Irida Mance

Constant spread of feature-based attention across the visual field

Attending to a feature in one location can produce feature-specific modulation in a different location. This global feature-based attention effect has been demonstrated using two stimulus locations. Although the spread of feature-based attention is presumed to be constant across spatial locations, it has not been tested empirically. We examined the spread of feature-based attention by measuring attentional modulation of the motion aftereffect (MAE) at remote locations. Observers attended to one of two directions in a compound motion stimulus (adapter) and performed a speed-increment task. MAE was measured via a speed nulling procedure for a test stimulus at different distances from the adapter. In Experiment 1, the adapter was at fixation, while the test stimulus was located at different eccentricities. We also measured the magnitude of baseline MAE for each location in two control conditions that did not require feature-based selection necessitated by a compound stimulus. In Experiment 2, the adapter and test stimuli were all located in the periphery at the same eccentricity. Our results showed that attention induced MAE spread completely across the visual field, indicating a genuine global effect. These results add to our understanding of the deployment of feature-based attention and provide empirical constraints on theories of visual attention.

The contribution of attentional lapses to individual differences in visual working memory capacity

Attentional control and working memory capacity are important cognitive abilities that substantially vary between individuals. Although much is known about how attentional control and working memory capacity relate to each other and to constructs like fluid intelligence, little is known about how trial-by-trial fluctuations in attentional engagement impact trial-by-trial working memory performance. Here, we employ a novel whole-report memory task that allowed us to distinguish between varying levels of attentional engagement in humans performing a working memory task. By characterizing low-performance trials, we can distinguish between models in which working memory performance failures are caused by either (1) complete lapses of attention or (2) variations in attentional control. We found that performance failures increase with set-size and strongly predict working memory capacity. Performance variability was best modeled by an attentional control model of attention, not a lapse model. We examined neural signatures of performance failures by measuring EEG activity while participants performed the whole-report task. The number of items correctly recalled in the memory task was predicted by frontal theta power, with decreased frontal theta power associated with poor performance on the task. In addition, we found that poor performance was not explained by failures of sensory encoding; the P1/N1 response and ocular artifact rates were equivalent for high- and low-performance trials. In all, we propose that attentional lapses alone cannot explain individual differences in working memory performance. Instead, we find that graded fluctuations in attentional control better explain the trial-by-trial differences in working memory that we observe.

Visual working memory

Visual working memory (VWM), the system of storing, manipulating, and utilizing, visual information is fundamental to many cognitive acts. Exploring the limitations of this system is essential to understand the characteristics of higher-order cognition, since at a basic level, VWM is the interface through which we interact with our environment. Given its important function, this system has become a very active area of research in the recent years. Here, we examine current models of VWM, along with the proposed reasons for what limits its capacity. This is followed by a short description of recent neural findings that have helped constrain models of VWM. In closing, we focus on work exploring individual differences in working memory capacity, and what these findings reveal about the intimate relationship between VWM and attention. WIREs Cogn Sci 2013, 4:179-190. doi: 10.1002/wcs.1219 For further resources related to this article, please visit the WIREs website.

Parallel Consolidation of Simple Features into Visual Short-Term Memory.

Although considerable research has examined the storage limits of visual short-term memory (VSTM), little is known about the initial formation (i.e., the consolidation) of VSTM representations. A few previous studies have estimated the capacity of consolidation to be one item at a time. Here we used a sequential-simultaneous manipulation to reexamine the limits of consolidating items into VSTM. Participants viewed briefly presented and masked color patches (targets), which were shown either sequentially or simultaneously. A probe color followed the targets and participants decided whether it matched one of the targets or was a novel color. In four experiments, we consistently found equal performance for sequential and simultaneous presentations for two targets. Worse performance in the simultaneous than the sequential condition was observed for larger set sizes (three and four). Contrary to previous results, suggesting a severe capacity limit of one item, our results indicate that consolidation into VSTM can occur in parallel and without capacity limits for at least two items.

A Soft Handoff of Attention between Cerebral Hemispheres

Each cerebral hemisphere initially processes one half of the visual world. How are moving objects seamlessly tracked when they traverse visual hemifields? Covert tracking of lateralized objects evokes a difference between slow-wave electrophysiological activity observed from contralateral and ipsilateral electrodes in occipitoparietal regions. This event-related potentials (ERP) waveform, known as contralateral delay activity (CDA) [1, 2], is sensitive to the number of objects tracked [1, 2] and responds dynamically to changes in this quantity [3]. When a tracked object crosses the midline, an inversion in CDA polarity revealed the dropping of the objects representation by one hemisphere and its acquisition by the other. Importantly, our data suggest that the initially tracking hemisphere continues to represent the object for a period after that object crosses the midline. Meanwhile, the receiving hemisphere begins to represent the object before the object crosses the midline, leading to a period in which the object is represented by both hemispheres. Further, this overlap in representation is reduced if the midline crossing is unpredictable. Thus, this process is sensitive to observer expectations and does not simply reflect overlapping receptive fields near the midline.

