Brace et al Auditory responses in a rodent model of Attention Deficit Hyperactivity Disorder Louise R. Brace A , Igor Kraev A , Claire L. Rostron A , Michael G. Stewart A , Paul G. Overton B and Eleanor J. Dommett A,C * A Department of Life, Health and Chemical Sciences, The Open University, Milton Keynes. MK7 6AA. U.K. B Department of Psychology, University of Sheffield, Western Bank, Sheffield. S10 2TN. U.K. C Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London. SE1 3QD. U.K. * Corresponding Author Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 9th Floor, Capital House, Guy's Campus, 42 Weston Street, 1
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Brace et al
Auditory responses in a rodent model of Attention Deficit Hyperactivity Disorder
Louise R. BraceA, Igor KraevA, Claire L. RostronA, Michael G. StewartA, Paul G. OvertonB
and Eleanor J. DommettA,C*
ADepartment of Life, Health and Chemical Sciences, The Open University, Milton Keynes.
MK7 6AA. U.K.
BDepartment of Psychology, University of Sheffield, Western Bank, Sheffield. S10 2TN.
U.K.
CDepartment of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King’s
College London, London. SE1 3QD. U.K.
* Corresponding Author
Department of Psychology,
Institute of Psychiatry, Psychology and Neuroscience,
To check that the depth of anaesthesia was comparable in the three strains during testing, the
dominant EEG frequency was obtained using a power spectrum analysis (Spike2) for the
period within which the 150 stimulations where presented. The respiration rate per minute
was calculated during the first and last 30 seconds of this period and then used to calculate an
average rate per minute over the whole recording period. Based on the EEG frequency bands
all animals were found to be in stage III-4, with an EEG frequency of 1-2 Hz during
recordings and have comparable respiration rates using a One-Way ANOVA (F(3)=3.52;
p=0.098) following confirmation of normality of data with a Kolmogorov–Smirnov test.
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Brace et al
Collicular recordings were analysed offline using Spike7, custom-made excel macros
(Sheffield University) and SPSS. All analyses were performed on averaged data where
averages were constructed from the full 5 minute period (150 stimulations) for each of the
five stimulus intensities. The main comparison of interest was between responses in the three
strains across the range of sound intensities. For LFP data a waveform average was created in
Spike7 (1-ms bins, 1 s duration, 0.1 s offset) for each intensity. The waveform average was
exported into the custom-made macro and a response was deemed to have occurred if the
trace extended beyond a pre-determined threshold after stimulus onset. The threshold for
change was set at ±1.96 standard deviations from the mean baseline (i.e. within 95%
confidence levels). This threshold was used to assess three parameters: onset latency, peak-
to-peak amplitude and duration. Onset latency was obtained by recording the time after
stimulus presentation at which the voltage trace extended beyond the threshold. Response
duration was determined by obtaining the time, post-stimulus, when the voltage trace
returned to within baseline levels (i.e. ±1.96 standard deviations of the pre-stimulation mean)
and consistently stayed below this value for 10 ms or 10 bins. The time between onset latency
and the response finishing was then used to calculate duration. Finally, peak-to-peak
amplitude was defined as the voltage difference between the maximum positive peak and the
maximum negative peak in the response period defined by the significant deviation from
baseline. For the MUA, similar measures were utilised following initial extraction of ‘spikes’
from the high-frequency data by thresholding. Individual spikes identified using template
matching (Spike7, CED) on a sample of the data and these used to calculate a threshold
which reliably separated the noise from the spikes. This threshold was used to create a spike
channel and this, in turn was used for analysis. Peri-stimulus time interval histograms
(PSTHs; 1-ms bins, 1 s duration, 0.1 s offset) were constructed from the trial-by-trial spike
counts in this newly created channel within Spike7 and the 100 ms pre-stimulus period was
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Brace et al
defined as baseline activity. An auditory response was deemed to have occurred if, post
stimulus, the activity rose above 1.96 standard deviations of the mean of the baseline period
for at least 5 ms (5 consecutive bins), the first of which was labelled as the onset of a
response. The duration was calculated by measuring when the response fell back to within
the baseline levels for at least 10 ms (10 consecutive bins), the first of which was labelled as
the end of the response. Duration was then given as the difference between onset latency and
the response ending. The amplitude was recorded as the peak value of the response minus the
mean baseline value. Prior to statistical analysis all data were deemed normally distributed
using the Kolmogorov–Smirnov test. Repeated measures ANOVAs with STRAIN as the
between-subjects factor and STIMULUS INTENSITY as the within-subjects factor were
used with a critical p-value of <0.05 considered to be significant. As with the behavioural
data, where Mauchly’s test of sphericity was significant in the ANOVAs, the degrees of
freedom were adjusted using Greenhouse–Geisser correction (Greenhouse and Geisser,
1959).
