Vertical asymmetries and inhibition of return: Effects of spatial and non-spatial cueing on behavior and visual ERPs

Vertical asymmetries and inhibition of return: Effects of spatial and non-spatial cueing on behavior and visual ERPs Authors: Francisco-Javier Gutiérrez-Domínguez, Paula Pazo-Álvarez, Sonia Doallo, Luis J. Fuentes, Laura Lorenzo-López, Elena Amenedo. This is the peer reviewed version of the following article: Gutiérrez-Domínguez, F-J., Pazo- Álvarez, P., Doallo, S., Fuentes, LJ., Lorenzo-López, L., & Amenedo, E. (2014).Vertical asymmetries and inhibition of return: Effects of spatial and non-spatial cueing on behavior and visual ERPs. International Journal of Psychophysiology, 91, 123-131. doi: 10.1016/j.ijpsycho.2013.12.004 This article may be used for non-commercial purposes in accordance with Elsevier and International Organization of Psychophysiology terms and conditions for use of self-archived versions. Post-print (final draft post-refereeing) 2 Vertical asymmetries and inhibition of return: Effects of spatial and Non-spatial cueing on behavior and visual ERPs Authors: Francisco-Javier Gutiérrez-Domíngueza, Paula Pazo-Álvareza, Sonia Doalloa, Luis J. Fuentesb, Laura Lorenzo-Lópezc, Elena Amenedoa. a Universidade de Santiago de Compostela, Spain b Universidad de Murcia, Spain c Universidade de A Coruña, Spain Corresponding author at: Campus Sur s/n, 15782, Santiago de Compostela, Galicia, Spain. Tel.: +34 981 563 100x13916; fax: +34 981 528 071. E-mail address: elena.amened[email protected]s (E. Amenedo). Post-print (final draft post-refereeing) 3 Abstract The mechanisms underlying inhibition of return (IOR) are still under debate. Besides the probable implication of several processes in its generation, a reason for this uncertainty may be related to experimental factors affecting the presence, time course, and magnitude of IOR. Two of them may be related to the arrangement of the stimuli in the visual field that could cause possible interactions between IOR and response conflict effects (horizontal arrangements) or between IOR and perceptual asymmetries (vertical arrangement). The purpose of the present study was to explore location and color cueing effects with a vertical arrangement of stimuli, free of S–R compatibility effects. To examine this possibility, a cue-back task with stimuli in the vertical meridian was employed. Targets could randomly and equiprobably appear at cued or uncued locations, or with cued or uncued color. These cueing effects were analyzed on behavior and ERPs separately for upper and lower visual fields (UVF and LVF). Under location cueing, behavioral responses were slower (spatial IOR) in both hemifields. In the ERPs, N1 reductions were observed in both visual fields although with different modulations in their latency and scalp distribution. In the P3 rising beginning, posterior negative deflections in the LVF (Nd) and anterior positive deflections (Pd) in the UVF were observed. Under color cueing, P3 amplitude was reduced in the UVF accompanied by no behavioral effects. These results suggest that different patterns of brain activation can be obtained in upper and lower visual fields under spatial- and non-spatial cueing conditions. Post-print (final draft post-refereeing) 4 Introduction When an uninformative peripheral cue appears in our visual field it automatically attracts our attention. If within a short time interval (approximately 250 ms following the cue) a target is presented at the same location as the cue, response times (RTs) are faster for that target than for a target appearing at a different location. However, if the time between the cue and the target is longer, RTs for targets at the cued location becomes lower. This effect was firstly explained as an inhibitory mechanism that prevents the processing of information appearing at explored locations to optimize the orienting of the visual system to novelty (Posner and Cohen, 1984), and it was later called Inhibition of Return (IOR; Posner et al., 1985). Since its discovery, IOR has been observed in a wide variety of experimental situations within the visual, auditory, and tactile modalities (e.g., Spence et al., 2000). IOR has also been observed across a variety of tasks, including detection, localization, and discrimination (see Klein (2000) for a review), and even in natural scenes (Klein and MacIness, 1999). IOR-like effects have also been observed to nonspatial dimensions of both cue and target stimuli such as color, shape, and semantics (non-spatial IOR; see, for example Chen et al., 2010; Fuentes et al., 1999; Hu et al., 2011). This ubiquity suggests that the mechanisms underlying IOR are important for the selection of information. Nevertheless, the neural substrates and functional significance of IOR are still under debate. Current evidence indicates that IOR mayarise from a combination of inhibited perceptual processing (Handy et al., 1999; McDonald et al., 1999; Prime and Ward, 2004; Prime et al., 2006), a more conservative