# Modulation of Network Oscillatory Activity and GABAergic Synaptic Transmission by CB1 Cannabinoid Receptors in the Rat Medial Entorhinal Cortex

Authors: Nicola H. Morgan; Ian M. Stanford; Gavin L. Woodhall
Journal: Neural Plasticity
 (2008)

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## Abstract

Cannabinoids modulate inhibitory GABAergic neurotransmission in many brain regions. Within the temporal lobe, cannabinoid receptors are highly expressed, and are located presynaptically at inhibitory terminals. Here, we have explored the role of type-1 cannabinoid receptors (CB1Rs) at the level of inhibitory synaptic currents and field-recorded network oscillations. We report that arachidonylcyclopropylamide (ACPA; 10μM), an agonist at CB1R, inhibits GABAergic synaptic transmission onto both superficial and deep medial entorhinal (mEC) neurones, but this has little effect on network oscillations in beta/gamma frequency bands. By contrast, the CB1R antagonist/inverse agonist LY320135 (500 nM), increased GABAergic synaptic activity and beta/gamma oscillatory activity in superficial mEC, was suppressed, whilst that in deep mEC was enhanced. These data indicate that cannabinoid-mediated effects on inhibitory synaptic activity may be constitutively active in vitro, and that modulation of CB1R activation using inverse agonists unmasks complex effects of CBR function on network activity.


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## Body

## 1. Introduction

Cannabinoid  receptors are a
family of G-protein coupled, presynaptic receptors [1, 2]. Autoradiography
studies using the cannabinoid receptor ligand CP55,940 [3–5] show that CB1Rs are
distributed throughout neuronal tissue. These studies report a dense binding of
CP55,940 in the basal ganglia, specifically the substantia nigra pars reticulata the globus pallidus (GP)
and also in cerebellum. In the cerebrum, the hippocampal formation and the entorhinal
cortex (EC) show the highest density of staining for CB1R.Cannabinoids
are known to exert powerful control over GABAergic inhibitory signalling in the
CNS [6–8], and it is reported that
CB1R inhibition of GABAA receptor mediated synaptic transmission
occurs through the inhibition of voltage-dependent calcium channels (VGCCs; [6]). In the hippocampus, the activation of
presynaptic CB1R depresses GABA release onto postsynaptic target cells [9, 10], and in these studies, endogenous
and exogenous CB1R agonists have been shown to reduce the amplitude and
frequency of GABAergic spontaneous inhibitory postsynaptic currents (sIPSCs),
but not to affect action-potential-independent miniature (m)IPSCs. Other
studies have shown that cannabinoid receptor activation enhances network
oscillatory activity [11]. However, in the parahippocampal region (PHR), the effects of cannabinoid
receptors are less well described. Here, we have investigated the functional
effects of CBRs on neuronal network activity modelled in vitro by kainate (KA-) induced persistent oscillations [8, 12]. Persistent oscillatory
activity in the gamma frequency band (30–80 Hz) has been the most commonly
reported and studied form of network activity in the in vitro slice preparation, and can be elicited by metabotropic
glutamate receptors [13] or application of kainic acid
[8, 12] and/or the muscarinic
agonist carbachol  Neuronal network oscillatory activity reflects the phasic inhibition of principal cells by GABAergic interneurones, which act to entrain and
synchronize principal cell activity (Cobb et al., [14]).  The mEC has been reported to express gamma oscillations (30–100 Hz) in response to application of nanomolar concentrations of kainate
[15, 16], and oscillatory
power was greatest in superficial layers II/III [15].


