Animals

Adult male mice (>10 weeks of age at the start of experiments) of the C57BL/6J strain (Stock No. 000664, Jackson Laboratory) were used. To selectively image or manipulate SST interneurons, we utilized adult male SST-IRES-Cre62 on a mixed C57BL/6 × 129S4/SvJae background (Stock No. 013044, Jackson Laboratory). Mice were group housed (3–5 mice per cage) on a 12:12-h light/dark cycle with free access to food and water. We typically performed experiments during the light cycle. Sample sizes for this study are selected based on numbers generally employed in the field. All experimental procedures were approved by the Institutional Animal Care and Use Committee at Yale University.

Surgery

For all stereotaxic surgical procedures, the mouse was first anesthetized with isoflurane in oxygen (3–4% during induction, 1–1.5% for the remainder of the surgery) while placed in a stereotaxic apparatus (David Kopf Instruments). The animal lay on top of a water-circulating pad (Gaymar Stryker) set at a constant temperature of 38 °C. Eyes were lubricated with ophthalmic ointment. Carprofen (5 mg/kg, s.c.; 024751, Henry Schein Animal Health) and dexamethasone (3 mg/kg, i.m.; 002459, Henry Schein Animal Health) was used pre-operatively. The skin above the skull was then sterilized by swabs of ethanol and betadine before an incision was made to expose the skull. We made a craniotomy (small or large depending on the experiment as detailed below) using a dental drill. Immediately after surgery and on each day for the following 3 days, carprofen (5 mg/kg, s.c.) was given to the animal. All animals had at least 1 week to recover before starting experiments unless stated otherwise.

For imaging, we made a small skin incision and craniotomy (~0.5 mm diameter) in the right hemisphere centered at 1.5 mm anterior of bregma (anterior-posterior, AP) and 0.3 mm lateral of midline (medial-lateral, ML) to target the medial prefrontal cortex (Cg1 and M2 sub-regions)63. A glass pipette (3–000–203-G/X, Drummond Scientific) was pulled to a fine tip (P-97 Flaming/Brown Micropipette Puller, Sutter Instrument), front-filled with the relevant viruses (see below) and then slowly lowered into the brain using the stereotaxic apparatus at 4 sites corresponding to vertices of a 0.2-mm wide square centered at the above coordinates. At depth of 0.3 to 0.5 mm below the dura, we ejected the virus using a microinjector (Nanoject II, Drummond Scientific). To target the retrosplenial cortex (RSC) and primary motor cortex (M1), we used the same approach centering at AP = −1.4 mm/ML = 0.3 mm, and AP = 1.8 mm/ML = 1.6 mm, respectively. We injected 9.2 or 18.2 nl per injection pulse, with ~30 s in between each injection pulse. To reduce backflow of the virus, we waited at least 5 min after finishing injection at one site before retracting the pipette to move on to the next site. For experiments that required more than one virus, we injected each virus sequentially. The brain was kept moist with artificial cerebrospinal fluid (ACSF, in mM: 5 KCl, 5 HEPES, 135 NaCl, 1 MgCl2, 1.8 CaCl2; pH 7.3). After completing all injections, the craniotomy was covered with silicone elastomer (0318, Smooth-On, Inc.), and the skin sutured (Henry Schein). After ~3 weeks, the animal underwent a second surgery for cranial window implant. After the initial steps as outlined above, an incision was made to remove all of the skin above the skull, which was cleaned to remove connective tissues. We made a 3-mm diameter craniotomy around the previously targeted location. A glass window was put together by gluing two 3-mm-diameter, #1-thickness circular glass (640720, Warner Instruments), using UV-sensitive optical adhesive (NOA61, Norland Products). The glass window was then placed on the exposed brain with slight downward pressure while applying high-viscosity adhesive (Loctite 454) around the perimeter of the glass window. After the adhesive cured, a custom-made stainless steel headplate (eMachineShop.com) was affixed to the skull using quick adhesive cement (C&B Metabond, Parkell).