response criterion on cued trials relative to uncued trials (Ivanoff and Klein, 2001, 2006), and an inhibition of motor (Pasttöter et al., 2008) and oculomotor programming (Ro et al., 2000). Given the evidence supporting several mechanisms, it has been proposed that IOR may arise from multiple processes (Kingstone and Pratt, 1999). In this context, Taylor and Klein (2000) proposed two mutually exclusive forms of IOR that depend essentially on whether the oculomotor system is activated (the motor form) or suppressed (the perceptual/attentional form). These forms have been recently observed both in behavioral execution and in visual event-related potential (ERP) results (Hilchey et al., 2013; Satel et al., 2013). Besides the probable implication of several processes in the generation of IOR, a reason for the current uncertainty on its origins may be related to several experimental factors affecting the presence, time course, and magnitude of IOR (Klein, 2000). In this regard, the most extensively used design to explore the effects of IOR has been the cue–target paradigm in the visualmodality (for a review, see Klein, 2000). In this paradigm, a peripheral cue is presented before the target stimulus at different cue-to-target time intervals (cue-to-target stimulus onset asynchrony, CTOA), and the differences between the responses tocued and uncued targets are examined. The fact that to obtain an IOR effect a CTOA longer than approximately 250 ms is necessary has been attributed to the need to disengage attention from the cued location before the presentation of the target stimulus (Posner et al., 1985; but see, for example, Chica and Lupiáñez, 2009; Riggio et al., 2004). However, the cue–target paradigm does not assure that the attentional focus has been disengaged from the cue at the time of target presentation (Prime et al., 2006). To overcome this limitation, an alternative paradigm, called the ‘cue-back design’, presents a second cue (the cue-back) during the CTOA interval at central fixation. This cue-back does not share any characteristic with either the cue or the target and plays the only role of attracting attention away from the cue to ensure that it has been reoriented away from the cued location. Post-print (final draft post-refereeing) 5 Another factor that may underlie the current uncertainty about the functional locus of the IOR effect is that related to the arrangement of the stimuli in the visual field. In this sense, the presentation of the stimuli along the horizontal axis has been one of the most frequently employed in this context (e.g. Fuchs and Ansorge, 2012; Taylor and Klein, 1998a; Wascher and Tipper, 2004). This arrangement, however, may result in an interaction of IOR effects with other related to the spatial relationships between the location of the target stimulus and the response hand (S– R compatibility). One of the most known is the Simon effect, which has been proposed to interact with IOR (see Ivanoff et al. (2002) for a review; Wang et al., 2013). To overcome possible interactions between IOR and spatial S–R compatibility effects, tasks presenting the stimuli along the vertical axis can be employed. Importantly, the perceptual characteristics of our visual hemifields along the vertical axis present several asymmetries (see Karim and Kojima (2010) for a recent review). On one hand, behavioral studies have found vertical asymmetries favoring the lower visual field (LVF) in contrast-sensitivity (Cameron et al., 2002; Carrasco et al., 2002), spatial resolution (Carrasco et al., 2002; Rezec and Dobkins, 2004), orientation (Raymond, 1994) and hue (Levine and McAnany, 2005). On the other hand, neurophysiological studies have also confirmed the higher sensitivity of the LVF to contrast patterns (Portin et al., 1999), high contrast checkerboards (Fioretto et al., 1995), and non-attended color (Czigler et al., 2004) or movement direction changes (Amenedo et al., 2007). Moreover, when studying visual ERP components, different patterns can be recorded due to the orientation of the cerebral tissue involved in the analysis of the stimuli, depending on the location in the visual field where stimuli are presented (Di Russo et al., 2001; Chica et al., 2010). Consequently, a main objective of the present research was to explore cueing effects with a vertical arrangement of stimuli, free of S–R compatibility effects. The existing difficulty to characterize the IOR functional significance and its neural locus, led several research groups to examine the underlying electrophysiological mechanisms of behavioral IOR effects, from target presentation to response execution. These studies revealed that it could be possible that a neural effect associated with IOR happens without its concomitant behavioral expression, as Klein (2000) has argued. In this sense, P1 and N1 components, related to information processing in visual areas, and known to be modulated by attention (for a review, see Luck et al. (2000) and Satel et al. (2013)) have been the