Differential effects of sound repetition rate on auditory cortex development and behavior in Fragile X Syndrome mouse model

Abstract

Fragile X syndrome (FXS) is a leading genetic form of autism and intellectual disability that is associated with a loss-of-function mutation in the Fragile X messenger ribonucleoprotein 1 (Fmr1) gene. The Fmr1 knockout (KO) mouse model displays many aspects of FXS-related phenotypes and is used to study FXS pathophysiology. Sensory manipulations, such as sound exposure, are considered as a non-invasive approach to alleviate FXS phenotypes. However, it is unclear what specific sound attributes may have beneficial effects.

In this study, we examined the effects of sound repetition rate on auditory cortex development and FXS-associated behaviors in a mouse model of FXS. KO and wild-type (WT) male littermates were exposed to 14 kHz pure tone trains with 1 Hz or 5 Hz repetition rates during postnatal day (P)9-P21 developmental period. We analyzed the effects of developmental sound exposure on PV cell development, cortical activity and exploratory behaviors in sound-exposed WT and KO mice. We found that parvalbumin (PV) cell density was lower in the auditory cortex (AuC) of KO compared to WT mice raised in sound-attenuated environment, but was increased following the exposure to both 1 Hz and 5 Hz sound trains. However, PV protein levels were upregulated only in AuC of 5 Hz rate exposed KO mice. Interestingly, analysis of baseline cortical activity using electroencephalography (EEG) recordings showed that sound attenuation or exposure to sound trains with 5 Hz, but not 1 Hz, repetition rates corrected enhanced resting state gamma power in AuC of KO mice to WT levels. In addition, sound attenuation and exposure to 5 Hz showed some beneficial effects on the synchronization to frequency-modulated chirp in the frontal cortex (FC) of both WT and KO mice. Analysis of event-related potentials (ERP) in response to broadband sound showed increased ongoing responses and decreased habituation to noise stimuli in the AuC and FC of naive KO mice. While sound-attenuation and exposure to 5 Hz showed no significant effects on the power of onset and ongoing responses, exposure to 1 Hz further enhanced ongoing responses and decreased habituation to sound in both WT and KO mice. Finally, developmental exposure to sound trains with 5 Hz, but not 1 Hz, repetition rates normalized exploratory behaviors and improved social novelty preference but not hyperactivity in KO mice.

Summarizing, our results show that developmental exposure of mice to sound trains with 5 Hz, but not 1 Hz, repetition rate had beneficial effects on PV cell development, overall cortical activity and behaviors in KO mice. While sound attenuation alone normalized some EEG phenotypes, it did not improve PV development or behaviors. These findings may have a significant impact on developing new approaches to alleviate FXS phenotypes and open possibilities for a combination of sound exposure with drug treatment which may offer highly novel therapeutic approaches.

Introduction

Abnormal sensory processing and associated behaviors, such as sensory hyperarousal and sensitivity, are common in Fragile X Syndrome (FXS), the leading genetic cause of autism and intellectual disability (Sinclair et al., 2017; Lachiewicz et al., 2023). Abnormal sensory processing during early development may lead to anxiety, social communication deficits, repetitive behaviors and language delays that are frequently observed in FXS (Orefice et al., 2016). However, the mechanisms of abnormal sensory processing remain unclear and treatments to alleviate sensory symptoms are not available. The Fragile X Messenger Ribonucleoprotein gene 1 (Fmr1) knockout (KO) mouse is an established pre-clinical model of FXS that provides a system with known etiology and consistent sensory hypersensitivity and defensiveness to study FXS (Rais et al., 2018; Auerbach et al., 2021; Razak et al., 2021; Rahmatullah et al., 2023; Willemsen and Kooy, 2023). The similarity of sensory phenotypes in humans with FXS and the mouse model enables discovery of underlying mechanisms and treatments. Our previous studies have shown altered auditory responses in the KO mouse (Lovelace et al., 2016; Lovelace et al., 2018; Wen et al., 2018; Wen et al., 2019; Pirbhoy et al., 2020; Rais et al., 2022) that are similar to those reported in humans with FXS (Ethridge et al., 2017; Wang et al., 2017). These alterations are likely neural correlates of abnormal central auditory processing in FXS. We also identified a developmental window during which the responses diverge between the KO and wildtype (WT) mice (Wen et al., 2018; Wen et al., 2019). More recently, we discovered that sound exposure during early development may reduce sensory hyperexcitability (Kulinich et al., 2020). However, it remains unknown what parameters of sound exposure have beneficial effects and how they may affect clinically relevant (electroencephalography) EEG phenotypes.

Mounting evidence showed robust physiological and behavioral effects of auditory stimuli on brain and behavior. It has been reported that an acoustically enriched environment (such as broad-band amplitude-modulated rippled noise) during the critical period of development improves frequency resolution and gap detection ability under complex testing conditions (Pysanenko et al., 2021) and induces permanent positive changes in the structure of neurons in the central auditory system (Svobodova Burianova and Syka, 2020). It has also been demonstrated that exposure to patterned auditory stimulus during an emotional challenge decreases despair-like behavior in rodents (Flores-Gutierrez et al., 2018) and mitigates anxiogenic-like effects caused by isolation stress in zebrafish (Marchetto et al., 2021). Interesting findings were also reported on the acoustic enrichment and prolonged natural lifespan in mice (Yamashita et al., 2018). Listening to 40 Hz binaural beats induces gamma oscillations in several brain areas associated with cognitive functions (Jirakittayakorn and Wongsawat, 2017).

Here, we studied the developmental effects of two different sound repetition rates on mouse auditory cortex development, clinically relevant EEG phenotypes and FXS-associated behaviors in KO mice. Our results show that developmental exposure of mice to sound trains with 5 Hz, but not 1 Hz, repetition rate had beneficial effects on PV cell development, cortical activity, and exploratory behaviors in KO mice. These findings have a significant impact on developing new, potentially non-pharmacological, approaches to alleviate FXS phenotypes.

Materials and methods

Ethics statement

All mouse studies were done according to the guidelines approved by the Institutional Animal Care and Use Committee at the University of California, Riverside and were performed in accordance with NIH “Guide for the Care and Use of Laboratory Animals” (AUP 30269).

Mice and sound exposure

The KO mice on C57BL/6 background (Jackson Laboratories, JAX:003025) and their wild-type (WT) counterparts (Jackson Laboratories, JAX: 000664) were bred as littermates (by crossing heterozygous Fmr1 KO females and wild-type males). Animals were maintained in an AAALAC accredited facility under a 12-h light/dark cycle and fed standard mouse chow. Water and food were provided to the mice ad libitum. Sound exposure was carried out as described earlier (Kulinich et al., 2020). For the naive exposure (NE) group, mice were raised in an accredited vivarium from birth to the day of the experiment (background ~65 dB SPL; BK Precision, model 732A). For the sound attenuated exposure (AE), age-matched WT and KO mouse litters with their mothers were housed together in a custom-built sound-shielded chamber lined with anechoic foam (105 cm × 105 cm × 63 cm, background ~40 dB SPL; BK Precision, model 732A sound level meter) from postnatal day (P)4–P7 until the time of testing (P20-P22). The chamber was placed in a closed room (275 cm × 420 cm) with a background ~45 dB SPL, which was accessed only once daily for animal health checks. In the sound exposure (SE) group, WT and KO male littermates were placed in the sound-shielded chamber and room with their mothers at P4–P7 and exposed to pure tone pips (65 dB SPL; 14 kHz; 30 ms duration, 5 ms on/off ramp; 6 pips at a 1 Hz or 5 Hz rep. rate; 2 s ITI) for 24 h/day from P9 to P21. The sound was generated (Avisoft-SASlab Pro) and delivered through a speaker (UltraSound Gate Player BL Light; RECORDER USGH) placed in the center of the chamber mounted to the ceiling (~ 30 cm above the floor). No harmonics were detected during the sound delivery (Sokolich Probe Microphone System; Spectra DAQ-200). To prevent any tone exposure of the AE group, SE 1 Hz, SE 5 Hz, and AE groups did not temporally overlap and only one sound attenuation chamber was present in the room. Therefore, different WT/KO litters were used for each group.

Immunofluorescence

Male WT and KO mice were euthanized with isoflurane at P21-P22 and perfused transcardially first with cold phosphate-buffered saline (PBS, 0.1 M) and then with 4% paraformaldehyde (PFA) in PBS as previously described with modifications (Wen et al., 2018). Brains were removed, post-fixed for 2 h in 4% PFA and 100 μm coronal sections containing auditory cortex were obtained using a vibratome (Campden Instruments) with a speed of 0.5–0.65 mm/s. Identification of the auditory cortex was performed using hippocampal landmarks (Wen et al., 2018). This method was previously validated using tonotopic mapping, dye injection (Martin del Campo et al., 2012) and Paxinos mouse brain atlas, and other publications on mouse auditory cortex (Anderson et al., 2009).

