Allocentric and Egocentric Spatial Attention Bias in Individuals with Right-Hemispheric Stroke and Unilateral Spatial Neglect: A Pilot Study

doi:10.21203/rs.3.rs-5301267/v1

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Research Article

Allocentric and Egocentric Spatial Attention Bias in Individuals with Right-Hemispheric Stroke and Unilateral Spatial Neglect: A Pilot Study

https://doi.org/10.21203/rs.3.rs-5301267/v1

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Background

In neurorehabilitation, limited research exists on response performance and attention deficits in individuals with neglect across allocentric (aSC) and egocentric (eSC) spatial coding frameworks. These deficits are commonly assessed using pen-and-paper tests, which often fail to detect subclinical lateralized attention deficits. A computer-based task involving detecting shapes using a cue-to-target paradigm offers precise and sensitive data for identifying allocentric and egocentric spatial attention deficits.

Methods

This pilot study involved 18 right-handed healthy volunteers (HC) aged 23.89 ± 3.44 years, 13 individuals with right-hemispheric stroke and neglect (USN+) aged 32.83 ± 4.45 years, and 10 with stroke but no neglect (USN-) aged 32.6 ± 5.18 years, who performed a computer-based attention task. Response time (RT), accuracy rate (AR), lateralized visual perception deficits, reorienting spatial attention deficits, and disengagement deficits were recorded and analyzed.

Results

The USN + group had lower AR and slower RT in both aSC and eSC conditions than the USN- and HC groups across visual fields and cue types. Notably, the USN + group showed a greater RT delay for left and right visual fields (LVF) targets in the contralesional visual field than in the ipsilesional field, a pattern absent in the USN- or HC. No significant differences in AR and total RT were found between the aSC and eSC groups, but both stroke groups took longer to identify LVF targets in aSC than in eSC. Only the HC group displayed a significantly positive validity effect, with slower RT after invalid cues. This reflected their ability to disengage attention and maintain alertness. The USN + group had significantly slower RT for invalidly cued contralesional targets compared to the USN- and HC groups both in conditions.

Conclusion

Our study shows that individuals with neglect exhibit a rightward attentional bias during visuospatial tasks in both aSC and eSC conditions. Individuals without neglect, though classified as subclinical by pen-and-paper tests, showed a rightward bias in aSC and a leftward bias in eSC tasks using computer-based assessments. Those with or without neglect had greater difficulty with allocentric target identification in the contralesional visual field compared to egocentric processing. Additionally, individuals with neglect demonstrated a disengagement deficit, while both groups showed reorienting deficits in visuospatial attention.

Unilateral spatial neglect

Spatial Attention Bias

allocentric and egocentric spatial coding

stroke

Unilateral spatial neglect (USN) is a common and debilitating consequence of unilateral brain damage, often following a right-hemisphere stroke. Individuals without hemianopsia are unable to perceive or respond to stimuli on the contralesional side of space, typically observed in right-hemispheric brain injuries. There is a growing consensus that the clinical syndrome of neglect is heterogeneous, involving several underlying deficits, with the most prominent being a spatial attention bias toward the ipsilesional side. Based on reference frames, psychological representation disorders of spatial information can be classified as space-based (egocentric) and object-based (allocentric) neglect. Egocentric neglect involves failing to attend to the contralesional side of space relative to the body’s midline, while allocentric neglect refers to ignoring the contralesional side of an object in focus [1]. Prevalence reports for neglect in individuals post-stroke during the acute phase range from 40–85% [2]. As the condition progresses, 17–43% of individuals continue to show neglect symptoms six months post-stroke [3], with 30% remaining affected in the chronic phase [4]. Neglect significantly impairs functional recovery and activities of daily living [5, 6], negatively impacting prognosis, prolonging hospital stays, increasing fall risk, and reducing the likelihood of safely returning home after discharge [7, 8]. Therefore, understanding the characteristics of USN post-stroke has important clinical implications for exploring effective rehabilitation treatments.

Several assessments have been designed to clinically detect neglect, with the most common being paper-and-pencil procedures and other conventional clinical tests, such as star or letter cancellation and line bisection tasks [9, 10]. However, subclinical lateralized attention deficits may remain undetected using performance-based functional neglect assessments. Many stroke survivors reportedly experience disabilities related to neglect that are not identified by commonly used therapist-rated performance-based measures, such as the Catherine Bergego Scale (CBS) [11]. Compared with paper-and-pencil procedures, computer-based tasks may provide more precise and sensitive data for detecting lateralized spatial attention deficits [12]. It is well-established that time-limited and more demanding attention tasks can reveal "hidden" attention deficits in individuals with mild or recovered neglect that may not appear during simple paper-and-pencil procedures without time constraints [13, 14]. However, there is limited research on the response performance and underlying attention deficits of individuals with neglect in different allocentric and egocentric spatial coding frameworks (aSC and eSC, respectively). Moreover, the use of a computerized visual search task to explore the psychological characteristics of individuals post-stroke, with or without neglect, and healthy individuals remains relatively rare.

In this study, we adopted a shape discrimination task previously used by Chan to study attention control networks [15], which included allocentric and egocentric spatial coding tests. This task was derived from Posner et al. [16] and utilizes the cueing-target paradigm to measure RT and AR, offering a promising alternative for screening neglect. The Posner cueing task evaluates three components of visual attention typically impaired in hemispatial neglect: lateralized visual perception deficits (visual field effect), deficits in reorienting spatial attention (validity effect), and a disengagement deficit .[17]

Our study compared individuals with chronic right-hemispheric stroke to real-life search situations using a computer-based Posner cueing task. Participants were grouped based on neglect-related functional disability and assessed using the line bisection task and clock drawing test, forming non-neglect and neglect groups. We then compared their performance on the shape discrimination task, derived from the Posner cueing task, with healthy participants within aSC and eSC, respectively. This study aimed to use the Posner cueing-target paradigm to distinguish psychological characteristics related to visuospatial attention in individuals post-stroke, with or without neglect, and healthy individuals across different visual frames of reference.

Participants

We studied 18 right-handed healthy volunteers aged 23.89 ± 3.44 years with no history of neurological, psychiatric, or ophthalmological conditions, comprising the healthy control group (HC group). None of the participants had taken sleeping pills, painkillers, antidepressants, alcohol, or other drugs within 1 month, nor had they experienced a cold or fever within 1 week. All participants volunteered and provided informed consent.