For behavior, we followed the surgical procedures for imaging, with the following exceptions. There was no second surgery for cranial window and head plate implant. All injections were bilateral injections, in which we used one of the coordinates above, plus the mirrored coordinates for the other hemisphere. We injected at all the locations in one hemisphere first, before front-filling more virus (if necessary), and moving onto the other hemisphere. We waited at least 4 weeks before behavioral testing.

For local field potential recordings, we fabricated bundles of stainless steel wire electrodes (2–3 wires per bundle) (790500, A-M Systems). The diameter of an electrode was 114.3 µm and 50.8 µm with and without coating, respectively. There was ~350 µm of exposed tip for each electrode which was separated by ~250 µm from other electrodes in the bundle. Impedance was typically less than 100 kΩ when tested at 1 kHz. Following the procedures above for surgery and small craniotomy, a bundle of electrodes was each lowered into the right Cg1/M2 and right RSC, centered at the stereotaxic coordinates as described above, to a depth of 0.5 mm below the dura. We used a miniature stainless steel screw (#0000–160) placed over the right cerebellum as the reference electrode. All electrodes were then soldered to a miniature connector (A79002–001 or A79000–001, Omnetics). Care was taken to avoid shorted connections. All pieces of the implant along with a stainless steel headplate were affixed to the skull using cyanoacrylate (Loctite 454) and quick adhesive cement (C&B Metabond, Parkell). For experiments combining viral injections and electrophysiology, we first injected the virus, and then waited 3 weeks before proceeding with a second surgery for electrode implant.

For electrical stimulation, we first injected viruses using the procedures above. Three weeks later, we performed a second surgery to implant stimulating electrodes. A bundle of stainless steel wires (3–4 wires per bundle) (790500, A-M Systems) was inserted into RSC. The wire implant was soldered to a miniature connector (A79002–001 or A79000–001, Omnetics). A glass-covered cranial window was made over Cg1/M2 using procedures described above. All pieces of the microstimulation implant and a stainless steel headplate were affixed to the skull using cyanoacrylate (Loctite 454) and quick adhesive cement (C&B Metabond, Parkell).

Histology

Mice were transcardially perfused with paraformaldehyde solution (4% (v/v) in phosphate-buffered saline). The brains stayed in the fixative for at least 48 h, and then were sectioned coronally with a vibratome and mounted on slides with coverslips. We imaged the sections with an upright fluorescence microscope (Zeiss Axio Imager M2).

Viruses

To image calcium transients in pyramidal neurons and their dendrites, we injected AAV1-CamKII-GCaMP6f-WPRE-SV40 (Penn Vector Core) diluted to a titer of 2 × 1012 genome copies (GC) per milliliter. A total of 73.6 nl of virus was injected for each experiment. For interneurons, we injected AAV1-Syn-DIO-GCaMP6s-WPRE-SV40 (Penn Vector Core; 1 × 1012 GC/ml titer, 147.2 nl) in SST-IRES-Cre animals. To downregulate GluN2B expression in a cell-type-specific manner, we designed a shRNA sequence targeting mouse GluN2B (5′ TGTACCAACAGGTCTCACCTTAAACTTCAAGAGAGTTTAAGGTGAGACCTGTTGGTACTTTTTTC 3′), ligated the GluN2BshRNA sequence into a modified pSico plasmid backbone21, and packaged the plasmid into an AAV to create AAV1-CMV-dsRed-pSico-GFP-GluN2BshRNA. For behavioral experiments, a total of 966 nl was injected in Cg1/M2 of each hemisphere, as well as at additional sites around Cg1/M2 in the anterior-posterior axis. For imaging experiments, the GluN2BshRNA sequence was ligated into another pSico backbone with no GFP (Vector Biolabs; AAV1-CMV-dsRed-pSico-GluN2BshRNA, 2 × 1013 GC/ml titer). The reason for removing the GFP is to avoid interference with GCaMP6f fluorescence. A total of 552 nL was injected in Cg1/M2, and then followed by injection of AAV1-CamKII-GCaMP6f-WPRE-SV40. For electrophysiology experiments, a total of 552 nl of AAV1-CMV-dsRed-pSico-GluN2BshRNA was injected in Cg1/M2. To acutely downregulate SST interneuron activity, we injected either AAV2-Syn-DIO-hM4D(Gi)-mCherry (Penn Vector Core, 1 × 1013 GC/ml titer, 552 nl) for the hM4D(Gi) group or AAV8-Syn-DIO-mCherry (Penn Vector Core, 1 × 1013 GC/ml titer, 552 nl) for the control group in SST-IRES-Cre animals.

