Erbb4 ^{f/f;Pet1-Cre;Ai9f/+} were generated by breeding Pet1-Cre (Fev-Cre) lines (JAX stock #012712; RRID:MGI:3696982) (Scott et al., 2005) with mice carrying the loxP-flanked (f) Erbb4 alleles (Golub et al., 2004) and Ai9/tdTomato lines (JAX stock #007909; RRID:MGI:J:155793) (Madisen et al., 2010). Control mice included mice carrying Pet1-Cre or Erbb4^f/f alleles. All animal procedures were approved by the Ethics Committee (CIPF, Spain) and complied with the Spanish and European regulations for the use of laboratory animals.

Mice (postnatal day P60–90) were transcardially perfused with 4% PFA, post-fixed for 2 h and sectioned with a freezing microtome. Immunohistochemistry for 5HT, ErbB4 and tdTomato was performed in 40 µm-thick sections using the following primary antibodies: rabbit anti-ErbB4 (0618 produced by Cary Lai), goat anti-5HT (Abcam 66047 (1:1,000), rabbit anti-5HT (1:5,000, Sigma #S5545, RRID:AB_477522) and rabbit anti-RFP (1:2,000, Rockland Cat# 600-401-379, RRID:AB_2209751). Secondary antibodies and Alexa555-conjugated streptavidin were purchased from Molecular Probes. Subsequently, sections were counterstained with DAPI and mounted with Mowiol. For the reconstruction of biocytin-filled neurons during ex vivo electrophysiology, 300 µm-thick brain sections were fixed overnight in 4% PFA at 4°C and incubated with Alexa488-conjugated streptavidin (1:500, Thermo Fisher Scientific Cat# S11223, RRID:AB_2336881).

Imaging of fluorescently labelled axonal arbors in target regions of the serotonergic system was performed with 20X 0.80NA objective in an Aperio Versa slide scanner (Leica Biosystems) or with the DMI-4 SP8 confocal microscope (Leica Biosystems). Following the neuroanatomical features (Franklin and Paxinos, 2008) in DAPI counterstained brain sections, images of 1,500 × 1,500 pixels (for the lateral hypothalamus, periventricular nucleus of the thalamus or corpus callosum) or manually delimited brain regions (for the dentate gyrus, CA3 and CA1) were extracted from two single z-planes per area and from 3 areas per mouse in ImageScope (Leica Biosystems). The percentage of area occupied by fluorescent signal was performed in Fiji/ImageJ (RRID:SCR_002285) applying the same threshold over the background for all genotypes. For analysis of relative density of fluorescently labeled fibers, a threshold of 30 and 50 arbitrary units of intensity over the background was applied in images acquired with AperioVersa and with the confocal microscope, respectively. Background signal was quantified from 3 different regions of the field of view without tdTomato+ neuropil labelling. For cell counting, colocalization analysis and morphological reconstruction of biocytin-filled neurons, images were acquired with a 20X 0.75NA objective in a DMI-4 SP8 confocal microscope (Leica Biosystems). Colocalization was quantified from two different optical planes per section. For analysis of fluorescence intensity, images were acquired at 16bit depth. For neural tracing and morphological reconstruction, stacks were acquired at 1 µm step size and the SNT 3.1.109 tool of Fiji/ImageJ was employed (Arshadi et al., 2021).

