Gamma frequency entrainment attenuates amyloid load and modifies microglia

Abstract

Changes in gamma oscillations (20–50 Hz) have been observed in several neurological disorders. However, the relationship between gamma oscillations and cellular pathologies is unclear. Here we show reduced, behaviourally driven gamma oscillations before the onset of plaque formation or cognitive decline in a mouse model of Alzheimer’s disease. Optogenetically driving fast-spiking parvalbumin-positive (FS-PV)-interneurons at gamma (40 Hz), but not other frequencies, reduces levels of amyloid-β (Aβ)1–40 and Aβ 1–42 isoforms. Gene expression profiling revealed induction of genes associated with morphological transformation of microglia, and histological analysis confirmed increased microglia co-localization with Aβ. Subsequently, we designed a non-invasive 40 Hz light-flickering regime that reduced Aβ1–40 and Aβ1–42 levels in the visual cortex of pre-depositing mice and mitigated plaque load in aged, depositing mice. Our findings uncover a previously unappreciated function of gamma rhythms in recruiting both neuronal and glial responses to attenuate Alzheimer’s-disease-associated pathology.

Full text

Gamma frequency entrainment attenuates amyloid load and
modifies microglia
Hannah F. Iaccarino1,3,*, Annabelle C. Singer2,3,4,*,+, Anthony J. Martorell1,3, Andrii
Rudenko1,3,&, Fan Gao1,3, Tyler Z. Gillingham1,3, Hansruedi Mathys1,3, Jinsoo Seo1,3, Oleg
Kritskiy1,3, Fatema Abdurrob1,3, Chinnakkaruppan Adaikkan1,3, Rebecca G. Canter1,3,
Richard Rueda1,3, Emery N. Brown2,3,5,6, Edward S. Boyden2,3,4, and Li-Huei Tsai1,3,7
1Picower Institute for Learning and Memory
2McGovern Institute for Brain Research
3Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology
4MIT Media Lab, Departments of Biological Engineering and Brain and Cognitive Sciences,
Massachusetts Institute of Technology
5Institute of Medical Engineering and Sciences, Massachusetts Institute of Technology,
Cambridge, USA
6Massachusetts General Hospital, Boston
7Broad Institute of Harvard and MIT, Cambridge, USA
Abstract
Changes in gamma oscillations (20-50 Hz) have been observed in several neurological disorders.
However, the relationship between gamma and cellular pathologies is unclear. Here, we show
reduced behaviorally-driven gamma before the onset of plaque formation or cognitive decline in a
mouse model of Alzheimer's disease (AD). Optogenetically driving FS-PV-interneurons at gamma
(40 Hz), but not other frequencies, reduced levels of amyloid-
β
(A
β
)1-40 and A
β
1-42 isoforms.
Gene expression profiling revealed induction of genes associated with morphological
transformation of microglia and histological analysis confirmed increased microglia co-
localization with A
β
. Subsequently, we designed a non-invasive 40 Hz light-flickering paradigm
that reduced A
β
1-40 and A
β
1-42 levels in visual cortex of pre-depositing mice and mitigated
Reprints and permissions information are available at www.nature.com/reprints.
Correspondence and requests for materials should be addressed to lhtsai@mit.edu.
*These authors contributed equally to this work.
+Present address: Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta
&Present address: Department of Biology, The City College of New York, New York
Author Contributions: H.F.I, A.C.S., E.N.B, E.S.B., and L.-H.T. designed experiments. H.F.I. and F.G. performed RNA sequencing
experiments. H.F.I. and A.C.S. performed electrophysiology. A.C.S. analyzed electrophysiology data. H.F.I. performed and analyzed
optogenetics and ELISA experiments. T.Z.G., J.S., and O.K. performed western blots. H.F.I., A.R., F.A., R.R., and R.G.C. performed
and analyzed imaging experiments. F.G. analyzed RNA sequencing data. H.F.I., A.J.M., and C.A. performed visual stimulation
experiments. H.M. performed FACS experiments. H.F.I, A.C.S., A.R., F.G., E.S.B., and L.-H.T. wrote the manuscript.
RNA-seq data available at https://www.ncbi.nlm.nih.gov/geo/ code: GSE77471. Other data is publically available upon request.
Competing financial interests: LHT and ESB are scientific founders and serve on the scientific advisory board of Cognito Therapeutics
and HFI and ACS own shares of Cognito Therapeutics.
HHS Public Access
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. Author manuscript; available in PMC 2017 October 25.
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. 2016 December 07; 540(7632): 230–235. doi:10.1038/nature20587.
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plaque load in aged, depositing mice. Our findings uncover a previously unappreciated function of
gamma rhythms in recruiting both neuronal and glial responses to attenuate AD-associated
pathology.
Activation of local circuits of excitatory and fast-spiking inhibitory neurons that resonate at
20-50 Hz gives rise to oscillations in the local field potential (LFP), called gamma
oscillations.1–3 Although studies have demonstrated disrupted gamma in various
neurological diseases, the interplay between pathology and this emergent circuit property
has yet to be determined.4,5 In general, molecular and cellular pathology is thought to alter
synaptic activity. However, in at least one disorder, Alzheimer's disease (AD), changes in
synaptic activity can also feedback to alter molecular pathology. Studies have shown that
increases in synaptic activity
in vivo
increase levels of amyloid-
β
(A
β
),6 a 36-43 amino acid
protein, whose aggregation is thought to initiate neurotoxic events, including
neuroinflammation, synaptic and neuronal loss, and Tau-associated pathology.7 We aimed to
determine how gamma might affect molecular pathology in a mouse model of AD.
Understanding how gamma may affect disease pathogenesis has important implications for
elucidating both the basic pathology of and possible therapeutic interventions for
neurological diseases with altered gamma.
Gamma is decreased during hippocampal sharp wave ripples in 5XFAD
mice early in disease
Altered gamma has been observed in multiple brain regions in several neurological and
psychiatric disorders, including a reduction in spontaneous gamma synchronization in AD
patients and reduced gamma power in multiple AD mouse models.4,5,8,9 However, it is
unclear if gamma is altered in other mouse models of AD, if it occurs early in disease
progression, and if gamma affects disease pathology. Accordingly, we recorded neural
activity from behaving 5XFAD mice, a well-established model of Alzheimer's disease.10 In
3-month-old mice, which have elevated levels of A
β
but no major plaque accumulation in
the hippocampus or manifestation of learning and memory deficits,10 we recorded neural
activity from hippocampal subregion CA1, where gamma has been particularly well
characterized (e.g.11–14), using a virtual environment (Ext. Data Fig. 1a). In CA1, gamma is
present during distinct periods of activity: running, when theta oscillations (4-12 Hz) occur
(Ext. Data Fig. 1b,
left
), and quiescent behavior, when sharp-wave ripples (SWR) occur15,16
(Ext. Data Fig. 1b,
right
). We found no clear differences in slow gamma power (20 to 50 Hz)
between 5XFAD mice and wild-type (WT) littermates during theta (Ext. Data Fig. 1c, d).
We next examined gamma during SWRs, high frequency oscillations of 150-250 Hz lasting
around 50-100 ms (Ext. Data Fig. 1b, e).14 Prior work has shown that slow gamma is
elevated during SWRs and increased gamma synchrony across CA3 and CA1 during SWR
correlates with more coordinated firing between neurons.16 Similarly, we found increased
gamma power during SWRs (Fig. 1da yellow arrow indicates elevated gamma, Ext. Data
Fig. 1e). The instantaneous frequencies of these slower oscillations (10-50 Hz, Methods)
were a unimodal distribution centered around 40 Hz (Fig. 1b, Ext. Data Fig. 1f). Comparing
gamma during SWRs in WT and 5XFAD littermates, we found that gamma power was
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significantly lower in 5XFAD than in WT mice (Methods, Fig. 1c, Ext. Data Fig. 1g, j;
examples in Fig. 1c,
top
). Spiking was phase modulated by gamma in both groups, although
the depth of modulation was significantly smaller in 5XFAD than in WT animals (Fig. 1d,
Ext. Data Fig. 1h, k). Furthermore, there were fewer SWRs per time in non-theta periods in
5XFAD mice compared to WT (Ext. Data Fig. 1i), reducing periods when gamma power is
elevated (Fig. 1a,c, Ext. Data Fig. 1e). These results reveal deficits in gamma modulation of
CA1 spiking in a mouse model of AD prior to the development of major amyloid plaque
accumulation or evidence of cognitive impairment. This deficit in gamma converges with
evidence of gamma deficits in different mouse models of AD, and reports that gamma is
altered in humans with AD.5,8,9 Indeed, molecular deficits in Nav1.1 in humans have been
linked with gamma deficits in hAPP mice.7
Gamma stimulation reduced A
β
production in hippocampal CA1
These gamma deficits during SWRs early in disease progression in this mouse model of AD
prompt the question of whether gamma could affect molecular and cellular AD
pathophysiology. To test this, we induced gamma optogenetically in 5XFAD/PV-Cre mice
(Methods, Fig. 1e,
left
, Ext. Data Fig. 2a, b, c). We chose to drive FS-PV-interneurons at 40
Hz because we found deficits in gamma during SWRs, and instantaneous gamma
frequencies during SWRs were centered around 40 Hz. Delivering 1 ms 473 nm light pulses
at 40 Hz resulted in increased power at 40 Hz in LFPs in CA1, while random stimulation did
not (Fig. 1e, Ext. Data Fig. 1l). Both resulted in similar firing rates (Ext. Data Fig. 1m, n, o).
A
β
accumulation is thought to initiate multiple neurotoxic events typical for AD pathology.
Therefore, we examined whether gamma stimulation affected overall A
β
peptide levels in
the hippocampus of 5XFAD mice. We found that 1 hr of FS-PV-interneuron stimulation
reduced A
β
1-40 by 53.22% and A
β
1-42 by 44.62% in the 40 Hz group which expresses
ChR2 compared to the EYFP control group, as measured in CA1 by A
β
enzyme-linked
immunosorbent assay (ELISA) (Fig. 1f, g, raw concentration (pg/ml) in Ext. Data Table 1).
We performed a comprehensive set of control experiments to determine whether the effect
was specific to frequency, cell type, and/or rhythmicity. Neither stimulation of CamKII-
positive excitatory neurons at 40 Hz, nor FS-PV-interneurons at 8 Hz or random intervals
significantly reduced A
β
levels (Fig. 1f-i, Methods). Immunohistochemical analysis using
two
β
-amyloid-specific antibodies (Cell Signaling Technology; D54D2, BioLegend; 12F417)
in CA1 confirmed these results: A
β
labeling intensity was significantly reduced by 39.5%
following 40 Hz stimulation compared to EYFP controls (Fig. 2e, f, D54D2 antibody, Ext.
Data Fig. 2e, f, 12F4 antibody).
Brain amyloid concentration depends on A
β
production from amyloid precursor protein
(APP) and A
β
clearance rates. To elucidate how 40 Hz stimulation reduced A
β
production,
we examined its effects on APP cleavage by measuring levels of the cleavage intermediates
of APP, C-terminal fragments (CTFs) and N-terminal fragments (NTFs), in the hippocampus
of the 5XFAD/PV-Cre mice. Following 40 Hz stimulation, we found significantly reduced
APP CTFs and NTFs compared to EYFP and random controls (Fig. 2a, b, c, d, Ext. Data
Fig. 2d).
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Prior work has shown that APP is transported and processed in recycling endosomes18, and
enlarged early endosomes have been observed in brain tissue from AD patients19. Therefore,
we characterized endosomes in CA1 following stimulation using two markers, EEA1 (early
endosomal antigen 1) and Rab5 (Ras-related protein encoded by the
RAB5A
gene).
Altogether, the intensity of endosomal labeling of CA1 neurons significantly decreased in
both EEA1 (39.7%) and Rab5 (40.1%) following 40Hz stimulation compared to EYFP
controls (Fig. 2e, g, Ext. Data Fig. 2g, h). These results suggest that in addition to observed
changes in APP cleavage products, 40 Hz stimulation also alters general endosomal
processing.
