No animal models of autism spectrum disorders (ASD) with good construct validity are currently available; using genetic models of pathologies characterized by ASD-like deficits, but with known causes, may be therefore a promising strategy. The Fmr1-KO mouse is an example of this approach, modeling Fragile X syndrome, a well-known genetic disorder presenting ASD symptoms. The Fmr1-KO is available on different genetic backgrounds (FVB versus C57BL/6), which may explain some of the conflicting results that have been obtained with these mutants up till now.
Fmr1 KO and their wild-type littermates on both the FVB and C57BL/6 genetic backgrounds were examined on a battery of tests modeling the clinical symptoms of ASD, including the triad of core symptoms (alterations in social interaction and communication, presence of repetitive behaviors), as well as the secondary symptoms (disturbances in sensori-motor reactivity and in circadian patterns of activity, epileptic events).
Fmr1-KO mice displayed autistic-like core symptoms of altered social interaction and occurrence of repetitive behaviors with additional hyperactivity. The genetic background modulated the effects of the Fmr1 deletion and it appears that the C57BL/6 background may be more suitable for further research on core autistic-like symptoms.
The Fmr1-mouse line does not recapitulate all of the main core and secondary ASD symptoms, but still can be useful to elucidate the neurobiological mechanisms underlying specific ASD-like endophenotypes.
Citation: Pietropaolo S, Guilleminot A, Martin B, D'Amato FR, Crusio WE (2011) Genetic-Background Modulation of Core and Variable Autistic-Like Symptoms in Fmr1 Knock-Out Mice. PLoS ONE 6(2): e17073. doi:10.1371/journal.pone.0017073
Editor: Bruce Cushing, University of Akron, United States of America
Received: November 6, 2010; Accepted: January 12, 2011; Published: February 22, 2011
Copyright: © 2011 Pietropaolo et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by grants from the March of Dimes (12-FY05-1198), Conseil Régional d'Aquitaine, CNRS, and the University of Bordeaux 1 to Wim E. Crusio. Aurélie Guilleminot and Benoît Martin were supported by grants from INSERM and the University of Rennes 1. Susanna Pietropaolo, Francesca D'Amato, and Wim E. Crusio were supported by the bilateral grant CNRS-CNR 2010 (#23779). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Despite much recent research on autism spectrum disorders (ASD), no animal models with good construct validity are currently available . To develop one, a promising strategy is the use of models of pathologies that are characterized by autistic features . The Fmr1 knock-out mouse (Fmr1-KO) is an example of this approach: it is a confirmed model of Fragile X syndrome (FXS), a genetic disorder due to a mutation in the FMR1 gene leading to a lack of FMRP, a protein playing a pivotal role in synaptic functioning , . As FXS patients often display autistic symptoms and approximately 30% of them meet the full diagnostic criteria for ASD , , , , , , these two syndromes may share some common underlying mechanisms . Fmr1-KO mice present many characteristics of FXS, including macro-orchidism, hyperactivity, and cognitive deficits . Although this model has been widely employed in the last years, the possible validity of the Fmr1-KO mouse as a model for ASD has not been demonstrated convincingly, for several reasons.
First, behavioral characterizations of Fmr1-KO mice have not yet systematically taken into account all clinical criteria used to diagnose ASD and, in addition, most studies on Fmr1-KO mice have focused on a limited number of behavioral tests only, which does not reflect the complexity of ASD symptomatology. The diagnosis of ASD is based on a triad of core symptoms, namely qualitative and quantitative alterations of social interactions, deficits in communication, and the occurrence of repetitive/perseverative behaviors . Beside these main alterations, several secondary symptoms that are variable in occurrence and severity can be present. They include increased sensory reactivity , reduced prepulse inhibition (PPI) of the acoustic startle response (, , but see also , ), hyperactivity and sleep-pattern (circadian) alterations , , increased anxiety , and epileptic seizures . Hence, a useful animal model should present behavioral features that resemble at least one of the ASD core symptoms. Of course, an ideal animal model for ASD would mimic all core autistic features (as assessed by multiple tests) in association with some of the secondary ones .
To our knowledge, the only core autistic-like symptoms that have been comprehensively tested in Fmr1-KO mice have been deficits in social interaction , , , , , . The presence of repetitive/perseverative behaviors has been investigated only through the evaluation of deficits in putative measures of behavioral flexibility such as reversal learning and working memory , , , , , while to date no reports on possibly altered communication are available. In addition, only some of the secondary autistic-like characteristics, such as changes in emotionality , ,  and activity , , , , , ,  have been assessed. Acoustic startle and its PPI have been investigated , , , , , but not their dependency on acoustic stimulus intensity. Finally, neither abnormalities in circadian patterns of activity, nor the presence of spontaneous episodes of epilepsy (for evoked seizures see:, , , , , ) have been evaluated in Fmr1-KO mice.
The second problem is that studies of autistic-like deficits in the Fmr1-KO model present contradicting results. For example, Fmr1-KO mice have been reported to display enhanced , normal , , or reduced levels of social interest and interaction , , . Similarly, they showed enhanced , , , , , unchanged , or reduced  PPI, accompanied by reduced , , , ,  or unaltered ,  startle reactivity. Apart from differences in experimental procedures, it is most likely that these disparate results are due to the use of different genetic backgrounds, most-frequently the FVB and C57BL/6 (B6). For example, previous studies have demonstrated that the Fmr1 mutation had opposite effects on the sizes of the hippocampal intra- and infrapyramidal mossy fiber terminal fields, depending on the background , . Surprisingly, apart from some of the secondary symptoms , , , a systematic study of the effects of the Fmr1-deletion on ASD-like features in these two backgrounds has not been conducted yet. The present study therefore investigated the possible validity of the Fmr1-KO mouse on both the FVB and B6 backgrounds as a model for ASD by assessing the occurrence of autistic-like alterations in behaviors relevant to the core ASD symptoms (deficits in social interest and recognition, alterations in social interaction and communication, occurrence of repetitive behaviors), as well as secondary symptoms (PPI deficits, presence of epileptic events, alterations in activity and its circadian patterns).
Materials and Methods
Subjects were adult (12±1 weeks old) male Fmr1-KO and their wild-type littermates. The original Fmr1 knock-out mutation was generated using 129P2 stem cells . Breeders of C57BL/6J-Fmr1tm1Cgr/Nwu (B6) or FVB.129P2-Fmr1tm1Cgr/J (FVB) were originally obtained from Neuromice.org (Northwestern University, IL 60208, USA; MGI ID: 1857169) and The Jackson Laboratory (Bar Harbor, ME 04609, USA; Stock number: 004624), respectively. Wild-type males were from either the C57BL/6J or the FVB.129P2-Pde6b+Tyrc-ch/AntJ strains, originally purchased respectively from Charles River (L'Arbresle, France) and The Jackson Laboratory (Bar Harbor, ME 04609, USA; Stock number: 004828). Breeding trios were formed by mating two heterozygous females with an appropriate wild-type male. After 2 weeks the sire was removed and the females were single caged and left undisturbed until weaning of the pups. Mice were weaned at 21 days of age and group-housed with their same-sex littermates (3–5/cage). On the same day, tail samples were collected for DNA extraction and subsequent PCR assessment of the genotypes as previously described .
