This research was made possible with startup funds from Arcadia University and Elmhurst College awarded to K.S.M., a student-faculty collaborative grant from Elmhurst College to E.A.W. and K.S.M., and an Arcadia University faculty development grant to K.S.M. We would like to thank Daniel H. Weissman, a collaborator on prior publications using versions of this protocol. We also wish to thank the additional students who collected data on previous versions of this protocol, including Marshall O'Moore, Patricia Chen, Amanda Lai, Elise Darling, Erika Pinsker, Somin Lee, Celine Santos, Greg Ramos, and Kathleen Trencheny.

All of the methods described here were approved by the Arcadia University Institutional Review Board.
1. Design and Prepare the Experiment for Data Collection
NOTE: See the introduction for general information about design and trial types. See the discussion for more information about specific choices that can be made in each of these sub-steps. See Video 1 for a dynamic view of the task, and Video 2 for a slowed down version of the task.
<ol>
	<li>Choose trial types (i.e., Target Alone, Same Target Colored distraction, and Different Target Colored distraction as well as either or both of Distractor Alone and Non Target Colored distraction), and the preferred number of trials within each trial type7,20.</li>
	<li>Choose the target-distractor lag lengths in each trial type that contains distractors and targets (e.g., lags 1, 2, 3, and 4, or just lags 1 and 4, etc.)</li>
	<li>Choose colors for the letters - target colors, peripheral distractor colors, and central filler colors; there must be at least two target colors. Ensure that target colors are separated in color space by at least one &#34;filler&#34; color that appears in the central RSVP. See Figure 2 for example stimulus colors.</li>
	<li>Program the task using a flexible and reliable stimulus presentation software package (e.g., Psychtoolbox implemented in MATLAB39). 
	NOTE: Refer to software tutorials to learn about how to create stimulus presentations and collect responses.</li>
	<li>Ensure that the letter stimuli subtend 2.07 x 1.88 degrees of visual angle and are written in Arial font. Display the peripheral letters 4.22 degrees of visual angle to the right and left of the central letter.</li>
	<li>Present each frame of the display for 116 ms. 
	NOTE: There are three letters per frame display: the central letter and two peripheral letters.</li>
	<li>Other than when a target appears, assign &#34;filler&#34; colors to the letters in the central RSVP (see Figure 1). Assign these colors randomly, with the caveat that no two letters appearing adjacently in time in the RSVP sequence have the same color.</li>
	<li>Other than when a colored peripheral distractor appears, assign the color grey to the letters in the peripheral locations.</li>
	<li>Collect keyboard responses for 1740 ms following every trial.</li>
	<li>Randomize the order of all of the trials throughout the experiment.</li>
	<li>Include a two-part practice session at the start of the experiment that eases participants into the task and exposes them to all of the trial types.
	<ol>
		<li>In the first part, include at least 16 Target Alone trials, presented in all target colors with even representation of each color.</li>
		<li>Remind participants of the to-be-searched target colors by including color patches of these colors that appear just above the RSVP display and keep them fixed throughout the first part of practice.</li>
		<li>Start the practice at a slower RSVP speed, 250 ms per frame. Increase the speed (decrease the frame rate) by 10 ms every time a target is presented until reaching the final experiment speed.</li>
		<li>In the second part, remove the color patches and introduce trial types with peripheral distractors. Include at least 12 trials in total, and ensure that all trial types are presented at least once.</li>
	</ol>
	</li>
	<li>Provide participants with self-paced breaks every minute. After 32 trials, halt the continuous RSVP sequence and display a screen that says, &#34;Please take a break. Press the space bar to continue.&#34; On this screen, remind participants of the colors they are seeking. Present this text: &#34;As a reminder, these are your target colors:&#34; and follow it with &#34;ABCXYZ&#34; written in each target color.</li>
</ol>
2. Set up the Apparatus
<ol>
	<li>Use a computer with a 60 Hz refresh rate and a monitor and graphics card combination that provides millisecond precision of timing (see the Table of Materials).</li>
	<li>Ensure that the keyboard, monitor, and participant chair are in a fixed location, as proper and consistent spacing from the participant to the computer screen is important. If using a shared space, use masking tape to mark desired locations of equipment on the desk/table.</li>
</ol>
3. Recruit participants for the experiment.
<ol>
	<li>Recruit participants who are 18 - 35 years of age, free of neurological conditions, have corrected to normal vision, and are not colorblind.</li>
	<li>Perform a power calculation using previously published results and/or pilot participants in order to determine the appropriate sample size.40,41</li>
</ol>
4. Test the participants
<ol>
	<li>Obtain necessary consent according to the authorizing review board&#39;s policies.</li>
	<li>Seat the participants at a distance of 57 cm from the monitor, at which distance 1 cm on the screen corresponds to 1 degree of visual angle. Enforce this viewing distance with the use of a chin rest or with experimenter supervision.</li>
	<li>Check for colorblindness, by asking the participant completing an online colorblindness test42. Do not analyze data from a participant who is deemed colorblind.</li>
	<li>Open the software, navigate to the experiment folder, and type the experiment script (designed based upon the guidelines from section 1) into the command window and press enter; the program will run.</li>
	<li>Help the participant through the instructions, which are printed on a series of screens and can be read in a self-paced fashion. In addition to reading the instructions on the screen, state the following: &#34;This task is very difficult, with performance averaging about 75% correct. Do not be discouraged if you feel you are making many mistakes.)&#34;</li>
	<li>Supervise the participant during the experiment to ensure that he/she maintains a uniform viewing distance from the monitor, is completing the task properly (e.g., using the correct response keys used), and is not falling asleep or becoming distracted.</li>
	<li>Provide feedback and encouragement during the practice session.
	<ol>
		<li>Remind the participants of the key responses. Tell them, &#34;Remember, the &#34;J&#34; response key is for any target letter coming from the first half of the alphabet, and the &#34;K&#34; response key is for any target letter coming from the second half of the alphabet. Do not press &#34;J&#34; for one target color and &#34;K&#34; for the other.&#34;</li>
		<li>Remind participants to slow down and consider which response to make after identifying a letter, and that the response well be recorded as &#34;correct&#34; even if it does not occur immediately.</li>
	</ol>
	</li>
	<li>When the program concludes, debrief and dismiss the participant. Explain the purpose of the experiment and answer questions. Ask if the participant had any difficulties with the experiment or with completing the task.</li>
</ol>