Gamma stimulation induced morphological transformation of microglia
To further explore the cellular and molecular effects of stimulation in an unbiased manner,
we performed genome-wide RNA sequencing (RNA-seq) of CA1 tissue following 1 hr of 40
Hz or no stimulation (EYFP) of the 5XFAD/PV-Cre mice (Fig. 3a, Ext. Data Fig. 3a, b, c).
Interestingly, 35% of all up-regulated genes had their highest expression in microglia (Fig.
3b). This RNA-seq analysis strongly suggests that 40 Hz stimulation causes an alteration in
the state of microglia, which is significant given the accumulating evidence that microglia
play a role in AD pathology.20 Transcriptomic changes following 40 Hz stimulation were
positively correlated with changes due to increased neural activity (by NMDA and
bicuculline), and negatively correlated with changes due to silencing activity (by
tetrodotoxin) (Ext. Data Fig. 3d). The immediate early genes
Nr4a1, Arc
, and
Npas4
, which
are up-regulated by neuronal activity, were elevated as shown by both RNA-seq and RT-
qPCR (Ext. Data Fig. 3e).
These transcriptomic results also suggest an engulfing state of microglia. The up-regulated
genes were positively correlated with genomic changes induced by macrophage colony-
stimulating factor (MCSF) and granulocyte macrophage colony-stimulating factor
(GMCSF), known to promote microglial A
β
uptake (Ext. Data Fig. 3d).21 RT-qPCR
confirmed that up-regulated genes included microglial engulfment associated genes
Cd68
,
B2m, Bst2, Icam1
, and
Lyz2
(Fig. 3c). Microglia-enriched transcriptional regulator
Irf7
, cell
adhesion and migration regulator
Spp1
, and microglia proliferation markers
Csf1r
and
Csf2ra
were also up-regulated (Fig. 3c). Importantly, RT-qPCR showed that the expression
levels of pro-inflammatory genes
Il6
,
Il1b
(
Il1-β)
,
Itgam
(
CD11-b)
and an anti-inflammatory
gene
Igf1
were not changed (Fig. 3c).
Given that 40 Hz stimulation up-regulated both phagocytosis- and migration/cell adhesion-
related genes, we examined morphological features of microglia activation. We used an
antibody against microglial marker Iba1 to label microglia in CA1 sections from
5XFAD/PV-Cre mice after 1 hr of 40 Hz or random stimulation, or in mice expressing only
EYFP (EYFP, Fig. 3d). We observed almost twice as many microglia in the 40 Hz group
compared to EYFP and random control groups (Fig. 3d, e). Furthermore, microglia cell body
diameter increased by 135.3% following 40 Hz stimulation compared to EYFP controls and
by 138.7% compared to random stimulation (Fig. 3d, f). The length of microglia primary
processes were reduced by 54.0% in the 40 Hz stimulation condition compared to EYFP
controls and by 38.5%compared to random stimulation (Fig. 3d, g). Iba1 levels did not affect
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these findings as gene expression analysis showed that Iba1 expression did not differ
between conditions (Ext. Data Fig. 3a, b). The increase in cell body size and decrease in
process length observed after 40 Hz stimulation are consistent with a shift towards a
phagocytic state of microglia.22To evaluate microglia A
β
uptake specifically, we measured
co-localization of A
β
within microglia by co-immunostaining with an A
β
antibody (12F4,
Methods). The percent of microglia co-localized with A
β
in the cell body increased to
85.6% following 40 Hz stimulation from 31.7% (EYFP control, Fig. 3d,h). 3D renderings of
microglia further demonstrate the presence of A
β
within microglia (Ext. Data Vid. 1, 2, 3).
We did not find evidence of neuronal loss by measuring the CA1 cellular layer thickness
(Ext. Data Fig. 3f, g). Together, these results suggest that gamma stimulation triggers
microglia to increase A
β
uptake.
Visual stimulation by light flicker drives gamma non-invasively in primary
visual cortex
Many studies have shown that visual stimulation can drive oscillations in the gamma
range.2,23 In particular, flickering lights at a specific frequency can induce that frequency in
primary visual cortex (VC).24 To determine if light flickering could entrain 40 Hz
oscillations and subsequently alter A
β
, we exposed 5XFAD mice to 40 Hz flickering for 1
hr, analogous to optogenetic stimulation that reduced A
β
described above (Fig. 4a, Ext.
Data Vid. 4). In VC, we found that light flickering at 40 Hz increased power in the LFP at 40
Hz, while random interval flickering (random flicker) and dark exposure did not (Fig. 4a,
Ext. Data Fig. 4a). All induced similar firing rates (Ext. Data Fig. 4b, c). Spiking increased
and decreased concomitantly as the light flickered on and off, resulting in spiking entrained
to 40 Hz during 40 Hz flicker but not during random flicker (Fig. 4b). Recordings from
saline above the brain exhibited no change in 40 Hz power during 40 Hz flicker, showing
that this effect was not due to photoelectric effects or electrical noise (Ext. Data Fig. 4d, e).
Visual stimulation by light flicker decreases A
β
levels in primary visual
cortex
Given that 40 Hz light flicker entrains 40 Hz oscillations in VC, we aimed to determine
whether 40 Hz flicker could reduce A
β
levels. 3-month-old 5XFAD mice were placed in a
dark box and exposed to either light flicker at different frequencies (20, 40, or 80 Hz),
random flicker, constant light on (light), or dark for 1 hr. One hour after 1 hr of 40 Hz
flicker, we observed that A
β
1-40 levels in VC were reduced by 57.96% and A
β
1-42levels by
57.97% compared to dark controls (as measured by A
β
ELISA, Fig. 4c). The effect was
specific to 40 Hz flicker as neither constant light nor 20 Hz, 80 Hz, or random flicker
significantly reduced A
β
levels compared to dark and light controls (Fig. 4c). We also found
no change in A
β
levels in somatosensory barrel cortex and hippocampus following 40 Hz
flicker (Ext. Data Fig. 5a-h). When we pretreated 5XFAD mice with a low dose GABA-A
antagonist (picrotoxin, 0.18 mg/kg25), the effects of 40 Hz flicker on A
β
levels were
completely abrogated, indicating that GABAergic neurotransmission is necessary for this
effect (Fig. 4c). To demonstrate that these effects extend beyond the 5XFAD mouse, we
examined the effect of 40 Hz flicker in APP/PS1 mice, another well-validated AD model,26
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and found significantly reduced A
β
1-40, by 20.80%, and a non-significant trend of reduced
A
β
1-42 by 37.68%(Ext. Data Fig. 6a). Furthermore, in 9-month-old WT mice, we found a
58.2% reduction in endogenous mouse A
β
1-40 following 1 hr of 40 Hz flicker (Ext. Data
Fig. 6b). The reduction of endogenous mouse A
β
1-40 in WT animals reveals that these
effects are not restricted to transgenic APP expression or mutant APP; rather, they extend to
A
β
produced from endogenous APP driven by its endogenous promoter.
Next, we investigated whether 40 Hz flicker alters microglia activity in VC in a similar
manner that 40 Hz optogenetic stimulation altered CA1 microglia. While microglia number
was unchanged (Fig. 4d, e), microglia cell body diameter increased by 165.8% following 40
Hz flicker compared to dark controls (Fig. 4d, f). Microglia primary process lengths were
reduced by 37.7% after 40 Hz flicker compared to dark controls (Fig. 4d, g). Consistent with
this morphology, which indicates enhanced engulfment activity,22 A
β
/Iba1 co-localization in
the cell body was increased to 90.8%after 40 Hz flicker from 57.3% in the dark condition,
indicating more A
β
-bearing microglia (Fig. 4d, h, p<0.01). To better resolve the
morphological change in microglia, we used CLARITY27 to create 3D renderings of
microglia from 100
μ
m sections of VC, (Ext. Data Vid. 5, 6). To demonstrate that microglia
indeed engulf
A β
in the 5XFAD mouse, we purified microglia from 5XFAD and WT
animals using fluorescence-activated cell sorting (FACS, Methods) and analyzed A
β
levels
via ELISA. We found that microglia-specific levels of A
β
are significantly higher in
5XFAD animals than in WT controls (Ext. Data Fig. 7a, b). Synaptophysin levels did not
change between dark and 40 Hz flicker conditions, indicating that microglia activation likely
did not affect synapse number (Ext. Data Fig. 7c, d, n.s. = not significant, n=4 mice). Thus,
40 Hz oscillations induced non-invasively via sensory entrainment reduced A
β
abundance
and promoted microglia/A
β
interactions.
Chronic visual stimulation by light flicker decreases plaque load in VC
We next assessed whether 40 Hz flicker was effective to treat animals that have amyloid
plaques. Because the effects of 40 Hz flicker on soluble A
β
levels were transient (Ext. Data
Fig. 8a), we hypothesized that we would need repeated exposure to affect insoluble A
β
.
Thus, we treated 6-month-old 5XFAD mice, which have amyloid plaque pathology in many
brain regions including VC,10 for 1 hr daily over 7 days with 40 Hz flicker or dark, and
analyzed VC tissue 24 hr later. We found that 7 days of 1 hr 40 Hz flicker reduced both
soluble A
β
1-40 and A
β
1-42 levels, by 60.5% and 51.7% respectively, (Fig. 4i, j) and
insoluble A
β
1-40 and A
β
1-42 levels by 43.7% and 57.9% respectively (Fig. 4i, j).
Immunohistochemical analysis showed that 40 Hz flicker significantly reduced plaque
number in VC by 67.2% compared to dark controls (Fig. 4k, l) and plaque size by 63.7%
(Fig. 4k, m). Taken together, these experiments identify a non-invasive treatment with a
profound effect on amyloid plaque pathology. We next determined if 40 Hz flicker reduced
tau phosphorylation, another AD-related pathology. Using the TauP301S tauopathy mouse
model28 we found that 7 days of 1 hr 40 Hz visual flicker treatment reduced phosphorylated
tau serine202 and serine404/threonine403/serine400 levels in VC by 41.2% and 42.3%,
respectively, and triggered microglia responses similar to those observed in 5XFAD mice
(Ext. Data Fig. 9a-k).
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Discussion
Gamma oscillations are thought to be important for higher cognitive functions and sensory
responses.2,12,23 Here, we demonstrated that entraining oscillations and spiking at 40 Hz,
using optogenetics in the hippocampus of 5XFAD mice and using a non-invasive light
flicker treatment to affect primary visual cortex in multiple mouse models, resulted in a
marked reduction of A
β
peptides. We also found a concomitant microglia response
following 40 Hz entrainment.
The robust reduction of total amyloid levels was likely mediated by both decreased
amyloidogenesis and increased amyloid endocytosis by microglia. Thus, it appears that
driving 40 Hz gamma oscillations may induce an overall neuroprotective response that
recruits both neurons and microglia. The fact that GABA-A antagonist treatment completely
abrogated the effects of 40 Hz stimulation on A
β
levels strongly suggests that GABAergic
neurotransmission is critical for these effects.
40 Hz flicker stimulation reduced A
β
in multiple mouse models, including 5XFAD, APP/
PS1, and WT mice. This replication in multiple mouse models shows that these findings are
not specific to one animal model and, importantly, extend to situations where A
β
is
produced from APP expressed by its physiological promoter as it is in WT animals. In
addition, we found that 40 Hz oscillations reduced phosphorylated tau in a mouse model of
tauopathy, TauP301S, showing that the protective effects of gamma stimulation generalize to
other pathogenic proteins. In summary, these findings uncover previously unknown cellular
and molecular processes mediated by gamma oscillations and establish a functional
connection between brain gamma rhythms, microglia function, and AD-related pathology.
These observations indicate that entraining gamma oscillations may provide a broad
spectrum of systemic effects in the brain, including in non-neuronal cells, to attenuate
Alzheimer's-related pathology. Because this approach is fundamentally different from prior
AD therapies,29 further study is needed to determine whether this approach will be
therapeutic in human AD.