most studied in IOR research. In this context, previous studies have found amplitude reductions in the P1 component for spatially cued targets (Chica and Lupiáñez, 2009; Chica et al., 2010; McDonald et al., 1999; Prime and Jolicoeur, 2009; Prime and Ward, 2004, 2006;Satel et al., 2013; Tian and Yao, 2008; Tian et al., 2011b; van der Lubbe et al., 2005; Wascher and Tipper, 2004), even when slower reaction times (RTs) were not observed (Doallo et al., 2004; Eimer, 1994; Hopfinger and Mangun, 1998). These effects have been interpreted as reflecting a suppression or inhibition of perceptual processing in visual areas of previously cued stimuli. However, no effects of IOR on P1 have also been reported (Hopfinger and Mangun, 2001; McDonald et al., 1999; Prime and Ward, 2006; van der Lubbe et al., 2005). The N1 component, which is considered as an electrophysiological index of discrimination processes within the focus of visuospatial attention (Vogel and Luck, 2000), has showed more divergent effects of IOR. Thus, reduced N1 amplitude in cued trials has been mainly observed in those studies using designs that included a cue-back stimulus, and in studies requiring a discrimination task (Prime and Ward, 2004, 2006; Prime et al., 2006; Prime and Jolicoeur, 2009). In other designs, enhanced N1 amplitude was found both along with (McDonald et al., 1999; Tian and Yao, 2008) or without (Eimer, 1994) a behavioral IOR effect. Another ERP that has shown cueing effects is the P3 component. The IOR effect on RTs has been also found to be associated Post-print (final draft post-refereeing) 6 with enhanced P3 amplitude on cued trials (McDonald et al., 1999). However, this effect has not been always reported, since Hopfinger and Mangun (2001) and Zhang et al. (2012) did not find P3 modulations when behaviorally significant IOR effects were present. The effects of cueing on P3 have been interpreted as a post perceptual effect more related to endogenous attention processes than to pure IOR (Chica and Lupiáñez, 2009). The comparison of the ERP wave forms between cueing conditions led several groups to analyze negative differences within different latency ranges (called in general Negative difference, Nd) in the IOR context, although no consensus has been reached on their direct relation to IOR effects. Thus, McDonald et al. (1999) explained the Nd component observed in their study (increased negativity within 100–200 ms in cued trials) as an index of sensory refractoriness caused by response to the cue. Posteriorly, Wascher and Tipper (2004) described three independent Nd components: Nd150 (140–160 ms), Nd250 (240–260 ms) and Nd310 (300–320 ms). They related the Nd150 to sensory refractoriness in the cued location, the Nd250 to inhibitory processes associated with the demands of the task, and the latter, Nd310, observed only when a behaviorally IOR effect was found, to the effort to allocate the focus of attention to a previously inhibited location. However, Prime and Ward (2006) and Prime and Jolicoeur (2009) did not relate directly the processes underlying the Ndwith the IOR generation per se.More recently, three differential waves (called Pd200, Nd240, and Nd280) have also been described associated to IOR effects (Tian et al., 2011a). Taking all the above into account, the purpose of the present study was to explore the neurocognitive correlates (behavioral and ERP data) of spatial and non-spatial cueing effects. To overcome S–R compatibility effects that might interact with IOR effects, a cue-back task with stimuli in the vertical meridian was employed. Finally, due to the well-known vertical asymmetries in visual processing, we tested the possible differences between UVF and LVF when the location and color of target stimuli were cued in a color discrimination task. Method Participants Twenty healthy naive volunteers (12 females) participated in the experiment. Participants mean age was 24.56 ± 5.86 (19–37 years), and two of them were left-handed. All participants reported having normal or corrected-to-normal vision. They obtained a monetary compensation for their participation. Stimuli and experimental procedure During the task (see Fig. 1), one central and two peripheral (external edge 4.5° of visual angle from the center of the screen) light gray boxes (RGB 200,200,200, 1.5° × 1.5° of visual angle) were always present on the vertical meridian of a computer screen (100 Hz resolution). A central fixation cross (RGB 150,150,150, 0.1° × 0.1° of visual angle) was also present and participants were instructed to maintain central fixation on it during the task performance. Each trial began with a 1500 ms blank screen (RGB 50,50,50, average luminance 2.4 cd/m2) that defined the background screen. After this, a blue (RGB 0,0,255, average luminance 8.3 cd/m2) or red (RGB 175,0,0, average luminance 8.2 cd/m2) patch was presented during 100 ms filling one of the two peripheral boxes (0.5 probability). This patch served as a cue for location or color dimension, and it was