Humans show an involuntary tendency to copy other people's actions. Although automatic imitation builds rapport and affiliation between individuals, we do not copy actions indiscriminately. Instead, copying behaviors are guided by a selection mechanism, which inhibits some actions and prioritizes others. To date, the neural underpinnings of the inhibition of automatic imitation and differences between the sexes in imitation control are not well understood. Previous studies involved small sample sizes and low statistical power, which produced mixed findings regarding the involvement of domain-general and domain-specific neural architectures. Here, we used data from Experiment 1 ( N = 28) to perform a power analysis to determine the sample size required for Experiment 2 ( N = 50; 80% power). Using independent functional localizers and an analysis pipeline that bolsters sensitivity, during imitation control we show clear engagement of the multiple-demand network (domain-general), but no sensitivity in the theory-of-mind network (domain-specific). Weaker effects were observed with regard to sex differences, suggesting that there are more similarities than differences between the sexes in terms of the neural systems engaged during imitation control. In summary, neurocognitive models of imitation require revision to reflect that the inhibition of imitation relies to a greater extent on a domain-general selection system rather than a domain-specific system that supports social cognition.

Open science aims to improve the rigor, robustness, and reproducibility of psychological research. Despite resistance from some academics, the open science movement has been championed by some early career researchers (ECRs), who have proposed innovative new tools and methods to promote and employ open research principles. Feminist ECRs have much to contribute to this emerging way of doing research. However, they face unique barriers, which may prohibit their full engagement with the open science movement. We, 10 feminist ECRs in psychology from a diverse range of academic and personal backgrounds, explore open science through a feminist lens to consider how voice and power may be negotiated in unique ways for ECRs. Taking a critical and intersectional approach, we discuss how feminist early career research may be complemented or challenged by shifts towards open science. We also propose how ECRs can act as grass-roots changemakers within the context of academic precarity. We identify ways in which open science can benefit from feminist epistemology and end with envisaging a future for feminist ECRs who wish to engage with open science practices in their own research.

complex organisational structures of control, which may involve contributions from multiple cognitive systems.

Is artificial intelligence (AI) changing our culture or creating its own? With advancements in AI and machine learning, artistic creativity is moving to a brave new world of possibility and complexity, while at the same time posing challenging questions, such as what defines something as art, what is the role of human creativity in an automated world, and do we evaluate artificial art in the same way as art made by humans? Across two pre-registered and statistically powered experiments we shed light on the nature of aesthetic responses toward computer-generated art by investigating observer prejudices against computer-generated dance choreography, and the impact of expertise and pre-conceived beliefs about the origin of artistic creation. Our results provide substantive evidence that an explicit bias exists among dance experts against computer-generated choreography, and the mere belief about a dance work’s origin biases aesthetic responses toward artworks among both dance experts and dance naïve participants. The implications of the current study serve to inform several disciplines across the arts and sciences including but not limited to empirical aesthetics, artificial intelligence, engineering, robotics, and social cognition and neuroscience. Along with physical form and content of artificial agents and art productions, the viewers’ knowledge and attitudes toward artistic AI and artificial agents will need to be taken into consideration for effective human-computer/human-AI interactions.