Abstract
Adding noise to a visual image makes object recognition more effortful and has a widespread effect on human electrophysiological responses. However, visual cortical processes directly involved in handling the stimulus noise have yet to be identified and dissociated from the modulation of the neural responses due to the deteriorated structural information and increased stimulus uncertainty in the case of noisy images. Here we show that the impairment of face gender categorization performance in the case of noisy images in amblyopic patients correlates with amblyopic deficits measured in the noise-induced modulation of the P1/P2 components of single-trial event-related potentials (ERP). On the other hand, the N170 ERP component is similarly affected by the presence of noise in the two eyes and its modulation does not predict the behavioral deficit. These results have revealed that the efficient processing of noisy images depends on the engagement of additional processing resources both at the early, feature-specific as well as later, object-level stages of visual cortical processing reflected in the P1 and P2 ERP components, respectively. Our findings also suggest that noise-induced modulation of the N170 component might reflect diminished face-selective neuronal responses to face images with deteriorated structural information.
Highlights
Human visual object recognition is fast and efficient when viewing conditions are good [1,2,3]
The Effect of Noise on Face Gender Categorization Adding noise to the face images resulted in a significant drop in face gender categorization performance as compared to the performance with intact, phase-coherent faces in both eyes (Fig1C.; rANOVA, main effect of noise: F(1,17) = 114.22, p,.0001)
The noise-induced performance decrement was more pronounced for the amblyopic than for the fellow eye: accuracy did not differ significantly between eyes in the case of phase-coherent faces while there was a marked performance difference between eyes in the case of noisy faces (rANOVA, eye 6 noise interaction: F(1,17) = 14.74, p = 0.0013, post-hoc PCFE vs. PCAE p = 0.096 while NFE vs. NAE p = 0.0002)
Summary
Human visual object recognition is fast and efficient when viewing conditions are good [1,2,3]. Despite the numerous studies using noisy visual images, it is still unclear, which neural processes constitute the mechanism that is actively engaged by the visual system to enable or support successful recognition of objects when the visual input is noisy These sensory processes that cope with stimulus noise are rather difficult to dissociate from other incidental processes invoked by the noisy input e.g. to deal with increased stimulus uncertainty, task difficulty or decreased task-relevant information content, as they are inherently involved due to the nature of the stimulus inseparable in studies on healthy subjects. Phase noise leads to a decreased N170 component, reflecting early structural face processing
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