5.4 Histology
Site reconstruction: Following electrophysiological recordings, animals were transcardially
perfused with physiological saline followed by 4% paraformaldehyde in phosphate buffered
fixative. The brains were the placed in fixative for 24 hours before being transferred to 20%
sucrose for a further 36 hours. They were then frozen to -18 C in isopentane (WWR
International, UK) and cut into 50 µm coronal sections using a cryostat (CM1900, Leica, UK)
with the cutting chamber held at -20 C. The slices were dehydrated with alcohol and Nissl
stained with cresyl violet (0.5%) (Sigma Aldrich, Gillingham, UK), before cover-slipping for
histological verification of recording sites, which were subsequently plotted onto
reconstructed sections from Paxinos and Watson (Paxinos and Watson, 1998) to confirm
location of recording in the superficial layers of the colliculus.
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Brace et al
Collicular volume and cell counts: Animals were given a terminal i.p. dose of sodium
pentobarbitone (Animalcare, York, UK) before being trancardially perfused and the brain
sectioned as described above. For volume analysis of the whole brain and the SC the
Cavalieri principle was used; the first 50 µm section was taken from every 1-in-5 series of
sections throughout the brain were used. For the cell counts, beginning at a random starting
point (between slices 1-5), every 5th section was collected for cell count analysis. For both
measures the slices were dehydrated with alcohol and Nissl stained with cresyl violet (0.5%,
Sigma Aldrich, Gillingham, UK) before cover-slipping for analysis. Images were captured
using a Microfibre digital camera attached to a Nikon Eclipse 80i microscope (Nikon UK
LTD, Kingston-upon-Thames, UK). For volume analysis, images of the section and an
appropriate scale bar were taken at x1 magnification (Nikon Plan UW, 1x/0.04, WD 3.2) and
exported to a freely available reconstruction programme (Reconstruct version 1.1.0.1
http://synapses.clm.utexas.edu/). The whole brain as well as the complete intermediate and
deep layers of the SC, as defined by Paxinos and Watson (Paxinos and Watson, 1998), were
then outlined throughout the slices using the Reconstruct programme. The multiplication of
the cut surface area by the known distance in thickness (250 µm) was calculated to provide
the estimated volume of the examined objects i.e. the whole brain and the intermediate and
deep layers of the colliculus. Factors such as the physical size of the animal influence the
maximum brain size (Raz et al., 1998) and it has therefore been suggested that comparing
solely volumes of intracranial structures between groups would not provide reliable data
(Knutson et al., 2001). As such, the volume fraction of the relevant layers of the SC within
the reference volume (the whole brain) was calculated, to give a proportion of the structure
(i.e. intermediate and deep layers) within the whole brain structure. These data were
confirmed as having a normal distribution using the Kolmogorov–Smirnov test before
analysis was conducted using a One-Way ANOVA to analyse strain differences. For cell
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Brace et al
counts, the images were taken at x40 magnification (Nikon Plan Flor, 40x/0.75, DIC M, WD
0.72). Contours were drawn at low magnification (x1; Nikon Plan UW, 1x/0.04, WD 3.2)
around the region of interest i.e. the superficial layers of the SC, as defined by Paxinos and
Watson (1998). The stereologically unbiased Optical Fractionator method on the Stereo-
Investigator software (MBF Biosciences, Magdeburg, Germany) was used to obtain an
estimate of the total number of cells in the region of interest, as it is not influenced by the
size, shape, spatial orientation, and spatial distribution of the cells studied. . A counting
frame was used (see Figure 2.16) to count cells using the specific rules for counting cells
in the frame (any cell within the frame or touching the top or left lines were included in
the count; similarly any cell touching the bottom or right lines were excluded; if a cell
touched top/left line and the bottom/right line; it was also excluded). The area
sampling fraction can be measured using the formula below;
asf = counting frame areagrid ¿¿¿