uninformative with regard to both location and color dimensions of the target. After a new blank screen of 500 ms duration, a cue-back consisting of a green patch (RGB 0,95,0, average luminance 8.4 cd/m2) filling the central box was presented for 100 ms. After another blank Post-print (final draft post-refereeing) 7 interval of 1300 ms, a target was presented until response or for a maximum of 1500 ms. Target stimuli consisted of a blue or red patch (0.5 probability), identical to the cue, filling the upper or lower box (0.5 probability). Target shared color or location dimension with the cue in 50% of trials. The time interval comprised between the cue onset and the target onset defined a cuetotarget onset asynchrony (CTOA) of 2000 ms1 (see Fig. 1). Four experimental conditions were obtained by combining cue and target color and location: trials with both target location and color cued by the first peripheral stimulus (Location Old Color Old, LOCO); target location cued, but not color (Location Old Color New, LOCN); target color cued, but not location (Location New Color Old, LNCO); and neither location nor color of the target cued by the first peripheral stimulus (Location New Color New, LNCN). Participants were asked to respond to target color (red or blue) irrespective of its location by pressing one button (Response Box RB-834 model, Cedrus Corporation) with their righthand to one color and another button with their left hand to the other color. The assignment of response hand to each color was counter balanced across participants. The task was divided in 25 blocks of 64 trials, with the different trial conditions randomly intermixed in each block. Short breaks, where lengths were controlled by subjects, were allowed between blocks. In order to examine the differences between spatial and non-spatial cueing and the possible interactions between them, we compared the four trial conditions (LOCN as spatial cueing condition, LNCO as non-spatial cueing condition, LOCO as the interaction condition, and LNCN as the condition free from cueing effects). Moreover, we performed the statistical analyses taking into account each of the visual fields where the target was presented (LVF or UVF). Recording and analysis Behavioral data Reaction times (RTs) and accuracy were on-line recorded for all participants in all conditions. Only RT values associated with correct responses were considered for data analyses. Responses were considered correct when RTs were faster than 1500 ms.Mean correct RTs and Error rates (%) were submitted to a repeated measures analysis of variance (ANOVA) with cueing condition (LNCN, LNCO, LOCN, and LOCO), and visual field (LVF vs. UVF) as within-subject factors (SPSS Statistical Package, v19, IBM Inc.). Whenever appropriate, degrees of freedom were corrected by the conservative Greenhouse-Geisser estimate. An alpha level of .05 was used for all analyses. Post hoc comparisons were made to determine the significance of pair-wise contrasts when appropriate, using the Bonferroni adjustment for multiple comparisons. Electroencephalographic (EEG) recording The recordings were made in an electrical shielded and sound attenuated room. Participants were sitting in an armchair placed at 112 cm distance from the computer screen. Continuous EEG activity was recorded with Brain Vision Recorder (Brain Products, Inc.) from 60 scalp Ag–AgCl electrodes placed according to the extended 10/20 International System. The cephalic electrodes were referred to the nose tip and grounded with an electrode placed at 10% of the nasion–inion distance above nasion. Vertical and horizontal electrooculogram (EOG) was recorded from above and below the participant's left eye and from the outer canthi of both eyes, respectively. Electrode impedances were kept below 10 kΩ. The sampling rate was 500 Hz/channel. The EEG signal was continuously amplified (10 K) and filtered online with a band pass of 0.05–100 Hz. EEG analysis Post-print (final draft post-refereeing) 8 Vision Analyzer Software (version 2.0, Brain Products, Inc.) was used for off-line processing. The EEG was digitally filtered with a band-pass of 0.1–30 Hz. Filtered EEG was segmented into epochs of 1500 ms poststimulus and 500 ms pre-stimulus to obtain the ERPs to the target stimulus for each participant, visual field (LVF, UVF) and cueing condition (LOCN, LNCO, LNCN, LOCO) separately. Ocular artifacts associated with blinks and vertical eye movements were removed from the EEG employing the Gratton et al. (1983) method, and EEG epochs exceeding ±100 μV, and/or containing horizontal eye movements were rejected and excluded from averaging, as well as epochs associated with incorrect or no responses. After this procedure, a mean percentage of 76.7% correct trials across conditions was included into the average to obtain the ERP waveforms, and a mean percentage of 16.6% of trials were rejected from averaging. To first explore the effects of the experimental manipulation with a blind method for selecting the time