Erratum: A Soft Handoff of Attention between Cerebral Hemispheres (Current Biology (2014) 24(10) (1133–1137) (S0960982214003467) (10.1016/j.cub.2014.03.054))

Department of Psychology, University of Oregon, Eugene,OR 97403, USASummaryEach cerebral hemisphere initially processes one half of thevisual world. How are moving objects seamlessly trackedwhen they traverse visual hemifields? Covert tracking oflateralized objects evokes a difference between slow-waveelectrophysiological activity observed from contralateraland ipsilateral electrodes in occipitoparietal regions. Thisevent-related potentials (ERP) waveform, known as contra-lateral delay activity (CDA) [1, 2], is sensitive to the numberof objects tracked [1, 2] and responds dynamically tochanges in this quantity [3]. When a tracked object crossesthe midline, an inversion in CDA polarity revealed the drop-ping of the object’s representation by one hemisphere andits acquisition by the other. Importantly, our data suggestthat the initially tracking hemisphere continues to representthe object for a period after that object crosses the midline.Meanwhile, the receiving hemisphere begins to representthe object before the object crosses the midline, leading toa period in which the object is represented by both hemi-spheres. Further, this overlap in representation is reducedif the midline crossing is unpredictable. Thus, this processis sensitive to observer expectations and does not simplyreflect overlapping receptive fields near the midline.Results and DiscussionWe recorded event-related potentials (ERPs) from healthyyoungadultsastheycovertlytrackedaverticallyorhorizontal-lymovingobjectwhileholdingcentralfixation(seetheSupple-mental Results and Discussion available online for additionalinformation on eye movements). As shown in Figure 1A, oneach trial, a pair of objects was presented in each quadrant.A brief (500 ms) cue informed the observer which object totrack. ERP waveforms were time-locked to the onset of thiscue. When the cue disappeared, all objects began to moveeither clockwise or counterclockwise, taking each pair overeitherthehorizontalorverticalmidline.Movementtowardmid-lines was held constant so that all objects crossed theirrespective midline at the same time. Movement in the orthog-onal direction was less constrained. For example, as a pair ofobjects moved to the right, they would vacilate up and down,allowing their paths to cross and making tracking difficult(see the Supplemental Results and Discussion and FiguresS1 and S2). As the objects were otherwise identical, closeattention was required in order to track the target. Objectsmoved for 2.55 s, crossing the midline 1.70 s after cue onset(1.20 s after motion onset). This design ensured that the num-ber of objects in each visual hemifield was always balancedand the distance traveled by objects on vertical and hori-zontal trials was identical. For more information on experi-mentalproceduresandbehavioraldata,seetheSupplementalInformation.Each trial was categorized in terms of the whether thetracked object crossed the vertical or the horizontal midline.We averaged across five pairs of occipitoparietal electrodes(selected based on prior work [1, 4]) and categorized the tworesultant waveforms as contra- or ipsilateral with respect tothe initial position of the tracked object (see Figure 1B). Tosimplify analysis, we collapsed across direction of motionand initial position. Only correct trials with no eye movementsor blinks artifacts were included. In our analyses, we refer toactivity over the initially contralateral hemisphere as thesourcehemisphereactivityandactivityfromtheinitiallyipsilat-eral hemisphere as target hemisphere activity. (Note that thisnaming convention is specific to the horizontal condition: inthe vertical condition, the target hemisphere never receivesthe object information since it was confined to a single visualhemifield.)Onverticaltrials,whenthetrackedobjectwasnotswitchinghemispheres, we observed a large contralateral delay activity(CDA) in the time window before the attended object crossedthe horizontal meridian (800–1,200 ms: t(13) = 7.76, p < 0.001)and a similar CDA after the crossing (2,000–2,400 ms: t(13) =7.35, p < 0.001). There were no differences between thosetime periods (t(13) = 1.64, p = 0.123). In contrast, on horizontaltrials when the attended objects crossed the vertical midlineand moved from one visual field to the other, we observed alarge CDA prior to the crossing (800–1,200: t(13) = 11.03, p <0.001). The waveform then inverted in polarity shortly afterthe tracked object crossed the vertical meridian, such thatipsilateral activity was more negative than contralateral activ-ity (2,000–2,400 ms: t(13) = 23.54, p = 0.004). As predicted,activity from the hemisphere contralateral to the current loca-tion of the tracked object was more negative than ipsilateralactivity regardless of whether the tracked object stayedwithin a hemifield or crossed between fields, revealing a dy-namic remapping of attended object information betweenhemispheres.Like the handoff between cellular phone towers transferringa live call on a moving mobile device, the handoff betweenhemispheres can be decomposed into two events that couldoccur at different times. There is a moment when the targethemisphere picks up the attended object information andanother when the source hemisphere drops the information.This hemispheric handoff is analogous to presaccadic remap-ping [5, 6], where two findings are consistent across a rangeof methodologies [7–10]. First, target information is typicallypicked up prospectively, meaning that cells at the new, post-saccadic position represent the object before the completionof the saccade [7]. Second, the remapping closely approxi-mates a ‘‘hard handoff’’ in which the cells that code the objectin its original eye position quickly truncate their activity once