Neural mechanisms of spatial- and feature-based attention: A quantitative analysis

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a v a i l a b l e a t w w w. s c i e n c e d i r e c t . c o m

w w w. e l s e v i e r. c o m / l o c a t e / b r a i n r e s

Research Report

Neural mechanisms of spatial- and feature-based attention: A quantitative analysis Christian Michael Stoppela,⁎, Carsten Nicolas Boehlerb , Clemens Sabelhausa , Hans-Jochen Heinzea,b , Jens Max Hopfa,b , Mircea Ariel Schoenfelda,b a

Department of Neurology II, Otto-von-Guericke-University Magdeburg, Leipziger Str. 44, 39120 Magdeburg, Germany Leibniz-Institute for Neurobiology, Brennecke Str. 6, 39118 Magdeburg, Germany

b

A R T I C LE I N FO

AB S T R A C T

Article history:

Attentional selection can be based on spatial locations, non-spatial stimulus features, or

Accepted 4 July 2007

entire objects as integrated feature ensembles. Several studies reported attentional

Available online 17 July 2007

modulations in those regions that process the constituent features of the presented stimuli. Here we employed functional magnetic resonance imaging (fMRI) to directly

Keywords:

compare the magnitude of space- and/or feature-based attentional modulations while

Feature-based attention

subjects directed their attention to a particular color (red or green) of a transparent surface

Spatial attention

and at the same time to a spatial location (left or right visual field). The experimental design

fMRI

made it possible to disentangle and quantify the hemodynamic activity elicited by identical

Motion

physical stimuli when attention was directed to spatial locations and/or stimulus features.

Color

The highest modulations were observed when the attentional selection was based on spatial location. Attended features also elicited a response increase relative to unattended features when their spatial location was attended. Importantly, at unattended locations, a response increase upon feature-based selection was observed in motion-sensitive but not in color-related areas. This suggests that compared to color, motion stimuli are more effective in capturing attention at unattended locations leading to a competitive advantage. These results support the idea of a high biological relevance of the feature motion in the visual world. © 2007 Elsevier B.V. All rights reserved.

1.

Introduction

An everyday visual scene comprises an overwhelming amount of information. Due to the limited processing capacity of the brain the existence of different coping strategies to avoid an excess of information is mandatory. Attentional selection is a powerful mechanism that enables us to focus onto relevant visual input while ignoring irrelevant information. Importantly, this selection process can be based on spatial locations (Posner et al., 1980), features such as color or motion (Corbetta et al., 1990;

Saenz et al., 2002), or even complex visual objects composed of ensembles of visual features (Duncan, 1984; Egly et al., 1994; O'Craven et al., 1999; Schoenfeld et al., 2003). Real world situations require these mechanisms to work together. The present work aims at investigating the interactions between space- and feature-based attentional selection mechanisms. Traditional theories viewed the attentional selection process in a spatial framework, suggesting the focus of attention to operate like a “spotlight” or “zoom lens” (Eriksen and St James, 1986; Posner et al., 1980). This “spotlight” can be shifted across

⁎ Corresponding author. Fax: +49 391 67 14474. E-mail address: [email protected] (C.M. Stoppel). 0006-8993/$ – see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.brainres.2007.07.019

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the visual field and the processing of items within that spatial region becomes enhanced regardless of their relevance to the task (Heinze et al., 1994). A common aspect in these theories is that the prototypical unit of attentional selection consists in a part of space. A second influential theory proposed that visual attention might not only be allocated to a particular region in space, but also to distinct non-spatial stimulus features such as color, shape or motion (Corbetta et al., 1990; Desimone and Duncan, 1995; Maunsell and Treue, 2006; Saenz et al., 2002). This feature-based allocation of attention can occur in an entirely location-independent manner (Motter, 1994; Saenz et al., 2002; Treue and Martinez Trujillo, 1999; Valdes-Sosa et al., 1998). Here the unit of attentional selection consists in a distinct visual feature, e.g., motion. When visual stimuli can be selected based on more than one sensory attribute hierarchical models propose that the information provided by the more rapidly available attribute biases the subsequent processing of the other attributes (Handy et al., 2001; Hillyard and Munte, 1984; Kingstone, 1992). The processing time of a distinct feature depends on its “inherent” complexity (Harter et al., 1982; Hillyard and Munte, 1984) and on the information provided by previously processed related features (Handy et al., 2001; Hillyard and Munte, 1984; Kingstone, 1992). Another theory, the integrated competition model suggested that attention may also be able to select out entire objects as integrated feature ensembles (Duncan et al., 1997). In this case objects in a visual scene compete for neural representation. Attending to one object leads to enhanced processing of all its constituent features in the respective cortical submodules, resulting in a competitive advantage of the attended object over other objects in the visual scene. A key

