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Spatial Neglect Midline Diagnostics From Virtual Reality and Eye Tracking in a Free-Viewing Environment

Spatial Neglect Midline Diagnostics From Virtual Reality and Eye Tracking in a Free-Viewing... ORIGINAL RESEARCH published: 29 November 2021 doi: 10.3389/fpsyg.2021.742445 Spatial Neglect Midline Diagnostics From Virtual Reality and Eye Tracking in a Free-Viewing Environment 1 1 2 3 Bastian I. Hougaard *, Hendrik Knoche , Jim Jensen and Lars Evald 1 2 Department of Architecture and Media Technology, Aalborg University, Aalborg, Denmark, Neurocenter Østerskoven, Hobro, Denmark, Hammel Neurorehabilitation Centre and University Research Clinic, Hammel, Denmark Purpose: Virtual reality (VR) and eye tracking may provide detailed insights into spatial cognition. We hypothesized that virtual reality and eye tracking may be used to assess sub-types of spatial neglect in stroke patients not readily available from conventional assessments. Method: Eighteen stroke patients with spatial neglect and 16 age and gender matched healthy subjects wearing VR headsets were asked to look around freely in a symmetric 3D museum scene with three pictures. Asymmetry of performance was analyzed to reveal group-level differences and possible neglect sub-types on an individual level. Results: Four out of six VR and eye tracking measures revealed significant Edited by: differences between patients and controls in this free-viewing task. Gaze-asymmetry Adriana Salatino, between-pictures (including fixation time and count) and head orientation were most Catholic University of Louvain, Belgium sensitive to spatial neglect behavior on a group level analysis. Gaze-asymmetry and Reviewed by: head orientation each identified 10 out of 18 (56%), compared to 12 out of 18 (67%) Tom Foulsham, for the best conventional test. Two neglect patients without deviant performance on University of Essex, United Kingdom conventional measures were captured by the VR and eyetracking measures. On the Anıl Ufuk Batmaz, Kadir Has University, Turkey individual level, five stroke patients revealed deviant gaze-asymmetry within-pictures and *Correspondence: six patients revealed deviant eye orientation in either direction that were not captured by Bastian I. Hougaard the group-level analysis. [email protected] Conclusion: This study is a first step in using VR in combination with eye tracking Specialty section: measures as individual differential neglect subtype diagnostics. This may pave the way This article was submitted to for more sensitive and elaborate sub-type diagnostics of spatial neglect that may respond Neuropsychology, a section of the journal differently to various treatment approaches. Frontiers in Psychology Keywords: hemispatial neglect, virtual reality immersion therapy, diagnostic techniques and procedures, unilateral Received: 16 July 2021 spatial neglect, eye tracking, head rotation, stroke, acquired brain injury Accepted: 19 October 2021 Published: 29 November 2021 Citation: 1. INTRODUCTION Hougaard BI, Knoche H, Jensen J and Evald L (2021) Spatial Neglect Globally, there is an annual incidence of about 16.9 million first-ever strokes and 33 million Midline Diagnostics From Virtual stroke survivors (Feigin et al., 2014). Stroke is a leading cause of cognitive impairments as Reality and Eye Tracking in a approximately one third of stroke survivors live with life-long disability (Singh et al., 2018). Free-Viewing Environment. Front. Psychol. 12:742445. Spatial neglect represents a common impairment following stroke affecting at least 30% of stroke doi: 10.3389/fpsyg.2021.742445 survivors (Hammerbeck et al., 2019). However, SN often goes under-diagnosed and consequently Frontiers in Psychology | www.frontiersin.org 1 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics under-treated (Bowen et al., 1999; Edwards et al., 2006; Chen position compared to those with no symptoms. But their study et al., 2013). Spatial neglect (SN) constitutes a heterogeneous did not include neglect patient without visual field defects and syndrome with several different, dissociable symptoms or all participants used chin rests removing the possibility of head subtypes (Buxbaum et al., 2004; Kerkhoff and Schenk, 2012; movements. Ptak et al. (2009) assessed neglect with free-viewing Rode et al., 2017). Conventional tests often simply assess one of photographs, but used a chin-rest and found a group-level aspect of these underlying deficits. No single conventional neglect ipsilesional shift in the fixation distribution for the patient group. test can reliably diagnose all patients, i.e., one patient may pass Results from eye tracking have been promising but not without the first four tests and fail the fifth, another may fail the first contradictions. For example, Primativo et al. (2015) found no and pass the rest. This often relates to different subtypes of differences in the number and durations of fixations between neglect e.g., motor and sensory neglect or ego- and allocentric SN and non-SN patients in a free viewing task of an albeit (body and object centered) neglect. Egocentric neglect manifests asymmetric picture. Studies use different measures derived from itself as inattention to stimuli presented in the contralesional gaze measurements to identify neglect, such as re-fixations, mean hemispace of different body midlines (trunk, head and eyes) amplitude and saccade landing position (Paladini et al., 2019) and allocentric neglect as inattention to the contralesional half and horizontal fixation frequency (Ptak et al., 2009). part of objects regardless of their egocentric placement. Many Contrary to setups in previous studies, this study provides of these subtypes differ in diagnostic measures and prognostic both head-mounted immersive VR and eye-tracking that allows consequences. Ego- and allocentric neglect seem to have different for unconstraint head and eye movement. We wanted to recovery rates (Demeyere and Gillebert, 2019) and different investigate to what extent SN can be assessed based on basic neglect midlines may require different treatment approaches, e.g., continuous measurements of head and eye movement while oculomotor neglect. patients are spontaneously and freely looking around in a simple Virtual Reality (VR) combined with eye tracking may be a immersive VR environment and whether these measures can useful technology to detect different aspects of SN in complex detect individual motor biases across different body midlines. 3D environments. The ability to control and monitor all motor We hypothesized that virtual reality and eye tracking may be and sensory input and output in high spatial resolution and used to assess sub-types of spatial neglect in stroke patients not temporal millisecond precision level may be ideal for assessing readily available from conventional assessments. Specifically, the subtle impairments in spatial attention. VR has for long been aim was to investigate whether differences in attentional biases a target for recording diagnostics of cognitive impairments across different frames of references (egocentric midlines of body, in cognitive neuroscience, although pen-and-paper tests still head, eyes, and allocentric midlines of objects) can be assessed by dominate clinical neuropsychology. Digital tests can provide VR and eye tracking on a group level (patients and controls) and novel measures to quantify neglect that are too cumbersome to individual level (subtypes diagnostics). compute from pen and paper tests in clinical contexts. A literature review by Negut et al. (2016) confirmed 2. METHODS virtual reality to be a sensitive neuropsychological assessment tool in detecting cognitive impairment for clinical practice. All participants were recruited at Hammel Neurorehabilitation They identified task performance indicators based on: Centre (HNC) and University Research Clinic. Patients with right 1) time measured, 2) number of errors in performing a task, hemisphere brain injury and behavioral symptoms of SN (with 3) quantitzation of head or body movement. Only one study used KF-NAP scores larger than zero) were included. KF-NAP was head movement, the rest used task-based parameters. A number used as a baseline measure to identify neglect patients, due to its of studies has explored VR measures to assess neglect, through high sensitivity to neglect symptoms direct relation to everyday task based measures, either for training cognitive functions or activities and changes in the severity of neglect symptoms during making assessments (Nolin et al., 2019). For example, Broeren recovery from stroke patients (Chen et al., 2015). Patients with et al. (2007) used cancellation tasks to derive the pattern of previous brain injury or neurodegenerative diseases as well as search and Yasuda et al. (2020) used object detection tasks to bedridden and blind patients were excluded. Healthy age and assess near- and far SN. To assess neglect, eye tracking can be gender matched controls were recruited from the staff at HNC. used in conjunction with head-mounted displays to scan eye movement patterns (Baheux et al., 2004, 2006). Kim et al. (2004) combined eye tracking with VR task to create a diagnostics tool 2.1. Conventional Measures for SN. Twelve patients and 40 controls were diagnosed based Conventional SN tests were applied for comparison to virtual on deviation angle (between mandated and actual gaze position), reality measurements. The Line bisection test from the no-attention time, scanning time, number of cues, failure rate Behavioral Inattention Test (Wilson et al., 1987) requires the of mission, and ratio of right/left scan. Their deviation angle patients to mark the center of each of three (8 inches 20.3 mm) correlated with line bisection test results. Other studies have horizontal lines that are printed on a sheet of white paper. In used eye tracking in non-VR environments to assess neglect, for the Apples Cancellation Test (Bickerton et al., 2011) patients example Cazzoli et al. (2016) who measured x-axis gaze position are instructed to cancel out targets depicting outlines of apples, while participants with neglect and visual field defect (VFD) but only complete apples without gaps, on a sheet of white paper. viewed a projected virtual traffic scene. The neglect patients with The test yields individual scores for both non-lateralized visual VFD showed a significant rightward deviation in x-axis gaze attention (accuracy), egocentric and allocentric neglect. The gray Frontiers in Psychology | www.frontiersin.org 2 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics FIGURE 1 | (Left) Experimental setup showing note taker, technician and the participant who wore a head-mounted display whilst sitting in a wheel chair. (Middle) Participants wore an HTC Vive with Pupil Labs eye tracking cameras mounted inside. (Right) The virtual museum contained the participant and three images to the ◦ ◦ ◦ left (−48 ), right (+48 ), and middle (0 ). scales gradient test requires patients to judge which of two left- and started an eye tracking calibration procedure (staring at right mirror-reversed gray scale gradients appears darker. For