subjects with psychosis were significantly less
sensitive to the changes in contingency as the task
progressed. Psychotic symptoms are often associated with pathological rigidity. Belief-updating
correlated with responses in the hippocampus
and cerebellum. Hippocampal activity correlates
with uncertainty in perceptual predictions (23).
The cerebellum has likewise been associated with
production and updating of predictive models (24).
Our X1, X2, and n findings are consistent with
a strong-prior theory of hallucinations. The X3
findings in psychotic patients may reflect a strong
prior that contingencies are fixed. On the other
hand, they could reflect a weak prior on volatility.
These beliefs were not associated with hallucinations but rather psychosis more broadly. Under
chronic uncertainty, secondary to consistent belief violation, it may be adaptive to resist updating beliefs (25).
Consistent with previous work applying signal
detection theory (SDT) to AVH (26), we found
liberal criteria and low perceptual sensitivity in
our H+ groups. A liberal criterion may reflect poor
reality monitoring (26). However, meta-d' (a metric
of participants’ meta-cognitive sensitivity) did
not differ significantly between groups (fig. S6).
SDT is a descriptive tool that does not distinguish aberrant perceptions from decisions.
Our modeling work, however, localized group
differences to the perceptual model alone. The
prior weighting parameter (n) distinguished
H+ from H– groups and also predicted confidence in conditioned hallucinations (fig. S7).
Our observations support an explanation of hallucinations based on strong perceptual priors.
They suggest precision treatments for hallucinations, such as targeting cholinergically mediated
priors (27), and interventions to mollify psychosis
more broadly, such as cerebellar transcranial
magnetic stimulation (28).
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The authors dedicate this work to the memory and legacy of
Ralph E. Hoffman, M.D. Additional thanks go to M. Kelley, A. Bianchi,
S. Bhatt, and E. Feeney for technical assistance as well as
A. Nidiffer, L. Marks, S. Woods, and J. Krystal for their advice. This
work was supported by the Connecticut Mental Health Center
(CMHC) and Connecticut State Department of Mental Health and
Addiction Services (DMHAS). P.R.C. was funded by an International
Mental Health Research Organization/Janssen Rising Star
Translational Research Award; National Institute of Mental Health
(NIMH) grant 5R01MH067073-09; Clinical and Translational
Science Award grant UL1 TR000142 from the National Center for
Research Resources (NCRR) and the National Center for
Advancing Translational Science (NCATS), components of the
National Institutes of Health (NIH); NIH roadmap for Medical
Research; the Clinical Neurosciences Division of the U.S.
Department of Veterans Affairs; and the National Center for Post-
Traumatic Stress Disorders, VA Connecticut Healthcare System
(VACHS), West Haven, CT, USA. The contents of this work are
solely the responsibility of the authors and do not necessarily
represent the official view of NIH or the CMHC/DMHAS. A.R.P. was
supported by the Integrated Mentored Patient-Oriented Research
Training (IMPORT) in Psychiatry grant (5R25MH071584-07) as well
as the Clinical Neuroscience Research Training in Psychiatry grant
(5T32MH19961-14) from NIMH and a VA Schizophrenia Research
Special Fellowship from VACHS, West Haven, CT, USA. Additional
support was provided by the Yale Detre Fellowship for Translational
Neuroscience as well as the Brain and Behavior Research
Foundation in the form of a National Alliance for Research on
Schizophrenia and Depression Young Investigator Award for
A.R.P. The authors declare no conflicts of interest. Model code and
data are stored at ModelDB ( http://modeldb.yale.edu/229278).
Imaging data are stored at NeuroVault ( http://neurovault.org/
Materials and Methods
Figs. S1 to S7
Tables S1 to S8
References (29, 30)
31 March 2017; accepted 4 July 2017
Single-cell methylomes identify
neuronal subtypes and regulatory
elements in mammalian cortex
Chongyuan Luo,1,2 Christopher L. Keown,3 Laurie Kurihara,4 Jingtian Zhou,1,5
Yupeng He,1,5 Junhao Li,3 Rosa Castanon,1 Jacinta Lucero,6 Joseph R. Nery,1
Justin P. Sandoval,1 Brian Bui,6 Terrence J. Sejnowski,2,6,7 Timothy T. Harkins,4
Eran A. Mukamel,3† M. Margarita Behrens,6† Joseph R. Ecker1,2†
The mammalian brain contains diverse neuronal types, yet we lack single-cell epigenomic
assays that are able to identify and characterize them. DNA methylation is a stable
epigenetic mark that distinguishes cell types and marks regulatory elements. We
generated >6000 methylomes from single neuronal nuclei and used them to identify
16 mouse and 21 human neuronal subpopulations in the frontal cortex. CG and non-CG
methylation exhibited cell type–specific distributions, and we identified regulatory
elements with differential methylation across neuron types. Methylation signatures
identified a layer 6 excitatory neuron subtype and a unique human parvalbumin-expressing
inhibitory neuron subtype. We observed stronger cross-species conservation of
regulatory elements in inhibitory neurons than in excitatory neurons. Single-nucleus
methylomes expand the atlas of brain cell types and identify regulatory elements that
drive conserved brain cell diversity.
Mammalian neuron types are identified bytheir structure, electrophysiology, and connectivity (1). The difficulty of scaling traditional cellular and molecular assays to whole neuronal populations has prevented comprehensive analysis of brain cell types.
Sequencing mRNA transcripts from single cells or
nuclei has identified cell types with unique tran-
scriptional profiles in the mouse brain (2, 3) and
human brain (4). However, these methods are re-
stricted to RNA signatures, which are influenced
by the environment. Epigenomic marks, such as
DNA methylation (mC), are cell type–specific and
developmentally regulated, yet stable across indi-
viduals and over the life span (5–7). We theorized
that epigenomic profiles using single-cell DNA
methylomes could enable the identification of neu-
ron subtypes in the mammalian brain.
During postnatal synaptogenesis, neurons ac-
cumulate substantial DNA methylation at non-CG
600 11 AUGUST 2017 • VOL 357 ISSUE 6351 sciencemag.org SCIENCE
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