Covert Visual Attention

COVERT VISUAL ATTENTION

An event-related potential study of the N2pc and PD components

Master Degree Project in Cognitive Neuroscience One year Advanced level 30 ECTS Spring term 2020

Andreas Karske

Supervisor: Oskar MacGregor Examiner: Andreas Kalckert Abstract

In the study of covert visual attention, two event-related potential (ERP) components have been identified by earlier research. The N2 posterior contralateral (N2pc) component has been suggested to index the enhancement of attention to a specific lateralized target item. The distractor positivity (PD) component has been suggested to index the suppression of distractors appearing in the same search array. Earlier studies have reported different latencies for the PD component depending on the task and experiment. Furthermore, the N2pc and the PD component are not always elicited in the same experiment. Relative target-to-difficult-distractor placement have been shown to affect the mean amplitude of the N2pc. Less is known about how different relative placements affect the PD component. The aim of the present study was to try and elicit both an N2pc and a PD component in the same visual search paradigm. The PD was recorded later time-window which previous studies have suggested to indicate the ending of attention to a previously attended target. Three relative placements were analysed, horizontally opposite, vertically opposite and diagonally opposite. When combining all three relative placements an N2pc component was elicited contralateral to the target. No PD component was found when combining all relative placements. A larger mean amplitude N2pc was measured for the vertically opposite condition. The results are not in line with previous research, that have found the N2pc to be smaller in conditions where both target and distractor are on the same side of the visual field. However, when comparing upper and lower visual field targets the N2pc was found to be larger for lower visual field stimuli, which is in line with previous research. A larger mean amplitude for the PD was found in the diagonally opposite condition. Earlier research has suggested that when difficult distractor and target are located on separate sides of the visual field, this leads to successful inhibition, indexed by the PD component. In contrast to earlier research a larger PD component was not found for upper visual field stimuli. The present study differs from previous studies in the way the target and difficult distractor were placed and analysed. By separating what has previously been called “opposite side” condition into two separate conditions diagonally opposite and horizontally opposite the results from the present study seem to suggest that these two conditions are not synonymous. However, the results should be regarded with caution due to the small sample size. Furthermore, the horizontally opposite side

condition also differs from previous studies with regards to relative target and distractor distances, which could have had an effect on the results.

Keywords: N2pc, PD, visual search, attentional capture, attention, event-related potential, cognitive neuroscience

The following story is said to have taken place between Ikkyū Sōjun, a 15th century zen master and his student. One day a man approached Ikkyū and asked: “Master, will you please write for me some maxims of the highest wisdom?” Ikkyū took his brush and wrote: “Attention.” “Is that all?” asked the man. Ikkyū then wrote: “Attention, Attention.” “Well,” said the man, “I really don’t see much depth in what you have written.” Then Ikkyū wrote the same word three times: “Attention, Attention, Attention.” Half-angered, the man demanded, “What does that word ‘Attention’ mean, anyway?” Ikkyū gently responded, “Attention means attention.” (Schiller, 1994, p.17).

Acknowledgements

The visual search paradigm used in the present thesis was a collaborate effort between myself and two other fellow students, Noah Kaufman and Oscar Magnusson. As a group we faced the challenge of both designing and programming a visual search paradigm that could be used for three separate aims that in turn would lead to three separate theses. It goes without saying that this would never have been possible without the joint effort from all of us. I would like to thank Noah Kaufman for having the patience and pedagogical skills to explain to me some of the (according to me) more difficult aspects of programming while we were working together. I would also like to thank Oscar Magnusson for helping me to design an experiment that could be used to study the N2pc. After working together with both Noah and Oscar I think it is safe to say that I hold both in high regard and couldn’t have asked for two more well- humoured and compassionate collaborators. I would also like to thank Oskar MacGregor, my supervisor, who through his more hands-off approach let me make many mistakes during the process of both designing and writing the present thesis. But also, for knowing when to step in and give more advice on how to fine-tune aspects of both the design of the experiment as well as the terminology used to communicate the finer details of the experiment to the reader. Finally, I would like to thank all the participants who volunteered for the project.

Table of Contents Introduction ...... 7

Background ...... 9

Attention, attention, attention ...... 9

The N2pc component ...... 11

N2pc and PD components ...... 12

Neuronal basis of visual attention ...... 15

Focus of the present study ...... 18

Method ...... 20

Participants ...... 20

Design ...... 20

Stimuli ...... 21

Procedure ...... 22

Electrophysiological recording ...... 24

Data analysis ...... 25

Results ...... 26

Behaviour ...... 26

Analysis N2pc ...... 26

Analysis PD ...... 29

Discussion ...... 30

The N2pc component ...... 32

The PD component ...... 35

Conclusion ...... 40

References ...... 42

Introduction

Attention is a broad umbrella term reflecting many different processes. In everyday life we use attention to select out information relevant to our personal goals. How this selection is carried out is a question that has been the subject of considerable research (Luck & Gold, 2008). The visual search paradigm has been used to inform many influential theories regarding visual selective attention. During a visual search experiment subjects search for a specific target among a number of distractors (Hickey, Di Lollo, & McDonald, 2009). Another question that has occupied the field of attention, is whether focused attention is the result of target enhancement or distractor suppression. Earlier research suggested that focused attention was mainly the result of enhancement of features related to target items (Luck & Hillyard, 1994). Later studies, however, found that suppression of features belonging to distracting objects also played a part in focused attention (Hickey, et al., 2009). Since the behavioural results are the same irrespective of the actual underlying mechanism, (i.e., attention is focused on a single target at the expense of irrelevant distractors), researchers have looked for answers on a neural basis to resolve the question (e.g. Sawaki, Geng, & Luck, 2012). The use of event-related potentials (ERPs) is a common way to investigate cognitive processes that happen on a short time scale. Research into visual perception has revealed different potential ERP components that relate to different stages of visual perception. Earlier ERP studies found that when subjects focused on a lateralized target, this elicited a more negative amplitude waveform in the contralateral hemifield compared to the waveform recorded at the ipsilateral hemifield relative to the target. The difference between the contralateral and ipsilateral waveforms was dubbed the N2 posterior contralateral (N2pc) component and is a member of the N2 component family appearing between 200-300 ms after stimulus onset (Luck & Hillyard, 1994). Earlier research suggested that the N2pc was the result of a filtering process, in which distracting stimuli were suppressed. Later research found that another component, the distractor positivity (PD), was more directly related to distractor suppression and suggested that the N2pc instead was an index of target enhancement (Eimer, 1996; Hickey et al., 2009). However, the PD component does not seem to be as easy to define as the N2pc and different studies have elicited a PD component during different time-windows, between 100-400 ms after stimulus onset (Luck, 2012). The appearance of the PD component during different time-windows

has led to different theories regarding its function. Earlier research suggested that the PD component, when appearing either before or during the same time window as the N2pc, was an index of distractor suppression (Hickey et al., 2009). However, the appearance of the PD component both after the time-window of the N2pc and in the same ERP waveform, has later been suggested to index the ending of attention to a recently enhanced target (Sawaki et al., 2012). Both the N2pc and the PD component seem to vary in amplitude depending on where they are located in relation to each other (Luck, Girelli, McDermott, & Ford, 1997; Sawaki et al., 2012). Earlier models on visual attention suggested that attentional modulation is the result of competition between different objects located close together in the visual field. The models were based on findings from earlier single-unit studies in non-human primates which found that the role of attention was greater when the receptive field of a neuron contained both a target and a distractor (e.g. Chelazzi, Miller, Duncan, & Desimone, 1993; Moran & Desimone, 1985). Later brain-imaging studies have found that attentional demands are greatest in the dorsolateral occipital part of V4 (Tootel et al., 1998). The same areas seem to coincide with the location of the occipital-temporal electrode sites PO7 and PO8 where the largest amplitude of the N2pc and the PD components have been measured (Hickey et al., 2009; Luck, 2012; Luck, Girelli et al., 1997; Serano et al., 1995). While there have been studies directly relating distractor suppression to cortical changes in the visual cortex, from V1 to higher extrastriate areas (e.g. Ruff & Driver, 2006; Slotnick, Schwarzbach, & Yantis, 2003), the amount of studies pale in comparison to the amount of research related to target enhancement. The aim of the present study was to elicit both an N2pc and a PD component in the same visual search paradigm, without isolating one or the other. The two components are known to either cancel out each other or add together to produce one single component, usually a large N2pc, if they appear during the same measurement window 200-300 ms after stimulus onset (e.g. Hickey et al., 2009). This is why most studies isolate the components by placing either the difficult distractor on the vertical midline (to elicit a N2pc) or place the target on the vertical midline (to isolate the PD). Since, relative target-to-difficult-distractor placement have been shown to affect the mean amplitude of the N2pc, three different relative, target-to-difficult-distractor placements were analysed. Less is known about how different relative placements affect the PD component, which is why the same three

relative placements were analysed for the PD as for the N2pc component. A later time-window was chosen for the PD component between 300-400 ms after stimulus- onset, which earlier studies have suggested could be an index of terminating attention to a recently focused object (Sawaki et al., 2012).

