findings (Carhart-Harris
et al., 2012b) that this would be modulated by the experi-
mental conditions.
1101LSD modulates music-induced imagery via changes in parahippocampal connectivity

3.1. MRI scanner and data pre-processing
All imaging was performed on a 3T GE HDx system. For
registration and segmentation of functional images, an
initial 3D FSPGR anatomical scan was obtained in an axial
orientation, with field of view=256 256 192 and
matrix=256 256 192 to yield 1-mm isotropic voxel reso-
lution (TR/TE=7.9/3.0 ms; inversion time=450 ms; flip
angle=201). Functional images were acquired using a
gradient echo planer imaging sequence, TR/TE=2000/
35 ms, field-of-view =220 mm, 64 64 acquisition matrix,
parallel acceleration factor=2, 901flip angle. Thirty five
oblique axial slices were acquired in an interleaved fashion,
each 3.4 mm thick with zero slice gap (3.4 mm isotropic
voxels). The precise length of each of the BOLD scans was
7:20 min.
Preprocessing utilised a combination of AFNI (Cox, 1996),
FSL (Smith et al., 2004b), Freesurfer (Dale et al., 1999) and
ANTS (Avants et al., 2011). After brain extraction (Free-
surfer), anatomical images were segmented into their three
underlying tissue types: cerebrospinal fluid (CSF), grey
matter (GM) and white matter (WM) (fast, FSL) and regis-
tered to a 2 mm MNI152 template using affine (ANTS),
followed by non-linear transformation (SyN, ANTS). Anato-
mical images also underwent segmentation to define sub-
cortical structures (Freesurfer).
One participant was excluded from analyses because of
early termination of the scanning due to him reporting
significant anxiety. Three participants were excluded from
analyses due to technical problems with the sound delivery
and four more subjects were discarded from the group
analyses due to excessive head movement. This leaves a
total of twelve participants that entered the group ana-
lyses. Principally, motion was measured using frame-wise
displacement (FD) (Power et al., 2014). The criterion for
exclusion for excessive head movement was subjects dis-
playing higher than 15% scrubbed volumes when the scrub-
bing threshold is FD=0.5. After discarding these subjects,
we reduced the threshold to FD=0.4. The between-
condition difference in mean FD for the 4 subjects that
were discarded was 0.28670.185 and for the 12 subjects
that were used in the analysis the difference in mean FD
was 0.04970.029 (mean FD for placebo was 0.08570.028
and mean FD for LSD was 0.13470.037, p=0.0001).
Functional images were pre-processed according to the
following sequence: (1) Removal of first three volumes (2)
de-spiking (3dDespike, AFNI), (3) slice time correction
(3dTshift, AFNI), (4) motion correction (3dvolreg, AFNI),
(5) brain extraction (bet, FSL), (6) rigid body registration to
anatomical scans (nine subjects with FSL's BBR, one subject
with Freesurfer's bbregister and two subjects manually),
(7) transformation of functional to MNI 2 mm space, using
previously calculated transformation matrix from the ana-
tomical scans, (8) motion scrubbing using an FD threshold of
0.4, and replacement with the mean of neighbouring
volumes (mean percentage of volumes scrubbed for placebo
and for LSD was 0.5%71 and 1.9%72.2, respectively.
Maximum volumes scrubbed for scan was 7.8%), (9) spatial
smoothing with a Gaussian kernel of 6 mm (FWHM) (3dBlur-
InMask, AFNI), (10) band-pass filtering between 0.01 and
0.08 Hz (3dFourier, AFNI), and (11) linear and quadratic
de-trending and regression of 9 nuisance parameters: 6
motion-related (3 translations, 3 rotations) and 3
anatomically-defined.
The anatomically defined regressors consisted of Ventri-
cles (Freesurfer), Cerebrospinal fluid (CSF) (FSL's FAST with
Freesurfer's Ventricles subtracted) and White matter (WM)
(FSL's FAST with Freesurfer's subcortical grey-matter sub-
tracted). All three masks were eroded to reduce partial
volume effects and were used to extract nuisance time-
series from an unsmoothed version of the pre-processed
functional data. The CSF and Venticles were used to extract
a single mean time-course for each mask, while WM mask
was used to produce a voxelwise regressor (3dLocalStat,
AFNI). Voxelwise WM regression has been found to outper-
form approaches using whole-brain averaged WM signal (Jo
et al., 2010,2013).