Only litters including males of both genotypes (+/• and −/•) were used for experiments. A total of 61 subjects were subjected to behavioral testing: 31 on the B6 background (15 wild-type and 16 KO) and 30 on the FVB background (16 wild-type and 14 KO). A different batch of adult (10±1 weeks old) mice (5 behaviorally-naive animals per genotype/background) was employed for EEG measurements.
NMRI mice (30 males and 30 females) were used as stimulus animals in the social tests. This strain was chosen because it differs from both genetic backgrounds on which the Fmr1 KOs are maintained. It is also commonly employed in studies of social behavior, because of its good levels of sociability , . Juvenile (3 weeks old) males and adult (12 weeks old) virgin females of the NMRI strain were purchased from Janvier (Le Genest-Saint-Isle, France), housed in same-sex groups, and left undisturbed for a week before being used for testing.
All animals were housed in polycarbonate standard cages (33×15×14 cm in size; Tecniplast, Limonest, France), provided with sawdust bedding (SAFE, Augy, France) and a stainless steel wired lid. Food chow (SAFE, Augy, France) and water were provided ad libitum. The animals were maintained in a temperature- (22°C) and humidity- (55%) controlled vivarium, under a 12:12 hr light–dark cycle (lights on at 7 a.m.).
Behavioral tests commenced at 12±1 weeks of age, as follows. Starting on day 1, a three-compartment test for sociability and preference for social novelty was administered, followed on day 3 by a direct social interaction test with a juvenile male, and on day 5 by a spontaneous alternation test in a Y-maze. On day 7, prepulse inhibition of the acoustic startle reactivity (PPI) was tested followed on day 11 by circadian modulation of locomotor activity, and, finally, on day 13 by a direct social interaction test with an adult female. Tests that relied mainly on observations of spontaneous behavior were conducted first in order to minimize possible undesirable transfer effects; tests that involved stressful stimulation, such as the acoustic startle test, or required social isolation, such as the assessment of circadian activity and social interaction with a female, were conducted last. All behavioral tests were carried out during the light phase of the cycle.
All 61 subjects were tested in the three-compartment test, direct social interaction with a juvenile male, spontaneous alternation, and PPI. In the three-compartment test, data from one FVB-KO and one B6-WT mouse were lost due to a problem with video recording: the analyses were therefore conducted on 30 B6 (14 WT and 16 KO) and 29 FVB (16 WT and 13 KO). The circadian modulation of activity was tested on a subgroup of 57 mice (14 B6-WT, 16 B6-KO, 15 FVB-WT and 12 FVB-KO), while the test of direct social interaction with a female was conducted on a subgroup of the latter of 54 mice (12 B6-WT, 15 B6-KO, 15 FVB-WT and 12 FVB-KO).
All experimental procedures were in accordance with the European Communities Council Directive of 24 November 1986 (86/609/EEC) and local French legislation.
Sociability and preference for social novelty in the three compartment test
The testing apparatus employed here is similar to the one previously described by others , . It consisted of 3 compartments (Fig.1): a central chamber (45×18×25 cm) connected on each side to another compartment (45×20×25 cm) through a small rectangular opening (15×5 cm). The floors and walls (1 cm thick) of all compartments were made of transparent Plexiglas. Each side compartment contained a round stimulus cage (10 cm in diameter, 7 cm high) made of wire mesh (hole size: 0.7×0.7 cm) covered by a plastic roof (5 cm high). A metal weight was attached to the roof in order to keep the stimulus cage stable. Each stimulus cage was placed at a distance of 6 cm from the back wall and 4 cm from the sides. Tracking images from a camera above the center of the apparatus were analyzed with Ethovision (Version 3.1, Noldus Technology, Wageningen, The Netherlands).
Figure 1. Schematic representation of the apparatus used for the three compartment test.
The apparatus consisted of three rectangular compartments made of transparent Plexiglas. A stimulus cage (wire mesh, 10 cm in diameter, here represented as a dark grey circle) allowing visual, olfactory and partial tactile contact was placed in each side compartment. Performance in the task was evaluated across three 5-min trials, based on the relative time spent in the contact areas (highlighted in light grey).doi:10.1371/journal.pone.0017073.g001
Experimental and stimulus mice (4-week old NMRI male mice) were individually housed in standard polycarbonate cages provided with sawdust, food, and water bottles and left undisturbed in the experimental room for about 10 min before testing began. Each experimental subject was then introduced in the middle of the central compartment and allowed to explore the apparatus for 3 trials of 5 min each:
- Trial 1 (habituation): the stimulus cages were empty; basal levels of exploration were assessed.
- Trial 2 (sociability): a stimulus mouse was introduced in one of the stimulus cages, while a novel object (a plastic grey cylinder, 6 cm in diameter, 2 cm high) was introduced in the opposite cage (sides were counterbalanced within experimental groups); preferential exploration of the social versus non-social novel stimuli was measured.
- Trial 3 (social novelty preference): as trial 2, but the object was exchanged for a novel stimulus mouse; preferential exploration of the novel versus familiar social stimulus was evaluated.
At the end of each trial the experimental animal was confined in the central compartment by means of two Plexiglas magnetic doors for 30 sec. At the end of the third trial the apparatus as well as the object and the stimulus cages were cleansed with water and dried.
Exploration of each stimulus was assessed by measuring the time spent in each contact area, a 20×22 cm area containing the stimulus cage (see Fig. 1). A percentage score was also computed for the last two trials as follows:
- On trial 2: Sociability score = 100×Tsocial stimulus/(Tsocial stimulus + Tnon-social stimulus),
- On trial 3: Social novelty preference score = 100×Tnovel social stimulus/(Tnovel social stimulus + Tfamiliar social stimulus).
Finally, the total distance moved in the entire apparatus was measured in meters in each trial.
Direct social interaction with a juvenile male
Direct social interaction was assessed in a 30×15×22 cm plastic cage with 3 cm of sawdust and a plastic roof with a 17×8 cm central opening.
Experimental and stimulus mice were habituated to the experimental room as before. Each experimental mouse was then introduced into the testing cage and left to habituate for 5 min. An unfamiliar stimulus mouse (a 4-week old NMRI male) was then introduced into the testing cage through the roof opening. The testing session lasted 3 min, but was stopped immediately if aggressive episodes occurred. The testing cage was cleansed with water and the sawdust was renewed between sessions.
Testing sessions were recorded and videos were analyzed with Observer XT (version 7, Noldus, The Netherlands), taking only the experimental animal into account. One observer who was unaware of the genotype of the animals scored both frequency and duration for each of the following behavioral categories and elements , :
- Affiliative behaviors: sniffing the head and the snout of the partner, its anogenital region, or any other part of the body; allogrooming (grooming the partner); traversing the partner's body by crawling over/under from one side to the other.
- Nonsocial activities: rearing (standing on the hind limbs sometimes with the forelimbs against the walls of the cage) and digging. Time spent in self-grooming (the animal licks and mouths its own fur) was analyzed separately, since this is sometimes considered representing repetitive behavior , , , , .
Spontaneous alternation was assessed in a grey, plastic Y-maze, placed on a table 80 cm high and located in the middle of a room containing a variety of extramaze cues. The three arms of the Y-maze were similar in appearance and spaced at 120° from each other. Each arm was 42 cm long and 8 cm wide. The entire maze was enclosed by a wall 15 cm high and 0.5 cm thick. Tracking images from a camera above the maze were analyzed with Ethovision.