Background

Attention, attention, attention

What is attention? Probably the most famous definition of attention was the one made by William James who after first remarking that: “ Everyone knows what attention is.” describes it as “It is the taking possession by the mind, in clear and vivid form, of one out of what seem several simultaneously possible objects or trains of thought” . . . “it implies withdrawal from some things in order to deal effectively with others . . .” (James, 1890/2017, p. 170). This seemingly intuitive description is still an apt way to define attention as a whole in the modern-day neuroscience literature (Luck & Gold, 2008). While modern-day neuroscience has managed to explain the process in finer detail, the concept is still more or less defined the same way as it was by James more than a century ago. How we attend to different objects (and thoughts) can however vary depending on whether we do it voluntarily or whether something catches our attention (Carrasco, 2011). The former is usually referred to as voluntary attention and is a top-down driven process, where intentional goals direct the placing of attention, (e.g. when writing a thesis or reading an article on attention). The latter reflexive attention is a stimulus-driven bottom-up process, where attention is captured by some form of sensory event, (e.g. a loud bang or a salient visual feature; like a red dot amongst green dots). The orienting of or the selecting of an object for attention can also be split in twain into either overt attention or covert attention (Carrasco, 2011). Overt attention is the same as turning your head towards a sound or moving your eyes to get a better look. Covert attention is probably best explained using a more modern analogy, computer games. Imagine that you are focusing intensely on a character in a computer game as you try to avoid obstacles or try to collect something of value, (e.g. course credits). At the same time while you are overtly focusing on your character you are also covertly scanning the periphery for possible dangers or rewards without moving your gaze, which is focused intensely on

the game character. In the visual modality overt and covert attention typically follow a certain sequence of steps. The process starts with defining a goal or something to look out for, that in turn can be used to guide the allocation or orientation of attention (Luck, 2012). Take for example a cognitive experiment on visual attention called the visual search paradigm. During a visual search paradigm subjects search for a specific target item that they have been briefed on before-hand (e.g. a red square), amongst a number of distracting items (e.g. green squares) (Hickey, et al., 2009). The features related to this target item (e.g. colour, shape) are stored as a search template in working memory which then guides the process of finding the target (Woodman, Luck, & Schall, 2007). The second step entails highlighting the features previously stored in working memory, by increasing the sensitivity for the specific features (e.g. colour, shape) (Hopf, Boelmans, Schoenfeld, Luck, & Heinze, 2004). In our example the combination of the colour red and the square shape are given precedence over other possible features in the search array (green squares) and is subsequently processed further. The third step is where covert attention comes in. After having stored the features of the target item in working memory and increased the sensitivity to the specific features related to the target item, the mere presence of an object containing these features is sufficient for the allocating of covert attention to the location of the object. This in turn leads to further processing of said object, where it is stored in working memory once again (Hollingworth & Luck, 2009). The fourth step works as a confirmation or matching step, between the search template previously stored in working memory and the new object recently added to working memory. The object in the search template is compared with the object that recently triggered the covert attention and if a match can be made, this may trigger the allocation of overt attention (i.e. shifting the gaze to take a better look) (Luck, 2012). The last step entails focusing more on the recently overtly attended object by either expanding or contracting the attention around the object (Hopf et al., 2006). In our example this would mean contracting attention around the red square and ignoring the green squares. Given that the above-mentioned steps happen on very short time scale, literally within a blink of an eye, the use of methods capable of high temporal resolution like event-related potentials (ERPs) have extensively been used when uncovering said underlying processes related to visual attention. Research into the

broader field of visual perception has revealed different potential ERP components that relate to different stages of visual perception. The main focus of this thesis is covert visual attention more specifically the ERP components related to covert selective visual attention which the following section will cover in more detail.

The N2pc component

Several studies have suggested that the N2pc could be an index of covert selective visual attention (Luck, 2012). The N2 posterior contralateral (N2pc) component, is a member of the N2 component family appearing around 200-300 ms after stimulus presentation. When attention is directed towards a target item presented amongst distracting non-targets, as is the case in visual search paradigms, ERP waveforms recorded over the posterior scalp situated contralateral to the target elicit a more negative amplitude compared to the waveform recorded at the posterior region ipsilateral to the target. The difference between these two waves is the N2pc (Luck & Hillyard, 1994). In their seminal study Luck and Hillyard (1994) proposed that the N2pc is linked to the suppression or filtering out of distracting stimuli during attentional focusing in visual search. The authors found that search arrays with targets containing a single salient feature produced a markedly reduced or no N2pc component, whereas search arrays with multiple features elicited a large N2pc. According to Luck and Hillyard (1994) search arrays containing targets with a single different feature pops out amongst the distractors and renders filtering unnecessary. Take for instance our earlier example with red and green squares. What Luck and Hillyard (1994), found was that when the only differing feature was colour (as in our example) this led to a small N2pc since the red target item can be easily located amidst the green distracting items. Earlier behavioural research has also shown that tasks containing single pop-out features encourage participants to adopt a singleton detection mode, where they search for discontinuities among features as opposed to identifying specific task related features (Bacon & Egeth, 1994). When both the target item and the distractor item share multiple features as in a conjunction task, filtering is seen as necessary for discerning between target and distractor (Luck & Hillyard, 1994). Expanding on our earlier example, if we change one of the distractor items to red (same as the target item) making it a difficult distractor (difficult since it resembles the target more than the rest of the distractors which are green). At the same time, we

add some features to the target and the newly created difficult distractor; a symbol in the middle, either x or +. Now the task is to find the red square with the x in the middle amongst the distractors (one red square with a + in the middle and many green squares). According to Luck and Hillyard (1994), when both target and distractor contain multiple matching features (e.g. square shape, red colour) more attention is needed to discern the red target from the red difficult distractor, or as the authors put it filter out the distractors. Luck and Hillyard (1994) based their filtering hypothesis on earlier models of visual attention which will be covered in the section: “Neuronal basis of visual attention”.

N2pc and PD components

Later studies have, however, questioned the suggestion that the N2pc simply represents suppression of distracting stimuli and proposed that the N2pc could reflect target enhancement instead (Eimer, 1996). The author proposed that the N2pc represents top-down neural mechanisms that are sensitive to features related to the task, (i.e. not directly reflecting suppression of distractors). Since their experiment only consisted of one distractor in the opposite hemifield, meaning that it was nowhere near the target, suppression was ruled out. According to Hickey et al. (2009), the N2pc component could be seen as two distinct processes added together. The authors suggested that N2pc consists of both a positive component, the distractor positivity (PD) contralateral to the distractor, and a negative component the target negativity (NT) contralateral to the target. In other words, the two components would be the electrophysiological index for target suppression (indexed by the PD) and target processing (indexed by the NT). PD occurred over more medial and dorsal areas, whereas NT occurred at more ventral and lateral areas. PD was larger when the distractor was presented in the upper visual field while the distractor was lateralized and the target was situated on the vertical midline. On the other hand, NT was larger when the target was presented in the lower visual field while the target was lateralized and the distractor was located on the vertical midline (Hickey et al., 2009). The problem with the results of Eimer (1996) and Hickey et al. (2009) is that the distractors, even when far away from the target, can occupy the same receptive field of the neuron that codes the target stimulus. This is especially the case in the late visual areas e.g. V4; thus, filtering would be expected to occur (more on the

receptive fields of neurons in the section “Neuronal basis of visual attention”). While it can be argued that filtering took place even when the target was lateralized and the distractor was situated far away, this still does not explain why a separate component, the PD, was observed when the distractor was lateralized and the target was situated on the vertical midline. A later study by Tay, Harms, Hillyard and McDonald (2019) failed to replicate the results reached by Luck and Hillyard (1994), in their experiment 2, which used singleton targets and was seen as evidence in favour of the filtering hypothesis. Tay et al. (2019) concluded that N2pc might be the result of other mechanisms than filtering. However, the study by Tay et al. (2019) used a bigger sample and a modified electrode setup, which later studies have found to elicit a stronger N2pc (Luck, 2012). Subsequent studies were able to observe a PD component in addition to the N2pc component during different visual attention paradigms. Sawaki and Luck (2010) asked subjects to find a target letter amongst other distracting letters. In some of the trials they included a salient distractor, (i.e. a distracting letter with a different colour). The authors found that a salient distractor produced a PD contralateral to the distractor but no N2pc, whereas trials with no salient distractors produced an N2pc but no PD. Other studies have produced similar results, where a PD can be elicited, but not an N2pc (Gaspar, Christie, Prime, Jolicoeur, & McDonald, 2016). However, some studies have elicited both components in the same ERP wave form (Kiss, Grubert, Petersen, & Eimer, 2012; Sawaki & Luck, 2014). The above-mentioned studies have all used salient distractors to elicit the PD (i.e. bright coloured items that stand out). This has led to the conclusion that the PD is mostly elicited by stimuli that captures the attention through bottom-up sensory processes. This seems to be in line with stimulus driven theories that suggest that salient stimuli catch the attention irrespective of the task relevant goals (Theeuwes, 1992, 2010). However, some studies also support the view that after attention has been captured by salient stimuli, top-down control can be used to actively suppress the distractor stimuli (e.g. Sawaki & Luck, 2010). This is consistent with goal-driven theories which suggest that salience alone is not enough for attention to be captured, but that other features relevant to the task might influence how much a distractor will interfere with target location (e.g. Lien, Ruthruff, Goodin, & Remington, 2008). The debate between stimulus driven and goal driven theories of attentional capture has been going on for over two decades and at present there

seems to be no sign that the debate would be resolved anytime soon. There is, however, more recent research that has tried to take into account both theories to explain attentional capture. According to the signal suppression hypothesis, salient distractors can attract attention if they are not actively suppressed by top-down mechanisms (Gaspelin & Luck, 2018a). Lastly, since the latency of the PD component seems to vary depending on the task and experiment, this has created additional confusion when trying to locate the PD component. While most experiments have measured the PD in a time- window between 150-300 ms after stimulus onset (Luck, 2012), a closer look reveals that the PD seems to appear in a broader time-window, between 100-400 ms (Sawaki et al., 2012). This can in turn lead to two problems. Firstly, the PD component can be missed entirely as a result of the chosen measurement-window. Earlier studies could have elicited a PD component in relation to the N2pc, but since the onset time can vary considerably with regards to the experiment the PD component may have been overlooked. Secondly, if the whole time-window that has been reported to house the PD component would be measured at the same time, this would result in a lot of noise in the ERP waveform, which in turn would reduce statistical power. In addition, since both components are usually recorded at the PO7 and PO8 electrodes; if the N2pc would appear during the same latency as the PD, but at opposite polarity, this would further reduce the chance of detecting the PD component (Hickey et al., 2009; Sawaki et al., 2012). Taken together it would seem that the deployment of covert visual attention is a product of both target enhancement (indexed by the N2pc) and distractor suppression (indexed by the PD). But since the latency of the PD seems to vary, it is still unclear whether it reflects distractor inhibition prior to target enhancement or inhibition of salient distractors after target selection has occurred. Yet another possibility is that the PD could reflect a suppressive process that returns attention back to a neutral unfocused state after attention has been focused (indexed by the N2pc) (Sawaki & Luck, 2014). The following section will focus more on models of visual attention and the neural basis of visual attention. The aim of the following section is not to lend support in favour of either the N2pc or the PD component, but rather to illustrate the complicated relationship between suppression and enhancement in visual attention.

