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WordPress Shortcode. Published in: Technology. In panel a is depicted a lag 1 trial. Attention triggered by the first target boosts processing of the second target also, such that both targets are encoded.

The moment at which encoding is complete is indicated by the arrow in the upper right, and corresponds to the point at which the tokens not shown cross threshold.

The temporal order in which the activation of the type nodes ends corresponds to the perceived order of the two targets T1 then T2. In panel b , two targets are separated by a ms distractor.

During this gap, attention is suppressed by T1 encoding so as to defer the processing of T2 into a second episode. However, because the T2 is quickly masked by a following distractor, this deferral of T2 processing produces an attentional blink that swallows the T2.

In the absence of a mask, the T2 would be encoded after T1 encoding was complete. Multiple items processed within a single episode interfere weakly with one another through lateral inhibitory projections.

This interference has a much larger influence on behavior when three or four targets are in the same episode, as will be seen below. Signs of this interference can be seen in figure 6a , as the T2 activation trace rises slightly at the end of T1 encoding.

In the bottom panel Figure 6b , the T2 arrives at lag 2 following an intervening distractor. Here, the T2 arrives too late to hold the attentional gate open and thus has missed the opportunity to join the episode initiated by the T1.

In a more natural visual context, the T2 representation might persist in early visual areas and begin a second episode once the prior episode has been encoded.

However, in RSVP, the backward masking from the following distractor wipes out the trace of the T2 so quickly that it can fail to be encoded during the delay.

Capacity limits of two types are often discussed in experimental paradigms involving rapidly presented stimuli.

The first of these is a limitation on the pool of available processing resources , which limits the rate at which information can be encoded into memory.

A second putative capacity limit is on the overall amount of information that can exist within a working memory store. Both of these limitations can reduce the overall number of items reported on a given trial.

Presenting too many targets within a short time window can make it impossible to encode all of the items presented within a trial, and trying to hold too many items in a memory store at the same time can likewise limit the number of reported items Davelaar However, in a model such as eSTST, which maintains a clear distinction between encoding of a target, and the subsequent maintenance of that target in a memory store, it is possible to separately consider limitations on processing and storage.

With regards to processing and storage capacity limits, the eSTST model has a weak form of the former, and none of the latter. Lateral inhibition in the type layer, which can be seen in figure 4 , causes each active type node to weakly suppress every other type node, thereby simulating the small but consistent cost of encoding multiple items at the same time.

However this weak interference does not cause the major portion of the attentional blink, a point we return to at length in the general discussion. As to the second type of capacity limit, the eSTST model does not simulate an overall limit on the number of targets in working memory.

Close inspection of the data from the present experiments does not suggest the involvement of this type of capacity limit in these experiments, a point we discuss in the final prediction of the paper.

Here, the eSTST model is used to generate seven predictions that explore the boundary conditions of what constitutes the break between attentional episodes and also the costs and benefits of allowing multiple items access to working memory during a single attentional episode.

These predictions are provided by simulating new experimental conditions with the same set of parameters used in the original publication of the model Wyble et al , with only the addition of new type and token nodes to allow up to 6 targets to be presented to the model.

Three main experiments are used to evaluate these predictions. What are the benefits and costs of encoding multiple items that are selected for working memory encoding during a single attentional episode?

In this experiment, subjects viewed four targets in different configurations. The model predicts that it is the temporal spacing of new target items that is most critical in sustaining an attentional episode.

If targets are presented within about ms of each other, attention can be sustained even during the presence of intervening distractors.

In the model, interleaving a distractor between two targets delays the encoding of the latter target, and thereby increases the accuracy of reporting the sequential order of the two targets.

The ten participants were volunteers from the MIT community between the ages of 18—35 who were paid to participate in the experiment, which took approximately 30 minutes.

All reported corrected or normal vision. The experiment was programmed using Matlab 5. An RSVP stream was presented centrally at the location of a fixation cross.

Black digits 2,3,4,5,6,7,8,9 in 70 point Arial were used as distractors. Stimuli were approximately 1. These stimuli comprised RSVP streams presented at either 53 or ms per item with no interstimulus interval.

Each trial consisted of an RSVP stream, which included four single-letter targets none repeated among digit distractors. There were two blocks of randomly mixed trial types.

Each trial began with a fixation cross for 1 second and a sequence of 7 to 12 distractors on the slow ms trials and double that number on the fast 53 ms trials, so that the average time before the first target was equated for the slow and fast RSVP rates.

At least 5 distractors followed the last target. Subjects were instructed that they would see four letters and should remember them for entry at the end of the trial.

They were told that they were free to report the targets if they were not sure, but not to guess randomly.

Report of temporal order of the targets was implicit in the response prompt provided to subjects, which appeared in a sequence of characters from left to right as subjects type in their response.

We intentionally avoided giving explicit emphasis to order information in the instructions out of concern that such emphasis would come at the expense of item information.

Subjects were allowed to correct their input string with backspace while entering it, and were given feedback as to the letters they saw and their correct order.

Responses were considered correct if subjects reported the correct identity, without regard to correct order although we did analyze the pattern of order errors for reported targets.

The predictions of the eSTST model for each of the four conditions were calculated. As the model uses time steps of 10 ms, presentation was simulated at 50 ms and ms per item rates.

In the simulation, the input strengths of the targets are varied over trials and performance is averaged over these trials to derive behavioral accuracy curves.

This strength value represents the processing difficulty of each target, which is assumed to vary due to differences in backward masking strength produced by the interaction of each target and the immediately following item, as well as intrinsic differences in the processing of each target, due to such factors as familiarity and orthographical or phonological similarity with other members of the target set, etc.

The model does not behave in the same way on every trial due to differences in item strength, but in the figure we have used a strength value in the middle of the input range.

Simulation of a single trial in each of the four conditions of Experiment 1. Traces reflect activation of 4 type nodes T1,T2,T3 and T4 in addition to the activation level of attention.

In the top panels, four consecutive targets are encoded at presentation rates of both ms and 50ms per item. In the bottom panels distractors are presented between the targets.

In the lower left panel, distractors separate the targets for a sufficient amount of time that two distinct episodes are formed by attention, at the loss of T2 and T4.

In contrast, at 50ms per item shown at the bottom right, the distractors are short enough that only one episode is triggered, but the weaker representations of the faster targets results in the loss of T4.

Target strength was fixed at 0. As previously described in Wyble et al. Attention triggered by the T1 spills over to the following item and amplifies the representation of T2, which in turn sustains the level of attention.

This dynamic continues for T3 and T4, although the accumulating interference between simultaneously active type nodes produces progressively weaker encoding.

In Figure 7 , for the trial in the upper left hand corner, all four targets are correctly encoded, and in the correct order.

When targets of the same input strength are presented for the same ms duration, but are now separated by distractors TDTDTDTD , the dynamics of attention are remarkably different.

Here, under the suppression from T1 encoding, the attentional gate is closed during the interval between the first two targets. Attention is thus suppressed when T2 arrives and remains so until T1 encoding is completed.

In the illustrated trial, T1 encoding is complete after approximately ms, freeing up the attentional gate in time for T3 to be encoded, which produces another period of attentional suppression that keeps the T4 from being encoded.

In this example trial bottom left panel of Figure 7 , attention has segmented the input into two episodes; successfully encoding T1 and T3 without overlap, but at the cost of missing T2 and T4 entirely.

Note that on other trials, using a different set of strength values for the targets, the predicted pattern of which targets are encoded would be different than this simulation.