Methods
Animals
All animal work was approved by the Committee for Animal Care of the Division of
Comparative Medicine at the Massachusetts Institute of Technology. Adult (3-month-old)
male double transgenic 5XFAD Cre mice were produced by crossing 5XFAD transgenic
mice with the transgenic PV or CW2 promoter driven Cre line. Adult (5-month-old) male
and female APP/PS1 mice were gifted from the Tonegawa Laboratory. Adult (4-month-old)
male TauP301S mice were obtained from the Jackson Laboratory. 9-month-old WT mice
(C57Bl/6) were obtained from the Jackson Laboratory. Mice were housed in groups of 3-5
on a standard 12 hr light / 12 hr dark cycle, and all experiments were performed during the
light cycle. Food and water were provided
ad libitum
unless otherwise noted. Littermates
were randomly assigned to each condition by the experimenter. Experimenter was blind to
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animal genotypes during tissue processing and electrophysiological recording and analysis.
No animals were excluded from analysis.
AAV vectors
Adeno-associated viral particles of serotype 5 were obtained from the Vector Core Facility at
The University of North Carolina at Chapel Hill. The AAV5 virus contained a
channelrhodopsin-2 (ChR2) fused to enhanced yellow fluorescent protein (EYFP) in a
double-floxed, inverted, open-reading-frame (DIO) driven by the EF1
α
promoter (Ext. Data
Fig. 2a). An AAV-DIO-EYFP construct was used as a control.
Surgical procedures
3-month-old 5XFAD/PV-Cre or CW2 mice were anesthetized with an intraperitoneal (i.p.)
injection of a mixture of ketamine (1.1 mg kg-1) and xylazine (0.16 mg kg-1). A small
craniotomy was made 2.0 mm posterior to bregma and 1.8 mm lateral to the midline on the
left side. Virus was delivered through a small durotomy by a glass micropipette attached to a
Quintessential Stereotaxic Injector (Stoelting). The glass micropipette was lowered to 1.2
mm below the brain surface. A bolus of 1
μ
L of virus (AAV-DIO-ChR2-EYFP or AAV-
DIO-EYFP; 2 × 1012 viral molecules per ml) was injected into the CA1 region of
hippocampus at 0.075
μ
L min-1. The pipette remained in place for 5 min following the
injection before being retracted from the brain. A unilateral optical fiber implant (300
μ
m
core diameter; Thor Labs) was lowered to 0.9 mm below the brain surface about the
injection site. Two small screws anchored at the anterior and posterior edges of the surgical
site were bound with dental glue to secure the implant in place.
For electrophysiological recordings adult (3-month-old) male 5XFAD/PV-Cre and 5XFAD
negative littermates (for CA1 recordings), or 5XFAD and their wild type littermates (for VC
recordings) mice were anesthetized using isoflurane and placed in a stereotactic frame. The
scalp was shaved, ophthalmic ointment (Puralube Vet Ointment, Dechra) was applied to the
eyes, and Betadine and 70% ethanol were used to sterilize the surgical area. For CA1
recordings, a craniotomy (in mm, from bregma: -2 A/P, 1.8 M/L) was opened to deliver 1
μ
L of virus to CA1 (as described above). The target craniotomy site for LFP recordings was
marked on the skull (in mm, from bregma: -3.23 A/P, 0.98 M/L for CA1 and 2.8 A/P, 2.5
M/L for VC), three self-tapping screws (F000CE094, Morris Precision Screws and Parts)
were attached to the skull, and a custom stainless steel headplate was affixed using dental
cement (C&B Metabond, Parkell). On the day of the first recording session, a dental drill
was used to open the LFP craniotomies (300-400
μ
m diameter) by first thinning the skull
until ∼100
μ
m thick, and then using a 30 gauge needle to make a small aperture. The
craniotomy was then sealed with a sterile silicone elastomer (Kwik-Sil WPI) until recording
that day and in between recording sessions.
Optogenetic stimulation protocol
Two to four weeks following virus injection and implant placement (which provides time for
the mice to recover and undergo behavior training for animals used for electrophysiology)
and the virus to express in the neurons, CA1 neurons were optogenetically manipulated. A
200 mW 4793 nm DPSS laser was connected to a patch cord with a fiber channel/physical
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contact connector at each end. During the experiment, 1 mW (measured from the end of the
fiber) of optical stimulation was delivered for 1 hr. For molecular and biochemical analyses,
each animal received one of three stimulation protocols: 8 Hz, 40 Hz, or random stimulation
(light pulses were delivered with a random interval determined by a Poisson process with an
average frequency of 40 Hz). EYFP control animals received 40 Hz stimulation. For
electrophysiological recordings each animal received all stimulation conditions interleaved
during recordings.
Visual stimulation protocol
15 minutes prior to the experiment 5XFAD mice were treated with saline (Control) or
picrotoxin (0.18 mg/kg).25 For molecular and biochemical analyses mice were then placed
in a dark chamber illuminated by a light emitting diode (LED) bulb and exposed to one of
five stimulation conditions: dark, light, 20 Hz, 40 Hz, 80 Hz flicker (12.5 ms light on, 12.5
ms light off, 60 W) for 1h. For electrophysiological recordings each animal received dark,
light, 40 Hz flicker, or random (light pulses were delivered with a random interval
determined by a Poisson process with an average interval of 40 Hz) stimulation conditions
interleaved in 10 s blocks during recordings.
Behavior training and virtual reality environment (VR) for electrophysiology
For CA1 recordings, headfixed animals ran on an 8” spherical treadmill supported by an air
cushion through a virtual reality environment, as described in Harvey et al.30 The motion of
the spherical treadmill was measured by an optical mouse and fed into virtual reality
software31, running in MATLAB (version 2013b, Mathworks). The virtual environment
consisted of a linear track with two small enclosures at the ends where the animal could turn
(Ext. Data Fig. 1a). Animals were rewarded with sweetened condensed milk (diluted 1:2 in
water) at each end of the track for alternating visits to each end of the track.
Animals learned to run on the virtual linear track over approximately one week. The animals
were left to recover from the surgery for one week, and habituated to handling for one to two
days before behavioral training began. To learn to maneuver on the treadmill and get
comfortable in the testing environment, on the first two days of training the animals were
placed on the spherical treadmill with the virtual reality system off and were rewarded with
undiluted sweetened condensed milk. On the second day of training on the spherical
treadmill, animals' food was restricted to motivate them to run. Animals were restricted to no
more than 85% of their baseline weight and typically weighed over 88% of their baseline
weight. From the third day until the end of training (typically 5-7 days) the animals were
placed on the treadmill for increasing amounts of time (30 min to 2 hr) running in the VR
linear track. Animals were rewarded with diluted (1:2) sweetened condensed milk at the end
of the linear track after traversing the length of the track. Between recording sessions,
animals were given refresher training sessions to maintain behavioral performance.
For VC recordings, animals ran on the spherical treadmill while exposed to dark, light, or
light flickering conditions (described below in data acquisition). Prior to recordings animals
learned to maneuver on the treadmill and get comfortable in the testing environment by
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being placed on the spherical treadmill (with the virtual reality system off) and receiving
reward of undiluted sweetened condensed milk.
Electrophysiology data acquisition
For optogenetic stimulation of CA1 during recording, a 300
μ
m core optical fiber was
advanced through the craniotomy used to deliver virus to CA1 to a depth of 900
μ
m into the
brain. Light pulses that were 1 ms and 1 mW (measured from the end of the fiber) were
delivered via a 473 nm DPSS (diode pumped solid state) laser (as described above).
To avoid photoelectric artifacts, neural activity was recorded with glass electrodes. LFP
electrodes were pulled from borosilicate glass pipettes (Warner) on a filament-based
micropipette puller (Flaming-Brown P97, Sutter Instruments), to a fine tip, which was then
manually broken back to a diameter of ∼10-20
μ
m and then filled with sterile saline. For
CA1 recordings the LFP electrode was advanced through the LFP recording craniotomy at
an angle 60 degrees posterior to the coronal plane and 45 degrees inferior to the horizontal
plane until clear electrophysiological signatures of the hippocampal
stratum pyramidale
layer were observed (∼600-1000
μ
V theta waves while the animal was running, clearly
distinguishable sharp-wave ripples during immobility, and multiple spikes greater than 150
μ
V, Ext. Data Fig. 1b). For VC recordings the LFP electrode was advanced vertically through
the LFP recording craniotomy to a depth of 600-900
μ
m and multiple spikes greater than
150
μ
V were observed.
Data was acquired with a sampling rate of 20 kHz and bandpass filtered 1 Hz-1 kHz.
Animals ran on the spherical treadmill or rested for prolonged periods. For optogenetic
simulation sessions, data was recorded for 30 minutes before any stimulation began. Then
stimulation was delivered at gamma (40 Hz), random (as described under
optogenetic
stimulation protocol
), or theta (8 Hz) frequency for 10 s periods interleaved with 10 s
baseline periods (no stimulation). In two animals, stimulation of each type or baseline was
delivered for 5 min periods instead of 10 s periods. Each 30 minutes of stimulation
recordings were followed by 5-30 minutes of recording with no stimulation. For visual light
flicker simulation sessions, LED strip lights surrounding the animal lights were flickered at
gamma (40 Hz), random (described above in
Visual stimulation protocol
), theta (8 Hz), or
20 Hz frequency for 10 s periods, or were on continuously for 10 s periods, interleaved with
10 s periods with lights off. A few recordings were made above the brain surface during
light flicker to ensure that the lights did not create electrical or photoelectric noise during
recording. Recording sessions were terminated after approximately 3-5 hr. Animals were 3-4
months old at the time of recording.
Analysis of electrophysiology recordings
Spike detection—Spikes were detected by thresholding the 300-6000 Hz bandpassed
signal. Threshold was the median of the filtered signal plus five times a robust estimator of
the standard deviation of the filtered signal (median/0.675) to avoid contamination of the
standard deviation measure by spikes. (Rossant 2015: http://biorxiv.org/content/biorxiv/
early/2015/02/16/015198.full.pdf)
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Local field potential (LFP)—Recorded traces were downsampled to 2 kHz and then
bandpass filtered between 1 to 300 Hz.
Theta and SWR detection—Activity across the hippocampal network changes markedly
when animals run or sit quietly and these changes are often referred to as different network
states. These network states are clearly distinguishable by the presence or absence of LFP
oscillations in different frequency bands12,13. When animals ran, we observed large theta
(4-12 Hz) oscillations in CA1 as others have shown (Ext. Data Fig. 1b, left)13,30,32,33. When
animals sat quietly, theta oscillations were no longer visible and we recorded sharp wave
ripples (SWRs), high frequency oscillations of 150-250 Hz that last around 50-100 ms and
are associated with bursts of population activity, as others have observed (Ext. Data Fig. 1b,
right
)15,16.
SWRs were detected (Fig. 1a, b, c, d, Ext. Data Fig. 1d, e, f, g, h, i) when the envelope
amplitude of the filtered trace was greater than four standard deviations above the mean for
at least 15 ms. The envelope amplitude was calculated by taking the absolute value of the
Hilbert transform of the filtered LFP. We also confirmed our results held when using a
higher threshold for SWR detection, 6 standard deviations above the mean, which detects
larger SWRs (Ext. Data Fig 1j, k). To detect theta (Ext. Data Fig. 1c,d), the LFP was
bandpass filtered for theta (4-12 Hz), delta (1-4 Hz), and beta (12-30 Hz) using an FIR
equiripple filter. The ratio of theta to delta and beta (“theta ratio”) was computed as the theta
envelope amplitude divided by the sum of the delta and beta envelope amplitudes. Theta
periods were classified as such when the theta ratio was greater than one standard deviation
above mean for at least two seconds and the ratio reached a peak of at least two standard
deviations above mean. Non-theta periods were classified as such when the theta ratio was
less than one for at least two seconds. Sharp wave ripples, theta periods, and non-theta
periods were visually inspected to ensure that these criteria accurately detected sharp wave
ripple, theta periods, and non-theta periods, respectively.
Power spectrum—Spectral analysis was performing using multitaper methods (Chronux
toolbox, time-bandwidth product = 3, number of tapers = 5). For examining power spectra
without stimulation (Ext. Data Fig. 1c, d), only theta periods were included: theta periods
greater than 5 s long were divided into 5 s trials and the average power spectral density was
computed for each animal over these trials. For examining power spectra during optogenetic
(Fig. 1e, Ext. Data Fig. 1l) and visual stimulation (Fig. 4a, Ext. Data Fig. 4a), data was
divided into 10 s trials of each stimulation condition or baseline periods, and the average
power spectral density was computed for each animal over these trials.
