Cognitive variation in threespined stickleback (Gasterosteus aculeatus)

Cognition encompasses important mechanisms with which animals are able to adjust their behavior in response to environmental cues. These cognitive processes play a clear role in many fitness-related behaviors such as foraging, predator avoidance, and courtship. Thus, how these processes have evolved are of key scientific interest. Historically, research on the evolution of cognitive traits has largely focused on variation between species. However, particularly in the last couple of decades, there has been increasing interest in examining variation in cognition within a species. These studies no longer look at intraspecific variation as noise, but see it as being potentially adaptive and therefore impacting evolutionary trajectories. Yet, while many of these studies seemingly demonstrate the benefits of different cognitive traits, this has inevitably led to questions about why intraspecific variation is maintained. How costly are these traits? Are there trade-offs that maintain variation? The aim of the research in this dissertation is to study the mechanisms that drive and maintain intraspecific variation in cognition in threespined sticklebacks. This is done from four different angles. First, I tested the hypothesis that learning is part of an overall suite of correlated traits related to how an individual copes with changes in the environment, and that trade-offs between early learning and responsiveness to changes in learning outcomes may maintain cognitive variation. I found that individuals that showed a higher cortisol stress response and that were more reactive to a predatory threat were slower to learn a novel discrimination task, but not necessarily faster to respond when learning conditions changed. Second, I tested the hypothesis that sticklebacks from populations inhabiting different environments are primed to learn different cue associations faster within novel learning conditions. When individuals from two separate populations were trained on either a color vs. spatial discrimination task, the two populations excelled on different tasks: fish from a river habitat performed significantly better on the side version than they did on the color version, while the opposite was observed in fish from a pond habitat. Third, I explored the underlying causes of why some individuals are more responsive than others when there is a change in learning outcomes (i.e., differences in behavioral flexibility) by asking whether individual differences in reversal learning performance were more strongly associated with variation in boldness, neophobia and/or inhibitory control. I found that early performance on reversal learning trials was associated with all three behavioral traits, while time to criterion during reversal learning was independent of the other behaviors. Finally, I took advantage of the radiation of sticklebacks to ask whether behaviors predicted to facilitate adaptation to new environments (i.e., neophilia and inhibitory control) have evolved as stickleback have repeatedly colonized freshwater environments . I found heritable population-level variation in both behaviors, suggesting that increased flexibility has evolved during the stickleback radiation. Altogether these studies highlight the wide range of both intra- and inter-population cognitive variation that can be found in threespined stickleback and further elucidate how trait correlations and ecological differences may drive the maintenance of this variation

A review and synthesis of dog cognition research : the world from a dog’s point of view

textDriven by both applied and theoretical goals, scientific interest in canine cognition has experienced a rapid surge in popularity, especially over the last 15 years (Morell, 2009). Here we provide the most comprehensive review to date of dog cognition research, capturing all the articles (285) we could find on the subject going back to 1911. We begin by summarizing general research trends, first documenting the rapid recent growth in dog cognition research (particularly in the domain of social cognition), and then identifying a number of trends in terms of the cognition topics and dog populations studied. Next, we summarize and synthesize the substantive conclusions emerging from research on non-social (discrimination learning, object permanence, object learning, categorization, object manipulation, quantitative understanding, spatial cognition, memory) and social (responses to human cues, perspective taking, dog-human communication, social learning) cognition. In light of burgeoning research on individual differences in cognition and on the biological organization of cognitive domains, we highlight the potential impact of these topics on dog cognition. Finally, based on our syntheses, we outline some ideas for future research, including recommendations that studies focus on: (1) incorporating multiple sensory modalities (most notably olfaction); (2) using more diverse populations of subjects; (3) replicating studies where current knowledge is based on small study sets or on small samples; (4) identifying fundamental developmental patterns of cognitive development; (5) identifying individual differences in cognitive ability; and (6) identifying potential cognitive constraints (e.g., cognitive abilities that are non-independent due to pleiotropic biological organization).Psycholog

Chapter Four Predictors of Individual Variation in Movement in a Natural Population of Threespine Stickleback (Gasterosteus aculeatus)

Species abundances and distributions are inherently tied to individuals' decisions about movement within their habitat. Therefore, integrating individual phenotypic variation within a larger ecological framework may provide better insight into how populations structure themselves. Recent evidence for consistent individual differences in behaviour prompts the hypothesis that variation in behavioural types might be related to variation in movement in natural environments. In a multiyear mark-recapture study, we found that individual sticklebacks exhibited consistent individual differences in behaviour both within a standardized testing arena designed to measure exploratory behaviour and within a river. Therefore, we asked whether individual differences in movement in a natural river were related to an individual's exploratory behavioural type. We also considered whether body condition and/or the individual's habitat or social environment use was related to movement. There was no evidence that an individual's exploratory behavioural type was related to movement within the river. Instead, an individual's habitat use and body condition interacted to influence natural movement patterns. Individuals in good condition were more likely to move further in the river, but only if they inhabited a vegetated complex part of the river; body condition had no influence on movement in those individuals inhabiting open areas of the river. Our results suggest that individual traits could help improve predictions about how populations may distribute themselves within patchy and complex environments

Temporal dynamics of neurogenomic plasticity in response to social interactions in male threespined sticklebacks

