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. 2023 May 30;17:1179081.
doi: 10.3389/fnhum.2023.1179081. eCollection 2023.

Spontaneous Necker-cube reversals may not be that spontaneous

Mareike Wilson  1   2   3   4 , Lukas Hecker  1   2   3   4   5 , Ellen Joos  6 , Ad Aertsen  4   7 , Ludger Tebartz van Elst  1   2 , Jürgen Kornmeier  1   2   3   4
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Free PMC article

Spontaneous Necker-cube reversals may not be that spontaneous

Mareike Wilson et al. Front Hum Neurosci. .
Free PMC article

Abstract

Introduction: During observation of the ambiguous Necker cube, our perception suddenly reverses between two about equally possible 3D interpretations. During passive observation, perceptual reversals seem to be sudden and spontaneous. A number of theoretical approaches postulate destabilization of neural representations as a pre-condition for reversals of ambiguous figures. In the current study, we focused on possible Electroencephalogram (EEG) correlates of perceptual destabilization, that may allow prediction of an upcoming perceptual reversal.

Methods: We presented ambiguous Necker cube stimuli in an onset-paradigm and investigated the neural processes underlying endogenous reversals as compared to perceptual stability across two consecutive stimulus presentations. In a separate experimental condition, disambiguated cube variants were alternated randomly, to exogenously induce perceptual reversals. We compared the EEG immediately before and during endogenous Necker cube reversals with corresponding time windows during exogenously induced perceptual reversals of disambiguated cube variants.

Results: For the ambiguous Necker cube stimuli, we found the earliest differences in the EEG between reversal trials and stability trials already 1 s before a reversal occurred, at bilateral parietal electrodes. The traces remained similar until approximately 1100 ms before a perceived reversal, became maximally different at around 890 ms (p = 7.59 × 10-6, Cohen's d = 1.35) and remained different until shortly before offset of the stimulus preceding the reversal. No such patterns were found in the case of disambiguated cube variants.

Discussion: The identified EEG effects may reflect destabilized states of neural representations, related to destabilized perceptual states preceding a perceptual reversal. They further indicate that spontaneous Necker cube reversals are most probably not as spontaneous as generally thought. Rather, the destabilization may occur over a longer time scale, at least 1 s before a reversal event, despite the reversal event as such being perceived as spontaneous by the viewer.

Keywords: EEG; Necker cube; ambiguous figures; bistable perception; perceptual reversals.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Schematic demonstration of the reversal dynamics. The participant observes an ambiguous Necker lattice discontinuously over a certain time interval and perceives it as facing in one orientation. The perceptual representation is postulated to destabilize over time (blue arrow) until the percept becomes so unstable (indicated by the light blue frame) that a perceptual reversal occurs. After the reversal, the perceptual representation is again temporally stable (dark blue frame). Bottom row: Necker lattice stimuli as ambiguous sensory input. Top row: perceptual interpretation of the observer. The instances R indicate perceptual reversals.
FIGURE 2
FIGURE 2
The experiment consisted of two experimental conditions, the Ambiguity Condition (top row) and Disambiguation Condition (bottom row). In both conditions, the lattice stimuli were presented for 1000 ms with ISIs of 400 ms in between. Participants had to compare successive stimuli and indicate via button press whether they perceived the current lattice orientation as reversed compared to the previous lattice (reversal trials, R) or as unchanged (stability trials, S). Participants were allowed to respond from stimulus onset until the end of the subsequent ISI. We focused our analysis on the stimulus time window before (Si) and after (Si+1) the reversed percept, including the ISI in between. Diagram adapted from Kornmeier and Bach (2012) and Joos et al. (2020).
FIGURE 3
FIGURE 3
Global Field Power (GFP) and p-values of the Disambiguation (red) and Ambiguous (blue) Conditions. The two top panels show the GFP averaged across participants. The dashed, darker traces depict the stable condition, whereas the lighter, continuous trace depicts the reversal condition. The middle two panels depict difference GFP traces of the top row (reversal minus stability) resulting in the difference traces. The shaded area is ± standard error of the mean. The bottom panels show the p-values logarithmically scaled. The orange-red horizontal lines depict alpha values of 0.05, 0.01, and 0.001, respectively. The filled (red and blue) areas indicate statistically significant time periods. The gray areas indicate interstimulus interval time ranges. The first range shown is the ISI preceding Si. The next 1,000 ms represent the onset period of Si and the 1000 ms after the interstimulus interval show Si+1.
FIGURE 4
FIGURE 4
Median accuracy of individual participants (colored circles) and the grand mean ± standard deviation (brown squares). The x-axis shows the accuracy in the Ambiguous Condition and the y-axis the accuracy in the Disambiguation Condition. The left panel shows the accuracy calculated during the Si stimulus time window and the right panel shows the accuracy during the ISI time window (reversal and stable). The number inserted in the top left shows the mean accuracy ratio (ambiguous divided by disambiguated) accuracies (with the standard deviation). The continuous gray horizontal and vertical lines indicate chance level at 50% accuracy.
FIGURE 5
FIGURE 5
Examples of accuracy distributions resulting from the bootstrap method and the corresponding Kolmogorov–Smirnov (KS) test statistic for participants 4, 11, and 5. The red distributions represent the Disambiguation Condition accuracies, the blue distributions represent the accuracies in the Ambiguous Condition. The KS test statistics ranges between 0 and 1. The closer the values are to 1, the further apart the distributions are.
FIGURE 6
FIGURE 6
Kolmogorov–Smirnov (KS) test statistic values indicating the separability of the distribution of ambiguous and disambiguated accuracies in Si (300–700 ms) and the ISI. The KS test statistic values ranges from 0 to 1. The closer the values are to 1, the further apart the distributions are. The x-axis presents the KS statistic of Si Time Window. The y-axis presents the statistic of the ISI Time Window. The colors correspond to the individual participants. Most participants with high/low separability in the Si Time Window also showed high/low values in the ISI Time Window, with overall better separability in the Si Time Window than in the ISI Time Window (i.e., more data points below the diagonal). Moreover, largest separability can be observed in participants 2, 3, 4, 9, 12, 13, 14, and 15 (indicative participants).
FIGURE 7
FIGURE 7
Accuracy ratio of Si (300–700 ms after stimulus onset) of the 8 indicative participants with different electrode subsets removed with each run. The values show the mean accuracy ratio of all indicative participants. The different colors depict the different participants and the numbers in the top left of each panel represents the mean accuracy ratio (Ambiguity divided by Disambiguation; with the standard deviation). The larger the distances (to the right and to the top) of the individual icons from the horizontal and vertical gray lines are, the higher is the discriminatory power of the respective participant’s EEG data.
FIGURE 8
FIGURE 8
Results of the source localization with thresholded t-values for the Ambiguity Condition. Reversal ERPs compared to stable ERPs. The size of the cluster does not represent the relevance of the cluster. Activity seems to be concentrated mainly in the right hemisphere, specifically the parahippocampal place area (PPA). There also seems to be some activity in the left hemisphere in a similar area. Additionally, the posterior cingulate cortex (PCC) also seems to be active.
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Grant support

This work was funded by Neurex, the Deutsch-Französische Hochschule (DFH), European Campus (Eucor) seeding money, and the Institute for Frontier Areas of Psychology and Mental Health (IGPP). We acknowledge support by the Open Access Publication Fund of the University of Freiburg.

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