Adaptive Sampling of Information in Perceptual Decision-Making

In many perceptual and cognitive decision-making problems, humans sample multiple noisy information sources serially, and integrate the sampled information to make an overall decision. We derive the optimal decision procedure for two-alternative choice tasks in which the different options are sampled one at a time, sources vary in the quality of the information they provide, and the available time is fixed. To maximize accuracy, the optimal observer allocates time to sampling different information sources in proportion to their noise levels. We tested human observers in a corresponding perceptual decision-making task. Observers compared the direction of two random dot motion patterns that were triggered only when fixated. Observers allocated more time to the noisier pattern, in a manner that correlated with their sensory uncertainty about the direction of the patterns. There were several differences between the optimal observer predictions and human behaviour. These differences point to a number of other factors, beyond the quality of the currently available sources of information, that influences the sampling strategy

Training interventions for improving telephone consultation skills in clinicians (Review)

Since 1879, the year of the first documented medical telephone consultation, the ability to consult by telephone has become an integral part of modern patient-centred healthcare systems. Nowadays, up to a quarter of all care consultations are conducted by telephone. Studies have quantified the impact of medical telephone consultation on clinicians’ workload and detected the need for quality improvement. While doctors routinely receive training in communication and consultation skills, this does not necessarily include the specificities of telephone communication and consultation. Several studies assessed the short-term effect of interventions aimed at improving clinicians’ telephone consultation skills, but there is no systematic review reporting patient-oriented outcomes or outcomes of interest to clinicians

Dissolving the dichotomies between online and campus-based teaching: a collective response to The manifesto for teaching online (Bayne et al. 2020)

This article is a collective response to the 2020 iteration of The Manifesto for Teaching Online. Originally published in 2011 as 20 simple but provocative statements, the aim was, and continues to be, to critically challenge the normalization of education as techno-corporate enterprise and the failure to properly account for digital methods in teaching in Higher Education. The 2020 Manifesto continues in the same critically provocative fashion, and, as the response collected here demonstrates, its publication could not be timelier. Though the Manifesto was written before the Covid-19 pandemic, many of the responses gathered here inevitably reflect on the experiences of moving to digital, distant, online teaching under unprecedented conditions. As these contributions reveal, the challenges were many and varied, ranging from the positive, breakthrough opportunities that digital learning offered to many students, including the disabled, to the problematic, such as poor digital networks and access, and simple digital poverty. Regardless of the nature of each response, taken together, what they show is that The Manifesto for Teaching Online offers welcome insights into and practical advice on how to teach online, and creatively confront the supremacy of face-to-face teaching

Models of the decision process for two different two-alternative decision problems.

<p>(a) Decision model for a single source two-alternative forced choice decision. A frequently used stimulus in such tasks is the random dot kinematogram (RDK), which consists of a number of dots, only some of which move in a particular “signal” direction. Subjects are typically asked to decide in which of two directions the RDK is moving. With a single source of visual information the sensory data provide evidence for both alternatives. In motion discrimination tasks this evidence comes from neurons in area MT whose activity (firing rate) is tuned to respond to motion in a particular direction. At each moment in time, evidence from two populations of neurons is used to update a single decision variable. (b) Decision model proposed by Krajbich et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0078993#pone.0078993-Laming1" target="_blank">[18]</a> for a comparative two-alternative decision problem with two sources of visual stimuli. In their study, participants were asked to choose between two food items presented simultaneously in different locations on the screen. With each stimulus providing evidence about one particular alternative, the decision variable is no longer updated simultaneously by evidence for all available targets. Instead, as a target is fixated (target X in (b)) evidence supporting that target is generated and incorporated into the decision variable. During this time, the mechanisms that represent the evidence for the non-fixated target remain silent (shaded out branch for target Y in (b)).</p

Sensory uncertainty estimates and their relation to gaze time.

<p>(a) Standard deviation of the angular errors (angular deviation metric; see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0078993#s4" target="_blank">Methods</a> for details) in the single pattern direction estimation task. Patterns were viewed for 750 ms (close to the average gaze time on the first pattern in the main experiment). (b) Gaze time ratio of low and high coherence first patterns (from trials in which the coherence of the two patterns differed) versus the ratio of the standard deviation of the single pattern direction estimates. Data are shown separately for known and unknown conditions (<i>N</i> = 8 in both conditions). The thick black line shows linear regression on the data averaged across the two levels of prior knowledge. The thin grey line shows the identity correspondence. (c) Same as panel b, but with the gaze time data pooled across prior knowledge and split depending on the number of switches. The thick black line shows the same regression as in (b).</p

The trial sequences of the presented experiments.

<p>(a) Comparative two-alternative forced choice decision task. During each trial observers are presented with two stationary RDKs with centres located above and below the centre point of the screen on the vertical axis. The activation of the RDKs was gaze contingent, with a given RDK activated once the observer's gaze fell within the appropriate region of the display. The task was to identify the target pattern: the one whose signal direction was further clockwise through the short angle. RDKs could consist of either black or white dots in both the full and no prior knowledge conditions but the conditions differed in whether the dot polarity was linked to a noise level. A trial started with a preview period of 1000 ms in which observers could process the polarity of the patterns and were instructed by an arrow (appearing 500 ms after trial onset) which pattern to view first. Following the preview, they were free to actively sample the patterns over a period of 1500 ms and subsequently gave their response once both RDKs were extinguished. They were instructed that they must look at each pattern at least once in the course of a trial but other than that, they could switch between patterns in any way they wanted. The figure shows a trial in which the observer was instructed to view the upper pattern first and made only one switch. The eye indicates the vertical eye position, the hatched arrows the signal direction of motion of the moving pattern. The figure is not to scale. (b) Single pattern direction estimation task. Observers viewed a single pattern between 75 and 1000 ms. Once the RDK had offset, they indicated their estimate of the signal direction by moving an arrow to this direction with a mouse and clicking.</p

Sampling allocation as measured by the gaze time on the first pattern.

<p>Gaze time on the first pattern includes all re-fixations and is expressed as a proportion of the overall gaze time on both patterns. In other words, this variable corresponds to the proportion of available sampling time (excluding the initial saccade latency and the duration of any subsequent movements) spent on the pattern that was cued first. Data are averaged over eight observers and the error bars display within-subject standard error <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0078993#pone.0078993-Bakeman1" target="_blank">[23]</a>. (a) Gaze time contingent on the coherence of the first and second patterns. (b) Gaze time contingent on the accuracy of the perceptual decision. (c) Gaze time contingent on the number of switches.</p