We would like to thank Megumi Sakai, Ayuko Harano, and Sho Tanaka for supporting data acquisition and analyses. The authors are most grateful to the participants in this study.
Global visual processing decreases with autistic-like traits: A study of early lateralized potentials with spatial attention
Article first published online: 8 APR 2013
© Japanese Psychological Association 2013
Japanese Psychological Research
Special Issue: Cognitive science approach to developmental disorders. Editor: Harumitsu Murohashi
Volume 55, Issue 2, pages 131–143, April 2013
How to Cite
Kasai, T. and Murohashi, H. (2013), Global visual processing decreases with autistic-like traits: A study of early lateralized potentials with spatial attention. Japanese Psychological Research, 55: 131–143. doi: 10.1111/jpr.12014
- Issue published online: 8 APR 2013
- Article first published online: 8 APR 2013
- Manuscript Accepted: 12 JAN 2013
- Manuscript Received: 19 JUN 2012
- autistic-like traits;
- visual attention;
- perceptual organization;
- event-related potential
Extensive research suggests that autistic individuals have deficits in global visual processing that may cause an attentional bias toward local details. This tendency has also been noted in nonclinical samples with high autistic-like traits, as measured using the autism-spectrum quotient (AQ). However, as top-down attention as an executive control can modulate early visual processing, it is still unclear whether this local processing bias is due to atypicality in bottom-up processing or a top-down attentional set. The present study explored this issue by examining event-related potentials (ERPs) in a sustained focal-attention task that involved bilateral stimulus arrays. In this task, a P1 spatial attention effect (at approximately 100–150 ms post-stimulus) reflects top-down attentional modulation of incoming sensory processing, and an N1 attention effect (150–200 ms) reflects obligatory attention-spreading based on perceptual grouping. The results showed that AQ scores were negatively correlated with the N1 attention effects for conditions in which bilateral stimuli were grouped with feature similarity and amodal completion. This finding supports the view that bottom-up processing in perceptual organization varies with autism spectrum.
Weak central coherence (WCC; Frith & Happé, 1994) is a key cognitive characteristic of individuals with autism. While autistic individuals have prominent difficulties in situations that require social or communicative behaviors, they also show atypicality in nonsocial domains, such as detail-focused attention or a local processing bias. Empirical evidence for this bias has frequently been reported as superior performance on visual tasks that require detail-focused processing: the Embedded Figure Test (EFT) and Block Design (BD) in the Wechsler Intelligence Scales (for a review, see Happé & Frith, 2006) or a high-demand visual search (O'Riordan, Plaisted, Driver, & Baron-Cohen, 2001). As performance in these tasks benefits from ignoring global contexts or the whole meaning, autistic individuals may have a weakness or deficit in global or holistic processing compared with typically developing individuals. In fact, a relative imbalance in global and local processing may exist at many levels of processing, from perception to higher cognition (Frith & Happé, 1994).
As predicted from the notion of WCC, many psychophysical studies have shown that individuals with autism have impaired global visual perception, and this may cause a local processing bias. For example, children with autism have been shown to have elevated thresholds for detecting coherent motion (Milne, Swettenham, Hansen, Campbell, Jeffries, & Plaisted, 2002), second-order or complex motion (Bertone, Mottron, Jelenic, & Faubert, 2003), and global form (Spencer & O'Brien, 2006). These findings suggest that autism has relatively extensive global processing deficits that involve both magnocellular and parvocellular visual pathways. Some kinds of Gestalt perception or visual illusions also require global interactions of local processing, and are reduced in both autistic children and adults (Bölte, Holtmann, Poustka, Scheurich, & Schmidt, 2006; Brosnan, Scott, Fox, & Pye, 2004). Furthermore, a local processing bias, as reflected by superior EFT or BD performance, exists in normal populations that have high autistic-like traits, associated with a decrease in global motion and form processing (Grinter, Maybery, Van Beek, Pellicano, Badcock, & Badcock, 2009; Grinter, Van Beek, Maybery, & Badcock, 2009). Autistic traits can be measured using the autism-spectrum quotient (AQ) scale, and it has been suggested that genetic factors associated with an autistic tendency exist in a continuum for individuals with autism-spectrum disorders and normal populations (Baron-Cohen, Wheelwright, Skinner, Martin, & Clubley, 2001).