Mice were habituated to the experimental room as before and then introduced at the end of one of the arms and allowed to explore the maze for 5 min. Allocation of the start arm was counterbalanced within experimental groups.
An entry into one of the arms was scored by an observer unaware of the genotype of the animals when all four paws of the animal were placed inside an arm. Spontaneous alternation, expressed as a percentage, refers to that proportion of arm choices differing from the previous two , . Thus, if an animal made the following sequence of arm choices: A, B, C, B, A, B, C, A, the total number of alternation opportunities would be six (total entries minus two) and the percentage alternation would be 67% (four out of six).
Prepulse inhibition of the acoustic startle reflex
The apparatus (SR-LAB, San Diego Instruments, San Diego, CA, USA) and procedures were previously described in detail , , , , . Briefly, animals were acclimatized to the apparatus for 5 min. The first six trials consisted of six pulse-alone trials, two for each pulse intensity (100, 110, or 120 dBA), presented in a pseudorandom order. Subsequently, ten blocks of trials were presented. Each block consisted of three pulse-alone trials, one for each pulse intensity, three prepulse-alone trials (+6, +12, or +18 dB units above the background of 65 dBA), nine possible combinations of prepulse-plus-pulse trials (3 levels of pulse×3 levels of prepulse), and one no-stimulus trial (i.e., background alone). These 16 trials were presented in a pseudorandom order within each block, with a variable intertrial interval of a mean duration of 15 sec. The session was concluded with a final block of six consecutive pulse-alone trials as in the first block.
Reactivity scores obtained on the first and the last blocks of six consecutive pulse-alone trials were separately analyzed to measure startle habituation. The data obtained in the remaining trials were categorized into three main different subsets according to their relevance to distinct behavioral constructs , , , , . First, startle reactivity was assessed by the reactivity scores obtained in the intermediate pulse-alone trials. Second, reactivity on prepulse-plus-pulse trials relative to middle pulse-alone trials was used to estimate prepulse inhibition. Third, to measure prepulse-elicited reactivity we included data from prepulse-alone and no-stimulus trials.
To better conform to the assumptions of parametric ANOVA, a natural logarithmic transformation was applied to the startle reactivity scores , , , , . First, PPI was assessed by analyzing the raw reactivity scores on intermediate pulse-alone and on prepulse-plus-pulse trials. We analyzed the linear coefficients derived from each reactivity curve using a 3-way ANOVA with background and genotype as between- and pulse intensity as within-subject factors. Second, PPI was analyzed converting the reactivity data into percent scores (%PPI = 100× (pulse-alone − prepulse-plus-pulse)/pulse-alone) calculated for each subject for each of the nine possible prepulse-plus-pulse combinations and analyzed in a similar way as the raw scores. The analysis of both raw and percent scores is widely employed in mouse studies , , , , ,  as a necessary precaution in case experimental groups show large differences in their startle reactivity.
Circadian modulation of locomotor activity
The apparatus (Actimeter system, Imetronic, France) consisted of an isolated plastic cupboard (1.80 m high, 1 m wide, 0.6 m deep) containing 8 transparent plastic cages (21×11×17 cm) with a grid floor. A metal food dispenser and a water bottle were inserted in the front wall of each cage, while two horizontal lines of infrared captors (two for each line, interline distance = 25 mm, distance between two captors = 12.5 cm) were mounted along each of the longer side walls. The cages were illuminated 12 hrs per day starting from 7 a.m. The rack was connected to an electronic interface to communicate with a computer for automatic data storing.
Each mouse was introduced into an activity cage at 6 p.m. and left undisturbed for the subsequent 25 hrs.
Locomotor activity was evaluated based on the number of breaks of the infrared captors. The first testing hour was analyzed separately in 10-min bins, in order to evaluate the locomotor response and habituation to a novel environment. The remaining 24 hrs were analyzed in 1 hr-blocks with the 12 hr-dark/light phase as a further within subject factor, in order to assess the circadian modulation of locomotor activity.
Immediately after testing, mice were housed singly in 30×15×14 polycarbonate cages (Tecniplast, Limonest, France) covered by a metal grid and with approximately 3 cm of sawdust on the floor.
Direct social interaction with an adult female
Apparatus and procedures.
Direct social interaction was assessed in the home cage in which the animals were isolated for about 36 hrs after the previous test. Experimental and stimulus mice were habituated to the experimental room as described for the previous experiments. An unfamiliar stimulus mouse (a 12-week old NMRI female) was then introduced into the testing cage and left there for 5 min.
During the test an ultrasonic microphone (Bat detector U30, Ultrasound Advice, UK) set on frequency division 10 was suspended 10 cm above the cage. Vocalizations were recorded using the Spectrogram 15 program (Visualisation Software LLC, sampling rate 48 kHz, format 16 bit) and analyzed with Avisoft SASLab Pro (Version 5. 013, Avisoft, Berlin, Germany) after a fast Fourier transformation (FFT). Spectrograms were generated with an FFT-length of 512 points, a time window overlap of 50% (100% Frame, FlatTop window), a frequency resolution of 488 Hz, and a time resolution of 1 ms. Call detection was provided by an automatic threshold-based algorithm and a hold time (0.04 s) mechanism.
Testing sessions were recorded and videos were analyzed with Observer XT, as described for the test with a juvenile male mouse. In addition, the frequency of mounting attempts was also recorded. Vocalizations were analyzed in terms of both frequency and mean duration.
The occurrence of epileptic episodes was assessed following a classical protocol . All animals were anesthetized (ketamine 60 mg/kg, xylazine 15 mg/kg, i.p.) and five monopolar tungsten rod electrodes were implanted and fixed to the skull with cyanoacrylate glue and acrylic cement. Four electrodes were placed bilaterally over the frontal and parietal cortex and one over the cerebellum (reference electrode). Animals were allowed to recover for at least two weeks before testing.
Apparatus and procedures.
Mice were placed in a 15×15×30 cm Plexiglas cage containing sawdust within a Faraday cage. EEG recordings were collected during a 3 hr-session of free exploration which was repeated on 5 consecutive days. The electrodes were connected to the EEG apparatus with flexible wires and EEG activities were recorded using a digital acquisition system (Coherence 18.104.22.168, Deltamed-France, sampling rate 1024 Hz).
The presence of epileptic activity, absence seizures (characterized by spike-wave discharges) or interictal events was assessed by visual inspection of video-EEG recordings.
All data were analyzed by ANOVA with genetic background B6 or FVB and Fmr1 genotype (+/• or −/•) as between-subject factors. Within-subject factors were included as needed. Post-hoc comparisons were performed using Fisher's LSD test. Data are presented as mean ± SEM throughout.
All statistical analyses were carried out using SPSS® 13.0 for Windows (Release 13.0.1, SPSS Inc. Chicago IL, USA) and α was set at 0.05.
Sociability and preference for social novelty in the three compartment test
Habituation (trial 1).
Animals did not show a preference for any compartment or contact area during the first 5 min-trial [all Fs<1, ns; data not shown]. No differences between backgrounds or genotypes were observed for locomotor activity [all Fs<1, ns; data not shown].
Sociability (trial 2).