We recruited 13 right-handed individuals aged 32.83 ± 4.45 years with unilateral visuospatial neglect due to right-hemispheric stroke (USN + group). Inclusion criteria were: (i) age 20–79 years; (ii) diagnosis by a neurologist confirmed by head CT or MRI; (ⅲ) right-hemispheric cortical and subcortical lesions; (ⅳ) ≥ 3 months [18] post-acquired brain injury resulting in spatial neglect, defined as deficient performance on the line bisection task. Participants were required to bisect 20 lines of varying lengths (100, 120, 140, 150, 160, 180, and 200 mm) by placing a small pencil mark through each line as close to the center as possible. An ipsilesional deviation above 9.5% indicated spatial neglect [19, 20]. (ⅴ) ability to maintain alertness and basic cognitive function with a mini-mental state examination (MMSE) score above 20 [21]; and (vi) normal or corrected vision. Exclusion criteria were: (i) age > 80 years; (ⅱ) hemianopsia or severe vision defects preventing task performance; (ⅲ) inability to maintain alertness, consciousness, or arousal; (ⅳ) right visual space neglect; and (ⅴ) other neurological or psychiatric conditions (e.g., dementia, schizophrenia) precluding participation or altering data interpretation.

We also recruited 10 right-handed individuals aged 32.6 ± 5.18 years who had experienced right-hemispheric strokes without unilateral visuospatial neglect (USN- group). The inclusion and exclusion criteria were the same as those for the neglect group. These individuals were not diagnosed with spatial neglect based on their performance on the line bisection task. All participants provided written informed consent before the study began. The study was approved by the Ethics Committee of Xiamen Fifth Hospital (approval number: XMWY-K2022-036).

Apparatus and Stimuli

The study was conducted in a clean, quiet room with a computer placed on an adjustable-height desk. Stimuli were displayed on a 23.8-inch LCD monitor with dimensions of 53.5 cm × 30.8 cm. Participants sat upright on a chair with a backrest, positioning their eyes 65 cm from the screen. The desk height was adjusted so that the participants' horizontal sightline aligned with the median line of the screen. A software package (E-Prime 3.0, Psychology Software Tools, 311 23rd Street Ext., Suite 200 Pittsburgh, USA) was used to control the stimulus presentation and response collection.

Cueing-Target Paradigm and Procedures

We employed a computer-based attention task by Chan to study attention control networks [15], which involved detecting shapes using a cue-to-target paradigm adapted from Wilson and Woldorff [22]. The visual-spatial attention task consisted of aSC and eSC. The aSC attention test was completed first, followed by the eSC attention test. Each test comprised 40 trials. Each trial began with the presentation of three stimuli and a cue for 1000 ms. The stimuli included one rectangular and two square markers. A pair of empty square placeholders (3.75° vertically and horizontally to the center in each direction) and one empty rectangular placeholder (3.75° vertically and 12.2° horizontally to the center) were displayed. The cue was a Chinese character presented at the center, either inclined ("左"/"右") in the aSC condition or upright ("左"/"右") in the eSC condition, indicating the type of response required later in the trial. The cue was followed by a stimulus-onset asynchrony (SOA) of 500 ms, during which a dot replaced the Chinese character. In the target phase, four squares appeared, two at each end of the rectangle. One of the four squares showed a "+" sign indicating the target, while the other three “*” showed asterisks, indicating distractors. The participant was instructed to determine whether the target "+" was on the left or right side by pressing the corresponding left or right button. The target picture was displayed for 3000 ms. In the eSC condition, the target "+" appeared in one of the squares outside the rectangle, and participants indicated whether the target was located on the left or right relative to their bodily coordinates. In the aSC condition, the target appeared inside the rectangle, and participants indicated whether the target was on the left or right side of the rectangle, regardless of their bodily coordinates. Finally, an intertrial interval with varying delays of 4000, 4500, 5000, and 5500 ms was organized randomly. Word and font combinations were counterbalanced across all participants.

There were three types of trials: valid, invalid, and neutral, with a ratio of 3:1:1. In valid trials, the target location was consistent with the information provided by the cue. In invalid trials, the target location was inconsistent with the cue. In neutral trials, the cue provided no information about the target location. The distribution of each trial type to the left or right was counterbalanced. The entire visual-spatial attention task took approximately 15 minutes to complete.

Training Session

All participants completed a training session to familiarize themselves with the task before the experiment. Participants practiced a simplified version of the spatial attention task twice daily for two consecutive days to ensure they were comfortable with the process, thereby avoiding result bias caused by unfamiliar experimental methods. All participants were required to achieve at least 80% accuracy in the total trials before advancing to the experiment.

Statistical Analysis

Demographic Information

Basic demographic information included age, sex, disease course, and MMSE scores. Quantitative data were described as mean ± standard deviation (‾X ± Sd). SPSS software (Version 25.0, IBM, USA) was used for the analysis. The Shapiro–Wilk test was employed to check for normality. If the data followed a normal distribution, a t-test or analysis of variance (ANOVA) was used; otherwise, a nonparametric test was applied. Categorical data were described by composition ratio (frequency %), and the chi-squared test was used for comparison.

Visuospatial Attention Ability

Visuospatial attention ability was assessed using AR and RT. Three components of visual attention typically impaired in hemispatial neglect were analyzed: (ⅰ) lateralized deficit in visual perception and attention. The target detection index (TDI), which reflects the speed of the response time difference, was calculated by subtracting right from left target trials. A positive TDI indicated slower attention response to targets in the contralesional visual field. (ii) Deficit in reorienting spatial attention. The validity effect was observed as a relative delay in responding to targets at unattended locations compared to attended locations. (ⅲ) Deficit in disengaging attention. The disengagement deficit was due to the ipsilesional field, reflected by difficulties in responding to unattended targets in the contralesional field.

For group-level analysis of visuospatial attention ability, only the time for accurate responses was counted. A multivariate repeated-measures ANOVA was performed to test the interactions (3× 2 × 3: group [USN+, USN-, and HC] × visual field site [left and right] × trial type [valid, invalid, and neutral]). Fisher's least significant difference test was used for post hoc analysis. Statistical significance was set at P < 0.05.