prediction of this model is that when attention is directed to one feature of an object, all other constituent features will also benefit from enhanced processing regardless of their relevance to the task. Evidence from behavioral and neuroimaging studies has been presented that this is indeed the case (Duncan, 1984, 1998; Egly et al., 1994; O'Craven et al., 1999; Schoenfeld et al., 2003). Importantly, in this model the unit of attentional selection is neither a part of space, nor one distinct feature but the entire object. Results from several studies using single-unit recordings in primates and functional neuroimaging in humans converge on the evidence that directing attention to a stimulus enhances its processing (for recent reviews, see Corbetta and Shulman, 2002; Hopf et al., 2005; Kastner and Ungerleider, 2000; Maunsell and Treue, 2006; Yantis and Serences, 2003). One important observation is that regardless of the type of attentional selection, the attentional modulations in the visual system always occur in those brain regions that process the physical attributes of the attended stimuli. If a particular color has been attended, the modulation of neuronal activity occurred in the color-sensitive area V4/V8 (Chawla et al., 1999; Saenz et al., 2002), whereas attending to motion, for example, leads to enhanced neuronal responses in the motion-sensitive area hMT (Buchel et al., 1998; Busse et al., 2005; Chawla et al., 1999; O'Craven et al., 1999, 1997; Schoenfeld et al., 2007, 2003). While convincing evidence has been presented that attentional selection can be based on different mechanisms the functional relations among them are still unclear. Studies using combined expectancies have shown that, depending on the context of the task, spatial attention might precede and

Fig. 1 – Visual stimulus configurations and experimental protocol. A central cue (red or green arrow) indicated the color (red vs. green) and the location (left vs. right) to attend. The stimuli comprised two superimposed transparent surfaces formed by red and green dots in the upper left and right visual field. Fast as well as slow movements could occur at the attended as well as the unattended location in the attended or unattended surface. Subjects were required to press a button upon the occurrence of a fast movement of the attended surface at the attended location.

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affect processing of the object attributes (Handy et al., 2001; Hillyard and Munte, 1984; Kingstone, 1992). On the other hand it also has been shown that feature-based selection may guide the allocation of spatial attention to target objects (Cave, 1999; Treisman and Sato, 1990; Wolfe and Horowitz, 2004). Some basic features (e.g., color and motion) are extracted preattentively and successively allocate spatial attention to the locations containing those features (Hopf et al., 2004). However, several examples of such ‘basic features’ that are not capable of guiding the deployment of attention have also been reported (Wolfe and Horowitz, 2004). In this respect only a few elemental features seem to be able to guide the deployment of attention, namely color, motion, orientation and size (Wolfe and Horowitz, 2004). Given the biological importance of motion stimuli it is not surprising that moving stimuli are highly effective in capturing attention when they occur outside the focus of (spatial) attention (Franconeri and Simons, 2003; Rauschenberger, 2003). This suggests that compared to other features motion might be either processed preferentially or suppressed ineffectively. Previous work has convincingly shown that both nonspatial as well as spatial attentional selection lead to enhancement of neuronal activity in those regions that process the physical attributes of the presented stimuli (Corbetta and Shulman, 2002; Kastner and Ungerleider, 2000; Maunsell and Treue, 2006; Yantis and Serences, 2003). This offers the opportunity to measure and quantify these modulations while attention is systematically directed to a distinct location and at the same time to a specific feature. Electrophysiological data indicate that modulations due to spatial attention occur earlier than feature-based ones (Schoenfeld et al., 2007).Given the retinotopical organization of the early visual areas, spatial attention is a powerful mechanism especially when stimuli are located outside the fovea (Handy and Khoe, 2005). Therefore spatial selection is expected to elicit the highest modulations in extrastriate areas, thereby biasing the processing of features within the attended location (Handy et al., 2001; Hillyard and Munte, 1984). Consequently at the attended location the modulations due to additional feature-based selection are rather expected to be small (Heinze et al., 1994). In contrast, modulations due to feature-based attention are expected to be more evident at unattended locations (Saenz et al., 2002). The experimental approach in the present study was to directly compare the magnitude of attentional modulations