The authors have nothing to disclose.

There are several considerations in using this method. The most important step to take is to ensure that the design requires participants to search for two or more targets at a time, and that there are &#34;STC&#34; and &#34;DTC&#34; distractor trial types, as these will provide the researcher with a measure of set-specific capture (STC - DTC). It is also helpful to have an &#34;NTC&#34; trial type to properly measure contingent attentional capture (NTC - STC), though one can estimate NTC performance with Target Alone pe...

Contingent attentional capture refers to a performance cost (slower reaction times and lower accuracy) that occurs when a participant erroneously directs attention to a distractor similar to their search goal. Indexing top-down orienting of attention, contingent attentional capture only occurs when a goal-relevant distractor is present (e.g., a green digit when searching for green letters), but not when a goal-irrelevant stimulus is present (e.g., a blue digit). Studies of contingent attentional capture have been integral to the understanding of top-down orienting and the limitations of information processing, namely, that once a stimulus captures attention, it is processed in a serial and effortful manner1,2,3. Contingent attentional capture is most often measured using static displays that mimic a common visual search, such as searching for a red pepper in the produce section of a grocery store3,4. In this example, an item sharing features with the target, such as a red apple, might capture attention, slowing down the search. Contingent attentional capture can be observed for color3,5,6,7, shape8, motion9, time10, and semantic relevance11,12. In addition to static displays, contingent attentional capture has been measured using dynamic displays that mimic situations such as searching for a landmark while driving along a road, or looking for a person in a quickly moving crowd13,14.
More recently, researchers have investigated the consequences of attending to distractors when more than one search goal is active (such as searching for a red pepper and&#160;garlic at the same time7,8,15,16,17,18,19,20,21,22,23.) In such situations, distraction costs can be especially devastating. While evidence is mixed as to whether multi-goal searches impair performance when distraction is not present, attentional capture from goal-related distractors can cause very large deficits in performance. In particular, we identified a new form of attentional capture called &#34;set-specific capture,&#34; which occurs when multiple goals are concurrently maintained. In the case of set-specific capture, performance costs are especially large when a distractor resembling one target goal (e.g., an apple) grabs attention from the target item matching the other goal (e.g., the garlic)7,20,21,22. See Figure 1 for an explanation of a typical finding, using this grocery example.
As in the case with contingent attentional capture, set-specific capture reveals that information is processed in a serial and effortful manner: when a distractor captures attention, attentional resources are drawn away from the target. In addition, set-specific capture shows that directing attention to the distractor&#39;s features leads to enhancement of the related goal within working memory. Thus, when more than one goal is concurrently maintained, this goal enhancement comes at the expense of any other current goals7,21,22. Set-specific capture is a consequence of multitasking, akin to switch costs and mixing costs found in task-switching studies, but also distinct from these measures24. It is important that future studies investigate this multitasking cost, both in order to understand the magnitude and nature of the impairment for practical reasons (e.g., safety-related situations involving dual-tasking), as well as to refine our understanding of the mechanics of visual search and how goals are maintained. For example, set-specific capture provides support for the idea that a single goal can be focused upon while a target or target-resembling distractor is attended, but that more goals are maintained in an accessory state during visual search25,26,27.
The present method provides a robust way of measuring both contingent attentional capture and set-specific capture within a single paradigm. It uses a dynamic display, inspired by previous work on the attentional blink and contingent attentional capture with rapid serial visual presentations (RSVPs) of stimuli13,14,28,29,30. This type of display yields much larger effects than do static display tasks, which usually rely on reaction time as a dependent measure, rather than accuracy3,31,32. These larger effects allow researchers to use this paradigm to measure more sensitive manipulations of set-specific capture, such as the effect of practice20.