Erbb4 ^{+/+;Pet1-Cre;Ai9f/+} and Erbb4 ^{f/f;Pet1-Cre;Ai9f/+} male mice (12–13 weeks-old) were used. First, mice were anaesthetized with isoflurane and perfused with ice-cold artificial cerebrospinal fluid (aCSF) medium containing (in mM): 87 NaCl, 25 NaHCO₃, 5 D-(+)-glucose, 65 sucrose, 2.5 KCl, 1.25 NaH₂PO4, 0.5 CaCl₂, 7 MgCl₂, 5 ascorbic acid and 3.1 pyruvic acid saturated with 95% CO₂ and 5% O₂(pH 7.4). Then, mice were decapitated and brain was removed and placed in oxygenated aCSF. 300-µm coronal slices were obtained with a vibratome (Microm HM 650 V) and transferred to a chamber with aCSF solution consisting of: 125 NaCl, 25 NaHCO₃, 25 D-(+)-glucose, 2.5 KCl, 1.25 NaH₂PO₄, 2 CaCl₂, 1 MgCl₂, 1 ascorbic acid and 4 pyruvic acid saturated with 95% CO₂ and 5% O₂ (pH 7.4). Slices were allowed to recover at 35°C for 30 min. Patch clamp recordings in whole-cell configuration were performed at 25°C using a potassium gluconate-based intracellular solution containing (in mM): 135 K-gluconate, 10 HEPES, 10 Na-phosphocreatinine, 4 KCl, 4 MgATP, 0.3 NaGTP and adjusted to 290mosmol/l and pH7.2–7.4. Biocytin was added to the internal solution at a concentration of 1.5–2.5 mg/ml for post hoc immunohistochemistry. tdTomato expressing neurons were visualized with an upright microscope (Olympus BX51WI; RRID:SCR_018949) equipped with an ORCA-ER CCD Camera (Hamamatsu), a 40X/0.8 nA water-immersion objective (Olympus), a X-Cite 120Q fluorescence lamp and infrared-differential interference optics contrast for bright field imaging. Micro-pipettes of 10–12 MΩ were pulled from borosilicate glass using a vertical P-10 puller (Narishige). Data was acquired and sampled at 20 kHz using a MultiClamp 700B (Molecular Devices, RRID:SCR_018455), a digitizer Digidata 1440A (Molecular Devices, RRID:SCR_021038) and pClamp software (Molecular Devices, RRID:SCR_011323).

Intrinsic electrophysiological properties were calculated using different current-clamp protocols. Resting Membrane Potential (V_rest) was measured after breaking into the cell. Input Resistance (R_in) was obtained using 500 ms hyperpolarizing current steps of ∆5 pA from −20 to 0 pA. Rheobase, action potential kinetics and input-output function were measured by applying 500 ms depolarizing current steps of ∆ 10 pA from 0 to +180 pA in neurons held at −70 mV. EasyElectrophysiology software (EasyElectrophysiology Ltd., RRID:SCR_021190) (Garcia et al., 2014) was used for the analysis of electrophysiological properties. Threshold potential was defined as dV/dt = 10 mV/ms using first derivative method. AP threshold was defined in a region of 10 ms before peak. Rise and decay time were determined in a minimum-maximum cutoff percentage of 10–90%. Half-width is calculated as the time between rise and decay at half amplitude. fAHP was detected in a search region of 0–9 ms after peak and mAHP in a region of 30–70 ms. Both values were calculated as baseline minus the minimum value within each region. Rheobase was defined as the minimum current injected to obtain the first AP from neurons held at −70 mV. Maximum firing frequency was obtained from spike frequency discharge upon +190 pA current injected. Inter-spike interval (ISI) was calculated as the difference between first and second AP at first step with ≥2AP. Spike frequency adaptation was obtained by dividing the first ISI by the final ISI of the trace with ≥4AP. Input-output curve was plotted averaging the number of AP detected for each neuron at each current step.

Adult Erbb4 ^f/f and Erbb4 ^f/f;Pet1-Cre male and female littermates (P60) were used for behavioral tests. Mice were maintained under standard housing conditions in 12 h dark/light cycles with food and water ad libitum. All different tests were implemented during the light phase blind to the genotype. Mice were handled and habituated to the experimenter for 3 days before the behavioral assays. All behavioral tests were separated at least by 24 h. The order of tests was as follows: open field, habituation to open field, Y-maze, sociability test, elevated plus maze (EPM), dark-light box and nest building test. Contextual fear conditioning, prepulse inhibition of the startle response (PPI), forced swimming and tail suspension test were performed in separated batches of animals. Testing apparatuses were cleaned with a solution of 70% ethanol in water after each trial to avoid olfactory cues. Behavioral tasks were recorded with a Logitech C270 webcam HD camera and analysed using Ethovision® XT software (Noldus, RRID:SCR_000441) unless otherwise stated.