On average, 5–6 slices containing the auditory cortex were obtained from each brain. Immunolabeling of sections was performed using the protocol as described (Kulinich et al., 2020) with some modifications. Specifically, brain slices were washed in 0.1 M PBS, and then antigen retrieval was performed (10 mM in citric buffer containing 0.05 % tween 20, pH 6.0) for 5 min at 55°C. After cooling down on ice, slices were washed in 0.1 M PBS. Then, brain tissues were incubated with a blocking solution containing 4% normal goat serum (NGS), 4% normal donkey serum (NDS) and 0.1% triton X100 (NGS, Jackson ImmunoResearch Labs # 005000121; NDS, Jackson ImmunoResearch labs # 017000121) in a 0.1 M PBS solution to block tissue nonspecific staining. Sections were further incubated with primary antibodies and fluorescein-tagged Wisteria floribunda agglutinin (WFA, 4 μg/mL; Vector Laboratories, # FL-1351, RRID:AB_2336875) in blocking buffer for 24 h. Mouse anti-PV antibody (1:1000; Sigma, # P3088, RRID:AB_477329) and rabbit anti-cFos (1:500; Cell Signaling Technologies, catalog # 2250, RRID:AB_ 224721) were used to visualize PV+ and cFos+ cells. WFA, a lectin that recognizes glycosaminoglycan side chains of chondroitin sulfate proteoglycans present in PNNs, primarily but not exclusively aggrecan, was used to label PNNs, referred here as WFA+ PNNs (Pizzorusso et al., 2002). Next, slices were washed in 0.1 M PBS containing 0.1% Tween-20 and incubated with secondary antibodies, donkey anti-mouse Alexa 594 (4 μg/mL; Thermo Fisher Scientific, catalog # A-21203, RRID: AB_2535789) or goat anti-mouse FITC (4 μg/mL; Thermo Fisher Scientific, # 31569, RRID:AB_228306) and donkey anti-rabbit Alexa 594 (2 μg/mL; Thermo Fisher Scientific, # A-21207, RRID:AB_141633), in blocking buffer for 2 h. Brain tissues were further washed with 0.1 M PBS containing 0.1% Tween-20, mounted with Vectashield (Vector Labs, # H-1200) and sealed with Cytoseal (ThermoScientific, # 8310–16). Each slice was imaged with a Zeiss 880 (airyscan mode) confocal microscope using a series of 10 high-resolution optical sections (1608 × 1608-pixel format) and a 10×, or a 40× immersion objective, 1× zoom at 1 μm step (z-stack). Image analysis was performed using the ImageJ macro plugin PIPSQUEAK (https://rewireneuro.com/pipsqueak-pro)). 10 images in the Z-stack (1.891 pixels/μm) were compiled into a single image using ImageJ macro plugin PIPSQUEAK, scaled, and converted into 32-bit, grayscale, TIFF files. PIPSQUEAK was run in “semi-automatic mode” to select ROIs to identify individual PV-, PNN- and cFos-positive cells, which were then verified by a trained experimenter. PV-, PNN- and cFos cell density and intensity were analyzed in layers (L)2-L6. A 2-way ANOVA with Bonferroni’s post-hoc test was used to determine genotype and sound effects. Statistical analysis was performed using GraphPad Prism 10 software (RRID:SCR_002798).

Western blotting

Mice were euthanized at P21 with isoflurane and cervical dislocation was performed. Auditory cortex was identified based on methods described earlier and dissected as previously described with modifications (Kulinich et al., 2020). Tissue samples were immediately homogenized in RIPA buffer (50 mm Tris-HCl, pH 7.4; 150 mm NaCl; 1 mm EDTA, pH 8.0; 1% Triton X-100; 0.1% SDS; protease inhibitor cocktail; 0.5 mm sodium pervanadate). Samples were rotated at 4°C for 1 h to allow for complete cell lysis and then cleared by centrifugation at 13,200 rpm for 20 min at 4°C. Samples were boiled in reducing sample buffer (Laemmli 2× concentrate, S3401, Sigma), and separated on 8–16% Tris-glycine SDS-PAGE precast gels (Invitrogen). Proteins were transferred onto Protran BA 85 Nitrocellulose membrane (GE Healthcare), washed 2 times (5 min each) with milli Q water and further blocked for 1 h at room temperature in 5% BSA (BSA; Fisher Scientific, # 9048468) or skim milk (#170–6404, Bio-Rad), based on the manufacturer’s protocol. Incubation with primary antibody diluted in TBS/0.1% Tween-20/5% BSA was performed overnight at 4°C. The following primary antibodies for protein detection were used: mouse anti-PV (1:1000; Millipore, # MAB1572, RRID:AB_2174013) and mouse anti-β-actin (1:1000; Santa Cruz, # sc-47778, RRID:AB_626632). Blots were washed 3 × 10 min with TBS/0.1% Tween-20 and incubated with the appropriate HRP-conjugated secondary antibodies for 2 h at room temperature in a TBS/0.1% Tween-20/5% BSA solution. The secondary antibodies used α-mouse-HRP at 1:10000 (Jackson ImmunoResearch Labs, # 715-035-150, RRID:AB_2340770). After secondary antibody incubations, blots were washed 3 × 10 min in TBS/0.1% Tween-20, incubated in ECL 2 Western Blotting Substrate (Thermo Scientific, #32106) and imaged using ChemiDoc imaging system (Bio-Rad, RRID:SCR_019037). For re-probing, membrane blots were washed in stripping buffer (2% SDS, 100 mm β-mercaptoethanol, 50 mm Tris-HCl, pH 6.8) for 30 min at 55°C, then rinsed repeatedly with TBS/0.1% Tween-20 (5×5 min), blocked with 5% skim milk, and then re-probed. Band density was analyzed by measuring band and background intensity using Adobe Photoshop CS5.1 software (RRID:SCR_014199). Samples from KO and their WT counterpart mice (NE, AE or SE groups) were run on the same blot, and precision/tolerance (P/T) ratios for KO samples were normalized to averaged P/T ratios of WT samples. A 2-way ANOVA with Bonferroni’s post-hoc test was used to determine genotype and sound effects. Statistical analysis was performed using GraphPad Prism 10 software (RRID:SCR_002798).

Surgery for in vivo EEG recordings

Surgical procedures were performed as described previously with modifications (Lovelace et al., 2018; Wen et al., 2019; Lovelace et al., 2020b; Pirbhoy et al., 2020). P20-P22 male NE WT (n=21), NE KO (n=14), AE WT (n = 11), AE KO (n = 16), SE 1 Hz WT (n=14), SE 1 Hz KO (n=16), SE 5 Hz WT (n=14), and SE 5Hz KO (n=14) mice were used for the EEG studies. Mice were anesthetized with isoflurane inhalation (0.2–0.5%) and an injection of ketamine and xylazine (K/X) (i.p. 80/10 mg/kg), and then secured in a bite bar, and placed in a stereotaxic apparatus (model 930; Kopf, CA). Ethiqa XR (buprenorphine extended-release injectable suspension; Fidelis pharma Inc.; 3.25 mg/kg body weight) and meloxicam (non-steroid anti-inflammatory drug; Covetrus; 5mg/kg) were injected subcutaneously. Both drugs were administered before the surgery to ensure that there was an adequate therapeutic drug level present postsurgically. Artificial tear gel (Akorn Animal Health) was applied to the eyes to prevent drying. The toe pinch reflex was used to measure the anesthetic state every 10 min throughout the surgery, and supplemental doses of K/X were administered as needed. Once the mouse was anesthetized, a midline sagittal incision was made along the scalp to expose the skull. A Foredom dental drill was used to drill 1 mm diameter holes in the skull overlying the right auditory cortex (AuC: −1.6 mm, ±4.0 mm), right frontal cortex (FC: +2.6 mm, ±1.0 mm), and left occipital (−3.5 mm, −5.2 mm) (coordinate relative to Bregma: anterior/posterior, medial/lateral). Three channel electrode posts from Plastics One (MS333-2-A-SPC) were attached to 1 mm stainless steel screws from Plastics One (8L003905201F) and screws were advanced into drilled holes until secure. Special care was taken not to advance the screws beyond the point of contact with the dura. Dental cement was applied around the screws, on the base of the post, and exposed skull. Triple antibiotic was applied along the edges of the dental cement. Mice were placed on a heating pad to aid recovery from anesthesia. A second meloxicam injection was administered between 12 and 24 hours after the surgery (and 48 h after the surgery if needed). Mice were group housed, returned to the vivarium and monitored daily until the day of EEG recordings, which allowed 4–5 days of recovery post-surgery before recording.

EEG recordings

All EEG recordings were obtained using the BioPac system (BIOPAC Systems, Inc.) from awake and freely moving mice as published previously (Lovelace et al., 2018). Mice were connected to the BioPac system through a three-channel tether under brief isoflurane anesthesia and placed inside a grounded Faraday cage, inside an anechoic foam-lined sound-attenuating room (Gretch Ken Industries, OR) after recovery from isoflurane. The tether was connected to a commutator located directly above the cage. Mice were then allowed to habituate while being connected to the tether for 20 min before EEG recordings were obtained. During the recording session, a piezoelectric sensor placed under the floor of the cage detected mouse movement in the recording arena.

The BioPac MP150 acquisition system was connected to two EEG 100C amplifier units (one for each channel) to which the commutator was attached. The lead to the occipital cortex was used as reference for both AuC and FC screw electrodes. The acquisition hardware was set to high-pass (>0.5 Hz) and low-pass (<100 Hz) filters. EEG data were collected with gain maintained the same (10,000x) between all recordings. Data were sampled at a rate of either 2.5 or 5 kHz using Acqknowledge software and down sampled to 1024 Hz post hoc using Analyzer 2.1 (Brain Vision Inc.). Sound delivery was synchronized with EEG recording using a TTL pulse to mark the onset of each sound in a train. Baseline (no auditory stimuli) EEGs were recorded for 5 min, followed by recordings in response to auditory stimulation. After these experiments were completed, mice were returned to the colony and used for tissue dissection on a later date.