In the simulated TTTT trial, all four targets are encoded, although in this particular example, the order is incorrect: T2,T3,T1,T4 as can be seen in the relative times at which the type node activations return to baseline.

For TDTDTDT trials, even though there are intervening distractors, the T2 arrives rapidly enough to benefit from the attention elicited by T1, and bolsters the deployment of attention against the suppression produced by encoding.

In this example trial but not in all cases , the building interference from the ongoing encoding of T1,T2 and T3 results in the episode being concluded prematurely and T4 is lost, producing the encoded sequence: T2, T1, T3.

In other trials, a stronger input strength for T4 would allow it to be encoded along with the preceding targets. An experimental block that uses randomly selected targets and distractors can be simulated by averaging over single trials that vary in their strength values.

For the following simulations, the strength of input values covered the same range as in Wyble et al a. Strength of an individual target varied in steps of.

The overall pattern of simulated accuracy in the four experimental conditions is depicted in Figure 8a—b , alongside the results of human subjects performing the same conditions as in Figure 8c—d.

Focussed analyses address each of the predictions. Comparison of simulated model output and human data in the four conditions of Experiment 1.

This ability to process multiple targets simultaneously with only a modest amount of interference is central to eSTST. Because attention is strongly engaged by a string of targets, performance is actually better when targets are presented closely together in time.

This is visible in the simulations shown in Figure 7 by comparing the top left panel to the bottom left panel. The human data are entirely consistent with an enhanced ability to process multiple targets arriving in immediate succession.

A highly reliable finding is that average accuracy was better for targets presented in a temporal cluster as compared to targets distributed over a longer time span.

As subjects are doing better on trials in which they are given less total time to process targets, it seems clear that resource limitations cannot be the primary cause of encoding failures in these trials.

There is, however, a potential confound of subject expectancy effects produced by mixing the slow and fast trials together and we address this problem in Experiment 1a below.

In the simulation, the presence of interleaved distractors at the 50 ms presentation rate does not produce an episodic division.

This comparison can be seen in the simulations shown in Figure 7 by comparing the top left panel to the bottom right panel.

In both cases there is a single attentional window, as can be seen by the trace of attentional activation. In both of these conditions, targets appear at ms intervals, so the temporal arrangement of targets is preserved but the presence of intervening distractors is varied.

Figure 9 depicts the comparison between these conditions in the human data. Comparison of simulation and human data between two conditions with equivalent spacing of target onsets.

Simulated SOAs were 50ms and ms. The model predicts that temporal information will be enhanced for two targets if attention segments them into separate episodes.

Specifically, on trials in which two given targets were successfully encoded, their reported order will be more accurate if those targets were separated by a distractor, while holding the temporal interval between them constant.

Figure 10 illustrates why the model has greater difficulty encoding order correctly when presented with TTT than TDT; in the former case, all three targets are encoded concurrently while in the latter, encoding of the second target begins when encoding of the first target is complete.

The strength values of the targets are the same in the two simulations, but the middle target of TTT allows attention to be sustained, creating an episode that includes all three targets.

In simulation, three contiguous targets are encoded as one episode a and targets presented as noncontiguous are divided into two episodes b.

The only difference between these conditions is the presence of an intervening target in panel a , which allows attention to be sustained.

The cost of combining multiple targets into a single episode can be observed as a temporal order error in panel a. T3 has greater strength and completes encoding before the T1 so that the encoded order of the targets is T3,T1, T2.

In b , T2 has exactly the same strength and relative TOA as the T3 in a but attentional suppression forces its encoding to wait until T1 is finished.

In this replication, ten participants saw an equal number of trials in condensed and distributed presentations in two mixed blocks of trials.

The results replicated the data of Experiment 1 for the slow trials in every respect as shown in Figure Comparison of accuracy between equivalent conditions in Experiment 1 and Experiment 1a.

How readily can subjects encode two episodes and how does encoding of a prior target affect encoding of the current one?

In this experiment, we asked subjects to report 6 targets. All items were presented for ms. Again, the simulations were run with the original parameters of the model.

In clustered presentation, performance averaged over both clusters of targets should be superior to the interleaved condition; subjects should be capable of encoding two episodes provided they are separated by an interval that is sufficiently long to allow the encoding of items acquired during the first episode to be completed.

The model predicts that attention functions differently during clustered vs interleaved target presentation; with clusters, reporting target T n-1 will only weakly affect report of target T n, because the close temporal proximity allows attention to be sustained across an entire episode.

With interleaved distractors, successful report of each target T n-1 will have a potent detrimental effect on the report of the following item T n, even though the two targets are now further apart in time, because successful encoding of T n-1 will have suppressed attention to T n.

The method was similar to that of Experiment 1 with the exceptions described below. Fourteen participants were drawn from the same subject pool as that of Experiment 1.

All stimuli were presented for ms. There were two trial types, intermixed randomly, in two identical blocks of trials. In each case, the temporal interval between the onset of the first and last targets was ms in the simulation, ms.

As in Experiment 1, the target sequences were preceded and followed by additional distractors. In the 6 target simulations, strength of an individual target varied in steps of.

In the results of the model simulation Figure 12 , report accuracy is superior for the clustered target presentation. Within each cluster, the close spacing of targets sustains the deployment of attention and targets are well encoded.

The separation between the clusters permits an episodic break, which allows processing of the first episode to be completed before the second begins, producing excellent performance for all six items.

When six targets are evenly distributed over the same temporal interval 1, ms , the simulated pattern of accuracy is distinctly different; performance decreases sharply for the second target and remains well below T1 levels until the end of the target sequence.

As with Experiment 1, the ms TOA between targets does not permit an attentional episode to be sustained and the attentional gate is intermittently opened and closed producing an overall reduction in average performance across trials.

Comparison of the model with human performance in Experiment 2 for six targets in the two conditions shown in the legend. For the data indicated by grey traces, targets were clustered into two groups, separated by about ms.

As shown in Figure 12 , participants in the same two conditions gave results similar to the model's with the exception that T4 accuracy the first target of the second cluster is quite low in the two cluster condition.

This result suggests that processing of the first cluster of targets is protracted and the T4, arriving ms after the T3, is still within an attentional blink induced by the first episode.

In the model, a parameter corresponding to the rate of WM encoding determines the duration of the blink and this parameter value does not capture the full extent of the blink duration in this case.

As in Experiments 1 and 1a, overall accuracy in the clustered presentation is substantially superior to that of the interleaved target presentation.

In the eSTST model, the sustained reduction in performance for T2-T6 in the interleaved condition is essentially the superposition of multiple attentional blinks at different lags in different trials.

In contrast, when targets are presented more closely in time i. This difference can be quantified by comparing performance on targets T2 through T6 as a function of whether the preceding target was seen or missed: p T n T n-1 and p T n!

T n These paired measurements are shown for simulations and human data in Figure The three way interaction was not significant. Therefore the impairment due to seeing the T n-1 target was greater in the interleaved condition and this impairment was not dependent on target position.

Encoding of each target as a function of whether the previous target was seen or missed in the two conditions in simulation and in the results of Experiment 2.

This analysis shows that the model correctly predicts the dynamics of encoding targets in the two presentations. In the interleaved condition, perception of each target impairs report of the following item, and this does not occur as strongly when the targets are clustered together.

This reflects weak interference between multiple items within an episode, an effect that we see as distinct from the attentional blink.

A supplemental section, available online, illustrates the results of conditional analyses of the data from experiments 1 2 and 3 for trials in which T1 was reported correctly, alongside simulations of those conditional analyses.