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across conditions when attentional selection was either spaceand/or feature-based while using exactly the same physical stimuli. For this purpose we employed a design in which a central cue (red or green arrow) directed the subject's attention to a particular feature (red vs. green dot color) and at the same time to a particular location in space (left vs. right visual field). The stimuli consisted of mixed arrays of red and green dots within two squared apertures one located in the left and the other in the right upper visual field (Fig. 1). At the beginning of each trial one dot population (red or green) started to move coherently up- or downwards within one aperture. In that aperture typically two transparent surfaces (Nakayama, 1996) are perceived that can be selectively attended to (Schoenfeld et al., 2003; Valdes-Sosa et al., 1998). Directed by the cue the subjects focused their attention on either the left or the right aperture on the red or the green dots and pressed a button upon the detection of a rarely occurring fast motion of the attended transparent surface. Importantly, slow motion served as a standard stimulus and occurred often either in the attended or unattended dot population at the attended or unattended location. As intended, this design permitted to study brain responses in motion- and color-sensitive areas elicited by the same physical stimulus (moving colored dots) in dependence of the different attentional conditions and thereby to quantify the magnitude of the attentional modulations in those regions during space- and/or feature-based selection.

2.

Results

2.1.

Behavioral results

Mean reaction times (RTs; min/max: 1.36/1.86 s; mean ± standard error of the mean (SEM): 1.62± 0.02 s) and percentage of correct responses (min/max: 35.71/100%; mean ± SEM: 90.43± 1.59%) were separately submitted to a RANOVA with the factors cue type (green vs. red) and cued location (left vs. right). For the RTs this analysis revealed a significant main effect of cued location (F(1,14)= 13.767, P b 0.003) but not of cue type (F(1,14) = 0.868, P = 0.367), as well as a significant interaction between these two factors (F(1,14)= 22.815, P b 0.0003). Analysis of the hit rates showed a significant main effect for the factor cue type (F(1,14)= 5.293, Pb 0.037) but not for the factor cued location (F(1,14) =1.689, P=0.215) and revealed a significant cue type×cued location interaction (F(1,14)=8.986, Pb 0.01). Post hoc comparisons of cue

Fig. 2 – The figure shows the foci of significant activations during task performance.

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Table 1 – Local maxima of ROIs showing significant attentional modulations Region

x [mm]

y [mm]

z [mm]

Z-score

T max.

FEF L FEF R LG L LG R FG L FG R aIPS L aIPS R f IPS L f IPS R hMT L hMT R

−38 34 −12 8 −40 32 −32 30 −34 26 −44 48

4 6 −74 −78 −82 −76 −62 −70 −66 −80 −74 −74

28 20 − 14 − 14 − 12 − 12 44 38 16 14 −2 −6

4.03 4.52 4.14 3.77 4.29 4.92 2.92 3.98 3.92 4.63 3.91 5.22

5.86 7.27 6.14 5.22 6.57 8.71 3.57 5.73 5.57 7.65 5.56 10.02

Values represent coordinates in millimeter in MNI-space, Z-scores and maximum T-values. Abbreviations: aIPS, anterior intraparietal sulcus; FEF, frontal eye field; FG, fusiform gyrus; fIPS, fundus of the intraparietal sulcus; hMT, human analogue of the middle temporal area; LG, lingual gyrus; L, left hemisphere; R, right hemisphere. Coordinates: x, left/right; y, posterior/anterior; z, inferior/superior in the reference frame of the MNI brain in SPM99.

from beta-images of each subject for each ROI. Attentional modulations for each ROI are depicted in Figs. 4 (FEF and fIPS) and 5 (aIPS, FG, hMT and LG).

2.3.

Main effects

For statistical evaluation the ROI analysis data were submitted to a RANOVA with the factors region (aIPS, FEF, FG, fIPS, hMT and LG), hemisphere (left vs. right) and attention condition (cS+F+, iS+F+, cS+, iS+, cF+, iF+ and RFE). Significant main effects were observed for the factor region (F(5,65) = 12.403, P b 0.0001), whereas a very strong trend towards significance was observed for the factors hemisphere (F(1,13) = 4.233, P = 0.060) and attention condition (F(6,78) = 2.570, P = 0.076). Moreover the analysis revealed a significant interaction between the factors region and attention condition (F(30,390) = 2.665, P b 0.05), hemisphere and attention condition (F(6,78) = 53.596, P b 0.0001) and between region, hemisphere and attention condition (F (30,390)= 10.220, P b 0.0001). For direct comparison of the magnitude of attentional modulations within each ROI, a RANOVA with the factor attention condition (cS+F+, iS+F+, cS+, iS+, cF+, iF+ and RFE) was applied to the data of each ROI separately. If statistical significance

type/cued location pairs indicated that the main effect for the RTs was due to faster responses upon stimuli presented to the right visual hemifield regardless of the stimulus color, whereas significantly higher hit rates were only observed upon green stimuli presented to the right visual hemifield.