Acoustic Stimulation

All experiments were conducted in a sound-attenuated chamber lined with anechoic foam (Gretch-Ken Industries, OR) as previously described (Lovelace et al., 2018; Lovelace et al., 2020b). Acoustic stimuli were generated using RVPDX software and RZ6 hardware (Tucker-Davis Technologies, FL) and presented through a free-field speaker (MF1 Multi-Field Magnetic Speaker; Tucker-Davis Technologies, FL) located 12 inches directly above the cage. Sound pressure level (SPL) was modified using programmable attenuators in the RZ6 system. The speaker output was ~65–70 dB SPL at the floor of the recording chamber.

We used acoustic stimulation paradigms that have been previously established in KO mice (Lovelace et al., 2018), which is analogous to work in humans with FXS (Ethridge et al., 2017). A chirp-modulated signal (henceforth, ‘chirp’) to induce synchronized oscillations in cortical responses was used to measure temporal response fidelity. The chirp is a 2 s broadband noise stimulus with amplitude modulated (100% modulation depth) by a sinusoid whose frequencies increase (Up-chirp) or decrease (Down-chirp) linearly in the 1–100 Hz range (Artieda et al., 2004; Purcell et al., 2004; Perez-Alcazar et al., 2008). The chirp facilitates a rapid measurement of transient oscillatory response (delta to gamma frequency range) to auditory stimuli of varying frequencies and can be used to compare oscillatory responses in different groups in clinical and preclinical settings (Purcell et al., 2004). Inter-trial coherence analysis (Tallon-Baudry et al., 1996) can then be used to determine the ability of neural generators to synchronize oscillations to the frequencies present in the stimulus.

To avoid onset responses contaminating phase locking to the amplitude modulation of the chirp, the stimulus was ramped in sound level from 0–100% over 1 s (rise time), which then smoothly transitioned into chirp modulation of the noise. Up chirp trains were presented 300 times each (for a total of 600 trains).

To study evoked response amplitudes and habituation, trains of 100 ms broadband noise were presented at two repetition rates, 0.25 Hz (a non-habituating rate) and 4 Hz (a strongly habituating rate) (Lovelace et al., 2016). Each train consisted of 10 noise bursts and the inter-train interval used was 8 s. Each repetition rate was presented 100 times in an alternating pattern (Lovelace et al., 2016). The onset of trains and individual noise bursts were tracked with separate TTL pulses that were used to quantify latency of response.

EEG Data Analysis

Data were extracted from Acqknowledge and saved in a file format (EDF) compatible with BrainVision Analyzer 2.1 software as previously described (Lovelace et al., 2018; Lovelace et al., 2020b). All data were notch filtered at 60 Hz to remove residual line frequency power from recordings. EEG artifacts were removed using a semi-automatic procedure in Analyzer 2.1 for all recordings. Less than 30% of data were rejected due to artifacts from any single mouse. If more than 30% of data was rejected, the animal was excluded from the analysis. Baseline EEG data were divided into 2 s segments and Fast Fourier Transforms (FFT) were calculated on each segment using 0.5 Hz bins and then average power (µV²/Hz) was calculated for each mouse from 1–100 Hz. Power was then binned into standard frequency bands: Delta (1–4 Hz), Theta (4–10 Hz), Alpha (10–13 Hz), Beta (13–30 Hz), Low Gamma (30–55 Hz), and High Gamma (65–100 Hz). Responses to chirp trains were analyzed using Morlet wavelet analysis. Chirp trains were segmented into windows of 500 ms before chirp onset to 500 ms after the end of the chirp sound (total of 3 s because each chirp was 2 s in duration). EEG traces wereprocessed with Morlet wavelets from 1 to 100 Hz using complex number output (voltage density, µV/Hz) for Inter-Trial Phase Coherence (ITPC) calculations, and power density (µV²/Hz) fornon-phase locked single trial power (STP). Wavelets were run with a Morlet parameter of 10 as this gave the best frequency/power discrimination. This parameter was chosen since studies in humans found the most robust difference around 40 Hz, where this parameter is centered (Ethridge et al., 2017). To measure phase synchronization at each frequency across trials Inter Trial Phase Coherence (ITPC) was calculated. The equation used to calculate ITPC is:

$$ITPC\left(f,t\right)=\frac{1}{n}\sum _{k=1}^n\frac{F_k\left(f,t\right)}{\left|F_k\left(f,t\right)\right|}$$

where f is the frequency, t is the time point, and k is the trial number. Thus, F_k(f,t) refers to the complex wavelet coefficient at a given frequency and time for the kth trial. There were no less than 225 trials (out of 300) for any given mouse after segments containing artifacts were rejected.

EEG Statistical Analysis

All statistical analysis was performed as described previously (Lovelace et al., 2018; Wen et al., 2019; Lovelace et al., 2020b; Pirbhoy et al., 2020). Statistical group comparisons of chirp responses (ITPC and STP) and broadband noise trains (ITPC and STP) were quantified using MATLAB (MATLAB, RRID:SCR_001622). The analysis was conducted by binning time into 256 parts and frequency into 100 parts, resulting in a 100 × 256 matrix. Non-parametric cluster analysis was used to determine contiguous regions in the matrix that were significantly different from a distribution of 1000 randomized Monte Carlo permutations (Maris and Oostenveld, 2007). Briefly, if the cluster sizes of the real genotype assignments (both positive and negative direction, resulting in a two-tailed alpha of p = 0.025) were larger than 97.25% of the random group assignments, those clusters were considered significantly different between genotypes. This method avoids statistical assumptions about the data and corrects for multiple comparisons.

Behavioral Assessments

Open-field test

Exploratory-like behaviors and locomotor activity were tested in mice as described previously with modifications (Dansie et al., 2013; Lovelace et al., 2018; Rais et al., 2022). The cages with mice were transferred to the behavioral room 30 min before the testing. A 72 × 72-cm open-field arena with 50-cm-high walls was constructed from opaque acrylic sheets with a clear acrylic sheet for the bottom. The open field arena was placed in a brightly lit room (304 lux), and one mouse at a time was placed in a corner of the open field and allowed to explore for 10 min while being recorded with digital video from above. The floor was cleaned with 2–3% acetic acid, 70% ethanol, and water between tests to eliminate odor trails. The mice were tested between the hours of 8:00 A.M. and 2:00 P.M., and this test was always performed prior to the elevated plus maze. The arena was subdivided into a 4 × 4 grid of squares with the middle of the grid defined as the center. A line 4 cm from each wall was added to measure thigmotaxis. Locomotor activity was scored by the analysis of total line crosses, distance traveled and speed using TopScan Lite software (Clever Sys., Inc., VA). A tendency to travel to the center (total number of entries into large and small center squares), time spent in the center of the open field and the time in thigmotaxis were used as an indicator of exploratory behaviors. The analysis was performed for first and second 5 min period of testing. Assessments of the digital recordings were performed blind to the condition.

Elevated plus maze

The elevated plus test was conducted as described previously (Dansie et al., 2013; Rais et al., 2022). Briefly, the maze consisted of four arms in a plus configuration. Two opposing arms had 15-cm tall walls (closed arms), and two arms were without walls (open arms). The entire maze sat on a stand 1 m above the floor. Each arm measured 30 cm long and 10 cm wide. Mice were allowed to explore the maze for 10 min while being recorded by digital video from above. The maze was wiped with 2–3% acetic acid, 70% ethanol and water between each test to eliminate odor trails. This test was always done following the open-field test. TopScan Lite software was used to measure the percent of time spent in open arms and speed. The time spent in the open arm was used to evaluate anxiety-like behavior while speed and total arm entries were measured to evaluate overall locomotor activity (Lovelace et al., 2020b). The analysis was performed for first and second 5 min period of testing. Assessments of the digital recordings were done blind to the condition using TopScan Lite software.

Social Novelty Test

Sociability and social memory were studied using a three-chamber test as described previously (Kaidanovich-Beilin et al., 2011; Sidhu et al., 2014; Nguyen et al., 2020b). Briefly, a rectangular box contained three adjacent chambers 19 × 45 cm each, with 30-cm-high walls and a bottom constructed from clear Plexiglas. The three chambers were separated by dividing walls, which were made from clear Plexiglas with openings between the middle chamber and each side chamber. Removable doors over these openings permitted chamber isolation or free access to all chambers. All testing was done in a brightly lit room (304 lux), between 9:00 A.M. and 4:00 P.M and after the elevated plus maze test. The test mouse was placed in the central chamber with no access to the left and right chambers and allowed to habituate to the test chamber for 5 min before testing began. Session 1 measured sociability. In session 1, another mouse (Stranger 1) was placed in a wire cup-like container in one of the side chambers. The opposite side had an empty cup of the same design. The doors between the chambers were removed, and the test mouse was allowed to explore all three chambers freely for 10 min, while being digitally recorded from above. The following parameters were monitored: the duration of direct contact between the test mouse and either the stranger mouse or empty cup and the duration of time spent in each chamber. Session 2 measured social memory and social novelty preference. In session 2, a new mouse (Stranger 2) was placed in the empty wire cup in the second side chamber. Stranger 1, a now familiar mouse, remained in the first side chamber. The test mouse was allowed to freely explore all three chambers for another 10 min, while being recorded, and the same parameters were monitored. Placement of Stranger 1 in the left or right side of the chamber was randomly altered between trials. The floor of the chamber was cleaned with 2%–3% acetic acid, 70% ethanol, and water between tests to eliminate odor trails. Assessments of the digital recordings were done using TopScan Lite software (Clever Sys., Inc., VA). To measure changes in sociability and social memory, percent time spent in each chamber was calculated in each test. Further, a sociability index = ($\frac{timeinS1chamber}{timeinS1chamber+timeinemptychamber}$) and social novelty preference index = ($\frac{timeinS2chamber}{timeinS2chamber+timeinS1chamber}$) were calculated as described previously (Nygaard et al., 2019; Nguyen et al., 2020b). For sociability index, values <0.5 indicate more time spent in the empty chamber, >0.5 indicate more time spent in the chamber containing Stranger 1, and 0.5 indicates no preference. For social novelty preference index, values <0.5 indicate more time spent in the chamber containing Stranger 1 or now familiar mouse, >0.5 indicate more time spent in the chamber containing Stranger 2 or new stranger mouse, and 0.5 indicates no preference. Statistical analysis was performed using two-way ANOVA followed by Tukey’s multiple comparison post-test to determine effects of genotype and sound using GraphPad Prism 10 software (RRID:SCR_002798). Data represent mean ± standard error of the mean (SEM).