The bottom-up processing of visual grouping or perceptual organization in early visual streams can cause global-directed attention, rather than detail-focused attention, because attention tends to automatically spread over a whole region of grouped elements or an object, as suggested in object-based attention research (for reviews, see Driver & Baylis, 1998; Hopf, Schoenfeld, & Heinze, 2005; Humphreys, 1999; Scholl, 2001). Object-based attention research offers an objective measurement of Gestalt perception, and object-based attention effects are obtained when the objects are completely task irrelevant (Driver & Baylis, 1989; Duncan, 1984; Egly, Driver, & Rafal, 1994). This suggests that the most fundamental units of attentional selection are objects or products of perceptual organization or grouping, and coherent percepts and actions for whole objects become possible during countless fragmented sensory inputs. Such functions may be selectively impaired in response to some Gestalt cues in autism-spectrum disorders (Falter, Grant, & Davis, 2010).
However, other notions regarding the cause of detail-focused attention or a local processing bias in autism are not negligible. Individuals with autism have been shown not to differ from control groups with regard to their performance on selective attention tasks that required them to discriminate global identity in hierarchical letter stimuli (Plaisted, Swetten, & Rees, 1999; Wang, Mottron, Peng, Berthiaume, & Dawson, 2007). This result has been interpreted as indicating that autistic participants possess intact global processing and have a default setting or preference toward local details, due to the enhancement or overfunctioning of low-level perceptual processing (Mottron, Dawson, Souliéres, Hubert, & Burack, 2006). Some studies also have shown that a local attentional bias in autism spectrum disorders only became manifest when attention was shifted from a local to a global stimulus level or space, which suggests a deficit of inhibitory processing or attentional control (Katagiri, Kasai, Kamio, & Murohashi, 2013; Mann & Walker, 2003). However, perceptual and attentional processing are not independent of each other. Even very early visual processing (i.e., feedforward processing in V1) cannot escape top-down control or attentional set, as directly evidenced by studies on event-related potential (ERP) with a high temporal resolution of brain activities (Kelly, Gomez-Ramirez, & Foxe, 2008). Thus, regarding the possible involvement of attention, the question as to whether the local processing bias in autism is due to an abnormality in bottom-up visual processing or a top-down attentional bias is a “chicken or the egg” problem.
The present study attempted to resolve this issue by using an ERP paradigm of object-based attention in which top-down attentional modulation and perceptual grouping operations can be observed separately (Kasai, 2010; Kasai, Moriya, & Hirano, 2011; Kasai & Takeya, 2012). This paradigm is basically a sustained focal attention task (Heinze, Luck, Mangun, & Hillyard, 1990; Heinze, Mangun, Burchert, Hinrichs, Scholz, Munte, Gos, Scherg, Johannes, Hundeshagen, Gazzaniga, & Hillyard, 1994; Woldorff, Liotti, Seabolt, Busse, Lancaster, & Fox, 2002), in which the participants must respond when an infrequent target is presented at an attended hemifield during a rapidly presented sequence of bilateral stimuli. Here, spatial attention is indexed by larger amplitudes of posterior P1 (with a peak at approximately 100 ms after stimulus onset) and N1 components (at approximately 150 ms) of ERPs over the hemisphere contralateral, rather than ipsilateral, to the attended hemifield. Such attention effects of early ERPs reflect gain control mechanisms of incoming sensory signals (Hillyard, Vogel, & Luck, 1999). In a previous study that used the bilateral focal attention task, the magnitude of lateralized P1 attention effect was greater when the task was more difficult (Mangun, Hopfinger, Kussmaul, Fletcher, & Heinze, 1997), which may reflect that spatial attention was narrowed or focused on the task-relevant location due to the task load, consistent with the perceptual-load theory of attention (Lavie, 2005). Although it has not explicitly been tested whether the P1 attention effect for bilateral stimulus arrays reflects the extent or breadth of spatial attentional focus, P1 amplitude in response to probe stimuli is generally used as an index of it (Handy, Soltani, & Mangun, 2001; Moriya & Nittono, 2011).