3.2. Subjective effects
A two-way repeated measures ANOVA with two factors (drug
condition and music condition) was performed to test for an
interaction between LSD and music on in-scanner ratings of
simple and complex hallucinations. A paired one-tailed t-
test was performed to examine between-condition differ-
ences in the post-scanner questionnaire item “I saw scenes
from my past”.
3.3. Seed-based functional connectivity analysis
A bilateral PHC region of interest (ROI) was acquired from
the Harvard anatomical atlas tool and used to extract PHC
time series for each subject. To begin with, a general linear
model (GLM) was used (FEAT, FSL) to model whole brain
resting state functional connectivity with the PHC seed,
with correction for autocorrelations (FILM, FSL) for each run
separately. Next, a fixed-effects model was used to compare
music versus non-music runs for each subject, for LSD and
placebo separately. Finally, these drug effects (LSD versus
placebo) were fed into a higher-level mixed effects model
(FLAME1, FSL) to calculate the modulation of the effects of
music by LSD on PHC functional connectivity across the
brain (cluster correction threshold z42.3, po0.05).
3.4. Dynamic causal modelling: background and
implementation
Dynamic Causal Modelling (DCM, as implemented in SPM12b)
was used to estimate changes in effective connectivity. DCM
is a biologically-informed modelling procedure that estimates
the causal interactions (i.e. effective connectivity) between
different pre-selected nodes of a network, and the changes in
coupling strength between and within those nodes (extrinsic
and intrinsic connections respectively) due to experimental
manipulations (Friston et al., 2003). The basic architecture of
amodelisdefined by structurally plausible and functionally-
informed brain regions, whose connections are defined as
either bilinear (i.e. information flow between regions) or
non-linear (i.e. activity in one region modulating information
flow between regions). Typically, experimental manipulations
can directly affect activity in each node (as ‘driving inputs’)
M. Kaelen et al.1102

or alter the strength of coupling within or between nodes (as
‘modulatory inputs’).
In the present study, all six scans were concatenated in
the following order: placebo no-music (NM), placebo music
(M), placebo NM, LSD NM, LSD M, LSD NM. The measured
BOLD time-series for the DCM were extracted as the first
principal eigenvalue from a bilateral PHC and VC mask (The
PHC mask was defined by Harvard-Oxford atlas, and the VC
mask was defined by results of the PHC functional con-
nectivity analysis, i.e. the occipital cluster), and adjusted
for the effects of interest (i.e. main effect of music, main
effect of drug, and an interaction effect –described below).
Between-node connections were defined as bilinear mean-
ing that information flow could be modulated in either
direction. Three experimental inputs entered the model as
modulatory inputs: a main drug effect, a main music effect,
and an interaction effect of music and drug (0.5–1 0.5–0.5 1–
0.5). Due to the resting-state conditions of the scanning,
activity in the nodes was driven by stochastic (i.e. sponta-
neous) fluctuations (Li et al., 2011).
3.5. Dynamic causal modelling: Bayesian model
selection
In DCM, a series of plausible models, representing compet-
ing hypotheses, are specified. Each model corresponds to a
hypothesis about how observed changes in BOLD signal were
caused by changes in neural activity in each network node.
The different models can vary in terms of the position of
driving and modulatory inputs. DCM uses a biophysical
model of the hemodynamic response to predict the under-
ling neuronal activity –and the underlying (changes in)
connectivity –from the observed BOLD signal (see
Figure 2D). Model estimation, or inversion, returns condi-
tional estimates for the changes in connectivity and scores
the model in terms of its accuracy and complexity (using a
Free Energy bound on log model evidence). Bayesian Model
Selection (BMS) is used to compare different models to
identify the model with the greatest evidence –i.e. the
model that offers the best explanation of the data. In the
present study, one “full model”was specified, with all three
experimental inputs modulating all extrinsic and intrinsic
connections. Following inversion of this full model, a post
hoc Bayesian model optimisation scheme was used to
identify the model structure with the greatest model
evidence (i.e. lowest free energy). This approach provides
an efficient scheme for scoring large numbers of competing
models (Friston and Penny, 2011). Optimal model structure
is usually determined by computing Bayes factors, as an
approximation of the model evidence. A Bayes factor of 20
corresponds to a belief of 95% in the statement that a
particular hypothesis (i.e. the proposed model) is true, and
therefore a p-value of 0.05. A Bayes factor higher than 150
corresponds to a belief of 99% in the hypothesis, and
equates a p-value smaller than 0.01. A Bayes factor higher
than 20 is therefore considered as strong evidence for the
proposed model (Penny et al., 2004). After model selection,
coupling parameters are analysed post-hoc to characterize
the size and direction of the changes in connection strength
caused by the experimental manipulations. Coupling para-
meters quantify the strength of the coupling in terms of the
rate (in Hz) at which a response is caused in a given region,
and modulation is expressed as either an increase or
decrease in this coupling measure.
