Infants' poor motor abilities limit their interaction with their environment and render studying infant cognition notoriously difficult. Exceptions are eye movements, which reach high accuracy early, but generally do not allow manipulation of the physical environment. In this study, real-time eye tracking is used to put 6- and 8-month-old infants in direct control of their visual surroundings to study the fundamental problem of discovery of agency, i.e. the ability to infer that certain sensory events are caused by one's own actions. We demonstrate that infants quickly learn to perform eye movements to trigger the appearance of new stimuli and that they anticipate the consequences of their actions in as few as 3 trials. Our findings show that infants can rapidly discover new ways of controlling their environment. We suggest that gaze-contingent paradigms offer effective new ways for studying many aspects of infant learning and cognition in an interactive fashion and provide new opportunities for behavioral training and treatment in infants.

in the bottleneck of a network, LFM fuses the lighting by layer-wise feature modulation to deliver more convincing results. Extensive experiments demonstrate that our proposed method achieves better results and is able to generate challenging lighting effects. CCS Concepts: • Computing methodologies → Image-based rendering; Computational photography; Neural networks.

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Background and MotivationMany different eye-tracking calibration techniques have been developed [e.g. see Talmi and Liu 1999;Zhu and Ji 2007]. A community standard is a 9-point-sparse calibration that relies on sequential presentation of known scene targets. However, fixating different points has been described as tedious, dull and tiring for the eye [Bulling, Gellersen, Pfeuffer, Turner and Vidal 2013].As an alternative, some research groups have proposed using smooth pursuit for eye-tracking calibration. E.g., [Bulling, Gellersen, Pfeuffer, Turner and Vidal 2013] tested rectangular constant velocity paths for calibration, and [Blake, Cipolla and Williams 2006] developed a Bayesian-Gaussian regression smooth pursuit approach. These smooth-pursuit approaches can obtain a greater amount of unique pupil-scene mapping information per unit time, potentially increasing the robustness and accuracy of eye-tracking calibration. Problem StatementWe aimed to advance alternative calibration techniques relying on smooth pursuit movements rather than saccades. To this end, we endeavored to preserve the efficiency of calibration in terms of time while increasing the accuracy, reliability and stability of calibration.In comparison to previous work, our approach differs in two ways: our smooth pursuit pattern and our regression technique. Many different designs would enforce smooth pursuit movements, but a good pattern should be predictable, have good spatial coverage, and little redundancy. Hence, we select an Archimedean spiral trajectory with constant linear velocity (6.4°/sec). In contrast, the corners of a rectangular path [Bulling et al., 2013] may lead to instabilities in pursuit following, and tracing the border alone provides little coverage of the rectangle's interior. As compared to the Bayesian-Gaussian regression technique [Blake, Cipolla and Williams 2006], we utilize a simple-to-implement error corrected regression technique (lag correction and outlier rejection) that achieves good performance. While the Bayesian-Gaussian regression technique is more general, we believe that our approach is highly accessible and effective, which should facilitate the adoption of the technique more broadly. Approach and Method StimuliTwo different calibration techniques are discussed in this paper: a smooth pursuit calibration using an Archimedean spiral with constant linear velocity (6.4 deg/sec), and a standard 9-point-sparse calibration. The accuracy of both techniques is validated by a 7x7 validation grid. Experiments were developed in Windows 7 using MATLAB (Windows, 32-bit) Eyelink Toolbox and data were collected with an SR Research Eyelink 1000 500hz desktop-mounted monocular eye-tracker. Smooth pursuit calibration took 27 seconds, during which up to 1600 data points were recorded. Presentation of scene targets in 9-point calibration (took 23 seconds) and validation was randomized. In order to examine comparable durations in smooth pursuit as compared to sparse calibration, we also examined truncating the tail of our smooth ...

BackgroundMolecular descriptors are essential for many applications in computational chemistry, such as ligand-based similarity searching. Spherical harmonics have previously been suggested as comprehensive descriptors of molecular structure and properties. We investigate a spherical harmonics descriptor for shape-based virtual screening.Methodology/Principal FindingsWe introduce and validate a partially rotation-invariant three-dimensional molecular shape descriptor based on the norm of spherical harmonics expansion coefficients. Using this molecular representation, we parameterize molecular surfaces, i.e., isosurfaces of spatial molecular property distributions. We validate the shape descriptor in a comprehensive retrospective virtual screening experiment. In a prospective study, we virtually screen a large compound library for cyclooxygenase inhibitors, using a self-organizing map as a pre-filter and the shape descriptor for candidate prioritization.Conclusions/Significance12 compounds were tested in vitro for direct enzyme inhibition and in a whole blood assay. Active compounds containing a triazole scaffold were identified as direct cyclooxygenase-1 inhibitors. This outcome corroborates the usefulness of spherical harmonics for representation of molecular shape in virtual screening of large compound collections. The combination of pharmacophore and shape-based filtering of screening candidates proved to be a straightforward approach to finding novel bioactive chemotypes with minimal experimental effort.

Atypical looking behaviors in neuropsychiatric conditions such as autism spectrum disorders (ASD) are not only a reflection of inherently abnormal neuropsychological processes, but also suggest that future access to observational learning opportunities may be limited. The work presented in this paper uses interactive eye tracking as a first step towards the development of automated tools that can help toddlers and young children with atypical visual attention learn to attend to social information in a more typical fashion. In our study, we designed an automated visual strategy training system that would redirect a viewers' attention to locations highly salient to the normative control group when the viewer drifted from those locations for a significant period of time. We evaluated our experimental technique on typicallydeveloping adults, obtaining results that suggest that looking patterns can be altered to be more similar to those evidenced by a normative group of young children. Furthermore, these alterations appear be retained in post-training sessions when considering new presentations of videos participants had been trained upon, and, on more sensitive outcome measures based on integrated scanpath probabilities (heatmaps), seemed to generalize presentations not trained upon as well. The development of these techniques may provide a new model for modifying attentional biases not only in toddlers with ASD, but also in children affected by other neuropsychiatric conditions, and may thus lead to new therapeutic interventions as well as more efficacious methods for identifying the patterns associated with abnormal, attention-driven experience.