Gamma during SWRs—Spectrograms were computed using multitaper methods
(Chronux toolbox). The spectrogram was computed for each SWR including a window of
400 ms before and after the peak of the SWR. Then a z-scored spectrogram was computed in
each frequency band using the mean and standard deviation of the spectrogram computed
across the entire recording session to create a normalized measure of power in units of
standard deviation (Fig. 1a, Ext. Data Fig. 1e). Instantaneous frequency of gamma during
SWRs was computed by bandpass filtering the LFP for 10-50 Hz, taking the Hilbert
transform, then taking the reciprocal of the difference in peaks of the transformed signal
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(Fig. 1b, Ext. Data Fig. 1f). Gamma power before, during, and after SWRs was computed by
filtering the LFP for low gamma (20-50 Hz) and taking the amplitude of the envelope of the
Hilbert transform to get the mean gamma power in 100 ms bins centered on the SWR peak.
This was normalized by the mean and standard deviation of the amplitude of the envelope
for the entire recording session to get z-scored gamma power for each bin around each SWR
(Fig. 1c, Ext. Data Fig. 1g, j). Phase modulation by gamma during SWRs was computed by
bandpass filtering the LFP for gamma (20-50 Hz), taking the Hilbert transform, and
determining the phase of the resulting signal for each spike that occurred during SWRs (Ext.
Data Fig. 1h). To measure differences in phase modulation between 5XFAD and WT
animals, we used resampling with replacement: a subset of 100 spikes from each recording
was randomly selected to create a phase modulation distribution and this was repeated 500
times for each recording (Fig. 1d, Ext. Data Fig. 1k). We then measured the depth of
modulation for the spike-gamma phase distribution by computing the difference between the
peak and trough divided by the sum of the peak and trough for each distribution (Fig. 1d,
Ext. Data Fig. 1k).
Differences in firing during stimulation—To plot stimulus-evoked multiunit firing
histograms, spikes were binned in 2.5 ms bins for 100 ms after the start of each light on
pulse and the fraction of spikes in each bin was computed. Mean and standard error was then
computed across all light-on periods. To compute differences in multi-unit firing rate
between conditions, firing rates were computed for each 10 s period of stimulation or
baseline (total number of spikes divided by duration of period). Differences in firing rate
were taken between nearby periods of the relevant type of stimulation (firing rate in gamma
stimulation period minus baseline or random periods for optogenetic stimulation, firing rate
in gamma stimulation period minus baseline, continuous on, or random periods for light
flicker stimulation). Differences from all animals were plotted in histograms (Ext. Data Fig.
1m, 4c) and the median and quartiles of the multiunit firing rates per 40 Hz stimulation,
random stimulation, and no stimulation period for each animal were plotted in box plots
(Ext. Data Fig. 1o, 4d).
Immunohistochemistry—Mice were perfused with 4% paraformaldehyde under deep
anesthesia, and the brains were post-fixed overnight in 4% paraformaldehyde. Brains were
sectioned at 40
μ
m using a vibratome (Leica). Sections were permeabilized and blocked in
PBS containing 0.2% Triton X-100 and 10% normal donkey serum at room temperature for
1 hr. Sections were incubated overnight at 4 °C in primary antibody in PBS with 0.2% Triton
X-100 and 10% normal donkey serum. Primary antibodies were anti-EEA1 (BD
Transduction Laboratories; 641057), anti-
β
-amyloid (Cell Signaling Technology; D54D2),
anti-Iba1 (Wako Chemicals; 019-19741), anti-parvalbumin (Abcam; ab32895), anti-Rab5
(Enzo Life Sciences; ADI-KAP-GP006-E). To confirm ELISA experiments, the anti-A
β
antibody D54D2 was used because it allowed for co-labeling with EEA1 and the anti A
β
antibody 12F4 was used because it does not react with APP allowing us to determine if our
labeling was specific to A
β
. For co-labeling experiments, the anti-A
β
antibody 12F4
(Biolegend; 805501) was used. Primary antibodies were visualized with Alexa-Fluor 488
and Alex-Fluor 647 secondary antibodies (Molecular Probes), and cell nuclei visualized
with Hoechst 33342 (Sigma-Aldrich; 94403). Images were acquired using a confocal
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microscope (LSM 710; Zeiss) with a 40X objective at identical settings for all conditions.
Images were quantified using ImageJ 1.42q by an experimenter blind to treatment groups.
For each experimental condition, 2 coronal sections from at least 3 animals were used for
quantification. Scale bars are 50
μ
m. For CA1 imaging, the analysis was restricted to the
pyramidal cell layer, except in the case of Iba1+ cells analysis, where the whole field of view
was required to image an adequate number of cells. ImageJ was used to measure the
diameter of Iba1+ cell bodies and to trace the processes for length measurement. In addition,
the Coloc2 plugin was used to measure co-localization of Iba1 and A
β
. Imarisx64 8.1.2
(Bitplane, Zurich, Switzerland) was used for 3D rendering. For counting the “plaque
number,” deposits ≥10
μ
m were included.
Clarity—Fixed brains were sliced into 100uM coronal sections on a vibratome (Leica
VT100S) in 1XPBS. Sections containing VC were selected, with reference to the Allen
Mouse Brain Atlas, and incubated in clearing buffer (pH 8.5-9.0, 200mM sodium
dodecylsulfate, 20mM lithium hydroxide monohydrate, 4mM boric acid in ddH2O) for 2
hours, shaking at 55°C. Cleared sections were washed 3 ×10mins in 1XPBST (0.1% Triton-
X100/1XPBS) and put into blocking solution (2% bovine serum albumin/1XPBST)
overnight, shaking at RT.27 Subsequently, three 1hour washes in 1X PBST were performed,
shaking at RT. Sections were then incubated at 4°C for 2 days, shaking, with anti-
β
-amyloid
(Biolegend;805501) and anti-Iba1 (Wako Chemicals; 019-19741) primary antibodies, diluted
to 1:100 in 1X PBST. Another set of 3×1 h washes in 1XPBST was conducted before
sections were incubated for 9 hours, shaking at RT, in 1:100 1X PBS diluted secondary
antibody mixture. Fragmented Donkey Anti-Rabbit Alexa Fluor® 488 (Abcam; ab175694)
and Anti-Mouse 568 (Abcam; ab150101) secondary antibodies were used to visualize the
primary antibody labeling. Halfway through this incubation period, Hoechst 33258 (Sigma-
Aldrich; 94403) was spiked into each sample at a 1:250 final dilution. Sections were then
washed overnight in 1×PBS, shaking at RT. Prior to mounting for imaging, slices were
incubated in RIMS (Refractive Index Matching Solution: 75g Histodenz, 20mL 0.1M
phosphate buffer, 60mL ddH2O) for 1 hour, shaking at RT. Tissue sections were mounted
onto microscopy slides with coverslips (VWR VistaVision, VWR International, LLC,
Radnor, PA) using Fluromount G Mounting Medium (Electron Microscopy Sciences,
Hatfield, PA, USA). Images were acquired on a Zeiss LSM 880 microscope with the
accompanying Zen Black 2.1 software (Carl Zeiss Microscopy, Jena, Germany). Section
overview and cellular level images used for 3D reconstruction were taken using a Plan-
Apochromat 63×/1.4 Oil DIC objective. Imaris×64 8.1.2 (Bitplane, Zurich, Switzerland) was
used for 3D rendering and analysis.
Western blot—CA1 whole cell lysates were prepared using tissue from 3-month-old male
5XFAD/PV-Cre mice. Tissue was homogenized in 1 ml RIPA (50 mM Tris HCl pH 8.0, 150
mM NaCl, 1% NP-40, 0.5% sodium deoxycholate, 0.1% SDS) buffer with a hand
homogenizer (Sigma), incubated on ice for 15 min, and rotated at 4 °C for 30 min. Cell
debris was isolated and discarded by centrifugation at 14,000 rpm for 10 minutes. Lysates
were quantitated using a nanodrop and 25 μg protein was loaded on a 10% acrylamide gels.
Protein was transferred from acrylamide gels to PVDF membranes (Invitrogen) at 100 V for
120 min. Membranes were blocked using bovine serum albumin (5% w/v) diluted in
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TBS:Tween. Membranes were incubated in primary antibodies overnight at 4 °C and
secondary antibodies at room temperature for 90 minutes. Primary antibodies were anti-APP
(Invitrogen; PAD CT695), anti-APP (Sigma;A8967), anti-
β
-actin (Abcam; ab9485).
Secondary antibodies were horseradish peroxidase-linked (GE Healthcare). Signal
intensities were quantified using ImageJ 1.46a and normalized to values of
β
-actin. We
examined tau protein solubility using sequential protein extraction as described in
Yoshiyama et al., 2007.28 We then probed the detergent insoluble tau fraction using an
antibody against Tau5 (Thermo Fisher Scientific; AHB0042).
Elisa—CA1 or VC was isolated from male mice, lysed with PBS or 5M Guanidine HCl,
and subjected to A
β
measurement with the use of mouse (for WT experiments) or human
(for all other experiments) A
β
1-40 or A
β
1-42 ELISA kit (Invitrogen) according to the
manufacturer's instructions. We lysed the tissue in phosphate-buffered saline (PBS) to
extract the PBS soluble A
β
fraction. The soluble A
β
fraction likely contained monomeric
and oligomeric A
β
. Tissue was further treated with guanidine HCl to extract the insoluble A
β
fraction. A
β
1-42 was below detectable levels for both flicker and control groups in WT VC
and microglia-specific samples.
Genome-Wide RNA Sequencing—Total RNA was extracted from CA1 isolates using
the RNeasy kit (Qiagen). Purified mRNA was used for RNA-seq library preparation using
the BIOO NEXTflex™ kit (BIOO# 5138-08) per the manufacturer's instructions. 1 μg of
total mRNA was subject to a sequential workflow of poly-A purification, fragmentation, 1st
strand and 2nd strand synthesis, DNA end-adenylation, and adapter ligation. The libraries
were enriched by 15 cycles of PCR reactions and cleaned with Agencourt AMPure XP
magnetic beads (Beckman Coulter). The quality of the libraries was assessed using an
Advanced Analytical-fragment Analyzer. The bar-coded libraries were equally mixed for
sequencing in a single lane on the Illumina HiSeq 2000 platform at the MIT BioMicro
Center. The raw fastq data of 50-bp single-end sequencing reads were aligned to the mouse
mm9 reference genome using TopHat2.0. The mapped reads were processed by Cufflinks
2.2 with UCSC mm9 reference gene annotation to estimate transcript abundances, and test
for differential expression. An average of 26,518,345 sequencing reads was obtained from 3
stimulated and 3 non-stimulated mice. Relative abundance of transcript was measured by
Fragments Per Kilobase of exon per Million fragments mapped (FPKM). Gene differential
expression test between treated and untreated groups was performed using Cuffdiff module
with an adjusted p-value<0.05 for statistical significance (GEO accession: GSE77471).
To understand the cellular and molecular mechanisms from our RNA-seq data, 14 of
publicly available RNA-seq datasets34 were processed for cell-type specific analysis.
Additionally, 60 publicly available neuron-, microglia-, and macrophage- specific RNA-seq
datasets under different chemical and genetic perturbations35–40 were downloaded and
processed using TopHat/Cufflinks pipeline for gene set enrichment (GSEA) statistical
analysis. GSEA was used to determine whether a defined gene set from our RNA-seq data is
significantly enriched at either direction of a ranked gene list from a particular perturbation
study. Genes detected in the public RNA-seq datasets were ranked by log2 values of fold
change (case versus control), from positive to negative values. A defined gene set (in our
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case, up- or down-regulated genes upon gamma treatment) was considered significantly
correlated with a perturbation-induced transcriptomic change (either up- or down-
regulation), when both nominal p-value and false discovery rate (FDR) q-value were less
than 0.05. The sign of the calculated normalized enrichment score (NES) indicates whether
the gene set is enriched at the top or the bottom of the ranked list. The heatmap for
differentially expressed genes was generated using a custom R script, and z-score values
across all libraries for each gene were calculated based on the gene FPKM values. The box
plots for cell-type specificity analysis were also generated by R program, based on gene
FPKM values.