dots shown in the head-mounted display). After successful Pupil each of the 12 pairs of stimuli, one of the grayscales is shaded Labs 2D calibration, they were presented with a simple museum from white on the left to black on right, and the other is shaded environment (Figure 1, Right). The environment consisted of in the opposite direction. The task is highly sensitive to unilateral three sets of three pictures shown on three walls. Head movement hemispheric brain damage, and can uncover attentional biases in was needed to see the entirety of the left and right pictures. patients without SN symptoms on conventional cancellation or The picture sets were either three faces of well known persons, line bisection tests (Mattingley et al., 2004). The chimeric faces three similar seasonal colored landscapes, or three non-figurative test consists of 12 pairs of chimeric faces generated from portraits paintings. The picture sets were selected to reflect symmetry of 10 different people smiling and 10 portraits of the same of salience, were placed equally far from the middle and people with a neutral expression arranged vertically (Mattingley counterbalanced. The participants viewed each picture set for 60 et al., 1993; Sarri et al., 2006). Each pair contains two chimeras s, totalling 180 s of free viewing time. While participants looked of the same person, one neutral in the left half and smiling around, we logged the VR headset’s position and orientation and in the right half, and the other vice versa, with the vertical their gaze. We used an HTC Vive VR headset with Pupil Labs eye position counterbalanced. Patients are instructed to chose the tracking equipment, which tracks with 1 degree accuracy (Pupil happier of the two thus revealing left (20/0) or right (0/20) Labs, 2021). The virtual environment was developed in Unity, attentional biases. The KF-NAP was developed on the basis of the which recorded the sensor data from the VR headset and Catherine Bergego Scale (Azouvi, 1996)—the most widely used raw raycasted gaze data using Pupil Labs’ API without jitter behavioral assessment instrument for SN (Azouvi, 2017). KF- postprocessing. The visual angle of each picture subtended 32 in ◦ ◦ NAP is a manual method for systematic observation of SN during width and 40 in height. The pictures were spaced 16 apart. The everyday activities, including 10 categories: gaze orientation, HTC Vive provided 110 field of view, although this depended limb awareness, auditory attention, dressing, grooming, personal on the fit (Lynn et al., 2020). Data from VR and Eye trackers belongings, navigation, collisions, having a meal, and cleaning were recorded at a 30 Hz sampling rate and analyzed with the after meals (Chen et al., 2012, 2015). Each category is scored from saccades package in R. 0 to 3, with higher scores indicating more severe neglect. The sum score ranging from 0 to 30 indicates the severity of SN with 2.3. Virtual Reality and Eye Tracking predefined cut-off scores of the severity (0 = none, 1–10 = mild, Measure Description, Preparation, and 11–20 moderate, 21–30 severe). KF-NAP has been shown to be Analysis very sensitive to neglect symptoms directly related to everyday After their calculation, all measures were normalized to range activities and to changes in the severity of neglect symptoms as from −1 (leftward) to 1 (rightward). For all measures except stroke patients are recovering (Chen et al., 2015). the fixations, we subtracted the percentage of time spent on the left side from the percentage of time spent on the right 2.2. Virtual Reality and Eye Tracking side (see Table 1). For these measures we defined impairments Procedure and Apparatus through cut-off criteria based on the difference between the Participants were instructed about wearing a virtual reality percentages of time spent in the left and the right hemispace headset and the free viewing task: “In a moment you will be in the control group (e.g., including the 5th percentile or none placed in a museum. You get a few minutes to look around. of the controls). These support clinical diagnostics e.g., whether You do not have to describe what you see.” We then equipped patients had allo-, egocentric neglect, or neglect related to head the participants with the virtual reality headset (Figure 1, Left) or eye midline deviations. Frontiers in Psychology | www.frontiersin.org 3 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics TABLE 1 | Virtual reality and eye tracking measurements. VR measure Description Interpretation Gaze asymmetry Estimated gaze from eye and head Egocentric-neglect (body between-pictures while comparing looking at the left midline) and right picture. Gaze asymmetry Difference in time spent on estimated Allocentric neglect within-picture gaze from eye and head combined (object midline) while looking at the pictures. Head orientation left/right Amount of time spent with the head Caputomotor neglect rotated to the left/right. (head midline) Eye orientation left/right Hemispheric orientation of the eyes Oculomotor neglect (eye only, without considering fixations or midline) gaze in scene. Fixation duration left/right Duration of eye fixations within the Egocentric neglect (body scene. Analyzed from saccades midline) (λ=1). Fixation count left/right Number of eye fixations made Egocentric neglect (body left/right within the scene. midline) TABLE 2 | Patient demographics and brain injury characteristics. ID Sex Hand Age Days since injury Lesion 2 M R 56 173 Traumatic subarachnoid hemorrhage and right subdural hematoma 4 F R 66 37 Hemorrhage right basal ganglia 7 M R 58 62 Subarachnoid hemorrhage 8 M R 56 55 Infarction right occipital lobe 16 M R 63 15 Infarction right internal carotid artery and middle cerebral artery 17 F R 61 74 Large hemorrhage right hemisphere 21 F L 54 52 Hemorrhage right hemisphere frontal 24 F R 68 25 Infarction right hemisphere frontal 26 M R 56 30 Infarction right middle cerebral artery 28 F R 69 31 Hemorrhage right thalamus 32 F R 74 497 Infarction right hemisphere 33 F R 58 100 Large hemorrhage right basal ganglia 34 F R 73 23 Infarction right middle cerebral artery 35 F R 63 100 Large infarction right frontal and parietal lobe 36 F R 58 54 Infarction right basal ganglia and parietal lobe, thrombus right internal carotid artery and middle cerebral artery 37 M R 51 154 Infarction right middle cerebral artery 38 M R 57 61 Infarction right middle cerebral artery 39 M R 64 17 Hemorrhage right middle and frontal Eye tracking data was filtered to include only data points Head- and eye orientation were measured irrespective of gaze from looking at the three pictures. Gaze asymmetry measured in virtual reality in order to assess motor neglect related to the position of the participants’ gaze projected onto these different body midlines. We did not correct for head position pictures. Between picture gaze asymmetry left out eye tracking when using head orientation as the patients were seated in wheel data from the middle picture and subtracted the amount chairs and potentially not sitting fully upright. Head Orientation of time spent looking at the left-most picture from the L/R subtracted the percentage of time (in seconds) participants time looking at the right-most picture. These temporal spent with the head rotated to the right from the percentage aggregates were solely based on the number of eye tracking of time spent on the left. For example, if a participant’s head samples located on each respective picture. Their fixation was oriented to the right side twice as long (66%) as to the left counts and the totalled duration of the fixations were side (33%), this measure reported an imbalance of −33%. Eye separate measures. Within-picture gaze asymmetry divided each Orientation L/R was based on how much time the person was picture into a left and right section and compared the looking to the left of their visual field center line (where the participants’ time spent gazing on each side, to measure nose is pointing) in comparison to looking right of it aggregated allocentric neglect. over all three pictures independent of head rotation. Fixation Frontiers in Psychology | www.frontiersin.org 4 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics durations and counts are common aggregate measures of gaze 3.2. Individual Results data but can behave differently. One could spend equal amounts Tables 5, 6 provides an overview of how well the conventional of gaze time left and right, yet still have fewer fixations and longer and virtual reality tests identified individual attentional biases durations of fixations to one side. Subtracting the percentage in the patient and control groups. Figure 3 show individual of fixations that happened on the left from those on the right gaze distributions. providing the measures fixation count L/R. The measure fixation 3.3. Gaze Asymmetry duration L/R relied on the difference of the sums of fixation Ten patients (2, 7, 8, 17, 24, 26, 33, 34, 35, 37) and one durations from the left and the right divided by the sum of all control (6) had abnormal right-ward bias related to the viewing fixation durations. time of the left and right most pictures, whereas two patients (28, 36) and one control (12) had small left-ward biases 2.4. Statistical Approach contrary to expectations (Figure 4). Right-ward biases could The conventional tests produced continuous raw scores for the be interpreted as SN behaviors centered at the body midline Apples Cancellation and the Line bisection tests, and asymmetry (egocentric neglect). scores for the gray scale gradients and the Chimeric faces. They Two patients (28, 33) and none of the controls had right-ward were analyzed according to their normative cut-off scores from bias related to the viewing time within the left and right half part the literature and binary neglect diagnostics were calculated. For of the pictures, whereas three patients (26, 34, 37) and one control the VR and eye tracking measures we relied on the data from (18) had left-ward bias (see Figure 5). Even though patients more the control group. For each measure we derived cut-offs (cu) commonly had deviant within-picture bias than controls, the by adding the mean m of the control group to 1.645 times its biases were both right-ward and left-ward and two patients (37, standard deviation sd (95th percentile): cu = m ± 1.645 ∗ c c 26) had fairly large left-ward biases contrary to expectation. This sd . Mann-Whitney tests checked for between group differences measure could be interpreted as SN behaviors related to the object unless indicated otherwise. An alpha value <5% (p < 0.05) was midline (allocentric neglect), even though the behavior of some considered statistically significant. Two-sided testing with a 5% patients was contrary to expectation. alpha value (α = 0.05) and 80% power (1 − β = 0.80) along with enrolling 18 patients and 16 healthy controls allowed us to detect 3.4. Head- and Eye-Orientation large effect sizes (Cohen’s d > 1.0). In terms of head orientation, 11 of the patients (2, 7, 8, 17, 24, 26, 33, 34, 35, 36, 37) and none of the controls showed an abnormal 2.5. Participant Characteristics right-ward bias, whereas one