Dataset Information

Evidence for Separate Contributions of High and Low Spatial Frequencies during Visual Word Recognition.

ABSTRACT: Previous studies have shown that different spatial frequency information processing streams interact during the recognition of visual stimuli. However, it is a matter of debate as to the contributions of high and low spatial frequency (HSF and LSF) information for visual word recognition. This study examined the role of different spatial frequencies in visual word recognition using event-related potential (ERP) masked priming. EEG was recorded from 32 scalp sites in 30 English-speaking adults in a go/no-go semantic categorization task. Stimuli were white characters on a neutral gray background. Targets were uppercase five letter words preceded by a forward-mask (#######) and a 50 ms lowercase prime. Primes were either the same word (repeated) or a different word (un-repeated) than the subsequent target and either contained only high, only low, or full spatial frequency information. Additionally within each condition, half of the prime-target pairs were high lexical frequency, and half were low. In the full spatial frequency condition, typical ERP masked priming effects were found with an attenuated N250 (sub-lexical) and N400 (lexical-semantic) for repeated compared to un-repeated primes. For HSF primes there was a weaker N250 effect which interacted with lexical frequency, a significant reversal of the effect around 300 ms, and an N400-like effect for only high lexical frequency word pairs. LSF primes did not produce any of the classic ERP repetition priming effects, however they did elicit a distinct early effect around 200 ms in the opposite direction of typical repetition effects. HSF information accounted for many of the masked repetition priming ERP effects and therefore suggests that HSFs are more crucial for word recognition. However, LSFs did produce their own pattern of priming effects indicating that larger scale information may still play a role in word recognition.

SUBMITTER: Winsler K

PROVIDER: S-EPMC5480267 | biostudies-other | 2017

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:In complex real-world scenes, image content is conveyed by a large collection of intertwined visual features. The visual system disentangles these features in order to extract information about image content. Here, we investigate the role of one integral component: the content of spatial frequencies in an image. Specifically, we measure the amount of image content carried by low versus high spatial frequencies for the representation of real-world scenes in scene-selective regions of human visual cortex. To this end, we attempted to decode scene categories from the brain activity patterns of participants viewing scene images that contained the full spatial frequency spectrum, only low spatial frequencies, or only high spatial frequencies, all carefully controlled for contrast and luminance. Contrary to the findings from numerous behavioral studies and computational models that have highlighted how low spatial frequencies preferentially encode image content, decoding of scene categories from the scene-selective brain regions, including the parahippocampal place area (PPA), was significantly more accurate for high than low spatial frequency images. In fact, decoding accuracy was just as high for high spatial frequency images as for images containing the full spatial frequency spectrum in scene-selective areas PPA, RSC, OPA and object selective area LOC. We also found an interesting dissociation between the posterior and anterior subdivisions of PPA: categories were decodable from both high and low spatial frequency scenes in posterior PPA but only from high spatial frequency scenes in anterior PPA; and spatial frequency was explicitly decodable from posterior but not anterior PPA. Our results are consistent with recent findings that line drawings, which consist almost entirely of high spatial frequencies, elicit a neural representation of scene categories that is equivalent to that of full-spectrum color photographs. Collectively, these findings demonstrate the importance of high spatial frequencies for conveying the content of complex real-world scenes.

Dataset Information

Evidence for Separate Contributions of High and Low Spatial Frequencies during Visual Word Recognition.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets