THE

JOURNAL• RESEARCH •www.fasebj.org

Temporal dynamics of learning-promoted synaptic
diversity in CA1 pyramidal neurons
Yuya Sakimoto,* Hiroyuki Kida,* and Dai Mitsushima*,†,1*Department of Physiology, Graduate School of Medicine, Yamaguchi University, Ube, Japan; and †The Research Institute for Time Studies,
Yamaguchi University, Yamaguchi, Japan

ABSTRACT: Although contextual learning requires plasticity at both excitatory and inhibitory (E/I) synapses in cornu

ammonis 1 (CA1) neurons, the temporal dynamics across the neuronal population are poorly understood. Using an
inhibitory avoidance task, we analyzed the dynamic changes in learning-induced E/I synaptic plasticity. The
training strengthened GABAA receptor–mediated synapses within 1 min, peaked at 10 min, and lasted for over 60
min. The intracellular loop (Ser4082409) of GABAA receptor b3 subunit was also phosphorylated within 1 min of
training. As the results of strengthening of a-amino-3-hydroxyl-5-methyl-4-isoxazole-propionate receptor–
mediated synapses, CA1 pyramidal neurons exhibited broad diversity of E/I synaptic currents within 5 min.
Moreover, presynaptic glutamate release probability at basal dendrites also increased within 5 min. To further
quantify the diversified E/I synaptic currents, we calculated self-entropy (bit) for individual neurons. The neurons
showed individual levels of the parameter, which rapidly increased within 1 min of training and maintained for over
60 min. These results suggest that learning-induced synaptic plasticity is critical immediately following encoding
rather than during the retrieval phase of the learning. Understanding the temporal dynamics along with thequantification of synaptic diversity would be necessary to identify a failure point for learning-promoted plasticity incognitive disorders.—Sakimoto, Y., Kida, H., Mitsushima, D. Temporal dynamics of learning-promoted synaptic
diversity in CA1 pyramidal neurons. FASEB J. 33, 000–000 (2019). www.fasebj.org
KEY WORDS: AMPA receptor • glutamate • GABAA receptor • GABA • contextual learning

The hippocampus is a primary area for contextual memory (1), known to process spatio-temporal information (2,3) within a specific episode (4). Long-term strengthening ofglutamatergic transmission has been identified as amechanism of contextual learning in the dorsal cornu
ammonis 1 (CA1) area of the hippocampus (5), and CA1specific immobilization or blockade of a-amino-3hydroxyl-5-methyl-4-isoxazole-propionate (AMPA) receptor delivery can impair the performance (6, 7), indicating a
causal relationship between learning and the receptor delivery into the synapses.
ABBREVIATIONS: Ab42, amyloid b peptide 1–42; AMPA, a-amino-3-hy-

droxyl-5-methyl-4-isoxazole-propionate; CA1, cornu ammonis 1; CNQX,
7-nitro-2,3-dioxo-1,4-dihydroquinoxaline-6-carbonitrile; E/I, excitatory
and inhibitory; EPSC, excitatory postsynaptic current; GluA, glutamate
receptor subunit A; IA, inhibitory avoidance; IPSC, inhibitory postsynaptic current; mEPSC, miniature EPSC; mIPSC, miniature IPSC
1

Correspondence: Department of Physiology, Yamaguchi University
School of Medicine, 1-1-1 Minami-Kogushi Ube, Yamaguchi 755-8505,
Japan. E-mail: mitsu@yamaguchi-u.ac.jp

This is an Open Access article distributed under the terms of theCreative Commons Attribution 4.0 International (CC BY 4.0) (http://
creativecommons.org/licenses/by/4.0/) which permits unrestricted use,
distribution, and reproduction in any medium, provided the original
work is properly cited.
doi: 10.1096/fj.201801893RRR

0892-6638/19/0033-0001 © The Author(s)AMPA receptors are tetrameric [glutamate receptor
subunit A (GluA)1–4] (8, 9) ligand-gated cation channels
at glutamatergic synapses. Considering that each presynaptic vesicle contains ;2000 molecules of glutamate(10, 11), we quantified miniature postsynaptic AMPA receptor current induced by single-synaptic vesicle ofglutamate [miniature excitatory postsynaptic current(mEPSC)]. Moreover, by comparing the current in untrained and trained animals, we analyzed the learninginduced plasticity (12, 13), and paired-pulse facilitationof AMPA receptor–mediated responses further allows
determining the presynaptic glutamate-release probability (14, 15).
The nature of learning-induced pre- and postsynaptic plasticity is more complicated by the fact thatlearning also affects GABAA receptor–mediated inhibitory synapses in CA1 pyramidal neurons (12, 16,17). GABAA receptors typically consist of 2 a subunits
and 2 b subunits, together with either 1 g or d subunit (18). Pore opening allows Cl2 influx to induce a
postsynaptic hyperpolarization upon GABA binding.
Considering that each presynaptic vesicle contains;2500 molecules of GABA (19, 20), we also quantified
miniature postsynaptic GABAA receptor current induced by single-synaptic vesicle of GABA [miniature
inhibitory postsynaptic current (mIPSC)]. Moreover,1m www.fasebj.org by Yamaguchi Univ Medical Lib (133.62.64.210) on November 06, 2019. The FASEB Journal Vol. ${article.issue.getVolume()}, No. ${article.issue.getIssueNumber()}

we compared the current in untrained and trained animals to analyze the learning-induced plasticity at
GABAA receptor–mediated synapses (12, 13). The
paired-pulse depression of GABAA receptor–mediatedresponses was also analyzed to determine the changes
in presynaptic GABA-release probability (15, 21). Bychanging holding potential of the membrane, we took
both mEPSC and mIPSC data sequentially from thesame CA1 neuron and multidimensionally plotted theneurons to evaluate the synaptic diversity.
Genetic deficiency of GABAA receptor b3 subunit severely impairs the contextual freezing response without
affecting pain perception (22), and the phosphorylation in
the cytoplasmic loop of b3 subunit (Ser4082409) is known
to play an essential role for PKA, PKB, PKC, or Ca2+and calmodulin–dependent protein kinase II–dependent
plasticity (23). Becausee the phosphorylation is known toincrease surface levels of GABAA receptors containing b3
subunits in cultured neurons (24–27), we also examinedthe effect of learning as well as the temporal dynamics.
Pharmacological manipulation of the AMPA or
GABAA receptors in the CA1 suggested different roles of
the receptors after training (12, 28–33). Microinjectionsof the AMPA receptor blocker [7-nitro-2,3-dioxo-1,4dihydroquinoxaline-6-carbonitrile (CNQX)] into CA1
impairs inhibitory avoidance (IA) task training immediately (0–5 min) but the effects are lost 30–60 min after
training (29, 30, 32), whereas GABAA receptor blocker
microinjection improves performance if performed
immediately following training (28, 31–33). Althoughthese studies suggest a critical period for plasticity immediately following training, the dynamic changes inlearning-induced synaptic diversity are poorly understood. Here, we analyze the dynamic changes seenin learning-induced excitatory and inhibitory (E/I)
synaptic function, pre- and postsynaptically. Learning
rapidly strengthened both E/I synapses in various
ways in individual CA1 neurons, producing a broad
diversity of synaptic input across the CA1 neuronal
population within 5 min after the training. Moreover,
we quantified the diversity levels by calculating theself-entropy per single CA1 neuron.

MATERIALS AND METHODS
Animals
Male Sprague-Dawley rats (postnatal 4 wk of age) were obtained
from Chiyoda Kaihatsu (Tokyo, Japan). Prior to the experiment,
the rats were individually housed in plastic cages for a couple ofdays (40 3 25 3 25 cm) at a constant temperature (23 6 1°C)
under a 12-h light/dark cycle (lights on from 8 AM to 8 PM) with ad
libitum access to water and food (MF; Oriental Yeast, Tokyo, Japan). All animal housing and surgical procedures were approvedby the Institutional Animal Care and Use Committee of Yamaguchi University Graduate School of Medicine and comply with
the Guide for the Care and Use of Laboratory Animals [National
Institutes of Health (NIH), Bethesda, MD, USA].
IA task
Hippocampus-dependent IA training procedures were previously described in refs. 6 and 12. The IA training apparatus(length, 33 cm; width, 58 cm; height, 33 cm) was a 2-chambered
box consisting of a lighted safe side and a dark shock side separated by a trap door (Fig. 1A). For training, rats were placed in thelight side of the box facing a corner opposite the door. After thetrap door was opened, the rats could enter the dark box at will.
The latency before entering the novel dark box was measured as abehavioral parameter (latency before IA learning, Fig. 1B). Fourseconds after the animals entered the dark side, we closed thedoor and applied a scrambled electrical foot-shock (2 s, 1.6 mA)
via electrified steel rods in the floor of the box. The rats were kept
in the dark compartment for 10 s before being returned to theirhome cage. The rats in the 0-min group were quickly euthanizedwith an overdose of pentobarbital within 1 min. Untrained control rats were not moved from their home cages and were injectedwith the same dose of anesthesia. The results of unpaired andwalk-through controls were previously reported (12).
Thirty minutes after the procedure described above, the rats
were placed in the light side. The latency before entering the dark
box was measured as an indicator of learning performance (latency after IA learning).

Slice patch-clamp
Acute brain slices were prepared as previously described in refs.
12 and 13. Detailed protocol of slice patch-clamp technique for

Figure 1. Diagram of experimental design and IA task. A) Rats were housed in a home cage but moved into the light box used forthe task on the training day. A brief electrical foot-shock (2 s) was applied in the dark box in the shock cage. Brain slices wereprepared at various time points of the training. B) Thirty minutes after the training, the rats consistently showed a longer latency
before entering the dark side of the box. **P , 0.01 vs. training. Error bars indicate 6 SEM. The number of rats is shown at thebottom of each bar.
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analyzing learning-induced synaptic plasticity was also published with a short demonstration movie (34).
Rats were deeply anesthetized with pentobarbital at 0, 5,
10, 20, 30, or 60 min after the paired foot-shock. Then, thebrains were quickly perfused with ice-cold dissection buffer(25.0 mM NaHCO3, 1.25 mM NaH2PO4, 2.5 mM KCl, 0.5 mM
CaCl2, 7.0 mM MgCl2, 25.0 mM glucose, 90 mM choline
chloride, 11.6 mM ascorbic acid, and 3.1 mM pyruvic acid)and gassed with 5% CO2 and 95% O2. Coronal brain slices(target CA1 area, AP -3.8 mm, DV 2.5 mm, LM 6 2.0 mm)
were cut (350 mm; Leica vibratome; VT-1200; Leica Microsystems, Buffalo Grove, IL, USA) in dissection buffer andtransferred to physiologic solution [22–25°C; 114.6 mM NaCl,
2.5 mM KCl, 26 mM NaHCO3, 1 mM NaH2PO4, 10 mM glucose, 4 mM MgCl2, and 4 mM CaCl2 (pH 7.4); gassed with 5%
CO2 and 95% O2]. We maintained 3–4 brain slices for patch
recordings based on the brain atlas by Paxinos and Watson(35). Glass electrodes were made with a horizontal puller(model P97; Sutter Instrument, Novato, CA, USA) and filledwith a suitable solution. Whole-cell recordings were obtained
from pyramidal neurons of the hippocampal CA1 layer, using an Axopatch-1D amplifier (Molecular Devices, Sunnyvale, CA, USA). Recordings were digitized using a Digidata
1440 AD board (Molecular Devices), recorded at 5 kHz, andanalyzed offline with pClamp v.10.4 software (Molecular
Devices).

Miniature recordings
For miniature recordings, we used a modified intracellularsolution to adjust the reversal potential of the GABAA receptor response [127.5 mM cesium methanesulfonate, 7.5 mM
CsCl, 10 mM HEPES, 2.5 mM MgCl2, 4 mM Na2ATP, 0.4 mM
Na3GTP, 10 mM sodium phosphocreatine, 0.6 mM EGTA (pH7.25)]. Moreover, we added 0.5 mM tetrodotoxin (Wako Pure
Chemicals, Osaka, Japan) to perfusate to block action potentials. The voltage was clamped at 260 mV for mEPSC recording and at 0 mV for mIPSC recording (Figs. 2A and 3A).
We analyzed the frequency and amplitude of mEPSCs andmIPSCs above 10 pA.
We obtained 4 miniature parameters (mean mEPSC amplitude, mean mIPSC amplitude, mean mEPSC frequency, andmean mIPSC frequency) in individual CA1 pyramidal neurons.
For graphic expression, the distribution was visualized 2-dimensionally in the R software environment (R Foundation for
Statistical Computing, Vienna, Austria) (amplitude in Fig. 2B;
frequency in Fig. 3B). To calculate E/I balance, the value ofmEPSC frequency or amplitude was divided by corresponding
value of mIPSC frequency or amplitude in each neuron. After
recording, we confirmed that mEPSCs and mIPSCs were completely abolished by 10 mM CNQX (MilliporeSigma, Burlington,
MA, USA) and 10 mM bicuculline methiodide (MilliporeSigma),
respectively.

Paired-pulse stimulation
To analyze presynaptic plasticity at excitatory synapses, we
added 0.1 mM picrotoxin and 4 mM 2-chloroadenosine to theperfusate and performed paired-pulse stimulation at 260
mV. To analyze presynaptic plasticity at inhibitory synapses,
we added 10 mM CNQX to the perfusate and performed
paired-pulse stimulation at 0 mV. To evaluate the pairedpulse ratio from the EPSC or IPSC average, 50–100 sweeps
were recorded with paired stimuli at 100-ms intervals. The
ratio of the second amplitude to the first amplitude was calculated as the paired-pulse ratio.

CHANGES IN SYNAPTIC DIVERSITY AFTER TRAINING

Western blotting
Western blotting was performed according to a previous study(13). Rats were deeply anesthetized with pentobarbital at 0, 5, or
30 min after the training. The brain was removed and incubatedfor 3 min in ice-cold buffer containing 0.32 M sucrose and 20 mM
Tris–HCl (pH 7.5). Dissected hippocampal CA1 tissues were
homogenized in 200 ml of buffer containing 50 mM Tris–HCl (pH7.4), 0.5% Triton X-100, 0.5 M NaCl, 10 mM EDTA, 4 mM EGTA,
1 mM Na3VO4, 50 mM NaF, 40 mM sodium pyrophosphate,
1 mM protease inhibitor, and 1 mM DTT. Insoluble material was
removed by a 10-min centrifugation at 15,000 rpm.
Samples containing equivalent amounts of protein based on
the bicinchoninic acid analysis (Thermo Fisher Scientific, Waltham, MA, USA) were heated at 100°C for 3 min in Laemmli
sample buffer and subjected to SDS-PAGE for 30 min at 200 V.
Proteins were transferred to an immobilon PVDF membrane for 1
h at 100 V. Membranes were blocked for 1 h at room temperaturein 50 mM Tris–HCl (pH 7.5), 150 mM NaCl, 0.1% Tween 20, and
5% skim milk. Then, the membranes were incubated overnight at
4°C with anti–GABAA receptor b3 subunit (1:1000; Abcam,
Cambridge, MA, USA), anti–phosphorylated GABAA receptor b3
subunit (Ser4082409) (1:1000; Abgent, San Diego, CA, USA), or
anti–b-tubulin (1:1000; BioLegend, San Diego, CA, USA). This
step was followed by incubation with horseradish peroxidase–
conjugated goat anti-rabbit IgG (1:5000; MilliporeSigma) for
GABAA receptor b3 subunit, phosphorylated GABAA receptor b3
subunit, and b-tubulin. Bound antibodies were visualized using
an ECL detection system (GE Healthcare, Chicago, IL, USA) andsemiquantitatively analyzed using the ImageJ program (NIH).

Self-entropy analysis
As we previously reported, standard spreadsheet software (Excel
2010; Microsoft, Redmond, WA, USA) was used to calculate theself-entropy per neuron (36). Although we obtained 4 miniatureparameters (mean mEPSC amplitude, mean mIPSC amplitude,mean mEPSC frequency, and mean mIPSC frequency) in individual CA1 pyramidal neurons, we determined the distributionof appearance probability of each miniature parameter using 1dimensional kernel density analysis. X1, X2, . . ., Xn denotes asample of size n from real observations. The kernel density estimate of P at the point x is given by
1 n
x 2 Xi+K
Pn ðxÞ ¼
nh i¼1hwhere K is a smooth function called the gaussian kernel function
and h . 0 is the smoothing bandwidth that controls the amount ofsmoothing. We chose Silverman’s reference bandwidth or Silverman’s rule of thumb (37, 38). It is given by:
h ¼ 0:9An21/5
where A = min (SD, interquartile range 1.34). By normalizing
integral value in untrained controls, we found the distribution of
appearance probability at any point. Then, we calculated theappearance probability at selected points. All data points forprobability in untrained and trained rats were converted toself-entropy (bit) using the Shannon entropy concept definedfrom the information theory (39).
In the spreadsheet software, the data of 4 miniature parameters were summarized in 4 different sheets, and we obtained the
bandwidth (h) of individual parameter in untrained group using
a formula [=0.9 STDEV (neuron 1, neuron 2, neuron N) /COUNT(neuron 1, neuron 2, neuron N)1/5]. Then, using the data of theuntrained group, we calculated the distribution of appearance
probability as follows:3m www.fasebj.org by Yamaguchi Univ Medical Lib (133.62.64.210) on November 06, 2019. The FASEB Journal Vol. ${article.issue.getVolume()}, No. ${article.issue.getIssueNumber()}

Figure 2. Temporal dynamics of the learning-induced diversity of mEPSC and mIPSC amplitudes and entropy analysis. A)
Representative traces of mEPSCs and mIPSCs. We measured the mEPSCs at 260 mV and mIPSCs at 0 mV sequentially in thesame CA1 pyramidal neuron in the presence of tetrodotoxin (0.5 mM). Vertical bar = 20 pA; horizontal bar = 50 ms. B) Plots ofthe means mEPSC and mIPSC amplitudes in each neuron (upper) and the visualized density by kernel analysis (lower). C ) By
(continued on next page)

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m www.fasebj.org by Yamaguchi Univ Medical Lib (133.62.64.210) on November 06, 2019. The FASEB Journal Vol. ${article.issue.getVolume()}, No. ${article.issue.getIssueNumber()}1. Probability distribution of first data of a parameter(neuron 1) was calculated using a formula [=EXP(-(((dataof neuron 1 2 any point)/h)2/2))/SQRT (2 3 PI())].
2. Also, probability distribution of second data of the parameter(neuron 2) was calculated using the formula [=EXP(-(((dataof neuron 2 2 any point)/h)2/2)) /SQRT(2 3 PI)].
3. Similarly, probability distribution of N data of the parameter(neuron N) was calculated using the formula [=EXP(-(((dataof neuron N 2 any point)/h)2/2)) /SQRT(2 3 PI)].
4. Sum all probability distribution from neuron 1 to N, andthe integral value was normalized to 1.
Based on the probability distribution, we calculated individual appearance probability of all recorded neurons. Then, theappearance probability of the neuron was converted to theself-entropy using Shannon’s formula [=2LOG (appearance
probability of the neuron, 2)]. For graphic expression, we visualized the self-entropy distribution by 2-dimensional kernel
analysis in the R software environment (Figs. 2C and 3C).
Statistical analysis
We used the paired Student’s t test to analyze the latency. The
data of mEPSC, mIPSC, self-entropy, and protein levels wereanalyzed using 1-way factorial ANOVA in which thebetween-group factors were the individual time points. The
Shapiro-Wilk test and F test were used for normality andequality of variance, respectively. Because the self-entropy data
had large variations within a group, we performed log (1 + x)transformation prior to the analysis (40). A value of P , 0.05
was considered significant.

RESULTS
The performance of IA task
To investigate learning-induced synaptic modification in
the hippocampus, we used the IA task (Fig. 1A). In thisparadigm, rats were allowed to cross from a light box to adark box, where an electric foot-shock (1.6 mA, 2 s) was
delivered. Half an hour after the task, we measured thelatency in the illuminated box as contextual learning performance. Figure 1B shows the latency in the training
session and the retrieval test. The rats consistently showed
longer latency in the retrieval test than in the training
session (Fig. 1B; t11 = 5.746; P , 0.0001).
Miniature postsynaptic currents
To analyze the learning-dependent synaptic plasticity, werecorded mEPSC or mIPSC in the presence of 0.5 mM tetrodotoxin on the dorsal hippocampus (Fig. 2A). By changing
the membrane potential, we sequentially recorded mEPSCs(at 260 mV) and mIPSCs (at 0 mV) from the same neuron, as
previously reported in refs. 12 and 13. We confirmed that themEPSC and mIPSC events were clearly blocked by the bathtreatment of an AMPA receptor blocker (CNQX) or GABAA
receptor blocker (bicuculline). The postsynaptic currents arethought to correspond to the response elicited by a single
vesicle of glutamate or GABA (41). In contrast, the number ofsynapses affects the frequency of events.
We found cell-specific mean AMPA receptor–mediatedexcitatory currents vs. GABAA receptor–mediated inhibitory currents in each neuron and plotted them 2-dimensionally [amplitude in Fig. 2B (upper); frequency inFig. 3B (upper)]. Although untrained rats exhibited anarrow distribution, trained rats had a broad distribution
suggesting a diversity of synaptic currents in CA1 pyramidal neurons [amplitude in Fig. 2B (lower); frequency inFig. 3B (lower)]. In the mEPSCs, 1-way ANOVA revealed
significant temporal change [amplitude in Fig. 2D, F(6, 318) =5.448, P , 0.0001; frequency in Fig. 3D, F(6, 318) = 3.738, P =0.0013]. Compared with untrained control, post hoc analysis further showed a significant effect from 5 to 60 min after
the training (Fig. 2D). Also in the mIPSCs, 1-way ANOVA
revealed significant temporal change [amplitude in Fig. 2E,
F(6, 318) = 20.296, P , 0.0001; frequency in Fig. 3E, F(6, 318) =19.492; P , 0.0001]. Post hoc analysis further showed asignificant effect from 0 to 60 min after the training (amplitude in Fig. 2E; frequency in Fig. 3E). These results
suggest rapid postsynaptic strengthening at both E/I
synapses within 5 min after the training.
Continuous plasticity in the sliced condition may affect thesynaptic functions. To rule out this possibility, we examinedthe change of mEPSC and mIPSC amplitude or frequency
along with the elapsed time of the slice in the interface
chamber. To this end, we recorded mEPSCs and mIPSCs
from CA1 pyramidal neurons 1–10 h after the slice preparation, showing no correlation between the mEPSC and mIPSC
parameters and the elapsed time of the slice (mEPSC amplitude, R2 = 0.003; mEPSC frequency, R2 = 0.083; mIPSC amplitude, R2 = 0.080; mEPSC frequency, R2 = 0.134; N = 75).
E/I balance
To calculate the balance of E/I inputs, mean mEPSC amplitude
was divided by mean mIPSC amplitude and mean mEPSC
frequency was divided by the mean mIPSC frequency in eachneuron. In the E/I balance of the amplitudes, the main effect oftraining [F(6, 318) = 1.570; P = 0.16] was not significant after the
training (Fig. 2F). Conversely, in the E/I balance of miniature
frequency, the main effect of training was significant after the
training [Fig. 3F, F(6, 318) = 2.371; P = 0.0296]. Post hoc analysis
further showed a significant decrease from 0 to 5 min after the
training, suggesting faster postsynaptic plasticity at the inhibitory synapses than that at excitatory synapses (Fig. 3F).

calculating appearance probability of each dot, we plotted self-entropy (bit) of individual neurons (upper) and visualized thedensity by kernel analysis in untrained and trained rats (lower). D, E ) Mean amplitude of mEPSCs (D) or mIPSCs (E ) in all
recorded neurons in untrained and trained rats. IA training increased mEPSC amplitude within 5 min, whereas it increased
mIPSC amplitude within 1 min after the training (0 min). F ) E/I balance of the mEPSC and mIPSC amplitude did not change
after the training. G, H) The training also increased the self-entropy (bit) of excitatory (G) and inhibitory (H ) synapses in CA1
neurons. I ) Combined self-entropy (bit) of the mEPSC and mIPSC amplitudes in untrained and trained rats. The number of cells
in each group is shown at the bottom of each bar. Error bars indicate + SEM. *P , 0.05, **P , 0.01 vs. untrained. ▼ or :indicate the timing of training or retrieval tests.
CHANGES IN SYNAPTIC DIVERSITY AFTER TRAINING

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Figure 3. Temporal dynamics of the learning-induced diversity of mEPSC and mIPSC frequencies and entropy analysis. A)
Representative traces of mEPSCs and mIPSCs. Vertical bar = 20 pA; horizontal bar = 50 ms. B) Plots of the means mEPSC andmIPSC frequency in each neuron (upper) and the visualized density by kernel analysis (lower). C ) By calculating appearance
probability of each dot, we plotted self-entropy (bit) of individual neurons (upper) and visualized the density by kernel analysis in(continued on next page)

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m www.fasebj.org by Yamaguchi Univ Medical Lib (133.62.64.210) on November 06, 2019. The FASEB Journal Vol. ${article.issue.getVolume()}, No. ${article.issue.getIssueNumber()}Self-entropy of mEPSC and mIPSC amplitude
Based on the information theory of Shannon (39), we calculated the appearance probability of the mean amplitudes of mEPSCs and mIPSCs. First, we found the
distribution of appearance probability in untrained controls (Fig. 2B, left) and then we analyzed cell-specific appearance probability of all recorded neurons one by one(Fig. 2C, upper panels). Each probability of a single neuron
was calculated as the self-entropy and plotted 2-dimensionally. For example, a point with a high appearance
probability (around the mean level of mEPSC and mIPSC
amplitude) indicated low self-entropy, whereas a pointwith very rare probability (a deviated point of mEPSC andmIPSC amplitude) indicated high self-entropy.
Two-dimensional kernel analysis visualized the density(Fig. 2C, lower panels). IA training clearly diversified theamount of information per neuron and sustained. For themEPSC amplitude, the results are statistically summarized
in Fig. 2G. Self-entropy in the mEPSC amplitude exhibiteda significant temporal change [F(6, 318) = 13.456; P , 0.0001].
Post hoc analysis further showed a significant effect from 5
to 60 min after the training compared with untrained
control. Similarly, self-entropy in the mIPSC amplitude
exhibited a significant temporal change [F(6, 318) = 15.057;
P , 0.0001; Fig. 2H], and post hoc showed a significant
effect from 5 to 60 min after the training. Combined
self-entropy (bit) at both synapses also increased within 5
min after the training [F(6, 318) = 8.565, P , 0.0001; Fig. 2I].

Moreover, combined self-entropy (bit) at both synapses
significantly increased within 1 min after the training[F(6, 318) = 15.511, P , 0.0001; Fig. 3I].
Presynaptic glutamate and GABA release
To analyze presynaptic plasticity, we examined thepaired-pulse ratio after the training. At the excitatory
synapses in the apical dendrite, the paired-pulse ratio forevoked EPSCs was significantly increased at 60 min after
training, suggesting a delayed decrease in presynaptic
glutamate release probability [Fig. 4A, B; F(4, 172) = 2.588; P= 0.0386, 1-way factorial ANOVA]. At the excitatory synapses in the basal dendrite, the paired-pulse ratio forevoked EPSCs was significantly decreased at 5 min after
the training, suggesting a transient increase in presynaptic
glutamate release probability [Fig. 4C; F(4, 163) = 3.994; P =0.0041, 1-way factorial ANOVA]. Conversely, at the inhibitory synapses in the apical dendrite, the paired-pulse
ratio for evoked IPSCs was significantly decreased at 30
min after the training, suggesting a transient increase in thepresynaptic GABA release probability [Fig. 4E; F(4, 164) =2.818; P = 0.0269, 1-way factorial ANOVA]. At the inhibitory synapses in the basal dendrite, the paired-pulse
ratio for evoked IPSCs was significantly increased at 0, 5,
and 60 min after the training, suggesting a rapid decreasein the presynaptic GABA release probability within 1 minafter training [Fig. 4D, F; F(4, 158) = 4.389; P = 0.0022, 1-way
factorial ANOVA].

Self-entropy of mEPSC and mIPSC frequency

Phosphorylation of GABAA receptor subunits

For mEPSC and mIPSC frequency, we found the distribution of appearance probability in untrained controls(Fig. 3B, left), and then we analyzed the appearance
probability of all recorded neurons one by one. We foundcell-specific self-entropy in all recorded neurons, showing
different self-entropy from each other (Fig. 3C, upper
panels).
Two-dimensional kernel analysis visualized the density(Fig. 3C, lower panels). IA training diversified the amountof information per neuron and sustained. For the mEPSC
frequency, the results are statistically summarized in Fig.
3G. Self-entropy in the mEPSC frequency exhibited a significant temporal change [F(6, 318) = 3.694; P = 0.0015]. Post
hoc analysis further showed a significant effect from 5, 10,20, and 60 min after the training compared with untrained
control. In contrast, self-entropy in the mIPSC frequency
increased quite rapidly [F(6, 318) = 20.938; P , 0.0001; Fig.
3H], showing a long horizontal kernel distribution at 0 and
5 min after the training (Fig. 3C, lower). Significant effectwas observed at 0, 5, and 20 min after the training.

To analyze phosphorylation of the receptors using Western blot, we trimmed dorsal hippocampal CA1 tissue andextracted the whole-cell fractions (Fig. 5A). GABAA receptor b3 subunit levels were significantly increased at 30
min after the training [Fig. 5B; F(4, 40) = 10.237; P = 0.0001, 1way factorial ANOVA]. Moreover, Ser4082409 phosphorylation of the b3 subunit was significantly increased within
1 min after the training [Fig. 5C; F(4, 40) = 3.117; P = 0.0253, 1way factorial ANOVA].
DISCUSSION
Rapid plasticity at excitatory synapses
Although rapid plasticity of excitatory CA1 synapses is
considered as an initial step of memory encoding rather
than retrieval (42), conclusive evidence for the dynamicchange of synaptic current is still lacking. Here we found a
rapid increase in mEPSC amplitude within 5 min after IA

untrained and trained rats (lower). D, E ) Mean frequency of mEPSCs (D) or mIPSCs (E ) in all recorded neurons in untrained
and trained rats. IA training increased mEPSC frequency within 5 min, whereas it increased mIPSC frequency within 1 min after
the training (0 min). F ) E/I balance of the mEPSC and mIPSC frequency transiently decreased from 0 to 5 min after the training.
G, H ) The training also increased the self-entropy (bit) of excitatory (G) and inhibitory (H ) synapses in CA1 neurons. I )Combined self-entropy (bit) of the mEPSC and mIPSC frequencies in untrained and trained rats. The number of cells in eachgroup is shown at the bottom of each bar. Error bars indicate + SEM. *P , 0.05, **P , 0.01 vs. untrained. ▼ or : indicate thetiming of training or retrieval tests.
CHANGES IN SYNAPTIC DIVERSITY AFTER TRAINING

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Figure 4. Presynaptic glutamate and GABA release probability. A) Representative traces of AMPA receptor–mediated pairedpulse responses at apical dendrites of CA1. B, C ) Mean ratio at the apical (B) or basal dendrites (C ) in untrained and trained rats.
D) Representative traces of GABAA receptor–mediated paired-pulse response at basal dendrites of CA1. E, F ) Mean ratio at theapical (E ) or basal dendrites (F ) in untrained and trained rats. Vertical bars = 20 pA; horizontal bars = 50 ms. *P , 0.05, **P ,0.01 vs. untrained. The number of neurons is shown at the bottom of each bar. Error bars indicate 6 SEM. ▼ and : indicate thetiming of training and retrieval tests, respectively.

training, showing that memory encoding rather than retrieval strengthens AMPA receptor–mediated excitatory
synapses. Using fluctuation analysis of CA1 pyramidal
neurons, we recently confirmed that the training increased
postsynaptic number of AMPA receptor channels withoutchanging cation current per single channel (36). As to thecausal relationship between learning and the plasticity, we
previously reported the bilateral gene expression of
GluA1-containing AMPA receptor delivery blockers in the

CA1 neurons impairs IA learning (6). Moreover, achromophore-assisted light-inactivation technique demonstrated that optical inactivation of synaptic AMPA receptors can erase acquired memory (43). These results
showed that newly delivered GluA1-containing AMPA
receptors contribute to form contextual memory.
Paired-pulse analysis further revealed the presynaptic
glutamate plasticity after the training. The decrease in thepaired-pulse ratio at 5 min after the training suggests
transient increase in presynaptic glutamate release within
5 min after the training. Because mEPSC frequency is used
as an indicator for evoked release (44–46) or the number offunctional synapses (47, 48), both pre- and postplasticity
may contribute to the increase in mEPSC frequency at 5
min after the training. Although the immobilization of
postsynaptic AMPA receptors can also decrease thepaired-pulse ratio (49), bilateral CA1 microinjections of the
AMPA receptor blocker (CNQX) seem to impair the IA
learning immediately (0–5 min) but not at 30–60 min after
the training (29, 30, 32). Optogenetic approach is a powerful technique to investigate spine-specific presynaptic
plasticity after contextual learning; glutamate-releaseprobability at the synapses between CA3-engram andCA1-engram cells was significantly greater than that ofother pair types of synapses (50). These findings together
with the present results support the notion that contextual
learning requires the presynaptic acute glutamate releasesoon after the training.