Dataset were downloaded from NCBI database (GSE135132) from Ren et al. (2019) article. RStudio (R version 4.0.2, RRID:SCR_001905) software was used for assessing scRNAseq analysis. Seurat package (version 4.0.1, RRID:SCR_016341) was used for performing filtering, highly-variable gene-selection, dimensionality reduction and clustering. Cells with fewer than 300 detected genes and genes detected in fewer than 3 cells were removed from original datasets for following analysis. SCTransform function was used for normalization, scale and detection of variable genes. Counts were log-normalized using the natural logarithm of 1 + counts per million [ln (CPM+1)]. PCA, tSNE and UMAP dimensional reductions were performed considering significant dimensions. Clusters were defined based on shared nearest neighbor (SNN) using FindClusters function considering PCA dimensional reduction. Pet1 (Fev) and Erbb4 transcripts in the datasets were visualized using FeaturePlot function of tSNE reduction. The percentage of Pet1 cells expressing Erbb4 was determined used custom function. Erbb4 transcripts in Pet1 cells was plotted using VlnPlot function.

Statistical analyses were carried out with the GraphPad Prism 9 software (RRID:SCR_002798) and with R programming. The study of the coordinates (Euclidean distance and nearest neighbor distance) and principal component analysis were performed with R. All data are presented as mean ± SEM. Biological replicas (N values) are different animals (behavior and immunohistochemistry) or cells from >3 different brains (electrophysiology) derived from >3 different litters. Statistical methods were used to predetermine the sample size. Randomization was not used. Experiments and analyses were performed blind to genotype by two different experimentalists. Differences were considered significant when p < 0.05 (*), p < 0.01 (**) or p < 0.001 (***). The data were analyzed with parametric tests (Student’s t test or ANOVA), when the datasets fulfilled the assumptions of normality (Kolmogorov-Smirnov test) and homoscedasticity (Levene’s test). Non-parametric tests for independent groups or Mann-Whitney test were applied when normality was not reached and Kolmogorov-Smirnov test was used when comparing probability distributions. Statistical analysis of the majority of experiments included the sex perspective except when appropriately indicated. For this purpose: animals of both sexes were included in the samples of each experiment. Pooled analysis for both sexes was carried out after performing stratified analysis by sex and validating that the patterns of data distribution were common in males and females.

To understand whether ErbB4 is involved in serotonergic circuit development, we employed mouse genetics to label serotonergic neurons with a fluorescent protein tdTomato reporter controlled by a Cre recombinase driven by Pet1 promoter (tdTomato ^{f/+; Pet1 -Cre mice}, hereafter named Pet1-reporter mice) (Figure 1A), a determinant of serotonergic fate (Hendricks et al., 1999). Pet1-reporter mice allow the specific genetic targeting of a major population of serotonergic neurons within the raphe nuclei (Figure 1B) as shown by colocalization analysis between tdTomato and 5HT in the dorsal raphe nucleus (DRN) (86 ± 2% 5HT+ among Pet1+tdTomato+ cells) (Figures 1C,D) (77 ± 3% of Pet1+tdTomato+ among 5HT+ cells) (data not shown).

We then evaluated whether serotonergic neurons from the Pet1 lineage express ErbB4. Erbb4:CreERT2 reporter mice suggest ErbB4 expression in approximately 20% of 5HT neurons in the DR (Bean et al., 2014; Zhang et al., 2020). To validate this finding in situ at protein level, we employed immunohistochemistry with a previously validated anti- ErbB4 antibody (Zhu et al., 1995; Del Pino et al., 2013) in Pet1-reporter mice (Figure 1E). Quantification of percentage of ErbB4-expressing neurons within the Pet1+tdTomato+ cells showed that a subset of Pet1+ cells colocalized with ErbB4 in the DRN (39%) and similar percentages of colocalization were observed in each of the DRN subregions (DRD: 43%; DRV: 37%; DRL: 38%) and in the MRN (B8) (37%) (Figure 1F). In addition, to elucidate whether Pet1+ErbB4+ are serotonergic, we performed immunohistochemistry for 5HT as well as ErbB4 onto Pet1-reporter mice (Supplementary Figure S1). Quantifications Pet1+/ErbB4+/5HT+ and Pet1+/ErbB4+/5HT- neurons revealed that 95 ± 2% and 85 ± 5% of Pet1+ErbB4+ cells are serotonergic in the DRN and MRN respectively (Supplemetary Figure S1). These data suggested that ErbB4 is present in the DRN/MRN and marks a subpopulation of Pet1+ serotonergic neurons. Notably, ErbB4 neurons that are Pet1-negative and express 5HT can be found intermingled with Pet1-positive neurons (data not shown), suggesting that Pet1+ErbB4+ cells represent a subset of ErbB4-expressing serotonergic population.