Neuronal basis of visual attention

According to the feature integration theory the visual system separates stimuli into different maps of features, (e.g. colour, orientation). The feature extraction process is proposed to occur in parallel for different features in different locations. Attention is seen as the “glue” that combines the different features that are coded at different locations belonging to the same object. When features from different objects become represented in the same receptive field of a single neuron it could lead to illusory conjunctions, where features from different objects mix together (Treisman, 1988; Treisman & Schmidt, 1982). This could explain the results of attentional capture studies where either highly salient or relevant distractors (relevant since they share features with the target) capture the attention (e.g. Kiss et al., 2012; Sawaki & Luck, 2010). The biased competition model of attention by Desimone and Duncan (1995) states that features belonging to different objects compete with each other in order to get processed further. According to the authors task-relevant objects are given a competitive advantage over the distractor objects with the help of top-down attentional mechanisms. This in turn inhibits the distractors by not giving them the same attentional resources as the task-relevant objects. Both models of visual attention suggest that some form of competition will occur if stimuli that resembles each other are located close together. This has been confirmed in single-unit studies on non-human primates which found that the role of attention was greater when the receptive field of a neuron contained both a target and a distractor (Chelazzi et al., 1993; Moran & Desimone, 1985). Other single unit studies on non-human primates have found that attention enhances firing rates of neurons associated with the target (Roelfsema, Lamme, & Spekreijse, 1998). Later studies on non-human primates have also found increases in neuronal response selectivity to single features related to targets in later visual areas V4 (McAdams & Maunsell, 1999). Taken together these single unit studies seem to support the notion that attention is the result of target enhancement, possibly mediated by top-down attentional mechanisms sensitive to target characteristics held in working memory (Hollingworth & Luck, 2009). A later study replicated and extended the single-unit study by Moran and Desimone (1985) and recorded neurons from V1, V2, and V4. The authors found that attentional modulation was consistently elicited in inferotemporal cortex area V4,

when the receptive field of a single neuron contained both a target and distractor. Areas V1 and V2 did not show similar attentional modulation (Luck, Chelazzi, Hillyard, & Desimone, 1997). This is consistent with earlier studies measuring the receptive fields of neurons within different visual areas in the primate brain. After light has hit the photoreceptor cells in the retina, it commences a neural process that moves from the retina to the lateral geniculate nucleus (LGN) in the thalamus. From here the neural process continues to the primary visual cortex (V1) where the neural process is thought to bifurcate into two pathways for further processing. Mishkin and Ungerleider (1982) proposed the split of visual information into two different pathways. In a study on primates the authors suggested that the ventral stream was responsible for identification, whereas the dorsal stream responded to localization. The authors dubbed the two pathways into the ventral “what” stream and the dorsal “where” stream. The further downstream the information flows the more complex features are coded within single neurons receptive fields. At the same time the receptive fields increase, leading to the possibility of features from different objects occupying the same receptive field of a single neuron. Area V4 is located in the intermediate to late part of the ventral visual stream in the inferotemporal cortex, which could explain the higher attentional demands needed for discriminating features belonging to a single object when multiple objects occupy the same receptive field of a single neuron (Luck, Chelazzi et al., 1997). While earlier single unit studies mainly focused on non-human primate visual cortex (e.g., Chelazzi et al., 1993; Moran & Desimone, 1985), later studies sought to combine the results found in single-unit studies on non-human primates with existing evidence from visual search experiments on humans (Luck, Girelli et al., 1997). The results showed several similarities between both species in the way visual attention operates. First, the N2pc component was larger when two items where positioned close together in a search array within each hemifield, as opposed to when only one item was placed in each hemifield. Second, the N2pc was larger when subjects performed conjunction tasks as opposed to single feature detection tasks. Third, a larger N2pc was observed when subjects had to foveate the target as opposed to simply detect the target. Lastly, the N2pc was smaller for upper visual field targets as opposed to lower visual field targets. However, it is worth mentioning that the authors interpreted this as evidence of distractor suppression rather than target enhancement since no PD component had been recorded at that time.

Topographic mapping of visual stimuli has found that lower visual field representations are located in the dorsolateral occipital part of V4, also known as lateral occipital area (LO1) in the human brain as opposed to the dorsal area (V4d) in macaques, located directly underneath the occipital-temporal electrode sites (Serano et al., 1995). Thus, stimuli located at the lower visual field should elicit a large ERP deflection at these sites. Upper visual field representations are located in the ventral surface of the occipital part of V4. This area is further from the scalp and would elicit a smaller ERP signal (Luck, Girelli et al., 1997). The occipital-temporal electrode sites PO7 and PO8 are also reportedly where the maximum voltage for the N2pc is recorded (Luck, 2012). There is, however, some debate whether LO1 found in humans is an exact homologue of V4d found in macaques. The distinction between upper and lower visual field in later visual areas seem to be more ambiguous in humans than in macaques (Kravitz, Saleem, Baker, Ungerleider, & Mishkin, 2013). Tootel et al. (1998) conducted an fMRI study to see how attention activates different areas of the visual cortex. By combining high resolution mapping of the borders of the human visual areas (retinotopic mapping) with spatial attention tasks, the authors could see how attention effects different areas of the visual cortex. The authors found some activation in the striate cortex V1, but most activation related to attention was found in the later parts of the hierarchy of the visual system. The above-mentioned studies all seem to indicate that attentional demands are greatest in the dorsolateral occipital part of V4. And as mentioned earlier this seems to coincide with the location of the occipital-temporal electrode sites PO7 and PO8 where the N2pc is largest (Luck, 2012; Luck, Girelli et al., 1997; Serano et al., 1995). While earlier brain imaging studies mainly focused on the facilitation of attention, or enhancement of a target (e.g. Tootel et al., 1998), later studies sought to find evidence for both attentional facilitation and inhibition, (i.e. target enhancement and distractor suppression). Slotnick et al. (2003) used event-related fMRI combined with retinotopic mapping to localize attentional modulation related to both attended and unattended locations. Apart from replicating earlier research on attentional facilitation related to attended locations, the authors also found direct evidence of suppression in both striate and extrastriate cortex. A later fMRI study by Ruff and Driver (2006) also found evidence of modulation in the occipital cortex contralateral to a distracting stimulus when subjects anticipated a distractor in the opposite visual field from the target.

With regards to eccentricity, studies on the distribution on receptive fields of neurons in later ventral visual areas have found the neurons to be heavily weighted towards the fovea (Dumoulin & Wandell, 2008). Thus, objects appearing near the periphery of the receptive field would be represented by fewer neurons which in turn produces less activity in relation to objects appearing near the midline. Furthermore, the receptive fields of neurons in the later ventral visual areas also seem to extend to the ipsilateral hemifield. For the N2pc, this would mean that the target stimuli would have to be presented far enough from the vertical midline so that most of the receptive field covers the contralateral visual hemifield but not too far from the midline as this would lead to a reduced signal due to the lessening of neurons near the periphery. Papaioannou and Luck (2020) performed a study to see how different eccentricities affect the amplitude of the N2pc. The authors found that the amplitude of the N2pc remained stable and clearly detectable for stimuli appearing directly adjacent to the vertical midline through to 4 degrees eccentricity. After 4 degrees eccentricity the amplitude of the N2pc was markedly reduced. The interesting find was that stimuli appearing near the vertical midline still produced a robust signal. As mentioned before studies have shown that the receptive fields of neurons in the later ventral visual areas in the inferotemporal cortex have been shown to extend to the ipsilateral hemifield, which in turn should lead to a weaker signal when the contralateral activity is subtracted from the ipsilateral, as is the case with the N2pc. Earlier studies have, however, found that when items are displayed in bilateral displays, neurons with bilateral receptive fields like the neurons in inferotemporal cortex, are biased to represent items appearing in the contralateral visual field (Chelazzi, Duncan, Miller, & Desimone, 1998). This is consistent with the biased competition model of visual attention mentioned earlier, where stimuli appearing in the same receptive field compete for further processing and task-relevant objects are given a competitive advantage over the distractor objects with the help of top-down attentional mechanisms (Desimone & Duncan, 1995.)