## 2. Materials and Methods

Combined EC-hippocampal slices were prepared from young male
Wistar rats (50–110 g) as previously described [17]. All experiments were performed in accordance with the UK Animals
(Scientific Procedures) Act 1986 and European Communities Council Directive
1986 (86/609/EEC). Rats were anaesthetised with isoflurane and N2/O2,
until cardiorespiratory arrest, and decapitated. The brain was rapidly removed
and immersed in oxygenated artificial cerebrospinal fluid (ACSF) chilled to 4°C. Slices (450μm) were cut using a vibrating microtome (MicroM,
Germany), and stored in ACSF continuously bubbled with 95% O2/5% CO2,
at room temperature. Following a recovery period of at least 1 hour, individual
slices were transferred to a recording chamber mounted on the stage of an
Olympus (BX50WI) upright microscope. The chamber was continuously perfused with
oxygenated ACSF at 30–32°C, at a flow rate of approximately 2 mL/min. The ACSF
contained the following (in mM): NaCl (126), KCl (3.25), NaH2PO4 (1.25), NaHCO3 (24), MgSO4 (2), CaCl2 (2.5),
and D-glucose (10). The solution was continuously bubbled with 95% O2/5%
CO2 to maintain a pH of 7.4. Neurones were visualized using differential
interference contrast optics and an infrared video camera.Patch-clamp electrodes
were pulled from borosilicate glass (1.2 mm OD, 0.69 ID; Harvard Apparatus) and
had open tip resistances of 4-5 MΩ. They were filled with a solution containing
the following (in mM): CsCl (90), HEPES (33), QX-314 (5), EGTA (0.6), MgCl2 (5.0),
TEA-Cl (10), phosophocreatine (7) ATP (4), GTP (0.4). The solution was adjusted
to 290 mOsmol with sucrose and to pH 7.4 with CsOH.
Whole-cell voltage clamp recordings were made from neurones in layers II and V
of the medial division of the EC, using an Axopatch 700 series amplifier
(Molecular Devices, USA).
The holding potential in all cases was –70 mV. Under
these experimental conditions, layer II/V neurones exhibited sIPSCs, mediated
by GABA acting primarily at GABAA receptors.Data were recorded
directly to computer hard disk using AxoScope software (Molecular Devices, USA). Mini Analysis (Synaptosoft, USA) was used
for analysis of sIPSCs offline. sIPSCs were detected automatically using a
threshold-crossing algorithm, and their frequency and amplitude are analysed.
200 sIPSCs were sampled during a continuous recording period for each neurone
under each condition. The nonparametric Kolmogorov-Smirnoff (KS) test was used
to assess the significance of shifts in cumulative probability distributions of
interevent interval (IEI). Differences between drug and control situations in
studies of sIPSCs were assessed by means of a one-way ANOVA. All error values
stated in the text refer to the S.E.M.All salts
used in preparation of ACSF were Analar grade and purchased from Merck/BDH (UK). LY320135 and ACPA were obtained from Tocris Cookson
(UK).For field
recordings of oscillatory activity, slices were placed into an interface chamber
(BRSC-1, Digitimer, UK) and the chamber was
continuously perfused with oxygenated ACSF at 30–32°C, at a flow rate of
approximately 1-2 mL/min. Extracellular
population recordings were made with glass microelectrodes filled with aCSF, of
resistance 1–3 MΩ.  Signals were amplified 1000-fold and recorded
unfiltered. Low amplitude 50 Hz interference was removed using a HumBug (Quest Scientific, Canada). Signals were digitized and recorded at 10 kHz using an NPI EXT-02F amplifier (NPI, Germany)
and pClamp 10 software (Molecular Devices, USA). Following 30–90 minutes control period of stable
oscillatory activity, drugs were applied to the bath in known concentration.  Pharmacological oscillatory activity was
analysed using the fast Fourier transform (FFT, Clampfit 10), cross-correlation
analysis and Morlet-wavelet time-frequency spectrogram analysis (MatLab 2007R,
Mathworks). Student t-tests were carried out to determine statistical
significance.We analysed oscillations at beta
(15–29 Hz) and gamma (30–90 Hz) bands, using bandpass filters (Clampfit 10.1)
and measurement of the area under the power spectrum curve in Sigmaplot 8.0.


