Serotonin modulates fast-spiking interneuron and synchronous activity in the rat prefrontal cortex through 5-HT1A and 5-HT2A receptors

Abstract

Alterations of the serotonergic system in the prefrontal cortex (PFC) are implicated in psychiatric disorders such as schizophrenia and depression. Although abnormal synchronous activity is observed in the PFC of these patients, little is known about the role of serotonin (5-HT) in cortical synchrony. We found that 5-HT, released by electrical stimulation of the dorsal raphe nucleus (DRN) in anesthetized rats, regulates the frequency and the amplitude of slow (<2 Hz) waves in the PFC via 5-HT(2A) receptors (5-HT(2A)Rs). 5-HT also modulates prefrontal gamma (30-80 Hz) rhythms through both 5-HT(1A)Rs and 5-HT(2A)Rs, but not 5-HT(2C)Rs, inducing an overall decrease in the amplitude of gamma oscillations. Because fast-spiking interneurons (FSi) are involved in the generation of gamma waves, we examined serotonergic modulation of FSi activity in vivo. Most FSi are inhibited by serotonin through 5-HT(1A)Rs, while a minority is activated by 5-HT(2A)Rs, and not 5-HT(2C)Rs. In situ hybridization histochemistry confirmed that distinct populations of FSi in the PFC express 5-HT(1A)Rs and 5-HT(2A)Rs, and that the number of FSi expressing 5-HT(2C)Rs is negligible. We conclude that 5-HT exerts a potent control on slow and gamma oscillations in the PFC. On the one hand, it shapes the frequency and amplitude of slow waves through 5-HT(2A)Rs. On the other hand, it finely tunes the amplitude of gamma oscillations through 5-HT(2A)R- and 5-HT(1A)R-expressing FSi, although it primarily downregulates gamma waves via the latter population. These results may provide insight into impaired serotonergic control of network activity in psychiatric illnesses such as schizophrenia and depression.

Figure 1.

Low-frequency stimulation of the DRN (1 Hz) increases the frequency and reduces the amplitude of cortical slow waves. A, LFP trace and corresponding spectrogram of 15 min of recording. Note that during the stimulations slow waves decrease in amplitude and increase in frequency toward the frequency of stimulation (white line in spectrogram). The spectrogram is raw PSD smoothed with a Gaussian filter. Vertical bar: 0.5 mV. DES, Desynchronization epoch (or wake-like state). SWS, Slow-wave sleep epoch (or SWS-like state). Red is maximum and blue is minimum signal in all figures. B, Top, Detail of 10 s of LFP signal during SWS-like (box 1 in A) and DRN stimulation segments (box 2 in A; vertical lines correspond to times of stimulation). Power spectra for 1 min segments that contain the 10 s traces in boxes 1 and 2 are shown on the far right. Bottom, LFPs were processed off-line for an accurate measure of UP-state duration. Briefly, the 20–100 Hz component of the LFP was digitally extracted and the SD of 10 ms sliding windows computed. Histograms of processed LFPs displayed two peaks corresponding to UP and DOWN potentials (far right). A threshold was set (red line) to discriminate UP states (Mukovski et al., 2007). Note the increase in UP-state potentials during the stimulations (arrow). C, D, The peaks of the power spectra and the percentage of time the LFPs spent in UP states were significantly increased during DRN stimulations at 1 mA (n = 21 rats), indicating an increase in the frequency of slow waves. Augmenting the intensity of the stimulations up to 2 mA reliably imposed a frequency of 1 Hz (C, right). These effects were not observed in negative control rats (NC; n = 7), even increasing the intensity of the stimulations up to 2 mA. **p < 0.01, ***p < 0.001. Data are mean ± SD. E, Effects of DRN simulation on the baseline power of slow waves (comparison of 30 s epochs before and during stimulations). Each dot depicts one experiment. Only one experiment was performed per animal.

Figure 2.

High-frequency stimulation of the DRN (100 Hz) strongly desynchronizes cortical slow waves and reduces gamma power. A, Stimulations of the DRN at 100 Hz (400 μA for 0.5 s) decrease the power of both slow and gamma oscillations in the LFP signal (comparison of 10 s epochs before and after the stimulations; n = 7 rats). B, The stimulation rapidly eliminates slow waves for several seconds in both the LFP and ECoG signals (top). Time–frequency analysis of the LFP reveals the disappearance of the slow-wave band and a reduction of the power of gamma waves (bottom). Spectrograms are normalized PSDs (in decibels), smoothed with a Gaussian filter. The red rectangle depicts the time of the stimulation and contains the stimulus artifacts in all the signals. Vertical bars are 0.5 mV.

Figure 3.