In this task, participants search a heterogeneously colored, centrally-located RSVP for letters appearing in either of two &#34;target&#34; ink colors (e.g., green and orange; see Figure 2 for example stimulus colors). Any time a participant detects a target-colored letter appearing in the central display, they indicate whether the letter was from the first half of the alphabet (&#34;press the &#39;J&#39; key&#34;) or the second half of the alphabet (&#34;press the &#39;K&#39; key&#34;). Meanwhile, participants ignore two RSVP displays consisting of mostly grey letters that appear on either side of the central display. Thus, at any given time, there are three letters on the screen at once - one centrally located and two peripheral. The letters change identity and color every 116 ms.
An experiment may consist of the following trial types: Target Alone, Distractor Alone, Non-Target Colored Distractor (NTC), Same Target Colored Distractor (STC), and Different Target Colored Distractor (DTC). In the Target Alone trial type, a target letter (e.g., a green C) appears in the central RSVP, without any color changes occurring in the peripheral RSVPs preceding it. In the Distractor Alone&#160;trial type, a target-colored item appears in one of the peripheral RSVP displays without a target item appearing afterward. The purpose of this trial type is to prevent participants from using a peripheral color change to predict an upcoming target, by including some trials in which a distractor did not predict a target. In the NTC, STC, and DTC trial types, a colored letter distractor appears in one of the peripheral displays before the target appears centrally, with a &#34;lag&#34; of 1 - 4 display frames (116 - 464 ms) between the appearance of the distractor and the target. For NTC trials, the distractor is not target-colored (e.g., a purple &#39;V&#39;). In STC trials, the distractor (e.g., an orange &#39;B&#39;) is the same color as the following target (e.g., an orange &#39;T&#39;). In DTC trials, the distractor (e.g., an orange &#39;C&#39;) is target-colored, but not the same color as the upcoming target (e.g., a green &#39;V&#39;). See Figure 3 for a schematic of the task, including examples of each trial type. See Video 1 (video) for an example of the task. Viewed on loop, the example includes two targets. Video 2 (video) is the same video at a reduced speed for clarity.
Contingent attentional capture is indicated by the difference between NTC and STC performance, as a target-colored item captures attention only when it bears resemblance to one of the current goals (i.e., not on NTC trials, which usually yield the same accuracy level as Target Alone trials). Set-specific capture is indicated by the difference between STC and DTC performance. We have published several versions of this task, with slightly different configurations of trial types (i.e., with or without NTC and Distractor Alone trials; with just lags 1 and 3, with a variety of target colors, with three targets, etc.7,20,21,22).
One notable feature of this method is that it uses a continuous display. Each trial includes the minimum components to represent that trial type, (e.g., a peripheral distractor, a target, and any letters that appeared in time between the distractor and target.) &#34;Filler&#34; stimuli connect one trial to the next seamlessly, and participants respond during this intertrial interval, whenever they detect a target. The interval lasts from 15 - 21 frames (1740 - 2436 ms), which is sufficient time to respond; most responses occur within 700 ms. An advantage of this method is that chance performance is near 0%; participants are not explicitly aware that a trial has ended if they miss a target item. This allows for three types of outcomes: 1) an identified letter, which will lead to a correct response, 2) a detected but not identified item (e.g., &#34;I saw something green&#34;), which will lead to a 50% chance of a correct response, and 3) an undetected / missed item, which leads to no response (coded as inaccurate). These three outcomes provide more information about the degree of stimulus processing than do tasks with a two alternative forced choice response, which cannot differentiate between detection-without-identification (i.e., a response error) and an outright miss (i.e., an omission error).
We describe the method here as we have used it in published work, in which participants search for colored letters. However, it can be modified for use with images33 and potentially other stimuli, such as words34. Moreover, distractors can appear as other colored items in the central display rather than just as colored letters appearing in the periphery (e.g., a target-colored digit in the central display)21. It is also likely that set-specific capture can be identified in static displays. The further development of the extensions of this method will allow researchers to investigate topics such as the effect of reward and motivation on distraction35, or whether distraction costs are modulated by the number of concurrently maintained goals33. Other applications could include measuring distraction costs in real-world contexts such as when completing a demanding visual search task (e.g., airport baggage screening or radiology screening)36,37,38.

