Subject ZT showed a slight increase of 4. The decrease in ERP threshold resulting from increased mask responses suggests that learning reduces the temporal interactions between target and mask. The results of this study show that performance level in the texture discrimination task is highly correlated with the early N1 mask ERPs recorded at occipital scalp sites positioned over early visual areas. This correlation, possibly due to target-mask interaction, exposed a neural determinant of performance which operates beyond the robust early target response, though still relatively early compared to later components such as the P response.
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Our ability to extract these neuronal thresholds using target-mask interactions enables us to predict the behavioral thresholds. Furthermore, our results suggest that perceptual learning could improve these neuronal thresholds by reducing the temporal interactions between target and mask. Our uncommon strong and fast negative responses instead of the common P may be a result of the high intensities we used.
Overall, these potentials depend on the stimulated visual field and stimulus type, showing high variability between different studies using a variable range of stimuli-types, locations and physical parameters such as luminance, contrast and spatial frequency see for example Vassilev et al. In particular, stimulus intensity has a major factor in setting the delay of the specific events. Therefore, our stimuli which present a strong intensity increment to the visual system, may explain the fast negative responses observed here when we used the same stimuli with lower intensity, we indeed obtained a more common delayed negative peak at around ms, of smaller magnitude; results not shown.
Our results show that the N1 mask response decreases with decreasing SOAs Figure 3b , while interestingly, the target N1 transient response is unaffected. The correlation with performance suggests that performance fails when the presented mask is integrated with the target, limiting its effective processing, thus revealing an extended processing time-course of up to ms beyond the transient target response, though still relatively early compared to later components such as the P response.
Integration of the mask with the preceding target, may explain the decreasing response to the mask signal: The reduced N1 mask response may be the response to elements in the mask stimulus that are not overlapping with the target and therefore not integrated with it, and processed in alternative networks. Furthermore, Musselwhite and Jeffreys showed that comparable limiting SOA values are needed for the C1 components of the two patterns to separate out forming a double-peaked response, and for the stimulus to be perceived as two distinct events. Decrease in amplitude of response to the second of two rapidly successive stimuli was also shown in the auditory domain, and correlated with performance decrease in an auditory discrimination task performed by poor readers Nagarajan et al.
Recordings from primary visual cortex of awake monkeys Lamme et al. However, V1 figure-ground signals were selectively suppressed at target-mask intervals that resulted in reduced performance.
Our current study, implying processing beyond the transient target response therefore extends these results to humans, using the texture discrimination task which requires figure-ground segregation. The results showing high correlation of the ERP N1 mask signal with behavior imply that performance in a visual task such as texture discrimination depends in early visual areas on the temporal interactions between early target and mask responses.
Moreover, the results presented here show that practice in a visual task such as texture discrimination, seems to reduce the temporal interactions between target and mask. Such inhibition of background elements reduces the sustained activity of the processing network, possibly reducing its duration, enabling better separation between the response to the target and the response to the following mask. This may explain why following learning, the N1 mask response decreases less, resulting in improvement of the neurometric ERP mask thresholds along with the improvement of the behavioral discrimination thresholds.
Enhanced inhibition may also be consistent with increments of BOLD signal in V1 as a result of perceptual learning as shown in previous studies Schwartz et al. Previous studies using the texture discrimination task Censor et al. These studies suggested that neuronal changes in early stages of the visual system underlie these performance gains. While most such studies showed small-scale modulations as a result of learning, the pronounced effects found here which highly match the behavioral outcome of individual subjects do not rule out smaller electrophysiological modulations, but do enable to predict the behavioral thresholds and suggests that perceptual learning could improve neuronal thresholds by reducing the temporal interactions between target and mask.
Our results show that behavioral performance can be predicted from early ERP signals obtained from early visual areas. Performance seems to fail when the presented mask interferes, possibly by integration, with the effective processing of the target signal, revealing an extended processing time-course beyond the transient target response. The correlation found here may have an essential role in the underlying mechanism limiting visual perception, such as backward masking.
Early intervention and Enablement
Perceptual learning in the texture discrimination task may therefore involve reduction of the temporal interactions between the target and the mask. Predicting performance level not detected in the transient target response but rather by further interactions shown here, may have important implications to the study of human perception, and could be used to study further limitations on perception including other sensory tasks.
Commercial relationships: none. Corresponding author: Dov Sagi. Email: dov. Bach, M. Meigen, T. Similar electrophysiological correlates of texture segregation induced by luminance, orientation, motion and stereo.
Vision Research, 37, — Electrophysiological correlates of human texture segregation, an overview. Documenta Ophthalmologica, 95, — Fabre-Thorpe, M. Thorpe, S. The time course of visual processing: Backward masking and natural scene categorisation. Vision Research, 45, — Boehler, C. Schoenfeld, M. Heinze, H. Hopf, J. Rapid recurrent processing gates awareness in primary visual cortex. Casco, C.
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Campana, G. Grieco, A. Fuggetta, G. Perceptual learning modulates electrophysiological and psychophysical response to visual texture segmentation in humans. Neuroscience Letters, , 18— Censor, N. Sagi, D. Benefits of efficient consolidation: Short training enables long-term resistance to perceptual adaptation induced by intensive testing. Vision Research, 48, — Vision Research,. Karni, A.clublavoute.ca/fetyw-sitios-para-conocer.php
Publications | Patrick Cavanagh
A link between perceptual learning, adaptation and sleep. Vision Research, 46, — Coltheart, M. Arthur, B. Evidence for an integration theory of visual masking. Quarterly Journal of Experimental Psychology, 24, — Del Cul, A. Baillet, S. Dehaene, S. Brain dynamics underlying the nonlinear threshold for access to consciousness. PLoS Biology, 5. Fahle, M. Quenzer, T.
Braun, C. Spang, K. Feature-specific electrophysiological correlates of texture segregation. Vision Research, 43, 7— Fahrenfort, J.
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Scholte, H. Lamme, V. Masking disrupts reentrant processing in human visual cortex. Journal of Cognitive Neuroscience, 19, — Harris, A. Nakayama, K.
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