2.2.

fMRI results

To assess activations based on the type of attention, a doublecueing paradigm in which the occurrence of a central cue (red or green arrow) directed the subject's attention to a particular color (red vs. green) at a particular location in space (left vs. right visual hemifield) was performed. Subjects were presented with two superimposed transparent surfaces formed by red and green dots in the upper left and right visual field. Upon the occurrence of a fast movement of the attended surface at the attended location the subjects were required to press a button. However, also slow movements could occur at the attended as well as the unattended location in the attended or unattended surface. Therefore epochs of identical physical content which only differed in terms of the attention condition were compared. The initial analysis identified foci of significant activation in several brain regions including ventral (fusiform gyrus (FG) and lingual gyrus (LG)) and dorsal (human analogue of the middle temporal area (hMT), anterior intraparietal sulcus (aIPS) and fundus of the intraparietal sulcus (fIPS)) visual stream areas, as well as in the human analogue of the frontal eye field (FEF). These regions are shown in Fig. 2 (see Table 1 for MNI coordinates, z-values and T max.). A region of interest (ROI) analysis was performed to directly compare the magnitude of attentional modulations between the different attention conditions (see Fig. 3 for illustration of ROI locations and Table 2 for the corresponding MNI coordinates).

2.2.1.

Region of interest analyses

To obtain a quantitative measure of the activity levels during the different experimental conditions T-values were extracted

Fig. 3 – Location of the regions of interest (ROIs). Y-coordinates in MNI space are depicted below each slice. Abbreviations: aIPS, anterior intraparietal sulcus; FEF, frontal eye field; FG, fusiform gyrus; fIPS, fundus of the intraparietal sulcus; hMT, human analogue of the middle temporal area; LG, lingual gyrus; L, left hemisphere; R, right hemisphere.

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Table 2 – MNI coordinates of the regions of interest (ROIs) Left

FEF FG LG aIPS f IPS hMT

Right

x

y

z

x

y

z

−41 ± 7 −39 ± 7 −20 ± 4 −34 ± 8 −24 ± 10 −45 ± 7

3±5 −76 ± 12 −71 ± 3 −61 ± 9 −82 ± 10 −73 ± 9

30 ± 4 −13 ± 7 −10 ± 4 45 ± 9 18 ± 10 −7 ± 9

41 ± 9 40 ± 4 22 ± 6 28 ± 8 27 ± 7 47 ± 7

−2 ± 8 −71 ± 9 −68 ± 8 −63 ± 9 −81 ± 11 −69 ± 9

30 ± 14 −16 ± 4 −10 ± 4 43 ± 9 21 ± 7 −3 ± 13

Values represent coordinates in millimeter in MNI-space. Abbreviations: aIPS, anterior intraparietal sulcus; FEF, frontal eye field; FG, fusiform gyrus; fIPS, fundus of the intraparietal sulcus; hMT, human analogue of the middle temporal area; LG, lingual gyrus. Coordinates: x, left/right; y, posterior/anterior; z, inferior/superior in the reference frame of the MNI brain in SPM99.

2.3.3.

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FG

The statistical evaluation of the FG data showed a significant main effect for both hemispheres ((F(6,78) = 11.102, P b 0.0001) for the left FG and (F(6,78) = 6.046, P b 0.001) for the right FG). Pairwise comparison revealed that the highest attentional modulations occurred upon spatially attended stimuli presented to the contralateral visual hemifield (cS+F+ and cS+). In the left hemisphere the cS+F+ condition differed significantly from all conditions except cS+, which in turn showed higher modulations in comparison to the cF+, iS+F+ and RFE contrasts. The right FG showed the highest attentional modulations upon the cS+ (differing significantly from all ipsilateral conditions and the RFE).

2.3.4.

hMT

For the aIPS data the RANOVA revealed a significant main effect only for the right hemisphere (F(6,78) = 3.193, P b 0.05), but none of the comparisons remained significant after Bonferroni correction.

The RANOVA applied to the hMT data showed a significant main effect for both hemispheres ((F(6,78)= 12.626, P b 0.0001) for the left and (F(6,78) = 6.046, P b 0.001) for the right). Pairwise comparison revealed a similar pattern as for the FG data. Both ROIs showed the highest attentional modulations upon the cS+F+ and cS+ contrasts. In the right hemisphere both contrasts differed significantly from all other conditions except each other. The left hMT was modulated in a similar manner whereas both cS+F+ and cS+ conditions were not significantly different from the iF+ condition.