Modulation of slow oscillations by 5-HT_2ARs. A, Scatter plots of the effects of WAY-100635 (WAY), ritanserin (RIT), and SB-242084 (SB) on the power of slow oscillations (comparison of 30 s epochs before and after drug injection). Arrows point to the examples shown in B and C. B, Examples of the effects of WAY, RIT, and SB on the power of slow waves by time–frequency analysis (normalized PSDs in decibels), and corresponding quantification of the power. Vertical arrows point to the start of the injections. RIT markedly decreases the power of slow waves. Since SB does not alter slow-wave power, the effects of RIT are likely mediated by 5-HT_2ARs. C, Representative 10 s traces of the LFPs from the examples shown in B. Analysis of UP and DOWN cycles reveals that RIT reduces the number, duration, and amplitude of DOWN states, markedly augmenting UP-state potentials. This leads to a desynchronization of slow waves. Proces. LFP, LFP processed as in Figure 1B. Red line indicates the calculated threshold between UP and DOWN states.

Figure 4.

Distinct modulation of cortical gamma oscillations by 5-HT_1AR and 5-HT_2AR antagonists. A, Scatter plots of the effects of WAY, RIT, and SB on the power of gamma oscillations (comparison of 30 s epochs before and after drug injections). Arrows point to the examples shown in B. WAY increased, RIT decreased, and SB did not alter the power of gamma oscillations. B, Examples of the effects of WAY, RIT, and SB on the power of gamma waves by time–frequency analysis (normalized PSDs in decibels), and corresponding quantification of the power. Vertical arrows point to the start of the injections.

Figure 5.

Opposite modulation of FSi activity in vivo through 5-HT_1ARs and 5-HT_2ARs. A, B, Top, DRN stimulation (1 Hz) delivered during UP states induced transient inactivations in many FSi recorded (left), while a subset of FSi were activated (right). Vertical bar is 0.5 mV. Bottom, Raster plots and corresponding peristimulus histograms of the units shown above. Inhibitions were mediated by 5-HT_1ARs and activations by 5-HT_2A/2CRs. Zero is time of DRN stimulation. Peristimulus histograms were built during baseline (black lines under raster plots) and after the administration of WAY or RIT (gray lines). Lines are 5 min epochs. Vertical arrows point to the start of the injections. Small vertical arrows point to stimulus artifacts. Both units were confirmed to be PV positive. C, Raster plot and peristimulus histogram of a FSi activated by DRN stimulation during baseline (black line), and after the administration of SB (gray line). SB failed to reverse the activation (up to 2 mg/kg), suggesting that it was 5-HT_2AR-mediated. Lines are 3 min epochs. Inset, Note the presence of a short-delay short-duration excitation (light gray arrows) with variable latencies. This cell was one of the few FSi recorded in the medial PFC (see Materials and Methods). Because the medial PFC projects densely to the DRN, this response may be due to feedforward inputs from cortico-raphe pyramidal neurons activated antidromically from the DRN (Puig et al., 2008). Alternatively, a glutamatergic response induced by 5-HT/glutamate corelease from serotonergic terminals should also be considered (Varga et al., 2009). This unit was confirmed to be PV positive.

Figure 6.

Effects of 5-HT_1AR and 5-HT_2A/2CR antagonists on FSi activity and synchronization to gamma waves. A, Scatter plot of firing rates before and after injection of WAY (filled circles) and RIT (crosses). Firing rates were measured from UP states detected in 1 min segments. B, Examples of the effects of WAY and RIT on the coupling of two distinct FSi to gamma waves. Shown are firing probability distributions around gamma troughs before and after drug injection. Two gamma cycles are shown for clarity. Top, WAY did not change the preferred firing phase (Φ; marked with an arrowhead), but increased the depth of the modulation (r), “sharpening” the distribution. Bottom, RIT uncoupled this unit to gamma waves (p > 0.05). p values are from the Rayleigh Test. Bin = 20°. C, Scatter plot of the depth of modulation to gamma waves before and after the administration of WAY (filled circles) or RIT (crosses). RIT uncoupled 2 of the 3 units tested, for which a depth of modulation could not be computed.

Figure 7.

Expression of 5-HT_1AR, 5-HT_2AR, and 5-HT_2CR mRNAs in PV-positive neurons. A–C, Colocalization of the FSi marker parvalbumin (PV) with 5-HT_1AR (A), 5-HT_2AR (B), and 5-HT_2CR (C) mRNAs by double ISH (MOs, n = 3 rats each). Note a higher background on the latter ISH, consequence of a weak expression of the signal. D, Colocalization of 5-HT_2CR mRNAs with the pyramidal neuron marker VGluT1. Examples of double-labeled neurons are marked with white arrows. Scale bars are 20 μm.