Focus of the present study

The principal objective of this study was to see if a visual search task would elicit both an N2pc and a PD component, without placing one of the components on the vertical midline. Placing one of the components on the vertical

midline will result in equal amounts of activation in the contralateral and ipsilateral side. Since the components are defined as the difference between the contralateral and ipsilateral side, any activation appearing in both sides will be subtracted away resulting in no difference between the sides for the component on the vertical midline (Hickey et al., 2009). According to earlier research the amplitude of the N2pc depends on the target and difficult distractor placement. A larger N2pc has been observed on conjunction tasks, when targets appear on the lower visual field and when multiple items are located close together (Luck, Girelli et al., 1997). Other research also shows that when the target and difficult distractor are located on opposite sides of the visual field (i.e. left and right sides of the screen) a larger N2pc can be observed (Gaspar & McDonald, 2014). To test the above-mentioned findings this study was designed to include three different relative, target-to-difficult- distractor placements. These three relative placements were target and difficult distractor horizontally opposite (target and difficult distractor same height on opposite sides of the screen), vertically opposite (target and difficult distractor different height same side of the screen) and diagonally opposite (target and difficult distractor both vertically and horizontally opposite). To get a clearer N2pc component both the left and right side of the search array included multiple items (i.e. grey easy distractors). The present study was also a conjunction task since both target and difficult distractor could share multiple features (i.e. have the same orientation and middle symbol, or same orientation and colour). The present study opted for all items being positioned at 4 degrees eccentricity from the middle, since this has been suggested to be the maximum distance from the middle that produces a clear N2pc component. Another reason for choosing a more distant position for all items is that this should minimize the risk for illusory conjunctions if the target and difficult distractor appear near each other (Treisman, 1988; Treisman & Schmidt, 1982). The PD component is less known to vary depending on distractor and target placement. However, there are studies suggesting that the PD is larger for upper visual field stimuli (e.g. Hickey et al., 2009). The present study tested for the same three placements as for the N2pc component (i.e. horizontally opposite, diagonally opposite, vertically opposite), to see if distractor placement affects the amplitude of the PD component. A later time-window was chosen for the PD component for two reasons. Firstly, because the components cancel out each other

when they appear during the same time-window, which renders measuring difficult (e.g. Hickey et al., 2009). Secondly, in order to test the hypothesis that the PD indexes an active ending of attention (e.g. Sawaki et al., 2012).

Method

Participants A total of ten neurologically typical university students between the ages of 18-29 years (males = 5, females= 5, mean age 23.9, SD = 2.8) volunteered for the study. All subjects reported that they were right-handed and had normal or corrected-to-normal vision. Before taking part in the experiment all participants gave their informed consent and were briefed on the purpose of the study, information of methods employed and possible risks associated with participation, information about the voluntariness of participation and the right to cancel participation at any time for any reason.

Design The study consisted of two separate tasks, a questionnaire related to everyday attention (not part of the present study) and a visual search task. The visual search-task was comprised of 24 blocks of 30 trials. The task was to identify a specific target figure consisting of different features, colour, middle-symbol and orientation. The target appeared within a search array amongst other distracting images. A typical trial would consist of a pre-stimulus fixation cross followed by a search array. After the search array a post-stimulus fixation cross appeared during which the subjects could make their response. To mark the end of the trial a blank screen flashed briefly before the next pre-stimulus fixation cross appeared. In addition to the search task, subjects were sometimes asked to rate how they performed on a given trial (i.e. whether they answered correctly or incorrectly). If the subjects answered that they made an error a follow-up question would appear asking the subjects to estimate when they sensed they made an error. The performance-related questions were not part of the present study and will be analysed in a separate study.

Figure 1. Illustrates a schematic of the visual search task where the target and difficult distractor are located diagonally opposite.

Stimuli Stimulus presentation was controlled by E-prime (version 2.0) from a Windows-based computer. A separate Windows-based computer was used to record EEG signal using Simulink in the Matlab environment (version R2019b). Stimulus was presented on a HP Compaq LA2306x 23-inch LCD monitor with a native resolution of 1920 x 1080, a refresh rate 60 Hz, viewed from a distance of 100 cm. The items for the search array were created using Microsoft Windows Paint, (version 6.1). The search array consisted of 12 images (each image 63 x 63 pixels), two of which were green, one representing the target and another one representing a difficult distractor, the rest of the images were grey representing easy distractors. The green images could vary between three equidistant colours of green; true-green (R= 0, G = 191, B = 0), blue-green (R= 0, G = 191, B = 150) and yellow-green (R= 150, G = 191, B = 0), all colours were equiluminant (90 cd/m2). The grey images were all the same colour; (R= 95, G = 95, B = 95), (89 cd/m2). All images consisted of a rectangular square with a symbol, either an x or a + in the middle. All grey coloured easy distractors had openings either on the top, bottom, left or right side. The green coloured targets and distractors had openings to either the right or the left. All the images were placed around a middle fixation cross in a circle at 4 degrees eccentricity. The 12 images were separated into four quadrants each quadrant containing three images. The target and difficult distractor could appear semi-

randomly at one of the 12 positions around the middle fixation cross with the constraint that they never appeared adjacent or in the same quadrant at the same time. The colour and the middle symbol (either x or +) of the target were changed for each block and could have an opening either to the left or to the right. The difficult distractor was always either a different coloured green with the same symbol in the middle or the same colour but with a different symbol in the middle than the target, see figure 2.

Figure 2. Illustrates the different relative target-to-difficult-distractor placements. From left to right, horizontally opposite, vertically opposite, diagonally opposite.

Procedure Before starting the visual-search task subjects were asked to fill in a questionnaire which is not part of the present study and will be analysed in a separate study. When they completed the questionnaire, subjects were instructed on how to proceed during the experiment first verbally and then by reading the same instructions on a computer screen. After reading through the instructions the subjects performed a practice search task, where the level of difficulty was gradually increased. The subjects could repeat each step as many times as they wanted. On average the participants practiced for ten minutes. Following the practice run subjects had an opportunity to ask questions related to the procedure if they still felt something was unclear. At the beginning of each block a fixation cross appeared for 1000 ms followed by a search array displayed for 200 ms. After the search array a post-

stimulus fixation cross was shown for 950 ms during which the participants could respond, after which a blank screen appeared for 100 ms, indicating that the time- window for responding had ended. The following trials had an inter-stimulus interval varying randomly between 400-600 ms. Not counting the first 1000 ms at the beginning of each block the average SOA was 1750 ms. A variation in timing was included (for a separate study) so that some trials the stimulus duration of some blocks changed from 200 ms to 83 ms. To keep the response-collection window the same, blocks with 83 ms stimulus duration was followed by a post-stimulus fixation cross for a period of 1067 ms as opposed to 950 ms. Participants were instructed to focus on the middle fixation cross and report whether the target image had an opening to the right or left by pressing the corresponding right / left arrow-key on a computer keyboard, see figure 3. At the same time as the target appeared in one of the 4 quadrants a green distractor appeared in one of the three other quadrants, which subjects were told to ignore. The target had a 0.5 probability of having an opening either to the right or left. There was also a 0.2 probability that trials featured two hard distractors instead of a target and a distractor. On these trials the subjects were instructed to press nothing. Between each block a 5 s experimenter-controlled rest period was added during which a slide-image appeared instructing the subjects to rest and memorize the new target image. After the experimenter-controlled rest period the subjects had the opportunity to rest more before deciding to continue to the next block. The entire experiment consisted of 24 blocks of 30 trials and lasted between 45-50 minutes depending on how long the subjects practiced, the amount of time they took to rest between blocks and answer the performance related questions.

Figure 3. Illustrates instructions for reporting the orientation of the target.

Electrophysiological recording The EEG was recorded using active Ag/AgCl biosignal electrodes (g.tec, Austria; http://www.gtec.at/) from 32 electrodes (Fz, FCz, AF3, AF4, F7, F8, F5, F6, F3, F4, C3, C4, CP1, CP2, P3, P4, PO3, PO4, PO7, PO8, O1, O2, CPZ, PZ, POZ, OZ), according to the modified 10-20 system. Before recording all electrodes were prepared by injecting a conductive saline solution electrode gel (g.tec, Austria; http://www.gtec.at/). Electrode impedances were transformed by the system to output impedances of about 1kOhm (as suggested by the manufacturer). The biosignal amplifier used was g.USBamp, with an input range of ± 250 mV, which allows recording of DC signals without saturation. Furthermore, the amplifier had 24-bit resolution with simultaneous sampling of 16 DC-coupled wide-range input channels with up to 38.4 kHz, connected via USB 2.0 (g.tec, Austria; http://www.gtec.at/). The ground was recorded from AFZ middle frontal scalp site. All electrodes were referenced from Cz during recording. Additional electrodes were used to detect eye movements and blinks. The horizontal electrooculogram (HEOG) was placed to the external canthi of each eye to record horizontal eye movements and the electrooculogram (EOG) was placed on the upper and lower right eye to record eye blinks. The EEG was continuously sampled at 512 Hz and filtered online with a bandpass filter of .01-100 Hz.

Data analysis Data was analysed with ERPlab toolbox (version 7; Lopez-Calderon, & Luck, 2014) within EEGlab (version 2019.1; Delorme & Makeig, 2004) through the Matlab environment (version R2019b). The EEG data was re-referenced offline to the average of the left and right mastoids after which the data was resampled at 250 Hz. An offline 180th-order notch filter at 50 Hz was used on the continuous EEG data to counteract line noise. An additional pre-processing step Independent Component Analysis (ICA) was added to remove artefacts and non-brain related activity from the data. The ICA data was filtered using a second-order Butterworth bandpass filter with a half-power (-3dB) cut-off at 1 and 30 Hz. (Increased high- pass filter settings are recommended when running the ICA analysis and since this is not done on the original data but only for identifying components it is not regarded as destructive). Further the continuous data was divided into epochs ranging from -200 ms pre- stimulus to 600 ms post-stimulus. The epochs were then run through an automatic artefact rejection function in EEGlab (pop-autorej), that detects large voltage fluctuations in all channels with a threshold setting of 150 µV. This was followed by IClabel, an automatic artefact labelling software that marks unwanted activity not related to brain functions for rejection and subsequently the ICA weighted data was transferred back to the pre-processed data. The data used for analysis was filtered using a second-order Butterworth high pass filter with a half-power cut-off at 0.1 Hz before being divided into epochs ranging from -200 ms pre-stimulus to 600 ms post-stimulus. Moving window peak- to-peak artefact detection was performed on the epochs using a window step of 20 ms, window size of 100 ms, rejecting epochs containing stepwise activity greater than 150 µV. After artefact detection subject 3 had channel F6 removed due to a faulty electrode, interpolation was performed on the removed electrode using the built-in spherical interpolation function in EEGlab. Subject 2 was removed from the study and from further processing since one of the electrodes PO7, one of the main electrodes of interest in the study, was faulty. Lastly the epochs were lowpass filtered using a second-order Butterworth filter with a half-power cut-off at 30Hz.