In studies of object-based attention using bilateral stimuli, we found that the P1 spatial attention effect was independent of object structures, and the N1 attention effect decreased in amplitude when bilateral stimuli had grouping factors (Kasai, 2010; Kasai et al., 2011; Kasai & Takeya, 2012). The decrease of the N1 effect may reflect obligatory attention-spreading over a whole region of the object/group, the neural source of which is located in the lateral occipital cortex (Martínez, Teder-Sälejärvi, Vazquez, Molholm, Foxe, Javitt, Di Russo, Worden, & Hillyard, 2006). Furthermore, the N1 attention effect gradually decreased as the extent of the perceptual grouping increased (Kasai, 2010). Thus, we assumed that the attention effect of P1 may index the extent of top-down focal attention, and that of N1 may index the extent of bottom-up grouping operations. This paradigm can also elicit an N2 spatial attention effect, which resembles the N2 posterior-contralateral (N2pc) component in visual search tasks (Luck & Hillyard, 1994). However, the N2 effect in the bilateral focal attention task can reverse in polarity according to task or stimulus contexts, and its functional significance is unclear (Kasai & Takeya, 2012).
The present study examined whether the P1 and N1 attention effects of ERPs are associated with autistic-like traits in populations without a diagnosis of autism, by using the ERP experimental paradigm of object-based attention (Kasai & Takeya, 2012). If the local processing bias in autism is due to top-down attention, such as a narrowed focus of attention, the P1 attention effects may increase (i.e., become more positive) as autistic-like traits increase. In contrast, if the local processing bias in autism is due to the bottom-up processing of perceptual organization or grouping, the N1 attention effects may increase (i.e., become more negative) as autistic-like traits increase, depending on the nature of the stimuli. In the present experiment, the bilateral stimuli in the all stimulus conditions (see Figure 1) basically had grouping factors, such as common onset, common color, or collinearity. Thus it could be possible that the N1 attention effects would increase as autistic-like traits increase in the all stimulus conditions, if autistic-like traits are associated with a general decline of perceptual grouping. However, the specific stimulus manipulation (separated, occluded, connected) enabled us to explore selective declines regarding perceptual organization cues: Connectedness may be the most primitive grouping cue that integrates elements into an object (Palmer, 2003; Watson & Kramer, 1999) or objects into a higher-level object (Saiki & Hummel, 1998), and amodal completion of occluded objects requires additional processing that overcomes physical discontinuities.
Sixteen volunteers (nine female), aged 21 to 36 years (M = 25 years), were recruited from among undergraduate and graduate students at Hokkaido University and their acquaintances. All participants had normal or corrected-to-normal visual acuity and had not been diagnosed as having psychiatric disorders. They participated in the present ERP experiment and completed the Japanese version of the AQ (Wakabayashi, Tojo, Baron-Cohen, & Wheelwright, 2004). This evaluation includes 50 questions; 10 each in the subcategories Social Skill, Attention Switching, Attention to Detail, Communication, and Imagination. Higher scores indicate higher autistic-like traits. The AQs in the present participants ranged from 4 to 40 (M = 20.6). Although the participants were sampled randomly, the AQ scores were distributed relatively uniformly (see Figure 4) and three participants had scores greater than the cut-off point (33). The present study was conducted following the guidelines laid down in the Helsinki Declaration and participants provided written informed consent.
The stimuli and procedure in the present ERP experiment were the same as those in our previous study (Kasai & Takeya, 2012). The stimuli were displayed on a Hitachi CRT monitor, at a viewing distance of 70 cm, and controlled using PsyScope on a personal computer (Macintosh G3) with a PsyScope button box (Cohen, MacWhinney, Flatt, & Provost, 1993). A large green rectangle (mean luminance = 7.9 cd/m2) with curved corners (occluder) was extended at a visual angle of 3.9 deg × 3.0 deg, and presented 0.8 deg (to the bottom edge) above a blue central fixation cross against a gray background (14.6 cd/m2) throughout the experiment. Black bilateral rectangles (1.2 cd/m2) were displayed horizontally 4.2 deg to the left and right (to the center of the rectangles) and at the central height of the occluder. Each rectangle was 1.0 deg high while the widths varied according to the type. The standards extended horizontally 0.7 deg or 1.4 deg and the targets extended 1.0 deg (i.e., they were square). As shown in Figure 1, the bilateral rectangles were connected by a line (0.8 deg wide) in front of the occluder in the connected condition, or behind the occluder in the occluded condition. There was no connecting line in the separated condition.