<table><tbody><tr><td>MATLAB</td><td>Mathworks</td><td>R2014b</td><td>General computing platform</td></tr><tr><td>Psychtoolbox</td><td>Psychtoolbox</td><td>PTB-3</td><td>Toolbox of routines for use with MATLAB</td></tr><tr><td>G*Power</td><td>Universit&amp;auml;t D&amp;uuml;sseldorf</td><td>G*Power 3.1.9.2 for Windows</td><td>Software to assist with performing power calculations</td></tr><tr><td>24&amp;rdquo; HDMI Gaming Monitor</td><td>ASUS</td><td>VG248QE</td><td>High quality LCD monitor with excellent timing</td></tr></tbody></table>

using rapid serial visual presentation to measure set-specific capture, a consequence of distraction while multitasking

This method uses a rapid serial visual presentation (RSVP) paradigm to measure the cost of distraction when participants maintain multiple search goals. The protocol identifies two types of distraction within a single task - contingent attentional capture and set-specific capture - that represent different types of limitations of cognitive processing. Participants search for letters in two or more &#34;target&#34; ink colors (e.g., green and orange) within a continuous RSVP stream of heterogeneously colored letters, while ignoring two peripheral RSVPs of letters. Upon detecting a target, participants are to identify the letter. On some trials, target-colored distractors appear in the periphery just prior to the presentation of a target, causing a drop in target identification performance. Contingent attentional capture is observed by examining performance on trials in which the peripheral distractor is the same color as the target on that trial (e.g., both orange). Set-specific capture is represented by performance on trials in which the peripheral distractor is target-colored (e.g., orange), but not the same color as the target on that trial (e.g., green.) By varying the amount of time (i.e., the number of stimuli appearing) between the presentation of the distractor and the target, researchers can observe how participants recover from these distraction costs over time. As compared to static displays that are often used to measure contingent attentional capture, the dynamic display produces much larger effects, allowing the researcher to identify subtle effects of smaller manipulations. An unusual aspect of our design is that it employs a continuous display; &#34;filler&#34; stimuli connect one trial to the next seamlessly, and participants respond during this interval whenever they detect a target. The continuous display reduces chance performance to near-zero levels (rather than 50%) and provides researchers with a more sensitive measure of performance differences across trial types.