patient (28) and one control (12) Twenty three stroke patients and 16 age and gender matched had a small abnormal left-ward bias (see Figure 6). Right-ward controls from a hospital staff population were recruited. bias of head orientation can be interpreted as motor neglect or However, five patients were excluded for different reasons: one lack of intention to initiate head movements toward the left. had a premorbid surgical fixation of the neck, that prevented Four patients (8, 33, 37, 39) and two controls (3, 18) had natural movement of the head; one was easily fatigued and the VR an abnormal right-ward eye position bias, i.e., the eyes spend procedure was aborted; one got emotional labile during testing more time looking to the right than the left regardless of head with the conventional test and VR testing was not performed; one movement whereas two patients (26, 32) and none of the controls patient could not be satisfyingly calibrated for the eye tracking; had left-ward eye movement biases (see Figure 7). Right-ward and one patient had left-sided brain damage and right-sided eye movement bias could be interpreted as oculomotor neglect neglect. Participants were matched to have equal age and gender or a lack of intention to move ones eyes to the left. in the patient (range 51–74, M = 61.4, SD = 6.6, 9F/9M) and control group (range 52–69, M = 60.0, SD = 4.8, 8F/8M), with 3.5. Fixation-Duration and Fixation-Count no significant difference for age according to a t-test (p = 0.491). Seven patients (7, 8, 17, 33, 34, 35, 37) and one control (3) had The patient demographic characteristics are presented in Table 2. abnormal right-ward fixation time bias, i.e., they spent more time Written informed consent was obtained from the participants. on each fixation in the right VR hemispace compared to the left, whereas no patients and no controls exhibited left-ward biases (see Figure 8). 3. RESULTS Likewise, eight patients (7, 8, 17, 24, 33, 34, 35, and 37) and none of the controls had abnormal right-ward fixation counts, 3.1. Group-Level Results interpreted from the number of saccades, whereas no patients Table 3 describes the means and p-values from Mann-Whitney and no controls had left-ward bias (see Figure 9). tests on both conventional and VR measures used in the study. All conventional measures were significantly different (p < 0.05) between the patient and control groups. Most 4. DISCUSSION virtual reality measures differed significantly, too, except gaze This study aimed at investigating whether attentional biases asymmetry within picture and eye orientation left/right. The across different egocentric midlines of body, head, eyes, and correlations between virtual reality measures are described in allocentric midlines of objects could be assessed by VR and eye Table 4. Figure 2 depicts the density plots of the three pictures tracking on a group and individual level in patients with SN. split by patient and control groups. Frontiers in Psychology | www.frontiersin.org 5 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics TABLE 3 | Group-level reports for patient and control groups (conventional and VR tests). Patients (18) Controls (16) Measurement N/Mean SD N/Mean SD Cut-off scores p-value KF-NAP 13.6 5.8 – – – – Line bisection 6.3 3.1 8.9 0.3 ≤ 7 0.001 AC accuracy 32.0 14.0 48.5 2.0 ≤ 41 0.000 AC asymmetry egocentric 7.4 6.6 0.1 1.5 ≥ ±3 0.001 AC asymmetry allocentric 3.1 4.9 0.0 0.0 ≥ ±2 0.006 Gray scales (average left/right) 4/16 – 9/11 – ≥ 1/19 0.002 Chimeric faces (average left/right 7/13 – 12/8 – ≥ 1/19 0.020 Gaze asym. between-pict. 0.22 0.25 0.01 0.05 −0.07 / 0.09 0.003 Gaze asym. within-pict. 0.09 0.41 0.14 0.26 −0.28 / 0.57 0.665 Head Orientation L/R 0.21 0.23 0.01 0.05 −0.07 / 0.10 0.002 Eye orientation L/R 0.15 0.29 0.08 0.20 −0.25 / 0.40 0.391 Fixation duration L/R 0.30 0.33 0.08 0.22 −0.29 / 0.44 0.028 Fixation count L/R 0.30 0.30 0.08 0.18 −0.21 / 0.37 0.012 Cut-off scores for conventional test based on normative data. Fifth and 95th percentiles for VR and ET measures are based on control group performances. * indicates significance (p < 0.05). TABLE 4 | Correlations between VR measures, calculated using a pearson correlation coefficient. Gaze asymmetry Head orientation, Eyes, duration Eye Fixations, Eye fixations, within pictures duration L/R L/R duration L/R count L/R Gaze asymmetry between pictures –0.39 1.00 0.11 0.68 0.77 Gaze asymmetry within pictures – –0.35 0.50 0.22 0.20 Head orientation, duration L/R – 0.11 0.69 0.78 Eyes, duration L/R – 0.49 0.49 Eye fixations, duration L/R – 0.92 Eye fixations, count L/R – On a group level, gaze asymmetry between-pictures measures, but were picked up by different conventional (egocentric neglect) was highly sensitive but gaze asymmetry tests. This underlines the heterogeneity of spatial neglect within-pictures (allocentric neglect) was not. Likewise, head and provides evidence for the complementarity of a VR and orientation (caputomotor neglect) was highly sensitive, though eye-tracking based free viewing task for neglect diagnostics. eye orientation (oculomotor neglect) was not. Finally, fixation We observed a small rightward gaze bias in the control time and fixation count were both highly sensitive to right-ward group’s means during 180 s of viewing time, contrary to the neglect behavior. leftward bias commonly found in the first 1.5 s by Foulsham On an individual level, even though gaze asymmetry within- et al. (2018). Our measures did not consider the initial pictures (allocentric neglect) was not a significant measure of gaze behavior. neglect behavior on a group level, five patients as opposed The free-viewing task in our study resembled findings in to one control did in fact revealed deviant behavior in group-level midline deviations from previous task-based studies, either direction. Likewise did six patients as opposed to such as the left/right ratio measured by Kim et al. (2004, 2010) two controls revealed deviant eye orientation behavior in and the head orientation deviation found by Ogourtsova et al. either direction. (2018). The very high correlation between head orientation Overall, gaze-asymmetry between-pictures and head and gaze asymmetry between pictures matches findings from orientation each identified 10 out of 18 (56%) of the stroke Sidenmark and Gellersen (2019), which showed that focusing on patients, compared to 12 out of 18 (67%) for the best of the a target further than 15 away typically involves head orientation. conventional tests. Interestingly, three patients (34, 38, and We found a median undershooting to the right of the leftmost 39) were not picked up by any of the conventional neglect painting in patients (see Figure 2), similar to what Ogourtsova test at all, apart from their low to moderate KF-NAP scores et al. (2018) observed when their participants approached a left- used as the inclusion criteria. However, two of these exhibited side (−15 ) target in a locomotive task. Since allocentric neglect deviant rightward bias in one or more of the six VR and normally is observed across both sides, we decided not to sub- eye tracking measures. Conversely, four patients (4, 16, 21, analyse the within-picture asymmetry on the left side further. 38) were not picked up by any of the VR and eye tracking Our group based results on fixations mirrored non-VR based Frontiers in Psychology | www.frontiersin.org 6 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics FIGURE 2 | Group level spatial distribution of gaze samples on the (solid line) and median gaze (dotted line) of patients and controls. The x-axis spans the horizontal world space of the virtual museum scene from −2.0 to 2.0. The y-axis plots the corresponding gaze sample counts in thousands (k). TABLE 5 | Patient group demographics and results from conventional and VR measures. ID (18 Patients) 2 4 7 8 16 17 21 24 26 28 32 33 34 35 36 37 38 39 KF-NAP sum score 6 16 18 15 18 16 4 20 16 9 16 16 13 15 4 26 8 9 - gaze orientation 1 1 2 2 2 2 1 2 2 1 2 1 1 2 0 3 1 0 - limb awareness 1 2 2 1 3 2 1 2 2 2 2 2 2 1 1 3 1 2 - auditory attention 0 1 1 2 2 1 0 2 1 0 1 1 1 1 0 2 0 0 - personal belongings 1 2 2 2 2 2 0 2 2 1 2 2 1 2 1 3 1 0 - dressing 0 1 2 1 2 2 0 2 2 0 2 2 2 2 1 3 2 2 - grooming 1 1 2 1 1 1 1 2 2 1 1 2 2 2 0 2 1 2 - navigation 1 2 2 2 - 2 0 3 2 2 - 2 2 1 0 3 2 - - collisions 1 2 3 2 1 2 0 2 2 2 1 2 2 1 1 3 0 - - meals 0 2 1 1 1 1 0 1 1 0 2 1 0 1 0 2 0 0 - cleaning after meals 0 2 1 1 2 1 1 2 0 0 1 1 0 2 0 2 0 - Line bisection 6 9 9 0 5 0 4 6 4 9 3 9 9 8 8 7 9 9 AC accuracy 13 35 36 10 38 20 47 18 7 48 18 37 42 42 48 29 41 47 AC asymmetry egoc. 13 15 14 10 11 14 3 4 7 2 14 13 –3 –3 0 16 2 1 AC asymmetry alloc. 0 1 16 0 3 3 0 2 3 0 9 0 –1 8 0 12 0 0 Gray scales left/right 18/2 2/18 0/20 0/20 0/20 20/0 0/20 0/20 0/20 0/20 0/20 0/20 11/9 0/20 0/20 1/19 4/16 12/8 Chimeric faces L/R 11/9 7/13 0/20 3/17 4/16 20/0 1/19 10/10 8/12 9/11 10/10 0/20 16/4 4/16 0/19 14/6 6/14 11/9 Gaze Asym. Between-Pict. 0.14 0.04 0.35 0.35 0.05 0.52 0.04 0.23 0.44 –0.19 0.08 0.27 0.43 0.42 –0.08 0.79 –0.01 0.03 Gaze Asym. Within-Pict. –0.09 0.16 0.45 0.37 0.20 0.20 0.08 –0.08 –0.61 0.61 –0.18 0.61 –0.28 0.47 0.37 –0.84 –0.25 0.47 Head Orientation L/R 0.14 0.05 0.36 0.35 0.05 0.52 0.03 0.23 0.43 –0.17 0.09 0.30 0.43 0.39 –0.07 0.67 –0.01 0.04 Eye Orientation L/R 0.06 0.09 0.29 0.43 0.28 –0.06 0.21 0.21 –0.28 0.40 –0.36 0.62 –0.21 0.09 0.10 0.48 –0.23 0.57 Fixations, time L/R –0.07 –0.10 0.63 0.58 0.25 0.48 0.20 0.11 0.20 –0.07 –0.09 0.59 0.62 0.95 0.14 0.70 –0.17 0.42 Fixations, Count L/R 0.06 0.02 0.51 0.52 0.22 0.67 0.13 0.41 0.12 –0.09 –0.04 0.54 0.51 0.86 0.17 0.67 –0.19 0.33 Underlined numbers are significantly different (beyond the normative threshold from the controls). Blue shading denotes bias to the right. Red shading denotes bias to the left. Frontiers in Psychology | www.frontiersin.org 7 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics FIGURE 3 | Individual spatial distributions of gaze samples on the three pictures with true picture midline (solid lines) and median gaze (dotted lines) of patients and controls. The x-axis reports the horizontal axis of the virtual museum scene. The y-axis counts the number of gaze samples in thousands (k). Frontiers in Psychology | www.frontiersin.org 8 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics TABLE 6 | Control group demographics and results from conventional and VR measures. ID (16 Controls) 1 3 5 6 9 10 11 12 13 14 15 18 20 22 23 25 Line bisection 8 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 AC accuracy 50 45 48 50 50 49 47 50 50 43 50 50 49 48 48 49 AC asymmetry egoc. 0 3 0 0 0 0 3 0 0 -2 0 0 1 -2 -2 1 AC asymmetry alloc. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Gray scales L/R 8/12 16/4 12/8 17/3 6/14 16/4 6/14 5/15 8/12 7/13 19/1 1/19 5/15 12/8 5/15 5/15 Chimeric faces L/R 10/10 13/7 11/9 15/5 17/3 11/9 5/15 17/3 6/14 10/10 18/2 18/2 14/6 11/9 10/10 2/18 Gaze Asym. Between-Pict. –0.01 0.00 0.04 0.10 0.06 0.04 0.06 –0.11 –0.05 0.00 0.01 0.01 –0.05 0.03 0.01 0.05 Gaze Asym. Within-Pict. –0.19 0.53 –0.07 0.14 0.22 –0.10 0.11 0.14 0.41 –0.02 0.19 0.66 0.14 –0.06 –0.23 0.42 Head Orientation L/R –0.02 0.01 0.05 0.09 0.07 0.05 0.08 –0.11 –0.04 0.00 0.02 –0.01 –0.05 0.02 0.00 0.06 Eye Orientation L/R –0.21 0.43 0.14 0.14 0.16 0.01 0.25 –0.09 –0.19 –0.11 –0.01 0.45 –0.07 0.01 0.07 0.24 Fixations, Time L/R 0.00 0.46 –0.06 0.05 0.12 0.14 0.27 0.16 0.08 –0.26 –0.22 0.36 –0.25 0.01 –0.02 0.39 Fixations, Count L/R –0.07 0.33 –0.03 0.12 0.23 0.02 0.35 –0.10 0.01 –0.03 0.03 0.32 –0.15 –0.05 –0.05 0.35 Numbers underlined are above the 95th or below the 5th percentile (false positives). Blue shading denotes bias to the right. Red shading denotes bias to the left. studies that found fewer fixations for SN patients on the left While neglect patients might perform worse than controls side both in free viewing (Fellrath and Ptak, 2015; Ohmatsu during eye tracking calibration given the spatial arrangement et al., 2019) and visual search tasks (Cazzoli et al., 2011). of focal points across the visual field all patients included in Similarly our gaze asymmetry results and fixations matched the our study successfully passed calibration. However, our results rightward median gaze in SN patients in both free viewing indicated opportunities for detailed measurement of behavior and visual search tasks (Machner et al., 2012, 2018). But in over time, rather than "single-instance" tests with potentially contrast to the study by Primativo et al. (2015) ours did find less cognitive strain and we saw opportunities for sub-diagnosis significant group level differences for fixation durations and on neglect symptoms. Some of the VR and eye tracking counts. measures incorrectly picked up four controls (3, 6, 12, 18). The current free-viewing VR task was not sensitive enough In total 5/96 (5.2%) observations were right-ward bias false to detect neglect in all patients but there are other behavioral positives and 2/96 (2.1%) were left-ward bias false positive, measures that can be derived from the data collected in our which fairly closely resembles the expected false positive rates setup. For example, Sidenmark and Gellersen (2019) showed from a cut-off criteria set at the 5th percentile. False positives that people use different combinations of torso, head, and could be reduced by setting a stricter cut-off criteria e.g., eye rotations to acquire targets, which might differ for SN at the first percentile. Conventional neglect tests are often patients. Scan paths from eye tracking provide another such confounded by ceiling effects that yield high specificity (true avenue that could leverage the spatio-temporal data from positive rates), while they suffer from low sensitivity (true viewing each picture (e.g., re-fixations, mean amplitude, saccade negative rates) leading to patients passing these tests while landing position, Paladini et al., 2019), and initial fixation still experiencing neglect related problems in more complex location (Foulsham et al., 2018). Our free viewing created everyday activities. In this study, we wanted to compare the no best outcomes but could still be analyzed according to sensitivity of VR and eye tracking measures to conventional measures similar to Dalmaijer et al. (2015) quality of search measure for patients with clinically evident SN measured by or best R. the KF-NAP. However, including a group of stroke patients Our approach poses some limitations to the results. The without SN may have revealed subtle gaze biases caused by inter- simple museum environment and the free-viewing task created hemispheric imbalance in this group, too. This may very well low attentional demands. This may have allowed patients to try be due to the lack of specificity (false negatives) of conventional spending equal amounts of time on each picture if they expected neglect test, thus VR and eye tracking may in fact increase being tested. Tracking of the headset and eye movements may specificity of SN assessment. This should be investigated in have addressed motor neglect specifically but missing sensory future studies. neglect subtypes. The eye tracking data was constrained by a Neglect symptoms may be provoked by multitasking, 30 Hz sampling rate and a fairly narrow field of view offered simultaneous stimuli, mental fatigue, stress, or emotional by the current generation head-mounted displays that provided states (Blini et al., 2016). These are intentionally avoided eye tracking.Our results are limited by the accuracy of the gaze in conventional assessments usually administered in a well- tracker both by spatial accuracy and the temporal resolution of controlled examination room, but could be purposefully the eye tracking data including the inherent jitter. To account exploited in a controlled VR environment. In addition to for these limitations our measures did not require high spatial ceiling effects, many conventional neglect tests lack ecological accuracy, except for the within-picture measure, which may validity, i.e., providing no direct link between the task tested account for why no significant group difference was found. (e.g., cancellation or line bisection tests) and activities of daily Frontiers in Psychology | www.frontiersin.org 9 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics FIGURE 4 | Gaze Asymmetry Between-pictures. (Left) Individual normalized time difference between looking at left/right picture in patient (black, top) and control (gray, bottom) with normative threshold cut-offs (red lines). (Right) Patient (black, top) and control (gray, bottom) histograms of horizontal gaze sample positions limited to the left and right painting with the true (solid) midline and the (dotted) group median of horizontal gaze positions. FIGURE 5 | Gaze Asymmetry Within-picture. (Left) Individual time spent looking right and left within all pictures in patient (black, top) and control (gray, bottom) with the empirical cut-offs (red lines). (Right) Spatial distribution of gaze samples within all pictures with true (solid) midline and group median (dotted). FIGURE 6 | Head orientation left/right. (Left) Individual time spent rotating head left and right in patient (black, top) and control (gray, bottom) with normative threshold cut-offs (red lines). (Right) Spatial distribution of patient and control head orientation with true (solid) midline and group median (dotted). Frontiers in Psychology | www.frontiersin.org 10 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics FIGURE 7 | Eye orientation left/right. (Left) Individual time spent rotating eye balls left and right in patient (black, top) and control (gray, bottom) with normative threshold cut-offs (red lines). (Right) Spatial distribution of patient and control eye ball orientation with true (solid) midline and group median (dotted). FIGURE 8 | Fixation left/right. (Left) Individual time spent fixating eyes in the left and right for patient (black, top) and control (gray, bottom) with normative threshold cut-offs (red lines). For example, –1 indicates that participants spent 100% of the time fixating on the left. (Right) Time-weighted spatial distribution of patient and control fixations, according to world midline, with time-weighted medians (dotted). FIGURE 9 | Fixation count left/right. (Left) Individual fixation count right/left for patient (black, top) and control (gray, bottom) with normative threshold cut-offs (red lines). (Right) Spatial distribution of patient and control fixation counts, according to the world (solid) midline with (dotted) median. Frontiers in Psychology | www.frontiersin.org 11 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics living. This may also be improved in VR and eye tracking AUTHOR CONTRIBUTIONS based assessment. HK, JJ, and LE conceptualized the study and designed the This study underlined the heterogeneity of symptoms methodology. Analysis of conventional measurements was done of SN and represents a first step in using virtual reality by LE and HK. BH and HK were responsible for data verification, in combination with eye tracking measures for individual cleanup and analysis of VR and eye tracking measures, and differential subtype diagnostics from a free viewing visualization of all data. BH created all graphical material and context. Virtual reality and eye tracking hold a potential wrote the background with supervision from HK. LE collected for individual subtype diagnostics that could inform and interpreted all clinical measurements. BH, LE, and HK clinical treatment choices and hence treatment efficacy. jointly wrote the discussion. All authors contributed to the article Improving sensitivity, specificity and ecological validity by and approved the submitted version. use of VR and eye-tracking measures may provide more accurate diagnostics and prognostics for patients with spatial neglect. ACKNOWLEDGMENTS The authors are indebted to the help of Bianca Clavio Christensen DATA AVAILABILITY STATEMENT (development and testing of VR and eye tracking), Jonas Lindeløv (initial data cleaning and analysis), Kristian Westergaard The raw data supporting the conclusions of this article will be Jensen (data collection), Rasmus Hougaard Pedersen (data made available by the authors, without undue reservation. collection), Alexander Kaiser (data collection), Kiefer Coze (VR implementation), and Théo Toupin (VR implementation). ETHICS STATEMENT The studies involving human participants were reviewed SUPPLEMENTARY MATERIAL and approved by the Scientific Ethics Committees for the Central Denmark Region. 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Conflict of Interest: The authors declare that the research was conducted in the doi: 10.1016/j.neuropsychologia.2003.07.007 absence of any commercial or financial relationships that could be construed as a Mattingley, J. B., Bradshaw, J. L., Phillips, J. G., and Bradshaw, J. A. (1993). potential conflict of interest. Reversed perceptual asymmetry for faces in left unilateral neglect. Brain Cogn. 23, 145–165. doi: 10.1006/brcg.1993.1052 Publisher’s Note: All claims expressed in this article are solely those of the authors Negut, A., Matu, S.-A., Sava, F. A., and David, D. (2016). Virtual reality measures and do not necessarily represent those of their affiliated organizations, or those of in neuropsychological assessment: a meta-analytic review. Clin. Neuropsychol. the publisher, the editors and the reviewers. Any product that may be evaluated in 30, 165–184. doi: 10.1080/13854046.2016.1144793 this article, or claim that may be made by its manufacturer, is not guaranteed or Nolin, P., Besnard, J., Allain, P., and Banville, F. (2019). “Assessment and endorsed by the publisher. rehabilitation using virtual reality after stroke: a literature review,” in Virtual Reality Technologies for Health and Clinical Applications, Chapter 15, Vol. 2, eds A. S. Rizzo and S. Bouchard (New York, NY: Springer), 307–326. Copyright © 2021 Hougaard, Knoche, Jensen and Evald. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC Ogourtsova, T., Archambault, P. S., and Lamontagne, A. (2018). Post-stroke visual neglect affects goal-directed locomotion in different perceptuo-cognitive BY). The use, distribution or reproduction in other forums is permitted, provided conditions and on a wide visual spectrum. Restor. 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Spatial Neglect Midline Diagnostics From Virtual Reality and Eye Tracking in a Free-Viewing Environment