Bilateral stimuli consisted of either two standard stimuli (rectangles) at 75% probabilities or one standard and one target (square) in the separate hemi-fields at 25% probabilities (Figure 2). The targets were assigned equally to each hemi-field (12.5% for each). For the standards, rectangles of different widths (thin, thick) were selected in equal probabilities for the left and right sides to make an asymmetric display, as symmetry is also a grouping factor and may cause a ceiling effect (Kasai, 2010; Kasai & Kondo, 2007). The bilateral stimuli were presented for 100 ms, and the interstimulus interval (offset to onset) was randomly varied between 300 and 650 ms (seven steps, rectangular distribution). While the ERPs in response to successive stimuli overlapped, due to the short ISI, this overlap should not differ among conditions due to the random order of stimulus presentation (Hillyard & Münte, 1984). Such rapid presentation can lead to large numbers of ERPs, and thus increase the signal-to-noise ratio in relatively short-term recordings.
The participant was seated in a reclining chair in a sound- and electric-shielded room. The experimental task was to attend to either the left or right hemi-field during the blocks and to press a button with the right thumb in response to an infrequent target (i.e., square) presented in the attended field, as accurately and quickly as possible. It was emphasized that they had to maintain fixation and to try not to move their eyes during the block. The attend-left and attend-right conditions consisted of 12 blocks, respectively, each consisting of 100 trials, which were alternated. The initial visual field to be attended was counterbalanced across the participants. The experiment started with one or two practice blocks for each attention condition to stabilize task performance and eye movement.
Recordings and analyses
The electroencephalogram (EEG) was measured using an electrocap (Neuroscan) with 25 Ag-AgCl electrodes (Fp1, Fp2, F7, F3, Fz, F4, F8, T3, C3, Cz, C4, T4, T5, P3, Pz, P4, T6, O1, Oz, O2, PO7, PO3, POz, PO4, and PO8, according to the International 10–20 System), which were referenced to the nose. Blinks and horizontal eye movements were monitored with electrodes at the outer canthi of the eyes (horizontal electrooculogram (EOG)) and Fp2 and below the right eye (vertical EOG). The impedance of the electrodes was kept below 10 kOhm. The EEGs were filtered with a bandpass of 0.1–30.0 Hz and sampled at 200 Hz.
Behavioral performance was measured, including the percentage of correct target detections (hits) and reaction times (RTs) for hits. Responses were scored as correct if they occurred within 200–1000 ms after a target was presented in the attended location. The responses to other stimuli were classified as false alarms (FAs). The ERPs were averaged separately for each stimulus type, stimulus condition, and attention condition. Averaging epochs were 1000 ms, starting 200 ms before the onset of the stimulus and ending 800 ms post-stimulus, while correcting for differences in the 200-ms pre-stimulus baseline. Automatic artifact rejection was applied to eliminate epochs contaminated above 75 μV, and epochs with incorrect responses were also excluded. Further analyses were focused on ERPs in response to standards with large average numbers. The ERPs at occipital-temporal sites (PO7, PO8) were quantified by mean amplitudes with latency windows of 100–140 ms (post-stimulus) for P1, and 140–180 ms and 180–220 ms for early and late N1s.
Each dependent measure for all participants was subjected to repeated-measures analysis of variance (ANOVA) to confirm the findings in the previous study (Kasai & Takeya, 2012). The main analyses were correlation analyses, which were conducted for total AQ scores with behavioral measures and ERP attention effects (i.e., subtraction of contralateral vs. ipsilateral ERPs), respectively, for each stimulus condition.
Table 1 summarizes the behavioral data. The hit rates were higher and the RTs were shorter for the separated condition than for the occluded and connected conditions, F(2, 30) = 14.2, p = .0005; F(2, 30) = 6.4, p = .005. In addition, the hit rates were higher and the RTs were shorter for the right-attend condition than for the left-attend condition, F(1, 15) = 14.2, p = .002; F(1, 15) = 7.1, p = .018. The FA rates for the separated condition were greater than those for the occluded condition, F(2, 30) = 4.8, p = .015.
|Reaction time (ms)|
|Hit rate (%)|
|False-alarm rate (%)|
The results of correlation analyses for behavioral measurements with AQ scores are shown in Table 2. There were no statistically significant correlations, while the hit rates for all stimulus conditions had a weak negative correlation with the AQ scores (approximately −.4).