## 3. Results

Whilst
recording from layers II and V of the mEC, we applied the CBR agonist
arachidonylcyclopropylamide (ACPA) at 10μM, onto slices from which stable gamma
activity had been induced by 300–400 nM kainate. As Figure 1(a) shows, KA-induced gamma oscillations in layer II were
broadly similar to those reported by Cunningham et al. [15]. Hence, mean area power in the γ-band was 561  ±  179μV2 and mean control
gamma frequency was 40.7±2.4 Hz. Following 40–60 minutes bath application of ACPA, we applied the
CB1R-specific inverse agonist LY320135 (500 nM; [18]). Figure 1(b) shows the power spectral density of activity bandpass filtered between 2–100 Hz, and Figure 1(c) shows similar data
filtered at gamma frequency (30–90 Hz). As Figure 1(c) shows, there was a tendency towards an increase in gamma power in ACPA in some
recordings, but this was not significant overall (P  ≥  .19, n  =  9). In pooled data, ACPA did
significantly reduce mean peak gamma frequency to 35.6±1.8 Hz (P  ≤  .04, n  =  9), although this
effect was variable, and some recordings showed multiple peaks.Figure 1
The effects of ACPA and LY320135 onγ-band activity in mEC layer
II. (a) Example traces from layer II showing γ-oscillations
under conditions in which ACPA (10μM) or LY320135 (500 nM) were
applied. (b) Plot of power spectral density during drug
application (filtered between 2–100 Hz). Control (black line), ACPA
(red line), LY320135 (blue line). (c) Similar plot to
(b) bandpass filtered between 30–90 Hz. Scale bar  =  200
milliseconds  ×  100μV.Following perfusion of the CB1R-specific
inverse agonist LY320135, there was a marked reduction in normalised gamma
power to39.4±10.1% of control, and this was highly significant (P  ≤  .0006, n  =  9). In addition, mean peak
frequency returned to 41.2±1.8 Hz (P  ≤  .04,
n  =  9).When
beta power in layer II was measured, we noted a similar pattern of drug
responses to that observed for gamma activity. Mean area power
in the beta band was lower than that of gamma activity at 26  ±  6μV2 and mean peak beta
frequency in control conditions was 25.6±1.4 Hz. Figure 2(a) shows the power spectral density of activity bandpass
filtered between 2–100 Hz, and Figure 2(c) shows similar data filtered at beta frequency (15–29 Hz). As Figure 2(c) shows, there was no significant
change in beta power in ACPA (81.4  ±  15% of control, P  ≥  .14, n  =  9),
and ACPA had no significant effect on mean peak beta frequency (27.6±1.43 Hz, P  ≥  .25, n  =  9). However, when we added the CB1R-specific inverse
agonist LY320135, there was a reduction in normalised beta power to 57  ±  13%
of control, and this was highly significant (P  ≤  .008, n  =  9). LY320135 had no effect on mean peak frequency (27.9±0.52 Hz, P  ≥  .4, n  =  9).Figure 2
The effects of ACPA and LY320135 onβ-band activity in mEC layer II. (a) Example traces from layer II
showing β-oscillations under conditions in which ACPA (10μM) or
LY320135 (500 nM) were applied. (b) Plot of power
spectral density during drug application (filtered between 2–100 Hz). Control (black line), ACPA (red line), LY320135 (blue line).
(c) Similar plot to (b) bandpass filtered
between 15–29 Hz. Scale bar  =  200 milliseconds  ×  50μV.During the above experiments, we
simultaneously recorded oscillatory activity in deep entorhinal cortex (layer
V). Oscillatory activity in layer V was lower in power in layer V compared to
layer II, with mean area gamma power just 60  ±  10μV2 and mean peak frequency
was similar to layer II at 39.19±3.1 Hz.When we applied ACPA whilst recording in layer V we observed a
significant increase in mean  gamma power (Figure3(a)),
by 38.1±13.4% of control (P  ≤  .03, n  =  9), however, baseline gamma power was very
low in this layer, and the absolute change in gamma power was difficult to
discern. Peak frequency was again slightly reduced to 36.0±2.4 Hz, but
this was not significant (P  ≥  .31, n  =  9). On subsequent addition
of the CB1R-specific inverse
