Research

Honesty and individual differences in signaling during aggressive interactions 

more wing waves. so cute!Animals often use signals in aggressive situations, such as when faced with an intruder of the same sex in their territory. Although some of these signals are reliable because they are inherently tied to fighting ability or their chances of winning the fight (such as the parallel walking of red deer which emphasizes the body size of the stag), many signals, particularly vocal signals in songbirds, seem to be not inherently tied to fighting ability. Instead these signals are thought to signal “aggressive intent”, the likelihood that the signaler is going to escalate if the opponent doesn’t withdraw. Given that these signals are often cheap to produce, an important question is, whether these signals are reliable and how the reliability may be sustained. I studied aggressive signals in song sparrows (Melospiza melodia) using playbacks coupled with taxi-dermic mounts and found that song sparrows possess a hierarchical signaling system that reliably predicts an actual attack on the taxi-dermic mount, starting with type matching (replying  to the opponent, with the same song he just sang) and if that doesn’t deter the opponent, switching to close-range signals, namely wing waves (a visual signal) and soft songs (low amplitude song) (Akcay et. al. 2011, 2013). A surprising result is that although each of these signals are reliable in predicting an attack, the reliability is imperfect. Even more surprisingly, many birds, who go on to attack do not seem to use these signals, despite the fact the signals in question are non-costly to produce. Further experiments showed that this tendency to signal or not signal is individually repeatable, and possibly due to individual differences in a personality trait that we have termed (tentatively) “communicativeness” (Akcay et al., 2014).

Individual recognition in communication networks

DSC_5784-001Individuals are part of social networks where they interact with a number of other individuals repeatedly in both competitive and cooperative contexts. Adaptively navigating these interactions requires that individuals recognize and keep track of their interactions partners. Often animals have opportunities to gather information about their social partners not only from direct interactions from them but also from eavesdropping on interactions between other individuals in a communication network. I have studied individual recognition and social dynamics in song sparrows and western bluebirds. My results with song sparrows showed that territory holders kept track of their neighbors’ aggressiveness through both direct interactions with them (Akcay et al. 2009) and through eavesdropping on the interactions of their neighbors with other neighbors (Akcay et al. 2010). My studies with western bluebirds have focused on the question of whether bluebirds can recognize their male relatives from their song. I found that male bluebirds can indeed recognize their relatives from their song, suggesting a role for vocal communication in mediating cooperative interactions between the males (Akcay et al. 2013). In this case, kin recognition seems to be based on recognizing individually distinct vocal signatures as opposed to kin signatures that are shared by the whole family group (Akcay et al. 2014).

Social factors in song learning

SOSPDeceptionPassThe 4000-odd species of songbirds are known for the diversity of their beautiful song. Bird song is also an important model system of neurobiology of learning and development of communication systems and displays a number of important parallels with human language learning. One particular parallel between learning of human language and bird song is the fact that both of these processes are social processes. I examined one particular social factor, namely the aggressiveness of potential tutors from whom young birds may learn their songs from. Although potential tutors exhibited strong consistent individual differences in aggressiveness, these differences did not affect whether young birds learned from them (Akcay et al., 2014). I am now testing novel hypotheses about how young sparrows choose their tutors.

Behavioral dynamics of extra-pair mating 

Untitled-1Although most songbirds are socially monogamous, genetic studies in the last 3 decades showed that genetic monogamy is in fact rare in songbirds. In most species, at least some females produce offspring with extra-pair males. Extra-pair paternity (EPP) is also common in song sparrows where 25% of offspring are sired by extra-pair males. In a detailed analyis of age, song traits and genetic quality, we found that there seemed to be no strong correlate of female choice in extra-pair partners (Hill, Akcay et al. 2011). Instead, most of the extra-pair paternity happened in the nests of older males, with other old males cuckolding the social male, suggesting age dependent strategies of seeking extra-pair mating vs. guarding paternity at home. In a subsequent study where we radio-tracked males and females through the nesting season, we found that females did not appear to be seeking particular extra-pair partners in their fertile periods, preferring to stay “at home”, while males intruded on the territories of fertile females, with older males more likely to be doing so (Akcay et al. 2012). These behavioral data suggest that the dynamics of extra-pair paternity in song sparrows is driven mostly by male strategies.

Cognitive control of action

Before becoming primarily an animal behaviorist, I worked in cognitive psychology and I still maintain a research interest in the field. As part of my graduate work at University of Iowa with Eliot Hazeltine, I investigated a particularly popular theory of cognitive control, namely, conflict monitoring, which states that the cognitive system monitors and adaptively adjusts the use of information from the environment depending on the conflict different sources of information present. A hallmark of conflict monitoring is the sequential effects: after a trial with high levels of conflicting information, the effect of irrelevant information on response times and accuracy is attenuated. We asked whether this sequential effect (termed “conflict adaptation”) can indeed be attributed to conflict monitoring (the answer was yes, Akcay and Hazeltine, 2007). Next we asked whether control recruited by conflict monitoring is deployed globally such that conflict in one type of task affects processing in other tasks. We found that by and large, deployment of conflict was local within a task, although it was sensitive to task structure such that when two tasks shared common stimulus or response features sequential effects carried over. (Akcay and Hazeltine, 2008). Finally, conflict monitoring also seems to be recruited locally with respect to type of conflict, such that if the preceding trial has conflicting information requiring higher levels of selective visual attention, the control was specifically increased for selective visual attention and not necessarily for other types of conflict such as stimulus-response conflict (Akcay and Hazeltine, 2011).