Quantitative RT-PCR—The CA1 subregion was isolated from hippocampus of 3-month-
old male 5XFAD/PV-Cre mice. Tissue was rapidly frozen using liquid nitrogen and stored at
-80 °C, and RNA extracted using the RNeasy kit according to the manufacturer's protocol
(Qiagen). RNA (3
μ
g) was treated with DNase I (4 U, Worthington Biochemical
Corporation), purified using RNA Clean and Concentrator-5 Kit (Zymo Research) according
to manufacturers' instructions and eluted with 14
μ
L DEPC-treated water. For each sample,
1
μ
g RNA was reverse transcribed in a 20
μ
Lreaction volume containing random hexamer
mix and Superscript III reverse transcriptase (50 U, Invitrogen) at 50 °C for 1 hr. First strand
cDNAs were diluted 1:10 and 1
μ
L were used for RT-qPCR amplification in a 20
μ
L
reaction (SsoFast EvaGreen Supermix, Bio-Rad) containing primers (0.2
μ
M). Relative
changes in gene expression were assessed using the 2-ΔΔCt method.
Isolation of microglia from VC—The primary visual cortex (V1 region) was rapidly
dissected and placed in ice cold Hanks' Balanced Salt Solution (HBSS) (Gibco by Life
Technologies, Catalog number 14175-095). The tissue was then enzymatically digested
using the Neural Tissue Dissociation Kit (P) (Miltenyi Biotec, Catalog number
130-092-628) according to the manufacturer's protocol, with minor modifications.
Specifically, the tissue was enzymatically digested at 37 °C for 15 minutes instead of 35
minutes and the resulting cell suspension was passed through a 40
μ
m cell strainer (Falcon
Cell Strainers, Sterile, Corning, Product #352340) instead of a MACS SmartStrainer, 70
μ
m. The resulting cell suspension was then stained using allophycocyanin (APC)-conjugated
CD11b mouse clone M1/70.15.11.5 (Miltenyi Biotec, 130-098-088) and phycoerythrin (PE)-
conjugated CD45 antibody (BD Pharmingen, 553081) according to the manufacturer's
(Miltenyi Biotec) recommendations. Fluorescence-activated cell sorting (FACS) was then
used to purify CD11b and CD45 positive microglial cells. The cells were sorted directly into
1XPBS (Ext. Data Fig. 6a).
Code Availability—Code is publically available upon request from the corresponding
author.
Statistics—For electrophysiological data that was not normally distributed, results are
presented as medians and quartiles unless otherwise noted. Two-sided Wilcoxon rank sum
tests for equal medians were performed to determine if distributions were significantly
different, and Wilcoxon signed rank tests were performed to determine if distributions were
significantly different from zero as these do not assume data is normally distributed.
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Variability was similar between the groups that were statistically compared. The Bonferroni
method was used to correct for multiple comparisons. No statistical method was used to
estimate sample size, but it is consistent with previous publications.
Molecular and biochemical results are presented as mean +SEM. Percentages stated in
manuscript are group means. All statistical analysis was performed using Prism GraphPad
software. Normality was determined using the D'Agostino & Pearson omnibus normality
test. Variability was similar between the groups that were statistically compared.
Comparison data for normally distributed data consisting of two groups was analyzed by
two-tailed unpaired
t
tests. Comparison of data for normally distributed data consisting of
three or more groups was analyzed by one-way ANOVA followed by Tukey's multiple
comparisons test. Comparison data for non-normally distributed data was carried out using
Mann Whitney tests. The statistical test, exact P values, and sample size (n) for each
experiment is specified in the figure legend. For optogenetic ELISA data, two-sided
unpaired Student's t-tests were performed to compare mice from the same litter that received
different conditions. No statistical method was used to estimate sample size, but is consistent
with previous publications. Molecular and biochemical analysis was performed using a
minimum of three biological replicates per condition.
Data availability—Data is publically available upon request from the corresponding
author.
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Extended Data
Extended Data Figure 1. 5XFAD mice have reduced power in gamma during hippocampal SWRs
b) Mouse in virtual reality environment.
c) Local field potential recorded in CA1, above, filtered for theta (left) or sharp wave ripples
(right), middle, and gamma, below.
d) Mean and standard deviation of the normalized power spectrum during theta. Each
animal's power spectral density was normalized to its peak (n=6 mice per group).
e) Normalized power spectral densities during theta periods in 3-month-old 5XFAD (green,
n=6 mice) and WT (black/grey, n=6 mice) mice. Each animal's power spectral density was
normalized to its peak (in theta).
f) Average SWR-triggered spectrograms for one WT and one 5XFAD mouse shows an
increase in the gamma band during SWRs. This increase is lower in the 5XFAD mouse than
in the WT mouse (n=370 and 514 SWRs in WT and 5XFAD, respectively; WT mouse
shown here is the same as in Fig. 1a).
g) Distributions for each recording (left) and the mean and standard error across sessions
(right) of instantaneous gamma frequencies during SWRs in 5XFAD (green) and WT (black)
mice show distributions around 40 Hz (n=820, 800, 679, 38, 1875, 57 gamma cycles per
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session in 6 5XFAD animals and 181, 1075, 919, 1622, 51, 1860, 1903 gamma cycles per
session in 6 WT animals).
h) Cumulative distribution of the Z-scored gamma power during the 100 ms around the peak
of the SWR for WT (black) and 5XFAD animals (green) for each animal (left) and the mean
and standard error (shaded) across animals (right) (n=514, 358, 430, 22, 805, 37 SWRs per
session in 6 5XFAD animals and 82, 311, 370, 776, 18, 710, 818 SWRs per session in 6 WT
animals)
i) Fraction of spikes in CA1 during SWRs as a function of the phase of gamma in 5XFAD
(green) and WT (black) mice for each animal (left) and the mean and standard error across
animals (right, n=2475, 1060, 3092, 25, 6521, 123 spikes during SWRs per session in 6
5XFAD mice and 360, 4741, 1564, 2961, 88, 3058, 4270 spikes during SWRs per session in
6 WT mice).
j) SWR rate per non-theta period in 5XFAD (green) and WT (black) mice for each animal
(left) and all animals combined (right, ranksum test, p < 10-10, n=117, 210, 151, 55, 100, 1
non-theta periods per session in 6 5XFAD mice and 80, 68, 115, 95, 15, 159, 218 non-theta
periods per session in 6 WT mice).
k) The cumulative distribution of gamma power during large SWRs (detection threshold
greater than 6 standard deviations above the mean, Methods) shows significantly smaller
increases in 5XFAD (green) than WT (black) mice (ranksum test, p<10-5, n=1000 SWRs in
6 5XFAD mice and 1467 SWRs in 6 WT mice).
l) Fraction of spikes as a function of the phase of gamma during large SWRs (detection
threshold greater than 6 standard deviations above the mean, Methods), mean ± SEM (left)
and histogram of the depth of modulation of spiking (right) as a function of gamma phase in
3-month-old 5XFAD (green, n=6 mice) and WT (black, n=6 mice) mice (ranksum test,
bootstrap resampling p < 10-10, n=2500 5XFAD spike-gamma phase distributions and 3000
WT distributions).
m) Power spectral density during 40 Hz stimulation (red, left), random stimulation (blue,
center), or no stimulation (black, right) of FS-PV-interneurons in CA1 for each mouse (n=4
5XFAD mice with 169, 130, 240, 73 40 Hz, 143, 129, 150, 72 random, and 278, 380, 52,
215 no stimulation periods per animal and n=3 WT mice with 65, 93, 91 40 Hz, 64, 93, 90
random, and 187, 276, 270 no stimulation periods per animal).
n)
Above
: Example raw LFP trace (above) and the trace filtered for spikes (300-6000 Hz,
below), with spikes indicated with red stars after optogenetic stimulation (blue vertical
lines).
Below
: histogram of spikes per pulse after the onset of the 1 ms laser pulse during 40
Hz stimulation (red), random stimulation (blue), or no stimulation (black, n=345762 40 Hz,
301559 random pulses, and 32350 randomly selected no stimulation times at least 500 ms
apart from 552 40 Hz, 543 random, and 1681 no stimulation periods in 4 5XFAD and 3 WT
mice).
o) Histogram of the difference in firing rates between 40 Hz stimulation and random
stimulation periods shows that both types of stimulation elicit similar amounts of spiking
activity (Wilcoxon signed rank test for zero median, p>0.6, n=538 stimulation periods from
4 5XFAD and 3 WT mice, n.s. indicates not significant).
p) Multiunit firing rates per 40 Hz stimulation (red), random stimulation (blue), and no
stimulation (black) period for each animal. Box and whisker plots show median (white lines
in box) and quartiles (top and bottom of box). In all animals firing rates between 40 Hz and
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random stimulation were not significantly different, showing that the random stimulation
condition serves as a control for spiking activity (ranksum tests for each animal, 3 WT and 4
5XFAD mice, p's>0.09, n=87, 130, 8, 65, 93, 91, 73 40 Hz stimulation periods and 85, 129,
5, 64, 93, 90, 72 random stimulation periods per animal). We also examined whether 40 Hz
stimulation caused neuronal hyperactivity relative to no stimulation, because according to a
recent report, this could have negative effects on neural circuit function.26 In most animals
the firing rates between 40 Hz or random stimulation and no stimulation were not
significantly different (ranksum tests for each animal, 2 WT and 2 5XFAD, p's>0.25, n=8,
93, 91, 73 40 Hz stimulation periods and 15, 277, 270, 215 baseline periods per animal) or
the firing rates during 40 Hz or random stimulation were lower than during no stimulation
(ranksum tests for each animal, 1 WT and 1 5XFAD, p's<10-5, which is significant when
corrected for performing multiple comparisons, n=130, 65 40 Hz stimulation periods and
379, 187 baseline periods per animal) indicating that 40 Hz stimulation did not cause
neuronal hyperactivity. In one animal there was significantly more activity with 40 Hz or
random stimulation than during baseline (ranksum test for 1 5XFAD, mouse, p<10-5, n=87
40 Hz stimulation periods and 251 baseline periods per animal). Therefore in six out of
seven animals we see no evidence that the 40 Hz optogenetic stimulation of FS-PV-
interneurons causes hyperactivity.
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Extended Data Figure 2. ChR2 was expressed in FS-PV-interneurons for optogenetic stimulation
a) AAV-DIO-ChR2-EYFP or AAV-DIO-EYFP drives Cre-dependent expression of ChR2-
EYFP or EYFP to produce celltype-specific targeting of ChR2 or EYFP, respectively. In the
presence of Cre, ChR2-EYFP or EYFP is inverted into the sense direction and expressed
from the EF-1α promoter in PV-positive cells. ITR, inverted terminal repeat; polyA; WPRE,
woodchuck hepatitis B virus post-transcriptional element.
b) ChR2-EYFP was strongly expressed in PV-positive interneurons in CA1 of 3-month-old
5XFAD/PV-Cre mice (scale bar = 100 μm).
c) Immunohistochemistry with anti-EYFP and anti-PV antibodies in CA1 of 3-month-old
5XFAD/PV-Cre mice expressing AAV-DIO-ChR2-EYFP shows EYFP expression only in
PV-positive cells (scale bar = 50 μm).
d) Representative western blots showing levels of full-length APP (top left, CT695), APP
CTFs (bottom left, CT695), APP NTFs (top right, A8967) and
β
-actin (bottom right, A5316,
loading control) in CA1 in EYFP, random, and 40 Hz stimulation conditions, 1 mouse per
lane, with 2 biological replicates of each condition.
e) Immunohistochemistry with anti-A
β
(12F4, red) antibodies in CA1 of 5XFAD/PV-Cre
mice expressing only EYFP or ChR2 with 40 Hz, and random stimulation conditions (scale
bar = 50 μm).