The grand-averaged ERPs at the occipital temporal brain area in response to standard stimuli are shown in Figure 3. Spatial attention effects were observed as differences between ERPs recorded at electrode sites ipsilateral and contralateral to task-relevant visual fields. Figure 4 shows the mean amplitudes of the ERP spatial attention effects in P1 (100–140 ms), early N1 (140–180 ms), and late N1 (180–220 ms) latency windows. Table 3 summarizes the results of omnibus ANOVAs.
|Stimulus||Laterality||Stimulus × laterality|
|P1 (100–140 ms)||–||–||11.5||.003||–||–|
|Early N1 (140–180 ms)||5.3||.010||–||–||12.4||.0001|
|Late N1 (180–220 ms)||8.1||.001||–||–||10.7||.0002|
P1 had greater amplitude at the contralateral than at the ipsilateral sites for all stimulus conditions equally, as reflected by the main effect of laterality (Figures 3, 4). The amplitudes of N1 in the early and late latencies differed across the stimulus conditions, as reflected by the main effect of stimulus, which may involve physical differences among the stimulus conditions. Importantly, the attention effects in the early and late N1s were different across the stimulus conditions, as reflected by the significant interactions of stimulus and laterality (Figure 3). To simplify further analyses, multiple comparisons (Bonferroni correction of t-tests) were conducted for the contralateral minus ipsilateral subtraction ERPs for each latency range (Figure 4). The early N1 attention effect for the occluded condition was more positive than that for the separated and connected conditions, t(15) = 4.0, p = .003 and t(15) = 3.0, p = .024, and the early N1 effect for the connected condition was more positive than that for the separated condition, t(15) = 2.8, p = .043. In contrast, the late N1 attention effects for the occluded and connected conditions were more positive than those for the separated condition, t(15) = 4.1, p = .003 and t(15) = 4.2, p = .002.
Figure 5 shows scatter graphs for the attention effects of P1, early N1, and late N1 with the AQ scores in each stimulus condition, and also includes the results for the Pearson's correlation coefficient (r- and P-values). The P1 attention effects in all stimulus conditions had negative correlations with the AQ scores (r-values ranged from −.47 to −.41), but these were not statistically significant. Importantly, the late N1 attention effects in the separated and occluded conditions had significant and relatively strong negative correlations with the AQs (r-values were −.55 and −.58, respectively, ps < .05). To test whether the above negative correlations were specific to the attention effects, correlation analyses were also conducted for the absolute mean amplitudes of P1 and N1 themselves in each stimulus condition and latency range. There was no reliable correlation (r-values ranged from −.39 to .09), except P1 amplitude in the occluded condition (r = −.55, p = .027).
The present study examined whether ERP lateralized attention effects for bilateral stimuli with perceptual grouping factors vary with autistic-like tendencies in populations without a clinical diagnosis of autism-spectrum disorder. We hypothesized that there is a negative correlation between AQs and the N1 attention effect, but not a positive correlation between AQs and the P1 attention effect, if an autistic-like tendency is associated with bottom-up integration processes, rather than a narrowed top-down attentional focus.
Functional significance of dependent measures
The basic patterns of results averaged over the participants in the present study replicated our previous study (Kasai & Takeya, 2012). Equally poor behavioral performance (hits, RTs) for the occluded and connected conditions compared with the separated condition indicates that attention spread for perceptually connected objects by amodal completion as well as for physically connected objects. This is consistent with the results of many previous studies (Moore, Yantis, & Vaughan, 1998; Pratt & Sekuler, 2001). The FA results may reflect the extent of stimulus saliency, such that a square at the attended side was most salient for the separated condition, while that for the occluded condition appeared to be located behind the occluder and was the least salient.
The ERP spatial attention effects (i.e., amplitude enhancements at the hemisphere contralateral rather than ipsilateral to an attended visual field) in the P1 latency (100–140 ms) were observed independent of the stimulus conditions. In the present task, a sustained shift of eye position toward the to-be-attended location cannot be detected by horizontal EOG, and the shift of eye position may destroy lateralized ERP effects because the contra-ipsi relation is no longer valid if the eyes are not fixated at the central location. The reliable P1 attention effect indicates that the participants successfully directed their attention to the task-relevant visual field. In contrast, the attention effects in the early N1 latency (140–180 ms) increased for the occluded condition, which may reflect a prolongation of the P1 effect associated with a mosaic stage in amodal completion (Rauschenberger & Yantis, 2001; Sekuler & Palmer, 1992). The late N1 attention effects (180–220 ms) were equally decreased or completely absent for the occluded and connected conditions, which reflected obligatory attention-spreading based on the perceptual unity of the integrated object.