We report several examples of representative data. In the first example, there were two lags (1 and 3), two distractor trial types (STC and DTC), and 57 participants. There were also Target Alone and Distractor Alone trial types. In a repeated measures ANOVA with the factors trial type and lag, there was a main effect of each factor as well as an interaction between the two. Performance was better at lag 3 (mean (M) = 0.655, standard error (SE) = 0.018) than at lag 1 (<e...

Watch this Scientific Journal Video about Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking at JoVE.com

Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking

This method uses a dynamic visual display to index costs of distraction during visual search, including both &#34;contingent attentional capture&#34; and &#34;set-specific capture,&#34; which is a cost of distraction that occurs when the participants maintain multiple search goals simultaneously. This method has revealed basic mechanisms and limitations of visual attention.

This method uses a rapid serial visual presentation (RSVP) paradigm to measure the cost of distraction when participants maintain multiple search goals. ...

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8.8K Views.  Arcadia University. Deze methode maakt gebruik van een dynamische visuele weergave index kosten van afleiding tijdens visuele zoekactie, met inbegrip van zowel "voorwaardelijke attentional opname" en "set-specifieke opname," oftewel een kosten van afleiding die optreedt wanneer de deelnemers Multi-zoeken behouden doelen tegelijkertijd. Deze methode heeft geopenbaard basismechanismen en beperkingen van visuele aandacht.

Video: Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking

Measuring Attentional Biases for Threat in Children and Adults

Investigators have long been interested in the human propensity for the rapid detection of threatening stimuli. However, until recently, research in this domain has focused almost exclusively on adult participants, completely ignoring the topic of threat detection over the course of development. One of the biggest reasons for the lack of developmental work in this area is likely the absence of a reliable paradigm that can measure perceptual biases for threat in children. To address this issue, we recently designed a modified visual search paradigm similar to the standard adult paradigm that is appropriate for studying threat detection in preschool-aged participants. Here we describe this new procedure. In the general paradigm, we present participants with matrices of color photographs, and ask them to find and touch a target on the screen. Latency to touch the target is recorded. Using a touch-screen monitor makes the procedure simple and easy, allowing us to collect data in participants ranging from 3 years of age to adults. Thus far, the paradigm has consistently shown that both adults and children detect threatening stimuli (e.g., snakes, spiders, angry/fearful faces) more quickly than neutral stimuli (e.g., flowers, mushrooms, happy/neutral faces). Altogether, this procedure provides an important new tool for researchers interested in studying the development of attentional biases for threat.

Here we describe a touch-screen visual search paradigm that can be used to study threat detection across the lifespan. The paradigm has already been used in various studies demonstrating that both children and adults detect threatening stimuli like snakes, spiders, and angry faces faster than non-threatening stimuli.

Investigators have long been interested in the human propensity for the rapid detection of threatening stimuli. However, until recently, research in this ...

A Cognitive Paradigm to Investigate Interference in Working Memory by Distractions and Interruptions

Goal-directed behavior is often impaired by interference from the external environment, either in the form of distraction by irrelevant information that one attempts to ignore, or by interrupting information that demands attention as part of another (secondary) task goal. Both forms of external interference have been shown to detrimentally impact the ability to maintain information in working memory (WM). Emerging evidence suggests that these different types of external interference exert different effects on behavior and may be mediated by distinct neural mechanisms. Better characterizing the distinct neuro-behavioral impact of irrelevant distractions versus attended interruptions is essential for advancing an understanding of top-down attention, resolution of external interference, and how these abilities become degraded in healthy aging and in neuropsychiatric conditions. This manuscript describes a novel cognitive paradigm developed the Gazzaley lab that has now been modified into several distinct versions used to elucidate behavioral and neural correlates of interference, by to-be-ignored distractors versus to-be-attended interruptors. Details are provided on variants of this paradigm for investigating interference in visual and auditory modalities, at multiple levels of stimulus complexity, and with experimental timing optimized for electroencephalography (EEG) or functional magnetic resonance imaging (fMRI) studies. In addition, data from younger and older adult participants obtained using this paradigm is reviewed and discussed in the context of its relationship with the broader literatures on external interference and age-related neuro-behavioral changes in resolving interference in working memory.