Next, we aimed to better characterize the molecular identity of adult ErbB4+ serotonergic neurons taking advantage of transcriptomic data from recent single cell RNAseq of adult Sert and/or Pet1-expressing serotonergic neurons (Okaty et al., 2020; Ren et al., 2019). From 999 to 2,350 sequenced cells expressing Sert and/or Pet1 in the Ren et al., 2019 (Ren et al., 2019) and Okaty et al., 2020 studies, respectively, Erbb4 transcripts where detected in 15 and 37% of all cells (Figure 1; Supplementary Figure S2). Importantly, cells displaying Erbb4 transcripts are not randomly distributed in the tSNE representation but locate mostly in four out of 13 clusters from the Ren et al., 2019 dataset (Figures 1G–J) and eight out of 14 clusters from the Okaty et al., 2020 dataset (Supplementary Figure S2). In addition, a close inspection of the molecular identity of Pet1-expressing neurons clustered by scRNAseq of the Ren et al., 2019 study (Ren et al., 2019) (Supplementary Figure S3), suggests that ErbB4-expressing neurons belong to clusters mapping to both the DRN as well as MRN. Specifically, Erbb4 transcripts are present in cells from the cluster expressing the Iruquois Homeobox 2 (Irx2) and Tachykinin3 receptor (Tacr3) which was mapped to MRN in the original study (Ren et al., 2019) (Supplementary Figure S3A). In agreement with this, we performed a colocalization analysis between Pet1+tomato+ and ErbB4 immunolabelled neurons and found that 22 ± 4% Pet1+ were ErbB4+ in the MRN (data not shown). These data strongly suggest that ErbB4 expression, despite being anatomically distributed throughout the different regions of the DRN and MRN, correspond to specific 5HT molecular subtypes of neurons.

Having identified that ErbB4 is expressed in a subset of adult DRN Pet1+ neurons, we examined whether ErbB4 is involved in serotonergic circuit development. To address the contribution of ErbB4 to serotonergic system formation, we generated ErbB4 ^{f/f;Pet1-Cre;Ai9f/+} mice (hereafter named ErbB4cKO mice) in which the exon 2 of the Erbb4 gene, is excised in serotonergic neurons since early fate specification using the Pet1-Cre-recombinase (Figure 2A). By performing immunohistochemistry against ErbB4 and quantifying the colocalization between Pet1+tdTomato+ cells and ErbB4 expressing cells, we observed a robust reduction in the percentage of Pet1+tdTomato+ neurons displaying high immunofluorescent signal for ErbB4 in the adult DRN in Erbb4cKO mice when compared to controls (Erbb4 ^{+/+;Pet1-Cre;Ai9f/+} mice) (control: 37 ± 8%; Erbb4cKO: 1 ± 0.2% ErbB4+ among tdTomato+ cells; p = 0.003) (Figures 2B,C), showing that in vivo Erbb4-deficiency in serotonergic neurons can be efficiently achieved with this genetic strategy.

The ligands of ErbB4, Neuregulin 1 (Nrg1) and Neuregulin 3 (Nrg3), mediate long and short-range attraction of migrating GABAergic interneurons expressing ErbB4 in the forebrain (Zhang et al., 1997; Flames et al., 2004; Bartolini et al., 2017). Recent studies suggest that Nrg3 is expressed in the roof plate early during morphogenesis E9–E11 (La Manno et al., 2021). At E9–E11, serotonergic neurons migrate from the ventricular zone close to the floor plate to the medial hindbrain (Hawthorne et al., 2010). Thus, we asked whether NRG/ErbB4 signaling would be involved in the migration and final cellular allocation of serotonergic neurons within the raphe nuclei. To tackle this question, we quantified the total number of Pet1-driven tdTomato+ cells in three different coordinates across the dorsal-caudal axis of the DRN corresponding to two different rostro-caudal levels of the B7 nucleus and the rostral B6 and MRN (B8). We observed that the total number of tdTomato+ neurons was not significantly different between control and Erbb4cKO mice at any of the neuroanatomical coordinates (p > 0.05, t-test) (Figures 2D,E,G,H,J,K; Supplementary Figure S4), indicating that migration and survival of serotonergic neurons is not affected by loss of ErbB4. In addition, cellular distribution of Pet1+ serotonergic neurons in the DRN and MRN was assessed by obtaining the spatial coordinates of each tdTomato+ cell within the DRN and MRN, respectively and calculating the distance from each tdTomato+ cells to its nearest neighbor (nearest neighbor distance or NND) at each coordinate. Spatial distributions were compared in cumulative fractions of NND for each population and did not reveal significant differences for any of the three neuroanatomical coordinates analyzed between control and Erbb4cKO mice (p > 0.05, Kolmogorov-Smirnov test) (Figures 2F,I,L) (Supplementary Figure S4). Altogether these data suggested that ErbB4 is dispensable for Pet1+ serotonergic neurons to migrate and allocate in the DRN and MRN (B8).