Results

Behaviour The mean reaction times for the different stimulus durations were: M= 636.96, SD=131.20 for 83 milliseconds and M=628.56, SD=143.69 for 200 milliseconds, t(18)=0.14, p=0.89, see figure 4. The mean accuracy rate for the different stimulus durations were: M=0.75, SD=0.42 for 83 milliseconds and M=0.70, SD=0.45 for 200 milliseconds, t(18)=0.26, p=0.80, see figure 5. The results from both the t-test on the different reaction times and the accuracy rates suggest that the difference in stimulus duration had no significant impact on the performance.

Figure 4. Mean reaction times for the different stimulus durations. Markings on the y-axis are in milliseconds.

Figure 5. Mean accuracy rates for the different stimulus durations. Values on the y- axis are in percent.

Analysis N2pc A paired sample t-test between the contralateral and the ipsilateral sides when all relative placements were included revealed a significant difference between contralateral and the ipsilateral sides. A more negative mean amplitude was measured for the contralateral side relative to target M=0.69 µV, SD=1.9 µV, than for the ipsilateral side M=1.70 µV, SD=2.00 µV, t(8)-10.04, P<0.001, 95% CI (-1.24, - 0.77), see figure 6.

Figure 6. Waveform representing contralateral and ipsilateral electrodes relative to target when all relative placements were combined. The difference between the electrodes is the N2pc. Y-axis markings are in µV, X-axis markings are in ms. The waveform was low-pass filtered at 30 Hz for clearer visualization.

A repeated measures one-way ANOVA with Greenhouse-Geisser correction was performed on the mean amplitudes of the different relative placements. The analysis indicated a significant main effect of relative placement, (F (1.35, 10.83) =55.03, p<0.001, h2=0.873). Mean amplitudes were measured from difference waves between 200-300 ms after stimulus onset. The mean amplitudes for the different relative placements were horizontally opposite, M= 1.05 µV, SD=0.45 µV, vertically opposite, M= -2.11 µV, SD=0.92 µV and diagonally opposite, M= -0.45 µV, SD= 0.25 µV, see figure 7. Post-hoc analysis using a paired sample t-test revealed that the mean amplitude was significantly larger for target vs difficult distractor

located vertically opposite than for target vs difficult distractor located diagonally opposite t(8)=5.19, p= 0.001, 95% CI (0.92 , 2.39) and target vs difficult distractor located horizontally opposite t(8)= 8.42, p<0.001, 95% CI (1.09, 1.91). There was also a significant difference between target vs difficult distractor located vertically opposite and target vs difficult distractor located horizontally opposite, with a larger amplitude for the vertically opposite condition t(8)=8.48, p< 0.001, 95% CI (2.30, 4.02).

Figure 7. N2pc difference waves for the different target and difficult distractor positions. Y-axis markings are in µV, X-axis markings are in ms. The waveform was low-pass filtered at 30 Hz for clearer visualization.

A paired sample t-test between all targets presented on the upper visual field vs all targets presented on the lower visual field was conducted separately for the N2pc. The results show that targets related to the lower visual field produced a larger mean amplitude compared to targets presented on the upper visual field, (t(8)=5.20, p=0.001).

Analysis PD A paired sample t-test between the contralateral and the ipsilateral sides when all relative placements were included, did not reveal a significant difference between contralateral and the ipsilateral sides, contralateral M=4.48 µV, SD=2.44 µV, ipsilateral M=4.54 µV, SD=2.35 µV, t(8)-0.66, P=0.53, 95% CI (-0.28, -0.16), see figure 8.

Figure 8. Waveform representing contralateral and ipsilateral electrodes relative to difficult distractor when all relative placements were combined. The difference between the electrodes is the PD. Y-axis markings are in µV, X-axis markings are in ms. The waveform was low-pass filtered at 30 Hz for clearer visualization.

A repeated measures one-way ANOVA with Greenhouse-Geisser correction was performed on the mean amplitudes of the different relative placements. The analysis indicated a significant main effect of relative placement, (F (1.64, 13.10) =11.410, p=0.002, h2=0.588). Mean amplitudes were measured from difference waves between 300-400 ms after stimulus onset. The mean amplitudes for the different relative placements were, horizontally opposite, M= -0.27 µV, SD=0.34 µV, vertically opposite, M= -0.93 µV, SD=0.73 µV and diagonally opposite, M=0.53 µV, SD=0.51 µV, see figure 9. Post-hoc analysis using a paired sample t-test revealed that the mean amplitude was significantly larger for difficult distractor vs target located diagonally opposite than for difficult distractor vs target located vertically

opposite (t(8)=4.00, p=0.004, 95% CI, (0.61, 2.30)) and difficult distractor vs target located horizontally opposite (t(8)= 0.79, P=0.01, 95% CI, (0.24, 1.35)). There was no significant difference between difficult distractor vs target located vertically opposite and difficult distractor vs target located horizontally opposite (t(8)=-2.19, p= 0.06, 95% CI, (-1.36, 0.35)).

Figure 9. PD difference waves for the different difficult distractor and target positions. Y-axis markings are in µV, X-axis markings are in ms. The waveform was low-pass filtered at 30 Hz for clearer visualization.

A paired sample t-test between all difficult distractors presented on the upper visual field vs all difficult distractors presented on the lower visual field was also conducted separately for the PD. The results showed no significant difference between difficult distractors presented on the upper visual field as opposed to difficult distractors presented on the lower visual field, (t(8)=1.82, p=0.106).

Discussion

The principal objective of this study was to see if a conjunction visual search task could elicit both a N2pc and a PD component, without isolating one or the other by placing one of the components on the vertical midline. Earlier research has mainly abstained from trying to elicit both components in one and the same visual search task, since the two components are known to either cancel out each other or add together to produce one single component, usually a large N2pc, if they appear during the same measurement window 200-300 ms after stimulus onset (e.g. Hickey et al., 2009). This is why most studies have isolated the components by placing either the difficult distractor on the vertical midline (to elicit a N2pc) or place the target on the vertical midline (to isolate the PD). Another way to circumvent the problem has been to choose two measurement windows for the respective components, 200-300 ms for the N2pc and either 100-200 ms or 300-400 for the PD. In the present study I opted for the latter, thereby joining previous studies that test the hypothesis that the PD is a possible electrophysiological index for terminating attention. Three relative placements were used to measure both the N2pc and the PD components. Earlier studies have not separated between what in the present study is referred to as horizontally opposite and diagonally opposite relative placements. As both relative placements have a target and a difficult distractor on opposite sides of the visual field, the conditions have been regarded as synonymous. The third relative placement was vertically opposite, where target and difficult distractor appeared on the same side of the visual field, see figure 2. The results show a clear N2pc component in relation to all combinations of target and difficult distractor relative placement. A larger mean amplitude was measured when target and difficult distractor were located vertically opposite. The results are not in line with previous studies that measured a larger N2pc when targets and distractors were located on opposite sides of the visual field, (in the present study separated into horizontally opposite and diagonally opposite) (Gaspar & McDonald, 2014). No PD component was elicited when all relative placements were combined. Since the PD has been shown to vary depending on the experimental paradigm it is difficult to draw any conclusions as to why a PD was not elicited in the combined comparison. However, when separating the relative placements, a larger mean amplitude for the late PD component appearing between 300-400 ms was measured for the diagonally opposite condition.

For both the N2pc and the PD components, the horizontally opposite side conditions elicited smaller ERPs, relative to diagonally opposite and vertically opposite. This finding was somewhat unexpected, since both the diagonally opposite and horizontally opposite conditions as mentioned earlier have been regarded as synonymous. The following sections will discuss the ERP components and possible interpretations for the result in more detail. I have tried to split the remainder of the discussion of the different components into two separate parts. But as both components strongly relate to each other, both components will inevitably be discussed in part within the respective sections of the different components.

