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Early and late effects of objecthood and spatial frequency on event-related potentials and gamma band activity.

Craddock M, Martinovic J, Müller MM - BMC Neurosci (2015)

Bottom Line: The peak-to-peak N1 showed that the N1 was much reduced for BB non-objects relative to all other images, while HSF and LSF non-objects still elicited as negative an N1 as objects.Different pathways are involved in the processing of low and high spatial frequencies during object recognition, as reflected in interactions between objecthood and spatial frequency in the visual N1 component.Total gamma band seems to be related to a late, probably high-level representational process.

View Article: PubMed Central - PubMed

Affiliation: Institute of Psychology, University of Leipzig, 04109, Leipzig, Germany. m.p.craddock@leeds.ac.uk.

ABSTRACT

Background: The visual system may process spatial frequency information in a low-to-high, coarse-to-fine sequence. In particular, low and high spatial frequency information may be processed via different pathways during object recognition, with LSF information projected rapidly to frontal areas and HSF processed later in visual ventral areas. In an electroencephalographic study, we examined the time course of information processing for images filtered to contain different ranges of spatial frequencies. Participants viewed either high spatial frequency (HSF), low spatial frequency (LSF), or unfiltered, broadband (BB) images of objects or non-object textures, classifying them as showing either man-made or natural objects, or non-objects. Event-related potentials (ERPs) and evoked and total gamma band activity (eGBA and tGBA) recorded using the electroencephalogram were compared for object and non-object images across the different spatial frequency ranges.

Results: The visual P1 showed independent modulations by object and spatial frequency, while for the N1 these factors interacted. The P1 showed more positive amplitudes for objects than non-objects, and more positive amplitudes for BB than for HSF images, which in turn evoked more positive amplitudes than LSF images. The peak-to-peak N1 showed that the N1 was much reduced for BB non-objects relative to all other images, while HSF and LSF non-objects still elicited as negative an N1 as objects. In contrast, eGBA was influenced by spatial frequency and not objecthood, while tGBA showed a stronger response to objects than non-objects.

Conclusions: Different pathways are involved in the processing of low and high spatial frequencies during object recognition, as reflected in interactions between objecthood and spatial frequency in the visual N1 component. Total gamma band seems to be related to a late, probably high-level representational process.

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Mean reaction times (ms) and errors (%). Error bars indicate bootstrapped 95% confidence intervals.
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Fig2: Mean reaction times (ms) and errors (%). Error bars indicate bootstrapped 95% confidence intervals.

Mentions: There was a significant interaction between Object and Frequency for RTs [F(2,28) = 40.72, p < .001, ƞ2g. = .03] and errors [F(2,28) = 44.90, p < .001, ƞ2g. = .34], see Figure 2. Post-hoc tests indicated that RTs were significantly slower when an object was present than when there was no object on LSF (p < .001) and HSF trials (p = .02), while there were no significant differences between objects and non-objects on BB trials (p = .2). Additionally, responses to objects on LSF trials were slower than responses to both BB and HSF non-objects (both ps < .001), while responses on HSF object trials were slower than responses on BB (p = .04) non-object trials. There were significantly more errors committed for LSF objects than in any other condition (all ps < .001). There were also significantly more errors for HSF objects than for BB (p = .002) and HSF (p = .005) non-objects. There were no significant differences in errors between BB objects and non-objects (p = .2) or HSF objects and non-objects (ps = .4). Errors did not significantly differ across frequency for any non-objects (ps > .4).Figure 2


Early and late effects of objecthood and spatial frequency on event-related potentials and gamma band activity.

Craddock M, Martinovic J, Müller MM - BMC Neurosci (2015)

Mean reaction times (ms) and errors (%). Error bars indicate bootstrapped 95% confidence intervals.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4352290&req=5

Fig2: Mean reaction times (ms) and errors (%). Error bars indicate bootstrapped 95% confidence intervals.
Mentions: There was a significant interaction between Object and Frequency for RTs [F(2,28) = 40.72, p < .001, ƞ2g. = .03] and errors [F(2,28) = 44.90, p < .001, ƞ2g. = .34], see Figure 2. Post-hoc tests indicated that RTs were significantly slower when an object was present than when there was no object on LSF (p < .001) and HSF trials (p = .02), while there were no significant differences between objects and non-objects on BB trials (p = .2). Additionally, responses to objects on LSF trials were slower than responses to both BB and HSF non-objects (both ps < .001), while responses on HSF object trials were slower than responses on BB (p = .04) non-object trials. There were significantly more errors committed for LSF objects than in any other condition (all ps < .001). There were also significantly more errors for HSF objects than for BB (p = .002) and HSF (p = .005) non-objects. There were no significant differences in errors between BB objects and non-objects (p = .2) or HSF objects and non-objects (ps = .4). Errors did not significantly differ across frequency for any non-objects (ps > .4).Figure 2

Bottom Line: The peak-to-peak N1 showed that the N1 was much reduced for BB non-objects relative to all other images, while HSF and LSF non-objects still elicited as negative an N1 as objects.Different pathways are involved in the processing of low and high spatial frequencies during object recognition, as reflected in interactions between objecthood and spatial frequency in the visual N1 component.Total gamma band seems to be related to a late, probably high-level representational process.

View Article: PubMed Central - PubMed

Affiliation: Institute of Psychology, University of Leipzig, 04109, Leipzig, Germany. m.p.craddock@leeds.ac.uk.

ABSTRACT

Background: The visual system may process spatial frequency information in a low-to-high, coarse-to-fine sequence. In particular, low and high spatial frequency information may be processed via different pathways during object recognition, with LSF information projected rapidly to frontal areas and HSF processed later in visual ventral areas. In an electroencephalographic study, we examined the time course of information processing for images filtered to contain different ranges of spatial frequencies. Participants viewed either high spatial frequency (HSF), low spatial frequency (LSF), or unfiltered, broadband (BB) images of objects or non-object textures, classifying them as showing either man-made or natural objects, or non-objects. Event-related potentials (ERPs) and evoked and total gamma band activity (eGBA and tGBA) recorded using the electroencephalogram were compared for object and non-object images across the different spatial frequency ranges.

Results: The visual P1 showed independent modulations by object and spatial frequency, while for the N1 these factors interacted. The P1 showed more positive amplitudes for objects than non-objects, and more positive amplitudes for BB than for HSF images, which in turn evoked more positive amplitudes than LSF images. The peak-to-peak N1 showed that the N1 was much reduced for BB non-objects relative to all other images, while HSF and LSF non-objects still elicited as negative an N1 as objects. In contrast, eGBA was influenced by spatial frequency and not objecthood, while tGBA showed a stronger response to objects than non-objects.

Conclusions: Different pathways are involved in the processing of low and high spatial frequencies during object recognition, as reflected in interactions between objecthood and spatial frequency in the visual N1 component. Total gamma band seems to be related to a late, probably high-level representational process.

Show MeSH