Back

Gaze biases can reflect task-specific spatial memorization strategies

Chota, S.; Arora, K.; Kenemans, L.; Gayet, S.; Van der Stigchel, S.

2024-08-30 neuroscience
10.1101/2024.08.30.610231 bioRxiv
Show abstract

Previous work has suggested that small directional eye movements not only reveal the focus of external spatial attention towards visible stimuli, but also accompany shifts of internal attention to stimuli in visual working memory (VWM)(van Ede et al., 2019). When the orientations of two bars are memorized and a subsequent retro-cue indicates which orientation needs to be reported, participants gaze is systematically biased towards the former location of the cued item (Figure 1AB). This finding was interpreted as evidence that the oculomotor system indexes internal attention; that is, attention directed at the location of stimuli that are no longer presented but are maintained in VWM. Importantly, as the location of the bars is presumably not relevant to the memory report, the authors concluded that orientation features in VWM are automatically associated with locations, suggesting that VWM is inherently spatially organized. This conclusion depends on the key assumption that participants indeed memorize and subsequently attend orientation features. Here we re-analyse Experiment 1 by van Ede et al. (2019) and demonstrate that this assumption does not hold. Instead of memorizing orientation features, participants deployed an alternative spatial strategy by memorizing bar endpoints. Although we do not call into question the conclusion that internal attention is inherently spatially organized, our results do imply that directional gaze biases might also reflect attention directed at task-relevant stimulus endpoints, rather than internal attention directed at memorized orientations. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=161 SRC="FIGDIR/small/610231v2_fig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@940e51org.highwire.dtl.DTLVardef@37ec3dorg.highwire.dtl.DTLVardef@176b186org.highwire.dtl.DTLVardef@180e8a7_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO Gaze density maps from Experiment 1 by van Ede et al. (2019) (N = 23, trials included = 20.864, 400 to 1000 ms). AB. Original reported effect of cued item location on gaze bias. Calculated by subtracting cued-item-left and cued-item-right gaze density maps. Rectangles indicate used stimulus positions and orientation ranges (min: 20{degrees}, mean: 45{degrees}, max: 70{degrees}; min: 110{degrees}, mean: 135{degrees}, max: 160{degrees}) of bar stimuli. C. Normalized Gaze bias vectors per condition (red dotted lines), horizontal vectors (dotted black lines) and average vectors pointing towards most foveal bar endpoints (solid black lines). Gaze bias vector endpoints were calculated from the centre of mass of each condition, ignoring negative values. Circular t-tests revealed that individual gaze bias vector angles (red dotted lines) were significantly different from horizontal vectors (dotted black lines) but not significantly different from endpoint vectors (solid black lines). FI. Vertical gaze bias revealed by separating trials based on bar orientations. Red dotted lines depict group average gaze bias vectors. F. Both bar endpoints "upwards" (left: 20{degrees} to 70{degrees} right: 110{degrees} to 160{degrees}) minus both bars endpoints "downwards" (left: 110{degrees} to 160{degrees}, right: 20{degrees} to 70{degrees}). I. Both "downwards" minus both "upwards". DEGH. Individual gaze density maps for each attention (left versus right) and bar endpoint direction (upwards versus downwards) separately. Solid black Lines show average vector pointing towards closest 45{degrees}/135{degrees} bar endpoint (i.e., average optimal gaze location for solving the memory task through memory maintenance of a spatial location). Red dotted lines depict group average gaze bias vectors (calculated from the centre of mass of each condition, ignoring negative values). C_FIG

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

1
Journal of Vision
92 papers in training set
Top 0.1%
16.9%
2
Journal of Cognitive Neuroscience
119 papers in training set
Top 0.1%
7.9%
3
Journal of Neurophysiology
263 papers in training set
Top 0.1%
4.7%
4
eneuro
389 papers in training set
Top 2%
4.7%
5
Scientific Reports
3102 papers in training set
Top 25%
4.7%
6
Attention, Perception, & Psychophysics
17 papers in training set
Top 0.1%
4.4%
7
European Journal of Neuroscience
168 papers in training set
Top 0.1%
3.7%
8
Vision Research
26 papers in training set
Top 0.1%
3.5%
50% of probability mass above
9
Psychonomic Bulletin & Review
14 papers in training set
Top 0.1%
3.5%
10
Cortex
102 papers in training set
Top 0.1%
2.8%
11
The Journal of Neuroscience
928 papers in training set
Top 4%
2.6%
12
PLOS Computational Biology
1633 papers in training set
Top 12%
2.6%
13
Experimental Brain Research
46 papers in training set
Top 0.2%
2.4%
14
PLOS ONE
4510 papers in training set
Top 47%
2.3%
15
Frontiers in Neuroscience
223 papers in training set
Top 3%
2.3%
16
Journal of Experimental Psychology: Human Perception and Performance
10 papers in training set
Top 0.1%
2.3%
17
Journal of Experimental Psychology: General
20 papers in training set
Top 0.1%
2.0%
18
iScience
1063 papers in training set
Top 13%
1.8%
19
eLife
5422 papers in training set
Top 44%
1.6%
20
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 34%
1.6%
21
Cerebral Cortex
357 papers in training set
Top 1.0%
1.6%
22
Nature Human Behaviour
85 papers in training set
Top 2%
1.6%
23
Cognition
44 papers in training set
Top 0.3%
1.6%
24
Psychological Review
19 papers in training set
Top 0.1%
1.4%
25
Neuropsychologia
77 papers in training set
Top 0.7%
1.4%
26
Frontiers in Psychology
49 papers in training set
Top 0.9%
0.9%
27
NeuroImage
813 papers in training set
Top 5%
0.9%
28
Royal Society Open Science
193 papers in training set
Top 5%
0.8%
29
Frontiers in Behavioral Neuroscience
46 papers in training set
Top 1.0%
0.8%
30
Neuroscience
88 papers in training set
Top 3%
0.8%