3.6. Correlations with subjective effects
Following model selection, the hypothesis was tested that
the magnitude of the modulation in effective connectivity
by the music drug interaction would explain the observed
variance in participants’subjective responses to the music
under LSD. More specifically, we asked whether the size of
the interaction effect as estimated by the DCM, correlated
with the magnitude of the enhancement of (1) eyes-closed
imagery and (2) visions of one's past (“I saw scenes from my
past”). A spearman's correlation was used due the non-
parametric nature of the data.
4. Results
4.1. Participant demographics
The data from twelve participants were found suitable for
data-analysis (2 female, mean age=3379 years, range 22–47
years). All had at least one previous experience with a classic
psychedelic drug. Mean estimated lifetime LSD-use was
12715 (range=0–40). Self-estimates of other drug-use were
as follows (mean7SD, range): weekly alcohol units=878, 0–
28; daily cigarettes=0; lifetime cannabis uses=6867625,
30–2000; lifetime MDMA uses=20718, 2–50; lifetime psilocy-
bin/magic mushroom uses=1079, 1–35; lifetime ayahuasca/
DMT uses=14721, 0–50; lifetime ketamine uses=376, 0–20;
lifetime cocaine uses=678, 0–20; lifetime amphetamine
uses=6711, 0–35; lifetime heroin uses=173, 0–10.
4.2. Subjective effects
A paired t-test revealed a significant increase in personal
memory recollection under LSD (t=1.9, df=19, p=0.04).
For simple hallucinations, a two-way ANOVA revealed a
significant drug effect (F=42.2, df=18, po0.001) but no
significant effects were found for music (F=1.7, df=18,
p=0.2) or the interaction between music and LSD (F=1.1,
df =18, p=0.3). For complex hallucinations, a two-way
ANOVA revealed a significant drug effect (F=24.7, df =18,
po0.001), a trend level effect of music (F=10.0, df=18,
p=0.09), but again, no significant interaction effect for
music LSD (F=1.8, df=18, p=0.5). Drug effects on simple
and complex hallucinations survived multiple comparisons,
using Bonferroni adjusted alpha levels of 0.025 per test
(0.05/2).
4.3. Functional connectivity
Seed-based functional connectivity analysis of the bilateral
PHC showed a positive interaction between music and LSD
for the contrast LSD (music versus no music) versus placebo
(music versus no music), with increased coupling between
the PHC and two main clusters: One being the bilateral
visual cortex and the other being the left inferior frontal
gyrus (see Table 1 and Figure 1a). No decreases in PHC
1103LSD modulates music-induced imagery via changes in parahippocampal connectivity

functional connectivity were observed for this contrast. A
two-way repeated-measures ANOVA on z-scores for the VC
did not show a significant effect of drug (F=0.49, df =11,
p=0.5) or music (F=2.27, df=11, p=0.16), but did reveal
an interaction effect of music and LSD (F=17.04, df =11,
p=0.002) (see Figure 1b. for a plot of the z-scores).
4.4. Dynamic causal modelling
Post-hoc model optimisation determined the optimal model
structure. The optimal model had a Bayes factor 344 higher
than the preceding model architecture. This equates, in a
frequentist statistical approach, to a p-value much smaller
than 0.01, and is therefore considered as strong evidence
for the model. The optimal model features a main effect of
drug and music modulating the intrinsic connections of both
nodes, and an interaction effect modulating the connection
from the PHC to the VC. Group averages for the posterior
estimates are 0.4170.05 Hz for drug effect on PHC,
0.4270.06 Hz for music effect on PHC, 0.3870.06 Hz
for drug effect on VC, and 0.4070.06 Hz for music effect
on VC. The group average of the posterior estimate for the
interaction effect is 0.0270.04 Hz (Table 2).
4.5. Correlations
A significant positive correlation was found between the
interaction effect of LSD and music on PHC to VC effective
connectivity, and increases in the in-scanner ratings for
complex visual imagery (Spearman's ρ=0.71, with p=0.01,
and Pearson r=0.65, with p=0.03). A trend-level positive
correlation was found between the interaction effect of LSD
and music on PHC to VC, and the post-scanner questionnaire
item “I saw scenes from my past”(Spearman ρ=0.67, with
p=0.02, and Pearson r=0.69, with p=0.01). These tests
were conducted using Bonferroni adjusted alpha levels of
0.0167 per test (0.05/3) (see Figure 3).