In addition to migration, NRG/ErbB4 signaling participates in axon navigation and synaptogenesis during embryonic and postnatal development in local and long-range projecting neural circuits within the forebrain (Lopez-Bendito et al., 2006; Fazzari et al., 2010; Del Pino et al., 2013; Del Pino et al., 2017). Therefore, we hypothesized that ErbB4 might be necessary for the development of long-range efferent serotonergic connectivity. To test this hypothesis, we monitored in adult control and Erbb4cKO the serotonergic axon arborization across different postsynaptic targets of the serotonergic system: the retrosplenial granular cortex (RSGc), the hippocampus (DG, CA1, and CA3), the posterior periventricular nucleus of the thalamus (PVT) and the lateral hypothalamus (LH) (Figures 3A,B). We observed that serotonergic axons labelled with tdTomato were present in all regions (RSGc, DG, CA3, CA1, PVT, and LH) in control as well as Erbb4cKO mice (Figures 3C–J; Supplementary Figure S5). To assess the density of terminal arborization from serotonergic connectivity, we quantified the area occupied by tdTomato+ signal normalized to a field of view/total area in each brain region (Figure 3C). Non-significant differences in axonal density were observed between control and Erbb4cKO in RSGs (control: 1.43 ± 0.31%; Erbb4cKO: 1.15 ± 0.20%; p = 0.446) (Figures 3D,E), hippocampus (control DG: 19.92 ± 1.74%; Erbb4cKO DG: 12.32 ± 1.44%; p = 0.630; control CA3: 1.8 ± 0.2%; Erbb4cKO CA3: 2.3 ± 0.4%; p = 0.509; control CA1: 1.2 ± 0.2%; Erbb4cKO CA1: 1.3 ± 0.2%; p = 0.28; (Figures 3F,G; Supplementary Figure S5); and LH (control: 30.26 ± 3.29%; Erbb4cKO: 33.14 ± 3.71%; p = 0.568) (Figures 3J,K). In contrast, Erbb4cKO mice displayed significantly reduced axonal density in the PVT region when compared to controls (control: 7.8 ± 1.0%; Erbb4cKO: 7.1 ± 1.0%; p = 0.0025) (Figures 3H,I). These results obtained with epifluorescence imaging were reproduced in the PVT using confocal microscopy (Supplementary Figure S6) (control: 13.5 ± 1.0%; Erbb4cKO: 7.5 ± 0.7%; p = 0.0002). Thus, our data suggest that, while global serotonergic connectivity arriving to the LH or to other cortical targets (i.e. hippocampus and RSGc) is not dependent on ErbB4 expression, ErbB4 is required for the axonal arborization of a subpopulation of Pet1+ serotonergic projections reaching the PVT area.

Since serotonergic branching is regulated by serotonin levels during brain development (Migliarini et al., 2013) we investigated whether the serotonergic connectivity deficits observed in the PVT region in Erbb4cKO mice could arise from changes in 5HT expression within the DRN. Immunohistochemistry against 5HT and colocalization analysis between 5HT+ and tdTomato+ cells did not reveal significant differences between the number of Pet1+ neurons expressing 5HT in controls and Erbb4cKO mice (control: 88.29 ± 3.90%; Erbb4cKO: 81.55 ± 2.11; p = 0.155) (Figures 4A–C). Quantification of 5HT signal intensity measured within Pet1+ neurons followed a similar distribution in controls and Erbb4cKO mice (p > 0.05; Kolmogorov-Smirnov test) (Figure 4D), indicating that ErbB4 deletion does not affect global 5HT content in the DRN.