agonist LY320135, there was a strong increase in normalised gamma power to
108.4  ±  58% of control, and this reached significance (P  =  .049,
n  =  9). Again, LY320135 did not significantly alter mean
peak gamma frequency (35.7±2.41 Hz in LY320135, P  ≥  .45, n  =  9).Figure 3
The effects of ACPA and LY320135 onγ-band activity in mEC layer V.
(a) Example traces from layer V showing γ-oscillations under conditions in
which ACPA (10μM) or LY320135 (500 nM) was applied. (b)
Plot of power spectral density during drug application (filtered
between 2–100 Hz). Control (black line), ACPA (red line), or
LY320135 (blue line). (c) Similar plot to
(b) bandpass filtered between 30–90 Hz. Scale bar = 200
milliseconds × 50μV.When beta power in layer V was analysed,
we noted a similar pattern of drug responses to that observed for gamma
activity. Mean area power in the beta band was lower than that of
gamma activity at9.6±0.6μV2 and mean control beta frequency was 27.9±0.52 Hz. Figure 4(a) shows field oscillations recorded in layer V before drug
application and during ACPA and LY320135 periods. Figure 4(b) shows the power spectral density of activity bandpass
filtered between 2–100 Hz, and Figure 4(c) shows similar data filtered at beta frequency (15–29 Hz). As Figure 4(c) shows, there was a slight
tendency towards an increase in beta power (by 27  ±  14%) in ACPA in some
recordings, but this was not significant overall (P  ≥  .06,
n  =  9). ACPA had no significant effect on mean peak beta frequency (28.4±0.7 Hz, P  ≥  .5, n  =  9). When we next
applied the inverse agonist LY320135, we noted an increase in normalised beta
power by 142.4  ±  88% of control, and this just failed to reach significance (P  ≤  .07, n  =  9). LY320135 (26.3±1.5 Hz, P  ≥  .3, n  =  9) had no effect on peak frequency.Figure 4
The effects of ACPA and LY320135 onβ-band activity in mEC layer V.
(a) Example traces from layer V showing β-oscillations under conditions in
which ACPA (10μM) or LY320135 (500 nM) were applied. (b)
Plot of power spectral density during drug application (filtered
between 2–100 Hz). Control (black line), ACPA (red line), LY320135
(blue line). (c) Similar plot to (b)
bandpass filtered between 15–29 Hz. Scale bar = 200 milliseconds ×
50μV.We
hypothesised that the lack of effects of ACPA in layer II might reflect
constitutive or tonic activation of CBR, perhaps due to persistent
kainate-induced activation of pyramidal neurones. To test this hypothesis, we applied
LY320135 in the absence of ACPA. Application of LY320135 suppressed gamma band activity to 19.5  ±  11% of control, and this was highly significant (P  ≤  .01, n  =  5). When beta activity was measured, it
was apparent that in LY320135, there was a significant reduction in mean
normalised beta power (58.4  ±  12% of control; P  ≤  .04, n  =  5).The data presented up to this point
indicated that, in general, gamma and beta power decreased in layer II in
response to blockade or inverse agonism of CB1R, and that in layer V, the
opposite was seen, with an increase in gamma and beta power.
Figures5(a)-5(b) shows summary bar charts indicating the effects of ACPA and LY320135 on normalised mean area power in
the gamma and beta bands in layers II and V of the mEC.Summary of the effects of
cannabinoid ligands on oscillatory activity in mEC. (a) Bar charts
showing the effects of cannabinoid ligands in layer II on normalised
area power atγ and β frequencies. (b) Bar charts
showing the effects of inverse agonists alone in layer V on
normalised area power at γ and β frequencies.
(a)(b)We hypothesised
that the alterations in oscillatory power seen during drug application would
relate to the effects of ACPA and LY320135 on sIPSCs impinging on neurones in
deep and superficial entorhinal cortex. To measure these effects, we performed
whole-cell voltage clamp recordings of sIPSCs, whilst bath applying ACPA and
LY320135 at concentrations similar to those used above.