Results

Developmental acoustic exposure of Fmr1 KO mice lead to repetition rate-specific increase in PV protein levels and decreased cFos immunoreactivity in the auditory cortex

Our previous study reported abnormal development of PV interneurons and impaired PNN formation in layers (L)2-L4 of developing auditory cortex (AuC) of KO mice (Wen et al., 2018; Kulinich et al., 2020; Pirbhoy et al., 2020). We have also shown that developmental acoustic exposure to 14 kHz tone restored the density of PV-positive(+) cells and PV protein levels in AuC of KO mice (Kulinich et al., 2020). However, it was not clear what specific sound properties had beneficial effects. In this study, we examined whether exposures to sound trains with different repetition rates during postnatal day (P)9-P21 period affect PV/PNN development in WT and KO mice. For this, we used four sound exposure groups: naïve exposure (NE, vivarium), attenuated exposure (AE, chamber without sound) and sound exposure (SE) to 14 kHz sound trains with 1 Hz (SE 1 Hz) or 5 Hz (SE 5 Hz) repetition rate, and examined the effects of sound exposures on two genotypes: WT and KO mice. After exposure to sound from P9 until P21, PV, PNN and cFos levels were analyzed by immunohistochemistry and PV protein levels were also examined using western blot analysis in P22 AuC (Fig 1A).

Fig 1. PV, PNN and cFos analysis in the auditory cortex of P22 WT and Fmr1 KO (KO) mice raised in naive environment (NE), sound-attenuated environment (AE), or sound exposed to 14 kHz sound trains with 1 Hz (SE 1 Hz) or 5 Hz (SE 5 Hz) repetition rates.

(A) Timeline of the experiments. (B) Confocal images of PV immunoreactivity and PNN-labeling in L4 AuC of AE WT mouse, scale bar 25 µm. (C-F) Quantitative analysis of the density of PV+ and PNN+ cells (C, E), percentage of PV cells with low or high PV levels (D), and PNN levels (E) in L4 AuC of NE, AE, SE 1Hz, SE 5Hz WT and KO groups (n=3–7 mice per group). (G, H) Western blot images of PV and β-actin (G) and quantitative analysis of PV levels (H) in AuC (n=3–4 mice per group). (I) Confocal image of PV (green) and cFos (red) immunoreactivity in L4 AuC of AE WT mouse, scale bar 25 µm. (J) Quantitative analysis of the density of cFos+ cells in L4 AuC (n=3–6 mice per group). Statistical analysis was done using two-way ANOVA with a Tukey’s post-hoc test: *, p < 0.05**, p < 0.01; ***, p < 0.001; ****, p <0.0001. Black stars (*) depict comparison between genotypes within sound-exposure group, red and blue stars depict comparisons to NE (blue for WT and red for KO); pound signs (#) depict comparisons to AE (blue for WT and red for KO); plus signs (+) depict comparisons between SE 1 Hz and SE 5 Hz (blue for WT and red for KO).

We found that PV+ cell density was decreased in L4 AuC of AE KO compared to WT, but exposure to sound trains with both 1 Hz and 5 Hz repetition rates increased the overall density of PV+ cells in KO mice to WT levels (Fig.1B–C). We also examined PV levels by analyzing intensity of PV immunoreactivity. We found that sound attenuation had a significant effect on PV levels in all layers of AuC in both WT and KO mice and observed a higher proportion of cells with low PV levels (low-PV cells) and less cells with high PV levels (high-PV cells) in the AE group compared to NE group (Fig. 1D; Extended data, Supplementary Fig. 1–2). In addition, we observed differential effects of 1 Hz and 5 Hz sound repetition rates. While in the SE 1 Hz group the percent of low-PV and high-PV cells was similar to the AE group, SE 5 Hz KO showed a decrease of low-PV and an increase of high-PV cells compared to AE KO (Fig. 1D; Extended data, Supplementary Fig. 1–2). A two-way ANOVA analysis of PNN+ cell density and intensity in all layers of AuC showed a genotype effect (Fig.1E,F; Extended data, Supplementary Fig. 1). Interestingly, PNN levels were further reduced in mice exposed to both 1 Hz and 5 Hz repetition rates (Fig 1F; Extended data, Supplementary Fig. 1), which may suggest ECM remodeling.

To confirm changes in PV protein levels observed by immunolabeling, we also performed western blot analysis. Our results indeed showed increased PV protein levels in AuC of WT and KO mice exposed to 5 Hz, and not 1 Hz, compared to AE mice (Fig. 1G,H). As PV levels directly correlate with their activity (Donato et al., 2013; Donato et al., 2015; Miranda et al., 2022; Luo et al., 2024), an increase in PV levels and their inhibitory activity may lead to an overall reduction in cortical neuronal activity. Therefore, we next examined the density of active cells by analyzing cFos immunoreactivity as cFos is commonly used to assess changes in neuronal activity (Renier et al., 2016). While sound attenuation reduced the number of cFos-expressing cells in AuC, we found an additional decrease in cFos+ cell density in SE 5 Hz KO compared to AE KO and SE 1 Hz KO mice (Fig. 1I, J; Extended data, Supplementary Fig. 1).

In summary, exposure to sound trains with 5 Hz repetition rate during P9-P21 developmental period increased density of PV+ cells, PV protein levels and decreased the number of cFos+ cells in AuC of Fmr1 KO mice, suggesting potential effects of 5 Hz repetition rate on reducing overall neuronal activity by activating inhibitory PV cells.

Cortical resting state EEG gamma power was restored in the Fmr1 KO mice following developmental sound attenuation or exposure to sound trains with 5 Hz but not 1 Hz repetition rate

Previously, we have shown that adult and young KO mice exhibit increased resting state gamma power (Lovelace et al., 2018; Lovelace et al., 2020b; Pirbhoy et al., 2020), a phenotype which is similar to that observed in the rat model of FXS (Anderson et al., 2009) and in humans with FXS (Ethridge et al., 2017; Wang et al., 2017). In this study, analysis of neuronal activity by assessing PV and cFos immunoreactivity suggested potential effects of 5 Hz, but not 1 Hz, sound repetition rate on cortical activity. Therefore, we assessed whether acoustic developmental exposures would affect cortical activity by analyzing resting state EEG power in these mice. Mice were implanted with two-channel EEG electrodes placed in the AuC and FC at P21-P22, allowed to recover for 4–5 days, and then baseline EEG activity was recorded at P26-P28. Resting EEG data (in the absence of auditory stimulation) were collected for 5 min and were divided into 2-s segments for spectral analysis. Resting EEG raw power (µV²/Hz) was calculated in the AuC and FC of WT and KO mice by analyzing all frequency bands during the entire 5-min resting period. Examples of 1s segment of representative baseline EEG in AuC of NE WT and NE KO are shown in Fig.2A.

Fig 2. Resting EEG recordings (5 min) from the auditory cortex and frontal cortex of WT and KO animals raised in different acoustic environments.

(A) Graphs show representative EEG traces in the AuC of NE WT (left) and NE KO (right) mice. (B-C) Graphs show average frequency power in (B) AuC and (C) FC of NE WT (n=21), NE KO (n=14), AE WT (n=11), AE KO (n=16), SE 1Hz WT (n=14), SE 1Hz KO (n=16), SE 5Hz WT (n=14) and SE 5Hz KO (n=14) mice. Statistical analysis was done using two-way ANOVA with a Tukey’s post-hoc test: *, p < 0.05; **, p < 0.01; ***, p <0 .001; **** p < 0 .0001. Black stars depict comparison between genotypes, red and blue stars depict comparisons to NE (blue for WT and red for KO); pound signs (#) depict comparisons to AE (blue for WT and red for KO); plus signs (+) depict comparisons between SE 1 Hz and SE 5 Hz (blue for WT and red for KO).

Similar to published work, we observed increased resting state gamma power in the AuC of NE KO mice compared to WT, primarily due to the differences in low (30–55 Hz) gamma frequency bands in both AuC and FC (Fig. 2B,C; Extended data, Supplemental Fig.3). Based on the two-way ANOVA analysis, we observed significant effects of genotype and sound exposure, but no interaction. There was a significant decrease of low and high gamma power in AuC and FC of AE KO compared to NE KO (Fig. 2B,C). Exposure to 5 Hz repetition rate also significantly decreased low and high gamma power in the AuC of SE 5 Hz KO compared to NE KO and SE 1 Hz mice for both genotypes, but no differences were observed between NE and SE 1 Hz groups (Fig. 2B). Sound attenuation and exposure to 5 Hz repetition rate also significantly reduced gamma power in WT mice (Fig. 2B).