A novel cognitive paradigm is developed to elucidate behavioral and neural correlates of interference by to-be-ignored distractors versus interference by to-be-attended interruptors during a working memory task. In this manuscript, several variants of this paradigm are detailed, and data obtained with this paradigm in younger/older adult participants is reviewed.

Goal-directed behavior is often impaired by interference from the external environment, either in the form of distraction by irrelevant information that ...

A Dual Task Procedure Combined with Rapid Serial Visual Presentation to Test Attentional Blink for Nontargets

When viewers search for targets in a rapid serial visual presentation (RSVP) stream, if two targets are presented within about 500 msec of each other, the first target may be easy to spot but the second is likely to be missed. This phenomenon of attentional blink (AB) has been widely studied to probe the temporal capacity of attention for detecting visual targets. However, with the typical procedure of AB experiments, it is not possible to examine how the processing of non-target items in RSVP may be affected by attention. This paper describes a novel dual task procedure combined with RSVP to test effects of AB for nontargets at varied stimulus onset asynchronies (SOAs). In an exemplar experiment, a target category was first displayed, followed by a sequence of 8 nouns. If one of the nouns belonged to the target category, participants would respond &#8216;yes&#8217; at the end of the sequence, otherwise participants would respond &#8216;no&#8217;. Two 2-alternative forced choice memory tasks followed the response to determine if participants remembered the words immediately before or after the target, as well as a random word from another part of the sequence. In a second exemplar experiment, the same design was used, except that 1) the memory task was counterbalanced into two groups with SOAs of either 120 or 240 msec and 2) three memory tasks followed the sequence and tested remembrance for nontarget nouns in the sequence that could be anywhere from 3 items prior the target noun position to 3 items following the target noun position. Representative results from a previously published study demonstrate that our procedure can be used to examine divergent effects of attention that not only enhance targets but also suppress nontargets. Here we show results from a representative participant that replicated the previous finding.&#160;

This paper describes a novel dual task procedure combined with Rapid Serial Visual Presentation to look at attentional blink at varied stimulus onset asynchronies. This experimental procedure differed from others in that it tested attentional blink for nontargets.

When viewers search for targets in a rapid serial visual presentation (RSVP) stream, if two targets are presented within about 500 msec of each other, the ...

Methods to Test Visual Attention Online

Online data collection methods have particular appeal to behavioral scientists because they offer the promise of much larger and much more representative data samples than can typically be collected on college campuses. However, before such methods can be widely adopted, a number of technological challenges must be overcome &#8211; in particular in experiments where tight control over stimulus properties is necessary. Here we present methods for collecting performance data on two tests of visual attention. Both tests require control over the visual angle of the stimuli (which in turn requires knowledge of the viewing distance, monitor size, screen resolution, etc.) and the timing of the stimuli (as the tests involve either briefly flashed stimuli or stimuli that move at specific rates). Data collected on these tests from over 1,700 online participants were consistent with data collected in laboratory-based versions of the exact same tests. These results suggest that with proper care, timing/stimulus size dependent tasks can be deployed in web-based settings.

To replicate laboratory settings, online data collection methods for visual tasks require tight control over stimulus presentation. We outline methods for the use of a web application to collect performance data on two tests of visual attention.

Online data collection methods have particular appeal to behavioral scientists because they offer the promise of much larger and much more representative ...

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

This protocol describes how to conduct temporal-order experiments to measure visual processing speed and the attentional resource distribution. The proposed method is based on a new and synergistic combination of three components: the temporal-order judgments (TOJ) paradigm, Bundesen&#39;s Theory of Visual Attention (TVA), and a hierarchical Bayesian estimation framework. The method provides readily interpretable parameters, which are supported by the theoretical and neurophysiological underpinnings of TVA. Using TOJs, TVA-based estimates can be obtained for a broad range of stimuli, whereas traditional paradigms used with TVA are mainly limited to letters and digits. Finally, the meaningful parameters of the proposed model allow for the establishment of a hierarchical Bayesian model. Such a statistical model allows assessing results in one coherent analysis both on the subject and the group level.
To demonstrate the feasibility and versatility of this new approach, three experiments are reported with attention manipulations in synthetic pop-out displays, natural images, and a cued letter-report paradigm.

