Los Modelos de desarrollo de la identidad étnica

To corroborate the behavioural preference results I measured the induction of Zenk-immunoreactivity in females when listening to conspecific or heterospecific songs (i.e., canary song). I assigned subjects to one of the playback conditions counterbalancing across developmental treatment, if they participated in the cognitive treatments, and the order in which they performed the behavioural preference comparisons.

4.2.4.1Playback procedure

Prior to the playback session, I housed birds individually for 48 h in a cage within a sound attenuation chamber with access to food and water ad libitum (Eckel Noise Control Technologies, Morrisburg, ON, Canada, model AB-2000 S). Lights in the chamber were synchronized to the same photoperiod as the colony room and two speakers (Spin-45 speakers, Labtec, WA, USA) were placed on either side of the cage. On the floor of the chamber was a microphone that allowed us to monitor the playback session. This was to ensure the playback was successful and that the bird did not vocalize during the session. There was minimal to no vocalizations from all subjects and therefore I do not account for vocal output as a factor in the analyses.

To create the playback stimuli for the Zenk playbacks, I used the same starling and canary songs used in the conspecific versus heterospecific behavioural preference comparison (Table 4-2). The starling playback consisted of 5 starling songs, each separated by 4.6 s of silence, repeated 7 times. The canary playback consisted of the 5

canary songs, each separated by 3 s of silence, repeated 18 times. Therefore, the starling

and canary playbacks had approximately equal sound:silence ratios of 1639:161 s and

1698:102 s, respectively.

All playback sessions commenced at 13:30 h daily. Fifteen minutes prior to

playback, I turned the chamber lights off (to deter subjects from vocalizing) and began

monitoring the auditory environment within the chamber. I played either a starling or

canary stimulus for 30 minutes, followed by 30 minutes of silence to maximize Zenk

induction (Mello and Clayton 1994). All sounds files were played at a maximum of 70

dB SPL as measured from the bird’s position in the closed chamber.

Once the playback session was completed, birds were deeply anesthetized with

isoflurane and transcardially perfused with phosphate buffered saline (PBS; pH 7.4)

followed by 4% buffered paraformaldehyde. Brains were then removed from the skull,

stored in 4% paraformaldehyde for 24 h and then in 30% sucrose (in PBS) for 48 h.

Brains were then frozen on powdered dry ice and then stored in at -80 °C until later

analysis. Prior to histological and immunohistochemistry analyses, each brain was cut in

half along the sagittal plane and either the left or right hemisphere was selected randomly

for further analyses.

4.2.4.2Zenk immunohistochemistry

Using a cryostat, I sectioned brains in the sagittal plane in 40 µm sections. I put alternating sections into 0.1 M PBS for Zenk immunohistochemistry and Nissl histology

(explained below). I ran immunohistochemistry in 6 runs, counterbalanced across

conditions. First, free-floating sections were washed twice in 0.1 M PBS, followed by a

a 1 h incubation in 10% normal goat serum (Vector, Burlingame, CA, USA) diluted in 0.3% Triton in PBS (PBST). Sections were then incubated for 20 h in the primary

antibody (anti-Egr-1 sc-189, Santa Cruz Biotechnology, Dallas, TX, USA) diluted 1:4000 in 0.3% PBST. I then washed section three times in 0.1% PBST and followed this with a 1 h incubation in the biotinylated secondary antibody diluted 1:250 in 0.3% PBST (goat anti-rabbit IgG, Vector). Following three washes in 0.1% PBST, sections were incubated in avidin-biotin horseradish-peroxidase complex (Vector Elite ABC kit) for 1-hour and then washed twice in 0.1% PBST. Section were then visualized with diaminobenzidine

solution (SigmaFast DAB) and washed 5 times in 0.1 M PBS and later mounted onto

gelatin-coated microscope slides. Last, mounted sections were serially dehydrated with graded ethanols, cleared in a solvent (Harleco Neoclear, EMD Chemicals), and protected by affixing a coverslip with Permount (Fisher Scientific).

4.2.4.3Zenk quantification

Using a similar protocol as previous studies (Gentner et al. 2001; Maney et al. 2003; Hernandez and Macdougall-Shackleton 2004; McKenzie et al. 2006; Schmidt et al. 2013), I measured the number of Zenk-immunoreactive cells within three regions of the telencephalon that have been found to show increased levels of immunoreactivity in response to conspecific song (Mello and Clayton 1994; Gentner et al. 2001; Maney et al. 2003): the CMM, dorsal NCM (NCMd) and ventral NCM (NCMv). In female starlings, NCMv has been shown specifically to respond to variation in quality of male conspecific song (Gentner et al. 2001).