## 4. ACPA and Ly320135 Have Subtle Effects on sIPSC Amplitude and Frequency in mEC Layer II

Figure6(a) shows typical
recordings of inward sIPSCs made from a layer II pyramidal neurone. As Figure 6(b) shows, the application of ACPA
(10μM) had subtle
effects on sIPSCs in layer II, decreasing their frequency without affecting mean
amplitude. Cumulative probability plots for sIPSC amplitude in the presence of
ACPA (Figure 6(c)) indicated a shift in
amplitude distribution, and mean amplitude showed a slight increase from 101.7±3.2 pA in
control to 108.3±3.4 pA in ACPA, but this was nonsignificant (P  ≥  .168, ANOVA). When we analysed amplitude distribution using the
nonparametric Kolmogorov-Smirnov test, the shift towards higher amplitude
sIPSCs was just significant (P  ≤  .021 KS test). In the case of interevent interval
(IEI; the reciprocal of frequency), we noted a shift to the right in the
cumulative probability plot (Figure 6(d)),
indicating an increase in the likelihood of greater IEI values (reduced
frequency). Mean median IEI
increased from 34.6±5.5 milliseconds in control to 47.6±9.7 milliseconds in
ACPA (P  ≤  .0001, ANOVA, n  =  5), and the
increase in IEI time distribution towards higher values was highly significant (P  ≤  .006, KS test).
When we performed similar experiments using LY320135 (500 nM), we noted effects
which tended towards the opposite of those seen with ACPA, that is, increased
sIPSC amplitude and frequency. Figure 7(a) shows a typical recording of inward sIPSCs made from a layer-II pyramidal
neurone. As Figure 7(b) shows, the
application of LY320135 increased sIPSC frequency and amplitude. Mean amplitude
increased from 51.7±3.6 pA in control to   69.0±5.9 pA in LY320135, and this was
significant (P  ≤  .013, ANOVA, n  =  6). Similarly, the
shift in distribution towards larger amplitudes was highly significant (P  ≤  .002, KS test). The mean median IEI
showed a slight decrease from 86.6±15.8 milliseconds in control to 80.6±16.1 milliseconds LY320135, but this decrease in IEI time was not significant (P  ≥  .116, ANOVA, n  =  6).The effects of ACPA on sIPSCs in
mEC layer II.
(a) Recording from a layer II neurone under
control conditions and (b) in the presence of ACPA
(10μM). (c) Cumulative probability plot for sIPSC
amplitude under control (black) and ACPA (red) conditions.
(d) Cumulative probability plot for sIPSC IEI under
control (black) and ACPA (red) conditions. Scale bars 500
millisconds  ×  100 pA.
(a)(b)(c)(d)The effects of LY320135 on sIPSCs
in mEC layer II. (a) Recording from a layer II neurone
under control conditions and (b) in the presence of
LY320135 (500 nM). (c) Cumulative probability plot for
sIPSC amplitude under control (black) and LY320135 (red) conditions.
(d) Cumulative probability plot for sIPSC IEI under
control (black) and LY320135 (red) conditions. Scale bars 500
milliseconds  ×  250 pA.
(a)(b)(c)(d)The
cumulative probability plots for sIPSC amplitude (Figure7(c)) and IEI (Figure 7(d))
in the presence of LY320135 indicate the shifts in distribution of these
parameters in the presence of LY320135.