Interesting effects of sound exposure were also detected in delta, alpha and beta frequencies. Delta frequency power increased in the AuC of SE 5Hz mice compared to NE, AE and SE 1 Hz, for both genotypes with similar trends in FC (Fig. 2B). Beta frequency power was significantly higher in SE 1 Hz groups compared to NE, AE and SE 5 Hz in both AuC and FC, and similar differences were observed for alpha frequency power in FC (Fig. 2B,C). EEG studies in humans also demonstrated power abnormalities in delta, theta, alpha frequencies, as well as impaired power coupling between low- and high-frequency oscillations in individuals with FXS and ASD (Sinclair et al., 2017; Wang et al., 2017). The power coupling indicates how population activity within and across cortical regions are coordinated through oscillatory rhythms. Therefore, using the same approach as in the human study (Wang et al., 2013), we analyzed power coupling between low (delta, theta, or alpha) and high (low gamma) frequency bands within the same brain area as well as between AuC and FC during the resting baseline recording (Extended data, Supplemental Fig. 4). We did not find a genotype difference in power coupling for all groups but detected an effect of sound exposure. Specifically, we observed an increase in alpha/gamma, delta/gamma, and theta/gamma, power coupling in AuC and FC, and across regions in both WT and KO mice exposed to both 1 Hz and 5 Hz, but no effects of sound attenuation (Extended data, Supplemental Fig. 4). However, there was an increase in the same frequency coupling (alpha/alpha, delta/delta and theta/theta) between AuC and FC in all sound exposure groups (Extended data, Supplemental Fig. 4). Our data show effects of sound exposure on low-high frequency power coupling in both 1 Hz and 5 Hz groups suggesting that sound repetition rate does not differentially affect it. As regional and frequency-specific low-high frequency power coupling are important in coordinating activity within and across active neural populations, developmental sound exposure may influence animal behaviors in specific sensory and cognitive tasks.

Developmental sound exposure affected synchronization to chirp-modulated sound in WT and KO mice

Developmental effects of sound exposure on baseline power and low-high frequency power coupling may affect responses to sounds. In addition, the deficits in the consistency of phase-locking to time varying stimuli in gamma frequency range were previously attributed to the enhanced resting gamma power in young and adult KO mice (Lovelace et al., 2018; Pirbhoy et al., 2020), as well as in humans with FXS (Ethridge et al., 2017). To test if developmental sound exposure also affects synchronization to time-varying stimuli, we recorded EEG responses to ‘up chirps’. A ‘chirp stimulus’ is a broadband noise which is amplitude modulated at an increasing rate of modulation from 1 Hz to 100 Hz over 2 seconds. Repeated chirp stimuli were delivered (300 trials) and electrocortical activity was recorded in the AuC and FC of freely moving animals. Phase locking factor (PLF) and non-phase locked single trial power (STP, background power) were analyzed using Morlet wavelet analysis as described (Lovelace et al., 2018; Lovelace et al., 2020b; Pirbhoy et al., 2020). PLF measures the ability of evoked oscillations to phase lock with fidelity from one trial to the next (a.k.a intertrial phase clustering) and STP represents summed background and evoked non-phase locked power during auditory stimulation.

Similar to our previous studies in NE mice, we found a significant decrease in synchronization to chirp-modulated sound in the 20–40 Hz beta/gamma range in AuC of NE KO compared to their WT littermates (Fig. 3A–C). In sound-exposed groups, we also observed a similar decrease of synchronization in AuC of KO mice compared to their corresponding WT in 20–40 Hz range in AE and SE 1 Hz groups and 40–60 Hz for SE 5Hz group (Fig. 3A–C).

Fig. 3. Phase locking to frequency-modulated sound “chirp” was still impaired in the auditory cortex of P26-P28 mice raised in different acoustic environments.

(A, B) Graphs show grand averages of Phase Locking Factor (PLF) to upward chirp in the AuC of NE WT (n=21), NE KO (n=14), AE WT (n=11), AE KO (n=16), SE 1Hz WT (n=14), SE 1Hz KO (n=16), SE 5Hz WT (n=14) and SE 5Hz KO (n=14) mice. (C) Graphs show differences between KO and their corresponding WT groups. (D) Graphs show AE KO/NE KO, SE 1 Hz KO/NE KO, SE 5 Hz KO/ NE KO and SE 5 Hz KO/SE 1 Hz KO comparisons. (E) Graphs show AE WT/NE WT, SE 1 Hz WT/NE WT, SE 5 Hz WT/ NE WT and SE 5 Hz WT/SE 1 Hz WT comparisons. The decrease is shown in blue and increase in orange. Significant clusters (p < 0.025) are highlighted by bold-lined contours (solid line depicts significant decrease and dotted line shows significant increase).

Although, there was a significant improvement in the SE 5 Hz KO mice compared to SE 5 Hz WT in the 20–40 Hz range in AuC (Fig. 3A–C) and SE 5 Hz KO also showed a significant increase in synchronization compared to SE 1 Hz group (Fig. 3A–D), it was still significantly lower than the naïve group (Fig. 3D). Both sound attenuation and sound exposure also reduced synchronization in high gamma range compared to naïve KO group. In addition, developmental sound exposure affected the synchronization to frequency-modulated chirp in low and high gamma range in WT groups (Fig. 3E). In the FC, all sound-exposed groups showed a decreased synchronization in KO mice compared to their corresponding WT in 40–60 Hz range (Fig. 4A–C), most likely due to overall enhanced responses in WT groups (Fig. 4E). However, sound attenuation led to a significant approvement in synchronization to chirp-modulated sound in the 40–100 Hz gamma range in AE KO and AE WT compared to NE KO and NE WT groups, respectively (Fig. 4D–E). Some improvements were also observed in the 5 Hz WT but not 5 Hz KO compared to their NE counterparts (Fig. 4D). These findings show improvements in the ability of FC but not AuC to produce synchronous stimulus-induced oscillations following the developmental sound attenuation and exposure of mice to sound trains with 5 Hz but not 1 Hz repetition rate.

Fig. 4. Phase locking to frequency-modulated sound “chirp” was improved in the frontal cortex of P26-P28 mice following sound attenuation or exposure to sound with 5 Hz repetition rate.

(A, B) Graphs show grand averages of Phase Locking Factor (PLF) to upward chirp in the FC of NE WT (n=21), NE KO (n=14), AE WT (n=11), AE KO (n=16), SE 1Hz WT (n=14), SE 1Hz KO (n=16), SE 5Hz WT (n=14) and SE 5Hz KO (n=14) mice. (C) Graphs show differences between KO and their corresponding WT groups. (D) Graphs show AE KO/NE KO, SE 1 Hz KO/NE KO, SE 5 Hz KO/ NE KO and SE 5 Hz KO/ SE 1 Hz KO comparisons. (E) Graphs show AE WT/NE WT, SE 1 Hz WT/NE WT, SE 5 Hz WT/ NE WT and SE 5 Hz WT/SE 1 Hz WT comparisons. The decrease is shown in blue and increase in orange. Significant clusters (p < 0.025) are highlighted by bold-lined contours (solid line depicts significant decrease and dotted line shows significant increase).

To examine whether young KO mice in this study also display increased background power during the chirp presentation similar to adult KO mice (Lovelace et al., 2018) and whether this is reversed by developmental sound exposure, we assessed non-phase locked single trial power (STP) during chirp stimulation in the AuC and FC. Using the same statistical cluster analysis as for the chirp ITPC, we found that P26-P28 NE KO mice exhibit a significant increase in background power in the AuC and FC (35–80 Hz range) compared to NE WT littermates (Fig. 5A–C, Fig.6A–C). While developmental exposure to the sound with 1 Hz repetition rate only slightly reduced background 40–80 Hz gamma power in the AuC of both WT and KO compared to their NE counterparts, sound attenuation and exposure to sound with 5 Hz repetition rate significantly reduced background 20–100 Hz power in the AuC and FC of both WT and KO (Fig. 5D–E, Fig. 6D–E). Moreover, 5 Hz KO showed a significantly lower background power compared to 1 Hz KO in 20–40 Hz low gamma range (Fig. 5D, 6D).

Fig. 5. Sound attenuation or exposure to sound with 5 Hz repetition rate were most effective in reducing background power in the auditory cortex of P26-P28 mice to WT levels during chirp presentation.

(A, B) Graphs show grand averages of Single Trial Power (STP) during the upward chirp in the AuC of NE WT (n=21), NE KO (n=14), AE WT (n=11), AE KO (n=16), SE 1Hz WT (n=14), SE 1 Hz KO (n=16), SE 5Hz WT (n=14) and SE 5Hz KO (n=14) mice. (C) Graphs show differences between KO and their corresponding WT groups. (D) Graphs show AE KO/NE KO, SE 1 Hz KO/NE KO, SE 5 Hz KO/ NE KO and SE 5 Hz KO/ SE 1 Hz KO comparisons. (E) Graphs show AE WT/NE WT, SE 1 Hz WT/NE WT, SE 5 Hz WT/ NE WT and SE 5 Hz WT/SE 1 Hz WT comparisons. The decrease is shown in blue and increase in orange. Significant clusters (p < 0.025) are highlighted by bold-lined contours (solid line depicts significant decrease and dotted line shows significant increase).

Fig. 6. Background power was reduced in the frontal cortex of P26-P28 mice following sound attenuation or exposure to sound with 5 Hz but not 1 Hz repetition rate.

(A, B) Graphs show grand averages of Single Trial Power (STP) during the upward chirp in the FC of NE WT (n=21), NE KO (n=14), AE WT (n=11), AE KO (n=16), SE 1 Hz WT (n=14), SE 1 Hz KO (n=16), SE 5 Hz WT (n=14) and SE 5 Hz KO (n=14) mice. (C) Graphs show differences between KO and their corresponding WT groups. (D) Graphs show AE KO/NE KO, SE 1 Hz KO/NE KO, SE 5 Hz KO/ NE KO and SE 5 Hz KO/ SE 1 Hz KO comparisons. (E) Graphs show AE WT/NE WT, SE 1 Hz WT/NE WT, SE 5 Hz WT/ NE WT and SE 5 Hz WT/SE 1 Hz WT comparisons. The decrease is shown in blue and increase in orange. Significant clusters (p < 0.025) are highlighted by bold-lined contours (solid line depicts significant decrease and dotted line shows significant increase).