Cell culture validation

We used primary neuronal cell cultures to validate the viral-mediated manipulation of NMDAR expression. Briefly, cortical neurons at E18 from pregnant female rats were dissected, dissociated, and plated in wells (~1 million cells/well) and cultured in standard media64. We added viruses at DIV5 stage. For GluN2BshRNA validation, we used the viruses AAV1-CMV-Cre-GFP (1 × 1013 GC/ml titer, 400 nl) for expression of Cre and AAV1-CMV-dsRed-pSico-GluN2BshRNA (2 × 1013 GC/ml titer, 400 nl) for expression of GluN2BshRNA. Using these two viruses, we made four well conditions: GluN2BshRNA, no Cre; GluN2BshRNA, Cre; no GluN2BshRNA, Cre; no GluN2BshRNA, no Cre (no virus added) (Supplementary Fig. 6). We then performed Western blots with antibodies for GluN2B (#4207S, Cell Signaling, 1:1000, rabbit polyclonal antibody) and beta-actin (#4967S, Cell Signaling, 1:1000, rabbit polyclonal antibody). Bands were quantified using Bio-Rad Image Lab software and raw band intensity values were normalized to beta-actin levels.

Drugs

We used saline (0.9% Sodium chloride, Hospira). Ketamine working solution (1 mg/ml in saline) was prepared from stock solution (McKesson), approximately every 30 days. All ketamine and saline injections were subcutaneous (s.c.). All imaging, locomotor activity and fear conditioning experiments used 10 mg/kg. Only the PPI experiments used a higher dose of 40 mg/kg. Initial testing at 10 mg/kg in control mice did not yield reliable effects on PPI performance. We therefore used a higher dosage, following a prior study65. Clozapine N-oxide (CNO) (Sigma Millipore) working solution (1 mg/ml) was prepared fresh daily before each experiment from a stock solution dissolved in DMSO (10 mg/ml) stored at 4 °C. Vehicle (1:10 DMSO in saline) was used in control injections. All CNO and vehicle injections were intraperitoneal (i.p.).