The N2pc component In line with previous studies, when combining all relative placements and comparing the contralateral and the ipsilateral sides, a larger mean amplitude was observed for the contralateral side relative to the target. As the N2pc is defined as the difference between the contralateral and the ipsilateral side in relation to the target, the results suggests that the visual search paradigm used in the present study is suitable for studying the N2pc component. According to earlier research the amplitude of the N2pc depends on the target and difficult distractor placement. A larger N2pc has been observed in conjunction tasks, when targets appear on the lower visual field and when multiple items are located close together (Luck, Girelli et al., 1997). Other research also shows that when the target and difficult distractor are located on opposite sides of the visual field (i.e. left and right sides of the screen) a larger N2pc can be observed (Gaspar & McDonald, 2014). To test the above-mentioned findings this study was designed to include three different relative target-to-difficult-distractor placements. These three relative placements were target and difficult distractor diagonally opposite, vertically opposite and horizontally opposite. To get a clearer N2pc component both the left and right side of the search array included multiple items (i.e. grey easy distractors). The present study was also a conjunction task since both target and difficult distractor could share multiple features (i.e. have the same orientation and middle symbol, or same orientation and colour). In contrast to previous research the target and difficult distractor diagonally opposite condition elicited a smaller N2pc component than the vertically opposite condition (e.g. Gaspar & McDonald, 2014; Kiss et al., 2012). At the same

time the result seems to be in line with some of the earlier models of visual attention (e.g. the biased competition model) that predicts there to be more competition when multiple objects appear in the same receptive field of a single neuron (Desimone & Duncan, 1995). Likewise, earlier electrophysiological research found that when multiple items were located close together within the same visual field a larger N2pc component was elicited (e.g. Luck, Girelli et al., 1997). According to Luck and Girelli et al. (1997) task-relevant objects were given a competitive advantage over the distracting objects with the help of top-down attentional mechanisms. The increase in amplitude for the N2pc was seen as indexing the increase in attentional demand when multiple objects competed for attention. Similar results have been found in behavioural paradigms researching the biased competition model (Mounts & Gavett, 2004). The authors found that in line with the biased competition model participants responded faster to target items when targets and difficult distractor were placed farther apart and when they were located on opposite sides of the visual field as opposed to the same side of the visual field. The authors also found that reaction times were slower when the target item was less salient or equally salient as the distractor, as opposed to faster reaction times when targets were more salient than the distractors. The increase in reaction times for less salient targets and targets positioned in the same visual field relative to the distractors was suggested by the authors to be a result of the distractor interacting with the target processing. The study by Mounts and Gavett (2004), however, differed from the earlier electrophysiological studies (e.g. Luck, Girelli et al., 1997), in that they included a difficult distractor on the same side as the target. Similarly, the present study included a difficult distractor as well as other distracting items in the same visual field as the target. Why this is important is probably best answered by the feature integration theory. According to feature integration theory the visual system separates stimuli into different maps of features, (e.g. colour, orientation). The feature extraction process is proposed to occur in parallel for different features in different locations. Attention is seen as the “glue” that combines the different features that are coded at different locations belonging to the same object. When features from different objects become represented in the same receptive field of a single neuron it could lead to illusory conjunctions, where features from different objects mix together. The risk for illusory conjunctions is greater when several objects share

multiple features (Treisman, 1988; Treisman & Schmidt, 1982). In our case as well as in the case of earlier behavioural paradigms (e.g. Mounts & Gavett, 2004) this could lead to both the target and difficult distractor being processed further since they share multiple features, which could result in a larger N2pc in the present study and as longer reaction times in the behavioural paradigms (e.g. Mounts & Gavett, 2004). How this leads to a larger N2pc component can best be explained by studies on attentional capture of salient distracting stimuli (e.g. Hickey et al., 2009; Sawaki & Luck, 2010). In our case the salient but also highly relevant stimuli is the difficult distractor, that can share two of three possible feature combinations with the target (i.e. colour and orientation or middle symbol and orientation). Relevance, as mentioned earlier, is in attentional capture literature the same as the difficult distractor sharing many features with the target. According to models of attentional capture, highly salient or relevant distractors can briefly capture the attention, thereby eliciting an N2pc contralateral to the distractor. In other words, the salient distractor briefly becomes the “target”. How is this possible? The short answer is that attention is blind as to what constitutes a “correct target”. Attention is by definition whatever one attends to, be it a target or a difficult distractor. Hence, if a difficult distractor captures the attention this naturally produces an N2pc contralateral to the difficult distractor, since it has become the focus of attention. And since both salient distractor and target were located in the same visual field, this would result in an N2pc for the difficult distractor in the same contralateral hemifield as the target elicited N2pc. The present study also included a condition where targets and distractors appeared on horizontally opposite sides. The finding that the vertically opposite condition elicited a larger N2pc in relation to the horizontally opposite and diagonally opposite conditions is difficult to interpret. There have been no previous studies separating between diagonally opposite and horizontally opposite conditions. Both conditions are usually referred to as “opposite side condition” since they both have targets and difficult distractors on opposite sides of the visual field. The finding that the horizontally opposite side condition elicited a smaller N2pc could be explained by the fact that some trials instead only elicited a PD component when attentional capture was successfully inhibited (Hickey et al., 2009; Sawaki & Luck, 2010). With regards to differences between upper and lower visual field, earlier research has found that the N2pc is larger when targets are presented in the lower

visual field (Luck, Girelli et al., 1997). In line with earlier studies, the present study found that lower visual field stimuli elicited a larger N2pc when compared to upper visual field stimuli. The difference in N2pc amplitude between upper and lower visual field has been attributed to the way the primate visual system is arranged and how the electrodes are positioned on the scalp during EEG recording. Topographic mapping of visual stimuli has found that lower-field representations are located in the dorsolateral occipital part of V4, also known as LO1 in the human brain as opposed to V4d in macaques, located directly underneath the occipital-temporal electrode sites (Serano et al., 1995). According to Luck, Girelli et al. (1997) this would explain why the lower-visual field targets elicit a large ERP deflection at these sites. Upper-field representations have been located in the ventral surface of the occipital part of V4, which is farther away from the scalp which in turn could explain the weaker ERP signal. And as mentioned earlier this seems to coincide with the location of the occipital-temporal electrode sites PO7 and PO8 where the N2pc is largest (Luck, 2012; Luck, Girelli et al., 1997; Serano et al., 1995).

The PD component The first comparison between contralateral and ipsilateral sides, when all relative placements were included, did not reveal a PD component. Contrary to its counterpart (the N2pc component), the PD component has been shown to be more difficult to produce (Gaspelin & Luck, 2018b). However, when separating the different relative placements, a significant effect was found when target and difficult distractor were located diagonally opposite. In contrast to the N2pc there was no significant effect for the horizontally opposite and the vertical opposite conditions. The result is interesting since according to Hickey et al. (2009), when difficult distractor and target appear on opposite sides, they should sum together to form a large N2pc component. The present study did find an N2pc when the target and difficult distractor were on diagonally opposite sides of the visual field, which might suggest that some of the amplitude difference could be attributed to the PD component. While the present study measured a different time-window for the PD than for the N2pc, previous studies have suggested that the late PD actually starts during the time-window for the N2pc and continues after the N2pc has ended (Sawaki et al., 2012). It is, however, difficult to say if the two components did sum up to produce an N2pc since no measurements were taken during the N2pc time-

window for the PD component. Furthermore, the present study measured a smaller N2pc for the diagonally opposite side condition than for the vertically opposite condition and since the former should lead to a larger N2pc (due to the summing of the two components) the present result is somewhat in contradiction to earlier studies (e.g. Hickey et al., 2009). It is also worth mentioning that Hickey et al., (2009) never actually compared conditions where targets and distractors were positioned on opposite sides or the same side of the visual field. The suggestion that the N2pc sums up to a large component when there is an NT and a PD component appearing during the same time-window, was a purely hypothetical argument based on separate measurements from both components. By inverting the PD component and adding it to the NT component Hickey et al. (2009) produced a hybrid component and compared it to the N2pc component. Since the amplitudes and waveforms seemed to resemble each other the authors suggested that the N2pc was the sum of the two components appearing during the same time-window, albeit on opposite polarities. The finding that the vertically opposite condition produced a smaller PD component is probably best explained by attentional capture. If the target and difficult distractor are located in the same visual field, this could lead to erroneous processing of the difficult distractor (indexed by N2pc) (e.g. Hickey et al., 2009; Sawaki & Luck, 2010). The present study as mentioned before elicited a larger N2pc for the vertically opposite condition. It is however, difficult to say whether the possible attentional capture was a result of both the target and the difficult distractor being more salient than the other grey distractors, or because they both shared multiple features which in turn resulted in high relevance for the difficult distractor as well as the target. In the case of the former, the attentional capture could be explained by stimulus driven theories that suggest that salient stimuli catch the attention irrespective of the task-relevant goals (e.g. Theeuwes, 1992, 2010). In case of the latter, it would be consistent with goal-driven theories which suggest that salience alone is not enough for attention to be captured, but that other features relevant to the task might influence how much a distractor will interfere with target location (e.g. Lien et al., 2008). Either way, if attentional capture did in fact occur it would result in an N2pc for the difficult distractor as discussed above, since the difficult distractor for a brief moment became the focus of attention, thus not eliciting a PD for the difficult distractor.

It is also possible that attention was captured on some trials (indexed by an N2pc) while the difficult distractor on some trials was successfully inhibited (indexed by the PD) (Weaver, van Zoest, & Hickey, 2017). Alternatively, the difficult distractor was indeed suppressed at first (indexed by a PD) but this suppression was not enough to prevent capture by the difficult distractor (indexed by the N2pc) (Gaspelin & Luck, 2018b). This is in line with the signal suppression hypothesis by Gaspelin and Luck, (2018a), where salient distractors can attract attention if they are not actively suppressed by top-down mechanisms. The signal suppression hypothesis is also a good way to avoid getting entangled in the decades long debate on whether attentional capture is a result of stimulus driven or goal drivel processes. And since the difficult distractor in the present study could be argued to be both salient and relevant it is difficult to say which theory of attentional capture would fit best. Earlier studies on attentional capture, have also suggested that if a difficult distractor is successfully suppressed this elicits a PD component but not an N2pc (Hickey et al., 2009; Sawaki & Luck, 2010). This could explain the larger PD component for the diagonally opposite condition. Since the target and the distractor were located on opposite sides of the visual filed the risk for illusory conjunctions could be smaller thus leading to successful suppression (Treisman, 1988; Treisman & Schmidt, 1982). However, Hickey et al. (2009) and Sawaki and Luck (2010) recorded a PD component during an earlier time-window than the present study, which makes the studies difficult to compare. Other studies have suggested that the late PD could reflect an active terminating of attention after completion of perception (Sawaki et al., 2012). Further, according to the authors, this could be the result of the same inhibition mechanism that normally is recorded contralateral to difficult distractors. Previous studies have found that after attention has shifted to a location it is followed by inhibition of return (IOR) to the previously attended location. This is marked by slower reaction times when targets appear in previously attended locations and it appears around 300 ms after stimulus onset, which is around the same time the late PD component starts (Dukewich & Klein, 2015; Klein, 2000; Posner, Rafal, Choate & Vaughan 1985). It is not clear as of yet if the late PD is the electrophysiological index of IOR and more research needs to be done before any definite conclusions can be made (Sawaki et al., 2012). However, as in the case of attentional capture studies, the differences between the study performed by Sawaki et al. (2012) and the present study render direct