Together, our data show that juvenile P26-P28 KO mice exhibit impaired timing of responses to frequency-modulated sounds, particularly low gamma oscillations, and increased background gamma power in both the AuC and FC similar to adult mice as well as humans with FXS. Sound attenuation and exposure to sound with 5 Hz but not 1 Hz repetition rate significantly reduced background gamma power during chirp presentation similar to the effects on the baseline gamma power without sound presentation.

Developmental exposure to sound trains with 1 Hz repetition rate had detrimental effects and further enhanced ongoing responses and decreased habituation to sound trains in both WT and KO mice.

The power of onset and ongoing responses during auditory stimulus presentation has been shown to increase in adult mice (Rais et al., 2022) and humans with FXS (Ethridge et al., 2016). Here, we assessed whether a similar phenotype occurs in P26-P28 NE WT and KO mice by quantifying responses to broadband noise. We compared evoked responses to trains of brief (100 ms) broadband noise stimuli (10 noise stimuli per train, 65–70 dB SPL, 100 repetitions of each train) and tested both a habituating rate of sound presentation (4 Hz repetition rate) and a non-habituating repetition rate (0.25 Hz) (Lovelace et al., 2016; Lovelace et al., 2020b). STP was measured for each repetition rate. Analysis was performed similar to chirp analysis.

We found that in the NE group, young P26–P28 KO mice exhibited an increase in the power of onset (0–50 ms) and ongoing (50–500 ms) responses to 4 Hz sound trains in the 20–40 Hz range in the AuC and FC compared to WT mice (Fig. 7A–C, D–F), suggesting hyperactivity and reduced habituation to repeated sound. We also observed a further increase in the power of responses in the high gamma range (60–100 Hz) in the AuC and FC of SE 1 Hz KO group compared to NE KO and AE KO groups (Fig. 7A–C). Although, in the 5 Hz KO group, the power of responses in the gamma range (20–100 Hz range) showed a non-significant trend towards a decrease compared to NE KO group, the responses were significantly lower than in the 1 Hz KO group (Fig. 7A–F). Similar trends in the effects of developmental sound exposure were observed in responses to non-habituating 0.25 Hz sound trains (Extended data, Supplemental Fig. 5).

Fig. 7. Developmental exposure to sound trains with 1 Hz repetition rate further enhanced power of onset and ongoing responses to 4 Hz sound trains in the AuC of both WT and KO mice.

(A, B) Graphs show grand averages of Single Trial Power (STP) during the upward chirp in the AuC of NE WT (n=21), NE KO (n=14), AE WT (n=11), AE KO (n=16), SE 1 Hz WT (n=14), SE 1 Hz KO (n=16), SE 5 Hz WT (n=14) and SE 5 Hz KO (n=14) mice. (C) Graphs show differences between KO and their corresponding WT groups. (D) Graphs show AE KO/NE KO, SE 1 Hz KO/NE KO, SE 5 Hz KO/ NE KO and SE 5 Hz KO/ SE 1 Hz KO comparisons. (E) Graphs show AE WT/NE WT, SE 1 Hz WT/NE WT, SE 5 Hz WT/ NE WT and SE 5 Hz WT/SE 1 Hz WT comparisons. The decrease is shown in blue and increase in orange. Significant clusters (p < 0.025) are highlighted by bold-lined contours (solid line depicts significant decrease and dotted line shows significant increase). The gray band indicates signals filtered out ~60 Hz to prevent electrical line interference. White triangles indicate sound presentations.

Previous studies in humans with FXS and Fmr1 KO mice also showed enhanced amplitude for N1 and P2 components of ERPs (Castren et al., 2003; Van der Molen and Van der Molen, 2013; Lovelace et al., 2018; Kulinich et al., 2020). To determine the effect of developmental sound exposure with different repetition rates, we calculated amplitudes and latencies of P1, N1 and P2 components of the ERP in response to 0.25 Hz and 4 Hz sound trains (Extended data, Supplementary Fig. 6, 7). Although we observed no significant genotype differences in the ERP amplitude, P1 and P2 amplitudes were reduced in AE and SE 5 Hz groups for both genotypes in the AuC and FC with similar effects also observed in the SE 1 Hz group in FC (Extended data, Supplementary Fig. 6A–F). In addition, we found genotype differences in N1 and P2 latencies in the AuC and FC of NE group with a decrease in the AuC and an increase in the FC of NE KO mice (Extended data, Supplementary Fig. 6G–L). Interestingly, both sound attenuation and sound exposure led to a similar increase in N1 and P2 latencies in both AuC and FC of WT and KO mice (Extended data, Supplementary Fig. 6G–L).

In summary, our findings show that NE KO mice exhibit a significant increase in overall power in the 20–40 Hz gamma range in response to sound trains with 0.25 and 4 Hz repetition rates in the AuC and FC compared to NE WT mice at P26-P28. Developmental exposure to sound trains with 1 Hz but not 5 Hz repetition rate further increases onset and ongoing responses to broadband noise in both WT and KO mice, whereas both sound exposures and sound attenuation have similar effects on ERP amplitude and latency.

Developmental exposure to sound trains with 5 Hz repetition rate normalizes exploratory behaviors, but not hyperactivity in Fmr1 KO mice.

Hyperactivity, anxiety and impaired social behaviors are among the most consistent behavioral symptoms in individuals with FXS (Tranfaglia, 2011). KO mice also display changes in exploratory behaviors and hyperactivity in open field and elevated plus maze tests, as well as impaired social behaviors in the three-chamber test (Dansie et al., 2013; Rais et al., 2022). Here, we examined the effects of developmental sound attenuation or exposure to sound trains with 1 Hz and 5 Hz repetition rates on hyperactivity, exploratory behaviors and sociability in WT and KO mice raised in different acoustic environments.

We observed that NE KO and AE KO mice spend significantly less time in thigmotaxis (Fig. 9A) and spend more time in the open field compared to their WT littermates during the first 5 min of testing (Fig. 9B). Developmental sound exposure to sound with 5 Hz but not 1 Hz repetition rate normalized their exploratory behavior, and SE 5 Hz KO spent more time in thigmotaxis and less time in open field compared to NE KO and AE KO mice and similar to NE WT (Fig. 10A–B). Interestingly, SE 5 Hz WT also exhibited increased time spent in thigmotaxis and made less time in open field than NE, AE and SE 1 Hz WT (Fig. 9A–B), suggesting that the effects of sound on these mouse behaviors are not specific to genotype. Further analysis of the open field test data showed genotype differences between WT and KO mice with higher velocity and overall distance traveled in KO groups. However, developmental sound exposure did not reduce hyperactivity, and SE 5 Hz KO mice displayed higher overall velocity and overall distance traveled than NE KO and AE KO (Fig. 9C–D). To assess social behaviors, we used a three-chamber test. We found no genotype differences in sociability and social novelty preference in NE group (Fig. 9E–H), however, sound exposure affected social preference to mouse (S1) compared to empty chamber (E) in SE groups (Fig. 9E, F). Exposure to both 1 Hz and 5 Hz decreased sociability in both WT and KO mice. SE groups showed no social preference between mouse and empty chamber and a decrease in sociability index compared to NE and AE groups (Fig. 9E, F). Interesting, effects of sound exposure on social novelty preference in KO mice was specific to SE 1 Hz group (Fig. 9G–H). SE 1 Hz KO mice showed no preference between novel (S2) and familiar mouse (S1), while SE 5 Hz KO mice showed normal preference to novel mouse. In summary, our findings show that developmental exposure to sound trains with 5 Hz, but not 1 Hz, repetition rate showed improvements in exploratory behaviors but not hyperactivity in KO mice. Furthermore, exposure to 1 Hz resulted in impaired social novelty preference behavior in KO mice.

Fig. 9. Developmental exposure to sound trains with 5 Hz repetition rate normalizes exploratory behaviors but not hyperactivity in KO mice.

(A-D) Graphs demonstrate the performance of NE WT (n=16), NE KO (n=16), AE WT (n=10), AE KO (n=21), 1 Hz, SE 1Hz WT (n=12), SE 1Hz KO (n=9), 5 Hz, SE 5Hz WT (n=14), and SE 5 Hz KO (n=11) mice in the open field test. Exploratory behaviors were evaluated by analyzing the percent time spent in thigmotaxis (A) and % time spent in open field (B) during the first 5 min. Hyperactivity was evaluated by measuring velocity and distance traveled (C, D) during 10 min. (E-H) Graphs demonstrate social interaction behaviors. Social preference (E) and sociability index (F) were evaluated by measuring the time spent with S1 mouse compared to the empty cage (E) during session 1 (10 min). Social novelty preference (G) and social novelty index (H) were evaluated by assessing the time spent with novel S2 compared to now familiar S1 mice (F) during session 2 (10 min). Statistical analysis was done using two-way ANOVA with a Tukey’s post-hoc test or uncorrected Fisher’s LSD test (for SNT): *, p < 0.05; **, p < 0.01. Black stars depict comparison between genotypes, red and blue stars depict comparisons to NE (blue for WT and red for KO); pound signs (#) depict comparisons to AE; plus signs (+) depict comparisons between SE 1 Hz and SE 5 Hz.