I began by measuring the most medial section by which NCM was visibly attached to the rest of the brain and field L2 was visible due to its lack of

immunoreactivity (Mello and Clayton 1994). In this section, and then next 5 lateral to it, I sampled each region by focusing on the center of the structure. Therefore, I measured six sections (alternating every 40 µm) for a total sampling area that spanned 480 µm wide mediolaterally (a comparable distance covered in other studies; Maney et al. 2003; Hernandez and Macdougall-Shackleton 2004; Schmidt et al. 2013). An observer blind to treatment and playback condition took images (0.515 x 0.386 mm) within each sampling region using a Leica Digital CCD camera mounted on a Leica DM5000B light

microscope using a X20 objective lens.

Using ImageJ software (National Institute of Health, USA), I counted the number of Zenk-immunoreactive cells within each image. First, I converted images to 8-bit grayscale and then counted the number of particles with an optical density that was above a threshold value using the threshold feature in ImageJ. Due to variability in the intensity of background staining, this threshold was set manually for each image such that a blind observer agreed that the highlighted pixels matched where nuclei were visible (Schmidt et al. 2013). To set the exclusion limits for cell size, I calculated the size of 60 cells (three cells per bird from randomly chosen sections) and then set the maximum/minimum cell size as the average plus/minus two standard deviations. Exclusion limits for sphericity were set at 0.65.

4.2.4.4Nissl histology and quantification

I mounted the alternate series of brain sections onto gelatin-coated microscope slides and let them air dry. Next, sections were stained with thionin, serially dehydrated in graded ethanols, cleared in a solvent (Harleco Neoclear) and protected by affixing a coverslip with Permount (Fisher Scientific). I quantified the volume of the three song-

control nuclei of interest: HVC, area X, and the robust nucleus of the archistriatum (RA). Volumes were calculated by taking images from every section that contained the nuclei of interest using a 5-megapixel digital camera (Spot Idea; Diagnostics Instruments) connected to a Zeiss Axiophot microscope. Using ImageJ, I traced the outlines of the nuclei and then using the formula for the volume of a frustum I estimated the total volume of the nuclei. As every second section was measured, volume estimates were made using areas spaced at 80 µm intervals. To estimate total brain size (telencephalon volume), microscope slides were scanned at 1200 dpi on a flatbed scanner with a

transparency adapter. Using ImageJ, I traced the telencephalon in every 20th section (800

µm sampling interval), and estimated total telencephalon volume using the formula for the volume of a frustum.

4.2.5

Data and statistical analysis

All data were analyzed using linear mixed models. I examined the effects of developmental treatment and if birds participated in the cognitive experiments (i.e., cognitive treatment). Therefore, developmental treatment, cognitive treatment, and their interaction were entered as fixed effects in all models. Models were subsequently tailored to each experiment by adding additional fixed effects of interest (and any of their higher order interactions with developmental treatment and cognitive treatment) and covariates of interest.

For the behavioural preference tests, I ran separate analyses for each preference test on each dependent variable. Block was entered as a repeated factor (unstructured covariance structure) and as a fixed effect. Nest of origin, order of the preference test, and the location of the silent perch were initially entered as random effects, but none of these

variables contributed significantly to any of the models so they were removed from the analysis. In addition to comparisons across the treatments, I ran one-sample t-tests for each treatment to determine if the preference scores differed significantly from chance (i.e., a score of 0.50). To determine if birds across treatments groups were equally motivated during the test I ran a full model using the total amount of song triggered during the playbacks as the dependent variable.

Zenk-immunoreactivity was analyzed using the total number of Zenk-

immunoreactive cells in each region as the dependent variable. Fixed effects of brain region (CMM, NCMd, NCMv), playback (starling/canary), and the covariate of telencephalon volume were entered along with random effects of nest of origin and hemisphere (left or right) analyzed. Hemisphere did not contribute significantly and was removed from the analysis.

I calculated for each song-control nucleus the volume of the nucleus as a

proportion of overall telencephalon size as the dependent variable. I included region as a fixed effect and included it with all higher-order interactions with developmental

treatment and if birds participated in the cognitive treatment. Random effects of nest of origin and hemisphere analyzed were first included, although neither of these effects contributed significantly to the model and were removed from the analysis. Last, I ran HVC size (as a proportion of telencephalon size) as a predictor against the preference ratios for both the conspecific/heterospecific and long/short song bout comparisons, while controlling for nest of origin. Nest remained in the conspecific/heterospecific analysis but was removed from the long/short analysis.

All models were first constructed as fully loaded models (all predictors and interactions included). I then calculated the minimal adequate model by removing non- significant predictors using log-likelihood ratio tests to maintain parsimony and improve model fit (Chapter 2; West et al. 2007). All significant results reported here are the minimal adequate models with restricted maximum likelihood estimation. Statistics reported for non-significant effects are the values from the full model prior to removal. Post-hoc tests were carried out using Bonferroni corrections. I checked residuals for each model against a normal distribution and found no violations of normality. SPSS Statistics (v. 21) was used for all analyses.

4.3

Results