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f) Bar graphs represent the relative immunoreactivity of A
β
normalized to EYFP (n=4 mice
per group; * indicates p<0.05 and *** indicates p<0.001 by one-way ANOVA). Bar graphs
show mean + SEM.
g) Immunohistochemistry with anti-Rab5 antibody (ADI-KAP-GP006-E, green) in CA1 of
5XFAD/PV-Cre mice (scale bar = 50 μm).
h) Relative Rab5 intensity levels normalized to EYFP controls (n=3 mice per group).
Extended Data Figure 3. Optogenetically driven 40 Hz oscillations in CA1 cause changes in gene
regulation and immediate early gene expression
a) Table of 130 genes up-regulated by 40 Hz FS-PV-interneuron stimulation determined by
whole transcriptome RNA-Seq of CA1 from 3-month-old 5XFAD/PV-Cre mice (p<0.05 by
Cufflinks 2.2).52
b) Table of 393 genes down-regulated by 40 Hz FS-PV-interneuron stimulation determined
by whole transcriptome RNA-Seq of CA1 from 3-month-old 5XFAD/PV-Cre mice (p<0.05
by Cufflinks 2.2).52
c) Box plot showing fragments per kilobase (FPKM) values of up- and down-regulated
genes in EYFP and 40 Hz groups. Box shows median (black lines in box) and quartiles (top
and bottom of box), whiskers show minimum and maximum values, and circles show
outliers.
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d) GSEA statistics tables showing statistical significance of correlation between genes up- or
down- regulated by 40 Hz stimulation and publicly available neuron, microglia, and
macrophage specific RNA-Seq data under different chemical and genetic perturbations; the
perturbation terms were ranked based on the FDR q-values for the up-regulated gene list,
from the smallest to the largest (Methods).
e) RT-qPCR verification of specific gene targets in the RNA-Seq data set. Bar graph shows
relative RNA levels (fold change) from EYFP (black) and 40 Hz stimulation (red) conditions
(* indicates p<0.05, ** indicates p<0.01, and *** indicates p<0.001 by Student's t-test, n=3
mice per group). All bar graphs show mean + SEM.
f) Immunohistochemistry with Hoechst to label all cell nuclei in CA1 of 5XFAD/PV-Cre
mice expressing only EYFP or ChR2 with 40 Hz stimulation conditions (scale bar = 50 μm).
g) Bar graph represents the estimated CA1 thickness in 5XFAD/PV-Cre mice expressing
only EYFP or ChR2 with 40 Hz stimulation conditions (n=4 mice per group; n.s. indicates
not significant, by Student's t-test).
Extended Data Figure 4. 40 Hz light flicker drives 40 Hz oscillations in VC, while random
flickering does not
a) Power spectral densities of local field potentials in VC during 40 Hz light flicker (red, far
left), random light flicker (blue, center left), dark (black, center right), or light (green, far
right) in VC for each recording session for each mouse (n=5 recordings from 4 5XFAD mice
with 47, 51, 64, 49, 16 40 Hz flicker, 47, 50, 64, 50, 16 random flicker, 279, 301, 382, 294,
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93 dark and 47, 50, 64, 49, 15 light periods). Light flicker at other frequencies increased
power in the flicker frequency, as others have found previously23,24 (data not shown).
b) Histogram of the difference in firing rates between 40 Hz light flicker and random light
flicker (n=226 stimulation periods from 5 recording sessions in 4 5XFAD mice).
c) Multiunit firing rates in VC during 40 Hz light flicker (red), random light flicker (blue),
dark (black), or light (green) periods. Box plots show median (white lines in box) and
quartiles (top and bottom of box). In all animals, firing rates between 40 Hz flicker and
random flicker conditions were not significantly different showing that the random
stimulation condition serves as a control for spiking activity (ranksum tests for each of 5
recording session from 4 5XFAD mice, p's>0.06, n=47, 51, 64, 49, 16 40 Hz flicker periods
and 47, 50, 64, 50, 16 random flicker periods per recording). There were no significant
differences in firing rates between 40 Hz flicker and light conditions indicating that 40 Hz
light flicker generally did not cause neuronal hyperexcitability (ranksum tests for each of 5
recording session from 4 5XFAD mice, p's > 0.2 for 4 recording sessions, p<0.01 for 1
recording session, which is not significant when corrected for performing multiple
comparisons, n=47, 51, 64, 49, 16 40 Hz periods and 47, 50, 64, 49, 16 light periods per
recording). In one session, there was more activity in the 40 Hz flicker than in the dark
condition.
d) Example traces of LFPs recorded above the brain during light flicker (above, yellow
indicates light on, black indicates light off), during three different recording sessions.
e) Power spectral densities of LFPs recorded above the brain during 40 Hz light flicker show
no increase in power at 40 Hz. Thus, the effect is not due to photoelectric effects on
recording equipment or electrical noise (n= 4, 2,1, 1, 17, 42, 36, 55, 53 40 Hz flicker periods
from 4 recording sessions in 3 5XFAD mice undergoing VC recordings and from 5
recording sessions in 2 5XFAD and 3 WT mice undergoing hippocampal recordings). Mean
(solid line) and standard deviation (shaded area) across recordings are shown on the left and
per animal on the right. Recordings with less than 3 flicker periods (light red) resulted in
noisier power spectral densities than recordings with more data (dark red) but none showed
evidence of peaks at 40 Hz.
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Extended Data Figure 5. 40 Hz light flicker does not affect A
β
levels in hippocampus or barrel
cortex
a) Example local field potential trace in hippocampal CA1 before and during 40 Hz light
flicker (above). Mean (solid line) and standard deviation (shaded area) of power spectral
density during 40 Hz light flicker (red), random light flicker (blue), or dark (black) in CA1
(n=2 5XFAD and 3 WT mice).
b) Histogram of the fraction of spikes in hippocampus as a function of time for 4 cycles of
40 Hz light flicker (left, red) or the equivalent period of time for random light flicker (right,
blue, n=2 5XFAD and 3 WT mice, mean ± SEM across animals). Bar above indicates when
light was on (yellow) or off (black). For random stimulation, spiking was aligned to the start
of the light turning on, additional periods with light-on occurred at random intervals
indicated by grey (Methods).
c) Histogram of the difference in firing rates between 40 Hz light flicker and random light
flicker (bottom n=168 stimulation periods from 5 recording sessions in 2 5XFAD and 3 WT
mice).
d) Power spectral densities of local field potentials in CA1 during 40 Hz light flicker (red,
far left), random light flicker (blue, center left), dark (black, center right), or light (green, far
right) for each recording session for each mouse (n=5 recordings from 2 5XFAD and 3 WT
mice with 22, 54, 42, 71, 55, 40 Hz flicker, 12, 34, 32, 54, 36 random flicker, 115, 240, 224,
342, 282 dark and 12, 33, 33, 54, 35 light periods).
e) Multiunit firing rates in CA1 during 40 Hz light flicker (red), random light flicker (blue),
dark (black), or light (green) periods. Box plots show median (white lines in box) and
quartiles (top and bottom of box). In all animals firing rates between 40 Hz flicker and
random flicker conditions were not significantly different showing that the random
stimulation condition serves as a control for spiking activity (ranksum tests for each of 5
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recordings from 2 5XFAD and 3 WT animals, p's>0.2, n=22, 54, 42, 71, 55 40 Hz flicker
periods and 12, 34, 32, 54, 36 random flicker periods per recording). There were no
significant differences in firing rates between 40 Hz flicker and light conditions indicating
that 40 Hz light flicker generally did not cause neuronal hyperexcitability (ranksum tests for
each of 5 recordings from 2 5XFAD and 3 WT animals, p's > 0.3, n=22, 54, 42, 71, 55 40
Hz periods and 12, 34, 33, 54, 35 light periods per recording).
f) Bar graphs of relative A
β
1-40 levels in VC of 5XFAD mice in dark, 40 Hz flicker, and
random flicker conditions, normalized to dark (n=4 mice per group; n.s. indicates not
significant). Bar graphs represent mean + SEM. Circles superimposed on bars in bar graphs
indicate individual data points in each group.
g) Bar graphs of relative A
β
1-42 levels in VC of 5XFAD mice in dark, 40 Hz flicker, and
random flicker conditions, normalized to dark (n=4 mice per group; n.s. indicates not
significant). Bar graphs represent mean + SEM. Circles superimposed on bars in bar graphs
indicate individual data points in each group.
h) Bar graph of relative A
β
1-40 and A
β
1-42 levels in barrel cortex of 5XFAD mice in dark
and 40 Hz flicker conditions, normalized to dark (n=3 mice per group; n.s. indicates not
significant by Student's t-test).
Extended Data Figure 6. Acute reduction in A
β
after light flicker in APP/PS1 and WT mice and
at various time points
a) Bar graph of relative A
β
1-40 and A
β
1-42 levels of APP/PS1 in VC in dark and 40 Hz
flicker conditions, normalized to dark (n=5 mice per group for dark and n=4 mice per group
for 40 Hz flicker conditions; n.s. indicates not significant and * indicates p<0.05, by
Student's t-test). All bar graphs show mean + SEM throughout this figure. Circles
superimposed on bars in bar graphs indicate individual data points in each group.
b) Bar graph of relative mouse A
β
1-40 and A
β
1-42 levels in VC of 9-month-old WT mice in
dark and 40 Hz flicker conditions, normalized to dark (n=11 mice per group for dark and
n=9 mice per group for 40 Hz flicker conditions; * indicates p<0.05, by Student's t-test).
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Extended Data Figure 7. 40 Hz light flicker does not decrease synaptic density in VC
a) Schematic depicting isolation of microglia from VC. VC was dissected, then single cells
were suspended and labeled with CD11b and CD45 antibodies. Subsequently, cells were
sorted via fluorescence-activated cell sorting (FACS) and lysed. A
β
1-40 levels were
analyzed by ELISA.
b) Bar graph of A
β
1-40 levels in microglia purified using FACS (Methods) from VC of 3-
month-old 5XFAD and WT mice (n=8 mice per group for 5XFAD and n=4 mice per group
for WT mice; * indicates p<0.05 by Student's t-test). Circles superimposed on bars in bar
graphs indicate individual data points in each group.
c) Immunohistochemistry with SVP38 (red) antibodies to detect synaptophysin in VC of3-
month-old 5XFAD mice in dark and 40 Hz flicker conditions (Images were taken with 40x
objective; scale bar = 50 μm). Right: 100X rendering of dark and 40 Hz flicker conditions.
d) Bar graph of relative SVP38 intensity levels in VC of 5XFAD mice after dark (black) and
40 Hz (red) flicker conditions, normalized to dark (n=4 mice per group; n.s. indicates not
significant, by Student's t-test).
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Extended Data Figure 8. A
β
levels in VC return to baseline 24 hr after 1 hr of 40 Hz light flicker
a) Bar graph of relative A
β
1-40 and A
β
1-42 levels in VC of 5XFAD mice 1, 4, 12, and 24
hours after 1 hour of dark or 40 Hz flicker treatment, normalized to dark (n=4 mice per
group for 4 and 12 hr wait, n=6 for 1 and 24 hr wait, n=12 for dark; n.s. indicates not
significant, * indicates p<0.05 and ** indicates p<0.01, by one-way ANOVA).
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Extended Data Figure 9. Driving 40 Hz oscillations in VC via light flicker reduces
phosphorylated tau in a tauopathy mouse model
a) Immunohistochemistry with anti-pTau (S202, green) and anti-MAP2 (red) antibodies in
VC of 4-month-old P301S mice after 7 days of 1 hr/day dark or 40 Hz flicker conditions
(Images were taken with 40× objective; scale bar = 50 μm). Insets: 100X rendering of
representative cell body in dark and 40 Hz flicker conditions. No changes were observed by
western blot (Data not shown).
b) Bar graph of relative pTau (S202) intensity levels in P301S mice after 7 days of 1 hr/day
dark (black) and 40 Hz flicker (red) conditions (n=8 mice per group; * indicates p<0.05 by
Student's t-test). All bar graphs show mean + SEM throughout this figure.
c) Bar graph of relative MAP2 intensity levels in P301S mice after 7 days of 1 hr/day dark
(black) and 40 Hz flicker (red) conditions (n=8 mice per group; n.s. indicates not significant
by Student's t-test).
d) Immunohistochemistry with anti-pTau (S396, red) antibodies in P301S mice after 7days
of 1 hr/day dark and 40 Hz flicker conditions (scale bar = 50 μm).
e) Bar graph of relative pTau (S396) fluorescence intensity levels in P301S mice after 7 days
of 1 hr/day dark (black) and 40 Hz flicker (red) conditions (n=8 mice per group; ****
indicates p<0.0001 by Student's t-test).
f) Immunohistochemistry with anti-pTau (S404, green) antibodies in P301S mice after 7
days of 1 hr/day dark and 40 Hz flicker conditions (cale bar = 50 μm).