This suggests that the gap between the two episodes was not long enough, and that subjects were still encoding the first episode when the second episode began.

As the two episodes were ms apart, this explanation would imply that attentional blinks produced by episodes containing several targets last considerably longer than blinks produced by single targets.

The results of this experiment, shown in Figure 14 alongside the simulated equivalent, agree with the prediction that some of the impaired accuracy of the first target in the second episode in Experiment 2 was a result of an interval between the episodes that was too short.

Finding this difference in accuracy despite the fact that the blink induced by the first episode had recovered suggests the influence of working memory capacity, an issue we focus on in the following section.

Experiment 2a replicates the general finding of Experiment 2, but adds three extra distractors between the two sets of targets in the clustered condition.

The targets which are the least often reported, in both data and simulation, arrived just after the double distractors positions 2, 4 and 6. This pattern suggests that the longer gap between targets allows greater suppression of attention, thus reducing performance on the following target.

This final experiment explores the boundary condition of the termination of an attentional episode. The eSTST model is likewise temporal, and it predicts that the continuation of an attentional episode is determined by the temporal continuity of target spacing.

Distractors can play a helpful role in delineating the end of an episode, but they should not be necessary. In this experiment a T4 is presented following a cluster of three targets, and they are separated by a blank gap rather than by distractors.

These results demonstrate that episodic changes in attention occur in the absence of distractors before and after the cluster of targets.

According to the eSTST model, the necessary condition for producing an attentional blink is a sufficiently long temporal gap between the final target in a sequence and the next target.

However, this blink will be substantially weaker in magnitude if no intervening distractors are present see experiment 3 of Olivers et al Four letters were presented one after the other at the center of the screen for ms each, without distractor items.

A backward mask was shown after the fourth letter. Participants saw a fixation cross for milliseconds, followed at a randomly chosen interval from ms to ms by three sequential letters for ms each.

The fourth letter was presented from 1 to 7 positions after the first three targets as illustrated in Figure 15 and was followed by a mask composed of an symbol superimposed on top of a symbol for ms.

This mask was used because it is effective as a trailing mask, and also because it is not an easily reportable character that subjects might inadvertently encode as a potential target.

No other stimuli were presented, until the response screen appeared ms after the fourth letter. The seven conditions used in Experiment 3, varying target clustering and SOA independently.

Figure 16 illustrates the predictions of the model when T4 is presented at various lags from T3 without any intervening distractors.

Note that in the simulation, T1 performance is better than T2 performance, unlike previous simulations in this paper. The reason for this difference, as explained by the eSTST model Wyble et al , is that Experiment 3 has no distractors prior to T1.

To simulate unselective processing in the model, the delay of attentional deployment is reduced from 40ms to 10ms see Wyble et al , which gives the T1 a competitive advantage over T2 rather than vice versa.

Experiment 3 measures the attentional blink created by processing of a 3 target episode without intervening distractors. In the simulation, T4 performance remains relatively lower than T1, even at lag 7 after recovery from the blink.

This is due to simulation of the more potent perceptual mask presented after T4 compared with the T1 which was masked by another letter i.

We simulate this enhanced masking by reducing the overall strength of the T4 representation. The results of the experiment are shown in Figure 16 , showing T1-T4 performance for the 7 lag conditions of T4.

T1 and T2 did not differ in any systematic or predicted way across the 7 lag conditions. This is expected given that at lag1, T3 was masked by T4, but at longer lags it was unmasked.

Thus, we obtained an attentional blink at lag 2 that recovered gradually over the course of hundreds of milliseconds despite the lack of distractors between the preceding targets and the blinked target.

These results chart the onset and recovery of a blink following a three target episode in the absence of any distractors, apart from the trailing mask of the T4 which is necessary to observe the blink.

This result supports the findings of Nieuwenstein, et al. The eSTST model predicts that a blank temporal gap initiates an attentional blink since it provides a period of time during which inhibitory control c.

Figure 2 has an opportunity to win the competition for control of attention. As a result, T1, T2 and T3 enter the encoding process as a single episode, and T4 encoding is delayed while the first three targets are encoded.

Because T4 is strongly masked, the delay of encoding at short lags results in lower accuracy. Another important facet of this result is that we observed an attentional blink following a blank gap for a T4 that was presented for ms.

In Nieuwenstein et al , an attentional blink was not observed for a ms T2 following a single target. The model suggests that this effect is obtained because a cluster of three targets are encoded simultaneously, producing a lengthier suppression of attention than does a single target.

The fact that three targets produce a measureable blink for a ms target lends further support to the theory that multiple targets presented in a single cluster are encoded simultaneously.

In RSVP target sequences containing three or more sequential targets followed by distractors, performance begins to degrade as the sequence progresses.

However, the eSTST model offers a different explanation: as additional targets are added to an episode, earlier targets are still being encoded, which slightly reduces the probability of encoding the new targets.

This encoding difficulty stems from two sources. During encoding, simultaneously active items weakly interfere with one another directly at the type layer the lateral inhibitory connections in the Types layer in Figure 4.

This interference effect is weak however, and is not capable of causing the attentional blink. Inhibition of attention due to encoding the inhibition of the blaster in Figure 4 grows stronger as more items are being encoded.

This inhibition can prevent a particularly weak target from keeping the attentional gate open, thereby reducing the proportion of targets which are encoded in positions 3 and 4 of an episode.

Both of these effects reduce performance on later targets within an episode and these effects are relieved when there is a gap between targets that allows the encoding process to run to completion.

This facet of the model leads to a specific prediction that we evaluate by revisiting data from experiments 1, 2, and 3.

To evaluate this prediction, we consider the comparison between performance in the three conditions illustrated in Table 1 , all of which are different arrangements of targets presented at ms SOA.

Thus, it seems that for a string of targets presented at RSVP speed, there is an accruing interference effect that is better captured by the eSTST model than by a working memory storage capacity limit.

For another example of this recovery, consider the results of Experiment 3. In accord with the prediction of the eSTST model, performance on the T4 at lag 1 is worse than T4 performance at lag 7.

Thus, the impairment of T4 at lag 1 could not have been due solely to a hard limit on working memory. In fact, at lag 7, not only is T4 performance improved relative to lag1, but T3 performance is markedly improved as well, which contradicts the explanation offered by overall working memory capacity.

It should be emphasized that these experiments do demonstrate some form of capacity limitation. This is most clearly evident in experiment 2a in which the second episode has apparently escaped the blink, yet its overall accuracy is significantly worse than report of the first episode.

The eSTST model, which has no capacity limit, fails to simulate this difference. Adding a capacity limit to the model is a potential avenue for exploration, but it is not yet clear how to represent such capacity.

Is visual attention episodic in the way described by the eSTST model? The present study confirms key predictions of the model, which suggests that the competitive interplay between working memory encoding and attentional selection results in a visual mechanism that is responsive to the temporal structure of its input.

In particular, the data demonstrate that participants are able to report more RSVP targets when presented in clusters, and the model suggests that this mechanism serves to encode temporally proximal information within a single episode.

In the model, a temporal gap between two targets of ms or longer produces an effect whereby the later target is encoded in a subsequent episode, and the consequent suppression of attention produces an attentional blink.

The ability of a stimulus to enter working memory is significantly compromised during this period, especially if the stimulus is briefly presented.

The duration of this window of suppression can be sufficiently long e. In all of these cases, apparent lapses in attention may occur not just from spatial capture to an inappropriate location, but from the temporal structure of events creating periods of inattention.

These predictions illustrate several properties of attentional episodes. First, for all five of the experiments overall performance is superior for targets presented in clusters in comparison to conditions of interleaved distractors.