comparisons difficult. Sawaki et al. (2012) recorded a PD component after the N2pc in the same ERP waveform, while the present study did not see any evidence of a PD component in the same ERP waveform as the N2pc. The present study also included a condition where difficult distractor and target appeared on horizontally opposite sides. While the results were not significant, the finding was still somewhat unexpected. As mentioned earlier previous studies do not separate between what in the present study was called diagonally opposite and horizontally opposite conditions, since they both have targets and difficult distractors on opposite sides of the visual field (Hickey et al., 2009; Kiss et al., 2012; Sawaki & Luck, 2010). The literature on attentional capture would suggest that successful inhibition occurs more easily when target and difficult distractor appear in the opposite visual field which should in turn lead to a PD component (Hickey et al., 2009; Sawaki & Luck, 2010). One possible explanation is that the target and the difficult distractor could appear closer to each other in the horizontally opposite condition than in the diagonal opposite condition. This could in turn have led to illusory conjunctions if the distractor was processed as a target (Treisman, 1988; Treisman & Schmidt, 1982). With regards, to the difference between distractors appearing on the upper visual field and the lower visual field, earlier studies have suggested that a PD component is larger for upper visual field distractors (Hickey et al., 2009). According to the author the PD could first and foremost be an index of spatial attention since their study found that PD occurs over more medial and dorsal areas, whereas NT occurs at more ventral and lateral areas, (i.e. representing processing on both the dorsal and lateral visual streams) (Mishkin & Ungerleider, 1982). The present study did not find a significant difference between upper and lower visual field difficult distractors. This could be the result of not having enough trials where a PD was successfully elicited. But whether this was due to attentional capture or the low power of the experiment is hard to say just by looking at the results. It might be that to replicate the finding by Hickey et al. (2009), some form of isolation of the difficult distractor would need to be carried out. The finding that the vertically opposite and the horizontally opposite conditions did not elicit a strong PD but an N2pc component could, however, be interpreted as the latter having precedence over the former when it comes to visual attention in general. Attention could first and foremost be a case of target

enhancement (indexed by the N2pc), but if a distractor with high salience or relevance was presented at the same time, only then would inhibition be necessary (indexed by the PD). The suggestion that target enhancement may play a bigger role than distractor suppression is supported by earlier single-unit recordings (McAdams & Maunsell, 1999; Roelfsema et al., 1998) and earlier models of visual attention, (e.g. biased competition model and feature integration theory) ( Desimone & Duncan, 1995; Moran & Desimone, 1985; Treisman, 1988; Treisman & Schmidt, 1982). Both single unit recordings and different models of visual attention simply state that attentional demands are higher when distractor items are included in search arrays. Similarly, both speak of attentional modulation in favour of the target by increasing priority to features related to the target. This could be seen as an active act of lifting up the features belonging to the target which in turn would lead to the distractors indirectly being filtered out (Luck, 2012). A good analogy is when you grab a hand full of gravel and sand and lift it up. As you proceed to lift up the mix of gravel and sand, the bigger gravel will not fall through your fingers while at the same time gravity does its work by pulling down the finer grains of sand through your fingers. Although gravity (definitely) is a force of its own, in this case it should be viewed as an indirect force that only takes place as a result of lifting the hand. Lastly, while there have been studies directly relating distractor suppression to cortical changes in the visual cortex, from V1 to higher extrastriate areas (e.g. Ruff & Driver, 2006; Slotnick et al., 2003), the amount of studies pale in comparison to the amount of research related to target enhancement, since the former have not yet benefitted from decades of research as is the case for the latter. The findings that the PD component seems to vary depending on the task and experiment, has also created additional confusion as to what the PD actually stands for (Gaspelin & Luck, 2018b). Similarly, the differences between the findings of the present study and previous studies seem to suggest that the PD is more complex than earlier thought. A late PD component was found in the diagonally opposite condition. But as both the actual experimental paradigm and results differ on many levels it is hard to say if the PD recorded between 300-400 ms in this study was the same PD component that has been observed in previous studies during the same time-window (e.g. Sawaki et al., 2012). However, since the experimental paradigm in the present study was a compromise between three separate studies with three separate aims,

both the undertaking as well as results of the experiment should be viewed as a success.

Conclusion

The principal objective of the present study was to see if a conjunction visual search task could elicit both an N2pc and a Pd component. The results show a clear N2pc component in relation to all combinations of target and difficult distractor placement. A larger mean amplitude was measured when target and difficult distractor were located vertically opposite. The results are not in line with previous studies that measured a larger N2pc when targets and distractors were located on opposite sides of the visual field, (in the present study separated into horizontally opposite and diagonally opposite). A plausible explanation for the contradicting findings in the present study could be that the difficult distractor appearing on the same side as the target became the focus of attention through attentional capture. Because the target and difficult distractor resembled each other, this could according to earlier models of visual attention have led to illusory conjunctions when both items were located in the same visual field. When all upper visual field and lower visual field targets were compared against each other, the results show a larger N2pc component for targets appearing in the lower visual field, which is in line with previous studies. No PD component was elicited when all relative placements were combined. Since the PD has been shown to vary depending on the experimental paradigm it is difficult to draw any conclusions as to why a PD was not elicited in the combined comparison. However, when separating the relative placements, a larger mean amplitude for the late PD component appearing between 300-400 ms was measured for the diagonally opposite condition. Earlier studies have shown that difficult distractors are more successfully suppressed when they occur farther apart from each other. As in the case of the N2pc component, a plausible explanation for the present finding is that attentional capture led to the difficult distractor in the vertically opposite condition being processed as a target. In contrast to earlier research the PD did not appear larger for difficult distractors appearing in the upper visual field. This could be a result of the way the study was carried out and, as mentioned above varying results have been obtained depending on the experimental paradigm.

Lastly, the present study also included a condition where the difficult distractor and target appeared horizontally opposite. But, as mentioned in the discussion, less is known about differences between diagonally opposite and horizontally opposite conditions as both are usually referred to synonymously as opposite side conditions. A possible explanation for the small amplitude for both the N2pc and the PD in the horizontally opposite condition could be attributed to the fact that the target and difficult distractor could appear closer together on some trials due to the way the search array was designed. The search array consisted of four quadrants each containing three possible positions, which meant that in the horizontally opposite condition target and difficult distractor could be separated by only one empty position between them. This could in turn have led to both the target and the difficult distractor occupying the same receptive field of a neuron, which in turn could have led to illusory conjunctions as both items looked similar. However, bearing in mind that the study was done with a small sample size all, conclusions should be regarded as tentative at best. Future studies could research whether the differences found between horizontally opposite and diagonally opposite persist when bigger sample sizes are used. If this is the case, then it should be taken into account when comparing studies measuring differences between vertically opposite conditions and conditions where target and difficult distractor appear on opposite sides of the visual field.

The roaring of the engines diminished, the squeaking rhetoric lapsed into an inarticulate murmur, and as the intruding noises died away, out came the frogs again, out came the uninterruptable insects, out came the mynah birds. “Karuna, Karuna.” And a semitone lower, “Attention”. (Huxley, 1962/2009, p. 534).

References

Bacon, W. F., & Egeth, H. E. (1994). Overriding stimulus-driven attentional capture. Perception & Psychophysics, 55(5), 485–496. https://doi.org/10.3758/BF03205306

Carrasco, M. (2011). Visual attention: The past 25 years. Vision Research, 51(13), 1484–1525. doi: 10.1016/j.visres.2011.04.012.

Chelazzi, L., Duncan, J., Miller, E. K., & Desimone, R. (1998) Responses of Neurons in Inferior Temporal Cortex During Memory- Guided Visual Search. Journal of Neurophysiology, 80(6), 2918-2940. https://doi.org/10.1152/jn.1998.80.6.2918

Chelazzi, L., Miller, E. K., Duncan, J., & Desimone, R. (1993). A neural basis for visual search in inferior temporal cortex. Nature, 363(6427), 345-7. doi:10.1038/363345a0

Delorme, A., & Makeig, S. (2004). EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods. 134(1):9-21. doi: 10.1016/j.jneumeth.2003.10.009

Desimone, R., & Duncan, J. (1995). Neural mechanisms of selective visual attention. Annu Rev Neurosci. 18,193–222. doi:10.1146/annurev.ne.18.030195.001205

Dukewich, K. R., & Klein, R. M. (2015). Inhibition of return: a phenomenon in search of a definition and a theoretical frame-work. Attention, Perception & Psychophysics, 77, 1647–1658. https://doi.org/10.3758/s13414-015-0835-3

Dumoulin, S. O., & Wandell, B. A. (2008). Population receptive field estimates in human visual cortex. Neuroimage, 39(2), 647-660. doi: 10.1016/j.neuroimage.2007.09.034

Eimer, M. (1996). The N2pc component as an indicator of attentional selectivity. Electroencephalography and Clinical Neurophysiology, 99(3), 225–234. https://doi.org/10.1016/0013-4694(96)95711-9

Gaspar, J. M., Christie, G. J., Prime, D. J., Jolicoeur, P., & McDonald, J. J. (2016). Inability to suppress salient distractors predicts low visual working memory capacity. Proceedings of the National Academy of Sciences, 113(13), 3693-3698. https://doi.org/10.1073/pnas.1523471113