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g) Bar graph of relative pTau (S400/T403/S404) fluorescence intensity levels in P301S mice
after 7 days of 1 hr/day dark (black) and 40 Hz flicker (red) conditions (n=8 mice per group;
** indicates p<0.01 by Student's t-test). Bar graphs show mean + SEM.
h) Immunohistochemistry with anti-Iba1 (019-19741, green) antibodies in 4-month-old
P301S mice after 7 days of 1 hr/day dark and 40 Hz flicker conditions (Images were taken
with 40× objective; scale bar = 50 μm.) Insets: 100X rendering of representative microglia in
EYFP and 40 Hz stimulation conditions.
i) Bar graph of the number of microglia in P301S mice after 7 days of 1 hr/day dark (black)
and 40 Hz flicker (red) conditions (n=8 mice per group; n.s. indicates not significant by
Student's t-test).
j) Bar graph of the diameter of microglia cell bodies in P301S mice normalized to dark after
7 days of 1 hr/day dark (black) and 40 Hz flicker (red) conditions (n=8 mice per group; ****
indicates p<0.0001 by Student's t-test).
k) Bar graph of the average length of microglia primary processes in P301S mice normalized
to control after 7 days of 1 hr/day dark (black) and 40 Hz flicker (red) conditions (n=8 mice
per group; **** indicates p<0.0001 by Student's t-test).
Extended Data Table 1
Raw A
β
1-40 and A
β
1-42 concentrations
Table displaying raw A
β
1-40 and A
β
1-42 levels with ELISA dilution ratios for each
experimental group. Equal tissue masses were compared for each ELISA experiment. For 7-
day experiments, values were normalized to within litter controls such that raw values 1-4 in
each condition were normalized to the mean of “Dark” values 1-4; raw values 5-9 in each
condition were normalized to the mean of “Dark” values 5-9; raw values 10-13 in each
condition were normalized to the mean of “Dark” values 10-13.
Treatment Dilution Factor Avgerage A
β
1-40 Concentration
(pg/ml) Average A
β
1-42 Concentration
(pg/ml)
Optogenetics
PV-Cre EYFP 1:2 100.01, 61.598, 65.462, 82.509,
69.023, 70.831, 82.152, 74.314 58.777, 54.546, 30.585
PV-Cre 40 Hz 1:2 46.604, 31.041, 26.639, 55.612,
69.326, 17.711, 3.9951 27.271, 41.950, 18.790, 18.262
PV-Cre 8 Hz 1:2 101.268, 54.283, 90.190, 151.690 50.699, 122.85, 35.507
PV-Cre Random 1:2 235.68, 89.962, 157.37, 323.902,
451.78, 241.63 54.029, 137.78, 144.63
αCaMKII-Cre EYFP 1:2 45.813, 59.069, 40.404, 66.810 72.052, 36.573, 67.243, 59.295
αCaMKII-Cre 40 Hz 1:2 55.942, 44.270, 57.498, 47.382,
115.08, 75.673 70.847, 79.683, 61.429
αCaMKII-Cre 8 Hz 1:2 52.829, 46.604, 57.720 95.939, 21.640, 102.987
αCaMKII-Cre Random 1:2 218.00, 191.72, 159.07 66.203, 168.867, 176.404
Light flicker
Dark 1 hr VC 1:2 343.8, 245.3, 210.6, 343.8, 588.4,
394.9, 123.3, 336.3, 328.2, 579.1,
420.0, 339.2
449.5, 320.7, 275.2, 449.5, 769.2,
516.2, 449.4, 320.6, 275.2, 449.4,
769.1, 516.1
Light 1 hr VC 1:2 366.9, 632.4, 378.2, 314.1, 266.9,
264.1 616.4, 592.3, 802.9, 394.5, 330.7,
337.8
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Treatment Dilution Factor Avgerage A
β
1-40 Concentration
(pg/ml) Average A
β
1-42 Concentration
(pg/ml)
20 Hz 1 hr VC 1:2 944.4, 313.2, 595.9, 530.0, 456.5,
289.9 1624, 302.4, 816.0, 687.2, 676.6,
343.0
40 Hz 1 hr VC 1:2 146.4, 143.6, 104.9, 99.6, 179.7,
219.8 191.4, 187.7, 137.2, 130.2, 234.9,
287.3
80 Hz 1 hr VC 1:2 332.5, 328.7, 363.5, 390.6, 530.0,
673.3 558.3, 418.9, 510.7, 609.5, 1186,
921.9
40 Hz + PTX 1 hr VC 1:2 367.2, 431.4, 445.2, 392.4, 386.7,
445.2 396.6, 540.5, 532.7, 705.0, 104.5,
104.5
Random 1 hr VC 1:2 461.8, 100.2, 9.819, 416.6 423.9, 157.9, 389.9, 841.5
Dark 1 hr HPC 1:2 97.949, 107.33, 119.92, 139.33 499.30, 355.13, 469.53, 598.03
40 Hz 1 hr HPC 1:2 88.136, 104.78, 161.52, 197.36 364.53, 408.41, 436.62, 873.83
Random 1 hr HPC 1:2 95.816, 136.77, 70.004, 125.47 466.39, 500.87, 311.26, 582.355
Dark 7 days soluble 1:50
1216.9, 1181.3, 1173.4, 1199.5,
134.73, 151.34, 113.26, 145.14,
127.91, 127.48, 143.02, 127.48,
141.07
5217.2, 8057.9, 9051.3, 6773.7,
244.11, 236.96, 235.38, 240.62,
286.19, 8.382, 11.21, 14.03, 13.56
Dark 7 days insoluble 1:100
1173.2, 1208.2, 1205.3, 1214.6,
994.86, 1059.2, 1176.6, 1065.4,
1002.9, 306.16, 690.70, 3442.7,
152.73
8572.7, 9127.1, 6349.3, 10138,
6852.2, 7056.7, 7039.7, 7094.2,
7289.0, 748.21, 1117.1, 1055.5,
504.95
40 Hz 7 days soluble 1:50
476.71, 283.83, 336.87, 237.22,
7.0175, 4.1480, 4.0580, 1.5205,
91.864, 152.73, 148.84, 141.07,
162.44
419.7, 248.1, 242.7, 90.974,
95.626, 56.936, 67.577, 47.586,
200.87, 13.56, 9.794, 15.44, 3.677
40 Hz 7 days insoluble 1:100
281.97, 270.37, 86.199, 239.71,
23.557, 15.166, 22.714, 1038.9,
1099.8, 1760.8, 1558.8, 187.69,
22.64
202.96, 130.71, 195.73, 193.70,
1646.89, 1579.1, 503.44, 1400.0,
7536.62, 955.23, 1208.8, 694.57,
784.91
Dark 1 hr BC 1:2 81.874, 18.343, 86.554 391.95, 883.69, 604.97
40 Hz 1 hr BC 1:2 81.307, 27.986, 30.113 300.34, 1152.5, 616.92
40 Hz 1 hr wait 4 hr 1:2 91.06, 141.8, 111.2, 12.30 108.0, 168.1, 157.3, 35.158
40 Hz 1 hr wait 12 hr 1:2 167.2, 101.6, 89.31, 119.9 236.1, 134.6, 124.8, 152.4
40 Hz 1 hr wait 24 hr 1:2 246.7, 177.6, 281.2, 175.0, 257.3,
204.2 231.8, 107.0, 402.7, 184.6, 245.1,
179.7
Dark APP/PS1 1:2 1050.16, 1085.25, 1522.45,
1153.69, 1750.77 19.22, 30.68, 28.08, 14.25, 25.30
40 Hz APP/PS1 1:2 512.42, 947.80, 850.45, 793.63 18.85, 15.58, 18.92, 11.44
Dark WT 1:1 0.038, 0.813, 2.016, 1.913, 0.313,
4.11, 7.23, 20.2, 40.4, 38.7, 11.9 N/A
40 Hz WT 1:1 0.139, 0.325, 0.346, 0.390, 8.92,
12.1, 6.34, 12.4, 13.1 N/A
Supplementary Material
Refer to Web version on PubMed Central for supplementary material.
Acknowledgments
We are grateful to S. Tonegawa and D. Roy for APP/PS1 mice and E. Demmons, W. Raja, E. Wu, and B. Arkhurst
and the Boyden laboratory for technical assistance. We thank members of the Tsai and Boyden laboratories, C.
Moore, C. Deister, D. Rei, J. Penney, R. Madabhushi, A. Mungenast, A. Bero, and J. Young for discussions and
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comments on the paper. H.F.I. acknowledges the Cameron Hayden Lord Foundation and Barbara J. Weedon
Fellowship; E.S.B. acknowledges the New York Stem Cell Foundation-Robertson Award, NIH 1R01EY023173, and
NIH 1DP1NS087724; L.H.T. acknowledges the JPB Foundation, Belfer Neurodegeneration Consortium, Halis
Family Foundation, and NIH RO1 AG047661.
References
1. Bartos M, Vida I, Jonas P. Synaptic mechanisms of synchronized gamma oscillations in inhibitory
interneuron networks. Nat Rev Neurosci. 2007; 8:45–56. [PubMed: 17180162]
2. Fries P, Nikolić D, Singer W. The gamma cycle. Trends Neurosci. 2007; 30:309–16. [PubMed:
17555828]
3. Cardin JA, et al. Driving fast-spiking cells induces gamma rhythm and controls sensory responses.
Nature. 2009; 459:663–667. [PubMed: 19396156]
4. Palop JJ, et al. Aberrant Excitatory Neuronal Activity and Compensatory Remodeling of Inhibitory
Hippocampal Circuits in Mouse Models of Alzheimer's Disease. Neuron. 2007; 55:697–711.
[PubMed: 17785178]
5. Verret L, et al. Inhibitory Interneuron Deficit Links Altered Network Activity and Cognitive
Dysfunction in Alzheimer Model. Cell. 2012; 149:708–721. [PubMed: 22541439]
6. Bero AW, et al. Neuronal activity regulates the regional vulnerability to amyloid-β deposition. Nat
Neurosci. 2011; 14:750–756. [PubMed: 21532579]
7. Selkoe DJ, et al. The role of APP processing and trafficking pathways in the formation of amyloid
beta-protein. Ann N Y Acad Sci. 1996; 777:57–64. [PubMed: 8624127]
8. Stam CJ, et al. Generalized synchronization of MEG recordings in Alzheimer's disease: evidence for
involvement of the gamma band. J Clin Neurophysiol. 2002; 19:562–574. [PubMed: 12488788]
9. Gillespie AK, et al. Apolipoprotein E4 causes age-dependent disruption of slow gamma oscillations
during hippocampal sharp-wave ripples. Neuron. 2016; 90:1–12. [PubMed: 27054611]
10. Oakley H, et al. Intraneuronal beta-Amyloid aggregates, neurodegeneration, and neuron loss in
transgenic mice with five familial Alzheimer's disease mutations: potential factors in amyloid
plaque formation. J Neurosci. 2006; 26:10129–10140. [PubMed: 17021169]
11. Colgin LL, et al. Frequency of gamma oscillations routes flow of information in the hippocampus.
Nature. 2009; 462:353–357. [PubMed: 19924214]