Two-photon calcium imaging

We used a laser-scanning two-photon microscope (Movable Objective Microscope, Sutter Instrument) controlled by the ScanImage software66. A tunable Ti:Sapphire femotosecond laser (Chameleon Ultra II, Coherent) was the excitation source which was focused onto the brain using a water immersion objective (XLUMPLFLN, ×20/0.95 N.A., Olympus). The time-averaged laser power was typically less than 100 mW during experiments. Filters had the following center excitation (ex) and emission (em) wavelengths (Semrock or Chroma): GCaMP6s/f, 920 nm (ex) and 525 nm (em); dsRed, 1040 nm (ex) and 605 nm (em). Emitted photons were collected by GaAsP photomultiplier tubes. We acquired images that were 256 × 256 pixels at 0.68 or 0.54 µm per pixel resolution for dendritic spines and axonal boutons or 1.35 µm per pixel resolution for cell bodies. Frame rate was 3.62 Hz using bidirectional scanning on a set of galvanometer-based scanners. A software program (Presentation, NeuroBehavioral Systems) sent TTL pulse via a data acquisition device (USB-201, Measurement Computing) to the two-photon microscope at 30-s intervals, as well as to trigger all the other equipment. The Presentation software would log timestamps so that data from imaging and other equipment (e.g., microstimulation and body motion) can be synchronized in later analyses. Mice were habituated to head fixation under the microscope for 3–5 days of increasing durations before the commencement of any data collection. While head fixed, the mouse would sit in an acrylic tube, which permits postural adjustments but limits gross body movements. Subcutaneous injections were given through a drilled hole in the tube so as to allow the mouse to remain head fixed. To examine the acute effects of ketamine, we would image a field of view for 10–15 min to obtain ‘pre-injection’ data. The imaging was then interrupted for ketamine (10 mg/kg) or saline (10 ml/kg) injection (s.c.). At 30 min after the injection, we would verify that the same field of view was still in focus, and then obtain imaging data for another 10–15 min. Imaging 30 min after the injection ensured that we bypass the transient hyperlocomotion effects of ketamine (Fig. 1c, d). In a subset of animals, we imaged continuously for 60 min after injection, but analyzed only the data after the 30-min post-injection mark. Each subject was imaged for ketamine and saline injections, with the order counterbalanced across subjects. We imaged at 0–200 µm below dura for dendritic spines, and 200–500 µm below dura for cell bodies. We targeted the medial portion of Cg1/M2, within 0–500 µm of the midline as visualized by the dark band of the midsagittal sinus. For imaging experiments with cell-type-specific knockdown experiments, during live imaging, we searched for and imaged fields of view with many cells double-labeled with dsRed and GCaMP6s.

Analysis of calcium imaging data

We first concatenated all of the .tiff image files from the same experiment and corrected for lateral motion using either TurboReg implemented as a plugin in ImageJ or NoRMCorre67 in MATLAB. A custom graphical user interface (GUI) in MATLAB was used for the manual selection of region of interests (ROI). The rest of the analysis depended on experiment type as described below.

For dendritic spines, we manually scrolled through the imaging frames to look for ROIs that likely represented dendritic spines and dendritic shaft—neurite segments with multiple protrusions that display correlated patterns of fluorescence transients. The dendritic shaft ROIs were selected to be within 20 µm of the corresponding dendritic spine ROIs. We averaged values of pixels within a ROI to generate F ROI (t). For each ROI, we quantified the contribution of neuropil to the fluorescence signal. Specifically, we would calculate a radius, r, treating the ROI area as the area of a circle, and then creating an annulus-shaped neuropil ROI with inner and outer radii of 2r and 3r, respectively. We excluded pixels that belonged to the ROIs of other spines and shaft. To also exclude pixels that may belong to unselected dendritic structures, we calculated the time-averaged signal for each pixel, and then determined the median for all pixels within the neuropil ROI. We then excluded pixels if their time-averaged signal was higher than the median. We finally averaged across the non-excluded pixels in the neuropil ROI to generate F neuropil (t). To subtract the neuropil signal, we used the formula:

$$F\left( t \right) = F_{{\mathrm{ROI}}}\left( t \right) - cF_{{\mathrm{neuropil}}}\left( t \right)$$ (1)

where c = 0.4 is the neuropil correction factor. The fractional change in fluorescence, ΔF/F(t), for each spine and shaft was calculated as follows:

$$\frac{{{\mathrm{\Delta }}F}}{F}(t)\,=\,\frac{{F\left( t \right)\,-\,F_o(t)}}{{F_o(t)}}$$ (2)

where F 0 (t) is the 10th percentile of F(t) within a 2-min sliding window. Because we were presently interested in calcium signals due to subthreshold synaptic inputs, we regressed out fluorescence signals from non-local sources17. For each spine with ΔF/F spine (t), we computed ΔF/F synaptic (t) by subtracting out the scaled version of fluorescence transients in the corresponding dendritic shaft, ΔF/F shaft (t) , using the following equation:

$$\frac{{{\mathrm{\Delta }}F}}{F}_{{\mathrm{synaptic}}}\left( t \right) = \frac{{{\mathrm{\Delta }}F}}{F}_{{\mathrm{spine}}}\left( t \right) - \alpha \frac{{{\mathrm{\Delta }}F}}{F}_{{\mathrm{shaft}}}\left( t \right)$$ (3)

where α was determined by a linear regression forced through the origin of ΔF/F spine (t) vs. ΔF/F shaft (t).