Mice preferentially explored the contact area containing the novel stimulus mouse compared to that with the novel object [F(1,55) = 24.13, p<0.0001]. This preference was similar in both genotypes [genotype × contact area: F(1,55) = 2.23, ns] and backgrounds [background × contact area: F<1, ns], as also confirmed by the analysis of the sociability scores [genotype: F(1,55) = 2.09, ns; background: F<1, ns; Fig.2A].
Figure 2. Sociability (A) and preference for social novelty (B) in the three compartment test.
Exploration of each stimulus was assessed by measuring the time spent in each contact area, i.e., a 20×22 cm area containing the stimulus cage. Data are mean ± SEM. *p<0.05. The dotted line represents chance level (50%).doi:10.1371/journal.pone.0017073.g002
Locomotor activity did not differ between Fmr1-KO and WT mice, but was higher in the FVB compared to the B6 background [F(1,55) = 10.16, p<0.01; B6: 1.69±0.07, FVB: 2.19±0.14].
Social novelty preference (trial 3).
Mice preferentially explored the novel stimulus mouse compared to the familiar one [F(1,55) = 7.19, p<0.05]. However, this preference was absent in Fmr1-KO mice of both backgrounds [genotype × contact area: F(1,55) = 3.24, p = 0.08; contact area effect in WT: F(1,28) = 13.58, p<0.01, in KO: F<1, ns; social novelty preference scores, genotype: F(1,55) = 4.31, p<0.05; Fig.2B].
No differences in social recognition were observed between backgrounds [background × contact area: F<1, ns; social novelty preference scores, background: F(1,55) = 1.12, ns; Fig.2B]. Fmr1-KO and WT displayed comparable levels of locomotion but FVB were again more active than B6 [F(1,55) = 7.87, p<0.01; B6: 1.65±0.063, FVB: 2.09±0.15].
Direct social interaction with a juvenile male
Surprisingly, some mice attacked the juvenile stimulus mouse before the end of the 3-min test causing early interruption of the encounter. These mice included 3 B6-WT (out of 15), 5 B6-KO (out of 16) and 1 FVB-WT (out of 16). In light of this unexpected finding we analyzed the latency to the first attack in all animals, assigning the maximum value of 180s to non-attacking mice (Fig.3A). The results showed that the Fmr1 mutation caused an increased tendency to attack the juvenile stimulus, but only in the B6 background, B6-KO differing from both B6-WT and FVB-KO [background × genotype: F(1,57) = 3.99, p = 0.05, post hoc: p<0.05].
Figure 3. Aggression and affiliation in the direct social interaction with a juvenile male mouse.
A: Attack latency (for non-attacking mice the maximum value of 180s was assigned). B: Time spent in affiliative behavior. Data are mean ± SEM. *p<0.05.doi:10.1371/journal.pone.0017073.g003
Subsequent behavioral analyses of the non-attacking animals demonstrated that Fmr1-KO did not differ from WT in the time spent performing affiliative behaviors (Fig.3B) or in their involvement in non-social activities, including self-grooming (data not shown). Furthermore, no background effects were detected for any behavior.
Fmr1-KO and WT displayed comparable levels of spontaneous alternation (mean percent alternation rates varied between 50 and 64) and general exploration (mean numbers of entries varied between 41 and 51). In contrast, the two genetic backgrounds differed on both behavioral measures: FVB showed higher levels of spontaneous alternation [F(1,57) = 19.16, p<0.0001] and more entries into the arms of the maze [F(1,57) = 5.90, p<0.05] than B6.
Acoustic startle response
One B6-KO exhibited a baseline startle value deviating more than 2SD from its group mean and was excluded from data analysis , . Statistical analyses therefore used data from 30 B6 (15 WT and 15 KO) and 30 FVB (16 WT and 14 KO).
Acoustic startle habituation.
There was a general reduction in the acoustic startle response from the first to the last block of pulse-alone trials [2-trial block effect: F(1,56) = 5.74, p<0.05], without any differences between genotypes or backgrounds (data not shown). Furthermore startle reactivity increased with pulse intensity [F(2,112) = 255.99, p<0.0001], an effect that was less prominent in Fmr1-KO of both backgrounds, showing a weaker startle response to the highest 120 dBA pulse than WT [genotype × pulse: F(2,112) = 4.64, p<0.05, post hoc: p<0.05; Fig.4A]. Differences between the two backgrounds were detected in the overall levels of startle reactivity that were critically modulated by the intensity of the pulse stimulus: B6 showed stronger responses to the 100 dBA and lower ones to the 120 dBA pulses compared to FVB [background × pulse: F(2,112) = 61.1, p<0.0001, post hoc: p<0.05; Fig.4-B].
Figure 4. Startle reactivity and prepulse inhibition (PPI).
A-B: Startle reactivity during the first and the last block of pulse alone trials; C–D: PPI expressed as the linear coefficient of the reactivity data. Data are mean ± SEM. *p<0.05.doi:10.1371/journal.pone.0017073.g004
Pulse reactivity on intermediate trials.
The analysis of the intermediate pulse alone trials confirmed the pattern of results observed during habituation. Fmr1-KO mice of both backgrounds showed lower levels of startle response to the highest 120 dBA pulse level compared to the WT animals [genotype × pulse intensity: F(2,112) = 4.1, p<0.05, post hoc: p<0.05; ln-transformed reactivity to 120 dBA, Fmr1-KO: 4.64±0.09, WT: 4.36±0.08]. Background differences were found again: B6 showing stronger responses to the 100 dBA and lower ones to the 120 dBA pulses than FVB [background × pulse: F(2,112) = 66.35, p<0.0001, post hoc: p<0.05; ln-transformed reactivity, B6: 2.86±0.07, FVB: 2.40±0.07 at 100 dBA; B6: 3.99±0.08, FVB: 4.99±0.08 at 120 dBA].
PPI (Reactivity scores).
PPI was demonstrated by the negative values of the mean linear coefficients of the reactivity curves (Fig.4, C–D). The magnitude of PPI was enhanced in Fmr1-KO mice, but only on the B6 background [genotype × background: F(1,56) = 3.9, p = 0.05]. Post-hoc comparisons confirmed that B6-KO displayed higher levels of PPI than B6-WT and FVB-KO (Fig.4C). PPI was higher in B6 than FVB, but only at the lowest pulse level [Fig.4D; background × pulse [F(2,112) = 5.83, p<0.01].
As expected , , , , PPI increased with prepulse intensity [F(2,112) = 11.04, p<0.0001] and the magnitude of this effect was modulated by the pulse level [pulse × prepulse: F(4,224) = 15.79, p<0.0001]. The analysis of the percent values led to a pattern of genotype and background differences similar to that described above (data not shown). The Fmr1 mutation enhanced PPI, and this effect tended to be more prominent in B6, although the genotype × background interaction was not significant [F(1,56) = 2.89, p = 0.10]. Background differences in the expression of PPI were also confirmed, B6 showing higher PPI levels than FVB, but only at the lowest pulse intensity [background × pulse F(4,224) = 3.03, p = 0.05].
The reactivity on prepulse alone trials was also evaluated separately, including trials where only background noise was presented (data not shown). The startle response of all animals increased with the intensity of the prepulse stimulus [F(3,168) = 3.29, p<0.0001] and this effect was similar in both Fmr1-KO and WT. Animals from the B6 background showed higher levels of prepulse reactivity compared to FVB, but this difference was observed only at the highest 83 dBA prepulse level [background × prepulse: F(3,168) = 3.29, p<0.05, post hoc: p<0.05; ln-transformed reactivity at 83 dBA, B6: 2.49±0.06, FVB: 2.33±0.06].