Hougaard, Bastian I.; Knoche, Hendrik; Jensen, Jim; Evald, Lars
Frontiers in Psychology – Nov 29, 2021
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ORIGINAL RESEARCH published: 29 November 2021 doi: 10.3389/fpsyg.2021.742445 Spatial Neglect Midline Diagnostics From Virtual Reality and Eye Tracking in a Free-Viewing Environment 1 1 2 3 Bastian I. Hougaard *, Hendrik Knoche , Jim Jensen and Lars Evald 1 2 Department of Architecture and Media Technology, Aalborg University, Aalborg, Denmark, Neurocenter Østerskoven, Hobro, Denmark, Hammel Neurorehabilitation Centre and University Research Clinic, Hammel, Denmark Purpose: Virtual reality (VR) and eye tracking may provide detailed insights into spatial cognition. We hypothesized that virtual reality and eye tracking may be used to assess sub-types of spatial neglect in stroke patients not readily available from conventional assessments. Method: Eighteen stroke patients with spatial neglect and 16 age and gender matched healthy subjects wearing VR headsets were asked to look around freely in a symmetric 3D museum scene with three pictures. Asymmetry of performance was analyzed to reveal group-level differences and possible neglect sub-types on an individual level. Results: Four out of six VR and eye tracking measures revealed significant Edited by: differences between patients and controls in this free-viewing task. Gaze-asymmetry Adriana Salatino, between-pictures (including fixation time and count) and head orientation were most Catholic University of Louvain, Belgium sensitive to spatial neglect behavior on a group level analysis. Gaze-asymmetry and Reviewed by: head orientation each identified 10 out of 18 (56%), compared to 12 out of 18 (67%) Tom Foulsham, for the best conventional test. Two neglect patients without deviant performance on University of Essex, United Kingdom conventional measures were captured by the VR and eyetracking measures. On the Anıl Ufuk Batmaz, Kadir Has University, Turkey individual level, five stroke patients revealed deviant gaze-asymmetry within-pictures and *Correspondence: six patients revealed deviant eye orientation in either direction that were not captured by Bastian I. Hougaard the group-level analysis. [email protected] Conclusion: This study is a first step in using VR in combination with eye tracking Specialty section: measures as individual differential neglect subtype diagnostics. This may pave the way This article was submitted to for more sensitive and elaborate sub-type diagnostics of spatial neglect that may respond Neuropsychology, a section of the journal differently to various treatment approaches. Frontiers in Psychology Keywords: hemispatial neglect, virtual reality immersion therapy, diagnostic techniques and procedures, unilateral Received: 16 July 2021 spatial neglect, eye tracking, head rotation, stroke, acquired brain injury Accepted: 19 October 2021 Published: 29 November 2021 Citation: 1. INTRODUCTION Hougaard BI, Knoche H, Jensen J and Evald L (2021) Spatial Neglect Globally, there is an annual incidence of about 16.9 million first-ever strokes and 33 million Midline Diagnostics From Virtual stroke survivors (Feigin et al., 2014). Stroke is a leading cause of cognitive impairments as Reality and Eye Tracking in a approximately one third of stroke survivors live with life-long disability (Singh et al., 2018). Free-Viewing Environment. Front. Psychol. 12:742445. Spatial neglect represents a common impairment following stroke affecting at least 30% of stroke doi: 10.3389/fpsyg.2021.742445 survivors (Hammerbeck et al., 2019). However, SN often goes under-diagnosed and consequently Frontiers in Psychology | www.frontiersin.org 1 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics under-treated (Bowen et al., 1999; Edwards et al., 2006; Chen position compared to those with no symptoms. But their study et al., 2013). Spatial neglect (SN) constitutes a heterogeneous did not include neglect patient without visual field defects and syndrome with several different, dissociable symptoms or all participants used chin rests removing the possibility of head subtypes (Buxbaum et al., 2004; Kerkhoff and Schenk, 2012; movements. Ptak et al. (2009) assessed neglect with free-viewing Rode et al., 2017). Conventional tests often simply assess one of photographs, but used a chin-rest and found a group-level aspect of these underlying deficits. No single conventional neglect ipsilesional shift in the fixation distribution for the patient group. test can reliably diagnose all patients, i.e., one patient may pass Results from eye tracking have been promising but not without the first four tests and fail the fifth, another may fail the first contradictions. For example, Primativo et al. (2015) found no and pass the rest. This often relates to different subtypes of differences in the number and durations of fixations between neglect e.g., motor and sensory neglect or ego- and allocentric SN and non-SN patients in a free viewing task of an albeit (body and object centered) neglect. Egocentric neglect manifests asymmetric picture. Studies use different measures derived from itself as inattention to stimuli presented in the contralesional gaze measurements to identify neglect, such as re-fixations, mean hemispace of different body midlines (trunk, head and eyes) amplitude and saccade landing position (Paladini et al., 2019) and allocentric neglect as inattention to the contralesional half and horizontal fixation frequency (Ptak et al., 2009). part of objects regardless of their egocentric placement. Many Contrary to setups in previous studies, this study provides of these subtypes differ in diagnostic measures and prognostic both head-mounted immersive VR and eye-tracking that allows consequences. Ego- and allocentric neglect seem to have different for unconstraint head and eye movement. We wanted to recovery rates (Demeyere and Gillebert, 2019) and different investigate to what extent SN can be assessed based on basic neglect midlines may require different treatment approaches, e.g., continuous measurements of head and eye movement while oculomotor neglect. patients are spontaneously and freely looking around in a simple Virtual Reality (VR) combined with eye tracking may be a immersive VR environment and whether these measures can useful technology to detect different aspects of SN in complex detect individual motor biases across different body midlines. 3D environments. The ability to control and monitor all motor We hypothesized that virtual reality and eye tracking may be and sensory input and output in high spatial resolution and used to assess sub-types of spatial neglect in stroke patients not temporal millisecond precision level may be ideal for assessing readily available from conventional assessments. Specifically, the subtle impairments in spatial attention. VR has for long been aim was to investigate whether differences in attentional biases a target for recording diagnostics of cognitive impairments across different frames of references (egocentric midlines of body, in cognitive neuroscience, although pen-and-paper tests still head, eyes, and allocentric midlines of objects) can be assessed by dominate clinical neuropsychology. Digital tests can provide VR and eye tracking on a group level (patients and controls) and novel measures to quantify neglect that are too cumbersome to individual level (subtypes diagnostics). compute from pen and paper tests in clinical contexts. A literature review by Negut et al. (2016) confirmed 2. METHODS virtual reality to be a sensitive neuropsychological assessment tool in detecting cognitive impairment for clinical practice. All participants were recruited at Hammel Neurorehabilitation They identified task performance indicators based on: Centre (HNC) and University Research Clinic. Patients with right 1) time measured, 2) number of errors in performing a task, hemisphere brain injury and behavioral symptoms of SN (with 3) quantitzation of head or body movement. Only one study used KF-NAP scores larger than zero) were included. KF-NAP was head movement, the rest used task-based parameters. A number used as a baseline measure to identify neglect patients, due to its of studies has explored VR measures to assess neglect, through high sensitivity to neglect symptoms direct relation to everyday task based measures, either for training cognitive functions or activities and changes in the severity of neglect symptoms during making assessments (Nolin et al., 2019). For example, Broeren recovery from stroke patients (Chen et al., 2015). Patients with et al. (2007) used cancellation tasks to derive the pattern of previous brain injury or neurodegenerative diseases as well as search and Yasuda et al. (2020) used object detection tasks to bedridden and blind patients were excluded. Healthy age and assess near- and far SN. To assess neglect, eye tracking can be gender matched controls were recruited from the staff at HNC. used in conjunction with head-mounted displays to scan eye movement patterns (Baheux et al., 2004, 2006). Kim et al. (2004) combined eye tracking with VR task to create a diagnostics tool 2.1. Conventional Measures for SN. Twelve patients and 40 controls were diagnosed based Conventional SN tests were applied for comparison to virtual on deviation angle (between mandated and actual gaze position), reality measurements. The Line bisection test from the no-attention time, scanning time, number of cues, failure rate Behavioral Inattention Test (Wilson et al., 1987) requires the of mission, and ratio of right/left scan. Their deviation angle patients to mark the center of each of three (8 inches 20.3 mm) correlated with line bisection test results. Other studies have horizontal lines that are printed on a sheet of white paper. In used eye tracking in non-VR environments to assess neglect, for the Apples Cancellation Test (Bickerton et al., 2011) patients example Cazzoli et al. (2016) who measured x-axis gaze position are instructed to cancel out targets depicting outlines of apples, while participants with neglect and visual field defect (VFD) but only complete apples without gaps, on a sheet of white paper. viewed a projected virtual traffic scene. The neglect patients with The test yields individual scores for both non-lateralized visual VFD showed a significant rightward deviation in x-axis gaze attention (accuracy), egocentric and allocentric neglect. The gray Frontiers in Psychology | www.frontiersin.org 2 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics FIGURE 1 | (Left) Experimental setup showing note taker, technician and the participant who wore a head-mounted display whilst sitting in a wheel chair. (Middle) Participants wore an HTC Vive with Pupil Labs eye tracking cameras mounted inside. (Right) The virtual museum contained the participant and three images to the ◦ ◦ ◦ left (−48 ), right (+48 ), and middle (0 ). scales gradient test requires patients to judge which of two left- and started an eye tracking calibration procedure (staring at right mirror-reversed gray scale gradients appears darker. For dots shown in the