Next, prediction three illustrates that while targets presented in clusters are reported more often, this enhanced report comes at a cost of temporal order information, even when TOA is held constant.

Experiments 2 and 2a demonstrated that two clusters can be encoded within a single trial, each of which has a similar pattern of performance that peaks at its second target.

Furthermore, performance for a given target within a cluster is not strongly affected by successful report of a previous target, unlike the case when targets are separated by distractors.

The boundary condition defining the end of an episode seems to hinge on a ms temporal gap between target onsets rather than the presence of post-target distractors.

This is suggested by two findings. First, in prediction two, it was found that distractors were insufficient to produce an AB if they were too brief.

Second, in prediction six, an attentional blink is observed without the presence of intervening distractors. Therefore the data exhibit an attentional blink without the presence of post target distractors cf.

Nieuwenstein et al. This question helps to define the limitations and capabilities of our ability to perceive multiple stimuli in rapid succession.

On the other hand, selection based accounts, such as the temporary loss of control Di Lollo et al. The eSTST model addresses this debate by illustrating how both attentional selection and limited resources interact within the same framework.

A weak form of interference i. These effects are produced by distinct mechanisms within the model. Furthermore, it is clearly the case that there is a limit on the rate at which tokenized representations of stimuli can be perceived, even when identification is not required Garner The model captures this interference between neighboring items with the inhibitory connections between Type nodes see figure 4.

As a further demonstration of this weak interference, a supplemental section is available online, which illustrates anayses of experiments 1, 2 and 3 conditional on report of T1 alongside simulations generated from the model.

To explain these effects, the model requires an attentional selection component. So while the simulation of limited resources do play an important role in allowing the model to replicate the complete pattern of data as described in the preceding paragraph, such limitations are not the cause of the attentional blink.

In the latter condition, report of each item is strongly diminished by the suppression of attention whenever the prior target is successfully encoded.

In agreement with these results, another experiment has demonstrated that inter-target interference can be dissociated from the effects of attentional selection by varying the SOA between two targets Olivers, et al.

In Press. Episodes, as simulated by the eSTST model, are not a memory structure. Rather, episodes refer to the temporal windows during which information is admitted for further processing and storage into memory.

Thus, when multiple items are successfully admitted during a single episode, they are not combined into a single representation, but instead form a series of sequentially organized representations of the individual target items.

The stored sequence, as noted, is sometimes in a different order than the input order. A second source of evidence is that subjects do recover a significant amount of order information from an uninterrupted four target sequence.

Figure 17 is reprinted from Wyble, et al a , and illustrates both simulated results and empirical data from the temporal order of 4 letter targets in an RSVP stream presented as TTTT.

These data represent the set of trials in which both the model and subjects reported all four items correctly. Clearly, some, but not all, of the order information is preserved for uninterrupted target sequences.

The overall pattern resembles perturbation Estes in which order report exhibits a tendency for individual targets to switch positions with their immediate neighbors.

Targets on either end of the episode are correctly positioned more often than targets in between the endpoints. The pattern of temporal positions for both the model and the human data when four targets are presented in a single cluster within an RSVP stream.

These graphs illustrate a pattern of migration errors between adjacent items in both the data and the eSTST model that are characteristic of perturbation models such as Estes This figure is reprinted from Wyble et al Research exploring the spatial and temporal aspects of attention typically find that presenting a salient cue produces a brief enhancement of processing at that particular location that is time locked to the onset of the cue.

It is possible that this spatiotemporal form of attentional deployment is mediated by the same episodic attentional control as we describe here for RSVP experiments with no spatial component cf.

Numerous computational models have used an attentional function with similar temporal characteristics to explain lag-1 sparing in the attentional blink Nieuwenhuis et al.

Further exploration of this idea awaits experiments that present two or more targets at different locations to determine how attentional episodes bridge or perhaps migrate between different spatial locations in response to the onset of salient or task relevant information.

A similar effect is characteristic of the attentional episodes described here, although it is not yet clear how much these various effects have in common.

Memory experiments typically present many to-be-remembered stimuli for as long as one second each, ensuring that each one is fully perceived by the subject.

The behavioral results tend to produce a U shaped function i. Despite this difference in primacy between RSVP and the much slower form of presentation used in memory experiments, there is commonality in the way that temporal clustering can enhance performance.

The eSTST model simulates an episodic form of attention, and experimental evidence supports its predictions both qualitatively and quantitatively.

These data illustrate the finding that if task relevant visual stimuli are presented in tight clusters, participants reliably report more of them than when they are interleaved with distractors.

This effect is suggested to be due to an attentional mechanism that is best suited to processing stimuli presented in clusters no more than three items in length, and separated by gaps of several hundred milliseconds or more.

In more natural viewing conditions, an analog of these episodes may be continuous sequence of attended visual input: the hand gesture of a magician, the kick of a ball, a passing vehicle, the approach of a person, or the reading of a grammatical unit of text, such as a clause.

If this hypothesis is correct, brief periods of attentional suppression occur between episodes, passing unnoticed during natural viewing because most perceptible real world objects persist for periods of at least several hundred milliseconds.

However, this suppression produces an attentional blink in a controlled laboratory setting in which targets are masked after abnormally brief durations such as 50ms or ms.

Under natural viewing conditions, when stimuli are available in the environment for several hundred milliseconds per fixation, this suppression of attention may not result in the loss of much information, yet still provide an important cognitive benefit in punctuating the endpoints of temporal units of visual input.

Electronic mail may be sent to moc. Publisher's Disclaimer: The following manuscript is the final accepted manuscript.

It has not been subjected to the final copyediting, fact-checking, and proofreading required for formal publication.

It is not the definitive, publisher-authenticated version. The American Psychological Association and its Council of Editors disclaim any responsibility or liabilities for errors or omissions of this manuscript version, any version derived from this manuscript by NIH, or other third parties.

The published version is available at www. In their terminology, episodes were the quantal, discrete shifts of attention from one mode of processing i.

The terminological differences can be reconciled by understanding that our definition of an episode refers only to periods of time when the attentional gate is open and encoding is therefore facilitated.

In the eSTST model, a token always represents 1 item. Read article at publisher's site DOI : Front Hum Neurosci , , 10 Apr Cited by: 0 articles PMID: Schneegans S , Bays PM.

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This attentional deployment enhances the strength of target representations and allows active targets to activate their corresponding type nodes.

Active type nodes trigger an encoding process which ultimately results in a tokenized representation of the target being stored in the binding pool.

Multiple targets can be encoded in this way, and the order or token allocation corresponds to the perceived order of the targets.

Encoding also provides top down suppression of attention, and the competition between the bottom up and top down pressures on attention drives the episodic behavior of the model.

Processing in the model depicted in Figure 4 proceeds generally from bottom to top. At the bottom of the figure, input nodes extract type information i.

When a visual stimulus is presented to the model, it activates a corresponding input node. These input nodes are filtered by a passive task demand which is configured by the task requirements to suppress distractors and allow targets to pass into the type layer of the model.

Targets nodes which have been activated excite the transient attention node referred to here as the blaster. When this attention node crosses its threshold, the node provides a multiplicative gain across the entire set of input nodes, which boosts their ability to activate type nodes.

When a type node is sufficiently activated by input, it triggers an encoding process, which takes several hundred milliseconds to complete.

This feedback is important because it allows the activation of the type node to outlast the duration of the stimulus at the input layer, persisting in fact until encoding is complete.