2.3.2.

2.3.5.

(P b 0.05) was assured, a paired t tests (Bonferroni corrected) was applied for post hoc comparison.

2.3.1.

aIPS

FEF

For the FEF a significant main effect was also only observed for the right hemisphere (F(6,78) = 6.501, P b 0.001). Post hoc comparison revealed significantly higher attentional modulations upon the cS+F+, cS+ and iS+F+ conditions in comparison to the RFE.

fIPS and LG

Significant main effects for both hemispheres were observed in a RANOVA applied to the fIPS as well as the LG data ((F(6,78) = 10.011, P b 0.0001) for the left fIPS; (F(6,78)= 13.235, P b 0.0001) for the right fIPS; (F(6,78) = 19.634, P b 0.0001) for the left LG and (F(6,78) = 8.243, P b 0.005) for the right LG). Post hoc analysis

Fig. 4 – Attentional modulations of neuronal activity in the frontal eye field (FEF) and the fundus of the intraparietal sulcus (fIPS) by the different attention conditions. The bar color indicates the particular attention condition (white: attended feature at the attended location N unattended feature at the unattended location (S+F+); light grey: attended feature at the attended location N attended feature at the unattended location (S+); dark grey: attended feature at the attended location N unattended feature at the attended location (F+); black: attended feature at the unattended location N unattended feature at the unattended location (relevant feature effect, RFE)). Abbreviations: FEF, frontal eye field; fIPS, fundus of the intraparietal sulcus; L, left; R, right. Coordinates: y, posterior/anterior in the reference frame of the MNI brain in SPM99.

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Fig. 5 – Attentional modulation of neuronal activity in the anterior intraparietal sulcus (aIPS), fusiform gyrus (FG), human analogue of the middle temporal area (hMT) and lingual gyrus (LG) by the different attention conditions. The bar color indicates the particular attention condition (white: attended feature at the attended location N unattended feature at the unattended location (S+F+); light grey: attended feature at the attended location N attended feature at the unattended location (S+); dark grey: attended feature at the attended location N unattended feature at the attended location (F+); black: attended feature at the unattended location N unattended feature at the unattended location (relevant feature effect, RFE)). Abbreviations: aIPS, anterior intraparietal sulcus; FG, fusiform gyrus; hMT, human analogue of the middle temporal area; LG, lingual gyrus; L, left; R, right. Coordinates: y, posterior/anterior in the reference frame of the MNI brain in SPM99.

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showed that in the left and right fIPS as well as the left LG neural activity increased if spatially attended stimuli were presented to the contralateral visual hemifield (cS+F+ and cS+, differing significantly from all other contrasts but not from each other), whereas it decreased for stimulus presentations to the ipsilateral hemifield (iS+F+ and iS+, differing significantly from all other contrasts but not from each other).

3.

Discussion

While it is well established that attentional selection can be based on spatial locations, non-spatial stimulus features, or entire objects as integrated feature ensembles (Corbetta et al., 1990; Duncan, 1984; Egly et al., 1994; O'Craven et al., 1999; Posner et al., 1980; Saenz et al., 2002; Schoenfeld et al., 2007, 2003), the functional relationship among these selection processes has so far not been well established. In the present experiment we directly measured the magnitude of attentional modulations based on space and/or features in different brain areas. We employed an experimental design that enabled us to disentangle hemodynamic activity elicited by identical physical stimuli while the attentional selection was manipulated to be based on spatial location, features or both. The stimuli consisted of colored moving dots forming a transparent surface and elicited activity in well-known motion- and color-selective brain regions (see Fig. 2). In addition to areas involved in the perceptual analysis of the stimuli we also observed activity in frontal and parietal areas involved in attentional control (see Fig. 2). More precisely, robust attentional modulations of hemodynamic activity were observed in ventral (FG and LG) and dorsal (hMT, aIPS and fIPS) visual stream areas, as well as in the FEF (see Fig. 2). These findings are in line with the literature reporting that regions that process the physical attributes of the presented stimuli exhibit increased neuronal activity regardless of the type (spatial or non-spatial) of attentional selection (Corbetta and Shulman, 2002; Kastner and Ungerleider, 2000; Maunsell and Treue, 2006; Yantis and Serences, 2003). The highest attentional modulations were observed when the selection was based on spatial location, i.e., when the particular stimuli were presented in the contralateral hemifield to the hemispheric location of the region in which the activity was measured (either in the cS+ or cS+F+ contrast). This result clearly points out that space-based selection leads to higher modulations of the BOLD signal than feature-based attentional selection. A signal enhancement of comparable size was also observed in all regions when stimuli possessing the attended feature were presented at the attended location (cF+). It is important to note that additional feature-based selection at the attended location in space does not lead to a higher BOLD response than the spatial selection alone. This is well in line with the idea that the processing of all features within the attended location is enhanced (Heinze et al., 1994). At unattended locations, however, higher activity in response to stimuli possessing the attended feature (RFE) could be observed in motion-sensitive areas but was absent in colorsensitive regions (see Fig. 5). This finding indicates that at unattended locations motion stimuli have either a higher bottom-up saliency (Nothdurft, 2002; Treue and Martinez Trujillo, 1999) or are able to capture attention to a much higher