Temporal-order judgments can be used to estimate processing speed parameters and attentional weights and thereby to infer the mechanisms of attentional processing. This methodology can be applied to a wide range of visual stimuli and works with many attention manipulations.

This protocol describes how to conduct temporal-order experiments to measure visual processing speed and the attentional resource distribution. The ...

Central and Divided Visual Field Presentation of Emotional Images to Measure Hemispheric Differences in Motivated Attention

Two dominant theories on lateralized processing of emotional information exist in the literature. One theory posits that unpleasant emotions are processed by right frontal regions, while pleasant emotions are processed by left frontal regions. The other theory posits that the right hemisphere is more specialized for the processing of emotional information overall, particularly in posterior regions.
Assessing the different roles of the cerebral hemispheres in processing emotional information can be difficult without the use of neuroimaging methodologies, which are not accessible or affordable to all scientists. Divided visual field presentation of stimuli can allow for the investigation of lateralized processing of information without the use of neuroimaging technology. 
This study compared central versus divided visual field presentations of emotional images to assess differences in motivated attention between the two hemispheres. The late positive potential (LPP) was recorded using electroencephalography (EEG) and event-related potentials (ERPs) methodologies to assess motivated attention. Future work will pair this paradigm with a more active behavioral task to explore the behavioral impacts on the attentional differences found.

This study compared central versus divided visual field presentations of emotional images to assess differences in motivated attention between the two hemispheres. The late positive potential (LPP) was recorded using electroencephalography (EEG) and event-related potentials (ERPs) methodologies to assess motivated attention.

Two dominant theories on lateralized processing of emotional information exist in the literature. One theory posits that unpleasant emotions are processed ...

Investigating Oculomotor Responses in Visual Duration Perception Tasks

Eye Movements in Visual Duration Perception: Disentangling Stimulus from Time in Predecisional Processes

Eye-tracking methods may allow the online monitoring of cognitive processing during visual duration perception tasks, where participants are asked to estimate, discriminate, or compare time intervals defined by visual events like flashing circles. However, and to our knowledge, attempts to validate this possibility have remained inconclusive so far, and results remain focused on offline behavioral decisions made after stimulus appearance. This paper presents an eye-tracking protocol for exploring the cognitive processes preceding behavioral responses in an interval comparison task, where participants viewed two consecutive intervals and had to decide whether it speeded up (first interval longer than second) or slowed down (second interval longer). 
Our main concern was disentangling oculomotor responses to the visual stimulus itself from correlates of duration related to judgments. To achieve this, we defined three consecutive time windows based on critical events: baseline onset, the onset of the first interval, the onset of the second interval, and the end of the stimulus. We then extracted traditional oculomotor measures for each (number of fixations, pupil size) and focused on time-window-related changes to separate the responses to the visual stimulus from those related to interval comparison per se. As we show in the illustrative results, eye-tracking data showed significant differences that were consistent with behavioral results, raising hypotheses on the mechanisms engaged. This protocol is embryonic and will require many improvements, but it represents an important step forward in the current state of art.

Author Spotlight: Exploring the Link Between Time Perception of Visual Stimuli and Reading Skills

We present a protocol that employs eye tracking to monitor eye movements during an interval comparison (duration perception) task based on visual events. The aim is to provide a preliminary guide to separate oculomotor responses to duration perception tasks (comparison or discrimination of time intervals) from responses to the stimulus itself.

Eye-tracking methods may allow the online monitoring of cognitive processing during visual duration perception tasks, where participants are asked to ...