Autistic-like traits and object-based attention
In the present study, we found no reliable correlation effects between the behavioral measures and the AQ scores, but found negative correlations between the late N1 attention effects and the AQ scores. As previous ERP studies of object-based attention have found that the pattern of the behavioral results was consistent with that of the N1 results (He, Fan, Zhou, & Chen, 2004; Kasai, 2010; Kasai et al., 2011; Kasai & Takeya, 2012), the lack of correlation in the behavioral indices appears puzzling. However, the behavioral indices are final outputs of multiple stages of processing, while the N1 reflects sensory modulation at intermediate stages of visual processing (Luck & Hillyard, 1999) and may have higher sensitivity for object-based attention-spreading. The present results suggest that the early and late phases of N1 attention effects reflect relatively low-level and high-level operations in global visual processing, respectively, and that the latter decreased as the autistic-like tendency increased.
The negative correlations of late N1 were found for the separated and occluded conditions, but not for the connected condition. The ERP data focused on the type of perceptual organization in global processing. Although the separated condition appeared to be an ungrouped condition, it may involve attention-spreading due to color similarity (Kasai et al., 2011). This suggests that similarity based grouping weakens with autistic-like traits, consistent with a behavioral finding (Falter et al., 2010). In addition, the present negative correlation of the late N1 attention effect for the occluded condition suggests that amodal completion or the integration of discontinuous regions declines with autistic traits. The absolute P1 amplitude decreased as autistic traits increased in the occluded condition, which may also imply deficits in early visual processing associated with amodal completion, although further investigations are required because amodal completion has previously been linked to the N1 component (Murray, Foxe, Javitt, & Foxe, 2004). Finally, the lack of correlation for the connected condition is consistent with the view that global processing deficits in autism are limited to relatively complex or higher processing (Bertone et al., 2003). Thus, the present ERP methodology may offer a useful tool for specifying the type of global processing or Gestalt factors in which autistic individuals are weak.
Local processing bias in autism
Together with the negative correlations between the N1 attention effects and the AQs, the important results in the present study were that the earliest ERP attention effects of P1 did not have positive correlations with the AQs and, in fact, were more likely to show negative correlations. The results suggest that weakness of global processing, or a local processing bias can be involved in the autistic-like tendency, regardless of a top-down spatial attentional set, at least in the early stages of processing. However, it is still unclear whether the P1 attention effect for bilateral stimulus arrays can reflect individual differences in a top-down focus of spatial attention, and this should be tested in future research that combines probe stimuli. The present study has found a decline of early global processing with autistic-like traits using a methodology that involves the high temporal resolution of brain activities and selective attention. This finding supports the original account of WCC (Frith & Happé, 1994) and many studies on global visual perception in autism or individuals with high autistic-like traits. The present finding does not conflict with the possibility that autism is associated with executive dysfunctions (for a review, see Hill, 2004), as the present examination was limited to the case of sustained attention, rather than a shift of attention.
Such global processing deficits may exist in early childhood in autism, as reflected by the N1 component in response to a Kanizsa figure (Stroganova, Orekhova, Prokofyev, Posikera, Morozov, Obukhov, & Morozov, 2007) and priming effects for hierarchical figures (Scherf, Luna, Kimuchi, Minshew, & Behmann, 2008). Here, the biased competition model (Desimone & Duncan, 1995) may offer a useful perspective for clarifying how such a decline in global processing affects selective attention. This model assumes that attention selects products of automatic processing of perceptual grouping as fundamental units, and objects compete for limited resources for further processing. Object representations exist hierarchically and perceptual grouping at higher levels can more effectively reduce the number of objects or the extent of competition in the scene, and increase the saliency of each object. The manner of saliency may be a “default setting” that guides the top-down biasing of attention. Such an interface between bottom-up processing and selective attention is important for understanding the mechanisms that underlie the local processing bias in autism.