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degree (Abrams and Christ, 2003; Franconeri and Simons, 2003; Hillstrom and Yantis, 1994; Rauschenberger, 2003) than the color stimuli. Both possibilities, however, would fit into the concept of a higher biological relevance of moving stimuli in the visual world. Based on the magnitude of the BOLD responses spatial attention leads to the highest modulations. This result provides further support for the outstanding importance of this mechanism in vision. Data from electrophysiological recordings clearly point out that spatial selection is faster than feature-based (Schoenfeld et al., 2007). Furthermore, studies using combined expectancies have shown that not only location-based selection precedes but also biases the processing of other visual attributes (Handy et al., 2001; Hillyard and Munte, 1984; Kingstone, 1992). Thus, spatially based attentional selection appears to be the fastest and most efficient mechanism. Given the retinotopical organization of early visual cortices the information about spatial location is directly coded and rapidly accessible. Information on specific visual features is accessible somewhat later since it has to be retrieved from higher visual areas. A visual scene is typically analyzed by making saccades from point to point and covert attention serves to plan these saccades. Since the visual system has to deal with narrow capacity limits, the locations to be successively fixated have to be carefully analyzed and selected. Space-based attentional selection improves acuity of percepts arising from parafoveal locations by increasing their sensory gain (Handy and Khoe, 2005). This mechanism facilitates the selection of relevant peripheral targets for subsequent saccade planning. Thus, it is not surprising that the neural circuits mediating covert attention and saccade-related processing overlap (Corbetta, 1998; Nobre et al., 2000). As expected feature-based attentional selection on its own (F+) led to a robust response increase throughout all ROIs. This finding is in line with the literature reporting increased hemodynamic activity or a response gain at single neuron level upon the occurrence of attended features (Corbetta and Shulman, 2002; Kastner and Ungerleider, 2000; Maunsell and Treue, 2006; Schoenfeld et al., 2007; Yantis and Serences, 2003). The concurrent spatial and feature-based selection (cS+F+) and the spatial selection (cS+) by itself showed a comparable magnitude of attentional modulation. At first glance this result seems to contradict the intuitive assumption that concurrent attentional modulation by space- and feature-based mechanisms should have an additive effect and therefore should elicit a greater hemodynamic response than just space-based attentional selection on its own. The most likely explanation for this finding, however, is that the signal enhancement induced by location-based selection leads to a ceiling effect preventing further response increases by concomitant occurrence of the attended feature at the focus of attention. This fits well into the framework that the processing of all features within the attentional focus is facilitated regardless of their relevance to the task (Heinze et al., 1994) but does not rule out the possibility that at single neuron level an integrated saliency map is formed (Maunsell and Treue, 2006). Nevertheless, the magnitude of such types of additive/subtractive effects might be below the resolution of the fMRI technique employed here.