Basic Information

We screened 176 patients with right-hemispheric brain injuries who were hospitalized in the Department of Rehabilitation Medicine between January and December 2023. Of these, 13 patients were excluded due to non-compliance with the test, six due to visual impairments that prevented symbol recognition, seven due to hemianopsia, one who could not read or write, seven who could not complete the workload during the preliminary spatial attention test stage, and nine patients whose missing data exceeded 40%. Ultimately, we included 13 USN + patients with an average onset time of 15.33 ± 5.9 months and 10 USN- patients with an average onset time of 12.4 ± 8.79 months. There were no significant differences in age or disease course between the two groups (P > 0.05). Additionally, 18 healthy subjects were included in Table 1. There were significant differences in MMSE scores between post-stroke patients (F2,38 = 43.08, P < 0.0001). Brain lesion volume analysis showed in Table 2 that the USN + group had significantly larger lesion volumes than the USN- group (t = 2.304, P = 0.032).

Table 1

Basic demographic information
Group	USN+	USN-	HC
Case number	13	10	18
Gender(Male)	83%	50%	66.67%
Age	32.83 ± 4.45	32.6 ± 5.18	23.89 ± 3.44
Disease duration	15.33 ± 5.9	12.4 ± 8.79	NA
Score of MMSE	20.83 ± 3.13	25.8 ± 3.27	29 ± 0.71
Cerebral hemorrhage	76.90%	80%	NA
lesion volumescm³	47.43 ± 10.22	19.16 ± 4.19	NA

Table 2

Focal areas of post-stroke patients (right hemisphere injury)
subjects	pre-frontal lesion	pre-central lesion	Posterior parietal lesions	lesion of temporo-parietal junction	temporal lobe lesions	occipital lesion	basal ganglia lesion	pyramidial tract /internal capsule lesion	lesion volumes (cm³)
USN+
1			√	√				√	14.4
2			√	√					83.4
3		√	√	√			√		34.5
4			√	√					35.3
5				√		√	√		120
6	√	√	√	√					61.4
7	√	√		√					94.5
8				√			√		8.6
9	√	√	√	√			√	√	15.6
10	√	√	√						82.3
11	√						√		32.3
12	√	√	√	√	√				24.6
13		√	√	√			√		9.7
USN-
1	√	√			√		√	√	35.2
2	√						√	√	19.1
3					√	√		√	7.2
4							√	√	43.9
5	√	√							13.6
6	√				√				2.8
7		√			√		√		26
8	√						√		25
9					√		√		8
10	√	√							10.8

Table 1 Basic demographic information

Table 2 Focal areas of post-stroke patients (right hemisphere injury)

AR

Accuracy measures in the aSC, in Table 3, expressed as percentage correct, were analyzed using the chi-square test, showing significant differences in overall accuracy among the three groups (X² = 126.094, P < 0.001). A pairwise comparison of multiple sample rates using the Bonferroni method (adjusted test levelα'=0.0167) revealed that the AR of the USN + group in the aSC was significantly lower than that of the USN- group (X² = 50.889, P < 0.001) and the HC group (X² = 90.679, P < 0.001). No significant difference in accuracy was found between the USN- and HC groups (P = 0.647).

Table 3

Behavioral data of error rate in aSC
Groups	Valid cue	Invalid cue	Neutral cue	overall	Left field	Right field
USN+	25.00%	39.42%	35.58%	30.00%	30.00%	30.00%
USN-	5.00%	2.50%	7.50%	5.00%	4.00%	6.00%
HC	3.24%	6.94%	4.17%	4.17%	3.89%	4.44%

A one-way ANOVA of AR under different cue types (valid, invalid, neutral) in the aSC condition showed significant differences in the USN + group (X² = 9.652, P = 0.008). However, there was no effect on AR scores in the USN- (P = 0.591) or HC groups (P = 0.396). Further analysis revealed that AR in the USN + group was significantly higher in the valid cue condition compared to the invalid and neutral cue conditions (X² = 30.602, P < 0.001; X² = 39.605, P < 0.001), in Table 3.

In all cue situations, AR in the aSC condition was ranked as follows: HC_allo>USN-_{_allo}>USN+_{_allo} (X² = 60.04, P < 0.001; X² = 37.06, P < 0.001; X² = 31.07, P < 0.001). Additionally, the USN + group had significantly lower AR scores in the aSC condition in both the left and right visual fields compared to the USN- and HC groups (X² = 66.03, P < 0.001; X² = 59.72, P < 0.001). No significant effects were observed in the USN- and HC groups (P = 0.937, P = 0.567), in Fig. 1.

Table 3 Behavioral data of error rate in aSC

The AR in the eSC condition, Table 4, ranked as HC_ego > USN-_ego > USN+_ego was analyzed using the chi-square test, which showed significant differences in overall accuracy among the three groups (X² = 189.461, P < 0.001). Pairwise comparisons revealed that the AR in the USN + group in the eSC condition was significantly lower than that of the USN- group (X² = 82.940, P < 0.001) and the HC group (X² = 121.51, P < 0.001). No significant difference in AR was found between the USN- and HC groups (P = 0.279).

Table 4

Behavioral data of error rate in eSC
Groups	Valid cue	Invalid cue	Neutral cue	overall	Left field	Right field
USN+	28.50%	49%	40.40%	35.00%	32.69%	37.31%
USN-	0.80%	5%	2.40%	2.00%	1%	1%
HC	2.80%	6.90%	2.80%	3.60%	3.90%	3.30%

Further analysis of AR using a one-way ANOVA of cue type (valid, invalid, neutral) in the eSC condition showed significant differences in the USN + group (X² = 16.083, P < 0.001). The USN + group had significantly higher AR scores in the valid cue condition than in the invalid and neutral cue conditions (X² = 14.699, P < 0.001; X² = 5.083, P = 0.024), with no significant difference between the invalid and neutral cues (X² = 1.575, P = 0.209). Across all cue types, the AR in the eSC condition was ranked as HC_ego > USN-_ego > USN+_ego (X² = 46.905, P < 0.001; X² = 50.315, P < 0.001; X² = 90.15, P < 0.001, respectively). The USN + group showed significantly lower AR scores in the eSC condition in both the left and right visual fields compared to the USN- and HC groups (X² = 39.89, P < 0.001; X² = 53.36, P < 0.001). No significant effects were observed in the USN- and HC groups (P = 0.164, P = 0.231), in Fig. 2.