Fig. 10.

Schematic of main changes observed in KO mice after different acoustic exposures during the development. Left panel, KO mice raised in sound attenuated environment (AE) during the early development showed: 1) no changes in behaviors, such as exploratory and locomotor activity, sociability and social novelty preference; 2) decreased PV+ cell density and PV levels; 3) decreased cFos+ cell density; 4) reduced baseline gamma power and sound evoked background gamma powercompared to NE KO. Center panel, KO mice exposed to a sound with 1 Hz repetition rate displayed: 1) impaired sociability and social novelty preference; 2) increased PV+ cell density but not PV levels; 3) decreased density of cFos+ cells; 4) enhanced baseline and sound-evoked background gamma power; 4) compared to NE KO. No changes were observed in baseline delta power, exploratory behavior and locomotor activity. Right panel, KO mice exposed to 5 Hz sound showed: 1) normalized exploratory behavior; 2) enhanced locomotor activity; 3) increased PV+ cell density and PV levels; 4) decreased cFos+ cell density; 5) increased delta power; 6) reduced baseline and sound-evoked background gamma power compared to NE KO. Blue arrows depict decrease and red arrows depict increase, with filled arrows indicating unique change to the particular acoustic exposure. Wavy lines depict no changes.

Discussion

In this study, we explored whether acoustic exposure during development using sound trains with different repetition rates affect behaviors and cortical development in young WT and KO mice (Fig. 10). One of our most significant findings was that developmental exposure to sound trains with 5 Hz, but not 1 Hz, repetition rates normalized exploratory behaviors and improved social novelty preference, but did not correct hyperactivity in KO mice. We further showed that developmental exposure to a sound with 5 Hz, but not 1 Hz, repetition rate increased PV levels and decreased overall cFos expression in the auditory cortex of KO mice compared to control naïve KO mice. Next, we found that enhanced resting state gamma power and background power during chirp presentation were downregulated in the cortex of KO mice exposed to sound trains with 5 Hz, but not 1 Hz, repetition rates. Finally, while exposure to 5 Hz sound trains showed no significant effects on the power of onset and ongoing responses, exposure to 1 Hz worsened the phenotype by further enhancing ongoing responses and decreased habituation to sound in both WT and KO mice.

Although developmental sound attenuation and sound exposure to 5 Hz trains had similar effects on gamma oscillations, only developmental exposure to 5 Hz sound trains enhanced PV levels, increased delta oscillations and normalized exploratory behaviors in KO mice. Previous studies reported that KO mice exhibit several FXS-associated behavior alterations (Bernardet and Crusio, 2006), including exploratory behaviors, locomotor activity and sociability. Both young and adult KO mice display increased locomotor activity in open field and elevated plus maze (Qin et al., 2005; Dansie et al., 2013; Pirbhoy et al., 2020; Pirbhoy et al., 2021; Rais et al., 2022) and show more exploratory behaviors by spending less time in thigmotaxis and making more center entries (Dansie et al., 2013). In this study, while we see improvements in exploratory behaviors following the developmental exposure to sound trains with 5 Hz repetition rate, enhanced locomotor activity was observed in both WT and KO mice. Similar increase in locomotor activity was previously reported in mice exposed to noise (Lee et al., 2024) or environmental enrichment (Singhal et al., 2019). Other studies showed no effects of different music therapies on locomotor activity in mice (Fu et al., 2023; Cheng et al., 2024). Since sensory enrichment, particularly acoustic exposure, has been considered as therapy for ASD, our findings are especially important because we demonstrated further enhancement in locomotor activity following developmental acoustic exposure in both WT and Fmr1 KO mice.

Impaired social interactions are also common behavioral observations in FXS especially during development. KO mice were reported to display reduced preference for novelty in social settings (Sidhu et al., 2014; Rais et al., 2022). There are also reports showing no differences in social behaviors between adult KO and WT mice (McNaughton et al., 2008). This variability in findings might stem from the genetic backgrounds, mouse age and experimental protocols. In our study, we did not observe genotype differences in sociability and social novelty between young naïve WT and KO. Surprisingly, both 5 Hz and 1 Hz repetition rates affected the sociability of WT and KO mice. However, only developmental exposure to 1 Hz sound trains reduced social novelty preference specifically in KO mice, potentially suggesting harmful effects of this sound repetition rate. Environmental enrichment was reported to alleviate the social deficits in the mouse model of ASD (Binder and Bordey, 2023) and music-based intervention improved social novelty in mice with Rett syndrome (Hung et al., 2021). Interestingly, noise exposure can increase social preference in zebrafish (Vasconcelos et al., 2023). Therefore, sensory intervention can have various effects on social behaviors depending on the type of sensory modality and animal model used in the study.

Animal studies has shown that sensory exposure can result in number of morphological and molecular alterations, potentially underlying changes in neuronal functions and ultimately behavior (Alwis and Rajan, 2014). For example, repetitive visual stimulation can increase the efficiency of the V1 neuronal circuitry by reducing the number of responsive neurons and dendritic spine density (Lopez-Ortega et al., 2024). Likewise, acoustic enrichment during development alters auditory cortex response selectivity in rats (Pysanenko et al., 2018), including reduced response magnitudes, that persist into adulthood. Since 1 Hz and 5 Hz repetition rates had differential effects on the mouse behavior we further examined if there were any differences observed at the cellular and molecular levels. The first main finding was that sound exposure affects PV cell density and PV protein levels in the AuC of KO mice. PV cells are GABAergic interneurons that are crucial for sensory cortical plasticity during development and adulthood (Rupert and Shea, 2022). We observed that PV cell density was also lower in the AuC of C57Bl6 background KO mice compared to their WT littermates raised by heterozygote dams in sound attenuated environment. These findings are similar to our previous work in FVB background Fmr1 KO mice raised by KO dams in sound attenuated environments (Kulinich et al., 2020). The fact that we still see a decreased PV+ cell density in KO mice independent of the mouse background and upbringing indicates a robust effect of sound attenuation on PV cells in the AuC. While we observed that sound exposure to both 1 Hz and 5 Hz repetition rates increases PV+ cell density, only 5 Hz KO showed a significant increase in the proportion of cells expressing higher PV levels and overall PV protein levels in the AuC.

PV cells are protected by PNNs from oxidative stress (Cabungcal et al., 2013). Similar to our previous study showing a significant decrease in the density of PNN-containing PV cells in KO mice (Wen et al., 2018), we found decreased PNN+ cell density in the AuC of KO. Developmental exposure to both sound trains with 1 Hz and 5 Hz repetition rates further decreased the density of PNN+ cells and PNN levels in the AuC. PNN formation is activity dependent (Dityatev et al., 2007) and alterations in GABAergic transmission were reported to affect PNN levels and promote cortical plasticity (Hensch, 2005; Harauzov et al., 2010; Sale et al., 2010). PNNs also regulate critical period plasticity (Pizzorusso et al., 2002), which is impaired in the auditory cortex of KO mice (Kim et al., 2013). Previous studies suggest a role for increased activity of matrix metalloproteinase-9 (MMP-9) in the generation of cortical hyper-responsiveness during AuC development (Wen et al., 2018; Pirbhoy et al., 2020). MMP-9 is an endopeptidase that cleaves PNN proteins, including aggrecan (Pollock et al., 2014; Reinhard et al., 2015), and therefore likely to be involved in the normal development and plasticity of PNNs. MMP-9 is a translational target of FMRP (Janusz et al., 2013) and in the absence of FMRP, there is increased activity of MMP-9 across multiple brain regions and developmental periods in KO mice (Sidhu et al., 2014; Wen et al., 2018; Kokash et al., 2019). Increased MMP-9 levels and activity were also observed in FXS human samples (Gkogkas et al., 2014; Sidhu et al., 2014) and linked neural circuit deficits to MMP dysregulation in the drosophila model of FXS (Siller and Broadie, 2011). Noise exposure can increase MMP-9 expression impacting PNN expression in the primary auditory cortex (Park et al., 2020). PNNs increase excitability of rapid-spiking (putative PV) neurons and its loss can affect inhibition (Balmer, 2016). On the other hand, transient inhibition of PV-expressing cells can trigger local changes PNN density as well (Devienne et al., 2021). While we see positive effects of developmental acoustic exposure on PV levels, noise exposure has been shown to have detrimental effects on both PNN and PV expression (Nguyen et al., 2017; Liu et al., 2018; Masri et al., 2021). Some mechanisms linked to synaptic and cortical plasticity, such as BDNF-TrkB signaling, can be potentially involved in sound-evoked changes as well (Wang et al., 2011; Kulinich et al., 2020). There is emerging interest in manipulating PV cell activity as a potential treatment for FXS, and currently pharmacological approaches are used (Pirbhoy et al., 2020; Kourdougli et al., 2023). Our data indicate that developmental acoustic exposure regulates PV levels and cortical activity which could be used as a non-pharmacological therapeutic approach.

To examine whether the changes in PV+ cell density following developmental sound exposure affected overall neuronal activity we assessed the levels of cFos, an early response gene that is used as a neuronal activity-dependent marker (Morgan et al., 1987; Guzowski et al., 1999). Although sound attenuation affected the number of PV+ cells, it also reduced overall neuronal activity as marked by lower density of cFos+ cells. While developmental exposure to sound with 1 Hz repetition rate also showed a decrease in the density of cFos+ cells, sound with 5 Hz repetition rate further affected overall neuronal activity as we observed an additional decrease in the number of cFos+ cells compared to AE and SE 1 Hz groups. Previous studies showed that cFos cell density is increased in the AuC of adult KO mice (Rais et al., 2022) and it is significantly higher in the inferior colliculus of young KO mice following the sound presentation (Nguyen et al., 2020a). In addition, studies show that increased cFos expression in the medial prefrontal cortex is associated with hyperactivity and impulsive behaviors (Xie et al., 2020), and environmental enrichment can improve ADHD-like behaviors by suppressing neuronal activity (Utsunomiya et al., 2022). Our data suggest that developmental sound exposure using a specific repetition rate can modulate neuronal activity in the auditory cortex and potentially affect FXS-associated EEG phenotypes in the mouse model of FXS.

