EternaBrain: Automated RNA design through move sets and strategies from an Internet-scale RNA videogame.

Emerging RNA-based approaches to disease detection and gene therapy require RNA sequences that fold into specific base-pairing patterns, but computational algorithms generally remain inadequate for these secondary structure design tasks. The Eterna project has crowdsourced RNA design to human video game players in the form of puzzles that reach extraordinary difficulty. Here, we demonstrate that Eterna participants' moves and strategies can be leveraged to improve automated computational RNA design. We present an eternamoves-large repository consisting of 1.8 million of player moves on 12 of the most-played Eterna puzzles as well as an eternamoves-select repository of 30,477 moves from the top 72 players on a select set of more advanced puzzles. On eternamoves-select, we present a multilayer convolutional neural network (CNN) EternaBrain that achieves test accuracies of 51% and 34% in base prediction and location prediction, respectively, suggesting that top players' moves are partially stereotyped. Pipelining this CNN's move predictions with single-action-playout (SAP) of six strategies compiled by human players solves 61 out of 100 independent puzzles in the Eterna100 benchmark. EternaBrain-SAP outperforms previously published RNA design algorithms and achieves similar or better performance than a newer generation of deep learning methods, while being largely orthogonal to these other methods. Our study provides useful lessons for future efforts to achieve human-competitive performance with automated RNA design algorithms.

Scientific Discovery Games for Biomedical Research.

Over the past decade, scientific discovery games (SDGs) have emerged as a viable approach for biomedical research, engaging hundreds of thousands of volunteer players and resulting in numerous scientific publications. After describing the origins of this novel research approach, we review the scientific output of SDGs across molecular modeling, sequence alignment, neuroscience, pathology, cellular biology, genomics, and human cognition. We find compelling results and technical innovations arising in problem-oriented games such as Foldit and Eterna and in data-oriented games such as EyeWire and Project Discovery. We discuss emergent properties of player communities shared across different projects, including the diversity of communities and the extraordinary contributions of some volunteers, such as paper writing. Finally, we highlight connections to artificial intelligence, biological cloud laboratories, new game genres, science education, and open science that may drive the next generation of SDGs.

Truth is in the eye of the beholder: Perception of the Müller-Lyer illusion in dogs.

Visual illusions are objects that are made up of elements that are arranged in such a way as to result in erroneous perception of the objects' physical properties. Visual illusions are used to study visual perception in humans and nonhuman animals, since they provide insight into the psychological and cognitive processes underlying the perceptual system. In a set of three experiments, we examined whether dogs were able to learn a relational discrimination and to perceive the Müller-Lyer illusion. In Experiment 1, dogs were trained to discriminate line lengths using a two-alternative forced choice procedure on a touchscreen. Upon learning the discrimination, dogs' generalization to novel exemplars and the threshold of their abilities were tested. In the second experiment, dogs were presented with the Müller-Lyer illusion as test trials, alongside additional test trials that controlled for overall stimulus size. Dogs appeared to perceive the illusion; however, control trials revealed that they were using global size to solve the task. Experiment 3 presented modified stimuli that have been known to enhance perception of the illusion in other species. However, the dogs' performance remained the same. These findings reveal evidence of relational learning in dogs. However, their failure to perceive the illusion emphasizes the importance of using a full array of control trials when examining these paradigms, and it suggests that visual acuity may play a crucial role in this perceptual phenomenon.

Animals can assign novel odours to a known category.

The ability to identify a novel stimulus as a member of a known category allows an organism to respond appropriately towards it. Categorisation is thus a fundamental component of cognition and an essential tool for processing and responding to unknown stimuli. Therefore, one might expect to observe it throughout the animal kingdom and across sensory domains. There is much evidence of visual categorisation in non-human animals, but we currently know little about this process in other modalities. In this experiment, we investigated categorisation in the olfactory domain. Dogs were trained to discriminate between 40 odours; the presence or absence of accelerants formed the categorical rule. Those in the experimental group were rewarded for responding to substrates with accelerants (either burnt or un-burnt) and inhibit responses to the same substrates (either burnt or un-burnt) without accelerants (S+ counterbalanced). The pseudocategory control group was trained on the same stimuli without the categorical rule. The experimental group learned the discrimination and animals were able to generalise to novel stimuli from the same category. None of the control animals were able to learn the discrimination within the maximum number of trials. This study provides the first evidence that non-human animals can learn to categorise non-biologically relevant odour information.