5. Discussion
The present study has demonstrated that increased PHC–VC
effective connectivity during music-listening under LSD
correlates with enhancements in eyes-closed mental-ima-
gery. These results are consistent with current thinking on
the role of the PHC in mental imagery, and provide new
insights into the brain mechanisms by which psychedelics
Table 1 Brain regions showing increased coupling with the parahippocampus.
Cluster Region Lateralization Size (mm) Peak z-score Peak coordinates (mm)
Occipital Calcarine fissure L 3722 4.02 8,76,8
Calcarine fissure R 4516 4.02 6,84,8
Cuneus L 4190 3.62 4,80,6
Cuneus R 2732 3.44 8, 88,10
Lingual cortex L 4600 3.29 6,78,4
Lingual cortex R 3052 3.28 6, 76,20
Superior occipital gyrus L 5036 3.07 26,78,2
Fusiform gyrus R 2848 2.74 12,70,22
Inferior frontal Middle frontal cortex L 3380 3.52 30,32, 8
Inferior frontal gyrus, opercular L 5058 3.47 44,36,22
Inferior frontal gyrus, triangularis L 9726 3.33 42,38,22
Precentral gyrus L 7052 3.28 56,2,28
Inferior frontal gyrus, orbitalis L 2076 3.27 44,12,18
Insula L 3716 3.11 32,22,14
Figure 1 Seed-based functional connectivity analysis of the bilateral parahippocampus. (A) Brain regions showing increased
coupling (displayed in yellow, cluster-corrected, Z42.3) with the bilateral PHC (displayed in red) for the contrast LSD (music4no
music)4placebo (music4no music) (the left side of the brain is shown on the right side of the brain in these images, as if the body is
being viewed through the soles of the feet). Significant effects were observed in the primary visual cortex, left anterior insula, and
left inferior frontal cortex. (B) Coupling between the PHC and the visual cortex under LSD and placebo (NM=No Music, M=Music)
(For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article).
M. Kaelen et al.1104

may enhance some of the subjective effects of music-
listening.
The PHC is implicated in the generation of visual mental
imagery (Brewer et al., 1998;Epstein, 2008), personal
memory recollection (Fink et al., 1996;Spreng et al.,
2009) and music-evoked personal memories (Janata,
2009). Within the MTL system, the PHC primarily functions
to encode and retrieve context-related memory content
(Ranganath and Ritchey, 2012), which is consistent with
complex rather than simple visual imagery. Direct structural
(Catani et al., 2002) and functional (Libby et al., 2012;
Powell et al., 2004) connections between the PHC and the
VC have been detected, and increased information flow
from the PHC to the VC (i.e. effective connectivity) has
previously been found to occur during the construction of
visually imagined scenery (Chadwick et al., 2013). Interest-
ingly, direct stimulation of the PHC can produce visual
hallucinations of complex scenes (Mégevand et al., 2014)
and autobiographical memories (Bancaud et al., 1994;
Bartolomei et al., 2004), and there is evidence that this is
related to a strengthening of PHC–VC coupling (Barbeau
et al., 2005). Damage to the PHC can result in visual neglect
(Hensley-Judge et al., 2013) visual hallucinations (Harding
et al., 2002) and hippocampal damage has been linked to an
impaired ability to imagine complex scenes (Cooper et al.,
2011).
In sum, these findings suggest that PHC–VC effective
connectivity constitutes an important pathway for the
construction of visual imagery (Chadwick et al., 2013;
Zeidman et al., 2014). Mechanistically, increased informa-
tion flow from the PHC to the visual cortex may correspond
to an increase in top-down (prior) information (instantiated
by PHC activity) being conferred on activity in the lower
levels of the visual system (that normally processes incom-
ing visual information) (Aguirre and D’Esposito, 1999;Libby
et al., 2012;Summerfield et al., 2006). The present study
has shown that the combination of LSD and music modulates
information flow from the PHC to the VC, and that the
Figure 2 Dynamic Causal Modelling. (A) Time series that enter the DCM are extracted as first principal eigenvalues from the PHC
mask and the VC mask (the latter is defined by the seed-based functional connectivity result) (Dale et al., 1999). The full DCM that
enters the Bayesian model selection (BMS) after model estimation. The model has two nodes (PHC and VC) that are connected via
extrinsic bilinear connections, and each node has one intrinsic connection. Every connection has three modulatory effects: D=main
drug effect, M=main music effect, I=Interaction effect. The nodes are driven by stochastic fluctuation. (C) Post-hoc model
optimisation determined the optimal model structure. Dashed lines indicate a negative connection or modulation, whereas normal
lines indicate a positive connection or modulation. This model has the main effect of drug and the main effect of music modulating
the intrinsic-connections of both nodes. The interaction effect has a modulatory effect on the connection from PHC to VC. (D) The
sum estimated neural activity in each node is convolved by the hemodynamic response function to yield a predicted BOLD response.