head-mounted display). After successful Pupil each of the 12 pairs of stimuli, one of the grayscales is shaded Labs 2D calibration, they were presented with a simple museum from white on the left to black on right, and the other is shaded environment (Figure 1, Right). The environment consisted of in the opposite direction. The task is highly sensitive to unilateral three sets of three pictures shown on three walls. Head movement hemispheric brain damage, and can uncover attentional biases in was needed to see the entirety of the left and right pictures. patients without SN symptoms on conventional cancellation or The picture sets were either three faces of well known persons, line bisection tests (Mattingley et al., 2004). The chimeric faces three similar seasonal colored landscapes, or three non-figurative test consists of 12 pairs of chimeric faces generated from portraits paintings. The picture sets were selected to reflect symmetry of 10 different people smiling and 10 portraits of the same of salience, were placed equally far from the middle and people with a neutral expression arranged vertically (Mattingley counterbalanced. The participants viewed each picture set for 60 et al., 1993; Sarri et al., 2006). Each pair contains two chimeras s, totalling 180 s of free viewing time. While participants looked of the same person, one neutral in the left half and smiling around, we logged the VR headset’s position and orientation and in the right half, and the other vice versa, with the vertical their gaze. We used an HTC Vive VR headset with Pupil Labs eye position counterbalanced. Patients are instructed to chose the tracking equipment, which tracks with 1 degree accuracy (Pupil happier of the two thus revealing left (20/0) or right (0/20) Labs, 2021). The virtual environment was developed in Unity, attentional biases. The KF-NAP was developed on the basis of the which recorded the sensor data from the VR headset and Catherine Bergego Scale (Azouvi, 1996)—the most widely used raw raycasted gaze data using Pupil Labs’ API without jitter behavioral assessment instrument for SN (Azouvi, 2017). KF- postprocessing. The visual angle of each picture subtended 32 in ◦ ◦ NAP is a manual method for systematic observation of SN during width and 40 in height. The pictures were spaced 16 apart. The everyday activities, including 10 categories: gaze orientation, HTC Vive provided 110 field of view, although this depended limb awareness, auditory attention, dressing, grooming, personal on the fit (Lynn et al., 2020). Data from VR and Eye trackers belongings, navigation, collisions, having a meal, and cleaning were recorded at a 30 Hz sampling rate and analyzed with the after meals (Chen et al., 2012, 2015). Each category is scored from saccades package in R. 0 to 3, with higher scores indicating more severe neglect. The sum score ranging from 0 to 30 indicates the severity of SN with 2.3. Virtual Reality and Eye Tracking predefined cut-off scores of the severity (0 = none, 1–10 = mild, Measure Description, Preparation, and 11–20 moderate, 21–30 severe). KF-NAP has been shown to be Analysis very sensitive to neglect symptoms directly related to everyday After their calculation, all measures were normalized to range activities and to changes in the severity of neglect symptoms as from −1 (leftward) to 1 (rightward). For all measures except stroke patients are recovering (Chen et al., 2015). the fixations, we subtracted the percentage of time spent on the left side from the percentage of time spent on the right 2.2. Virtual Reality and Eye Tracking side (see Table 1). For these measures we defined impairments Procedure and Apparatus through cut-off criteria based on the difference between the Participants were instructed about wearing a virtual reality percentages of time spent in the left and the right hemispace headset and the free viewing task: “In a moment you will be in the control group (e.g., including the 5th percentile or none placed in a museum. You get a few minutes to look around. of the controls). These support clinical diagnostics e.g., whether You do not have to describe what you see.” We then equipped patients had allo-, egocentric neglect, or neglect related to head the participants with the virtual reality headset (Figure 1, Left) or eye midline deviations. Frontiers in Psychology | www.frontiersin.org 3 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics TABLE 1 | Virtual reality and eye tracking measurements. VR measure Description Interpretation Gaze asymmetry Estimated gaze from eye and head Egocentric-neglect (body between-pictures while comparing looking at the left midline) and right picture. Gaze asymmetry Difference in time spent on estimated Allocentric neglect within-picture gaze from eye and head combined (object midline) while looking at the pictures. Head orientation left/right Amount of time spent with the head Caputomotor neglect rotated to the left/right. (head midline) Eye orientation left/right Hemispheric orientation of the eyes Oculomotor neglect (eye only, without considering fixations or midline) gaze in scene. Fixation duration left/right Duration of eye fixations within the Egocentric neglect (body scene. Analyzed from saccades midline) (λ=1). Fixation count left/right Number of eye fixations made Egocentric neglect (body left/right within the scene. midline) TABLE 2 | Patient demographics and brain injury characteristics. ID Sex Hand Age Days since injury Lesion 2 M R 56 173 Traumatic subarachnoid hemorrhage and right subdural hematoma 4 F R 66 37 Hemorrhage right basal ganglia 7 M R 58 62 Subarachnoid hemorrhage 8 M R 56 55 Infarction right occipital lobe 16 M R 63 15 Infarction right internal carotid artery and middle cerebral artery 17 F R 61 74 Large hemorrhage right hemisphere 21 F L 54 52 Hemorrhage right hemisphere frontal 24 F R 68 25 Infarction right hemisphere frontal 26 M R 56 30 Infarction right middle cerebral artery 28 F R 69 31 Hemorrhage right thalamus 32 F R 74 497 Infarction right hemisphere 33 F R 58 100 Large hemorrhage right basal ganglia 34 F R 73 23 Infarction right middle cerebral artery 35 F R 63 100 Large infarction right frontal and parietal lobe 36 F R 58 54 Infarction right basal ganglia and parietal lobe, thrombus right internal carotid artery and middle cerebral artery 37 M R 51 154 Infarction right middle cerebral artery 38 M R 57 61 Infarction right middle cerebral artery 39 M R 64 17 Hemorrhage right middle and frontal Eye tracking data was filtered to include only data points Head- and eye orientation were measured irrespective of gaze from looking at the three pictures. Gaze asymmetry measured in virtual reality in order to assess motor neglect related to the position of the participants’ gaze projected onto these different body midlines. We did not correct for head position pictures. Between picture gaze asymmetry left out eye tracking when using head orientation as the patients were seated in wheel data from the middle picture and subtracted the amount chairs and potentially not sitting fully upright. Head Orientation of time spent looking at the left-most picture from the L/R subtracted the percentage of time (in seconds) participants time looking at the right-most picture. These temporal spent with the head rotated to the right from the percentage aggregates were solely based on the number of eye tracking of time spent on the left. For example, if a participant’s head samples located on each respective picture. Their fixation was oriented to the right side twice as long (66%) as to the left counts and the totalled duration of the fixations were side (33%), this measure reported an imbalance of −33%. Eye separate measures. Within-picture gaze asymmetry divided each Orientation L/R was based on how much time the person was picture into a left and right section and compared the looking to the left of their visual field center line (where the participants’ time spent gazing on each side, to measure nose is pointing) in comparison to looking right of it aggregated allocentric neglect. over all three pictures independent of head rotation. Fixation Frontiers in Psychology | www.frontiersin.org 4 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics durations and counts are common aggregate measures of gaze 3.2. Individual Results data but can behave differently. One could spend equal amounts Tables 5, 6 provides an overview of how well the conventional of gaze time left and right, yet still have fewer fixations and longer and virtual reality tests identified individual attentional biases durations of fixations to one side. Subtracting the percentage in the patient and control groups. Figure 3 show individual of fixations that happened on the left from those on the right gaze distributions. providing the measures fixation count L/R. The measure fixation 3.3. Gaze Asymmetry duration L/R relied on the difference of the sums of fixation Ten patients (2, 7, 8, 17, 24, 26, 33, 34, 35, 37) and one durations from the left and the right divided by the sum of all control (6) had abnormal right-ward bias related to the viewing fixation durations. time of the left and right most pictures, whereas two patients (28, 36) and one control (12) had small left-ward biases 2.4. Statistical Approach contrary to expectations (Figure 4). Right-ward biases could The conventional tests produced continuous raw scores for the be interpreted as SN behaviors centered at the body midline Apples Cancellation and the Line bisection tests, and asymmetry (egocentric neglect). scores for the gray scale gradients and the Chimeric faces. They Two patients (28, 33) and none of the controls had right-ward were analyzed according to their normative cut-off scores from bias related to the viewing time within the left and right half part the literature and binary neglect diagnostics were calculated. For of the pictures, whereas three patients (26, 34, 37) and one control the VR and eye tracking measures we relied on the data from (18) had left-ward bias (see Figure 5). Even though patients more the control group. For each measure we derived cut-offs (cu) commonly had deviant within-picture bias than controls, the by adding the mean m of the control group to 1.645 times its biases were both right-ward and left-ward and two patients (37, standard deviation sd (95th percentile): cu = m ± 1.645 ∗ c c 26) had fairly large left-ward biases contrary to expectation. This sd . Mann-Whitney tests checked for between group differences measure could be interpreted as SN behaviors related to the object unless indicated otherwise. An alpha value <5% (p < 0.05) was midline (allocentric neglect), even though the behavior of some considered statistically significant. Two-sided testing with a 5% patients was contrary to expectation. alpha value (α = 0.05) and 80% power (1 − β = 0.80) along with enrolling 18 patients and 16 healthy controls allowed us to detect 3.4. Head- and Eye-Orientation large effect sizes (Cohen’s d > 1.0). In terms of head orientation, 11 of the patients (2, 7, 8, 17, 24, 26, 33, 34, 35, 36, 37) and none of the controls showed an abnormal 2.5. Participant Characteristics right-ward bias, whereas one patient (28) and one