Bayesian adaptive method for estimating speed-accuracy tradeoff functions of multiple task conditions.

The speed-accuracy tradeoff (SAT) often makes psychophysical data difficult to interpret. Accordingly, the SAT experimental procedure and model were proposed for an integrated account of the speed and accuracy of responses. However, the extensive data collection for a SAT experiment has blocked its popularity. For a quick estimation of SAT function (SATf), we previously developed a Bayesian adaptive SAT method, including an online stimulus selection strategy. By simulations, the method was proved efficient with high accuracy and precision with minimal trials, adequate for practically applying a single condition task. However, it calls for extensions to more general designs with multiple conditions and should be revised to achieve improved estimation performance. It also demands real experimental validation with human participants. In the current study, we suggested an improved method to measure SATfs for multiple task conditions concurrently and to enhance robustness in general designs. The performance was evaluated with simulation studies and a psychophysical experiment using a flanker task. Simulation results revealed that the proposed method with the adaptive stimulus selection strategy efficiently estimated multiple SATfs and improved performance even for cases with an extreme parameter value. In the psychophysical experiment, SATfs estimated by minimal adaptive trials (1/8 of conventional trials) showed high agreement with those by conventional trials required for reliably estimating multiple SATfs. These results indicate that the Bayesian adaptive SAT method is reliable and efficient in estimating SATfs in most experimental settings and may apply to SATf estimation in general behavioral research designs.

Visual attention in spatial cueing and visual search.

To characterize internal processes of an observer conducting perceptual tasks, we developed an observer model that combines the perceptual template model (PTM), the attention mechanisms in the PTM framework (Lu & Dosher, 1998), and uncertainty of signal detection theory (Green & Swets, 1966). The model was evaluated with a visual search experiment conducted in a range of external noise, signal contrast, and target-distractor similarity conditions. In each trial, eight Gabor patches were shown in each of two brief intervals, with one target at a different orientation from the distractors in one of the presentations. Subjects were precued to a subset of the stimuli (1, 2, 4, or 8) and asked to report (a) which interval contained the target and (b) where the target was. Individual roles of uncertainty and of attention in visual search were investigated by comparing models with and without an attention component. The results showed that decision uncertainty alone was sufficient to account for the set-size effect, even in conditions with high target-distractor similarity. Our theoretical model and empirical results provide a coherent picture regarding how visual information is selected and processed during feature search.

qPR: An adaptive partial-report procedure based on Bayesian inference.

Iconic memory is best assessed with the partial report procedure in which an array of letters appears briefly on the screen and a poststimulus cue directs the observer to report the identity of the cued letter(s). Typically, 6-8 cue delays or 600-800 trials are tested to measure the iconic memory decay function. Here we develop a quick partial report, or qPR, procedure based on a Bayesian adaptive framework to estimate the iconic memory decay function with much reduced testing time. The iconic memory decay function is characterized by an exponential function and a joint probability distribution of its three parameters. Starting with a prior of the parameters, the method selects the stimulus to maximize the expected information gain in the next test trial. It then updates the posterior probability distribution of the parameters based on the observer's response using Bayesian inference. The procedure is reiterated until either the total number of trials or the precision of the parameter estimates reaches a certain criterion. Simulation studies showed that only 100 trials were necessary to reach an average absolute bias of 0.026 and a precision of 0.070 (both in terms of probability correct). A psychophysical validation experiment showed that estimates of the iconic memory decay function obtained with 100 qPR trials exhibited good precision (the half width of the 68.2% credible interval = 0.055) and excellent agreement with those obtained with 1,600 trials of the conventional method of constant stimuli procedure (RMSE = 0.063). Quick partial-report relieves the data collection burden in characterizing iconic memory and makes it possible to assess iconic memory in clinical populations.

Perceived magnitude of visual displays: Area, numerosity, and mean size.