To further understand whether developmental deletion of ErbB4 in serotonergic cells alters the excitability of the DRN, we probed the intrinsic electrophysiological properties of tdTomato+ neurons in acute brain slices of controls and Erbb4cKO mice. Through whole-cell patch-clamp recordings performed in adult tdTomato+ neurons within the DRN (Figure 4E), we observed that the majority of neurons exhibited spike frequency adaptation (73% in control [11 of 15 recorded cells]; 84% in mutant [16 of 19 recorded cells]). For comparison of intrinsic properties, we explored whether neurons recorded belonged to a similar neural subtype. We examined the morphology of neurons recorded by performing post hoc histochemistry against biocytin-filled tdTomato+ neurons. Sholl analysis of neuronal morphology did not reveal significant differences between control and Erbb4cKO mice (p > 0.05; two-way ANOVA test) (Figures 4F,G), indicating that recorded neurons with adapting firing profile displayed similar dendrite complexity and suggesting that they belonged to an electrophysiologically and morphologically similar Pet1-expressing neuronal subtype. Next, our analysis of multiple electrophysiological properties as well as the input/output relationship did not reveal significant differences in most of the passive and active intrinsic properties between neurons from control and Erbb4cKO mice (p > 0.05; two-way ANOVA test) (Figure 4H; Table 1). A significantly reduced medium after hyperpolarization was observed in Erbb4cKO mice when compared to control (Table 1), indicating that ErbB4 deficiency in serotonergic neuron has an effect on specific membrane properties without causing a prominent change in global excitability. Altogether, our findings suggest that ErbB4 dysfunction in the DRN does not lead to a local phenotype in DRN neither at the intrinsic excitability level nor in serotonergic tone of Pet1+ neurons.

To evaluate whether the connectivity deficits observed upon ErbB4-deficiency in Pet1+ serotonergic neurons impact on brain function, we tested control (Erbb4 ^f/f ) and Erbb4cKO littermates in behavioral assays. Spontaneous locomotor activity was evaluated using the open field and the Y-maze, respectively. Controls and Erbb4cKO mice travelled similar distances (control: 49.63 ± 2.22 m; Erbb4cKO: 54.77 ± 301 m; p = 0.254) with a comparable velocity in the open field (control: 5.52 ± 0.24 cm/s; Erbb4cKO: 6.09 ± 0.33 cm/s; p = 0.255) (Figures 5A,B). In addition, we did not find differences in other parameters indicative of anxiety such as the time spent in the center vs borders in the open field between control and mutant mice (Centre: control: 17.81 ± 1.24%; Erbb4cKO: 18.36 ± 1.207%; p > 0,9999; Borders: control: 82.19 ± 1.24%; Erbb4cKO: 81.64 ± 1.21%; p > 0.9999) (Figure 5C). Spontaneous alternation was also evaluated in the Y-maze (Figures 5D–F). Similar number of entries (control: 32.00 ± 1.55; Erbb4cKO: 32.54 ± 1.30; p = 0.792) (Figure 5E) as well as percent of alternations were observed between control and Erbb4cKO mice (control: 51.40 ± 2.19%; Erbb4cKO: 47.25 ± 2.71; p = 0.242) (Figure 5F), indicating that ErbB4-dysfunction in the serotonergic systems does not affect locomotor activity or working memory.

To test sociability and social memory we employed the three-chamber test that consisted of three sessions: habituation (empty cylinders), sociability (conspecific mouse “stranger 1” or “S1” and object) and preference for social novelty (familiar mouse “S1” and new-conspecific “stranger 2” or “S2”) (Figure 5G). In the habituation phase, mice explored similarly the lateral chambers of the 3-chamber test (Figure 5H), indicating no contextual preference. During the sociability phase, we observed no differences between control and Erbb4cKO mice in distance travelled (data not shown), in agreement with a lack of locomotion phenotype in the open field. Both genotypes showed preference for mouse S1 over the object (control: 0.23 ± 0.040; Erbb4cKO: 0.22 ± 0.04; p = 0.8353) (Figure 5I). However, when animals were exposed to the preference for social novelty test, we observed that Erbb4cKO mice spent less time exploring the novel mouse S2 and displayed a significantly reduced preference index for the novel S2 conspecific over the previously known S1 mouse when compared to controls (control: 0.26 ± 0.04; Erbb4cKO: 0.10 ± 0.06; p = 0.036) (Figure 5J). Together, the lack of sociability phenotype and the reduced preference for social novelty that we observed suggest that social memory could be impaired in Erbb4cKO mice.