Table 4 Behavioral data of error rate in eSC

Overall, the AR scores of USN + participants did not differ significantly between the aSC (70%) and eSC (65%) trials (P = 0.085). Similarly, the USN- and HC groups showed no significant difference in AR scores between the aSC (95% and 95.83%) and eSC (98% and 96.4%) trials (P = 0.099 and P = 0.70, respectively).

RT

In the aSC condition, multi-way ANOVA for RT indicated no significant interaction between groups × visual field × cue type (F4,852 = 0.082, P = 0.998). However, a significant main effect was found for the groups (F2,852 = 1133.737, P < 0.001), with no significant main effect for visual field or trial type (P = 0.247, P = 0.614). Post-hoc (least significant difference) testing revealed that the total RT was greater in the USN + group compared to the USN- and HC groups (P < 0.001), with significant differences between the latter two (P = 0.02). RT in the aSC condition in Table 5 was ranked as USN+_allo > USN-__allo>HC_allo, indicating that the USN + group required significantly more time to recognize the target compared to the USN- and HC groups in the aSC condition.

Table 5

Response time in aSC condition (ms)
Group	aSC	Mean	SEM	95% Confidence Interval
Group	aSC	Mean	SEM	Lower Bound	Upper Bound
USN+	LVF allo-target	2753.42	167.869	2422.75	3084.09
	RVF allo-target	2554.65	155.04	2249.21	2860.10
	Total RT	2450.82	110.039	2234.65	2667.00
USN-	LVF allo-target	861.09	34.049	793.41	928.77
	RVF allo-target	818.13	24.486	769.45	866.80
	Total RT	798.66	24.052	751.20	846.11
HC	LVF allo-target	403.35	6.988	389.55	417.14
	RVF allo-target	434.41	6.657	421.27	447.54
	Total RT	419.05	4.888	409.44	428.67

There were also significant differences in RT between the left and right visual fields (LVF and RVF) across groups (F2,431 = 81.287, P < 0.001; F2,433 = 77.203, P < 0.001) in Fig. 3. Post-hoc tests revealed that USN + participants had significantly longer RT in the LVF compared to the USN- (P < 0.001) and HC groups (P < 0.001), with a significant difference between the latter two groups (P = 0.033). In the RVF, the USN + group also had significantly longer RT than the USN- (P < 0.001) and HC groups (P < 0.001), with no significant difference between the latter two (P = 0.055). These findings suggest that the RT of the USN + group for identifying targets in both visual fields in the aSC condition was significantly prolonged.

Table 5 Response time in aSC condition (ms)

In the eSC condition, multi-way ANOVA for RT indicated no significant interaction effects between groups × visual field × cue types (F4,865 = 0.779, P = 0.539). However, a significant interaction effect was found between groups × visual field (F2,865 = 3.074, P = 0.047). There was no significant main effect of cue type (P = 0.549), but a significant main effect was observed for groups (F2,865 = 99.094, P < 0.001). Post-hoc tests indicated that RT in the eSC condition in Table 6 was ranked as USN+__ego>USN-_{_ego}>HC_ego, with the mean total RT value being longer in the USN + group than in the USN- and HC groups (P < 0.001), while showing significant differences between the latter two (P = 0.041). This suggests that the USN + group spent significantly more time recognizing the target in the eSC condition.

Table 6

Response time in eSC condition (ms)
Group	eSC	Mean	SEM	95% Confidence Interval
Group	eSC	Mean	SEM	Lower Bound	Upper Bound
USN+	LVF ego-target	2594.18	188.14	2223.37	2964.98
	RVF ego-target	2549.07	174.92	2177.03	2858.01
	Total RT	2571.12	128.13	2319.31	2822.93
USN-	LVF ego-target	731.78	17.83	697.61	768.86
	RVF ego-target	794.95	24.98	743.78	823.74
	Total RT	763.36	15.47	732.86	793.87
HC	LVF ego-target	409.16	7.15	394.37	423.34
	RVF ego-target	439.54	12.61	409.93	457.95
	Total RT	424.31	7.27	410.01	438.61

There was a significant difference in RT between the LVF and RVF among groups (P < 0.001) in Fig. 4. Post-hoc tests revealed that USN + participants had significantly longer RT than the USN- (P < 0.001) and HC groups (P < 0.001) in both the LVF and RVF. However, no significant difference was found between the latter two in the LVF (P = 0.186) and RVF (P = 0.176). These findings suggest that the RT of the USN + group to recognize targets from both visual fields in the eSC condition was significantly prolonged.

Table 6 Response time in eSC condition (ms)

Overall, an independent-samples t-test for RT indicated no significant difference between the reference frames of aSC (2655.49 ± 114.37ms) and eSC (2571.12 ± 128.13ms) in the USN + group (P = 0.623). Similarly, no significant differences in RT were found between the reference frames of aSC (794.66 ± 24.05ms, 419.05 ± 4.88ms) and eSC (755.732 ± 16.23ms, 424.31 ± 7.27ms) in the USN + and HC groups (P = 0.134 and P = 0.552, respectively). This suggests that participants, regardless of neurological damage, took about the same time to orient and focus on the target from both the eSC and aSC reference frames (P > 0.05) in Fig. 5. However, significant differences in RT for the LVF were found between the aSC and eSC reference frames in the USN + and USN- groups (P < 0.05), while no significant difference was observed in the HC group (P > 0.05). The USN + group spent more time identifying LVF targets in the aSC frame (2550.69 ± 185.13 ms) compared to the eSC reference frame (1947.74 ± 174.46 ms; t = 2.366, P = 0.019). Similarly, the USN- group spent more time identifying LVF targets in the aSC (861.09 ± 34.05 ms) compared to the eSC reference frame (733.23 ± 17.95 ms; t = 3.418, P = 0.001). Interestingly, no significant differences in RT were found between the aSC and eSC reference frames for the RVF in any group (P > 0.05).