During this period of encoding, activation accrues steadily across a population of trace nodes in the binding pool and the token layer.

When one of these nodes crosses threshold in the token layer, encoding is complete and the recurrent circuit between the type node, the binding pool and the token layer collapses, leaving just the stored representation of the token.

This encoding process is described in greater detail below. Critically, activation of the type node is required only during encoding into memory, and not for maintenance of that information.

This detail is important because it would be difficult to encode a repetition of the same item at any point within a single trial if the type node was used to store the memory.

However it is generally easy to encode and report two instances of the same target if they are sufficiently far apart in time see Wyble et al a for a discussion of repetition blindness effects and how they relate to the eSTST model.

As regards working memory capacity limits, in the following simulations, it is assumed that there are sufficient tokens to encode all of the targets presented in a trial.

To simulate the inherent variance between different stimuli, targets are activated with different strength values from one trial to the next.

When simulating an experiment containing multiple targets, target strength values are chosen independently and systematically for each different target.

Thus, to simulate 4 targets for each of 11 different target strengths, simulations are run for each of the 14, e. On presentation of a single target item, a chain of events occurs over a period of approximately simulated milliseconds that culminates in the encoding of the stimulus into memory as a tokenized representation.

Figure 5 depicts these events as activation traces of nodes within the model starting from input at the bottom and progressing upwards to the encoding of a token.

First, within an RSVP stream, depicted as a series of ovals, the target representation is activated at the input layer and excites attention.

Activation of the type node initiates encoding of a token. While the token is being formed in WM, attention is suppressed, producing an attentional blink as seen at c.

Finally, referring to d , the token has reached sufficient strength and encoding is complete; the type node activation is freed to return to baseline and the suppression of attention is ended.

Simulation of a single trial containing the sequence DTDDDD presented at ms per item as shown by the ovals at the bottom of the figure.

The four horizontal traces above these ovals depict time aligned traces of the activation level nodes at different levels of processing.

In each trace, vertical fluctuations indicate excitation or inhibition of simulated neural activity levels relative to the resting baseline. These nodes produce no output unless activation exceeds that threshold.

The sequence of events is such that a target first triggers attention a , which activates a type node and begins the process of encoding b.

Ongoing encoding suppresses attention c and ultimately results in a stored representation of the target at which point the type node activation falls back to baseline d.

Refer to the text for a more detailed description of this encoding process. Figure 6a illustrates the encoding of two targets within a single episode.

In the top panel, two targets are presented in immediate succession at an SOA of ms, producing lag 1 sparing.

Here, the T2 arrives soon enough to hold the attentional gate open, extending the episode to include both T1 and T2. Note that encoding of the two types overlaps.

When encoding of each target is completed--first T1, then Tactivation returns to baseline. In this example, the two items were encoded in the correct order, but during sparing it can be the case that T2 completes first, producing a temporal order error, a point we return to later.

Time course of the encoding of two sequential targets. Each panel depicts a simulation of the presentation of two targets, along with activation traces of attention and the type nodes corresponding to T1 and T2.

In panel a is depicted a lag 1 trial. Attention triggered by the first target boosts processing of the second target also, such that both targets are encoded.

The moment at which encoding is complete is indicated by the arrow in the upper right, and corresponds to the point at which the tokens not shown cross threshold.

The temporal order in which the activation of the type nodes ends corresponds to the perceived order of the two targets T1 then T2.

In panel b , two targets are separated by a ms distractor. During this gap, attention is suppressed by T1 encoding so as to defer the processing of T2 into a second episode.

However, because the T2 is quickly masked by a following distractor, this deferral of T2 processing produces an attentional blink that swallows the T2.

In the absence of a mask, the T2 would be encoded after T1 encoding was complete. Multiple items processed within a single episode interfere weakly with one another through lateral inhibitory projections.

This interference has a much larger influence on behavior when three or four targets are in the same episode, as will be seen below. Signs of this interference can be seen in figure 6a , as the T2 activation trace rises slightly at the end of T1 encoding.

In the bottom panel Figure 6b , the T2 arrives at lag 2 following an intervening distractor. Here, the T2 arrives too late to hold the attentional gate open and thus has missed the opportunity to join the episode initiated by the T1.

In a more natural visual context, the T2 representation might persist in early visual areas and begin a second episode once the prior episode has been encoded.

However, in RSVP, the backward masking from the following distractor wipes out the trace of the T2 so quickly that it can fail to be encoded during the delay.

Capacity limits of two types are often discussed in experimental paradigms involving rapidly presented stimuli. The first of these is a limitation on the pool of available processing resources , which limits the rate at which information can be encoded into memory.

A second putative capacity limit is on the overall amount of information that can exist within a working memory store. Both of these limitations can reduce the overall number of items reported on a given trial.

Presenting too many targets within a short time window can make it impossible to encode all of the items presented within a trial, and trying to hold too many items in a memory store at the same time can likewise limit the number of reported items Davelaar However, in a model such as eSTST, which maintains a clear distinction between encoding of a target, and the subsequent maintenance of that target in a memory store, it is possible to separately consider limitations on processing and storage.

With regards to processing and storage capacity limits, the eSTST model has a weak form of the former, and none of the latter. Lateral inhibition in the type layer, which can be seen in figure 4 , causes each active type node to weakly suppress every other type node, thereby simulating the small but consistent cost of encoding multiple items at the same time.

However this weak interference does not cause the major portion of the attentional blink, a point we return to at length in the general discussion.

As to the second type of capacity limit, the eSTST model does not simulate an overall limit on the number of targets in working memory. Close inspection of the data from the present experiments does not suggest the involvement of this type of capacity limit in these experiments, a point we discuss in the final prediction of the paper.

Here, the eSTST model is used to generate seven predictions that explore the boundary conditions of what constitutes the break between attentional episodes and also the costs and benefits of allowing multiple items access to working memory during a single attentional episode.

These predictions are provided by simulating new experimental conditions with the same set of parameters used in the original publication of the model Wyble et al , with only the addition of new type and token nodes to allow up to 6 targets to be presented to the model.

Three main experiments are used to evaluate these predictions. What are the benefits and costs of encoding multiple items that are selected for working memory encoding during a single attentional episode?

In this experiment, subjects viewed four targets in different configurations. The model predicts that it is the temporal spacing of new target items that is most critical in sustaining an attentional episode.

If targets are presented within about ms of each other, attention can be sustained even during the presence of intervening distractors.

In the model, interleaving a distractor between two targets delays the encoding of the latter target, and thereby increases the accuracy of reporting the sequential order of the two targets.

The ten participants were volunteers from the MIT community between the ages of 18—35 who were paid to participate in the experiment, which took approximately 30 minutes.

All reported corrected or normal vision. The experiment was programmed using Matlab 5. An RSVP stream was presented centrally at the location of a fixation cross.

Black digits 2,3,4,5,6,7,8,9 in 70 point Arial were used as distractors. Stimuli were approximately 1. These stimuli comprised RSVP streams presented at either 53 or ms per item with no interstimulus interval.

Each trial consisted of an RSVP stream, which included four single-letter targets none repeated among digit distractors. There were two blocks of randomly mixed trial types.

Each trial began with a fixation cross for 1 second and a sequence of 7 to 12 distractors on the slow ms trials and double that number on the fast 53 ms trials, so that the average time before the first target was equated for the slow and fast RSVP rates.

At least 5 distractors followed the last target. Subjects were instructed that they would see four letters and should remember them for entry at the end of the trial.

They were told that they were free to report the targets if they were not sure, but not to guess randomly. Report of temporal order of the targets was implicit in the response prompt provided to subjects, which appeared in a sequence of characters from left to right as subjects type in their response.