Figure 5. Rapid Ser4082409 phosphorylation of GABAA receptor
b3 subunit. A) Whole-cell fractions of dissected dorsal CA1
were analyzed. Molecular masses of standards are indicated on
the right. B) Total GABAA receptor b3 subunit was normalized
to total b-tubulin, showing an increase in the subunit 30 min
after the training. C) The phosphorylation-speciﬁc signals of
Ser4082409 were normalized to the total GABAA receptor b3
subunit. IA training increased Ser4082409 phosphorylation
within 1 min after the training (0 min). *P , 0.05, **P ,0.01 vs. untrained; n = 9 in all groups. Error bars indicate 6
SEM. ▼ indicates the timing of training.

Rapid plasticity at inhibitory synapses

8Vol. 33

December 2019

Conversely, the plasticity at inhibitory synapses seems to
be task dependent and region specific (12, 13, 16). As tohippocampal-dependent contextual learning, IA training
clearly increased the mIPSC amplitudes, suggesting a
postsynaptic strengthening of GABAA receptor–mediatedplasticity (12). Also, the mIPSC frequency was rapidly
increased without increase in GABA release probability, suggesting rapid activation of inhibitory silent or

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SAKIMOTO ET AL.

m www.fasebj.org by Yamaguchi Univ Medical Lib (133.62.64.210) on November 06, 2019. The FASEB Journal Vol. ${article.issue.getVolume()}, No. ${article.issue.getIssueNumber()}subthreshold synapses to increase the number ofover-threshold synapses. It is possible that many mIPSC
events are small and below the level of detection threshold(,10 pA) and increased postsynaptic responses may increase the amplitude of these small events above the levelof detection (.10 pA), resulting in an apparent increase in
mIPSC frequency. Although the mechanism at GABAergic synapses is still unclear, it was well-described regarding the postsynaptic function of GluA3 containing
AMPA receptors in the hippocampal CA1 (51). Moreover,
we further found a rapid increase in mIPSC amplitude
immediately after the training, indicating that the memory encoding rather than the retrieval strengthens the
GABAA receptor–mediated inhibitory synapses. This is
the first report showing a rapid phosphorylation of theSer4082409 GABAA receptor b3 subunit within 1 min after
the training, the sites of which are necessary to attenuate
clathrin-dependent endocytosis of the synaptic receptors
increasing both amplitude and frequency of mIPSCs incultured neurons (52).
A possible causal relationship between the GABAergic
plasticity and learning has been previously reported. Not
only the genetic deficiency of GABAA receptor b3 subunit
but also the prevention of GABAA receptor–mediatedplasticity in CA1 impairs the contextual learning (12, 22).
Optogenetic manipulation of CA1 neurons further
proved the timing-specific causal relationship between
the GABAergic inputs and the learning; optic inactivationof dendrite-targeting CA1 interneurons during aversive
stimuli was sufficient to prevent fear learning (17). In apreliminary study, we found that microinjections of aninterference peptide in Ser4082409 phosphorylation into
the CA1 successfully blocked the training-induced strengthening of mIPSCs. Moreover, bilateral microinjections of thepeptide resulted in a drastic decrease in IA task-learning
performance, suggesting further causal relationship between
the learning and the Ser4082409 phosphorylation of the
GABAA b3 subunit.
Questions arise as to how the training can increase
GABAA receptor–mediated currents so rapidly. Mobilityof GABAA receptors may be closely associated with theissue, because the removal from the postsynaptic membrane or lateral diffusion decreases the synaptic GABAergic current (53–55). Recent single-particle tracking analysis
further demonstrated quick diffusion of a single GABAA
receptor (0.07 mm2/s) in cultured hippocampal neurons; it
can move rapidly between the 2 different synapses within a
few hundred milliseconds to a few seconds. Surprisingly,
abundant GABAA receptors heterosynaptically locate at
glutamatergic synapses, playing a key role in the stimulusdependent rapid changes in the postsynaptic number ofreceptors (56). Because single CA1 pyramidal neuron
possesses around 30,000 excitatory and 1700 inhibitory
synapses (57), learning may rapidly recruit the heterosynaptic GABAA receptors to strengthen the inhibitory
synapses.
Once the receptor reaches the postsynaptic region
through lateral diffusion (53, 54), gephyrin seems to stabilize the synaptic receptors (23, 58). Gephyrin can bindmajor subunits of GABAA receptors (a1–3 and b2–3) (59),and the prevention decreases mIPSC amplitudes (60).
CHANGES IN SYNAPTIC DIVERSITY AFTER TRAINING

Because the phosphorylation of Ser4082409 GABAA receptor b3 subunit is known to prevent clathrin adaptor
protein 2–mediated GABAA receptor internalization, thetraining-induced Ser4082409 phosphorylation may help tostabilize the surface receptors (61–63). Although thetraining-induced Ser4082409 phosphorylation is rapid andtransient, gephyrin may contribute to sustaining large
mIPSC amplitude. Finally, using fluctuation analysis of
CA1 pyramidal neurons, we recently confirmed that thetraining increased the postsynaptic number of GABAA
receptor channels without changing Cl2 current per single
channel (36).
Overall significance of temporal dynamics
An early-phase long-term potentiation (,1 h) is thought toarise from rapid changes in the functional status of preexisting synapses, which may include conversion of synapses from silent state to an active one (47) and increase in
the release probability of presynaptic vesicles (45, 46).
Because the training did not increase the release probability except some time points (Fig. 4; glutamate at 5 min
and GABA at 30 min), it may increase the number offunctional synapses drastically. Considering the peaklevels of mEPSC and mIPSC frequency, the number ofover-threshold synapses (.10 pA) may increase up to 2–4
times greater than the pretraining levels and then decreased gradually (excitatory synapses, Fig. 3D; inhibitory
synapse, Fig. 3E).
Temporal dynamics of mEPSCs and mIPSCs further
revealed a time lag of synaptic plasticity. IA training rapidly increased both mIPSC amplitude and frequency
within 1 min, whereas the training enhanced both mEPSC
amplitude and frequency within 5 min. Moreover, the time
lag transiently reduced E/I balance of the mEPSC andmIPSC frequency but returned to the pretraining levelwithin 10 min (Fig. 3F). The quicker plasticity at inhibitory
synapses may contribute to reduce seizure vulnerabilityon the remodeling of hippocampal networks (64).
The E/I imbalance may be caused by training-induced
spike bursts of CA1 neurons, because optogeneticallyinduced spike burst reduces E/I balance in CA1 pyramidal neurons (65). Then, concomitant calcium influx may
induce the specific phosphorylation of GluA1 and GABAA
receptor b3 subunits. Abundant extrasynaptic membrane
GABAA receptors of CA1 pyramidal neurons (66) and therapid motility (53) may enable rapid activation of GABAA
receptor–mediated synapses. In contrast, it is known totake at least 5 min for long-term potentiation induction,
because GluA1-containing AMPA receptors are inserted
at the plasma membrane and move laterally to the excitatory synapses (67, 68).
Quantification of diversity
Shannon’s information theory was applied to the recent
studies on learning and memory (69, 70). Although theinduction of long-term potentiation expands synaptic information storage capacity in hippocampal dentate gyrus
neurons in vivo (70), it is still unknown whether the9m www.fasebj.org by Yamaguchi Univ Medical Lib (133.62.64.210) on November 06, 2019. The FASEB Journal Vol. ${article.issue.getVolume()}, No. ${article.issue.getIssueNumber()}