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For stimuli presented contralateral to each ROI a homogenous pattern emerged, in that all regions showed the highest modulations upon space-based attentional selection. In contrast, space-based attentional modulations upon stimuli presented to the ipsilateral visual hemifield (to the hemispheric location of the ROI) differed substantially between ROIs: the more anterior regions (aIPS and FEF) showed a signal increase, the more laterally located posterior areas (FG and hMT) showed no modulations, whereas the more medially located posterior areas (fIPS and LG) showed a signal decrease during the iS+ and iS+F+ conditions. This pattern strongly suggests that these regions are involved differently in the processing of the ipsilateral input. The FEF and aIPS are both higher tier areas belonging to the fronto-parietal attention control network (Corbetta and Shulman, 2002; Hopfinger et al., 2000; Mesulam, 1981; Woldorff et al., 2004). Having big receptive fields, neurons in these regions pick up stimuli outside the focus of attention and send top-down signals to lower tier areas, in this case most likely to suppress the “unwanted” input outside the focus of attention. The present results suggest this suppression to be mediated by other parietal areas located in the fundus of the intraparietal sulcus (fIPS) in which a signal decrease could equally be observed. This is well in line with the idea that higher tier dorsal stream areas in the posterior IPS exert inhibitory control over extrastriate regions (Fuggetta et al., 2006). The consequences of this inhibition are evident in all investigated extrastriate occipital areas ipsilateral to the presented stimuli, most prominently in the lingual gyrus (LG) in which a signal decrease was observed. In the regions hMT and FG, that contain neurons with receptive field sizes just big enough to pick up stimuli at 8° in the ipsilateral field (Felleman and Kaas, 1984; Smith et al., 2001), neither an increase, nor a decrease of signal was observed. These findings add to the evidence that visual regions are inhibited during ipsilateral stimulation outside the focus of attention and that inhibition in parietal and occipital extrastriate areas is associated with BOLD signal decreases (Schwartz et al., 2005; Vandenberghe et al., 2005; Yantis et al., 2002). A similar dissociated response pattern between medial and lateral parietal areas has also been reported by Woldorff et al. (2004). They showed a functional parcellation of frontal and parietal regions into medial and lateral subregions exerting different functions, suggesting that the medial regions are involved in the orienting of visual spatial attention, which is in line with our interpretation regarding the response pattern of the two parietal ROIs. Importantly, the present results also revealed another functional dissociation between the activated brain regions. This dissociation was evident for stimuli having the attended feature that were presented contralateral to the focus of spatial attention (relevant feature effect; RFE). In this condition a signal enhancement only occurred in frontal and parietal regions (FEF and aIPS) and in the area hMT. The signal in all other ROIs remained unaffected. This finding is of general importance, because it supports the notion that major differences exist among the different feature categories that have been defined thus far (Wolfe and Horowitz, 2004). Some basic features are extracted preattentively (e.g., color and motion) and successively may allocate the spatial focus of attention to their location (Hopf et al., 2004). But among these

‘basic features’ only few (color, motion, orientation and size) seem to be able to guide the deployment of attention (Wolfe and Horowitz, 2004). Given the particular property of moving stimuli to capture attention even when they occur distant from the focus of attention (Abrams and Christ, 2003; Franconeri and Simons, 2003; Hillstrom and Yantis, 1994; Rauschenberger, 2003) the elemental feature motion appears to be special. Our results indeed show a robust signal increase in area hMT when the moving stimuli are far from the focus of attention (RFE) and are in agreement with this idea. Motion, and in particular motion onset might yield a substantial survival benefit (as a powerful cue to animacy) by possibly indicating the appearance of a living, perhaps dangerous being.

4.

Experimental procedures

4.1.

Subjects

Fifteen right-handed young adults (11 females), all with normal or corrected-to-normal vision, participated as paid volunteers in the study (mean age: 24.1 ± 0.4 years). All gave informed consent and the study was approved by the local ethics committee.

4.2.

Stimuli and experimental design

Subjects were presented within two apertures of 2°× 2° each, located in the upper left and right visual quadrant at 8° eccentricity (inner edge) of a fixation cross (see Fig. 1). The luminance of the background was set at 45 cd/m2. Each aperture contained 50 red and 50 green randomly distributed isoluminant dots (200 cd/m2). The fixation cross and the stationary dots were present continuously on the screen during every run. During each trial either 50 red or green dots moved coherently up- or downwards for 500 ms within the left or right aperture on a pseudorandom basis, whereas the velocity of the movement could be either slow (4°/s) or fast (6°/s). The inter-trial interval varied randomly between 1 and 7 s following a gamma function to allow trial separation in an event-related analysis (Hinrichs et al., 2000). Subjects received six scanning runs of 7.5–8.2 min which consisted of 11–12 blocks of 16–24 trials. The pseudorandomized order of the stimuli guaranteed that 180 trials were collected for each condition to be compared. Before each block, a central cue (red or green arrow pointing to the left or right) replaced the fixation cross for 1 s, thereby directing the subject's attention to a particular subset of dots (either red or green) at a particular location (left or right aperture). Subjects were instructed to press a button as rapidly as possible upon the detection of a fast movement of the attended subset of dots that formed a transparent surface at the attended aperture. Such fast movements (targets) occurred in 10% of the cases while 90% of the movements were slow (standards). For the quantification of the modulations during spaceand/or feature-based deployment of attention the following contrasts were formed: S+F+: attended feature at attended location vs. unattended feature at unattended location (reflecting attentional modulations during concomitant feature- and locationbased selection).