Lateralized Spatial Attention

In the aSC condition, a two-way ANOVA for the TDI indicated no significant interaction effects for groups × cue types (F4,490 = 0.687, P = 0.602). However, a significant main effect for the groups was found (F2,490 = 4.34, P = 0.013). Post-hoc tests revealed that the USN + group showed a significant rightward bias (432.14 ms) compared to the USN- group (96.28 ms less rightward bias, P = 0.041) and the HC group (24.87 ms more leftward bias, P = 0.001). Significant differences were also observed between the USN- and HC groups in terms of spatial bias (P = 0.032).

In the eSC condition, the two-way ANOVA for the TDI indicated no significant interaction effects for groups × cue type (P = 0.101) or a main effect for cue types (P = 0.473). However, a significant main effect was found for the groups (F2,491 = 5.049, P = 0.007). Post-hoc tests showed that the USN + group exhibited a significant rightward bias (476.73 ms) compared to the USN- group (182.22 ms more leftward bias, P < 0.001) and the HC group (25.09 ms more leftward bias, P = 0.001). No significant differences in spatial bias were observed between the USN- and HC groups (P = 0.404).

The performance on the Posner cueing task confirmed these findings (Table 7 and Fig. 6), indicating that the USN + group produced notably slower response times when identifying LVF targets compared to the USN- and HC groups in both the aSC and eSC conditions. This result also indicates that USN + individuals exhibited a typical attentional rightward bias during visuospatial attention.

Table 7

TDI in aSC and eSC condition
frame	Groups	Mean	SEM	95% confidence interval
frame	Groups	Mean	SEM	Lower	Uper
allocentric	USN+	432.14	119.47	196.79	667.47
	USN-	96.28	45.72	5.39	187.16
	HC	-24.87	8.41	-41.47	-8.26
egocentric	USN+	476.73	139.16	202.54	750.93
	USN-	-182.22	100.99	-382.66	18.21
	HC	-25.09	11.95	-48.67	-1.51

Table 7 TDI in aSC and eSC conditions

Validity Effect

Tables 8 and 9, along with Figs. 7 and 8, graphically present the data for the USN+, USN-, and HC groups. The data were analyzed using a two-factor ANOVA with target site (left vs. right) and cue type (valid vs. invalid vs. neutral) manipulated within subjects in each group. In the aSC condition, the only significant main effect was for cue types in the HC group (F2,346 = 10.275, P < 0.001). Post-hoc tests revealed that the RT for the invalid cue was slower than for the valid (P < 0.001) and neutral cues (P = 0.808), and the RT for the neutral cue was slower than for the valid cue (P = 0.001).

Table 8

Response time between cue types in the aSC condition (ms)
Group	Cue types	Mean	SEM	95% Confidence Interval
Group	Cue types	Mean	SEM	Lower Bound	Upper Bound
USN+	valid	2604.19	146.002	2316.84	2891.54
	invalid	2790.37	262.67	2268.98	3311.77
	neutral	2677.35	259.197	2162.25	3192.45
USN-	valid	855.02	28.555	798.4	911.64
	invalid	787.43	32.684	721.01	853.85
	neutral	845.91	51.486	741.16	950.66
HC	valid	401.78	5.096	391.74	411.83
	invalid	446.87	12.955	421.04	472.71
	neutral	443.19	12.974	417.29	469.1

Table 9

Response time between cue types in eSC condition
Group	Cue types	Mean	SEM	95% Confidence Interval
Group	Cue types	Mean	SEM	Lower Bound	Upper Bound
USN+	valid	2591.64	165.54	2265.74	2917.55
	invalid	2473.91	291.96	1893.52	3054.30
	neutral	2602.98	283.28	2040.02	3165.93
USN-	valid	777.83	22.33	733.61	822.04
	invalid	706.97	21.63	663.14	750.80
	neutral	773.55	30.00	712.86	834.24
HC	valid	410.12	9.30	391.78	428.45
	invalid	453.89	15.54	422.91	484.87
	neutral	437.11	16.91	403.39	470.83

Table 8 Response time between cue types in the aSC condition (ms)

In the eSC condition, the only significant main effect was also for cue types in the HC group (F2,359 = 3.151, P = 0.044). Post-hoc tests showed that the RT for the invalid cue was slower than for the valid cue (P = 0.019) and the neutral cue (P = 0.462), with no significant difference between the RT for the valid and neutral cues (P = 0.148).

Table 9 Response time between cue types in eSC condition

Disengagement Deficit

A significant main effect for the groups (F2,982 = 142.365, P < 0.001) was found in both the aSC (F2,989 = 114.892, P < 0.001) and eSC conditions. In the valid cue condition, the USN + group exhibited significantly slower reaction times for target identification compared to the USN- (P < 0.001, P < 0.001) and HC groups (P < 0.001, P < 0.001). There was also a significant difference between the USN- and HC groups in the aSC condition (P = 0.03), but no significant difference was observed in the eSC condition (P = 0.081). In the invalid cue condition, the USN + group produced significantly slower reaction times to identify the targets than the USN- (P < 0.001, P < 0.001) and HC groups (P < 0.001, P < 0.001) in both the aSC and eSC conditions, with no significant differences between the USN- and HC groups (P = 0.359, P = 0.488). In the neutral cue condition, the USN + group again had significantly slower reaction times compared to the USN- (P < 0.001, P < 0.001) and HC groups (P < 0.001, P < 0.001) in both the aSC and eSC conditions, with no significant differences between the USN- and HC groups (P = 0.257, P = 0.341).

Additionally, the USN + group had significantly slower RTs for unattended (invalidly cued) targets in the contralesional hemifield compared to the USN- (P = 0.001, P < 0.001) and HC groups (P < 0.001, P < 0.001) in both the aSC and eSC conditions. No significant differences were observed between the USN- and HC groups (P = 0.565, P = 0.625).

This study used a shape discrimination task based on the Posner cueing-target paradigm to distinguish the psychological characteristics related to visuospatial attention in individuals post-stroke, with or without neglect, and healthy controls across different visual frames of reference. The USN + group exhibited significantly lower AR than the USN- and HC groups in both the aSC and eSC conditions for the LVF and RVF, regardless of cue type. Similarly, the USN + group demonstrated slower reaction time compared to the USN- and HC groups across both conditions. Notably, the USN + group exhibited slower reaction times when identifying the relative RT delay for LVF targets in the contralesional visual field compared to the ipsilesional visual field, a difference not observed in the USN- and HC groups. These findings suggest that the USN + group exhibited a characteristic attentional rightward bias in visual perception and attention.