learning affects the information content of CA1 neurons.
Here, we calculated the self-entropy of each CA1 neuron toquantify the learning-induced synaptic diversity. Each
CA1 neuron had a different self-entropy that was clearly
increased after the training (Figs. 2C and 3C). Because bilateral blockade of the synaptic diversity clearly impaired
the learning performance (12, 71), we hypothesized thatthe increased self-entropy may code a piece of experienced information after training. Considering the total
number of pyramidal neurons in rat dorsal CA1 (72),the self-entropy in untrained condition (5.2 3 106 bit)would increase up to 42.1 3 106 bits at 10 min after the
training. In any case, the analysis may be a useful approach to quantify the learning-induced synaptic diversity at the entropy level.
Temporal dynamics and cognitive disorders
Synaptic dysfunction is well-correlated with cognitive
decline in Alzheimer’s disease (73). Amyloid b peptide
1–42 (Ab42) is well-known as a major causative agent(74–77), and long-term exposure to Ab42 (1–3 d) impairs
the AMPA receptor trafficking by reducing synaptic distribution of Ca2+ and calmodulin–dependent protein kinase II in cultured pyramidal neurons (78). In contrast, theeffect of soluble oligomeric assemblies of Ab42 is more
rapid, decreasing surface level of AMPA receptors within
30 min (79). Although less is known about the toxic effect at
inhibitory synapses, Ab42 specifically binds to nicotinic a7
receptors (80), impairing the learning-induced plasticity at
the GABAA receptor–mediated inhibitory synapses (12,81). Bath application of Ab42 weakens GABAA receptor–
mediated synaptic currents within 10 min (82), whereas it
directly blocks the nicotinic a7 receptor–mediated cholinergic response within 3 min (83). Understanding the dynamic changes occurring during learning-promoted
plasticity would be necessary to identify a failure point incognitive disorders.

ACKNOWLEDGMENTS
The authors thank H. Tsurutani for technical support ofWestern blot, and R. Fujimoto for helpful comments (bothfrom Yamaguchi University). This project was supported by
Grants-in-Aid for Scientiﬁc Research B (Grants 16H05129
and 19H03402 to D.M.), Scientiﬁc Research C (Grant
25460314 to Y.S. and D.M.), and Scientiﬁc Research in
Innovative Areas (Grant 26115518 to D.M.) from the the
Ministry of Education, Culture, Sports, Science, and Technology of Japan. The authors declare no conﬂicts of interest.

AUTHOR CONTRIBUTIONS
Y. Sakimoto and H. Kida performed the experiments; Y.
Sakimoto and D. Mitsushima wrote the manuscript andanalyzed data for both statistics and self-entropy; D.
Mitsushima and H. Kida developed the patch-clamp
system; D. Mitsushima designed the study and supervised
the work; and all authors reviewed the manuscript.
10Vol. 33 December 2019

REFERENCES
1. Scoville, W. B., and Milner, B. (1957) Loss of recent memory after
bilateral hippocampal lesions. J. Neurol. Neurosurg. Psychiatry 20, 11–21
2. Mitsushima, D., Takase, K., Funabashi, T., and Kimura, F. (2009)
Gonadal steroids maintain 24 h acetylcholine release in the
hippocampus: organizational and activational effects in behaving
rats. J. Neurosci. 29, 3808–3815
3. Wills, T. J., Cacucci, F., Burgess, N., and O’Keefe, J. (2010)
Development of the hippocampal cognitive map in preweanlingrats. Science 328, 1573–1576
4. Gelbard-Sagiv, H., Mukamel, R., Harel, M., Malach, R., and Fried, I.
(2008) Internally generated reactivation of single neurons in humanhippocampus during free recall. Science 322, 96–101
5. Whitlock, J. R., Heynen, A. J., Shuler, M. G., and Bear, M. F. (2006)
Learning induces long-term potentiation in the hippocampus. Science
313, 1093–1097
6. Mitsushima, D., Ishihara, K., Sano, A., Kessels, H. W., and Takahashi,
T. (2011) Contextual learning requires synaptic AMPA receptor
delivery in the hippocampus. Proc. Natl. Acad. Sci. USA 108,
12503–12508
7. Penn, A. C., Zhang, C. L., Georges, F., Royer, L., Breillat, C., Hosy, E.,
Petersen, J. D., Humeau, Y., and Choquet, D. (2017) Hippocampal
LTP and contextual learning require surface diffusion of AMPA
receptors. Nature 549, 384–388
8. Hollmann, M., and Heinemann, S. (1994) Cloned glutamate
receptors. Annu. Rev. Neurosci. 17, 31–108
9. Traynelis, S. F., Wollmuth, L. P., McBain, C. J., Menniti, F. S., Vance,
K. M., Ogden, K. K., Hansen, K. B., Yuan, H., Myers, S. J., andDingledine, R. (2010) Glutamate receptor ion channels: structure,
regulation, and function. Pharmacol. Rev. 62, 405–496
10. Ryan, T. A., Reuter, H., Wendland, B., Schweizer, F. E., Tsien, R. W.,
and Smith, S. J. (1993) The kinetics of synaptic vesicle recycling
measured at single presynaptic boutons. Neuron 11, 713–724
11. Hori, T., and Takahashi, T. (2012) Kinetics of synaptic vesicle reﬁllingwith neurotransmitter glutamate. Neuron 76, 511–517
12. Mitsushima, D., Sano, A., and Takahashi, T. (2013) A cholinergic
trigger drives learning-induced plasticity at hippocampal synapses.
Nat. Commun. 4, 2760
13. Kida, H., Tsuda, Y., Ito, N., Yamamoto, Y., Owada, Y., Kamiya, Y., andMitsushima, D. (2016) Motor training promotes both synaptic andintrinsic plasticity of layer II/III pyramidal neurons in the primary
motor cortex. Cereb. Cortex 26, 3494–3507
14. Debanne, D., Guérineau, N. C., Gähwiler, B. H., and Thompson, S. M.
(1996) Paired-pulse facilitation and depression at unitary synapses in
rat hippocampus: quantal ﬂuctuation affects subsequent release.
J. Physiol. 491, 163–176
15. Zucker, R. S., and Regehr, W. G. (2002) Short-term synaptic plasticity.
Annu. Rev. Physiol. 64, 355–405
16. Cui, Y., Costa, R. M., Murphy, G. G., Elgersma, Y., Zhu, Y., Gutmann,
D. H., Parada, L. F., Mody, I., and Silva, A. J. (2008) Neuroﬁbromin
regulation of ERK signaling modulates GABA release and learning.
Cell 135, 549–560
17. Lovett-Barron, M., Kaifosh, P., Kheirbek, M. A., Danielson, N.,
Zaremba, J. D., Reardon, T. R., Turi, G. F., Hen, R., Zemelman, B. V.,
and Losonczy, A. (2014) Dendritic inhibition in the hippocampus
supports fear learning. Science 343, 857–863
18. Avoli, M., and de Curtis, M. (2011) GABAergic synchronization in thelimbic system and its role in the generation of epileptiform activity.
Prog. Neurobiol. 95, 104–132
19. Telgkamp, P., Padgett, D. E., Ledoux, V. A., Woolley, C. S., andRaman, I. M. (2004) Maintenance of high-frequency transmission at
purkinje to cerebellar nuclear synapses by spillover from boutons withmultiple release sites. Neuron 41, 113–126
20. Pugh, J. R., and Raman, I. M. (2005) GABAA receptor kinetics in the
cerebellar nuclei: evidence for detection of transmitter from distantrelease sites. Biophys. J. 88, 1740–1754
21. Davies, C. H., Davies, S. N., and Collingridge, G. L. (1990)
Paired-pulse depression of monosynaptic GABA-mediated inhibitory postsynaptic responses in rat hippocampus. J. Physiol. 424,
513–531
22. DeLorey, T. M., Handforth, A., Anagnostaras, S. G., Homanics, G. E.,
Minassian, B. A., Asatourian, A., Fanselow, M. S., Delgado-Escueta, A.,
Ellison, G. D., and Olsen, R. W. (1998) Mice lacking the b3 subunit of
the GABAA receptor have the epilepsy phenotype and many of the
behavioral characteristics of Angelman syndrome. J. Neurosci. 18,
8505–8514

The FASEB Journal x www.fasebj.org

SAKIMOTO ET AL.

m www.fasebj.org by Yamaguchi Univ Medical Lib (133.62.64.210) on November 06, 2019. The FASEB Journal Vol. ${article.issue.getVolume()}, No. ${article.issue.getIssueNumber()}