- 2001). The autism-spectrum quotient (AQ): Evidence from Asperger syndrome/high-functioning autism, males and females, scientists and mathematicians. Journal of Autism and Developmental Disorders, 31, 5–17. , , , , & (
- 2003). Motion perception in autism: A “complex” issue. Journal of Cognitive Neuroscience, 15, 218–225. , , , & (
- 2006). Gestalt perception and local-global processing in high-functioning autism. Journal of Autism and Developmental Disorders, 37, 1493–1504. , , , , & (
- 2004). Gestalt processing in autism: Failure to process perceptual relationships and the implications for contextual understanding. Journal of Child Psychology and Psychiatry, 45, 459–469. , , , & (
- 1993). PsyScope: An interactive graphic system for designing and controlling experiments in the psychology laboratory using Macintosh computers. Behavior Research Methods, Instruments, and Computers, 25, 257–271. , , , & (
- 1995). Neural mechanisms of selective visual attention. Annual Review of Neuroscience, 18, 193–222. , & (
- 1989). Movement and visual attention: The spotlight metaphor breaks down. Journal of Experimental Psychology: Human Perception and Performance, 15, 448–456. , & (
- 1998). Attention and visual object segmentation. In R. Parasuraman (Ed.), The attentive brain. Cambridge, MA: MIT Press, pp. 299–325. , & (
- 1984). Selective attention and the organization of visual information. Journal of Experimental Psychology: General, 113, 501–517. (
- 1994). Shifting visual attention between-object and locations: Evidence from normal and parietal lesion subjects. Journal of Experimental Psychology: General, 123, 161–177. , , & (
- 2010). Object-based attention benefits reveal selective abnormalities of visual integration in autism. Autism Research, 3, 128–136. , , & (
- 1994). Autism: Beyond “theory of mind”. Cognition, 50, 115–132. , & (
- 2009). Global visual processing and self-rated autistic-like traits. Journal of Autism and Developmental Disorders, 39, 1278–1290. , , , , , & (
- 2009). Brief report: Visuospatial analyses and self-rated autistic-like traits. Journal of Autism and Developmental Disorders, 39, 670–677. , , , & (
- 2001). Perceptual load and visuocortical processing: Event-related potentials reveal sensory-level selection. Psychological Science, 12, 213–218.Direct Link:, , & (
- 2006). The weak coherence account: Detail-focused cognitive style in autism spectrum disorders. Journal of Autism and Developmental Disorders, 36, 5–25. , & (
- 2004). Cue validity and object-based attention. Journal of Cognitive Neuroscience, 16, 1085–1097. , , , & (
- 1990). Visual event-related potentials index focused attention within bilateral stimulus arrays. I. Evidence for early selection. Electrophysiological and Clinical Neurophysiology, 75, 511–527. , , , & (
- 1994). Combined spatial and temporal imaging of brain activity during visual selective attention in humans. Nature, 372, 543–546. , , , , , , , , , , , & (
- 2004). Executive dysfunction in autism. Trends in Cognitive Science, 8, 26–32. (
- 1984). Selective attention to color and location: An analysis with event-related brain potentials. Perception and Psychophysics, 36, 185–198. , & (
- 1999). Sensory gain control (amplification) as a mechanism of selective attention: Electrophysiological and neuroimaging evidence. In G. W. Humphreys , J. Duncan , & A. Treisman (Eds.), Attention, space, and action: Studies in cognitive neuroscience. New York, NY: Oxford University Press, pp. 31–53. , , & (
- 2005). The temporal flexibility of attentional selection in the visual cortex. Current Opinion in Neurobiology, 15, 183–187. , , & (
- 1999). Neural representation of objects in space: A dual coding account. In G. W. Humphreys , J. Duncan , & A. Treisman (Eds.), Attention, space, and action: Studies in cognitive neuroscience. New York, NY: Oxford University Press, pp. 165–182. (
- 2010). Attention-spreading over hierarchical spatial representations for connected objects. Journal of Cognitive Neuroscience, 22, 12–22. (
- 2007). Electrophysiological correlates of attention-spreading in visual grouping. NeuroReport, 18, 93–98. , & (
- 2011). Are objects the same as groups? ERP correlates of spatial attentional guidance by irrelevant feature similarity. Brain Research, 1399, 49–58. , , & (
