scispace - formally typeset
Journal ArticleDOI

From spatial frequency contrast to edge preponderance: the differential modulation of early visual evoked potentials by natural scene stimuli.

Reads0
Chats0
TLDR
The results suggest that the relative dominance in signal output of the N1 and P1 components is dependent on spatial frequency (SF) luminance contrast for simple stimuli up to natural scene imagery possessing few edges, however, such a dependency shifts to a dominant N1 signal for natural scenes possessing abundant edge content and operates independently of SF luminance Contrast.
Abstract
The contrast response function of early visual evoked potentials elicited by sinusoidal gratings is known to exhibit characteristic potentials closely associated with the processes of parvocellular and magnocellular pathways. Specifically, the N1 component has been linked with parvocellular processes, while the P1 component has been linked with magnocellular processes. However, little is known regarding the response properties of the N1 and P1 components during the processing and encoding of complex (i.e., broadband) stimuli such as natural scenes. Here, we examine how established physical characteristics of natural scene imagery modulate the N1 and P1 components in humans by providing a systematic investigation of component modulation as visual stimuli are gradually built up from simple sinusoidal gratings to highly complex natural scene imagery. The results suggest that the relative dominance in signal output of the N1 and P1 components is dependent on spatial frequency (SF) luminance contrast for simple stimuli up to natural scene imagery possessing few edges. However, such a dependency shifts to a dominant N1 signal for natural scenes possessing abundant edge content and operates independently of SF luminance contrast.

read more

Citations
More filters
Journal ArticleDOI

Contributions of low- and high-level properties to neural processing of visual scenes in the human brain

TL;DR: It is suggested that this problem can be resolved by questioning the utility of the classical low- to high-level framework of visual perception for scene processing, and why low- and mid-level properties may be particularly diagnostic for the behavioural goals specific to scene perception as compared to object recognition.
Journal ArticleDOI

From Image Statistics to Scene Gist: Evoked Neural Activity Reveals Transition from Low-Level Natural Image Structure to Scene Category

TL;DR: It is shown that, when human observers categorize global information in real-world scenes, the brain exhibits strong sensitivity to low-level summary statistics, and that global scene information may be computed by spatial pooling of responses from early visual areas (e.g., LGN or V1).
Journal ArticleDOI

Spatially Pooled Contrast Responses Predict Neural and Perceptual Similarity of Naturalistic Image Categories

TL;DR: Computationally estimated low-level contrast responses to computer-generated naturalistic images, and tested whether spatial pooling of these responses could predict image similarity at the neural and behavioral level, suggesting that statistics derived from low- level contrast responses can be extracted in early visual processing and can be relevant for rapid judgment of visual similarity.
Journal ArticleDOI

Different spatial frequency bands selectively signal for natural image statistics in the early visual system

TL;DR: The results suggest that the dependency of early VEPs on natural image statistics results from an interaction between the early neural processes tuned to different bands of spatial frequency.
Journal ArticleDOI

Early spatial frequency processing of natural images: an ERP study.

TL;DR: A linear relationship between the spectral power and the amplitude of the P1 and P2 was observed, which is likely to reflect the progressive engagement of the lateral occipital complex as the amount of information in both the low and high portions of the frequency spectrum increased.
References
More filters
Journal ArticleDOI

A Practical Guide to Wavelet Analysis.

TL;DR: In this article, a step-by-step guide to wavelet analysis is given, with examples taken from time series of the El Nino-Southern Oscillation (ENSO).
Journal ArticleDOI

Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope

TL;DR: The performance of the spatial envelope model shows that specific information about object shape or identity is not a requirement for scene categorization and that modeling a holistic representation of the scene informs about its probable semantic category.
Journal ArticleDOI

Relations between the statistics of natural images and the response properties of cortical cells.

TL;DR: The results obtained with six natural images suggest that the orientation and the spatial-frequency tuning of mammalian simple cells are well suited for coding the information in such images if the goal of the code is to convert higher-order redundancy into first- order redundancy.
Journal ArticleDOI

Natural image statistics and neural representation

TL;DR: It has long been assumed that sensory neurons are adapted to the statistical properties of the signals to which they are exposed, but recent developments in statistical modeling have enabled researchers to study more sophisticated statistical models for visual images, to validate these models empirically against large sets of data, and to begin experimentally testing the efficient coding hypothesis.
Journal ArticleDOI

Normalization of cell responses in cat striate cortex

TL;DR: A modified version of the linear/energy model is presented in which striate cells mutually inhibit one another, effectively normalizing their responses with respect to stimulus contrast, and shows that the new model explains a significantly larger body of physiological data.
Related Papers (5)