While no significant difference in AR or total RT was observed between the aSC and eSC conditions, the USN + and USN- groups took longer to identify LVF targets in the aSC compared to the eSC reference frame. This finding suggests that individuals post-stroke, with or without neglect, exhibited a more pronounced attentional deficit in allocentric compared to egocentric spatial processing, particularly when detecting targets in the contralesional visual field versus the ipsilesional visual field.

In all cue types, the USN + group demonstrated significantly slower reaction times for both visual fields compared to the USN- and HC groups in the aSC and eSC conditions. However, only healthy participants exhibited a significantly positive validity effect, with slower RTs following invalid cues compared to valid cues in both conditions. In the HC group, target detection latency influenced by valid-invalid cues reflected the ability to disengage from the current attentional focus, while the influence of valid-neutral cues reflected attentional alertness and distribution. The absence of significant RT delays between cue types in the USN + and USN- groups suggests difficulties with basic attentional processes, such as disengaging from the current focus, shifting to the target, and engaging with the target. Furthermore, the USN + group exhibited significantly slower RTs for invalidly cued targets in the contralesional hemifield compared to the USN- and HC groups in both the aSC and eSC conditions, indicating a disengagement deficit in individuals with neglect during visual attention.

Typical Attentional Rightward-Bias

The statistical analysis confirmed that the USN + group had slower reaction times compared to the USN- and HC groups in both the aSC and eSC conditions. Additionally, the USN + group exhibited prolonged RTs for identifying targets from both the left and right visual fields in the aSC and eSC conditions, significantly more prolonged than in the USN- and HC groups. This finding aligns with previous studies. Machner B et al.[17] found that individuals with severe neglect had lower detection rates than other study groups in both hemifields. In the Posner reaction time test, individuals with neglect had higher RTs compared to healthy controls and "no neglect" individuals, with the slowest RTs observed in individuals with severe neglect for targets in both the left and right hemifields. Similarly, Ptak and Schnider [23] reported a high rate of missed targets in individuals with neglect, while healthy and right-hemisphere control groups had fewer missed targets. They also noted that the mean RT for left hemifield targets in individuals with neglect was slower than in healthy and right-hemisphere-damaged controls. However, the studies mentioned above on spatial attention did not differentiate between allocentric and egocentric frameworks.

The most notable findings suggest that the USN + group had significantly slower reaction times in identifying LVF targets compared to the USN- and HC groups in both the aSC and eSC conditions. This indicates that the USN + group exhibited a characteristic attentional rightward bias in temporal dynamics during visuospatial attention. Our findings align with those of other studies, such as Ptak and Schnider, who found that individuals with neglect had a significantly higher TDI than healthy and right-hemisphere controls [23]. Similarly, Posner et al. discovered that individuals with neglect were particularly slow in responding to left-sided targets following right-sided cues [16]. Rabuffetti et al.[24] compared the latency of left-right target detection and found that latency increased overall in individuals with USN compared to controls, with a significantly negative latency gradient indicating worsening performance toward the left side. This rightward attentional orienting bias is typical in individuals with neglect following right-hemispheric strokes. Moreover, in the present study, slower reaction times for left-right target detection were observed not only in the aSC condition but also in the eSC condition. Healthy participants showed no noticeable leftward or rightward bias in either condition. However, the USN- group in our study exhibited a prominent rightward bias in the aSC condition and a leftward bias in the eSC condition, suggesting that the underlying neural mechanisms of this opposite direction in time lateralization warrant further investigation. We observed congruency in behavioral performance as individuals with right-hemispheric stroke displayed some degree of visuospatial attention dysfunction, reflected in missed AR and slower reaction times in the contralesional visual field, placing them between the healthy and neglect groups. This finding aligns with Umarova et al. [25], who reported that individuals showed a rightward bias during visual attentional processing, with progressively increasing reaction time (RT) differences between targets detected in the left versus right visual hemifields, from control and extinction individuals to neglect individuals in behavioral testing. Additionally, our study confirms that individuals with neglect and right-hemispheric damage exhibited a typical rightward attentional bias in temporal dynamics during visuospatial attention processing, as seen in left versus right reaction time lateralization. Van Vleet T et al. [26] also investigated 49 participants with hemispatial neglect who demonstrated significant spatially biased attention during the Posner cueing task. Their study showed that alertness training could reduce the RT difference between detecting left and right targets, indicating that improvements in spatially rightward-biased attention accompanied functional recovery in individuals with neglect.

Reference Frame Effects

Our study revealed that both the USN + and USN- groups took significantly longer to identify targets in the contralesional visual field in the aSC compared to the eSC reference frame. Interestingly, no significant differences were observed in RT for the ipsilesional visual field between the aSC and eSC reference frames across all groups. Neither AR nor total RT differed significantly between the aSC and eSC conditions. This pattern of longer response times in the aSC condition relative to the eSC condition suggests that processing target identification in the contralesional visual field may require more complex spatial attention processing in the allocentric condition than in the egocentric condition. Similar findings were reported by Wilson et al. [22], who, using the cueing-target paradigm adapted from our study, observed a non-significant trend for longer response times in the aSC condition compared to the eSC condition. Moreover, the total accuracy measures, expressed as percentage correct, did not differ between viewer-centered and object-centered trials. However, accuracy in the RVF was higher than in the LVF trials, indicating a lateralized deficit in visual perception and attention across both the aSC and eSC conditions. Wilson et al. [22] concluded that the object-centered (allocentric) condition was more challenging than the viewer-centered (egocentric) condition. Moraresku et al. [27] employed a task involving 3D scenes of a circular arena containing three objects, asking participants to judge whether a ball was closer to their current point of view (egocentric) or to a yellow mark (allocentric). They found no significant difference in AR between the egocentric and allocentric conditions (P = 0.473)., but reaction times in the allocentric condition were significantly slower than those in the egocentric condition. Our findings, which suggest more complex spatial attention processing in the allocentric condition compared to the egocentric condition, align with Moraresku et al. [27]. Their results support the view that egocentric representations are primary and allocentric representations are secondary, derived by translating egocentric representations during visual scene encoding. Several neuroimaging studies have corroborated this view, demonstrating large overlapping patterns of activation in both allocentric and egocentric selectivity in brain regions [22], including bilateral areas such as the intraparietal sulcus, frontal eye fields, supplementary motor and anterior cingulate cortices, and the left dorsolateral prefrontal cortex. Most frontoparietal attentional control networks were more heavily recruited during object-centered attention than during viewer-centered attention. Arrington et al. [28] also noted that orienting attention in an object-centered coordinate system requires additional processing resources beyond those used for orienting attention in the more common viewer-centered reference frame.