The grid spacing and counting frame size were X: 35 µm and Y: 35 µm and constant
throughout the experiment for all animals.. Nuclei from different cell types were
differentiated based on morphological criteria of shape and relative size. Neurons were
identified by their generally larger shape and non-spherical outline, as well as a pale and
uniformly Nissl-stained cytoplasm with a well-marked nucleolus. Glial nuclei were identified
by being generally smaller in size, ovoid shape with the absence of stained cytoplasm, the
presence of a thicker nuclear membrane, and more heterogeneous chromatin within the
nucleus (Cotter et al., 2002). Although we cannot definitively distinguish between glial types,
on the basis of their appearance we believe that the large majority are astrocytes.
Acknowledgments
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Brace et al
The authors would like to thank Steve Walters, Agata Stramek and Karen Evans for their
technical support and care of the animals and Jackie Brown and Paul Gabbott for advice and
guidance on histological techniques.
Financial Disclosures
This work was supported by a PhD studentship provided by the Biomedical Research
Network at the Open University.
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Figure Legends
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Figure 1 The percentage of animals responding to consecutive auditory tones (A) and the
duration of responses as a percentage of the five second period in which the tone was on (B).
There were no significant strain differences in responsiveness. A representative key is shown
in part A.
Figure 2 Locomotor activity for all three strains. There was a main effect of time and strain
on distance travelled (A) and vertical activity (C) but not on average velocity (B). For
stereotypic activity (D) there was a main effect of time but not strain. There was also an
interaction effect for distance travelled. ‘s’ – main effect of strain; ‘t’ main effect of time; ‘x’
interaction. * p<0.05, ** p<0.001. See text for results of posthoc comparisons.
Figure 3 Reconstructed plots of recording sites in the superficial layers of the SC for SHR
(black circles), WKY (grey circles) and WIS (grey triangles). Plots are collapsed onto three
sections through the colliculus (Paxinos and Watson, 1998) with position relative to Bregma
given. There was no significant association between the layer recorded from and strains.
Figure 4 Example of a local field potential auditory response recorded in the SC with a 75 dB
SPL stimulus in an SHR with the stimulus presented at time zero (grey line) (A). The
relationship between LFP response parameters and stimulus intensity is shown for onset
latency (B), peak-to-peak amplitude (C) and duration (D).Overall there was a significant
difference in onset latency for the 65 and 70 dB SPL responses and the SHR had significantly
reduced amplitude in comparison to the control strains. A representative key is shown in part
B. * indicated p<0.05.
Figure 5: Example multiunit auditory response recorded in the SC of an SHR at the 75 dB
SPL intensity The top trace shows a raster plot with a line for each trial whilst the lower trace
is a histogram (1 ms bins) of spike activity with the stimulus presented at time zero (grey
line) (A). The relationship between multiunit response parameters and stimulus intensity is
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Brace et al
shown for onset latency (B), peak-to-peak amplitude (C) and duration (D). Overall there was
a significant main effect of stimulus intensity on onset latency and amplitude. For onset
latency there was also a significant main effect of strain with the SHR having greater onset
latency than control strains although this effect diminished with increasing intensity, creating
a significant interaction between STRAIN and STIMULUS INTENSITY. A representative
key is shown in B.
Figure 6: There was no significant difference between the three strains in terms of superficial
collicular volume (A). However, there were some differences in absolute cell numbers (B),
although these would have been confounded by absolute volume differences between strains.
Independent of volume, glia:neuron ratio (C) and cell density did not differ between strains