To elucidate whether alterations found in social memory might be influenced by anxiety, control and Erbb4cKO animals were tested for anxiety-like behavior using the elevated plus maze and the dark-light box test. In agreement with a lack of anxiety-like behavior in the open field (Figure 5C), we did not find significant differences between control and mutant mice in the percentage of time spent in the different zones of the elevated plus maze (Figure 6A), or in the ratio of time spent in open vs close arms of the elevated plus maze (control: 4.48 ± 0.534; Erbb4cKO: 4.20 ± 0.59; p = 0.729) (Figure 6B). In addition, we did not observe significant differences in the number of transitions (control: 6.0 ± 0.27; Erbb4cKO: 6.30 ± 0.26; p = 0.448) (Figure 6C) and ratio of time spent in the dark over the brightly illuminated area (control: 1.60 ± 0.21; Erbb4cKO: 1.77 ± 0.32; p = 0.660) in the dark-light box test (Figure 6D), indicating that Erbb4 deficiency in Pet1+ serotonergic circuits have no effect on anxiety levels.

To further elucidate whether behavioral deficits could involve abnormal attentional levels, control and Erbb4cKO animals were tested in the prepulse inhibition of the startle reflex (PPI) test. Both genotypes display startle reflex to a 120dB sound (control: 56.64 ± 6.81%; Erbb4cKO: 48.89 ± 7.45%; p = 0.457) (Figure 6E). Inhibition of startle reflex by the presentation of a prepulse of 80, 85 or 90 dB was not significantly different between controls and Erbb4cKO animals (80dB: control: 18.67 ± 5.46%; Erbb4cKO: 22.95 ± 5.72%; p > 0.999; 85dB: control: 29.43 ± 5.07%; Erbb4cKO: 32.37 ± 6.09%; p > 0.999; 90 dB: control: 34.97 ± 4.49%; Erbb4cKO: 33.04 ± 5.71%; p > 0.999) (Figure 6F), suggesting that Erbb4cKO do not have attentional deficits.

We also monitored nesting behavior in the home cage to determine the species-typical behavior of Erbb4cKO animals (Figure 6G). We did not observe significant differences in the ability of animals to build a nest between controls and Erbb4cKO mice, suggesting that serotonergic deficits observed in Erbb4cKO mice are not relevant for the innate organized behavior (p > 0.05; two-way ANOVA) (Figure 6H).

In light of the deficits observed in social memory in Erbb4cKO animals, we evaluated whether other types of memory could be affected by Erbb4 deficiency in Pet1+ serotonergic circuits with the contextual fear conditioning paradigm (Figure 6I). While Erbb4cKO and control mice displayed similar levels of freezing upon presentation of the unconditional stimulus (electric shock), freezing displayed 24 h after fear conditioning during fear memory retrieval was significantly reduced in Erbb4cKO mice when compared to controls (control: 57.37 ± 2.49; Erbb4cKO: 48.28 ± 2.54; p = 0.013) (Figure 6J). These data indicated that fear memory retrieval is impaired in Erbb4cKO mice.

Finally, to assess whether Erbb4-deficiency in Pet1+ neurons is affecting parallel serotonergic sub-systems described to regulate coping behavior in face of challenge (Ren et al., 2018), mice performed the forced swimming and tail suspension tasks. In both tasks, Erbb4cKO mutants and control mice presented similar levels of immobility (FS: control: 23.57 ± 1.64s; Erbb4cKO: 20.66 ± 1.95s; p = 0.263; TS: control: 38.03 ± 2.37s; Erbb4cKO: 34.75 ± 2.66s; p = 0.361) (Figures 6K–L) indicative of normal coping behavior in Erbb4cKO mutants.

Altogether our data suggest that developmental deficiency of Erbb4 in Pet1+ serotonergic circuits leads to the abnormal processing of specific types of memory that contain a social or aversive components, but does not have an effect on locomotion, emotional, attentional or organizational behaviors.