Previous studies have shown that the visual system is able to estimate properties such as area, numerosity, and mean size efficiently and accurately. In the current study, we investigated whether our percepts of each of them could be based on ratios of the other two of these three properties. In each trial, observers viewed a display containing various quantities of filled circles and judged whether the magnitude of a property of the display, such as summed area, numerosity, or average size of the circles, was greater or less than a corresponding probe display. We found that mean size judgments were more accurate and precise compared to the other judgments. We then predicted observers' performances for each task using the measured performance for the other judgments. The results showed that the other properties predicted perceived summed area, but not perceived mean size and numerosity. Together, our results suggest that the visual system does not use ratios to compute mean size and numerosity.

Bias and sensitivity in numerosity perception of negative emotions among individuals with high social anxiety.

The cognitive model of social anxiety suggests an association between social anxiety and cognitive bias toward negative social information. This study investigated the numerosity perception of emotional faces among individuals with high social anxiety. Seventy-five college students completed self-reported questionnaires-assessing social anxiety symptoms-and a numerosity comparison experiment. In each trial of the experiment, participants were presented with a group of 16 emotional faces, varying in the number of faces expressing positive and negative emotions. They were asked to judge which emotion-positive or negative-was more numerous in the crowd. Bias and sensitivity in numerosity perception of emotions were estimated by fitting a psychometric function to participants' responses. Individuals with low social anxiety showed a bias toward positive faces (t(17) = 2.44, p = 0.026), while those with high social anxiety did not (t(17) = 1.87, p = 0.079). Correlation analyses indicated that social anxiety was negatively associated with the parameters of the function (mean for bias and standard deviation for sensitivity; r = - 0.34, p = 0.003 for mean; r = - 0.23, p = 0.047 for standard deviation). Thus, our results suggest that socially anxious individuals lack the bias toward positive emotion and are more sensitive to negative emotion than nonanxious individuals in perceiving the numerosity of facial expressions.

Bayesian adaptive model estimation to solve the speed accuracy tradeoff problem in psychophysical experiments.

Most psychological experiments measure human cognitive function through the response time and accuracy of the response to a set of stimuli. Since response time and accuracy complement each other, it is often difficult to interpret cognitive performance based on only one dependent measurement and raises a speed-accuracy tradeoff (SAT) problem. In overcoming this problem, SAT experimental paradigms and models that integrate response time and accuracy have been proposed to understand information processing in human cognitive function. However, due to a lengthy SAT experiment for reliable model estimation, SAT experiments' practical limitations have been pointed out. Thus, these limitations call for an efficient technique to shorten the number of trials required to estimate the SAT function reliably. Instead of using a block's stimulus-onset asynchrony (SOA) accuracy with long block-based task trials, we introduced a Bayesian SAT function estimation using trial-by-trial response time and correctness, which makes SAT tasks flexible and easily extendable to multiple trials. We then proposed a Bayesian adaptive method to select optimal SOA by maximizing information gain to estimate model parameters. Simulation results showed that the proposed Bayesian adaptive estimation was highly efficient and robust for accuracy and precision of estimating SAT function by enabling "multiple-step ahead search."

Bayesian adaptive estimation of the contrast sensitivity function: the quick CSF method.

The contrast sensitivity function (CSF) predicts functional vision better than acuity, but long testing times prevent its psychophysical assessment in clinical and practical applications. This study presents the quick CSF (qCSF) method, a Bayesian adaptive procedure that applies a strategy developed to estimate multiple parameters of the psychometric function (A. B. Cobo-Lewis, 1996; L. L. Kontsevich & C. W. Tyler, 1999). Before each trial, a one-step-ahead search finds the grating stimulus (defined by frequency and contrast) that maximizes the expected information gain (J. V. Kujala & T. J. Lukka, 2006; L. A. Lesmes et al., 2006), about four CSF parameters. By directly estimating CSF parameters, data collected at one spatial frequency improves sensitivity estimates across all frequencies. A psychophysical study validated that CSFs obtained with 100 qCSF trials ( approximately 10 min) exhibited good precision across spatial frequencies (SD < 2-3 dB) and excellent agreement with CSFs obtained independently (mean RMSE = 0.86 dB). To estimate the broad sensitivity metric provided by the area under the log CSF (AULCSF), only 25 trials were needed to achieve a coefficient of variation of 15-20%. The current study demonstrates the method's value for basic and clinical investigations. Further studies, applying the qCSF to measure wider ranges of normal and abnormal vision, will determine how its efficiency translates to clinical assessment.