intervals and the electrodes with significant differences among cueing conditions, the targetlocked ERP waveforms across all electrodes and along the entire epoch for each participant, visual field, and condition were submitted to separate spatiotemporal analyses with BESA Statistics Software (v1.0, May 2012; BESA GmbH, Inc., http://www.besa.de/products/besa_statistics/). On these data, to calculate the time intervals and the electrodes with significant amplitude differences between conditions in each participant, an initial paired t-test (alpha level 0.05) was computed per data-point, electrode, and participant in each visual field separately. The resulting timewindows with significant differences in amplitudes among conditions were subsequently passed onto a cluster-based permutation testing for each visual field separately with correction for multiple comparisons. In this procedure, clustering in time (across time points) and space (across electrodes) is based on the results of the preliminary t-test. Depending on the cluster-alpha setting, adjacent data points are subsumed to form a cluster. The significance of these data clusters is probed during permutation testing. The main idea behind this permutation test is that if a statistical effect is found over an extended time period in several neigh boring channels, it is unlikely that this effect occurred by chance. For the present analyses, 1000 permutations with a 4 cm distance between neighbor electrodes, and with an initial alpha level of 0.05, were executed. Finally, the mean amplitude values of the time intervals and electrodes where permutations showed significant differences were calculated and subsequently submitted to parametric statistical testing by means of analyses of variance (ANOVAs). Thus, the results of these permutation analyses enabled us to objectively select different electrode sites and latency windows for further ERP traditional amplitude analyses. Specifically, for the location-cueing effect, differences were found in the latency range of N1 within a time interval from 148 to 208 ms for the LVF at P5, P3, P1, Pz, P2, P4, P6, PO7, PO3, POz, PO4, PO8, O1, Oz and O2 electrode sites, and within a time interval from 168 to 188 ms for the UVF at F3, F1, Fz, F2, F4, FC3, FC1, FCz, FC2, FC4, C3, C1, Cz, C2, C4 electrode sites. The permutation tests also showed differences from288 to 348 ms at P5, P3, P4, P6, PO7, PO3, PO4 and PO8 for the LVF, and from 320 to 380 ms at F3, F1, Fz, F2, F4, FC3, FC1, FCz, FC2, FC4, C1, Cz, and C2 for the UVF. As these two latency intervals fell along the rising part of the P3wave, difference wave forms were obtained by subtracting LNCN from LOCN conditions in each visual field to better see the cueing effects. We will refer to the resulting waveforms thereafter as Nd (Negative difference) or Pd (Positive difference) depending on the polarity of the difference associated to the IOR effect. For the color-cueing effect, significant differences were found in the latency range of P3 wave in a time interval from 418 to 438 ms, only for the UVF at CP3, CP1, CPz, CP2, CP4, P7, P5, P3, P1, Pz, P2, P4, P6, P8, PO7, PO3, POz, PO4, PO8, O1, Oz, and O2 electrode sites. For the comparison between uncued (LNCN) and both spatial and color cued dimensions (LOCO), permutation tests showed Post-print (final draft post-refereeing) 9 differences within the N1 time range in the LVF from 174 to 222 ms at CP3, CP1, CPz, CP2, CP4, P3, P1, Pz, P2, P4, PO3, POz, PO4, O1, Oz, and O2 electrode sites, and in the UVF from168 to 200 ms at FCz, C1, Cz, C2, CP1, CPz, CP2, and Pz electrode sites. Differences were also found in the P3 rising interval from 280 to 350 ms in the LVF at P7, P5, P3, P4, P6, P8, PO7, PO3, POz, PO4, PO8, O1, Oz, and O2 electrode sites, and from 268 to 400 ms at F3, F1, Fz, F2, F4, FC3, FC1, FCz, FC2, FC4, C1, Cz, and C2 electrodes in the UVF. Mean ERP amplitudes in each of the above latency windows were submitted to separate repeated measures ANOVAs, using the Bonferroni adjustment for multiple comparisons when appropriate, with the within-subject factors electrode (with the specific levels for each of the above-referred time intervals and visual field respectively), location cueing (LNCN, LOCN), color-cueing (LNCN, LNCO), and location and color cueing (LNCN vs. LOCO) effects. Results Behavioral results Mean RTs and error rates as a function of the cueing condition in each visual field are presented in Table 1. After removing from the behavioral data those trials with incorrect responses, an average of 95.3% of correct trials across conditions was included in the statistical analyses. On RT values, the repeated measures ANOVA showed significant effects of visual field (RT were 6.04 ms faster for LVF, F(1,19) = 7.98; p b .011), and cueing condition (F(3,57) = 8.86; p b .0001), but analyses did not reveal any statistically significant interaction between cueing condition and visual field. Bonferroni adjustment for comparisons among the cueing conditions showed