control (12) Twenty three stroke patients and 16 age and gender matched had a small abnormal left-ward bias (see Figure 6). Right-ward controls from a hospital staff population were recruited. bias of head orientation can be interpreted as motor neglect or However, five patients were excluded for different reasons: one lack of intention to initiate head movements toward the left. had a premorbid surgical fixation of the neck, that prevented Four patients (8, 33, 37, 39) and two controls (3, 18) had natural movement of the head; one was easily fatigued and the VR an abnormal right-ward eye position bias, i.e., the eyes spend procedure was aborted; one got emotional labile during testing more time looking to the right than the left regardless of head with the conventional test and VR testing was not performed; one movement whereas two patients (26, 32) and none of the controls patient could not be satisfyingly calibrated for the eye tracking; had left-ward eye movement biases (see Figure 7). Right-ward and one patient had left-sided brain damage and right-sided eye movement bias could be interpreted as oculomotor neglect neglect. Participants were matched to have equal age and gender or a lack of intention to move ones eyes to the left. in the patient (range 51–74, M = 61.4, SD = 6.6, 9F/9M) and control group (range 52–69, M = 60.0, SD = 4.8, 8F/8M), with 3.5. Fixation-Duration and Fixation-Count no significant difference for age according to a t-test (p = 0.491). Seven patients (7, 8, 17, 33, 34, 35, 37) and one control (3) had The patient demographic characteristics are presented in Table 2. abnormal right-ward fixation time bias, i.e., they spent more time Written informed consent was obtained from the participants. on each fixation in the right VR hemispace compared to the left, whereas no patients and no controls exhibited left-ward biases (see Figure 8). 3. RESULTS Likewise, eight patients (7, 8, 17, 24, 33, 34, 35, and 37) and none of the controls had abnormal right-ward fixation counts, 3.1. Group-Level Results interpreted from the number of saccades, whereas no patients Table 3 describes the means and p-values from Mann-Whitney and no controls had left-ward bias (see Figure 9). tests on both conventional and VR measures used in the study. All conventional measures were significantly different (p < 0.05) between the patient and control groups. Most 4. DISCUSSION virtual reality measures differed significantly, too, except gaze This study aimed at investigating whether attentional biases asymmetry within picture and eye orientation left/right. The across different egocentric midlines of body, head, eyes, and correlations between virtual reality measures are described in allocentric midlines of objects could be assessed by VR and eye Table 4. Figure 2 depicts the density plots of the three pictures tracking on a group and individual level in patients with SN. split by patient and control groups. Frontiers in Psychology | www.frontiersin.org 5 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics TABLE 3 | Group-level reports for patient and control groups (conventional and VR tests). Patients (18) Controls (16) Measurement N/Mean SD N/Mean SD Cut-off scores p-value KF-NAP 13.6 5.8 – – – – Line bisection 6.3 3.1 8.9 0.3 ≤ 7 0.001 AC accuracy 32.0 14.0 48.5 2.0 ≤ 41 0.000 AC asymmetry egocentric 7.4 6.6 0.1 1.5 ≥ ±3 0.001 AC asymmetry allocentric 3.1 4.9 0.0 0.0 ≥ ±2 0.006 Gray scales (average left/right) 4/16 – 9/11 – ≥ 1/19 0.002 Chimeric faces (average left/right 7/13 – 12/8 – ≥ 1/19 0.020 Gaze asym. between-pict. 0.22 0.25 0.01 0.05 −0.07 / 0.09 0.003 Gaze asym. within-pict. 0.09 0.41 0.14 0.26 −0.28 / 0.57 0.665 Head Orientation L/R 0.21 0.23 0.01 0.05 −0.07 / 0.10 0.002 Eye orientation L/R 0.15 0.29 0.08 0.20 −0.25 / 0.40 0.391 Fixation duration L/R 0.30 0.33 0.08 0.22 −0.29 / 0.44 0.028 Fixation count L/R 0.30 0.30 0.08 0.18 −0.21 / 0.37 0.012 Cut-off scores for conventional test based on normative data. Fifth and 95th percentiles for VR and ET measures are based on control group performances. * indicates significance (p < 0.05). TABLE 4 | Correlations between VR measures, calculated using a pearson correlation coefficient. Gaze asymmetry Head orientation, Eyes, duration Eye Fixations, Eye fixations, within pictures duration L/R L/R duration L/R count L/R Gaze asymmetry between pictures –0.39 1.00 0.11 0.68 0.77 Gaze asymmetry within pictures – –0.35 0.50 0.22 0.20 Head orientation, duration L/R – 0.11 0.69 0.78 Eyes, duration L/R – 0.49 0.49 Eye fixations, duration L/R – 0.92 Eye fixations, count L/R – On a group level, gaze asymmetry between-pictures measures, but were picked up by different conventional (egocentric neglect) was highly sensitive but gaze asymmetry tests. This underlines the heterogeneity of spatial neglect within-pictures (allocentric neglect) was not. Likewise, head and provides evidence for the complementarity of a VR and orientation (caputomotor neglect) was highly sensitive, though eye-tracking based free viewing task for neglect diagnostics. eye orientation (oculomotor neglect) was not. Finally, fixation We observed a small rightward gaze bias in the control time and fixation count were both highly sensitive to right-ward group’s means during 180 s of viewing time, contrary to the neglect behavior. leftward bias commonly found in the first 1.5 s by Foulsham On an individual level, even though gaze asymmetry within- et al. (2018). Our measures did not consider the initial pictures (allocentric neglect) was not a significant measure of gaze behavior. neglect behavior on a group level, five patients as opposed The free-viewing task in our study resembled findings in to one control did in fact revealed deviant behavior in group-level midline deviations from previous task-based studies, either direction. Likewise did six patients as opposed to such as the left/right ratio measured by Kim et al. (2004, 2010) two controls revealed deviant eye orientation behavior in and the head orientation deviation found by Ogourtsova et al. either direction. (2018). The very high correlation between head orientation Overall, gaze-asymmetry between-pictures and head and gaze asymmetry between pictures matches findings from orientation each identified 10 out of 18 (56%) of the stroke Sidenmark and Gellersen (2019), which showed that focusing on patients, compared to 12 out of 18 (67%) for the best of the a target further than 15 away typically involves head orientation. conventional tests. Interestingly, three patients (34, 38, and We found a median undershooting to the right of the leftmost 39) were not picked up by any of the conventional neglect painting in patients (see Figure 2), similar to what Ogourtsova test at all, apart from their low to moderate KF-NAP scores et al. (2018) observed when their participants approached a left- used as the inclusion criteria. However, two of these exhibited side (−15 ) target in a locomotive task. Since allocentric neglect deviant rightward bias in one or more of the six VR and normally is observed across both sides, we decided not to sub- eye tracking measures. Conversely, four patients (4, 16, 21, analyse the within-picture asymmetry on the left side further. 38) were not picked up by any of the VR and eye tracking Our group based results on fixations mirrored non-VR based Frontiers in Psychology | www.frontiersin.org 6 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics FIGURE 2 | Group level spatial distribution of gaze samples on the (solid line) and median gaze (dotted line) of patients and controls. The x-axis spans the horizontal world space of the virtual museum scene from −2.0 to 2.0. The y-axis plots the corresponding gaze sample counts in thousands (k). TABLE 5 | Patient group demographics and results from conventional and VR measures. ID (18 Patients) 2 4 7 8 16 17 21 24 26 28 32 33 34 35 36 37 38 39 KF-NAP sum score 6 16 18 15 18 16 4 20 16 9 16 16 13 15 4 26 8 9 - gaze orientation 1 1 2 2 2 2 1 2 2 1 2 1 1 2 0 3 1 0 - limb awareness 1 2 2 1 3 2 1 2 2 2 2 2 2 1 1 3 1 2 - auditory attention 0 1 1 2 2 1 0 2 1 0 1 1 1 1 0 2 0 0 - personal belongings 1 2 2 2 2 2 0 2 2 1 2 2 1 2 1 3 1 0 - dressing 0 1 2 1 2 2 0 2 2 0 2 2 2 2 1 3 2 2 - grooming 1 1 2 1 1 1 1 2 2 1 1 2 2 2 0 2 1 2 - navigation 1 2 2 2 - 2 0 3 2 2 - 2 2 1 0 3 2 - - collisions 1 2 3 2 1 2 0 2 2 2 1 2 2 1 1 3 0 - - meals 0 2 1 1 1 1 0 1 1 0 2 1 0 1 0 2 0 0 - cleaning after meals 0 2 1 1 2 1 1 2 0 0 1 1 0 2 0 2 0 - Line bisection 6 9 9 0 5 0 4 6 4 9 3 9 9 8 8 7 9 9 AC accuracy 13 35 36 10 38 20 47 18 7 48 18 37 42 42 48 29 41 47 AC asymmetry egoc. 13 15 14 10 11 14 3 4 7 2 14 13 –3 –3 0 16 2 1 AC asymmetry alloc. 0 1 16 0 3 3 0 2 3 0 9 0 –1 8 0 12 0 0 Gray scales left/right 18/2 2/18 0/20 0/20 0/20 20/0 0/20 0/20 0/20 0/20 0/20 0/20 11/9 0/20 0/20 1/19 4/16 12/8 Chimeric faces L/R 11/9 7/13 0/20 3/17 4/16 20/0 1/19 10/10 8/12 9/11 10/10 0/20 16/4 4/16 0/19 14/6 6/14 11/9 Gaze Asym. Between-Pict. 0.14 0.04 0.35 0.35 0.05 0.52 0.04 0.23 0.44 –0.19 0.08 0.27 0.43 0.42 –0.08 0.79 –0.01 0.03 Gaze Asym. Within-Pict. –0.09 0.16 0.45 0.37 0.20 0.20 0.08 –0.08 –0.61 0.61 –0.18 0.61 –0.28 0.47 0.37 –0.84 –0.25 0.47 Head Orientation L/R 0.14 0.05 0.36 0.35 0.05 0.52 0.03 0.23 0.43 –0.17 0.09 0.30 0.43 0.39 –0.07 0.67 –0.01 0.04 Eye Orientation L/R 0.06 0.09 0.29 0.43 0.28 –0.06 0.21 0.21 –0.28 0.40 –0.36 0.62 –0.21 0.09 0.10 0.48 –0.23 0.57 Fixations, time L/R –0.07 –0.10 0.63 0.58 0.25 0.48 0.20 0.11 0.20 –0.07 –0.09 0.59 0.62 0.95 0.14 0.70 –0.17 0.42 Fixations, Count L/R 0.06 0.02 0.51 0.52 0.22 0.67 0.13 0.41 0.12 –0.09 –0.04 0.54 0.51 0.86 0.17 0.67 –0.19 0.33 Underlined numbers are significantly different (beyond the normative threshold from the controls). Blue shading denotes bias to the right. Red shading denotes bias to the left. Frontiers in Psychology | www.frontiersin.org 7 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics FIGURE 3 | Individual spatial distributions of gaze samples on the three pictures with true picture midline (solid lines) and median gaze (dotted lines) of patients and controls. The x-axis reports the horizontal axis of the virtual museum scene. The y-axis counts the number of gaze samples in thousands (k). Frontiers in Psychology | www.frontiersin.org 8 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics TABLE 6 | Control group demographics and results from conventional and VR measures. ID (16 Controls) 1 3 5 6 9 10 11 12 13 14 15 18 20 22 23 25 Line bisection 8 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 AC accuracy 50 45 48 50 50 49 47 50 50 43 50 50 49 48 48 49 AC asymmetry egoc. 0 3 0 0 0 0 3 0 0 -2 0 0 1 -2 -2 1 AC asymmetry alloc. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Gray scales L/R 8/12 16/4 12/8 17/3 6/14 16/4 6/14 5/15 8/12 7/13 19/1 1/19 5/15 12/8 5/15 5/15 Chimeric faces L/R 10/10 13/7 11/9 15/5 17/3 11/9 5/15 17/3 6/14 10/10 18/2 18/2 14/6 11/9 10/10 2/18 Gaze Asym. Between-Pict. –0.01 0.00 0.04 0.10 0.06 0.04 0.06 –0.11 –0.05 0.00 0.01 0.01 –0.05 0.03 0.01 0.05 Gaze Asym. Within-Pict. –0.19 0.53 –0.07 0.14 0.22 –0.10 0.11 0.14 0.41 –0.02 0.19 0.66 0.14 –0.06 –0.23 0.42 Head Orientation L/R –0.02 0.01 0.05 0.09 0.07 0.05 0.08 –0.11 –0.04 0.00 0.02 –0.01 –0.05 0.02 0.00 0.06 Eye Orientation L/R –0.21 0.43 0.14 0.14 0.16 0.01 0.25 –0.09 –0.19 –0.11 –0.01 0.45 –0.07 0.01 0.07 0.24 Fixations, Time L/R 0.00 0.46 –0.06 0.05 0.12 0.14 0.27 0.16 0.08 –0.26 –0.22 0.36 –0.25 0.01 –0.02 0.39 Fixations, Count L/R –0.07 0.33 –0.03 0.12 0.23 0.02 0.35 –0.10 0.01 –0.03 0.03 0.32 –0.15 –0.05 –0.05 0.35 Numbers underlined are above the 95th or below the 5th percentile (false positives). Blue shading denotes bias to the right. Red shading denotes bias to the left. studies that found fewer fixations for SN patients on the left While neglect patients might perform worse than controls side both in free viewing (Fellrath and Ptak, 2015; Ohmatsu during eye tracking calibration given the spatial arrangement et al., 2019) and visual search tasks (Cazzoli et al., 2011). of focal points across the visual field all patients included in Similarly our gaze asymmetry results and fixations matched the our study successfully passed calibration. However, our results rightward median gaze in SN patients in both free viewing indicated opportunities for detailed measurement of behavior and visual search tasks (Machner et al., 2012, 2018). But in over time, rather than "single-instance" tests with potentially contrast to the study by Primativo et al. (2015) ours did find less cognitive strain and we saw opportunities for sub-diagnosis significant group level differences for fixation durations and on neglect symptoms. Some of the VR and eye tracking counts. measures incorrectly picked up four controls (3, 6, 12, 18). The current free-viewing VR task was not sensitive enough In total 5/96 (5.2%) observations were right-ward bias false to detect neglect in all patients but there are other behavioral positives and 2/96 (2.1%) were left-ward bias false positive, measures that can be derived from the data collected in our which fairly closely resembles the expected false positive rates setup. For example, Sidenmark and Gellersen (2019) showed from a cut-off criteria set at the 5th percentile. False positives that people use different combinations of torso, head, and could be reduced by setting a stricter cut-off criteria e.g., eye rotations to acquire targets, which might differ for SN at the first percentile. Conventional neglect tests are often patients. Scan paths from eye tracking provide another such confounded by ceiling effects that yield high specificity (true avenue that could leverage the spatio-temporal data from positive rates), while they suffer from low sensitivity (true viewing each picture (e.g., re-fixations, mean amplitude, saccade negative rates) leading to patients passing these tests while landing position, Paladini et al., 2019), and initial fixation still experiencing neglect related problems in more complex location (Foulsham et al., 2018). Our free viewing created everyday activities. In this study, we wanted to compare the no best outcomes but could still be analyzed according to sensitivity of VR and eye tracking measures to conventional measures similar to Dalmaijer et al. (2015) quality of search measure for patients with clinically evident SN measured by or best R. the KF-NAP. However, including a group of stroke patients Our approach poses some limitations to the results. The without SN may have revealed subtle gaze biases caused by inter- simple museum environment and the free-viewing task created hemispheric imbalance in this group, too. This may very well low attentional demands. This may have allowed patients to try be due to the lack of specificity (false negatives) of conventional spending equal amounts of time on each picture if they expected neglect test, thus VR and eye tracking may in fact increase being tested. Tracking of the headset and eye movements may specificity of SN assessment. This should be investigated in have addressed motor neglect specifically but missing sensory future studies. neglect subtypes. The eye tracking data was constrained by a Neglect symptoms may be provoked by multitasking, 30 Hz sampling rate and a fairly narrow field of view offered simultaneous stimuli, mental fatigue, stress, or emotional by the current generation head-mounted displays that provided states (Blini et al., 2016). These are intentionally avoided eye tracking.Our results are limited by the accuracy of the gaze in conventional assessments usually administered in a well- tracker both by spatial accuracy and the temporal resolution of controlled examination room, but could be purposefully the eye tracking data including the inherent jitter. To account exploited in a controlled VR environment. In addition to for these limitations our measures did not require high spatial ceiling effects, many conventional neglect tests lack ecological accuracy, except for the within-picture measure, which may validity, i.e., providing no direct link between the task tested account for why no significant group difference was found. (e.g., cancellation or line bisection tests) and activities of daily Frontiers in Psychology | www.frontiersin.org 9 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics FIGURE 4 | Gaze Asymmetry Between-pictures. (Left) Individual normalized time difference between looking at left/right picture in patient (black, top) and control (gray, bottom) with normative threshold cut-offs (red lines). (Right) Patient (black, top) and control (gray, bottom) histograms of horizontal gaze sample positions limited to the left and right painting with the true (solid) midline and the (dotted) group median of horizontal gaze positions. FIGURE 5 | Gaze Asymmetry Within-picture. (Left) Individual time spent looking right and left within all pictures in patient (black, top) and control (gray, bottom) with the empirical cut-offs (red lines). (Right) Spatial distribution of gaze samples within all pictures with true (solid) midline and group median (dotted). FIGURE 6 | Head orientation left/right. (Left) Individual time spent rotating head left and right in patient (black, top) and control (gray, bottom) with normative threshold cut-offs (red lines). (Right) Spatial distribution of patient and control head orientation with true (solid) midline and group median (dotted). Frontiers in Psychology | www.frontiersin.org 10 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics FIGURE 7 | Eye orientation left/right. (Left) Individual time spent rotating eye balls left and right in patient (black, top) and control (gray, bottom) with normative threshold cut-offs (red lines). (Right) Spatial distribution of patient and control eye ball orientation with true (solid) midline and group median (dotted). FIGURE 8 | Fixation left/right. (Left) Individual time spent fixating eyes in the left and right for patient (black, top) and control (gray, bottom) with normative threshold cut-offs (red lines). For example, –1 indicates that participants spent 100% of the time fixating on the left. (Right) Time-weighted spatial distribution of patient and control fixations, according to world midline, with time-weighted medians (dotted). FIGURE 9 | Fixation count left/right. (Left) Individual fixation count right/left for patient (black, top) and control (gray, bottom) with normative threshold cut-offs (red lines). (Right) Spatial distribution of patient and control fixation counts, according to the world (solid) midline with (dotted) median. Frontiers in Psychology | www.frontiersin.org 11 November 2021 | Volume 12 | Article 742445 Hougaard et al. Spatial Neglect Motor Midline Diagnostics living. This may also be improved in VR and eye tracking AUTHOR CONTRIBUTIONS based assessment. HK, JJ, and LE conceptualized the study and designed the This study underlined the heterogeneity of symptoms methodology. Analysis of conventional measurements was done of SN and represents a first step in using virtual reality by LE and HK. BH and HK were responsible for data verification, in combination with eye tracking measures for individual cleanup and analysis of VR and eye tracking measures, and differential subtype diagnostics from a free viewing visualization of all data. BH created all graphical material and context. Virtual reality and eye tracking hold a potential wrote the background with supervision from HK. LE collected for individual subtype diagnostics that could inform and interpreted all clinical measurements. BH, LE, and HK clinical treatment choices and hence treatment efficacy. jointly wrote the discussion. All authors contributed to the article Improving sensitivity, specificity and ecological validity by and approved the submitted version. use of VR and eye-tracking measures may provide more accurate diagnostics and prognostics for patients with spatial neglect. ACKNOWLEDGMENTS The authors are indebted to the help of Bianca Clavio Christensen DATA AVAILABILITY STATEMENT (development and testing of VR and eye tracking), Jonas Lindeløv (initial data cleaning and analysis), Kristian Westergaard The raw data supporting the conclusions of this article will be Jensen (data collection), Rasmus Hougaard Pedersen (data made available by the authors, without undue reservation. collection), Alexander Kaiser (data collection), Kiefer Coze (VR implementation), and Théo Toupin (VR implementation). ETHICS STATEMENT The studies involving human participants were reviewed SUPPLEMENTARY MATERIAL and approved by the Scientific Ethics Committees for the Central Denmark Region. 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Conflict of Interest: The authors declare that the research was conducted in the doi: 10.1016/j.neuropsychologia.2003.07.007 absence of any commercial or financial relationships that could be construed as a Mattingley, J. B., Bradshaw, J. L., Phillips, J. G., and Bradshaw, J. A. (1993). potential conflict of interest. Reversed perceptual asymmetry for faces in left unilateral neglect. Brain Cogn. 23, 145–165. doi: 10.1006/brcg.1993.1052 Publisher’s Note: All claims expressed in this article are solely those of the authors Negut, A., Matu, S.-A., Sava, F. A., and David, D. (2016). Virtual reality measures and do not necessarily represent those of their affiliated organizations, or those of in neuropsychological assessment: a meta-analytic review. Clin. Neuropsychol. the publisher, the editors and the reviewers. Any product that may be evaluated in 30, 165–184. doi: 10.1080/13854046.2016.1144793 this article, or claim that may be made by its manufacturer, is not guaranteed or Nolin, P., Besnard, J., Allain, P., and Banville, F. (2019). “Assessment and endorsed by the publisher. rehabilitation using virtual reality after stroke: a literature review,” in Virtual Reality Technologies for Health and Clinical Applications, Chapter 15, Vol. 2, eds A. S. Rizzo and S. Bouchard (New York, NY: Springer), 307–326. Copyright © 2021 Hougaard, Knoche, Jensen and Evald. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC Ogourtsova, T., Archambault, P. S., and Lamontagne, A. (2018). Post-stroke visual neglect affects goal-directed locomotion in different perceptuo-cognitive BY). The use, distribution or reproduction in other forums is permitted, provided conditions and on a wide visual spectrum. Restor. 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