Gaspar, J. M., & McDonald, J. J. (2014) Suppression of salient objects prevents distraction in visual search. The Journal of Neuroscience, 34(16), 5658 –5666. doi:10.1523/JNEUROSCI.4161-13.2014

Gaspelin, N., & Luck, S. J. (2018a). Combined electrophysiological and behavioural evidence for the suppression of salient distractors. Journal of Cognitive Neuroscience, 30(9), 1265-1280. https://doi.org/10.1162/jocn_a_01279

Gaspelin, N., & Luck, S. J. (2018b). The Role of Inhibition in Avoiding Distraction by Salient Stimuli. Trends in cognitive sciences, 22(1), 79-92. https://doi.org/10.1016/j.tics.2017.11.001

Hickey, C., Di Lollo, V., & McDonald, J. J. (2009). Electrophysiological indices of target and distractor processing in visual search. Journal of Cognitive Neuroscience, 21(4), 760–775. https://doi.org/10.1162/ jocn.2009.21039

Hollingworth, A., & Luck, S. J. (2009). The role of visual working memory in the control of gaze during visual search. Attention, Perception, & Psychophysics, 71(4), 936-949. doi:10.3758/APP.71.4.936

Hopf, J. M., Boehler, C. N., Luck, S. J., Tsotsos, J. K., Heinze, H. J., & Schoenfeld, M. A. (2006). Direct neurophysiological evidence for spatial suppression surrounding the focus of attention in vision. Proceedings of the National Academy of Sciences, 103(4), 3532–3540. doi: 10.1073/pnas.0507746103

Hopf, J. M., Boelmans, K., Schoenfeld, M. A., Luck, S. J., & Heinze, H. J. (2004). Attention to features precedes attention to locations in visual search: evidence from electromagnetic brain responses in humans. The Journal of neuroscience, 24(8), 1822–1832. https://doi.org/10.1523/JNEUROSCI.3564-03.2004

Huxley, A. (2009). Island. New York, Ny: Harper Perennial. (Original work published 1962).

James, W. (2017). The Principles of Psychology, Vols. 1-2. (n.p.): Pantianos Classics. (Original work published 1890).

Kiss, M., Grubert, A., Petersen, A., & Eimer, M. (2012). Attentional capture by salient distractors during visual search is determined by temporal task demands. Journal of Cognitive Neuroscience, 24(3), 749–759. doi: 10.1162/jocn_a_00127

Klein, R. M. (2000). Inhibition of return. Trends Cogn Sci. 4(4),138-147. doi: https://doi.org/10.1016/S1364-6613(00)01452-2

Kravitz, D. J., Saleem, S. S., Baker, C. I., Ungerleider, L. G., & Mishkin, M. (2013). The ventral visual pathway: An expanded neural framework for the processing of object quality. Trends Cogn Sci., 17(1), 26–49. doi: 10.1016/j.tics.2012.10.011

Lien, M. C., Ruthruff, E., Goodin, Z., & Remington, R. W. (2008). Contingent attentional capture by top-down control settings: Converging evidence from event- related potentials. Journal of Experimental Psychology: Human Perception and Performance, 34, 509–530. doi: 10.1037/0096-1523.34.3.509

Lopez-Calderon, J., & Luck, S. J. (2014). ERPLAB: an open-source toolbox for the analysis of event-related potentials. Frontiers in human neuroscience, 8, 213. https://doi.org/10.3389/fnhum.2014.00213

Luck, S. J. (2012). Electrophysiological correlates of the focusing of attention within complex visual scenes: N2pc and related ERP components. In S. J. Luck, & E. S. Kappenman (Eds.), The Oxford hand- book of event-related potential components (pp. 329–360). Oxford, UK: Oxford University Press.

Luck, S. J., Chelazzi, L., Hillyard, S. A., & Desimone, R. (1997). Neural mechanisms of spatial selective attention in areas V1, V2, and V4 of macaque visual cortex. J. Neurophysiology, 77, 24–42. doi:10.1152/jn.1997.77.1.24

Luck, S. J., Girelli, M., McDermott, M. T., & Ford, M. A. (1997). Bridging the gap between monkey neurophysiology and human perception: an ambiguity resolution theory of visual selective attention. Cogn Psychol, 33,64–87. https: //doi.org/10.1006/cogp.1997.0660

Luck, S. J., & Gold, J. M. (2008). The construct of attention in schizophrenia. Biological Psychiatry, 64(1), 34–39. https://doi. org/10.1016/j.biopsych.2008.02.014

Luck, S. J., & Hillyard, S. A. (1994). Spatial filtering during visual search: Evidence from human electrophysiology. Journal of Experimental Psychology: Human Perception and Performance, 20, 1000–1014. doi:10.1037//0096-1523.20.5.1000

McAdams, C. J., & Maunsell, J. H. R. (1999). Effects of attention on orientation- tuning functions of single neurons in macaque cortical area V4. Journal of Neuroscience, 19 (1) 431-441. doi: https://doi.org/10.1523/JNEUROSCI.19-01- 00431.1999

Mishkin, M., & Ungerleider, L. G. (1982). Contribution of striate inputs to the visuospatial functions of parieto-preoccipital cortex in monkeys. Behavioural brain research, 6(1), 57-77. https://doi.org/10.1016/0166-4328(82)90081-X

Moran, J., & Desimone, R. (1985). Selective attention gates visual processing in the extrastriate cortex. Science, 229(4715), 782–784. doi: 10.1126/science.4023713

Mounts, J. R. W., & Gavett, B. E. (2004) The role of salience in localized attentional interference. Vision Research, 44(13), 1575–1588. https://doi.org/10.1016/j.visres.2004.01.015

Papaioannou, O., & Luck, S. J. (2020). Effects of eccentricity on the attention-related N2pc component of the event-related potential waveform. Psychophysiology, 57(5), e13532. doi: 10.1111/psyp.13532

Posner, M. I., Rafal, R. D., Choate, L. S., & Vaughan, J. (1985). Inhibition of return: Neural basis and function. Cognitive Neuropsychology, 2(3), 211–228. https://doi.org/10.1080/02643298508252866

Roelfsema, P. R., Lamme, V. A., & Spekreijse, H. (1998). Object-based attention in the primary visual cortex of the macaque monkey. Nature, 395, 376–381. https://doi.org/10.1038/26475

Ruff, C. C., & Driver, J. (2006). Attentional preparation for a lateralized visual distractor: Behavioral and fMRI evidence. Journal of Cognitive Neuroscience, 18(4), 522–538. doi: 10.1162/jocn.2006.18.4.522

Sawaki, R., Geng, J. J., & Luck, S. J. (2012) A Common neural mechanism for preventing and terminating the allocation of attention. Journal of Neuroscience, 32 (31) 10725-10736. doi: 10.1523/JNEUROSCI.1864-12.2012

Sawaki, R., & Luck, S. J. (2010). Capture versus suppression of attention by salient singletons: electrophysiological evidence for an automatic attend-to-me signal. Attention Perception Psycho- phys. 72, 1455–1470. doi: 10.3758/APP.72.6.1455

Sawaki, R., & Luck, S. J. (2014). Chapter 2 - How the Brain Prevents and Terminates Shifts of Attention. In G. R. Mangun (Ed), Cognitive Electrophysiology of Attention. (PP. 16-29). Academic Press. https://doi.org/10.1016/B978-0-12-398451-7.00002-6

Schiller, D. (1994). The little Zen companion. New York: Workman Publishing, p17.

Serano, M. I., Dale, A. M., Reppas, J. B., Kwong, K. K., Belliveau, J. W., Brady, T. J., . . . Tootel, R. B. H. (1995). “Borders of multiple visual areas in humans revealed by functional magnetic resonance imaging. Science, 268(5212), 889-893. doi:10.1126/science.7754376

Slotnick, S., Schwarzbach, J. V., & Yantis, S. (2003). Attentional inhibition of visual processing in human striate and extrastriate cortex. NeuroImage, 19(4),1602-11. doi: 10.1016/S1053-8119(03)00187-3

Tay, D., Harms, V., Hillyard, S. A., & McDonald, J. J. (2019). Electrophysiological correlates of visual singleton detection. Psychophysiology, 56(8), e13375. https://doi.org/10.1111/psyp.13375

Theeuwes, J. (1992). Perceptual selectivity for color and shape. Perception & Psychophysics, 51, 599–606. https://doi.org/10.3758/BF03211656

Theeuwes, J. (2010). Top–down and bottom–up control of visual selection. Acta Psychologica, 135(2), 77-99. https://doi.org/10.1016/j.actpsy.2010.02.006

Tootel, R. B. H., Hadjikhani, N., Hall, E. K., Marret, S., Vanduffel, W., Vaughan, J. T., & Dale, A. M. (1998). The retinotopy of visual spatial attention. Neuron, 21, 1409- 1422. https://doi.org/10.1016/S0896-6273(00)80659-5

Treisman, A. (1988). "Features and objects: the fourteenth Bartlett Memorial Lecture." Quarterly Journal of Experimental Psychology, 40, 201–236. https://doi.org/10.1080/02724988843000104

Treisman, A., & Schmidt, H. (1982). "Illusory conjunctions in the perception of objects." Cognitive Psychology, 14, 107–141. doi:10.1016/0010-0285(82)90006-8

Weaver, M. D., van Zoest, W., & Hickey, C. (2017). A temporal dependency account of attentional inhibition in oculomotor control. Neuroimage, 147, 880–894. http://dx.doi.org/10.1016/j.neuroimage.2016.11.004

Woodman, G. F., Luck, S. J., & Schall, J. D. (2007). The role of working memory representations in the control of attention. Cereb Cortex, 17(1), 118–124. doi: 10.1093/cercor/bhm065