The predicted BOLD response is compared to the observed BOLD response to determine how well the model explains the data.
Displayed are predicted and observed time-series from one subject for illustration purposes. (E) Scatterplots illustrate model fitby
correlation of predicted verses observed BOLD responses for both regions.
Table 2 Pearson correlation coefficients from all par-
ticipants for predicted versus observed BOLD signals for
visual cortex (VC) and parahippocampus (PHC).
Participant VC PHC
1 0.95 0.94
2 0.91 0.97
3 0.89 0.91
4 0.92 0.95
5 0.88 0.93
6 0.91 0.93
7 0.97 0.95
8 0.82 0.87
9 0.93 0.90
10 0.92 0.96
11 0.88 0.86
12 0.85 0.94
1105LSD modulates music-induced imagery via changes in parahippocampal connectivity

magnitude of this modulation predicts enhanced visual
imagery. Importantly, this correlation was only evident for
the complex visual imagery item (defined as the eyes-closed
hallucinations of objects, entities and scenes), and not for
simple imagery (defined as low-level visual features such as
colours and patterns). We therefore propose that the
experience of perceiving complex imagery whilst listening
to music under LSD may be the result of an enhanced gain
on circuits (such as the PHC to VC circuit) that normally
confer complex, top-down information about (a potential)
visual scene. Perceiving complex scenes in the absence of
visual input may therefore result from a “flip”in the normal
direction of information flow within the visual system such
that higher-level components of the system, responsible for
processing high-level features, take precedence over incom-
ing sensory information.
The PHC possesses high baseline connectivity with high-
level cortical regions such as those that make-up the so-
called default-mode network (Raichle et al., 2001;Ward
et al., 2014). Under normal conditions, the top-down inhibi-
tory control over PHC activity is provided by projections from
the posterior cingulate cortex (PCC), the retrosplenial cortex
(RSC) and the medial prefrontal cortex (mPFC), that termi-
nate on interneurons within the PHC (Mohedano-Moriano
et al., 2007;Morris et al., 1999;Vann et al., 2009). The
RSC, PCC and mPFC express notably high levels of serotonin
2A receptors (Erritzoe et al., 2009), and psychedelics have a
dysregulating effect on activity within these regions
(Carhart-Harris et al., 2012a;Muthukumaraswamy et al.,
2013). The dysregulating effect of psychedelics on activity in
these cortical regions may compromise their ability to
maintain top-down control over the PHC. Indeed, reduced
functional connectivity between the PHC and the RSC has
been observed after both psilocybin and LSD (Carhart-Harris
et al., 2014). Thus, the effects of psychedelics on the PHC's
inhibitory afferents may increase its sensitivity and respon-
siveness to stimuli that normally engage it, such as music
(Koelsch, 2014;Mitterschiffthaler et al., 2007;Tros t e t a l . ,
2012)orodour(Jung et al., 2006).
Effects of sound on eyes-closed visual experiences under
LSD have been reported since its discovery. Albert Hoffman,
who discovered the powerful psychoactive effects of LSD by
accidentally intoxicating himself, describes his experience
in his memoir (Hoffman, 1970): “It was particularly remark-
able how every acoustic perception, such as the sound of a
door handle or a passing automobile, became transformed
into optical perceptions. Every sound generated a vividly
changing image, with its own consistent form and colour.”
Such experiences are often compared to synaesthesia, a
neurological condition characterized by involuntarily sen-
sory experiences (for example seeing a colour) in response
to a different sensory stimulus (for example, hearing a
sound). Synaesthesia is characterized by responses that are
consistent to a specific stimulus (Ward, 2013), and it is
therefore not possible to say to what extent the audio-visual
experiences reported under LSD can be formally be termed
“synesthetic”in the conventional sense. The present results
do, however, suggest a plausible mechanism via which such
experiences can arise, and highlight how psychedelics can
inform on the neuroscience of sensory processing.