For axonal boutons, we drew ROIs that are likely single axonal boutons—varicosities on a relatively thin neurite branch with no protrusions. This manual identification is supported by the known neuroanatomy. For SST interneurons, they send axons but very few dendrites, if any, to layer 1. For retrosplenial cortical neurons, they send long-range axons to layer 1 of Cg1/M2. To generate F ROI (t), values of pixels within an ROI were averaged. For each ROI, we would estimate the contribution of neuropil to the fluorescence signal, by calculating and subtracting F neuropil (t) to obtain F candidate_bouton (t), using the procedures described above. Some boutons may belong to the same neuron. To limit duplicates, we used a modified a published procedure68. Briefly, we first analyzed a subset of imaging experiments to identify pairs of boutons on the same branch, based on distance (within 10 µm of each other) and visual confirmation of a connecting axonal segment. From this subset of bouton pairs (n = 46 bouton pairs, 2 animals), we used their F candidate_bouton (t) values to compute a correlation coefficient for each pair. The 5th percentile value for all the correlation coefficients in this subset was 0.59, which was used as the cut-off threshold value. Then, for each axonal imaging experiment, we performed an iterative procedure to select unique boutons. In each iteration, a correlation matrix using F candidate_bouton (t) between all pairs of candidate boutons in a field of view was computed. The pair of candidate boutons with the highest correlation coefficient was identified. If the value exceeded the threshold of 0.59, we would select one out of that pair of candidate boutons randomly, and looked for other boutons whose correlation coefficient with the selected bouton exceeded the threshold of 0.59. The original identified pair and boutons from subsequent search then would form one cluster. Entries in the correlation matrix corresponding to this cluster would be excluded for subsequent iterations. The process continued again to identify another cluster until no pair of candidate boutons in the correlation matrix had value above the threshold of 0.59. At the end of the iterative procedure, each of the remaining boutons was assigned to be its own cluster. We randomly selected one bouton as the representative for each cluster. The fluorescence signals of these representative boutons, F bouton (t), were then converted to fractional changes in fluorescence, ΔF/F bouton (t), as described above and used for subsequent analyses.

For cell bodies, we selected ROIs that are likely cell bodies—fluorescent objects with a round boundary and a lateral extent of about 10 µm. Values of pixels within a ROI were averaged to generate F ROI (t). For each ROI, we would remove the contribution of neuropil to the fluorescence signal, by calculating and subtracting F neuropil (t) to obtain F soma (t), and then calculating the fractional changes in fluorescence ΔF/F soma (t), using procedures outlined in the previous sections. For experiments with cell-type-specific GluN2B manipulation, we selected only GCaMP6s-expressing cells that were co-labeled with dsRed.