We intentionally avoided giving explicit emphasis to order information in the instructions out of concern that such emphasis would come at the expense of item information.

Subjects were allowed to correct their input string with backspace while entering it, and were given feedback as to the letters they saw and their correct order.

Responses were considered correct if subjects reported the correct identity, without regard to correct order although we did analyze the pattern of order errors for reported targets.

The predictions of the eSTST model for each of the four conditions were calculated. As the model uses time steps of 10 ms, presentation was simulated at 50 ms and ms per item rates.

In the simulation, the input strengths of the targets are varied over trials and performance is averaged over these trials to derive behavioral accuracy curves.

This strength value represents the processing difficulty of each target, which is assumed to vary due to differences in backward masking strength produced by the interaction of each target and the immediately following item, as well as intrinsic differences in the processing of each target, due to such factors as familiarity and orthographical or phonological similarity with other members of the target set, etc.

The model does not behave in the same way on every trial due to differences in item strength, but in the figure we have used a strength value in the middle of the input range.

Simulation of a single trial in each of the four conditions of Experiment 1. Traces reflect activation of 4 type nodes T1,T2,T3 and T4 in addition to the activation level of attention.

In the top panels, four consecutive targets are encoded at presentation rates of both ms and 50ms per item. In the bottom panels distractors are presented between the targets.

In the lower left panel, distractors separate the targets for a sufficient amount of time that two distinct episodes are formed by attention, at the loss of T2 and T4.

In contrast, at 50ms per item shown at the bottom right, the distractors are short enough that only one episode is triggered, but the weaker representations of the faster targets results in the loss of T4.

Target strength was fixed at 0. As previously described in Wyble et al. Attention triggered by the T1 spills over to the following item and amplifies the representation of T2, which in turn sustains the level of attention.

This dynamic continues for T3 and T4, although the accumulating interference between simultaneously active type nodes produces progressively weaker encoding.

In Figure 7 , for the trial in the upper left hand corner, all four targets are correctly encoded, and in the correct order.

When targets of the same input strength are presented for the same ms duration, but are now separated by distractors TDTDTDTD , the dynamics of attention are remarkably different.

Here, under the suppression from T1 encoding, the attentional gate is closed during the interval between the first two targets.

Attention is thus suppressed when T2 arrives and remains so until T1 encoding is completed. In the illustrated trial, T1 encoding is complete after approximately ms, freeing up the attentional gate in time for T3 to be encoded, which produces another period of attentional suppression that keeps the T4 from being encoded.

In this example trial bottom left panel of Figure 7 , attention has segmented the input into two episodes; successfully encoding T1 and T3 without overlap, but at the cost of missing T2 and T4 entirely.

Note that on other trials, using a different set of strength values for the targets, the predicted pattern of which targets are encoded would be different than this simulation.

In the simulated TTTT trial, all four targets are encoded, although in this particular example, the order is incorrect: T2,T3,T1,T4 as can be seen in the relative times at which the type node activations return to baseline.

For TDTDTDT trials, even though there are intervening distractors, the T2 arrives rapidly enough to benefit from the attention elicited by T1, and bolsters the deployment of attention against the suppression produced by encoding.

In this example trial but not in all cases , the building interference from the ongoing encoding of T1,T2 and T3 results in the episode being concluded prematurely and T4 is lost, producing the encoded sequence: T2, T1, T3.

In other trials, a stronger input strength for T4 would allow it to be encoded along with the preceding targets. An experimental block that uses randomly selected targets and distractors can be simulated by averaging over single trials that vary in their strength values.

For the following simulations, the strength of input values covered the same range as in Wyble et al a. Strength of an individual target varied in steps of.

The overall pattern of simulated accuracy in the four experimental conditions is depicted in Figure 8a—b , alongside the results of human subjects performing the same conditions as in Figure 8c—d.

Focussed analyses address each of the predictions. Comparison of simulated model output and human data in the four conditions of Experiment 1.

This ability to process multiple targets simultaneously with only a modest amount of interference is central to eSTST. Because attention is strongly engaged by a string of targets, performance is actually better when targets are presented closely together in time.

This is visible in the simulations shown in Figure 7 by comparing the top left panel to the bottom left panel. The human data are entirely consistent with an enhanced ability to process multiple targets arriving in immediate succession.

A highly reliable finding is that average accuracy was better for targets presented in a temporal cluster as compared to targets distributed over a longer time span.

As subjects are doing better on trials in which they are given less total time to process targets, it seems clear that resource limitations cannot be the primary cause of encoding failures in these trials.

There is, however, a potential confound of subject expectancy effects produced by mixing the slow and fast trials together and we address this problem in Experiment 1a below.

In the simulation, the presence of interleaved distractors at the 50 ms presentation rate does not produce an episodic division.

This comparison can be seen in the simulations shown in Figure 7 by comparing the top left panel to the bottom right panel.

In both cases there is a single attentional window, as can be seen by the trace of attentional activation.

In both of these conditions, targets appear at ms intervals, so the temporal arrangement of targets is preserved but the presence of intervening distractors is varied.

Figure 9 depicts the comparison between these conditions in the human data. Comparison of simulation and human data between two conditions with equivalent spacing of target onsets.

Simulated SOAs were 50ms and ms. The model predicts that temporal information will be enhanced for two targets if attention segments them into separate episodes.

Specifically, on trials in which two given targets were successfully encoded, their reported order will be more accurate if those targets were separated by a distractor, while holding the temporal interval between them constant.

Figure 10 illustrates why the model has greater difficulty encoding order correctly when presented with TTT than TDT; in the former case, all three targets are encoded concurrently while in the latter, encoding of the second target begins when encoding of the first target is complete.

The strength values of the targets are the same in the two simulations, but the middle target of TTT allows attention to be sustained, creating an episode that includes all three targets.

In simulation, three contiguous targets are encoded as one episode a and targets presented as noncontiguous are divided into two episodes b. The only difference between these conditions is the presence of an intervening target in panel a , which allows attention to be sustained.

The cost of combining multiple targets into a single episode can be observed as a temporal order error in panel a. T3 has greater strength and completes encoding before the T1 so that the encoded order of the targets is T3,T1, T2.

In b , T2 has exactly the same strength and relative TOA as the T3 in a but attentional suppression forces its encoding to wait until T1 is finished.

In this replication, ten participants saw an equal number of trials in condensed and distributed presentations in two mixed blocks of trials.

The results replicated the data of Experiment 1 for the slow trials in every respect as shown in Figure Comparison of accuracy between equivalent conditions in Experiment 1 and Experiment 1a.

How readily can subjects encode two episodes and how does encoding of a prior target affect encoding of the current one? In this experiment, we asked subjects to report 6 targets.

All items were presented for ms. Again, the simulations were run with the original parameters of the model. In clustered presentation, performance averaged over both clusters of targets should be superior to the interleaved condition; subjects should be capable of encoding two episodes provided they are separated by an interval that is sufficiently long to allow the encoding of items acquired during the first episode to be completed.

The model predicts that attention functions differently during clustered vs interleaved target presentation; with clusters, reporting target T n-1 will only weakly affect report of target T n, because the close temporal proximity allows attention to be sustained across an entire episode.

With interleaved distractors, successful report of each target T n-1 will have a potent detrimental effect on the report of the following item T n, even though the two targets are now further apart in time, because successful encoding of T n-1 will have suppressed attention to T n.