Locomotor activity and its circadian modulation
Activity and locomotor habituation during the first testing hour.
The first hour of testing was analyzed separately in 10-min time bins, in order to evaluate exploration of the novel environment and locomotor habituation (Fig.5A, B). Locomotor activity decreased over time [F(5,265) = 33.32, p<0.0001] and this was similar in Fmr1-KO and WT of both backgrounds (data not shown). Nonetheless, Fmr1-KO were overall more active during the first hour than their WT littermates [F(1,53) = 5.15, p<0.05] and this effect was larger in the FVB background [background × genotype: F(1,53) = 4.01, p = 0.05]. Post-hoc comparisons confirmed that FVB-KO were more active than both FVB-WT and B6-KO (p<0.05; Fig.5-A).
Figure 5. Locomotor habituation and circadian modulation of activity.
A-B: Locomotion during the first testing hour; C–D: Total activity during the subsequent 24 hrs; E: 24 hr activity profile. Data are mean ± SEM. *p<0.05.doi:10.1371/journal.pone.0017073.g005
Differences between the two backgrounds were also observed (Fig.5-B, F(1,53) = 34.05, p<0.0001), FVB mice being less active and habituating faster [background × bins: F(5,265) = 6.40, p<0.0001] than B6.
Changes in locomotor activity during 24 hrs.
The analysis of the subsequent 24 h (starting at 7 pm) confirmed the results observed during the habituation phase. Fmr1-KO were overall more active than WT [F(1,53) = 4.57, p<0.05], but this effect was mostly observed in the FVB background [background × genotype: F(1,53) = 5.43, p<0.05; post-hoc: p<0.05; Fig.5-C]. As before, B6 was more active than FVB, although only during the 12 hrs of darkness [background × light/dark phase: F(1,53) = 16.92, p<0.0001; post-hoc: p<0.05; Fig.5D]. The activity profile of Fmr1-KO of both backgrounds was comparable to that observed in WT (Fig. 5E, F). All animals showed highest levels of activity during the first 4-5 hrs of the dark period, which were drastically reduced during the light phase [1 hr-bin effect: F(11,583) = 4.007, p<0.0001; light/dark phase effect: F(1,53) = 200.39, p<0.0001, 1 hr-bin × light/dark phase: F(11,583) = 41.28, p<0.0001; Fig.5E].
Direct social interaction with an adult female
Fmr1-KO spent less time in affiliative behaviors [F(1,50) = 4.78, p<0.05; Fig.6A] and showed a non-significant tendency to display more mounting attempts [F(1,50) = 3.08, p = 0.09; Fig.6B] compared to WT. It should be noted here that even if mounting attempts would have been classified as an affiliative behavior, the effect of the Fmr1 mutation would have remained significant (data not shown). Fmr1-KO also showed higher levels of self-grooming, depending on the background: B6-KO spent more time performing self-grooming than both B6-WT and FVB-KO [background × genotype: F(1,50) = 5.07, p<0.05, post hoc: p<0.05; Fig.6-C]. Behavioral differences were also found between the two genetic backgrounds: FVB were more engaged in affiliative behaviors [F(1,50) = 149.62, p<0.0001, Fig.6-A] and less in non-social activities [F(1,50) = 5.69, p<0.05, Fig.6D] than B6.
Figure 6. Social and non-social behaviors in the direct social interaction with an adult female.
A: Time spent on affiliative behaviors towards an adult female. B: Frequency of attempts to mount the female. C: Self-grooming. D. Time spent on non-social activities. Data are mean ± SEM. *p<0.05.doi:10.1371/journal.pone.0017073.g006
Fmr1-KO and WT emitted comparable ultrasonic vocalizations in terms of both frequency (Fig.7A) and duration (Fig.7B). However, there was a significant effect of background: FVB emitted a higher number of vocalizations [F(1,50) = 19.1, p<0.0001; Fig.7-A] and of longer duration [F(1,50) = 54.69, p<0.0001; Fig.7-B].
Figure 7. Ultrasonic vocalizations during the direct social interaction with an adult female.
A: Frequency. B: Mean duration. Data are mean ± SEM. *p<0.05.doi:10.1371/journal.pone.0017073.g007
Fmr1-KO of both backgrounds displayed EEGs which were comparable to those of WT (Fig. 8). No seizures, absences, or interictal events were observed in any animal during any of the five consecutive 3-hr recording sessions.
Figure 8. EEG analysis.
Left: Examples of bipolar electrocorticographic recordings from each experimental group, illustrating the clear absence of any seizures, absences, or interictal events. Right: Electrode placements. 1 and 2: frontal cortex. 3 and 4: parietal cortex. Ref: cerebellar reference electrode.doi:10.1371/journal.pone.0017073.g008
Our data show (i) that the Fmr1 phenotype partially reproduces core symptoms of ASD with a very limited recapitulation of secondary autistic-like alterations and (ii) that the effects of the Fmr1-KO deletion are in part modulated by the genetic background. An overview of the results obtained is given in Table 1.
Table 1. Summary of the results.doi:10.1371/journal.pone.0017073.t001
Autistic-like symptoms in Fmr1-KO mice
Fmr1-KOs of both genotypes displayed a deficit in the preference for social novelty in the three compartment test, but had intact levels of sociability, in agreement with recent reports on the B6  and the B6 × FVB backgrounds . Despite the absence of ASD-like reduced levels of social interest, this lack of preference for social novelty may be interpreted as an autistic-like deficit in social recognition. Furthermore, Fmr1-KO of both backgrounds showed reduced social investigation, although this effect was dependent on the nature of the social stimulus, because it was observed only during the interaction with an adult female. This deficit does not seem to be due to reduced levels of sexual interest, since Fmr1-KO actually displayed more mounting attempts than WT (albeit non-significantly). Indeed, reductions in affiliative behaviors have been observed in Fmr1-KOs also during interaction with an ovariectomized female . Besides these quantitative alterations, some qualitative changes were also observed in the social behavior of Fmr1-KOs in the B6 background. Here, an unexpected tendency to attack a juvenile stimulus mouse was found (i.e. a social stimulus that normally does not elicit aggressive responses). This resembles the signs of aggressiveness that have been reported in autistic patients , , , , . In sum, it appears that Fmr1-KO display inappropriate responses in social situations.
B6-KO were also the only ones showing signs of repetitive behaviors by being more engaged in self-grooming during social interaction with an adult female. This result is corroborated by previous studies conducted in the B6  and the B6 × FVB backgrounds , and it could be interpreted as a form of repetitive behavior due to increased emotional distress induced by the social context. Interestingly, increased self-grooming has been reported in other proposed mouse models for ASD as well (such as neuroligin-1  and neurexin-1α KO mice , as well as the BTBR strain , ). Nonetheless, the occurrence of repetitive/perseverative behaviors seems to be modeled only partially by the Fmr1-KO, given our results in the Y-maze and previous findings from others on reversal learning in multiple backgrounds .