After obtaining ΔF/F synaptic (t), ΔF/F bouton (t), or ΔF/F soma (t) for a ROI, we did the following analysis to detect calcium events. We employed a validated “peeling” algorithm15, which used an iterative, template-matching procedure to decompose ΔF/F(t) into a series of elementary calcium events. We used a template for an elementary calcium event with instantaneous onset, an amplitude of 0.3, and a decay time constant of 1 s for a single-exponential function. The algorithm would search for a match to this specified template in ΔF/F(t). When a match occurred, a calcium event was recorded, and the template subtracted from ΔF/F(t) (i.e., peeling). The remaining ΔF/F trace was then searched for another match, in an iterative manner until no further matches were found. The times of recorded calcium events formed the output of the algorithm. The temporal resolution of the output is limited by the imaging frame rate. There can be multiple events associated with the same event time. In the paper describing the peeling algorithm, extensive numerical simulations suggested excellent detection performance, even in worst-case scenarios with low signal-to-noise ratios and low sampling rate15. For each imaging session, we calculated calcium event rate by dividing the number of calcium events by the duration of the imaging period. For Figs. 2e, 3c, and Supplementary Fig. 1a, c, we characterized the calcium events in terms of amplitude and frequency. We identified calcium events that co-occurred in the same imaging frame (same event time), distinguishing amplitude (mean number of calcium events per frame, for frames with at least one event) from frequency (number of frames with at least one event divided by the duration of the imaging session). We imaged the same compartment (spine, bouton, or cell body) before and after injection, and therefore were able to quantify the change in calcium event rate, amplitude, and frequency for each compartment by calculating the post-injection minus pre-injection values normalized by the pre-injection value.

To determine if our results depend on the event detection procedure, we used an alternative method to quantify calcium transients in dendritic spines (Supplementary Fig. 4). We started from ΔF/F synaptic (t). For each ROI and for each condition (i.e., pre-injection or post-injection), we would calculate a threshold corresponding to 3 times the median absolute deviation of ΔF/F synaptic (t). We noted imaging frames in which ΔF/F synaptic (t) was above the threshold. From this subset of frames, we determined the mean amplitude above threshold (ΔF/F synaptic (t) minus the threshold), and the fraction of time spent above the threshold (the number of above-threshold frames divided by the number of all frames) (see Supplementary Fig. 4a for an illustration). We quantified the changes in these measures—mean amplitude above threshold and fraction of time above threshold—by calculating the post-injection minus pre-injection values normalized by the pre-injection value.

Recording animal movements during two-photon imaging

To assess the mouse’s movements during two-photon imaging (Fig. 1c, d), we illuminated the animal with infrared light and recorded videos (640 × 480 pixels, 20 Hz) of the animal’s face and body using an infrared camera (See3CAM_12CUNIR, e-con Systems). Although the animal was head-fixed, it could still move parts of its body such as the face, trunk, and limbs. To synchronize the infrared video with imaging, the infrared illuminator was triggered to turn off for 100 ms by the same TTL pulse used to trigger the two-photon microscope. During analysis, the interval between dark frames therefore indicated a duration of 30 s. We computed motion m in 1-s bins:

$$m = \frac{{\mathop {\sum }

olimits_{f = 1}^{N - 1} \mathop {\sum }

olimits_{x = 1}^X \mathop {\sum }

olimits_{y = 1}^Y |p_{x,y}\left( {f + 1} \right) - p_{x,y}\left( f \right)|}}{{N - 1}}$$ (4)

where N is the number of video frames in the 1-s bin, X and Y are the width and height of the frame, p x,y (f + 1) and p x,y (f) are values of the pixel at coordinates x and y in frames f + 1 and f, respectively.

Simultaneous electrical stimulation and imaging

Imaging in Cg1/M2 was performed as described above. For microstimulation, we injected electrical currents into the implanted stimulation electrodes in RSC, using an analog stimulus isolator (Model 2200, A-M Systems). The timing and strength of the stimulation were specified by a script written in a software program (Presentation, NeuroBehavioral Systems) via command voltages out of a multifunctional input/output device (USB-6001, National Instruments). During each experiment, to calibrate the stimulation current (which could vary due to depleting battery for the stimulus isolator or high impedance of the implanted electrode), an electronic circuit was placed in-series, allowing us to measure the stimulation current online and tune the electrical current to within 5% of the desired level. For the stimulation pattern, each pulse had a biphasic waveform, lasted 5 ms in each phase, and had peak amplitudes of ±150 µA. We used 1, 2, 4, 8, 16, 32, or 64 pulses as the stimulation levels. If more than 1 pulse was used, the pulses were applied one after the other with no inter-pulse interval. A block consisted of the 7 stimulation levels, presented in random order with a random inter-trial period of 10–14 s. For each experiment, we presented 10 blocks successively before injection of ketamine or saline, and then presented another 10 blocks successively 30–60 min after injection. Prior to the post-injection stimulation, we imaged to confirm that the field of view has not changed. Using procedures described in earlier sections, we determined ΔF/F in each dendritic spine and axonal bouton. The log files generated by the Presentation software were used to align the timestamps of the imaging data to the stimulation events. For each dendritic spine or axonal bouton, we determined the ΔF/F measured within 1 s following the onset of stimulation, and reported the averaged values across the 10 blocks.