The method was similar to that of Experiment 1 with the exceptions described below. Fourteen participants were drawn from the same subject pool as that of Experiment 1.

All stimuli were presented for ms. There were two trial types, intermixed randomly, in two identical blocks of trials.

In each case, the temporal interval between the onset of the first and last targets was ms in the simulation, ms. As in Experiment 1, the target sequences were preceded and followed by additional distractors.

In the 6 target simulations, strength of an individual target varied in steps of. In the results of the model simulation Figure 12 , report accuracy is superior for the clustered target presentation.

Within each cluster, the close spacing of targets sustains the deployment of attention and targets are well encoded. The separation between the clusters permits an episodic break, which allows processing of the first episode to be completed before the second begins, producing excellent performance for all six items.

When six targets are evenly distributed over the same temporal interval 1, ms , the simulated pattern of accuracy is distinctly different; performance decreases sharply for the second target and remains well below T1 levels until the end of the target sequence.

As with Experiment 1, the ms TOA between targets does not permit an attentional episode to be sustained and the attentional gate is intermittently opened and closed producing an overall reduction in average performance across trials.

Comparison of the model with human performance in Experiment 2 for six targets in the two conditions shown in the legend. For the data indicated by grey traces, targets were clustered into two groups, separated by about ms.

As shown in Figure 12 , participants in the same two conditions gave results similar to the model's with the exception that T4 accuracy the first target of the second cluster is quite low in the two cluster condition.

This result suggests that processing of the first cluster of targets is protracted and the T4, arriving ms after the T3, is still within an attentional blink induced by the first episode.

In the model, a parameter corresponding to the rate of WM encoding determines the duration of the blink and this parameter value does not capture the full extent of the blink duration in this case.

As in Experiments 1 and 1a, overall accuracy in the clustered presentation is substantially superior to that of the interleaved target presentation.

In the eSTST model, the sustained reduction in performance for T2-T6 in the interleaved condition is essentially the superposition of multiple attentional blinks at different lags in different trials.

In contrast, when targets are presented more closely in time i. This difference can be quantified by comparing performance on targets T2 through T6 as a function of whether the preceding target was seen or missed: p T n T n-1 and p T n!

T n These paired measurements are shown for simulations and human data in Figure The three way interaction was not significant.

Therefore the impairment due to seeing the T n-1 target was greater in the interleaved condition and this impairment was not dependent on target position.

Encoding of each target as a function of whether the previous target was seen or missed in the two conditions in simulation and in the results of Experiment 2.

This analysis shows that the model correctly predicts the dynamics of encoding targets in the two presentations. In the interleaved condition, perception of each target impairs report of the following item, and this does not occur as strongly when the targets are clustered together.

This reflects weak interference between multiple items within an episode, an effect that we see as distinct from the attentional blink.

A supplemental section, available online, illustrates the results of conditional analyses of the data from experiments 1 2 and 3 for trials in which T1 was reported correctly, alongside simulations of those conditional analyses.

This suggests that the gap between the two episodes was not long enough, and that subjects were still encoding the first episode when the second episode began.

As the two episodes were ms apart, this explanation would imply that attentional blinks produced by episodes containing several targets last considerably longer than blinks produced by single targets.

The results of this experiment, shown in Figure 14 alongside the simulated equivalent, agree with the prediction that some of the impaired accuracy of the first target in the second episode in Experiment 2 was a result of an interval between the episodes that was too short.

Finding this difference in accuracy despite the fact that the blink induced by the first episode had recovered suggests the influence of working memory capacity, an issue we focus on in the following section.

Experiment 2a replicates the general finding of Experiment 2, but adds three extra distractors between the two sets of targets in the clustered condition.

The targets which are the least often reported, in both data and simulation, arrived just after the double distractors positions 2, 4 and 6.

This pattern suggests that the longer gap between targets allows greater suppression of attention, thus reducing performance on the following target.

This final experiment explores the boundary condition of the termination of an attentional episode. The eSTST model is likewise temporal, and it predicts that the continuation of an attentional episode is determined by the temporal continuity of target spacing.

Distractors can play a helpful role in delineating the end of an episode, but they should not be necessary.

In this experiment a T4 is presented following a cluster of three targets, and they are separated by a blank gap rather than by distractors.

These results demonstrate that episodic changes in attention occur in the absence of distractors before and after the cluster of targets.

According to the eSTST model, the necessary condition for producing an attentional blink is a sufficiently long temporal gap between the final target in a sequence and the next target.

However, this blink will be substantially weaker in magnitude if no intervening distractors are present see experiment 3 of Olivers et al Four letters were presented one after the other at the center of the screen for ms each, without distractor items.

A backward mask was shown after the fourth letter. Participants saw a fixation cross for milliseconds, followed at a randomly chosen interval from ms to ms by three sequential letters for ms each.

The fourth letter was presented from 1 to 7 positions after the first three targets as illustrated in Figure 15 and was followed by a mask composed of an symbol superimposed on top of a symbol for ms.

This mask was used because it is effective as a trailing mask, and also because it is not an easily reportable character that subjects might inadvertently encode as a potential target.

No other stimuli were presented, until the response screen appeared ms after the fourth letter. The seven conditions used in Experiment 3, varying target clustering and SOA independently.

Figure 16 illustrates the predictions of the model when T4 is presented at various lags from T3 without any intervening distractors.

Note that in the simulation, T1 performance is better than T2 performance, unlike previous simulations in this paper. The reason for this difference, as explained by the eSTST model Wyble et al , is that Experiment 3 has no distractors prior to T1.

To simulate unselective processing in the model, the delay of attentional deployment is reduced from 40ms to 10ms see Wyble et al , which gives the T1 a competitive advantage over T2 rather than vice versa.

Experiment 3 measures the attentional blink created by processing of a 3 target episode without intervening distractors.

In the simulation, T4 performance remains relatively lower than T1, even at lag 7 after recovery from the blink.

This is due to simulation of the more potent perceptual mask presented after T4 compared with the T1 which was masked by another letter i.

We simulate this enhanced masking by reducing the overall strength of the T4 representation. The results of the experiment are shown in Figure 16 , showing T1-T4 performance for the 7 lag conditions of T4.

T1 and T2 did not differ in any systematic or predicted way across the 7 lag conditions. This is expected given that at lag1, T3 was masked by T4, but at longer lags it was unmasked.

Thus, we obtained an attentional blink at lag 2 that recovered gradually over the course of hundreds of milliseconds despite the lack of distractors between the preceding targets and the blinked target.

These results chart the onset and recovery of a blink following a three target episode in the absence of any distractors, apart from the trailing mask of the T4 which is necessary to observe the blink.

This result supports the findings of Nieuwenstein, et al. The eSTST model predicts that a blank temporal gap initiates an attentional blink since it provides a period of time during which inhibitory control c.

Figure 2 has an opportunity to win the competition for control of attention. As a result, T1, T2 and T3 enter the encoding process as a single episode, and T4 encoding is delayed while the first three targets are encoded.

Because T4 is strongly masked, the delay of encoding at short lags results in lower accuracy. Another important facet of this result is that we observed an attentional blink following a blank gap for a T4 that was presented for ms.

In Nieuwenstein et al , an attentional blink was not observed for a ms T2 following a single target. The model suggests that this effect is obtained because a cluster of three targets are encoded simultaneously, producing a lengthier suppression of attention than does a single target.

The fact that three targets produce a measureable blink for a ms target lends further support to the theory that multiple targets presented in a single cluster are encoded simultaneously.

In RSVP target sequences containing three or more sequential targets followed by distractors, performance begins to degrade as the sequence progresses.