12. Buzsáki, G. Rhythms of the brain. Oxford University Press; 2006.
13. Buzsáki G, et al. Hippocampal network patterns of activity in the mouse. Neuroscience. 2003;
116:201–211. [PubMed: 12535953]
14. Carr MF, Karlsson MP, Frank LM. Transient slow gamma synchrony underlies hippocampal
memory replay. Neuron. 2012; 75:700–713. [PubMed: 22920260]
15. Foster DJ, Wilson MA. Reverse replay of behavioural sequences in hippocampal place cells during
the awake state. Nature. 2006; 440:680–3. [PubMed: 16474382]
16. Carr MF, Jadhav SP, Frank LM. Hippocampal replay in the awake state: a potential substrate for
memory consolidation and retrieval. Nat Neurosci. 2011; 14:147–153. [PubMed: 21270783]
17. Helwig M, et al. The neuroendocrine protein 7B2 suppresses the aggregation of neurodegenerative
disease-related proteins. J Biol Chem. 2013; 288:1114–24. [PubMed: 23172224]
18. Das U, et al. Activity-induced convergence of APP and BACE-1 in acidic microdomains via an
endocytosis-dependent pathway. Neuron. 2013; 79:447–460. [PubMed: 23931995]
19. Cataldo AM, et al. Endocytic pathway abnormalities precede amyloid beta deposition in sporadic
Alzheimer's disease and Down syndrome: differential effects of APOE genotype and presenilin
mutations. Am J Pathol. 2000; 157:277–286. [PubMed: 10880397]
20. Gjoneska E, et al. Conserved epigenomic signals in mice and humans reveal immune basis of
Alzheimer's disease. Nature. 2015; 518:365–369. [PubMed: 25693568]
21. Chitu V, Stanley ER. Colony-stimulating factor-1 in immunity and inflammation. Curr Opin
Immunol. 2006; 18:39–48. [PubMed: 16337366]
22. Wang Y, et al. TREM2 lipid sensing sustains the microglial response in an Alzheimer's disease
model. Cell. 2015; 160:1061–1071. [PubMed: 25728668]
Iaccarino et al. Page 31
Nature
. Author manuscript; available in PMC 2017 October 25.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript

23. Gray CM, König P, Engel AK, Singer W. Oscillatory responses in cat visual cortex exhibit inter-
columnar synchronization which reflects global stimulus properties. Nature. 1989; 338:334–7.
[PubMed: 2922061]
24. Eckhorn R, et al. Coherent oscillations: a mechanism of feature linking in the visual cortex? Biol
Cybern. 1988; 60:121–30. [PubMed: 3228555]
25. Pericic D, Bujas M. Sex differences in the response to GABA antagonists depend on the route of
drug administration. Exp Brain Res. 1997; 25:187–90.
26. Jankowsky JL, et al. Mutant presenilins specifically elevate the levels of the 42 residue β-amyloid
peptide in vivo: Evidence for augmentation of a 42-specific β-amyloid secretase. Human Mol
Genet. 2004; 13:159–70. [PubMed: 14645205]
27. Chung K, et al. Structural and molecular interrogation of intact biological systems. Nature. 2013;
497:332–7. [PubMed: 23575631]
28. Yoshiyama Y, et al. Synapse Loss and Microglial Activation Precede Tangles in a P301S Tauopathy
Mouse Model. Neuron. 2007; 53:337–51. [PubMed: 17270732]
29. Canter RG, Penney J, Tsai LH. The road to restoring neural circuits for the treatment of
Alzheimer's disease. Nature. 2016 in press.
Extended Data and Methods References
30. Harvey CD, Collman F, Dombeck DA, Tank DW. Intracellular dynamics of hippocampal place
cells during virtual navigation. Nature. 2009; 461:941–6. [PubMed: 19829374]
31. Aronov D, Tank DW. Engagement of Neural Circuits Underlying 2D Spatial Navigation in a
Rodent Virtual Reality System. Neuron. 2014; 84:442–456. [PubMed: 25374363]
32. Buzsaki G. Theta oscillations in the hippocampus. Neuron. 2002; 33:325–340. [PubMed:
11832222]
33. Ravassard P, et al. Multisensory control of hippocampal spatiotemporal selectivity. Science. 2013;
340:1342–1346. [PubMed: 23641063]
34. Zhang Y, et al. An RNA-sequencing transcriptome and splicing database of glia, neurons, and
vascular cells of the cerebral cortex. J Neurosci. 2014; 34:11929–11947. [PubMed: 25186741]
35. Crotti A, et al. Mutant Huntingtin promotes autonomous microglia activation via myeloid lineage-
determining factors. Nat Neurosci. 2014; 17:513–521. [PubMed: 24584051]
36. Erny D, et al. Host microbiota constantly control maturation and function of microglia in the CNS.
Nat Neurosci. 2015; 18:965–977. [PubMed: 26030851]
37. Chiu IM, et al. A neurodegeneration-specific gene-expression signature of acutely isolated
microglia from an amyotrophic lateral sclerosis mouse model. Cell Rep. 2013; 4:385–401.
[PubMed: 23850290]
38. Gosselin D, et al. Environment drives selection and function of enhancers controlling tissue-
specific macrophage identities. Cell. 2014; 159:1327–1340. [PubMed: 25480297]
39. Huang SCC, et al. Cell-intrinsic lysosomal lipolysis is essential for alternative activation of
macrophages. Nat Immunol. 2014; 15:846–855. [PubMed: 25086775]
40. Yu H, et al. Tet3 regulates synaptic transmission and homeostatic plasticity via DNA oxidation and
repair. Nat Neurosci. 2015; 18:836–43. [PubMed: 25915473]
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Figure 1. 5XFAD mice have reduced power in gamma during hippocampal SWRs
a) Average SWR-triggered spectrograms for one mouse (left) showing gamma (yellow
arrow) during SWRs (red arrow);
right:
frequencies below 80 Hz enlarged (n=370 SWRs). b)
Histogram of instantaneous gamma frequencies during SWRs for mouse in d. a)
Above:
Z-
scored gamma power around SWR peak for one WT and one 5XFAD mouse (mean ± SEM).
Below:
Cumulative distribution of gamma power during SWRs (ranksum test, n=2166 and
3085 SWRs in 6 5XFAD and WT mice, respectively). c)
Above:
Fraction of spikes during
SWRs as a function of gamma phase (mean ± SEM).
Below:
Depth of gamma spiking
modulation during SWRs. (ranksum test, bootstrap resampling, n=2500 5XFAD and 3000
WT phase distributions). d)
Above:
Local field potential trace before and during 40 Hz
optogenetic stimulation.
Below:
Mean and standard deviation of power spectral density (n=4
5XFAD and 3 WT mice). e) Relative A
β
1-40 levels in CA1 of 5XFAD/PV-Cre mice in each
stimulation condition normalized to EYFP controls (n=8 EYFP, n=7 40 Hz, n=4 8 Hz n=6
random mice). f) As in i for A
β
1-42(n=4 EYFP, n=4 40 Hz, n=3 8 Hz n=3 random mice). g)
Relative A
β
1-40 levels in CA1 of 5XFAD/αCamKII-Cre mice in each stimulation condition
normalized to EYFP controls (n=6 40 Hz, n=3 8 Hz n=3 random mice). h) As in k for A
β
1-42(n=3 mice per group). n.s. not significant, * p<0.05, ** p<0.01, *** p<0.001 by one-
way ANOVA; circles indicate n, mean+SEM in bar graphs.
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Figure 2. Driving 40 Hz oscillations optogenetically in hippocampus reduces A
β
in 5XFAD mice
a) Representative western blot showing levels of APP (CT695), APP NTFs (A8967), APP
CTFs (CT695), and
β
-Actin (A5316, loading control) in CA1 of 5XFAD/PV-Cre mice
expressing only EYFP or ChR2 with 40 Hz, or random stimulation conditions. 1 mouse per
lane, 2 biological replicates. b) Relative immunoreactivity of full-length APP normalized to
actin (for b-d, n=6 mice per group). c) Relative immunoreactivity of APP NTF normalized
to actin. d) Relative immunoreactivity of APP CTFs normalized to actin. e)
Immunohistochemistry with anti-A
β
(D54D2, green) and anti-EEA1 (610457, red)
antibodies in CA1 of 5XFAD/PV-Cre mice (scale bar = 50 μm). f) Relative
immunoreactivity of A
β
normalized to EYFP controls(for f, g, n=3 mice per group). g)
Relative immunoreactivity of EEA1 normalized to EYFP controls. n.s. not significant, *
p<0.05, ** p<0.01, by one-way ANOVA; mean + SEM in bar graphs.
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Figure 3. Driving 40 Hz oscillations optogenetically in hippocampus causes a distinct
morphological transformation of microglia in 5XFAD mice
a) Heat map of differentially expressed genes determined by whole-transcriptome RNA-Seq
of CA1 from 5XFAD/PV-Cre mice expressing only EYFP or ChR2 with 40 Hz stimulation.
Normalized z-score values (high: red, low: blue) were calculated for each differentially
expressed gene (row). b) Cell-type-specific expression patterns of up-regulated genes
following 40 Hz stimulation (MO: myelinating oligodendrocyte, OPC: oligodendrocyte
progenitor cell, NFO: newly formed oligodendrocyte). c) RT-qPCR of specific up-regulated
genes:relative RNA levels (fold change) in CA1 of 5XFAD/PV-Cre expressing only EYFP or
ChR2 with 40 Hz stimulation, normalized to EYFP controls (Student's t-test; n=6 mice per
group). d) Immunohistochemistry with anti-Iba1 (019-19741, green) to identify microglia
and anti-A
β
(12F4, red) antibodies in CA1 of 5XFAD/PV-Cre mice expressing only EYFP
or ChR2 with 40 Hz, and random stimulation (40× objective; scale bar = 50 μm). e) Number
of Iba1-positive microglia (for f-I,
one
-way ANOVA; n=4 mice per group). f) Diameter of
Iba1-positive microglia cell bodies. g) Average length of Iba1-positive microglia primary
processes. h) Percent of Iba1-positive microglia cell bodies that are also A
β
-positive. n.s.
not significant, * p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001; mean + SEM in bar
graphs.
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Figure 4. Driving 40 Hz oscillations in VC via light flicker reduces A
β
and amyloid plaques in
5XFAD mice
a) Local field potential trace in VC before and during 40 Hz light flicker (above). Power
spectral density mean and standard deviation (below, n=4 5XFAD mice, 5 recording
sessions). b) Fraction of spikes in VC over 4 cycles of 40 Hz flicker (left) or the equivalent
time for random flicker (right, n=4 5XFAD mice from 5 recording sessions, mean ± SEM
across animals). For random stimulation, spiking was aligned to light turning on, grey
indicates additional light-on flickers occurring randomly (Methods). c) Relative A
β
1-40
(left) and A
β
1-42 (right) levels normalized to dark, in VC of 5XFAD mice exposed to dark,
light, 40 Hz, 20 Hz, 80 Hz, 40 Hz with picrotoxin (PTX), and random conditions (n=12
dark; n=6 light, 40 Hz, 20 Hz, 80 Hz flicker and PTX; n=4 random mice; one-way ANOVA).
d) Immunohistochemistry with anti-Iba1 (019-19741, green) and anti-A
β
(12F4,
red)antibodies in VC of 5XFAD mice exposed to dark or 40 Hz flicker. Right: 120X zoom;
arrows indicate +Iba1/+A
β
signal in cell body(scale bar=50 μm). e) Number of Iba1-positive
microglia(for e-h Student's t-test unpaired, n=4 mice per group) f) Diameter of Iba1-positive
microglia cell bodies. g) Average length of Iba1-positive microglia primary processes. h)
Percent of Iba1-positive microglia cell bodies that are also A
β
-positive. i) Relative A
β
1-40
levels in VC of 6-month-old 5XFAD mice after 7 days of 1 hr/day dark or 40 Hz flicker
(Student's t-test unpaired; n=13 mice per group). j) As in i forA
β
1-42. k)
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Immunohistochemistry with anti-A
β
(D5452, green) antibody in 6-month-old VC of 5XFAD
mice after 7 days of 1 hr/day dark or 40 Hz flicker showing plaques (white arrows; scale
bar=50 μm). i) Number of A
β
-positive plaques; (for l,m Student's t-test unpaired, n=8 mice
per group). m) Area of A
β
-positive plaques. n.s. not significant, * p<0.05, ** p<0.01, ***
p<0.001; circles indicate n, mean + SEM in bar graphs.
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