Electrophysiology

Animals were head-fixed and placed in a Faraday cage. An interface cable was mated to the connector on the animal’s head in order to amplify local field potential (LFP) signals using a differential amplifier (RHD2216, Intan Technology), high-pass filtered at 0.5 Hz and digitized at 1 kHz (RHD2000, Intan Technology). Before actual electrophysiological recordings, mice were habituated to head-fixation for 3–5 days of increasing durations. We recorded for 30 min pre-injection, and then for 60 min post-injection. We discarded data from electrodes that were noisy (impedance >1 GΩ). One electrode from each site (Cg1/M2 or RSC) was chosen randomly for analysis. For analysis, we compared the 30-min segment recorded pre-injection to the 30-min segment recorded from 30–60 min post-injection. We focused on the integrated gamma band power, because it was previously found to correlate with hemodynamic signals underlying blood-oxygenation-level-dependent resting-state connectivity31. To determine the integrated gamma band power, spectrograms were computed from the local field potential recordings using a sliding window with duration of 2 s and step size of 0.4 s. At each window, spectral power within the gamma band from 30 to 80 Hz was summed, and this yielded the integrated gamma band power. Correlation between integrated gamma band power in Cg1/M2 and RSC was calculated based on Pearson correlation coefficient at zero lag. Coherence between integrated gamma band power in Cg1/M2 and RSC was computed using the Chronux69 package in MATLAB, and the magnitude of coherence was reported.

Behavior

Fear learning was assessed using a conditioning box utilizing an infrared video camera (320 × 240 pixels, 30 Hz; Med Associates, Inc.). To enable more flexible protocols involving multiple stimuli and repetitions, we modified the box to be controlled by a behavioral control software (Presentation, NeuroBehavioral Systems). Each of the conditioned stimuli (CS) was a 20-s long series of auditory pips (500 ms on, 500 ms off). The pip was either 2.5 kHz (85 dB, calibrated by A-weighting at 15 cm from speaker) or 11 kHz (75 dB). For delay conditioning experiments, one CS (CS+) co-terminated with the unconditioned stimulus of footshock (US; 0.65 mA, 0.5 s), and the other CS (CS−) was not associated with any event. For trace conditioning experiments, the end of CS+ and US was separated by 15 s of no stimulus. In the acquisition phase, animals were injected with either ketamine (10 mg/kg, s.c.) or saline (10 ml/kg, s.c.), returned to the home cage, and then placed in the conditioning box 15 min later. For DREADD experiments, CNO (5 mg/kg, i.p.) or vehicle (10 mg/ml, i.p.) was injected 30 min before trace fear conditioning followed by ketamine or saline 15 min before commencement of conditioning. After 6 min of habituation, conditioning started during which 5 CS− and 5 CS+ were presented in a random order with a random inter-trial period of 100–110 s. We counter-balanced across subjects the auditory characteristics of CS+ and CS−, as well as the ketamine and saline injections. In the recall phase, which occurred about 24 h later, we tested the animals in a different context. Context was altered using different odors, wall inserts, light, and ambient noise. After 6 min of habituation, testing commenced, during which 4 CS− were presented followed by 4 CS+ (with no US) with a random inter-trial period of 100–110 s. Motion was quantified from the infrared video data using automated procedures in the Video Freeze software (Med Associates, Inc.). Briefly, according to the publication related to the software70, motion was quantified by calculating the sum of pixel-by-pixel value changes across successive video frames. Time periods when the motion values fell below the software-preset threshold for at least 1 s were considered freezing periods. For 35 s after the onset of each CS+ or CS− (i.e., the 20-s long CS presentation plus the 15-s long trace period), we determined the fraction of time in which freezing was detected. We reported the differential value, i.e., the fraction of time spent freezing in response to CS+, subtracted by the fraction of time spent freezing in response to CS−, as measured in the recall phase.