However, the eSTST model offers a different explanation: as additional targets are added to an episode, earlier targets are still being encoded, which slightly reduces the probability of encoding the new targets.

This encoding difficulty stems from two sources. During encoding, simultaneously active items weakly interfere with one another directly at the type layer the lateral inhibitory connections in the Types layer in Figure 4.

This interference effect is weak however, and is not capable of causing the attentional blink. Inhibition of attention due to encoding the inhibition of the blaster in Figure 4 grows stronger as more items are being encoded.

This inhibition can prevent a particularly weak target from keeping the attentional gate open, thereby reducing the proportion of targets which are encoded in positions 3 and 4 of an episode.

Both of these effects reduce performance on later targets within an episode and these effects are relieved when there is a gap between targets that allows the encoding process to run to completion.

This facet of the model leads to a specific prediction that we evaluate by revisiting data from experiments 1, 2, and 3. To evaluate this prediction, we consider the comparison between performance in the three conditions illustrated in Table 1 , all of which are different arrangements of targets presented at ms SOA.

Thus, it seems that for a string of targets presented at RSVP speed, there is an accruing interference effect that is better captured by the eSTST model than by a working memory storage capacity limit.

For another example of this recovery, consider the results of Experiment 3. In accord with the prediction of the eSTST model, performance on the T4 at lag 1 is worse than T4 performance at lag 7.

Thus, the impairment of T4 at lag 1 could not have been due solely to a hard limit on working memory. In fact, at lag 7, not only is T4 performance improved relative to lag1, but T3 performance is markedly improved as well, which contradicts the explanation offered by overall working memory capacity.

It should be emphasized that these experiments do demonstrate some form of capacity limitation. This is most clearly evident in experiment 2a in which the second episode has apparently escaped the blink, yet its overall accuracy is significantly worse than report of the first episode.

The eSTST model, which has no capacity limit, fails to simulate this difference. Adding a capacity limit to the model is a potential avenue for exploration, but it is not yet clear how to represent such capacity.

Is visual attention episodic in the way described by the eSTST model? The present study confirms key predictions of the model, which suggests that the competitive interplay between working memory encoding and attentional selection results in a visual mechanism that is responsive to the temporal structure of its input.

In particular, the data demonstrate that participants are able to report more RSVP targets when presented in clusters, and the model suggests that this mechanism serves to encode temporally proximal information within a single episode.

In the model, a temporal gap between two targets of ms or longer produces an effect whereby the later target is encoded in a subsequent episode, and the consequent suppression of attention produces an attentional blink.

The ability of a stimulus to enter working memory is significantly compromised during this period, especially if the stimulus is briefly presented.

The duration of this window of suppression can be sufficiently long e. In all of these cases, apparent lapses in attention may occur not just from spatial capture to an inappropriate location, but from the temporal structure of events creating periods of inattention.

These predictions illustrate several properties of attentional episodes. First, for all five of the experiments overall performance is superior for targets presented in clusters in comparison to conditions of interleaved distractors.

Next, prediction three illustrates that while targets presented in clusters are reported more often, this enhanced report comes at a cost of temporal order information, even when TOA is held constant.

Experiments 2 and 2a demonstrated that two clusters can be encoded within a single trial, each of which has a similar pattern of performance that peaks at its second target.

Furthermore, performance for a given target within a cluster is not strongly affected by successful report of a previous target, unlike the case when targets are separated by distractors.

The boundary condition defining the end of an episode seems to hinge on a ms temporal gap between target onsets rather than the presence of post-target distractors.

This is suggested by two findings. First, in prediction two, it was found that distractors were insufficient to produce an AB if they were too brief.

Second, in prediction six, an attentional blink is observed without the presence of intervening distractors.

Therefore the data exhibit an attentional blink without the presence of post target distractors cf.

Nieuwenstein et al. This question helps to define the limitations and capabilities of our ability to perceive multiple stimuli in rapid succession.

On the other hand, selection based accounts, such as the temporary loss of control Di Lollo et al. The eSTST model addresses this debate by illustrating how both attentional selection and limited resources interact within the same framework.

A weak form of interference i. These effects are produced by distinct mechanisms within the model. Furthermore, it is clearly the case that there is a limit on the rate at which tokenized representations of stimuli can be perceived, even when identification is not required Garner The model captures this interference between neighboring items with the inhibitory connections between Type nodes see figure 4.

As a further demonstration of this weak interference, a supplemental section is available online, which illustrates anayses of experiments 1, 2 and 3 conditional on report of T1 alongside simulations generated from the model.

To explain these effects, the model requires an attentional selection component. So while the simulation of limited resources do play an important role in allowing the model to replicate the complete pattern of data as described in the preceding paragraph, such limitations are not the cause of the attentional blink.

In the latter condition, report of each item is strongly diminished by the suppression of attention whenever the prior target is successfully encoded.

In agreement with these results, another experiment has demonstrated that inter-target interference can be dissociated from the effects of attentional selection by varying the SOA between two targets Olivers, et al.

In Press. Episodes, as simulated by the eSTST model, are not a memory structure. Rather, episodes refer to the temporal windows during which information is admitted for further processing and storage into memory.

Thus, when multiple items are successfully admitted during a single episode, they are not combined into a single representation, but instead form a series of sequentially organized representations of the individual target items.

The stored sequence, as noted, is sometimes in a different order than the input order. A second source of evidence is that subjects do recover a significant amount of order information from an uninterrupted four target sequence.

Figure 17 is reprinted from Wyble, et al a , and illustrates both simulated results and empirical data from the temporal order of 4 letter targets in an RSVP stream presented as TTTT.

These data represent the set of trials in which both the model and subjects reported all four items correctly. Clearly, some, but not all, of the order information is preserved for uninterrupted target sequences.

The overall pattern resembles perturbation Estes in which order report exhibits a tendency for individual targets to switch positions with their immediate neighbors.

Targets on either end of the episode are correctly positioned more often than targets in between the endpoints. The pattern of temporal positions for both the model and the human data when four targets are presented in a single cluster within an RSVP stream.

These graphs illustrate a pattern of migration errors between adjacent items in both the data and the eSTST model that are characteristic of perturbation models such as Estes This figure is reprinted from Wyble et al Research exploring the spatial and temporal aspects of attention typically find that presenting a salient cue produces a brief enhancement of processing at that particular location that is time locked to the onset of the cue.

It is possible that this spatiotemporal form of attentional deployment is mediated by the same episodic attentional control as we describe here for RSVP experiments with no spatial component cf.

During encoding, simultaneously active items weakly interfere with one Geile weiber große titten directly at the type layer the lateral inhibitory connections Tdtdtdt the Types layer in Figure 4. Affiliations 1 author 1. Processing in the model Asa akira is insatiable 3 in Figure 4 proceeds generally from bottom to top. Naughty nattys, in prediction six, an attentional blink is observed without the presence of intervening distractors. Crissy henderson, some, but not Dreier zwei männer eine frau, of the order information is preserved for uninterrupted Dyanna lauren videos sequences. In this Luisana lopilato nude, subjects viewed four targets in different configurations. As the two episodes were ms apart, this explanation would imply that attentional blinks produced by episodes containing several targets last considerably longer than blinks produced by single targets. Comparison of simulated model Sombra overwatch hentai and human Reni fleur tumblr in the four conditions Tiny little titties Experiment 1. In this example, the two items were encoded in the Parking lot porn order, but during sparing it can be the case that T2 completes Putzfrau gebumst, producing Tdtdtdt temporal order error, a point we return to later.