BR A IN RE S E A RCH 1 1 81 ( 20 0 7 ) 5 1 –6 0

S+: attended feature at attended location vs. attended feature at unattended location (reflecting solely spacebased attentional modulations). F+: attended feature at attended location vs. unattended feature at attended location (reflecting feature-based attentional modulations within the focus of spatial attention). RFE (relevant feature effect): attended feature at unattended location vs. unattended feature at unattended location (reflecting feature-based attentional modulations outside the focus of spatial attention). The magnitude of the effects was assessed using a region of interest (ROI) analysis in which the activity was measured for stimuli presented to the ipsilateral (e.g., iS+F+) as well as contralateral visual hemifield (e.g., cS+F+). For the RFE the ipsilateral and contralateral values were averaged resulting in only one RFE value per ROI.

4.3.

fMRI data acquisition

During the scanning session the stimuli were presented via a projector-mirror system. fMRI data were collected using a Siemens TRIO 3-T MR scanner equipped with an 8-channel head coil. Functional images were acquired with a T2*weighted echo planar imaging (EPI) gradient echo sequence (TR = 2000 ms, TE = 30 ms, flip angle = 80°). Thirty axial (AC–PC oriented) slices were acquired (thickness = 3.5 mm, in-plane resolution 64 × 64 mm, no gap, resulting voxel size = 3.5 × 3.5 × 3.5 mm3) for 245 volumes in each of 6 runs. In a structural session, sagittal whole-head T1-weighted images (spatial resolution, 1 × 1 × 1 mm3; 256 × 256 matrix; 192 slices, no gap) were acquired by using a MP-RAGE sequence (TR = 2500 ms, TE = 3.82 ms, TI = 1100 ms, flip angle = 7°).

4.4.

fMRI data analysis

All image processing was performed using SPM99 software (Wellcome Department of Cognitive Neurology, University College London, UK). Following correction for differences in timing of slice acquisition and motion, EPI volumes were realigned and resliced using sinc interpolation and then spatially normalized to stereotaxic space using the MNI template. The normalized functional images were spatially smoothed with a 6-mm isotropic Gaussian kernel. Statistical analysis of the data was performed by convolving the BOLD signal with the canonical hemodynamic response function built-in into SPM99 in an event-related design for each subject. Data were collapsed over both colors. Group data were analyzed with a random effects analysis. A brain locus was considered to be activated if 10 or more adjacent voxels all passed the threshold of P b 0.001 (uncorrected). Stereotaxic coordinates for voxels with maximal z-values within activation clusters are reported in the MNI standard space. To directly compare the magnitude of attentional modulations between the different attention conditions a region of interest (ROI) analysis was performed using the MarsBar toolbox in SPM99 (Brett et al., 2002). Six ROIs (see also Figs. 2 and 3) were functionally defined for each hemisphere by means of an effects of interest contrast (all stimuli vs. baseline) (anterior intrapar-

59

ietal sulcus (aIPS), frontal eye field (FEF), fundus of the intraparietal sulcus (fIPS), fusiform gyrus (FG), human analogue of the middle temporal area (hMT) and lingual gyrus (LG)). Mean beta values for the functionally defined ROIs were extracted from individual subjects' data for each attention condition. These values were subjected to a repeated measures analysis of variance (RANOVA) with the factors region (aIPS, FEF, FG, fIPS, hMT and LG), hemisphere (left vs. right) and attention condition (cS+F+, iS+F+, cS+, iS+, cF+, iF+ and RFE). The significance threshold was set to P b 0.05 following Greenhouse–Geiser correction for non-sphericity. For evaluation of differences in the magnitude of the attentional modulations, the data for each ROI were separately subjected to a RANOVA with the factor attention condition. If statistical significance (P b 0.05) was obtained, a paired t test (Bonferroni corrected) was applied for post hoc comparison between the attention conditions.

Acknowledgments The authors thank Nicolai Heinze for programming the stimuli and Dr. Michael Scholz for the technical advice. This work was supported by the following grants: Scho 1217/1-1 from the Deutsche Forschungsgemeinschaft (DFG) awarded to M.A.S. and 01GO0504 from the Bundesministerium für Bildung and Forschung awarded to H.-J.H.

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