Gap-detection using the AudioBox, in MBP neo mice …

PPI of the ASR tests spontaneous responses related to a reflex. I was interested in testing gap-detection using a paradigm that resembled a more naturalistic environment. For this reason, I used an automated system for mice behavior: the AudioBox (NewBehavior, TSE systems) (de Hoz and Nelken, 2014) (see Materials and Methods section II.IX.II). Briefly, in the AudioBox, mice leave in a large home-cage in a large social group. Animals have food ad libitum, but for drinking water, they need to enter the sound box, which has a corner where they are recognized by the system because each animal was tagged previously with a transponder ID on the neck. Above the corner, there is a speaker, with which animals can be exposed to specific sounds and need to learn to discriminate them and behave accordingly.

‘Safe’ sounds carry the meaning of the possibility of drinking water, so animals can safely nosepoke and get water. ‘Conditioned’ sounds have a negative meaning; when animals hear them, they should not try to get water, otherwise they will get an air puff. In this case, I used a BBN continuous sound as the ‘safe’ sound and a sound with a gap recognizable gap of 50 ms was used as the ‘conditioned’ sound. Mice were then tested for the detection of different

93 gap-lengths in the sound (each of them also conditioned to avoid generalization of avoiding nose poking to any new sound).

Because the MBP^shi mice have a very strong motor impairment, and usually tend to be more stressed than control mice, I was not able to use this model in the AudioBox.

Nevertheless the partial dysmyelination mice did not show any motor impairment (data not shown) so they were suitable for this paradigm. First, the basic behavior in the AudioBox was tested between the two groups. I did not find a difference between the mean visit number per day between control and MBP^neo animals (p=0.32) when using the average of all days for the duration of the experiment (see Figure 36-A, control in black vs MBP^neo in orange, total duration depicted by ‘t’). Nevertheless, there was a significant difference on the average visit number per day, when considering only the first 4 days of exposure to the AudioBox (p=0.012) (see Figure 36-A, control in gray vs MBP^neo in peach, first 4 days depicted by ‘4’). I did not observe a difference in the mean visit number per day in control animals when comparing the total duration of the experiment (~40 days) and only the first 4 days (p=0.17).

Nevertheless, MBP^neo mice showed a reduction in the mean number of visits per day in the first four days compared to the total duration (p=0.015) (mutant total duration in orange vs mutant first 4 days in peach). This means that when the animals were first exposed to the AudioBox, during the initial habituation period of 4 days, MBP^neo mice did significantly less visits to the corner than control littermates. This could represent a behavioral problem with novelty coping in MBP^neo mice. Nevertheless, they only showed this behavior for a brief period at the very beginning of the experiment, and afterwards, they did similar amount of visits per day. This was especially important because mice that make fewer visits would be less exposed to the sounds, and this could have an effect in their performance. To make sure the comparisons I am doing between groups are accurate, I measured the average number of visits that the animals made per day for the gaps used. I found no differences between control and MBP^neo animals in the average amount of visits per day, in any of the gaps tested, which means both groups had an equal exposure to the gaps (ANOVA, F(1,162)=1.11,p=0.29) (Figure 36-B). There was also no effect of the gap to which the animals were exposed, in the amount of visits they were doing (ANOVA, F(8,162)=0.56, p=0.81), which means that even though the animals sometimes had a challenging task when detecting small gaps, this did not affect their motivation to continue doing visits to the corner.

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A B

C

D

Figure 36. Behavioral gap-detection in the AudioBox is impaired in MBP^neo mice.

A) Quantification of the total average visits per day for the entire duration of the experiment (x axis: ‘t’) for control (black) and MBP^neo mice (orange). The average number of visits per day for the first 4 days of habituation (x axis: ‘4’) is represented for control (gray) and mutant (peach) animals. No differences between groups were seen for the total experimental duration, but a significant difference was seen between groups in the first 4 days of habituation (p=0.012). Gray bars show the mean of each condition.

B) Shows the quantification of the average number of visits per sound. No differences were seen in any of the gaps tested for both groups (ANOVA, p=0.29). In C) the quantification of visit duration represents a measure of perceptual difficulty for control (black) and mutant (orange) animals. A significant increase in the visit duration was seen overall the gaps tested (ANOVA, p=0.0017). D) The quantification of avoidance behavior revealed that above the gap-detection threshold (>1 ms gap), there is a significant difference between control (black) and mutant (orange) animals (ANOVA, p=0.014) showing the MBP^neo mice reduced avoidance, meaning that they have difficulties detecting gaps in sound and therefore have temporal acuity deficits in this behavioral paradigm.

95 A way of quantifying the perceptual difficulties of the task the animals are performing is by measuring the duration of the visits to the corner, depending on the sound the animals were exposed to.

I measured the mean time that the animals spent on each visit depending on the sound that was being played (Figure 36-C) and found that overall, MBP^neo mice tend to spend more time in the corner (ANOVA, F(1,288)=10.08, p=0.0017). In addition, I found a strong dependence of the gap length on the visit length (ANOVA, F(15,288)=80.16, p<0.0001), meaning that animals recognized the gaps that were conditioned (all except 0 ms), and were leaving the corner faster when they heard those sounds (in ~3 seconds) compared to when they heard the ‘safe’ sound (~10 seconds).

Finally, I measured the behavioral output of the gap-detection task by quantifying the number of visits where animals did not do a nosepoke (avoidance percentage) depending on the sound they were hearing. The avoidance percentage increases proportionally with the increase in gap-length (ANOVA, F(14,270)=35.21, p<0.0001) (Figure 36-D), meaning that animals learnt to recognize that sounds with a gap meant not to drink water, and they avoided trying to get water effectively. In addition, we see a strong categorization of the gap lengths, meaning that, in fact, smaller gaps were more difficult to recognize in this behavioral setup, than longer gaps. We can also observe that from gaps of 2 to 6 ms, there is a tendency of the mutant animals to have lower avoidance percentages, being closer to the threshold line (dotted horizontal line) that represents 80 % of avoidance, compared to control littermates.

Nevertheless, at 1 ms gap, it seems that there is no difference between groups, that could be related to the fact that the threshold for gap detection is higher than 1 ms in mice. When comparing both groups above the gap-detection threshold (2 ms), which has also been reported for mice in other studies (Radziwon et al., 2009; Strenzke et al., 2016; Walton et al., 1997), taking gap-lengths from 2 ms until 45 ms, I found a significant difference in the percentage of nose-poke avoidance, having the MBP^neo mice significantly lower avoidance percentage (ANOVA, F(1,234)=6.07, p=0.014), meaning that MBP^neo mice also show a temporal acuity impairment in this behavioral paradigm. In this case, I was able to find a correlate of the electrophysiological temporal acuity abnormalities seen in these mutants, with the gap-detection measurement from the inhibition of the startle reflex, and with a naturalistic behavioral setup. With this, I confirm with full certainty that MBP^neo mice show reduced temporal acuity, which has a strong neuronal correlate in the auditory cortex.

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