5.1. Implications for psychedelic-assisted
psychotherapy
Music is an effective medium for evoking emotion (Trost
et al., 2012) and autobiographical memories (Janata, 2009;
Janata et al., 2007) and these effects of music have been
therapeutically exploited (Castillo-Pérez et al., 2010;
Erkkilä et al., 2011). Music may serve to deepen the
psychedelic experience by enhancing emotional engage-
ment (Kaelen et al., 2015) and stimulating personally
meaningful mental imagery (Carhart-Harris et al., 2012b).
The findings of the present study help to elucidate the
mechanisms by which music and psychedelics can do this
but further research is required to test its therapeutic value
directly.
5.2. Limitations
No interaction was found between LSD and music on in-
scanner subjective ratings, whereas connectivity analyses
did show a significant interaction effect on PHC–VC cou-
pling. Since enhanced PHC–VC coupling via the interaction
between LSD and music correlated with complex mental
imagery, this could be explained by individual differences in
Figure 3 Correlation analyses suggest that the interaction between LSD and music induces certain subjective experiences via
increasing the influence of PHC activity on VC activity. Changes in coupling parameters are displayed on the x-axis and are
significantly correlated with: (A) increases in complex visual imagery (Y-axis) (i.e. music4rest for LSD4placebo) and (B) increases
in visions of one's personal past (Y-axis) (i.e. LSD4placebo).
M. Kaelen et al.1106

subjective response to LSD and music, and perhaps appraisal
of the subjective experience. For example, it may have
been the case that some participants disliked the genre of
music or were distracted by the considerable ambient noise
emitted by the MRI machinery. Some participants may also
have been emotionally relaxed by the particular music that
was chosen, rather than emotionally stimulated. Further
work is required to test these different hypotheses. For
example, a study could be designed that incorporates more
than one genre of music (e.g. emotionally relaxing music
versus emotionally evocative and/or arousing music).
Finally, the present results cannot be extrapolated to a
patient population, in which the music psychedelic inter-
action is thought to be especially important (Bonny and
Pahnke, 1972;Kaelen et al., 2015). Subsequent work is
therefore needed to further our understanding of how music
and psychedelics interact and how this may be useful for
psychedelic-assisted therapy.
6. Conclusions
The present study revealed a positive interaction between
LSD and music on PHC functional and effective connectivity.
More specifically, a modulation of PHC to VC connectivity
was observed that correlated positively with eyes-closed
visual imagery, and particularly imagery of a complex and
autobiographical nature. These results extend our under-
standing of circuitry involved in visual imagery and suggest
how LSD and music can work in synergy to enhance this
phenomenon. The present results provide the beginnings of
a mechanistic explanation for the role of music listening in
psychedelic drug-assisted psychotherapy; however, a large
amount of work is required to develop our understanding of
whether and how psychedelic-assisted psychotherapy can
be effective.
Role of funding source
The Beckley Foundation provided financial and intellectual support,
and the study was conducted as part of a wider Beckley-Imperial
research programme. The researchers also received financial sup-
port from the Walacea.com crowd-funding campaign. The report
presents independent research carried out at the NIHR/Wellcome
Trust Imperial Clinical Research Facility. The Beckley Foundation
and the Walacea crowd-funding campaign had no further role in
study design; in the collection, analysis and interpretation of data;
in the writing of the report; and in the decision to submit the paper
for publication.
Contributors
MK designed and coordinated the study, carried out data collection,
undertook data analyses and wrote the first draft of the manuscript.
LR, JK, ASR, CO and RL undertook data analyses. MB, TW and LW
carried out data collection. FSB, MBW, AF helped designing the
study.SM and DJN helped designing and coordinating the study. RCH
designed and coordinated the study, and carried out data collection
and writing of the manuscript. All authors contributed to and have
approved the final manuscript.
Conflict of interest
Author MBW's primary employer is Imanova Ltd., a private company
that performs contract research work for the pharmaceutical and
biotechnology industries. All other authors declare that they have
no conflicts of interest.
Acknowdgements
This research received financial and intellectual support from the
Beckley Foundation (Grant number: P41825) and was conducted as
part of a wider Beckley-Imperial research programme. The
researchers would like to thank supporters of the Walacea.com
crowd-funding campaign who played a crucial role in securing funds
to complete the study.
Appendix A. Supplementary material
Supplementary data associated with this article can be
found in the online version at http://dx.doi.org/10.1016/
j.euroneuro.2016.03.018.
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1109LSD modulates music-induced imagery via changes in parahippocampal connectivity