The B6 background was also more sensitive to the effects of the Fmr1 mutation on PPI, but the direction of these effects was opposite to expectation: Fmr1-KOs displayed enhanced PPI. To our knowledge, there are no reports of increased PPI in ASD or FXS patients. On the contrary, most studies report PPI deficits in ASD ,  (albeit subtle ones and with the exception of two experiments on younger subjects that reported no differences , ), and FXS patients display more severe PPI deficits , . The magnitude of the acoustic startle response is also unaltered or even mildly increased in autistic and FXS patients , , , , in contrast to what is observed here in both backgrounds. Interestingly, these incongruent effects on PPI and startle have been consistently replicated across different mouse studies , , , , , . Only one previous report has described a PPI deficit in B6-KO , but it did not use acoustic stimuli and measurements of whole body startle response. It should be noted that the enhanced PPI in B6-KO is not due to the decrease in startle response, as the effect on PPI is found at all pulse intensities, but for startle only at the highest pulse level. We therefore conclude that although sensorimotor response and gating are obviously influenced by Fmr1-KO in both humans and mice, the direction of the effects is opposite. The reasons for this discrepancy between the two species remain unknown; some authors have suggested a more important role of other FMRP-related proteins such as FXR2 in the mouse. This hypothesis needs further investigation, but is supported by the observation of PPI deficits in Fxr2-KO mice .
The only secondary autistic-like symptom displayed by Fmr1-KO mice was hyperactivity, although this was observed only in the FVB background and seems to be critically dependent on the testing conditions as the activity levels of Fmr1-KO were comparable to those of WT in all behavioral tests other than the 24 hr-monitoring. This result highlights the importance of test duration and apparatus, an issue that has been raised by previous studies (see  for review).
Further studies using more different test situations are needed to definitely exclude altered ultrasonic communication in the Fmr1-KO, for example by testing pup calls towards the dam , . In addition, the absence of epileptic tendencies is surprising in view of the increased seizure susceptibility reported in both FXS and ASD. Our results, however, are in agreement with previous studies showing no difference in the responsiveness to chemical convulsants , but not with reports of increased sound- and kindling-induced seizures , , , , , .
The impact of the genetic background
Our findings show that the genetic background partially modulates the Fmr1 autistic-like phenotype, in such a way that certain alterations appear only in a specific background. As shown in Table 1, this modulation was rather subtle, since many important abnormalities were observed in both backgrounds. This pattern of results differs from the opposite effects found for the sizes of IIPMF terminal fields reported for the B6 and FVB backgrounds , . It should be interesting to determine the genetic bases of this epistatic interaction, although that would be a far from trivial undertaking.
It should perhaps be noted here that “background” in this experiment not only consists of all genes in the genome differing between the FVB and B6 strains, but also by the pre- and postnatal maternal environment. There is no obvious way to control for this, barring laborious cross-fostering and embryo-transfer experiments. However, our observations of maternal behavior from PND 1 to 7 in heterozygous females did not detect any significant differences in the amount of maternal care (nursing postures, grooming of the pups) received by B6 and FVB pups, although B6 dams spent slightly more time in the nest (data not shown). While we cannot exclude that maternal effects are (partly) responsible for the background effects reported here, we feel that this is rather unlikely.
Based on our results, both backgrounds can be employed for modeling specific features of ASD. Even so, the B6 background seems to be the most suitable one for future autism research, since it presents more autistic-like core symptoms, in terms of both quantitative and qualitative alterations, even though this background already shows the lowest levels of social affiliation, ultrasonic vocalizations, and spontaneous alternation.
Conclusion: Is the Fmr1-KO mouse a valid model for ASD?
The findings presented here clearly demonstrated that Fmr1-KO mice model only some specific autistic-like deficits. According to the view that the ideal ASD model should reproduce all core symptoms and some secondary ones , the Fmr1-KO should therefore be of limited validity only, especially in view of the lack of communication deficits that are reported here for the first time. However, some authors have suggested that the triad of core symptoms may, or even cannot, have a unitary explanation and should instead be fractionated and studied separately . According to this view, a model displaying only some individual symptoms may still be valuable for future ASD research (as also suggested for other neuropsychiatric disorders ). Hence, the Fmr1-KO can still serve as a useful tool to investigate the neurobiology of specific ASD endophenotypes, with the design of novel therapeutic approaches as an ultimate goal.
The authors thank Diego Oddi for his valuable assistance with the analysis of ultrasonic vocalizations.
Conceived and designed the experiments: WEC SP FD BM. Performed the experiments: SP AG. Analyzed the data: SP FD BM. Wrote the paper: SP WEC. Final approval of the manuscript: SP AG BM FD WEC.
- 1. Belzung C, Leman S, Vourc'h P, Andres C (2005) Rodent models for autism. a critical review. Drug discovery today: Disease models 2: 93–101.
- 2. Moy SS, Nadler JJ, Magnuson TR, Crawley JN (2006) Mouse models of autism spectrum disorders: the challenge for behavioral genetics. Am J Med Genet C Semin Med Genet 142C: 40–51.
- 3. Greenough WT, Klintsova AY, Irwin SA, Galvez R, Bates KE, et al. (2001) Synaptic regulation of protein synthesis and the fragile X protein. Proc Natl Acad Sci U S A 98: 7101–7106.
- 4. Verkerk AJ, Pieretti M, Sutcliffe JS, Fu YH, Kuhl DP, et al. (1991) Identification of a gene (FMR-1) containing a CGG repeat coincident with a breakpoint cluster region exhibiting length variation in fragile X syndrome. Cell 65: 905–914.
- 5. Hatton DD, Sideris J, Skinner M, Mankowski J, BaileyJr DB, et al. (2006) Autistic behavior in children with fragile X syndrome: prevalence, stability, and the impact of FMRP. Am J Med Genet A 140A: 1804–1813.
- 6. Rogers SJ, Wehner DE, Hagerman R (2001) The behavioral phenotype in fragile X: symptoms of autism in very young children with fragile X syndrome, idiopathic autism, and other developmental disorders. J Dev Behav Pediatr 22: 409–417.
- 7. Bailey DB Jr, Hatton DD, Skinner M, Mesibov G (2001) Autistic behavior, FMR1 protein, and developmental trajectories in young males with fragile X syndrome. J Autism Dev Disord 31: 165–174.
- 8. Bailey DB Jr, Mesibov GB, Hatton DD, Clark RD, Roberts JE, et al. (1998) Autistic behavior in young boys with fragile X syndrome. J Autism Dev Disord 28: 499–508.
- 9. Brock M, Hatton D (2010) Distinguishing features of autism in boys with fragile X syndrome. J Intellect Disabil Res.
- 10. Symons FJ, Clark RD, Hatton DD, Skinner M, BaileyJr DB (2003) Self-injurious behavior in young boys with fragile X syndrome. Am J Med Genet A 118A: 115–121.
- 11. Loesch DZ, Bui QM, Dissanayake C, Clifford S, Gould E, et al. (2007) Molecular and cognitive predictors of the continuum of autistic behaviours in fragile X. Neurosci Biobehav Rev 31: 315–326.
- 12. Dutch-Belgian Fragile X Consortium (1994) Fmr1 knockout mice: a model to study fragile X mental retardation. Cell 78: 23–33.
- 13. American psychiatric association (1994) Diagnostic and statistical manual of mental disorders (DSM-IV). Washington, DC.
- 14. Baranek GT (2002) Efficacy of sensory and motor interventions for children with autism. J Autism Dev Disord 32: 397–422.
