Schematic illustration of the different paradigms for the animal groups in cognitive training.

<p>(A) Control group without training in an operant task. (B) S-R task. During training with colored operant keys, each trial started with the presentation of either a green or a red stimulus on one of the three keys. After 15 correct pecks the REWARD phase started with 3 s food access. This was followed by an intertrial interval (ITI) before the next trial started. (C) SMTS task. Training in the simultaneous matching-to-sample task always started with the presentation of either a green or red stimulus as the SAMPLE on the central key. 15 pecks onto this directly started the CHOICE period, where the pigeons had to peck the lateral key that matched the color of the sample. During this phase all keys were simultaneously illuminated. No maintaining of information was required. A single correct peck started the REWARD phase with 3 s food access. This was followed by an ITI before the next trial started. (D) DMTS task. During training of the delayed matching-to-sample task each trial started with the presentation of either a green or red stimulus as the SAMPLE on the central key. 15 pecks onto this started a 4 s DELAY period during which the animals had to memorize the sample color. Then, the lateral keys lit and started the CHOICE period, where the pigeons had to peck the lateral key that matched the color of the sample. A single correct peck started the REWARD phase with 3 s food access. This was followed by an ITI before the next trial started.</p

Schematic depiction of the logical structure of the behavioral approach.

<p>Expression levels of dopamine receptors are tested in different animal groups under control conditions (no operant behavioral task involved), and during execution of an S-R, an SMTS, or a DMTS task. Much like Russian “Matryoshka” dolls, each of the tasks involves the cognitive components of the previous one, but adds new components that are depicted on the right side of each box.</p

Comparison of pigeon DA receptor probe sequences to gene sequences in chicken (c) and human (h).

<p>Data is presented as x/y (%), with x the number of identical bases and y the total length of the fragment followed by the percentage value of sequence identity. Similarities to pigeon sequences differ between chicken and human and are generally larger for chicken sequences. For the D1D probe only low correspondences were detected to the D1B/D5 gene, while high correlations were found with the chicken D1D gene. Empty boxes indicate absence of any significant identities.</p

Differences of D1-like mRNA levels in the NCL (A) and the anterior forebrain (aFB; B) between the trained groups.

<p>In the NCL and in the aFB, D1A receptor expression levels decreased in the S-R and in the SMTS groups, and increased to control levels after training in the DMTS group. D1B receptor expression increased in both areas in the DMTS group. D1D receptor expression levels decreased in the S-R and the SMTS groups in both areas, and increased to control levels in the NCL while increasing above control levels in the aFB. Thus, a rigid training program that involved a reward-dependent learning of an association between external stimuli and own responses resulted in a down-regulation of the expression of D1A and D1D. D1B expression is only affects after DMTS training. A sole comparison of control and DMTS tasks would have resulted in the wrong conclusion that a DMTS procedure increases D1B expression levels but has no effect on D1A or D1D. All data is presented as mean ± SEM; n = 10 each group. All statistical analyses were only performed on the original data (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036484#pone-0036484-g003" target="_blank">Figure 3</a>). Significant differences between groups are marked with asterisks (*p<0.05; **p<0.01; ***p<0.001).</p

Quantification of dopamine receptor (DAR) mRNA levels in the NCL (A) and the anterior forebrain (aFB; B) of the control and the trained groups.

<p>Expression of different DA receptors at the mRNA level is shown relative to the expression of the housekeeping gene histone H3.3B (mean ± SEM; n = 10 each group). Significant differences between groups are marked with asterisks (*p<0.05; **p<0.01; ***p<0.001).</p

Primers used for real-time RT-PCR.

<p>The primers were used for quantitative RT-PCR. Each primer pair binds specifically the indicated gene without cross-reactions. The obtained fragments were verified by sequence analysis.</p

The siRNA-mediated knockdown of GluN3A in 46C-derived neural stem cells affects mRNA expression levels of neural genes, including known iGluR interactors

<div><p>For years, GluN3A was solely considered to be a dominant-negative modulator of NMDARs, since its incorporation into receptors alters hallmark features of conventional NMDARs composed of GluN1/GluN2 subunits. Only recently, increasing evidence has accumulated that GluN3A plays a more diversified role. It is considered to be critically involved in the maturation of glutamatergic synapses, and it might act as a molecular brake to prevent premature synaptic strengthening. Its expression pattern supports a putative role during neural development, since GluN3A is predominantly expressed in early pre- and postnatal stages. In this study, we used RNA interference to efficiently knock down GluN3A in 46C-derived neural stem cells (NSCs) both at the mRNA and at the protein level. Global gene expression profiling upon GluN3A knockdown revealed significantly altered expression of a multitude of neural genes, including genes encoding small GTPases, retinal proteins, and cytoskeletal proteins, some of which have been previously shown to interact with GluN3A or other iGluR subunits. Canonical pathway enrichment studies point at important roles of GluN3A affecting key cellular pathways involved in cell growth, proliferation, motility, and survival, such as the mTOR pathway. This study for the first time provides insights into transcriptome changes upon the specific knockdown of an NMDAR subunit in NSCs, which may help to identify additional functions and downstream pathways of GluN3A and GluN3A-containing NMDARs.</p></div

Primers used in qRT-PCRs.

<p>Primers used in qRT-PCRs.</p

Genes affected by the knockdown of GluN3A in 46C-derived NSCs.

<p><b>A:</b> Heatmap of genes statistically significantly (*<i>p</i> < 0.05) differentially expressed in 46C-derived NSCs upon knockdown of GluN3A. GluN3A was knocked down in 46C-derived NSCs using a mixture of GluN3A siRNA1/GluN3A siRNA2 (siNR3), which was compared to a mixture of non-targeting scrambled siRNA1/scrambled siRNA2 (siCtrl) used as a control. Differentially expressed genes were detected using global gene expression profiling. The log₂-fold changes (L) for statistically significantly up- (red) and down-regulated (blue) genes as well as the signal values (S) for two biological replicates per condition (Roman numerals) and the corresponding P-values (P) are illustrated using a color code. <b>B to G:</b> Examples of regulated genes after knockdown of GluN3A in 46C-derived NSCs. The log2-fold change in expression rate is depicted for genes significantly up- and downregulated in 46C-derived NSCs transfected with siRNA against GluN3A in comparison to 46C-derived NSCs transfected with scrambled siRNA. Only genes significantly up- or downregulated (*<i>p</i> < 0.05) are depicted. Red = upregulation; blue = downregulation.</p

Hierarchical clustering of transcriptome data.

<p>Hierarchically clustered biological and technical replicates of the transcriptome data using the Euclidean Distance of the signals as a distance metric. scrambl = scrambled siRNA; siGluN3 = siRNA directed against GluN3A.</p