CRISP: a computational model of fixation durations in scene viewing

Eye-movement control during scene viewing can be represented as a series of individual decisions about where and when to move the eyes. While substantial behavioral and computational research has been devoted to investigating the placement of fixations in scenes, relatively little is known about the mechanisms that control fixation durations. Here, we propose a computational model (CRISP) that accounts for saccade timing and programming and thus for variations in fixation durations in scene viewing. First, timing signals are modeled as continuous-time random walks. Second, difficulties at the level of visual and cognitive processing can inhibit and thus modulate saccade timing. Inhibition generates moment-by-moment changes in the random walk’s transition rate and processing-related saccade cancellation. Third, saccade programming is completed in 2 stages: an initial, labile stage that is subject to cancellation and a subsequent, nonlabile stage. Several simulation studies tested the model’s adequacy and generality. An initial simulation study explored the role of cognitive factors in scene viewing by examining how fixation durations differed under different viewing task instructions. Additional simulations investigated the degree to which fixation durations were under direct moment-to-moment control of the current visual scene. The present work further supports the conclusion that fixation durations, to a certain degree, reflect perceptual and cognitive activity in scene viewing. Computational model simulations contribute to an understanding of the underlying processes of gaze control

Self-Consistent Estimation of Mislocated Fixations during Reading

During reading, we generate saccadic eye movements to move words into the center of the visual field for word processing. However, due to systematic and random errors in the oculomotor system, distributions of within-word landing positions are rather broad and show overlapping tails, which suggests that a fraction of fixations is mislocated and falls on words to the left or right of the selected target word. Here we propose a new procedure for the self-consistent estimation of the likelihood of mislocated fixations in normal reading. Our approach is based on iterative computation of the proportions of several types of oculomotor errors, the underlying probabilities for word-targeting, and corrected distributions of landing positions. We found that the average fraction of mislocated fixations ranges from about 10% to more than 30% depending on word length. These results show that fixation probabilities are strongly affected by oculomotor errors

Was ging in ihm vor? Laientheorien über kognitive und emotionale Vorgänge eines Selbstmörders

Tested Rational-Emotive Behavior Therapy’s (REBT; Ellis, 1962, 1994) assumption that irrational beliefs and maladaptive emotions are associated with dysfunctional behaviors, whereas rational cognitions and adaptive emotions lead to functional actions. Participants read newspaper articles about the defeat of a boxer. In one condition, the (authentic) article informed participants that he committed suicide, and in a second (fictitious) article about the same defeat, the athlete was described as successfully resuming his career. Participants’ assumptions about the stimulus person’s defeat-related cognitions and emotions were assessed on rating scales and via sentence completion and free responses. Participants responding to the suicide scenario assumed significantly more irrational beliefs (e.g., ”I absolutely have to win”) on the side of the boxer regarding his defeat than controls in the fictitious non-suicide version. This finding was obtained by all assessment methods. Additionally, participants expected the suicidal stimulus person to be experiencing maladaptive emotions (e.g., depression, guilt), whereas the stimulus person who successfully resumed his career was expected to experience adaptive affects (e.g., sadness, concern). Subsequent ratings of the functionality of selected emotions revealed that sadness, fear, annoyance, and concern were rated to be more functional than depression, anxiety, rage, and guilt.In einer Fragebogenstudie wurden den Teilnehmenden reale Zeitungsartikel vorgelegt, die vom Selbstmord eines besiegten Boxers berichteten. Die Probanden sollten sich in die Person des Sportlers hineinversetzen und die Gedanken und Gefühle schildern, die sie bei ihm in Zusammenhang mit der Niederlage erwarteten. Die Probanden vermuteten bei dem Sportler durchgängig in höherer Weise irrationale rigide Gedanken (z.B. „ich muss unbedingt siegen“) als rationales Denken (z.B. „ich möchte gerne siegen“) und eher maladaptive Emotionen (Angst, Wut, Depression und Schuld) als adaptive Emotionen (Furcht, Ärger, Trauer und Bedauern). Dies trat jedoch nur dann ein, wenn in den Zeitungsartikeln nachfolgendes dysfunktionales Verhalten des Boxers (Suizid) geschildert wurde: In einer Kontrollbedingung, die ebenfalls von der Niederlage – allerdings mit erfolgreicher Fortsetzung der Boxerkarriere – berichtet, zeigte sich dieses Datenmuster nicht. Diese Befunde entsprechen den theoretischen Annahmen und Vorhersagen der Rational-Emotiven-Verhaltenstherapie (REVT) von Albert Ellis. Zusätzlich erhobene Daten zur generellen Funktionalität der acht Emotionen bestätigen ebenfalls die theoretischen Annahmen

Saliency Benchmarking Made Easy: Separating Models, Maps and Metrics

Dozens of new models on fixation prediction are published every year and compared on open benchmarks such as MIT300 and LSUN. However, progress in the field can be difficult to judge because models are compared using a variety of inconsistent metrics. Here we show that no single saliency map can perform well under all metrics. Instead, we propose a principled approach to solve the benchmarking problem by separating the notions of saliency models, maps and metrics. Inspired by Bayesian decision theory, we define a saliency model to be a probabilistic model of fixation density prediction and a saliency map to be a metric-specific prediction derived from the model density which maximizes the expected performance on that metric given the model density. We derive these optimal saliency maps for the most commonly used saliency metrics (AUC, sAUC, NSS, CC, SIM, KL-Div) and show that they can be computed analytically or approximated with high precision. We show that this leads to consistent rankings in all metrics and avoids the penalties of using one saliency map for all metrics. Our method allows researchers to have their model compete on many different metrics with state-of-the-art in those metrics: "good" models will perform well in all metrics.Comment: published at ECCV 201

New Young Star Candidates in BRC 27 and BRC 34

We used archival Spitzer Space Telescope mid-infrared data to search for young stellar objects (YSOs) in the immediate vicinity of two bright-rimmed clouds, BRC 27 (part of CMa R1) and BRC 34 (part of the IC 1396 complex). These regions both appear to be actively forming young stars, perhaps triggered by the proximate OB stars. In BRC 27, we find clear infrared excesses around 22 of the 26 YSOs or YSO candidates identified in the literature, and identify 16 new YSO candidates that appear to have IR excesses. In BRC 34, the one literature-identified YSO has an IR excess, and we suggest 13 new YSO candidates in this region, including a new Class I object. Considering the entire ensemble, both BRCs are likely of comparable ages, within the uncertainties of small number statistics and without spectroscopy to confirm or refute the YSO candidates. Similarly, no clear conclusions can yet be drawn about any possible age gradients that may be present across the BRCs.Comment: 54 pages, 19 figures, accepted by A