- 15. McAlonan GM, Daly E, Kumari V, Critchley HD, van Amelsvoort T, et al. (2002) Brain anatomy and sensorimotor gating in Asperger's syndrome. Brain 125: 1594–1606.
- 16. Perry W, Minassian A, Lopez B, Maron L, Lincoln A (2007) Sensorimotor gating deficits in adults with autism. Biol Psychiatry 61: 482–486.
- 17. Yuhas J, Cordeiro L, Tassone F, Ballinger E, Schneider A, et al. (2010) Brief Report: Sensorimotor Gating in Idiopathic Autism and Autism Associated with Fragile X Syndrome. J Autism Dev Disord.
- 18. Ornitz EM, Lane SJ, Sugiyama T, de Traversay J (1993) Startle modulation studies in autism. J Autism Dev Disord 23: 619–637.
- 19. Polimeni MA, Richdale AL, Francis AJ (2005) A survey of sleep problems in autism, Asperger's disorder and typically developing children. J Intellect Disabil Res 49: 260–268.
- 20. Gail Williams P, Sears LL, Allard A (2004) Sleep problems in children with autism. J Sleep Res 13: 265–268.
- 21. Muris P, Steerneman P, Merckelbach H, Holdrinet I, Meesters C (1998) Comorbid anxiety symptoms in children with pervasive developmental disorders. J Anxiety Disord 12: 387–393.
- 22. Tuchman R, Rapin I (2002) Epilepsy in autism. Lancet Neurol 1: 352–358.
- 23. Crawley JN (2007) Mouse behavioral assays relevant to the symptoms of autism. Brain Pathol 17: 448–459.
- 24. Liu ZH, Chuang DM, Smith CB Lithium ameliorates phenotypic deficits in a mouse model of fragile X syndrome. Int J Neuropsychopharmacol 1–13.
- 25. McNaughton CH, Moon J, Strawderman MS, Maclean KN, Evans J, et al. (2008) Evidence for social anxiety and impaired social cognition in a mouse model of fragile X syndrome. Behav Neurosci 122: 293–300.
- 26. Mines MA, Yuskaitis CJ, King MK, Beurel E, Jope RS (2010) GSK3 influences social preference and anxiety-related behaviors during social interaction in a mouse model of fragile X syndrome and autism. PLoS One 5: e9706.
- 27. Mineur YS, Sluyter F, de Wit S, Oostra BA, Crusio WE (2002) Behavioral and neuroanatomical characterization of the Fmr1 knockout mouse. Hippocampus 12: 39–46.
- 28. Mineur YS, Huynh LX, Crusio WE (2006) Social behavior deficits in the Fmr1 mutant mouse. Behav Brain Res 168: 172–175.
- 29. Spencer CM, Alekseyenko O, Serysheva E, Yuva-Paylor LA, Paylor R (2005) Altered anxiety-related and social behaviors in the Fmr1 knockout mouse model of fragile X syndrome. Genes Brain Behav 4: 420–430.
- 30. D'Hooge R, Nagels G, Franck F, Bakker CE, Reyniers E, et al. (1997) Mildly impaired water maze performance in male Fmr1 knockout mice. Neuroscience 76: 367–376.
- 31. Paradee W, Melikian HE, Rasmussen DL, Kenneson A, Conn PJ, et al. (1999) Fragile X mouse: strain effects of knockout phenotype and evidence suggesting deficient amygdala function. Neuroscience 94: 185–192.
- 32. The Dutch-Belgian Fragile X Consortium (1994) Fmr1 knockout mice: a model to study fragile X mental retardation. Cell 78: 23–33.
- 33. Van Dam D, D'Hooge R, Hauben E, Reyniers E, Gantois I, et al. (2000) Spatial learning, contextual fear conditioning and conditioned emotional response in Fmr1 knockout mice. Behav Brain Res 117: 127–136.
- 34. Yan QJ, Asafo-Adjei PK, Arnold HM, Brown RE, Bauchwitz RP (2004) A phenotypic and molecular characterization of the fmr1-tm1Cgr fragile X mouse. Genes Brain Behav 3: 337–359.
- 35. Zhao MG, Toyoda H, Ko SW, Ding HK, Wu LJ, et al. (2005) Deficits in trace fear memory and long-term potentiation in a mouse model for fragile X syndrome. J Neurosci 25: 7385–7392.
- 36. Restivo L, Ferrari F, Passino E, Sgobio C, Bock J, et al. (2005) Enriched environment promotes behavioral and morphological recovery in a mouse model for the fragile X syndrome. Proc Natl Acad Sci U S A 102: 11557–11562.
- 37. Ventura R, Pascucci T, Catania MV, Musumeci SA, Puglisi-Allegra S (2004) Object recognition impairment in Fmr1 knockout mice is reversed by amphetamine: involvement of dopamine in the medial prefrontal cortex. Behav Pharmacol 15: 433–442.
- 38. Chen L, Toth M (2001) Fragile X mice develop sensory hyperreactivity to auditory stimuli. Neuroscience 103: 1043–1050.
- 39. de Vrij FM, Levenga J, van der Linde HC, Koekkoek SK, De Zeeuw CI, et al. (2008) Rescue of behavioral phenotype and neuronal protrusion morphology in Fmr1 KO mice. Neurobiol Dis 31: 127–132.
- 40. Frankland PW, Wang Y, Rosner B, Shimizu T, Balleine BW, et al. (2004) Sensorimotor gating abnormalities in young males with fragile X syndrome and Fmr1-knockout mice. Mol Psychiatry 9: 417–425.
- 41. Nielsen DM, Derber WJ, McClellan DA, Crnic LS (2002) Alterations in the auditory startle response in Fmr1 targeted mutant mouse models of fragile X syndrome. Brain Res 927: 8–17.
- 42. Qin M, Kang J, Smith CB (2005) A null mutation for Fmr1 in female mice: effects on regional cerebral metabolic rate for glucose and relationship to behavior. Neuroscience 135: 999–1009.
- 43. Musumeci SA, Bosco P, Calabrese G, Bakker C, De Sarro GB, et al. (2000) Audiogenic seizures susceptibility in transgenic mice with fragile X syndrome. Epilepsia 41: 19–23.
- 44. Pacey LK, Heximer SP, Hampson DR (2009) Increased GABA(B) receptor-mediated signaling reduces the susceptibility of fragile X knockout mice to audiogenic seizures. Mol Pharmacol 76: 18–24.
- 45. Qiu LF, Lu TJ, Hu XL, Yi YH, Liao WP, et al. (2009) Limbic epileptogenesis in a mouse model of fragile X syndrome. Cereb Cortex 19: 1504–1514.
- 46. Yan QJ, Rammal M, Tranfaglia M, Bauchwitz RP (2005) Suppression of two major Fragile X Syndrome mouse model phenotypes by the mGluR5 antagonist MPEP. Neuropharmacology 49: 1053–1066.
- 47. Zupan B, Toth M (2008) Wild-type male offspring of fmr-1+/- mothers exhibit characteristics of the fragile X phenotype. Neuropsychopharmacology 33: 2667–2675.
- 48. Ivanco TL, Greenough WT (2002) Altered mossy fiber distributions in adult Fmr1 (FVB) knockout mice. Hippocampus 12: 47–54.