We observed that developmental exposure to a sound with 5 Hz but not 1 Hz repetition rate normalizes low resting gamma power in the AuC and FC of KO mice at the baseline and during sound presentation. Increased low gamma power has been reported in the young and adult KO mice (Lovelace et al., 2018; Pirbhoy et al., 2020). Increased gamma power was also reported in rat models of FXS (Kozono et al., 2020) and FXS humans (Ethridge et al., 2017; Wang et al., 2017). Accumulating evidence suggests that increased resting state gamma power is associated with sensory processing and communication deficits in FXS and ASD (Ethridge et al., 2017; Sinclair et al., 2017; Wang et al., 2017; Lovelace et al., 2018; Ethridge et al., 2019; Lovelace et al., 2020b). As abnormal PV neuron function can lead to a broadband gamma power increase (Guyon et al., 2021), the aberrant gamma responses in the EEG signals may reflect abnormal development and function of PV-expressing GABAergic interneurons in the KO mouse cortex (Wen et al., 2018). Although, it is possible that increased PV levels following the developmental exposure to sound with 5 Hz repetition rate may underlie the changes in gamma power in KO mice, sound attenuation showed similar changes in gamma power while reducing PV cell density, particularly the number of cells with high PV expression. Our data show that the changes in PV cell density may not be the only cellular change responsible for the enhanced resting gamma power that is also observed in both human and rodent models of FXS.

Besides changes in gamma power we also found that developmental sound exposure affected power of oscillations in alpha, beta and delta frequencies. Human studies suggest that alpha power contributes to underlying hyperexcitability (Van der Molen and Van der Molen, 2013) and delta was reported to be increased in individuals with ADHD (Barry et al., 2009). In addition, beta power was demonstrated to be reduced in KO rats (Kozono et al., 2020). Here, we found a decrease in alpha power in the FC of KO mice, but exposure to 1 Hz, not 5 Hz, increased alpha and beta power. In contrast, sound exposure to 5 Hz, but not 1 Hz, increased delta power in both WT and KO. EEG studies in humans showed an inverted U-shaped pattern of power abnormalities with reduced alpha frequencies and increased delta, theta, beta and gamma frequencies in children with ASD (Wang et al., 2013; Sinclair et al., 2017). Previous studies also demonstrated impaired low/high frequencies power coupling in young and adult KO mice (Pirbhoy et al., 2020; Pirbhoy et al., 2021). Our studies showed no differences in low to high EEG power coupling between genotypes, however, exposure to both 1 Hz and 5 Hz repetition rates increased power coupling between frequencies within and across the regions. Overall, our findings indicate the developmental exposure to 1 Hz and 5 Hz sound trains differentially affected resting state EEG power.

In our study we also found beneficial effects of developmental sound attenuation and exposure to 5 Hz sound trains on background power during chirp presentation in both AuC and FC of both genotypes. Although naïve P26-P28 KO mice showed a reduced ability to synchronize stimulus-induced oscillations in 20–40 Hz range in the AuC and 40–60 Hz range in the FC, similarly to previous study in young and adult KO mice (Lovelace et al., 2018; Pirbhoy et al., 2020), we observed only improvements in the FC of KO mice following sound attenuation. Improvements in the ability to phase-lock to frequency-modulated sound were earlier reported in mice after the treatment with MMP-9 inhibitor SB3-ST (Pirbhoy et al., 2020), minocycline (Lovelace et al., 2020a) and Fmr1 gene re-activation (Rais et al., 2022). Future study will show if combination of non-invasive developmental exposure to a tone with pharmacological treatment can be a beneficial therapeutic approach in correcting functional alterations in FXS.

Previous studies in the adult mouse auditory cortex also showed enhanced responses to tones (Rotschafer and Razak, 2013) and reduced habituation of ERPs to repeated sounds in KO mice (Lovelace et al., 2016). Here, we found that naive P26-P28 KO mice also exhibit a significant increase in onset and ongoing overall power to broadband noise in the gamma range in response to sound trains with 0.25 and 4 Hz repetition rates in the AuC and FC. Although we found no improvements in all sound exposure groups, developmental exposure to sound trains with 1 Hz repetition rate further increased onset and ongoing responses in KO mice. We also found that developmental sound attenuation as well as exposure to 1 Hz and 5 Hz tones overall decreased ERP amplitudes and increased ERP latencies in the AuC and FC of both WT and KO in response to both 0.25 Hz and 4 Hz tone. Increased auditory N1 and P2 ERP components were reported in humans with FXS (Castren et al., 2003; Knoth et al., 2014; Ethridge et al., 2019; Ethridge et al., 2020) and elevated P1, N1, P2 amplitude and increased P2 latency were observed in adult KO mice (Wen et al., 2019; Jonak et al., 2020; Croom et al., 2023). It is unclear how the effects on amplitude and latency of cortical responses may affect mouse behaviors.

In this study, we observed differential effects of developmental exposure to sound trains with 1 Hz and 5 Hz repetition rates on cortical activity and mouse behaviors. These differences might arise from the changes in cortical temporal response properties. Several studies show the effects of the stimulus repetition rate and frequencies in the auditory cortex (Nakahara et al., 2004). For instance, the important role of patterned acoustic inputs for critical period plasticity was shown for A1 cortical field in both spectral and temporal domains (Zhou and Merzenich, 2008). Rats reared to noise repeated at 4–5 Hz repetition rates (4–5 events per second) displayed reduced cortical representation of higher repletion rates and reduced synchronization of cortical responses to the higher repetition rates (Zhou and Merzenich, 2008). Another study showed that exposures to pulsed tones of a specific frequency resulted in over-representation of that frequency and broader-than normal receptive fields in A1cortical field (Zhang et al., 2001). Interestingly, exposure to temporally modulated white noise resulted in degradation of tonotopic re-organization of A1 and closure of critical period plasticity (CPP) (Zhang et al., 2002; Zhou and Merzenich, 2007), while exposure to continuous white noise affected spectral and temporal response selectivity and delayed CPP closure for A1 development (Chang and Merzenich, 2003; Chang et al., 2005; Zhou and Merzenich, 2008). As PV cells play a crucial role in sensory cortical plasticity (Rupert and Shea, 2022), future studies are needed to examine whether developmental sound exposure to a tone with 5 Hz or higher 40 Hz repetition rate also affect sensory cortical plasticity in FXS.

In conclusion, we have shown that developmental sound exposure to 14 Hz pure tones with 5 Hz but not 1 Hz repetition rate might have beneficial effects on PV cell development, neural oscillatory patterns and some behaviors associated with FXS. These findings implicate that manipulating the acoustic environment during development might be a possible approach to alleviate FXS-related phenotypes. There is growing interest in the use of sound-based interventions in alleviating autism-related symptoms (Gee et al., 2014; Weitlauf et al., 2017), and our study provides novel data in an animal model of ASD that this approach carries promise and needs further investigation to optimize. Given that hypersensitivity to sounds is a common and debilitating issue in FXS, our initial hypothesis that development in a sound-attenuated environment will improve symptoms was not supported. Rather, a 5 Hz tone exposure during development showed most improvement in cellular, electrophysiological and behavioral effects. One limitation of current study is inclusion of only male mice. The effect of acoustic exposure in females should be investigated in future study. Another potential direction of future study is investigating the long-term effects of developmental sound exposure and the effects of adult sound exposure on mouse behavior and cortical functions.

Fig. 8. Developmental exposure to sound trains with 1 Hz repetition rate further enhanced power of onset and ongoing responses to 4 Hz sound trains in the FC of both WT and KO mice.

(A, B) Graphs show grand averages of Single Trial Power (STP) during the upward chirp in the FC of NE WT (n=21), NE KO (n=14), AE WT (n=11), AE KO (n=16), SE 1 Hz WT (n=14), SE 1 Hz KO (n=16), SE 5 Hz WT (n=14) and SE 5 Hz KO (n=14) mice. (C) Graphs show differences between KO and their corresponding WT groups. (D) Graphs show AE KO/NE KO, SE 1 Hz KO/NE KO, SE 5 Hz KO/ NE KO and SE 5 Hz KO/ SE 1 Hz KO comparisons. (E) Graphs show AE WT/NE WT, SE 1 Hz WT/NE WT, SE 5 Hz WT/ NE WT and SE 5 Hz WT/SE 1 Hz WT comparisons. The decrease is shown in blue and increase in orange. Significant clusters (p < 0.025) are highlighted by bold-lined contours (solid line depicts significant decrease and dotted line shows significant increase). The gray band indicates signals filtered out ~60 Hz to prevent electrical line interference. White triangles indicate sound presentations.

Highlights.

1. Developmental sound exposure corrects exploratory behaviors, but not hyperactivity

2. 1 Hz and 5 Hz sound trains differentially affect auditory cortex development

3. Acoustic exposure to 5 Hz trains normalizes EEG phenotypes and PV expression

4. 1 Hz sound trains exacerbate EEG deficits and impair social preference in mice

5. Sound attenuation improves EEG phenotypes but not PV levels or mouse behaviors