<div><p>Animals exhibit dramatic immediate behavioral plasticity in response to social interactions, and brief social interactions can shape the future social landscape. However, the molecular mechanisms contributing to behavioral plasticity are unclear. Here, we show that the genome dynamically responds to social interactions with multiple waves of transcription associated with distinct molecular functions in the brain of male threespined sticklebacks, a species famous for its behavioral repertoire and evolution. Some biological functions (e.g., hormone activity) peaked soon after a brief territorial challenge and then declined, while others (e.g., immune response) peaked hours afterwards. We identify transcription factors that are predicted to coordinate waves of transcription associated with different components of behavioral plasticity. Next, using H3K27Ac as a marker of chromatin accessibility, we show that a brief territorial intrusion was sufficient to cause rapid and dramatic changes in the epigenome. Finally, we integrate the time course brain gene expression data with a transcriptional regulatory network, and link gene expression to changes in chromatin accessibility. This study reveals rapid and dramatic epigenomic plasticity in response to a brief, highly consequential social interaction.</p></div

Integrating TFs with DEG_x and chromatin accessibility.

<p>These TFs are in the TRN and are enriched in the DAPDEG_x with accessibility indicated. Some of the TFs (in bold) were differentially expressed and in a cluster. The general expression pattern of their cluster is indicated. A complete set of enrichments is in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006840#pgen.1006840.s012" target="_blank">S10 Table</a>.</p

Network of interacting transcription factors (TFs) in the transcriptional regulatory network highlighting enrichments of TFs in clusters of DEG_x.

<p>Each node represents a TF. Slices of pie correspond to different clusters in diencephalon or telencephalon; the key to the clusters is in the lower left corner. A full orange slice represents a diencephalon cluster. A purple half slice represents a telencephalon cluster, a purple and orange slice represents clusters in both brain regions. For example, <i>cebpb</i> is predicted to regulate D4, D5, D6, T3, T4, T9.</p

Brain region-specific changes in gene expression in response to a territorial challenge over time.

<p>(A) Numbers of up- (blue) and down (red)-regulated genes at 30, 60 and 120 minutes after a territorial challenge in diencephalon and telencephalon. Overlap between differentially expressed genes across time points in diencephalon (B) and telencephalon (C). Correlation between expression in diencephalon (X axis) and telencephalon (Y axis) at 30 min (D), 60 min (E) and 120 min (F) after a territorial challenge. The numbers in the Venn diagram indicate the number of differentially expressed genes in each brain region and the overlap between them at a given time. Scatterplots show the expression pattern of the genes that were shared between brain regions at a time point. Note the cluster of genes in the lower right corner of 1f, hereafter referred to as ‘discordant genes’, which were differentially expressed in both brain regions at 120 minutes but in opposite directions: they were upregulated in diencephalon and downregulated in telencephalon. (G) Functional enrichment of DEGs by time point (columns) and by brain region (rows), shown as revigo-like MDS graphs. Blue indicates enrichment of up-regulated genes, red indicates enrichment of down-regulated genes. Groups of terms with similar functions are highlighted.</p

Hierarchical clustering of genes whose expression profiles changed over time in response to a territorial challenge (DEG_x) and their functional enrichments.

<p>Hierarchical clustering grouped together genes with similar expression profiles over time. 13 clusters were identified in diencephalon (D1-D13, A). 12 clusters were identified in telencephalon (T1-T12, B). Each line represents the expression pattern of a different gene, where positive fold change indicates upregulation and negative fold change indicates downregulation in response to a territorial challenge. Clusters of genes with similar expression profiles (columns) had different GO molecular functions associated with them (rows); C) diencephalon; D) telencephalon. Some clusters did not have significant functional enrichment.</p

Connecting gene expression and chromatin accessibility in diencephalon.

<p>(A) Fold change of differentially accessible peaks at 30 minutes and 120 minutes; blue indicates up in experimental, red indicates down in experimental. (B) Functional enrichment (molecular function) of genes associated with differentially accessible peaks at 30 minutes and 120 minutes. Blue indicates up in challenged, red indicates down in challenged. (C) Overlap of genes whose expression profile changed over time in response to a social interaction (DEG_x) with genes associated with differentially accessible peaks at 30 minutes and 120 minutes. The overlap between DEG_x and accessibility at 120 minutes is statistically significant (P<0.0001). (D-F) Examples of differentially accessible peaks around DEG_x. Separate tracks are shown for H3K27Ac peaks in control 30 min, experimental 30 min, control 120 min, experimental 120 min, and H3k4Me3, which marks the location of the promoter. (D) <i>Pparg</i> (a TF in D9 and also present TRN) was more accessible at 120 minutes and was also up-regulated at 120 minutes. (E) <i>P2ry12</i> (cluster D9) is purinergic receptor involved in synaptic plasticity [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006840#pgen.1006840.ref065" target="_blank">65</a>] that was more accessible in controls at 30 minutes then become more accessible in experimental animals at 120 minutes. <i>P2ry12</i> is known to stimulate microglia migration toward neuronal damage [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006840#pgen.1006840.ref066" target="_blank">66</a>]. (F) <i>C4B</i> (cluster D9) was not accessible at baseline but became accessible at 120 mins.</p