- 49. Dobkin C, Rabe A, Dumas R, El Idrissi A, Haubenstock H, et al. (2000) Fmr1 knockout mouse has a distinctive strain-specific learning impairment. Neuroscience 100: 423–429.
- 50. D'Amato FR, Pavone F (1996) Reunion of separated sibling mice: neurobiological and behavioral aspects. Neurobiol Learn Mem 65: 9–16.
- 51. Moles A, D'Amato FR (2000) Ultrasonic vocalization by female mice in the presence of a conspecific carrying food cues. Anim Behav 60: 689–694.
- 52. Moy SS, Nadler JJ, Perez A, Barbaro RP, Johns JM, et al. (2004) Sociability and preference for social novelty in five inbred strains: an approach to assess autistic-like behavior in mice. Genes Brain Behav 3: 287–302.
- 53. Nadler JJ, Moy SS, Dold G, Trang D, Simmons N, et al. (2004) Automated apparatus for quantitation of social approach behaviors in mice. Genes Brain Behav 3: 303–314.
- 54. McFarlane HG, Kusek GK, Yang M, Phoenix JL, Bolivar VJ, et al. (2008) Autism-like behavioral phenotypes in BTBR T+tf/J mice. Genes Brain Behav 7: 152–163.
- 55. Terranova ML, Laviola G, Alleva E (1993) Ontogeny of amicable social behavior in the mouse: gender differences and ongoing isolation outcomes. Dev Psychobiol 26: 467–481.
- 56. Blundell J, Blaiss CA, Etherton MR, Espinosa F, Tabuchi K, et al. (2010) Neuroligin-1 deletion results in impaired spatial memory and increased repetitive behavior. J Neurosci 30: 2115–2129.
- 57. Etherton MR, Blaiss CA, Powell CM, Sudhof TC (2009) Mouse neurexin-1alpha deletion causes correlated electrophysiological and behavioral changes consistent with cognitive impairments. Proc Natl Acad Sci U S A 106: 17998–18003.
- 58. Hughes RN (2004) The value of spontaneous alternation behavior (SAB) as a test of retention in pharmacological investigations of memory. Neurosci Biobehav Rev 28: 497–505.
- 59. King DL, Arendash GW (2002) Behavioral characterization of the Tg2576 transgenic model of Alzheimer's disease through 19 months. Physiol Behav 75: 627–642.
- 60. Csomor PA, Yee BK, Vollenweider FX, Feldon J, Nicolet T, et al. (2008) On the influence of baseline startle reactivity on the indexation of prepulse inhibition. Behav Neurosci 122: 885–900.
- 61. Yee BK, Chang T, Pietropaolo S, Feldon J (2005) The expression of prepulse inhibition of the acoustic startle reflex as a function of three pulse stimulus intensities, three prepulse stimulus intensities, and three levels of startle responsiveness in C57BL6/J mice. Behav Brain Res 163: 265–276.
- 62. Pietropaolo S, Singer P, Feldon J, Yee BK (2008) The postweaning social isolation in C57BL/6 mice: preferential vulnerability in the male sex. Psychopharmacology (Berl) 197: 613–628.
- 63. Pietropaolo S, Feldon J, Yee BK (2008) Nonphysical contact between cagemates alleviates the social isolation syndrome in C57BL/6 male mice. Behav Neurosci 122: 505–515.
- 64. Pietropaolo S, Crusio WE (2009) Strain-Dependent Changes in Acoustic Startle Response and its Plasticity Across Adolescence in Mice. Behav Genet 39: 623–31.
- 65. Yee BK, Russig H, Feldon J (2004) Apomorphine-induced prepulse inhibition disruption is associated with a paradoxical enhancement of prepulse stimulus reactivity. Neuropsychopharmacology 29: 240–248.
- 66. Yee BK, Chang DL, Feldon J (2004) The effects of dizocilpine and phencyclidine on prepulse inhibition of the acoustic startle reflex and on prepulse-elicited reactivity in C57BL6 mice. Neuropsychopharmacology 29: 1865–1877.
- 67. Yee BK, Chang T, Pietropaolo S, Feldon J (2005) The expression of prepulse inhibition of the acoustic startle reflex as a function of three pulse stimulus intensities, three prepulse stimulus intensities, and three levels of startle responsiveness in C57BL6/J mice. Behav Brain Res 163: 265–276.
- 68. Swerdlow NR, Braff DL, Geyer MA (2000) Animal models of deficient sensorimotor gating: what we know, what we think we know, and what we hope to know soon. Behav Pharmacol 11: 185–204.
- 69. Vergnes M, Marescaux C, Micheletti G, Reis J, Depaulis A, et al. (1982) Spontaneous paroxysmal electroclinical patterns in rat: a model of generalized non-convulsive epilepsy. Neurosci Lett 33: 97–101.
- 70. Geyer M, Swerdlow NR (1998) Measurement of Startle Response, Prepulse Inhibition, and Habituation. Current Protocols in Neuroscience 8.7.1–8.7.15.
- 71. Csomor PA, Vollenweider FX, Feldon J, Yee BK (2005) On the feasibility to detect and to quantify prepulse-elicited reaction in prepulse inhibition of the acoustic startle reflex in humans. Behav Brain Res 162: 256–263.
- 72. Dominick KC, Davis NO, Lainhart J, Tager-Flusberg H, Folstein S (2007) Atypical behaviors in children with autism and children with a history of language impairment. Res Dev Disabil 28: 145–162.
- 73. Horrigan JP, Barnhill LJ (1997) Risperidone and explosive aggressive autism. J Autism Dev Disord 27: 313–323.
- 74. Brodkin ES, McDougle CJ, Naylor ST, Cohen DJ, Price LH (1997) Clomipramine in adults with pervasive developmental disorders: a prospective open-label investigation. J Child Adolesc Psychopharmacol 7: 109–121.
- 75. Schreier HA (1998) Risperidone for young children with mood disorders and aggressive behavior. J Child Adolesc Psychopharmacol 8: 49–59.
- 76. Spivak B, Golubchik P, Mozes T, Vered Y, Nechmad A, et al. (2004) Low platelet-poor plasma levels of serotonin in adult autistic patients. Neuropsychobiology 50: 157–160.
- 77. Bontekoe CJ, McIlwain KL, Nieuwenhuizen IM, Yuva-Paylor LA, Nellis A, et al. (2002) Knockout mouse model for Fxr2: a model for mental retardation. Hum Mol Genet 11: 487–498.
- 78. Bernardet M, Crusio WE (2006) Fmr1 KO mice as a possible model of autistic features. ScientificWorldJournal 6: 1164–1176.
- 79. Scattoni ML, Gandhy SU, Ricceri L, Crawley JN (2008) Unusual repertoire of vocalizations in the BTBR T+tf/J mouse model of autism. PLoS One 3: e3067.
- 80. Scattoni ML, McFarlane HG, Zhodzishsky V, Caldwell HK, Young WS, et al. (2008) Reduced ultrasonic vocalizations in vasopressin 1b knockout mice. Behav Brain Res 187: 371–378.
- 81. Happe F, Ronald A, Plomin R (2006) Time to give up on a single explanation for autism. Nat Neurosci 9: 1218–1220.
- 82. Radde R, Duma C, Goedert M, Jucker M (2008) The value of incomplete mouse models of Alzheimer's disease. Eur J Nucl Med Mol Imaging 35: Suppl 1S70–74.