23. Luscher, B., Fuchs, T., and Kilpatrick, C. L. (2011) GABAA receptor
trafﬁcking-mediated plasticity of inhibitory synapses. Neuron 70,
385–409
24. McDonald, B. J., and Moss, S. J. (1994) Differential phosphorylation of
intracellular domains of gamma-aminobutyric acid type A receptor
subunits by calcium/calmodulin type 2-dependent protein kinaseand cGMP-dependent protein kinase. J. Biol. Chem. 269, 18111–18117
25. McDonald, B. J., Amato, A., Connolly, C. N., Benke, D., Moss, S. J., andSmart, T. G. (1998) Adjacent phosphorylation sites on GABAA
receptor beta subunits determine regulation by cAMP-dependent
protein kinase. Nat. Neurosci. 1, 23–28
26. Brandon, N. J., Delmas, P., Kittler, J. T., McDonald, B. J., Sieghart, W.,
Brown, D. A., Smart, T. G., and Moss, S. J. (2000) GABAA receptor
phosphorylation and functional modulation in cortical neurons by aprotein kinase C-dependent pathway. J. Biol. Chem. 275, 38856–38862
27. Brandon, N. J., Jovanovic, J. N., Smart, T. G., and Moss, S. J. (2002)
Receptor for activated C kinase-1 facilitates protein kinase
C-dependent phosphorylation and functional modulation of
GABA(A) receptors with the activation of G-protein-coupled receptors. J. Neurosci. 22, 6353–6361
28. Castellano, C., and McGaugh, J. L. (1990) Effects of post-training
bicuculline and muscimol on retention: lack of state dependency.
Behav. Neural Biol. 54, 156–164
29. Jerusalinsky, D., Ferreira, M. B. C., Walz, R., Da Silva, R. C., Bianchin,M., Ruschel, A. C., Zanatta, M. S., Medina, J. H., and Izquierdo, I.
(1992) Amnesia by post-training infusion of glutamate receptor antagonists into the amygdala, hippocampus, and entorhinal cortex.
Behav. Neural Biol. 58, 76–80
30. Bonini, J. S., Rodrigues, L., Kerr, D. S., Bevilaqua, L. R., Cammarota,M., and Izquierdo, I. (2003) AMPA/kainate and group-I metabotropic receptor antagonists infused into different brain areas impair
memory formation of inhibitory avoidance in rats. Behav. Pharmacol.
14, 161–166
31. Luft, T., Pereira, G. S., Cammarota, M., and Izquierdo, I. (2004)
Different time course for the memory facilitating effect of bicuculline
in hippocampus, entorhinal cortex, and posterior parietal cortex ofrats. Neurobiol. Learn. Mem. 82, 52–56
32. Izquierdo, I., Bevilaqua, L. R. M., Rossato, J. I., Bonini, J. S., Medina,J. H., and Cammarota, M. (2006) Different molecular cascades indifferent sites of the brain control memory consolidation. Trends
Neurosci. 29, 496–505
33. Kim, D. H., Kim, J. M., Park, S. J., Cai, M., Liu, X., Lee, S., Shin,
C. Y., and Ryu, J. H. (2012) GABA(A) receptor blockade enhances
memory consolidation by increasing hippocampal BDNF levels.
Neuropsychopharmacology 37, 422–433
34. Kida, H., Sakimoto, Y., and Mitsushima, D. (2017) Slice patch clamp
technique for analyzing learning-induced plasticity. J. Vis. Exp. 129,e55876
35. Paxinos, G., and Watson, C. (2007) The Rat Brain in Stereotaxic
Coordinates, 6th ed., Academic Press, San Diego, CA, USA
36. Sakimoto, Y., Mizuno, J., Kida, H., Kamiya, Y., Ono, Y., andMitsushima, D. (2019) Learning promotes subﬁeld-speciﬁc synaptic diversity in hippocampal CA1 neurons. Cereb. Cortex 29,
2183–2195
37. Silverman, B. W. (1986) Density Estimation for Statistics and Data
Analysis. Monographs on Statistics and Applied Probability, Chapman andHall, London
38. Sheather, S. J. (2004) Density estimation. Stat. Sci. 19, 588–597
39. Shannon, C. E. (1948) A mathematical theory of communication. Bell
Syst. Tech. J. 27, 379–423
40. Mitsushima, D., Hei, D. L., and Terasawa, E. (1994) g-Aminobutyricacid is an inhibitory neurotransmitter restricting the release ofluteinizing hormone-releasing hormone before the onset of puberty.
Proc. Natl. Acad. Sci. USA 91, 395–399
41. Pinheiro, P. S., and Mulle, C. (2008) Presynaptic glutamate receptors:
physiological functions and mechanisms of action. Nat. Rev. Neurosci.
9, 423–436
42. Morris, R. (2006) Theory of hippocampal function. In The
Hippocampus Book (Andersen, P., Morris, R., Amaral, R. D., Bliss, T.,
and O’Keefe, J., eds), pp. 581–714, Oxford University Press, New York43. Takemoto, K., Iwanari, H., Tada, H., Suyama, K., Sano, A., Nagai, T.,
Hamakubo, T., and Takahashi, T. (2017) Optical inactivation ofsynaptic AMPA receptors erases fear memory. Nat. Biotechnol. 35,
38–47
44. Prange, O., and Murphy, T. H. (1999) Correlation of miniaturesynaptic activity and evoked release probability in cultures of corticalneurons. J. Neurosci. 19, 6427–6438

CHANGES IN SYNAPTIC DIVERSITY AFTER TRAINING

45. Liao, D., Scannevin, R. H., and Huganir, R. (2001) Activation of silent
synapses by rapid activity-dependent synaptic recruitment of AMPA
receptors. J. Neurosci. 21, 6008–6017
46. Bolshakov, V. Y., Golan, H., Kandel, E. R., and Siegelbaum, S. A.
(1997) Recruitment of new sites of synaptic transmission during thecAMP-dependent late phase of LTP at CA3-CA1 synapses in the hippocampus. Neuron 19, 635–651
47. Isaac, J. T., Nicoll, R. A., and Malenka, R. C. (1995) Evidence for silent
synapses: implications for the expression of LTP. Neuron 15, 427–434
48. Wierenga, C. J., Ibata, K., and Turrigiano, G. G. (2005) Postsynaptic
expression of homeostatic plasticity at neocortical synapses. J. Neurosci.
25, 2895–2905
49. Heine, M., Groc, L., Frischknecht, R., Béı̈que, J. C., Lounis, B.,
Rumbaugh, G., Huganir, R. L., Cognet, L., and Choquet, D. (2008)
Surface mobility of postsynaptic AMPARs tunes synaptic transmission.
Science 320, 201–205
50. Choi, J. H., Sim, S. E., Kim, J. I., Choi, D. I., Oh, J., Ye, S., Lee, J., Kim, T.,
Ko, H. G., Lim, C. S., and Kaang, B. K. (2018) Interregional synaptic
maps among engram cells underlie memory formation. Science 360,
430–435
51. Renner, M. C., Albers, E. H., Gutierrez-Castellanos, N., Reinders,N. R., van Huijstee, A. N., Xiong, H., Lodder, T. R., and Kessels, H. W.
(2017) Synaptic plasticity through activation of GluA3-containing
AMPA-receptors. eLife 6, e25462
52. Kittler, J. T., Chen, G., Honing, S., Bogdanov, Y., McAinsh, K.,
Arancibia-Carcamo, I. L., Jovanovic, J. N., Pangalos, M. N., Haucke, V.,
Yan, Z., and Moss, S. J. (2005) Phospho-dependent binding of theclathrin AP2 adaptor complex to GABAA receptors regulates the efﬁcacy of inhibitory synaptic transmission. Proc. Natl. Acad. Sci. USA 102,
14871–14876
53. Thomas, P., Mortensen, M., Hosie, A. M., and Smart, T. G. (2005)
Dynamic mobility of functional GABAA receptors at inhibitory
synapses. Nat. Neurosci. 8, 889–897
54. Bogdanov, Y., Michels, G., Armstrong-Gold, C., Haydon, P. G.,
Lindstrom, J., Pangalos, M., and Moss, S. J. (2006) Synaptic GABAA
receptors are directly recruited from their extrasynaptic counterparts.
EMBO J. 25, 4381–4389
55. Mele, M., Leal, G., and Duarte, C. B. (2016) Role of GABAAR
trafﬁcking in the plasticity of inhibitory synapses. J. Neurochem. 139,
997–1018
56. De Luca, E., Ravasenga, T., Petrini, E. M., Polenghi, A., Nieus, T.,
Guazzi, S., and Barberis, A. (2017) Inter-synaptic lateral diffusion of
GABAA receptors shapes inhibitory synaptic currents. Neuron 95,
63–69.e5
57. Megı́as, M., Emri, Z., Freund, T. F., and Gulyás, A. I. (2001) Total
number and distribution of inhibitory and excitatory synapses on
hippocampal CA1 pyramidal cells. Neuroscience 102, 527–540
58. Tretter, V., Mukherjee, J., Maric, H. M., Schindelin, H., Sieghart, W.,
and Moss, S. J. (2012) Gephyrin, the enigmatic organizer at
GABAergic synapses. Front. Cell. Neurosci. 6, 23
59. Kowalczyk, S., Winkelmann, A., Smolinsky, B., Förstera, B., Neundorf,
I., Schwarz, G., and Meier, J. C. (2013) Direct binding of GABAA
receptor b2 and b3 subunits to gephyrin. Eur. J. Neurosci. 37, 544–554
60. Mukherjee, J., Kretschmannova, K., Gouzer, G., Maric, H. M.,
Ramsden, S., Tretter, V., Harvey, K., Davies, P. A., Triller, A.,
Schindelin, H., and Moss, S. J. (2011) The residence time of GABA(A)Rs at inhibitory synapses is determined by direct binding of thereceptor a1 subunit to gephyrin. J. Neurosci. 31, 14677–14687
61. Jovanovic, J. N., Thomas, P., Kittler, J. T., Smart, T. G., and Moss, S. J.
(2004) Brain-derived neurotrophic factor modulates fast synaptic
inhibition by regulating GABA(A) receptor phosphorylation, activity,and cell-surface stability. J. Neurosci. 24, 522–530
62. Lu, H., Cheng, P. L., Lim, B. K., Khoshnevisrad, N., and Poo, M. M.
(2010) Elevated BDNF after cocaine withdrawal facilitates LTP in
medial prefrontal cortex by suppressing GABA inhibition. Neuron 67,
821–833
63. Petrini, E. M., and Barberis, A. (2014) Diffusion dynamics of synaptic
molecules during inhibitory postsynaptic plasticity. Front. Cell.
Neurosci. 8, 300
64. Staley, K. (2015) Molecular mechanisms of epilepsy. Nat. Neurosci. 18,
367–372
65. Mendez, P., Stefanelli, T., Flores, C. E., Muller, D., and Lüscher, C.
(2018) Homeostatic plasticity in the hippocampus facilitates memory
extinction. Cell Rep. 22, 1451–1461
66. Brickley, S. G., and Mody, I. (2012) Extrasynaptic GABA(A) receptors:
their function in the CNS and implications for disease. Neuron 73,
23–34