Ensemble perception and focused attention: Two different modes of visual processing to cope with limited capacity.

The visual system has a limited capacity for dealing with complex and redundant information in a scene. Here, we propose that a distributed attention mode of processing is necessary for coping with this limit, together with a focused attention mode of processing. The distributed attention mode provides a statistical summary of a scene, whereas the focused attention mode provides relevant information for object recognition. In this paper, we claim that a distributed mode of processing is necessary because (1) averaging performance improves with increased set-sizes, (2) even unselected items are likely to contribute to averaging, and (3) the assumption of variable capacity limits in averaging over different set-sizes is not plausible. We then propose how the averaging process can access multiple items over the capacity limit of focused attention. The visual system can represent multiple items as population responses and read out relevant information using the two modes of attention. It can summarize population responses with a broad application of a Gaussian profile (i.e., distributed attention) and represent its peak as the mean. It can focus on relevant population responses with a narrow application of a Gaussian profile (i.e., focused attention) and select important information for object recognition. The two attention modes of processing provide a framework for incorporating two seemingly opposing fields of study (ensemble perception and selective attention) and a unified theory of a coping strategy with our limited capacity.

Distributed attention model of perceptual averaging.

The visual system efficiently processes complex and redundant information in a scene despite its limited capacity. One strategy for coping with the complexity and redundancy of a scene is to summarize it by using average information. However, despite its importance, the mechanism of averaging is not well understood. Here, a distributed attention model of averaging is proposed. Human percept for an object can be disturbed by various sources of internal noise, which can occur either before (early noise) or after (late noise) forming an ensemble perception. The model assumes these noises and reflects noise cancellation by averaging multiple items. The model predicts increased precision for more items with decelerated increments for large set-sizes resulting from late noise. Importantly, the model incorporates mechanisms of attention, which modulate each item's contribution to the averaging process. The attention in the model also results in saturation of performance increments for small set-sizes because the amount of attention allocated to each item is greater for small set-sizes than for large set-sizes. To evaluate the proposed model, a psychophysical experiment was conducted in which observers' ability to discriminate average sizes of two displays was measured. The observers' averaging performance increased at a decreasing rate with small set-sizes and it approached an asymptote for large set-sizes. The model accurately predicted the observed pattern of data. It provides a theoretical framework for interpreting behavioral data and leads to an understanding of the characteristics of ensemble perception.

Anthropomorphic Design: Emotional Perception for Deformable Object.

Despite the increasing number of studies on user experience (UX) and user interfaces (UI), few studies have examined emotional interaction between humans and deformable objects. In the current study, we investigated how the anthropomorphic design of a flexible display interacts with emotion. For 101 unique 3D images in which an object was bent at different axes, 281 participants were asked to report how strongly the object evoked five elemental emotions (e.g., happiness, disgust, anger, fear, and sadness) in an online survey. People rated the object's shape using three emotional categories: happiness, disgust-anger, and sadness-fear. It was also found that a combination of axis of bending (horizontal or diagonal axis) and convexity (bending convexly or concavely) predicted emotional valence, underpinning the anthropomorphic design of flexible displays. Our findings provide empirical evidence that axis of bending and convexity can be an important antecedent of emotional interaction with flexible objects, triggering at least three types of emotion in users.

Effect of Redundant Haptic Information on Task Performance during Visuo-Tactile Task Interruption and Recovery.