Stimulus-specific Cortical Visual Evoked Potential Morphological Patterns

This paper presents a methodology for the recording and analysis of cortical visual evoked potentials (CVEPs) in response to various visual stimuli using 128-channel high-density electroencephalography (EEG). The specific aim of the described stimuli and analyses is to examine whether it is feasible to replicate previously reported CVEP morphological patterns elicited by an apparent motion stimulus, designed to simultaneously stimulate both ventral and dorsal central visual networks, using object and motion stimuli designed to separately stimulate ventral and dorsal visual cortical networks.&#160; Four visual paradigms are presented: 1. Randomized visual objects with consistent temporal presentation. 2. Randomized visual objects with inconsistent temporal presentation (or jitter).&#160; 3. Visual motion via a radial field of coherent central dot motion without jitter.&#160; 4. Visual motion via a radial field of coherent central dot motion with jitter.&#160; These four paradigms are presented in a pseudo-randomized order for each participant.&#160; Jitter is introduced in order to view how possible anticipatory-related effects may affect the morphology of the object-onset and motion-onset CVEP response.&#160; EEG data analyses are described in detail, including steps of data exportation from and importation to signal processing platforms, bad channel identification&#160;and removal, artifact rejection, averaging, and categorization of average CVEP morphological pattern type based upon latency ranges of component peaks. Representative data show that the methodological approach is indeed sensitive in eliciting differential object-onset and motion-onset CVEP morphological patterns and may, therefore, be useful in addressing the larger research aim. Given the high temporal resolution of EEG and the possible application of high-density EEG in source localization analyses, this protocol is ideal for the investigation of distinct CVEP morphological patterns and the underlying neural mechanisms which generate these differential responses.&#160; &#160; &#160;&#160;

In this paper, we present a protocol to investigate differential cortical visual evoked potential morphological patterns through stimulation of ventral and dorsal networks using high-density EEG. Visual object and motion stimulus paradigms, with and without temporal jitter, are described. Visual evoked potential morphological analyses are also outlined.&#160;&#160;

This paper presents a methodology for the recording and analysis of cortical visual evoked potentials (CVEPs) in response to various visual stimuli using ...

Neuroscience

Multiple Object Tracking

Source: Laboratory of Jonathan Flombaum&#8212;Johns Hopkins University

In a staggeringly complex and engaging world, it is crucial to selectively process some stimuli at the expense of others. Experimental psychologists call this ability attention. Specifically, visual attention refers to the ability to selectively process aspects of a visual scene.
Many paradigms used to study visual attention involve brief, punctuated, and repeated trials. However, everyday situations often place sustained demands on attention, as opposed to requiring only brief focus. For example, compare driving through busy city streets, which demands sustained attention, with crossing a busy street, which demands just a few moments of caution. To investigate sustained visual attention, experimental psychologists typically rely on a paradigm called multiple object tracking.
This video demonstrates standard procedures for investigating sustained visual attention through multiple object tracking.

Multiple Object Tracking: Studying Sustained Visual Attention

Source: Laboratory of Jonathan Flombaum&#8212;Johns Hopkins University

In a staggeringly complex and engaging world, it is crucial to selectively process ...

Education

JoVE Science Education

Psychology

Cognitive Psychology

Inattentional Blindness

Source: Laboratory of Jonathan Flombaum&#8212;Johns Hopkins University
We generally think that we see things pretty well if they are close by and right in front of us. But do we? We know that visual attention is a property of the human brain that controls what parts of the visual world we process, and how effectively. Limited attention means that we can't process everything at once, it turns out, even things that might be right in front of us. 
In the 1960s, the renowned cognitive psychologist Ulrich Neisser began to demonstrate experimentally that people can be blind to objects that are right in front of them, literally, if attention is otherwise distracted. In the 1980s and 1990s, Arien Mack and Irvin Rock followed up on Neisser's work, developing a simple paradigm for examining how, when, and why distracted attention can make people fail to see the whole object. Their experiments, and Neisser's, did not involve people with brain damage, disease, or anything of the sort, just regular people who failed to see objects that were right in front of them. This phenomenon has been called inattentional blindness. This video will demonstrate basic procedures for investigating inattentional blindness using the methods of Mack and Rock.1

Investigating Visual Awareness and Inattentional Blindness

Source: Laboratory of Jonathan Flombaum&#8212;Johns Hopkins University
We generally think that we see things pretty well if they are close by and right in ...

Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking

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