## 5. ACPA and LY320135 Have Marked Effects on sIPSC Amplitude and Frequency in mEC Layer V

In contrast to the effects observed
in layer II and layer V we noted a significant reduction in sIPSC frequency in
response to ACPA application.  As Figure8(a) shows, sIPSCs in layer V are
considerably less frequent than those in layer II (see Woodhall et al., [17]). When ACPA was applied, sIPSC
frequency was greatly attenuated (Figure 8(b)),
but there was no overall shift
in amplitude distribution (confirmed by a nonsignificant KS test (P  ≥  .23)). Mean amplitude rose slightly from
59.41±7.33 pA in control to 70.49±8.89 pA in ACPA, but this increase was not
significant (P  ≥  .33, ANOVA, n  =  6). When
we analysed IEI, the change in distribution towards larger IEI values was significant
(P  ≤  .0001 KS test), and mean median IEI was found
to increase very significantly from 792  ±  41 milliseconds in control to 1317  ±  75 milliseconds in ACPA (P  ≤  .0001, ANOVA, n  =  6). This effect of ACPA on IEI
in layer V was consistent in all recordings. Cumulative
probability plots for sIPSC amplitude (Figure 8(c))
and IEI (Figure 8(d)) illustrate the
effects of ACPA on sIPSC amplitude and IEI.The effects of ACPA on sIPSCs in
mEC layer V.
(a) Recording from a layer V neurone under
control conditions and (b) in the presence of ACPA
(500 nM). (c) Cumulative probability plot for sIPSC
amplitude under control (black) and ACPA (red) conditions.
(d) Cumulative probability plot for sIPSC IEI under
control (black) and ACPA (red) conditions. Scale bars 2000
milliseconds× 250 pA.
(a)(b)(c)(d)When we performed similar
experiments using LY320135 (500 nM), we again noted robust effects, which opposed
those seen with ACPA, that is, increased sIPSC amplitude and frequency. Figure9(a) shows a typical recording of
inward sIPSCs made from a layer-II pyramidal neurone. As Figure 9(b) shows, the application of LY320135 had marked effects on
sIPSCs in layer V, increasing their frequency and amplitude. Mean sIPSC
amplitude in layer V increased from 47.0 pA  ±  3.0 to 87.9 pA  ±  7.4 pA in
LY320135, and this increase was significant (P  ≤  .001, ANOVA
n  =  7). Cumulative probability plots for sIPSC amplitude in the presence of LY320135
(Figure 9(c)) show the shift in amplitude
distribution, and this was confirmed statistically (P  ≤  .0004, KS test). In the case of IEI, we noted
a shift to the left in the cumulative probability plot (Figure 9(d)), indicating an increase in the likelihood of lower IEI values
(increased frequency). During LY320135 application the mean median IEI
decreased from 477.1±108.0 milliseconds in control to 300.0±71.5 milliseconds
in LY320135 showing that an overall increase in sIPSC frequency has occurred.
The decrease in mean median IEI between control and LY320135 periods was
significant (P  ≤  .014
ANOVA, n  =  7), as was the change in distribution (P  ≤  .016, KS test).The effects of LY320135 on sIPSCs
in mEC layer V.
(a) Recording from a layer V neurone under
control conditions and (b) in the presence of LY320135
(500 nM). (c) Cumulative probability plot for sIPSC
amplitude under control (black) and LY320135 (red) conditions.
(d) Cumulative probability plot for sIPSC IEI under
control (black) and LY320135 (red) conditions. Scale bars 2000
milliseconds×  250 pA.
(a)(b)(c)(d)