- 2012). Time course of spatial and feature selective attention for partly-occluded objects. Neuropsychologia, 50, 2281–2289. , & (
- 2013). Individuals with Asperger's disorder exhibit difficulty in switching attention from a local level to a global level. Journal of Autism and Developmental Disorders, 43, 395–403. , , , & (
- 2008). Spatial attention modulates initial afferent activity in human primary visual cortex. Cerebral Cortex, 18, 2629–2636. , , & (
- 2005). Distracted and confused?: Selective attention under load. Trends in Cognitive Science, 9, 75–82. (
- 1994). Electrophysiological correlates of feature analysis during visual search. Psychophysiology, 31, 291–308. , & (
- 1999). The operation of selective attention at multiple stages of processing: Evidence from human and monkey electrophysiology. In M. S. Gazzaniga (Ed.), The new cognitive neuroscience. Cambridge, MA: MIT Press, pp. 687–700. , & (
- 1997). Covariations in ERP and PET measures of spatial selective attention in human extrastriate visual cortex. Human Brain Mapping, 5, 273–279. , , , , & (
- 2003). Autism and a deficit in broadening the spread of visual attention. Journal of Child Psychology and Psychiatry, 44, 274–284. , & (
- 2006). Objects are highlighted by spatial attention. Journal of Cognitive Neuroscience, 18, 298–310. , , , , , , , , & (
- 2002). High motion coherence thresholds in children with autism. Journal of Child Psychology and Psychiatry, 43, 255–263. , , , , , & (
- 1998). Object-based visual selection: Evidence from perceptual completion. Psychological Science, 9, 104–110.Direct Link:, , & (
- 2011). Effect of mood states on the breadth of spatial attentional focus: An event-related potential study. Neuropsychologia, 49, 1162–1170. , & (
- 2006). Enhanced perceptual functioning in autism: An update, and eight principles of autistic perception. Journal of Autism and Developmental Disorders, 36, 27–43. , , , , & (
- 2004). Setting boundaries: Brain dynamics of modal and amodal illusory shape completion in humans. Journal of Neuroscience, 24, 6898–6903. , , , & (
- 2001). Superior visual search in autism. Journal of Experimental Psychology: Human Perception and Performance, 27, 719–730. , , , & (
- 2003). Perceptual organization and groupings. In R. Kimuchi , M. Behrman , & C. R. Olson (Eds.), Perceptual organization in vision. Mahwah, NJ: Erlbaum, pp. 3–43. (
- 1999). Children with autism show local precedence in a divided attention task and global precedence in a selective attention task. Journal of Child Psychology and Psychiatry, 40, 733–742. , , & (
- 2001). The effects of occlusion and past experience on the allocation of object-based attention. Psychonomic Bulletin and Review, 8, 721–727. , & (
- 2001). Masking unveils pre-amodal completion representation in visual search. Nature, 410, 369–372. , & (
- 1998). Connectedness and the integration of parts with relations in shape perception. Journal of Experimental Psychology: Human Perception and Performance, 24, 227–251. , & (
- 2008). Missing the big picture: Impaired development of global shape processing in autism. Autism Research, 1, 114–129. , , , , & (
- 2001). Objects and attention: The state of the art. Cognition, 80, 1–46. (
- 1992). Perception of partly occluded objects: A microgenetic analysis. Journal of Experimental Psychology: General, 121, 95–111. , & (
- 2006). Visual form-processing deficits in autism. Perception, 35, 1047–1055. , & (
- 2007). Inverted event-related potentials response to illusory contour in boys with autism. NeuroReport, 18, 931–935. , , , , , , & (
- 2004). The Autism-spectrum Quotient (AQ) Japanese version: Evidence from high-functioning clinical group and normal adults. Japanese Journal of Psychology, 75, 78–84. (In Japanese with English abstract.) , , , & (
- 2007). Local bias and local-to-global interference without global deficit: A robust finding in autism under various conditions of attention, exposure time, and visual angle. Cognitive Neuropsychology, 24, 550–574. , , , , & (
- 1999). Object-based visual selective attention and perceptual organization. Perception and Psychophysics, 61, 31–49. , & (
- 2002). The temporal dynamics of the effects in occipital cortex of visual-spatial selective attention. Cognitive Brain Research, 15, 1–15. , , , , , & (