11

m www.fasebj.org by Yamaguchi Univ Medical Lib (133.62.64.210) on November 06, 2019. The FASEB Journal Vol. ${article.issue.getVolume()}, No. ${article.issue.getIssueNumber()}

67. Jaafari, N., Henley, J. M., and Hanley, J. G. (2012) PICK1 mediates
transient synaptic expression of GluA2-lacking AMPA receptors during glycine-induced AMPA receptor trafﬁcking. J. Neurosci. 32,
11618–11630
68. Ren, S. Q., Yan, J. Z., Zhang, X. Y., Bu, Y. F., Pan, W. W., Yao, W., Tian,
T., and Lu, W. (2013) PKCl is critical in AMPA receptor
phosphorylation and synaptic incorporation during LTP. EMBO J.
32, 1365–1380
69. Martı́nez-Bellver, S., Cervera-Ferri, A., Luque-Garcı́a, A., Martı́nez-Ricós,J., Valverde-Navarro, A., Bataller, M., Guerrero, J., and Teruel-Marti, V.
(2017) Causal relationships between neurons of the nucleus incertus
and the hippocampal theta activity in the rat. J. Physiol. 595, 1775–1792
70. Bromer, C., Bartol, T. M., Bowden, J. B., Hubbard, D. D., Hanka, D. C.,
Gonzalez, P. V., Kuwajima, M., Mendenhall, J. M., Parker, P. H.,
Abraham, W. C., Sejnowski, T. J., and Harris, K. M. (2018) Long-term
potentiation expands information content of hippocampal dentate
gyrus synapses. Proc. Natl. Acad. Sci. USA 115, E2410–E2418
71. Ono, K., and Mitsushima, D. (2017). Learning creates diversity of
excitatory and inhibitory synapses in the hippocampal CA1: a possibleamount of information at a single synapse. J. Physiol. Sci. 67 (Suppl 1),
S124.
72. Bezaire, M. J., and Soltesz, I. (2013) Quantitative assessment of CA1
local circuits: knowledge base for interneuron-pyramidal cell connectivity. Hippocampus 23, 751–785
73. Terry, R. D., Masliah, E., Salmon, D. P., Butters, N., DeTeresa, R., Hill,
R., Hansen, L. A., and Katzman, R. (1991) Physical basis of cognitive
alterations in Alzheimer’s disease: synapse loss is the major correlateof cognitive impairment. Ann. Neurol. 30, 572–580
74. Shankar, G. M., Li, S., Mehta, T. H., Garcia-Munoz, A., Shepardson,
N. E., Smith, I., Brett, F. M., Farrell, M. A., Rowan, M. J., Lemere, C. A.,
Regan, C. M., Walsh, D. M., Sabatini, B. L., and Selkoe, D. J. (2008)
Amyloid-beta protein dimers isolated directly from Alzheimer’s
brains impair synaptic plasticity and memory. Nat. Med. 14, 837–842
75. Querfurth, H. W., and LaFerla, F. M. (2010) Alzheimer’s disease. N.
Engl. J. Med. 362, 329–344

12Vol. 33 December 201976. Penzes, P., Cahill, M. E., Jones, K. A., VanLeeuwen, J. E., and Woolfrey,
K. M. (2011) Dendritic spine pathology in neuropsychiatric disorders.
Nat. Neurosci. 14, 285–293
77. Sevigny, J., Chiao, P., Bussière, T., Weinreb, P. H., Williams, L., Maier,M., Dunstan, R., Salloway, S., Chen, T., Ling, Y., O’Gorman, J., Qian,
F., Arastu, M., Li, M., Chollate, S., Brennan, M. S., Quintero-Monzon,O., Scannevin, R. H., Arnold, H. M., Engber, T., Rhodes, K., Ferrero,J., Hang, Y., Mikulskis, A., Grimm, J., Hock, C., Nitsch, R. M., andSandrock, A. (2016) The antibody aducanumab reduces Ab plaquesin Alzheimer’s disease. Nature 537, 50–56
78. Gu, Z., Liu, W., and Yan, Z. (2009) b-Amyloid impairs AMPA receptor
trafﬁcking and function by reducing Ca2+/calmodulin-dependent
protein kinase II synaptic distribution. J. Biol. Chem. 284, 10639–10649
79. Zhao, W. Q., Santini, F., Breese, R., Ross, D., Zhang, X. D., Stone, D. J.,
Ferrer, M., Townsend, M., Wolfe, A. L., Seager, M. A., Kinney, G. G.,
Shughrue, P. J., and Ray, W. J. (2010) Inhibition of calcineurin-mediatedendocytosis and alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionicacid (AMPA) receptors prevents amyloid beta oligomer-induced synaptic disruption. J. Biol. Chem. 285, 7619–7632
80. Wang, H. Y., Lee, D. H., D’Andrea, M. R., Peterson, P. A., Shank, R. P.,
and Reitz, A. B. (2000) b-Amyloid1-42 binds to a7 nicotinic acetylcholine
receptor with high afﬁnity. Implications for Alzheimer’s disease
pathology. J. Biol. Chem. 275, 5626–5632
81. Townsend, M., Whyment, A., Walczak, J. S., Jeggo, R., van den Top,
M., Flood, D. G., Leventhal, L., Patzke, H., and Koenig, G. (2016) a7nAChR agonist enhances neural plasticity in the hippocampus via a
GABAergic circuit. J. Neurophysiol. 116, 2663–2675
82. Ulrich, D. (2015) Amyloid-b impairs synaptic inhibition via GABA(A)receptor endocytosis. J. Neurosci. 35, 9205–9210
83. Liu, Q., Kawai, H., and Berg, D. K. (2001) b-Amyloid peptide blocks
the response of a 7-containing nicotinic receptors on hippocampal
neurons. Proc. Natl. Acad. Sci. USA 98, 4734–4739

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Received for publication September 7, 2018.
Accepted for publication September 23, 2019.

SAKIMOTO ET AL.

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