Cue-Related Attentional Efficiency

The cue-related validity effect only influenced the healthy groups' relative RT delays when responding to targets at unattended (invalidly cued) locations compared to attended (validly cued) locations (P < 0.05). In contrast, no significant difference was found between RTs in the invalid and valid trials for the USN + and USN- groups. Moreover, both the USN + and USN- groups, regardless of cue type, exhibited slower RTs for target identification in both hemifields compared to the HC group in the aSC and eSC conditions. These results show that there was no significant validity effect for individuals with or without neglect, while a significant validity effect was present for the HC group. Additionally, the USN + group demonstrated significantly slower RTs for unattended (invalidly cued) targets in the contralesional hemifield compared to the USN- and HC groups in both the aSC and eSC conditions, with no significant difference observed between the USN- and HC groups. This suggests that individuals with neglect experience a disengagement deficit during visuospatial attention.

Our results demonstrated that the absence of a validity effect indicated a deficit in reorienting spatial attention in individuals with or without neglect. The "Posner task," developed by Posner et al., is commonly used to examine processes involving visuospatial attention [29]. The paradigm can be modified based on the type of cue employed, such as a central arrow or words, as in the present research, or an eye gaze cue, as demonstrated in the work of Goldberg et al. [30], where the cue was used to direct visuospatial attention to a location in the periphery. Machner et al. [17] also found that healthy controls exhibited a validity effect only for targets in the right hemifield, while invalid cues caused individuals with neglect to show increased RTs for targets in either hemifield, indicating a reorientation deficit in individuals with neglect. Compared with typically developing (TD) children, who consistently exhibited slower RTs on invalid trials than on valid trials, children with high-functioning autism (HFA) showed no significant validity effect. The lack of an RT advantage on valid trials for children with HFA compared to invalid trials [30] suggests impairments in utilizing static line drawings of gaze cues to orient visuospatial attention.

The results of the present study differ from those of Ptak et al. [23], who found that individuals with neglect exhibited a deficit in reorienting spatial attention, with a larger validity effect (a positive value indicating slower RTs following invalid than valid cues) than in healthy and RH control groups. Our results were also not consistent with those of Posner et al., who observed that responses to valid contralateral targets were faster than those to invalid ipsilateral targets, suggesting a validity effect for spatially primed contralateral targets and that the move operation was not responsible for the increased RTs in response to invalidly cued contralateral targets [16]. In our study, both invalid and valid cues in the USN + and USN- groups led to prolonged RTs for contralateral and ipsilateral targets. Regardless of cue type, target identification in both hemifields was significantly slower in the USN + and USN- groups compared to the HC group under both aSC and eSC conditions. This suggests a potential directional impairment and slowing of the move operation. The inconsistencies in the validity effect might be related to the ratio of valid to invalid cues. For example, Goldberg et al. [30] found a significant validity effect in children with HFA using the "Posner task," which involved 48 trials with 50% valid and 50% invalid cues. In contrast, Ristic et al. [31] found that adults with HFA did not show significant validity effects in response to eye gaze cues with 50% validity but did show significant validity effects when the eye gaze cues were 80% predictive of the target location. Due to the brain's limited processing capacity, certain visual features receive higher processing priority, a process termed feature-based attention (FBA). Huang et al. [32] demonstrated that in an orientation discrimination task, discrimination speed was significantly faster following a valid cue than an invalid cue (validity effect) when 80% cue validity was emphasized for both response accuracy and speed. This validity effect was also observed, though reduced, in the session with 50% cue validity using the line cue, but it disappeared in the session with 50% cue validity using the symbolic cue. This suggests that both top-down attention mediation and feature priming are important mechanisms for FBA. In contrast to our findings, where no validity effect was found in individuals with or without neglect, healthy participants did show a significant validity effect in the session with a 500 ms SOA and 60% valid and 20% invalid word cues. Ptak et al. [23] found a larger validity effect in individuals with neglect compared to healthy and RH-controls in a session with a 200 ms SOA and 50% valid and 50% invalid rectangle-shaped cues. Future studies should investigate how individuals with neglect perform tasks with varying cue validity ratios to predict target location and different SOA lengths between cueing-target presentations.

Our results on disengagement deficits align with previous studies, showing poorer performance for unattended targets in the left visual field during visuospatial attention. Rengachary et al. [33] reported that disengagement deficits were significantly greater in acute patients than in controls but not in chronic patients during the Posner task. This suggests that these deficits may persist permanently in longitudinally measured processing in individuals with neglect. Morrow and Ratcliff [34] further demonstrated that disengagement deficits, measured using pencil-and-paper cancellation tasks in the Posner task, correlated with the severity of neglect.

Clinical and Functional Implications of" Subclinical" Lateralized Attention Deficits