a significant 11.79 ms increase in RT for spatial cueing condition (LOCN) compared to the uncued (LNCN) condition (p b .032), but not for non-spatial cueing. Moreover, Bonferroni corrected comparisons showed that the spatial and colorcued condition (LOCO) showed the largest significant differences with both spatial uncued conditions: 15.28 ms slower compared to LNCN (p b .0001), and 11.29 ms slower compared to LNCO (p b .006). No significant differences were found between spatial and color cued trials (LOCN vs. LNCO). Finally, no effects of visual field (F(1,19) = 1.30; p = .27) or cueing condition (F(1,19) = 1.05; p = .38)were observed on error rates. Event-related potential (ERPs) results Figs. 2–5 display the grand-average ERP waveforms across cueing conditions and visual fields. A visual inspection of the waveforms in Fig. 2 shows that the N1 component distribution was slightly lateralized over right centro-parietal sites for targets in the UVF, but it was of higher amplitude and more bilateral at posterior electrodes in the LVF. Along with N1, P1 showed more positive values in the UVF compared with the LVF. In the P3 latency range, larger amplitudes for UVF targets were apparent. Additionally, at the P3 rising (Fig. 3), under spatial cued conditions (LOCN) compared to uncued conditions (LNCN), the waveforms were more negative (referred to as Nd thereafter) in the LVF, while in the UVF they were more positive (referred to as Pd thereafter). Moreover, in the subtraction wave forms (LOCN minus LNCN) the Nd showed a slight left-lateralized distribution at parietal and parietooccipital electrodes while the Pd was fronto-centrally distributed in the UVF (see Fig. 3). Location cueing effects Post-print (final draft post-refereeing) 16 In summary, the aim of the present research was to explore the possible differences between UVF and LVF when the location and color was cued in a color discrimination task. We found spatial cueing effects on RTs, but color cueing failed to show behavioral effects, even when the relevant dimension of the task was reversed. These results indicate that, at least with the design employed in the present study, only location cueing is associated with IOR. Electrophysiologically, under spatial IOR we have found N1 amplitude reductions in both upper and lower visual fields although with different scalp distribution (posterior in the LVF, and more anterior in the UVF). Significant amplitude modulations in the rising part of P3 were also observed under location cueing. However, the polarity and scalp distribution of such modulations differed depending on the visual field where location cueing occurred (a posterior Nd in the LVF, and an anterior Pd in the UVF), which can suggest that different underlying processes are activated depending on the visual field where the target has to be discriminated. Under color cueing, results showed reduced P3 amplitude only in the UVF. As the P3 modulation was found in the absence of behavioral effects, it is likely that it could be indexing a process different from IOR. The use of a vertical arrangement of stimuli allows avoiding of spatial compatibility effects between stimuli and response (e.g. Simon effect), but the results of the present study suggest that with these displays, it would be necessary to explore each visual field separately, attending to the differences found in the neurocognitive IOR expression. In this regard, the different modulations observed in the rising period of P3 under spatial cueing (posterior Nd and anterior Pd effects in this study) that suggest that the activation of two different processes depending on the visual field of stimulation need further study to reach conclusions on the underlying processes. The other remaining questions should be investigated in the future, such as how the advantages in each visual field act in the IOR generation. To this purpose, and in accordance with the present results, the visual field effect should be taken into account in future designs. Acknowledgments This study was supported by grants from the Spanish MICINN (PSI2010-21427) and Xunta de Galicia (10PXIB211220PR). S.D. was supported by an Isidro Parga Pondal contract (Xunta de Galicia, Spain). References Amenedo, E., Pazo-Álvarez, P., Cadaveira, P., 2007. Vertical asymmetries in pre-attentive detection of changes in motion direction. Int. J. Psychophysiol. 64 (2), 184–189. Andersen, S.K., Müller, M.M., Hillyard, S.A., 2009. Color-selective attention need not be mediated by spatial attention. J. Vis. 9 (6), 1–7. Cameron, E.L., Tai, J.C., Carrasco, M., 2002. Covert attention affects the psychometric function of contrast sensitivity. Vis. Res. 42, 949–967. Post-print (final draft post-refereeing) 17 Carrasco, M., Williams, P.E., Yeshurun, Y., 2002. Covert attention increases spatial resolution with or without masks: support for signal enhancement. J. Vis. 2, 467–479. Castel, A.D., Chasteen, A.L., Scialfa, C.T., Pratt, J., 2003. 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