## 6. Discussion

We
found that the cannabinoid receptor agonist ACPA had little effect on either
oscillatory activity or synaptic inhibition in superficial layers of the mEC,
and that effects in deep layers were more robust, especially in the case of
sIPSC frequency. However, the inverse agonist, LY320135, strongly suppressed
oscillatory activity in superficial mEC even while its effects on sIPSC
frequency and amplitude were not great. We also observed that suppression of
oscillatory activity in layer II by LY3201235 was accompanied by augmentation
of oscillatory power in layer V, and that the suppression of sIPSCs by ACPA and
subsequent enhancement by LY320135 in this layer were marked.We
have reported previously [17] that spontaneous inhibition is much greater in superficial layer
II of mEC than in deep layer V. In addition, more than 90% of IPSCs in layer II
are action-potential (AP) independent, whereas in layer V, AP-dependent events
comprise a much greater (>50%) proportion of sIPSCs. Given that CBRs act
only on Ca2+ dependent release of GABA and have no effect on mIPSCs
([8];  it seems likely that cannabinoid ligands would show greater
effects in the deep layers, where activity is low at baseline, and probably
more sensitive to modulation since it is more likely to be AP-dependent.Since,
compared to layer II, both ACPA and
LY320135 had more profound effects on synaptic inhibition in layer V, it seems
likely that the relative dominance of mIPSCs in layer II may mask CB1R effects
on the minority of AP-dependent sIPSCs to some degree. The lack of a robust
effect of ACPA on oscillatory activity in layer V suggests, however, that CB1R
may already be activated by ongoing network activity, and that further attempts
at activation using an agonist did not increase any effect that CB1R might have
on oscillatory power. This appears to be supported by the effects of the
inverse agonist LY320135 in layer II. Here, we observed a robust reduction in
both beta and gamma power in layer II, suggesting that CB1R do contribute to
maintaining oscillatory activity in this layer. The apparently contradictory
result of enhanced oscillatory activity in layer V in response to LY320125 may
relate to effects that are secondary to activity in layer II, for example, Bragin [11], working in vivo, noted that ablation of superficial EC causes augmented
oscillatory activity in CA3-CA1, and it may be that a similar mechanism allows
suppression of oscillations in layer II to unmask activity in layer V, which
receives inputs from CA1. Similarly, previous reports [15] indicate that superficial
layers (especially layer III) show the strongest gamma power, perhaps
suggesting a role in driving oscillatory activity in other layers. However,
layer V is not driven directly by layers II or III [19], and hence any effect in layer V may well be
indirect.Cannabinoid
receptors exert powerful control over GABA release from presynaptic terminals,
with CB1 receptors having been shown to suppress both IPSPs and IPSCs in
pyramidal neurones (IPSPs, [20]; IPSCs, [8]). Endocannabinoids, such as 2-arachidonyl glycerol and
anandamide also suppress inhibition in CNS (see [21], for review). Cannabinoids are also believed to
mediate the phenomenon of depolarisation-induced suppression of inhibition
(DSI; [22–24]). Recently, studies have suggested
that CB1R are present at terminals from specific subsets of inhibitory
interneurones. For example, fast spiking (FS) inhibitory neurones in neocortex
express parvalbumin (PV) but not CB1R, and by contrast, irregular spiking (IS)
neurones express CB1R but not PV [25, 26].
Recently, Galaretta et al. [27]
have demonstrated that synapses between IS neurones and pyramidal cells express
CB1R and show DSI, whereas synapses between FS neurones and
pyramidal cells show neither CB1R nor DSI. FS cells are thought to
pace fast oscillatory network rhythms such as gamma activity ([28]; and IS cells are thought to possess properties that
predispose towards nonrhythmic activity [25, 29]. A subset of neurones that express CB1R but not PV expresses cholecystokinin
(CCK), and these neurones have been suggested to act, through DSI, to
differentiate subgroups of pyramidal cells into neuronal assemblies which are
then entrained by FS cells (“sparse coding” in place cell assemblies,
[30]). In this
scenario, pyramidal cell activation leads to endocannabinoid synthesis and
release, which inhibits IS-cell inputs to the somata and proximal dendrites of
active cells, but allows IS-cell-mediated inhibition to remain intact (and
ongoing) at less active pyramids. This effect, in turn, allows FS-cells to
entrain oscillatory activity only at the disinhibited population of pyramidal
cells, effectively selecting that subset for rhythmic activity.It
seems possible that PV−/CCK+/CB1R+ inhibitory interneurones might similarly select
populations of pyramidal cells involved in rhythmogenesis in the mEC, which
contains both PV+ and PV− neurones [31, 32] and CCK+ interneurones [33], which also express CB1R [34]. We used a selective cannabinoid
receptor inverse agonist to globally inhibit CB1Rs during persistent gamma and
beta band oscillations in brain slices from the mEC. Under conditions in which
CB1 were subject to blockade or inverse agonist effects, we observed a decrease
in oscillatory power in gamma and beta bands in layer II. This is consistent
with the literature described above [27, 30] and we propose that, in layer II, blockade or inverse agonism of
CBRs results in increased irregular phasic inhibition from IS-cells onto
pyramidal cells, decreasing the population available to participate in network
oscillations and hence reducing field oscillatory power. This appears to be
supported by our voltage-clamp recordings showing that LY320135 increased
phasic GABAergic inhibition at principal cells in layer II.When
we measured oscillatory activity in layer V, inverse agonists at CBRincreased gamma and beta power and this
appeared to be correlated with decreased superficial beta and gamma power. At
first, this appears paradoxical, however, oscillatory activity in specific
laminae does not exist in isolation, and we might expect interactions between,
as well as within, networks of neurones. Bragin et al. [11] have demonstrated that, in vivo, bilateral ablation of the EC suppresses gamma activity
in the dentate gyrus (DG), but augments gamma oscillations in CA3-CA1. As
previously discussed, superficial mEC projects to DG, and CA1 projects to deep mEC
layers. Given that in our experiments, oscillatory activity in superficial mEC
was suppressed, it is reasonable to suggest that this may depress gamma and/or
beta activity in DG and enhance such activity in CA3-CA1. This, in turn, would
feed through to layer V, where increased gamma and beta power is seen. Hence,
although phasic inhibition in layer V appeared to increase in LY320135, it may
be that this effect is not involved in selection of neuronal assemblies for
oscillatory activity in layer V; rather, excitatory inputs to this area from hippocampus
may be the dominant influence on pyramidal cell activity.



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*Source: 808564-2008-12-01.xml*