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. 2021 Jun 1;16(6):e0237278.
doi: 10.1371/journal.pone.0237278. eCollection 2021.

How predictability affects habituation to novelty

Affiliations

How predictability affects habituation to novelty

Kazutaka Ueda et al. PLoS One. .

Abstract

One becomes accustomed to repeated exposures, even for a novel event. In the present study, we investigated how predictability affects habituation to novelty by applying a mathematical model of arousal that we previously developed, and through the use of psychophysiological experiments to test the model's prediction. We formalized habituation to novelty as a decrement in Kullback-Leibler divergence from Bayesian prior to posterior (i.e., information gain) representing arousal evoked from a novel event through Bayesian update. The model predicted an interaction effect between initial uncertainty and initial prediction error (i.e., predictability) on habituation to novelty: the greater the initial uncertainty, the faster the decrease in information gain (i.e., the sooner habituation occurs). This prediction was supported by experimental results using subjective reports of surprise and event-related potential (P300) evoked by visual-auditory incongruity. Our findings suggest that in highly uncertain situations, repeated exposure to stimuli can enhance habituation to novel stimuli.

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Conflict of interest statement

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

Figures

Fig 1
Fig 1. Updates of information gain for different initial prediction errors (initial uncertainty = 1.0, noise = 0.5, learning rate α = 0.1).
Fig 2
Fig 2. Updates of information gain for different initial uncertainties (initial prediction error = 0, noise = 0.5, learning rate α = 0.1).
Fig 3
Fig 3. Updates of information gain for different initial uncertainties (initial prediction error = 10.0, noise = 0.5, learning rate α = 0.1).
Fig 4
Fig 4. Relationship between the initial uncertainty and the integrated value of the information gain.
Fig 5
Fig 5. Subjectively reported scores for surprise intensities in response to percussive sounds congruent with the instrument shown (i.e., low initial prediction error).
The results for familiar and unfamiliar instruments were compared at every 40 exposures (N = 16).
Fig 6
Fig 6. Subjectively reported scores for surprise intensities in response to percussive sounds incongruent with the instrument shown (i.e., high initial prediction error).
The results for familiar and unfamiliar instruments were compared at every 40 exposures (N = 16).
Fig 7
Fig 7. Grand mean ERP waveforms for the four combinations of percussion instruments and percussive sounds at the parietal midline region (Pz).
Open triangles: The onset of film presentation. Solid triangle: The onset of beating sound presentation. The horizontal bars show the time range of 250–600 ms for the P300 latency.
Fig 8
Fig 8. P300 amplitudes evoked by percussive sounds congruent with the instrument shown (i.e., low initial prediction error).
The results for familiar and unfamiliar instruments were compared at every 40 exposures (N = 15).
Fig 9
Fig 9. P300 amplitudes evoked by percussive sounds incongruent with the instrument shown (i.e., high initial prediction error).
The results for familiar and unfamiliar instruments were compared at every 40 exposures (N = 15).

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