Previous studies have revealed that interruption induces disruptive influences on the performance of cognitive tasks. While much research has focused on the use of multimodal channels to reduce the cost of interruption, few studies have utilized haptic information as more than an associative cue. In the present study, we utilized a multimodal task interruption scenario involving the simultaneous presentation of visual information and haptic stimuli in order to investigate how the combined stimuli affect performance on the primary task (cost of interruption). Participants were asked to perform a two-back visuo-tactile task, in which visual and haptic stimuli were presented simultaneously, which was interrupted by a secondary task that also utilized visual and haptic stimuli. Four experimental conditions were evaluated: (1) paired information (visual stimulus + paired haptic stimulus) with interruption; (2) paired information without interruption; (3) non-paired information (visual stimulus + non-paired haptic stimulus) with interruption; and (4) non-paired information without interruption. Our findings indicate that, within a visuo-tactile task environment, redundant haptic information may not only increase accuracy on the primary task but also reduce the cost of interruption in terms of accuracy. These results suggest a new way of understanding the task recovery process within a multimodal environment.

The development of visual search in infancy: Attention to faces versus salience.

Four experiments examined how faces compete with physically salient stimuli for the control of attention in 4-, 6-, and 8-month-old infants (N = 117 total). Three computational models were used to quantify physical salience. We presented infants with visual search arrays containing a face and familiar object(s), such as shoes and flowers. Six- and 8-month-old infants looked first and longest at faces; their looking was not strongly influenced by physical salience. In contrast, 4-month-old infants showed a visual preference for the face only when the arrays contained 2 items and the competitor was relatively low in salience. When the arrays contained many items or the only competitor was relatively high in salience, 4-month-old infants' looks were more often directed at the most salient item. Thus, over ages of 4 to 8 months, physical salience has a decreasing influence and faces have an increasing influence on where and how long infants look.

Developing Bayesian adaptive methods for estimating sensitivity thresholds (d') in Yes-No and forced-choice tasks.

Motivated by Signal Detection Theory (SDT), we developed a family of novel adaptive methods that estimate the sensitivity threshold-the signal intensity corresponding to a pre-defined sensitivity level (d' = 1)-in Yes-No (YN) and Forced-Choice (FC) detection tasks. Rather than focus stimulus sampling to estimate a single level of %Yes or %Correct, the current methods sample psychometric functions more broadly, to concurrently estimate sensitivity and decision factors, and thereby estimate thresholds that are independent of decision confounds. Developed for four tasks-(1) simple YN detection, (2) cued YN detection, which cues the observer's response state before each trial, (3) rated YN detection, which incorporates a Not Sure response, and (4) FC detection-the qYN and qFC methods yield sensitivity thresholds that are independent of the task's decision structure (YN or FC) and/or the observer's subjective response state. Results from simulation and psychophysics suggest that 25 trials (and sometimes less) are sufficient to estimate YN thresholds with reasonable precision (s.d. = 0.10-0.15 decimal log units), but more trials are needed for FC thresholds. When the same subjects were tested across tasks of simple, cued, rated, and FC detection, adaptive threshold estimates exhibited excellent agreement with the method of constant stimuli (MCS), and with each other. These YN adaptive methods deliver criterion-free thresholds that have previously been exclusive to FC methods.

How arousal modulates the visual contrast sensitivity function.

Recent evidence indicates that emotion enhances contrast thresholds in subsequent visual perception (Phelps, Ling, & Carrasco, 2006) and perceptual sensitivity for low-spatial frequency but not high-spatial frequency targets (Bocanegra & Zeelenberg, 2009b). However, these studies just report responses to various frequencies at a fixed contrast level or responses to various contrasts at a fixed frequency. In the current study, we measured the full contrast sensitivity function as a function of emotional arousal in order to investigate potential interactions between spatial frequency and contrast. We used a Bayesian adaptive inference with a trial-to-trial information gain strategy (Lesmes, Lu, Baek, & Albright, 2010) and a fear-conditioned stimulus to manipulate arousal level. The spatial frequency at which people showed peak contrast sensitivity shifted to lower spatial frequencies in the arousing condition compared with the nonarousing condition and people had greater contrast sensitivity function bandwidth in the arousing than in the nonarousing condition.