To measure sensorimotor gating, we used a commercial system (SR-Lab, San Diego Instruments). An animal would be injected with ketamine (40 mg/kg, s.c.) or saline (10 ml/kg, s.c.) and then immediately placed in a cylinder on a platform with an accelerometer for recording motion, all of which lie inside a soundproof chamber. For DREADD experiments, CNO (5 mg/kg, i.p.) or vehicle (10 mg/ml, i.p.) was given 30 min before injection of ketamine or saline and immediate commencement of PPI. The animal was habituated for 5 min to background noise (66 dB, calibrated by A-weighting at 25 cm from speaker) and startle stimuli (120 dB noise, 50 ms). For testing, there were 5 types of trials: startle, pre-pulse trials during which the onset of a pre-pulse stimulus (3, 6, or 9 dB noise above background, 50 ms) preceded a startle stimulus by 100 ms, and catch trials with no stimulus. A block consisted of 5 trials, 1 of each type, in a random order with a random inter-trial period of 8–23 s. For each animal, we would test for 10 blocks (i.e., 50 trials in total). The pre-pulse inhibition (PPI) is calculated as follows:

$${\mathrm{PPI}} = \frac{{S_{{\mathrm{startle}}} - S_{{\mathrm{prepulse}}}}}{{S_{{\mathrm{startle}}}}}$$ (5)

where S startle and S prepulse were the rectified motion signals recorded by the accelerometer during the 50-ms long startle stimulus averaged across trial repeats, for the startle and prepulse trials, respectively.

To assess locomotor activity, we placed animals in a conditioning box equipped with an infrared video camera (320 × 240 pixels, 30 Hz; Med Associates, Inc.). After ~30 min of habituation, they were injected with either ketamine (10 mg/kg, s.c.) or saline (10 ml/kg, s.c.) and returned to the box for another 60 min. Motion was assessed from the infrared video data quantified using automated procedures in the Video Freeze software (Med Associates, Inc.). To plot the results for Fig. 6d, we smoothed the motion signals with a 5-min long moving window at 1 s steps, for visualization purposes. For statistical comparisons, we used the time-averaged motion for each of the epochs: pre-injection, 5–30 min post-injection and 30–60 min post-injection.

Statistics

Statistical tests as described in figure legends were done in MATLAB. For the imaging experiments, all planned two-group comparisons were done with parametric t-tests (two-tailed, α = 0.05). For experiments with multiple parameters and conditions, we employed ANOVA tests, with groupings as indicated in the figure legend, followed by post-hoc tests using Tukey-Kramer for statistically significant main or interaction effects. The sampling distribution of the mean was assumed to be normal, but this was not formally tested. To test the robustness of our results, we also ran all the statistical tests in Figs. 1–3 using the two-sample Kolmogorov–Smirnov (K-S) test. This nonparametric test allows us to compare the two cumulative fraction plots (saline vs. ketamine) directly without any assumption of normality. None of the conclusions of whether to reject the null hypothesis at α = 0.05 were affected by a change in statistical tests (data not shown). For behavior and electrophysiology experiments, we used non-parametric tests (two-tailed, α = 0.05). In the figures, P-values were represented as n.s., not significant; P > 0.05; *P < 0.05; **P < 0.01; ***P < 0.001. See figure legends for exact P-values.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.