The Posner cueing task, a computerized task requiring time-limited accuracy, revealed detection and reorienting deficits in the patient groups compared to healthy controls. Individuals with and without neglect exhibited lateralized attention deficits in both the aSC and eSC conditions. Specifically, USN + individuals demonstrated a typical rightward attentional bias in temporal dynamics during visuospatial attention. However, USN- individuals with right-hemispheric stroke exhibited a prominent rightward bias in the aSC condition and a leftward bias in the eSC condition, indicating some degree of visuospatial attention dysfunction. This was evident in missed AR and slower reaction times in the contralesional visual field, positioning them between the healthy and neglect groups. As noted earlier, the time-limited computerized desk task revealed spatial attention bias in individuals with right-hemispheric stroke, without clinical signs of neglect, that was not detected by established paper-and-pencil tests. Our findings of "subclinical" lateralized attention deficits in the USN- group align with those of Machner et al. who observed a similar pattern[17]. They noted that the sensitivity of detecting lateralized spatial attention deficits in individuals who suffered a right-hemispheric stroke for the first time was higher using specialized assessments compared to conventional bedside tests. Similarly, Rengachary et al. [35] tested individuals with neglect in both the acute and chronic stages using clinical and Posner tests, demonstrating that computerized reaction time tests can detect subtle but clinically significant left neglect, which may not be identifiable by conventional clinical tests, especially in the chronic stage. It is well established that time-limited tasks with high attentional demands can reveal "hidden" attention deficits in individuals with mild or recovered neglect, who may otherwise compensate during simple paper-and-pencil tests without time constraints [13, 14]. Assessing neglect is crucial because failing to identify it can significantly impair all activities of daily living in stroke survivors [36]. Although mild and subclinical lateralized attention deficits may not be apparent in daily activities as measured by clinical tests, they can still affect functional performance, particularly in high-attention-demand environments. These deficits are often better detected in complex, time-limited tasks where multiple objects compete for attention. This hypothesis is supported by a case report of an individual with a right-hemispheric stroke who, despite fully recovering from initial neglect based on behavioral attention test performance, was involved in nine car accidents, all affecting the left side of his car [37]. Deouell et al. [37] found that such individuals exhibited slower responses to left-sided events than right-sided events in a computerized, dynamic RT task. Therefore, clinicians should prioritize time-limited computerized tasks, such as the Posner cueing task, when assessing individuals with neglect and subclinical neglect. However, a survey of self-reported assessments by Gasque et al. [38] revealed that most occupational therapists preferred using short paper-and-pencil assessments for quick evaluations rather than more sensitive assessments that could more accurately identify neglect despite expressing high confidence in their routine neglect assessments. This highlights the need for increased clinical education about neglect and its assessment methods.

This study has several limitations. Firstly, the relatively small sample size may limit the generalizability of the findings. Additionally, the study focused primarily on individuals with right-hemisphere stroke, which restricts insights into whether similar deficits occur in left-hemisphere stroke cases. Future studies should aim to include larger sample sizes, covering both the subacute and chronic phases of visuospatial neglect, and explore more sensitive diagnostic tools. Moreover, neuroimaging studies should be employed to investigate the neural mechanisms underlying attentional deficits in both allocentric and egocentric reference frames.

In conclusion, the present study demonstrated that individuals with neglect exhibited a typical rightward attentional bias in temporal dynamics during visuospatial attention in both the aSC and eSC conditions. "Subclinical" lateralized attention deficits were observed in individuals without neglect, who displayed a prominent rightward bias in the aSC condition and a leftward bias in the eSC condition. Our study emphasizes the importance of using time-limited, complex tasks to detect subtle attention deficits in stroke survivors, potentially improving the diagnosis and treatment of visuospatial neglect. Additionally, individuals post-stroke, with or without neglect, exhibited more severe attentional deficits in allocentric processing for target identification in the contralesional visual field than in egocentric spatial processing. Furthermore, our findings revealed a disengagement deficit in individuals with neglect during visuospatial attention, reflected by poorer performance for unattended targets in the contralesional hemifield in both the aSC and eSC conditions. The absence of a validity effect indicated a deficit in reorienting spatial attention in individuals with or without neglect, while healthy participants demonstrated a significant validity effect, which may be related to the ratio of valid to invalid cues. Future studies investigating cueing-target tasks should consider varying cue validity ratios and SOA lengths to understand better how individuals with neglect perform in reorienting spatial attention.

aSC: Allocentric Spatial Coding; eSC: Egocentric Spatial Coding; HC: Healthy Controls; USN+: Individuals with Right-Hemispheric Stroke and Unilateral Spatial Neglect; USN-: Individuals with Right-Hemispheric Stroke without Unilateral Spatial Neglect; RT: Response Time; AR: Accuracy Rate; LVF: Left Visual Field; RVF: Right Visual Field; SOA: Stimulus-Onset Asynchrony; TDI: Target Detection Index; MMSE: Mini-Mental State Examination; ANOVA: Analysis of Variance.

Ethics approval and consent to participate

The studies involving human participants were reviewed and approved by the Ethics Committee of Xiamen Fifth Hospital (No.XMWY-K2022-036). The participants or proxies were provided their written informed consent to participate in this study, informed by written format about the ongoing analyses of data from their medical records, and were given the opportunity to oppose the use of their data.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

This research was funded by the Youth Innovation Project from the Ministry of Science and Technology of Fujian (to SJC; Grant No.: 2022D010), the Medical and Health Guidance Project of Xiamen (to SJC; Grant No.: 3502Z20199100), the Xiamen Key Project of Medical Treatment and Public Health (to XKH; No. 3502Z20234005) and Xiamen Natural Science Foundation (to XKH; No. 3502Z202373135) .

Authors' contributions

Authors’ contributions to the work: conception and design: SJC, JYH, XKH. Acquisition, interpretation of data: SJC, LL,GY, JHY,XL. Analysis of data: SJC,LL. Interpretation of data:SJC, LL,GY, JHY,XL. Drafting of the article: SJC, JYH, XKH. Revision for intellectual content: SJC,LL, JYH, XKH. All authors approved the final version. All authors agree to be accountable for all aspects of the work.

Acknowledgments

The authors wish to thank the entire staff of Xiamen Key Laboratory of Rehabilitation Technology Transformation of Encephalopathy for their commitment to improve participant care and early mobilization.

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No competing interests reported.

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Allocentric and Egocentric Spatial Attention Bias in Individuals with Right-Hemispheric Stroke and Unilateral Spatial Neglect: A Pilot Study

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Abstract

Background

Methods

Results

Conclusion

Figures

Introduction

Materials and Methods

Participants

Apparatus and Stimuli

Cueing-Target Paradigm and Procedures

Training Session

Statistical Analysis

Demographic Information

Visuospatial Attention Ability

Results

Basic Information

AR

RT

Lateralized Spatial Attention

Validity Effect

Disengagement Deficit

Discussion

Typical Attentional Rightward-Bias

Cue-Related Attentional Efficiency

Clinical and Functional Implications of" Subclinical" Lateralized Attention Deficits

Conclusions

Abbreviations

Declarations

References

Additional Declarations

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