Re-entrant feedback processing is a key mechanism of visual object-recognition, especially under compromised viewing conditions where only sparse information is available and object features must be interpolated. Illusory Contour stimuli are commonly used in conjunction with Visual Evoked Potentials (VEP) to study these filling-in processes, with characteristic modulation of the VEP in the ∼100-150 ms timeframe associated with this re-entrant processing. Substantial inter-individual variability in timing and amplitude of feedback-related VEP modulation is observed, raising the question whether this variability might underlie inter-individual differences in the ability to form strong perceptual gestalts. Backward masking paradig ms have been used to study inter-individual variance in the ability to form robust object perceptions before processing of the mask interferes with object-recognition. Some individuals recognize objects when the time between target object and mask is extremely short, whereas others struggle to do so even at longer target-to-mask intervals. We asked whether timing and amplitude of feedback-related VEP modulations were associated with individual differences in resistance to backward masking. Participants (N=40) showed substantial performance variability in detecting Illusory Contours at intermediate target-to-mask intervals (67 ms and 117 ms), allowing us to use kmeans clustering to divide the population into four performance groups (poor, low-average, high-average, superior). There was a clear relationship between the amplitude (but not the timing) of feedback-related VEP modulation and Illusory Contour detection during backward masking. We conclude that individual differences in the strength of feedback processing in neurotypical humans lead to differences in the ability to quickly establish perceptual awareness of incomplete visual objects.
|Original language||English (US)|
|State||Published - Oct 1 2022|
- Object recognition
- Perceptual closure
- Reentrant processing
ASJC Scopus subject areas
- Cognitive Neuroscience