Electrophysiological correlates of texture segregation in the human visual evoked potential

Bach, Michael; Meigen, Thomas

doi:10.1016/0042-6989(92)90233-9

Cited by 103 publications

(78 citation statements)

References 13 publications

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“…When the frame and stack textures start to differentiate from the homogenous textures, the responses are consistent with earlier studies (Appelbaum et al, 2006;Caputo & Casco, 1999;Bach & Meigen, 1992;Lamme et al, 1992) and are always larger. A more complex pattern emerges when stack and frame textures start to differentiate from each other.…”

Section: Electroencephalographysupporting

confidence: 78%

“…MRI studies have indicated the involvement of areas V1, V2, V3, V4, and V3a (Schira et al, 2004;Altmann et al, 2003;Kastner et al, 2000;Reppas et al, 1997) in the differentiation between homogenous texture and figure textures. EEG studies indicate that occipital areas differentiate between homogenous texture and figure textures around 140-219 msec (Caputo & Casco, 1999;Bach & Meigen, 1992;Lamme, Vandijk, & Spekreijse, 1992). These studies found a greater negativity in occipital electrodes for figure textures compared to homogenous textures.…”

Section: Introductionmentioning

confidence: 79%

See 1 more Smart Citation

Feedforward and Recurrent Processing in Scene Segmentation: Electroencephalography and Functional Magnetic Resonance Imaging

Scholte

Jolij

Fahrenfort

et al. 2008

Journal of Cognitive Neuroscience

132

131

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In texture segregation, an example of scene segmentation, we can discern two different processes: texture boundary detection and subsequent surface segregation [Lamme, V. A. F., Rodriguez-Rodriguez, V., & Spekreijse, H. Separate processing dynamics for texture elements, boundaries and surfaces in primary visual cortex of the macaque monkey. Cerebral Cortex, 9, 406–413, 1999]. Neural correlates of texture boundary detection have been found in monkey V1 [Sillito, A. M., Grieve, K. L., Jones, H. E., Cudeiro, J., & Davis, J. Visual cortical mechanisms detecting focal orientation discontinuities. Nature, 378, 492–496, 1995; Grosof, D. H., Shapley, R. M., & Hawken, M. J. Macaque-V1 neurons can signal illusory contours. Nature, 365, 550–552, 1993], but whether surface segregation occurs in monkey V1 [Rossi, A. F., Desimone, R., & Ungerleider, L. G. Contextual modulation in primary visual cortex of macaques. Journal of Neuroscience, 21, 1698–1709, 2001; Lamme, V. A. F. The neurophysiology of figure ground segregation in primary visual-cortex. Journal of Neuroscience, 15, 1605–1615, 1995], and whether boundary detection or surface segregation signals can also be measured in human V1, is more controversial [Kastner, S., De Weerd, P., & Ungerleider, L. G. Texture segregation in the human visual cortex: A functional MRI study. Journal of Neurophysiology, 83, 2453–2457, 2000]. Here we present electroencephalography (EEG) and functional magnetic resonance imaging data that have been recorded with a paradigm that makes it possible to differentiate between boundary detection and scene segmentation in humans. In this way, we were able to show with EEG that neural correlates of texture boundary detection are first present in the early visual cortex around 92 msec and then spread toward the parietal and temporal lobes. Correlates of surface segregation first appear in temporal areas (around 112 msec) and from there appear to spread to parietal, and back to occipital areas. After 208 msec, correlates of surface segregation and boundary detection also appear in more frontal areas. Blood oxygenation level-dependent magnetic resonance imaging results show correlates of boundary detection and surface segregation in all early visual areas including V1. We conclude that texture boundaries are detected in a feedforward fashion and are represented at increasing latencies in higher visual areas. Surface segregation, on the other hand, is represented in “reverse hierarchical” fashion and seems to arise from feedback signals toward early visual areas such as V1.

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Section: Electroencephalographysupporting

confidence: 78%

Section: Introductionmentioning

confidence: 79%

Feedforward and Recurrent Processing in Scene Segmentation: Electroencephalography and Functional Magnetic Resonance Imaging

Scholte

Jolij

Fahrenfort

et al. 2008

Journal of Cognitive Neuroscience

132

131

View full text Add to dashboard Cite

show abstract

“…Prior work using transient VEPs to study the segmentation of textures into regions has indicated that a differentiation between uniform and segmented stimuli occurs as early as 90-115 ms (Bach and Meigen, 1992;Caputo et al, 1999;Lamme et al, 1992;Scholte et al, 2006Scholte et al, , 2008. Texture-segmentation-related activity localizes to V1 (Appelbaum et al, 2012;Lamme et al, 1992Lamme et al, , 1998.…”

Section: From Representation To Decisionmentioning

confidence: 99%

The time course of shape discrimination in the human brain

et al. 2013

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The lateral occipital cortex (LOC) activates selectively to images of intact objects versus scrambled controls, is selective for the figure-ground relationship of a scene, and exhibits at least some degree of invariance for size and position. Because of these attributes, it is considered to be a crucial part of the object recognition pathway. Here we show that human LOC is critically involved in perceptual decisions about object shape. High-density EEG was recorded while subjects performed a threshold-level shape discrimination task on texture-defined figures segmented by either phase or orientation cues. The appearance or disappearance of a figure region from a uniform background generated robust visual evoked potentials throughout retinotopic cortex as determined by inverse modeling of the scalp voltage distribution. Contrasting responses from trials containing shape changes that were correctly detected (hits) with trials in which no change occurred (correct rejects) revealed stimulus-locked, target-selective activity in the occipital visual areas LOC and V4 preceding the subject's response. Activity that was locked to the subjects' reaction time was present in the LOC. Response-locked activity in the LOC was determined to be related to shape discrimination for several reasons: shape-selective responses were silenced when subjects viewed identical stimuli but their attention was directed away from the shapes to a demanding letter discrimination task; shape-selectivity was present across four different stimulus configurations used to define the figure; LOC responses correlated with participants' reaction times. These results indicate that decision-related activity is present in the LOC when subjects are engaged in threshold-level shape discriminations.

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“…More often, studies focus on a specific ERP component during a variety of hypothesis driven task manipulations (e.g., Woodman & Luck, 2003a; 2003b). New ERP components are still being discovered (e.g., Bach & Meigen, 1992; Klaver, Talsma, Wijers, Heinze, & Mulders, 1999; Luck & Hillyard, 1994b) and the significance of existing ERP components reinterpreted (e.g., Vogel & Luck, 2000). However, many papers are submitted which tout the discovery of a new ERP component or novel modulation, but do not actually report something new.…”

Section: Fundamentals Of Rigorous Erp Studiesmentioning

confidence: 99%

A brief introduction to the use of event-related potentials in studies of perception and attention

Woodman

2010

Attention, Perception & Psychophysics

256

205

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Due to the precise temporal resolution of electrophysiological recordings, the event-related potential (ERP) technique has proven particularly valuable for testing theories of perception and attention. Here, I provide a brief tutorial of the ERP technique for consumers of such research and those considering the use of human electrophysiology in their own work. My discussion begins with the basics regarding what brain activity ERPs measure and why they are well suited to reveal critical aspects of perceptual processing, attentional selection, and cognition that are unobservable with behavioral methods alone. I then review a number of important methodological issues and often forgotten facts that should be considered when evaluating or planning ERP experiments.

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Electrophysiological correlates of texture segregation in the human visual evoked potential

Cited by 103 publications

References 13 publications

Feedforward and Recurrent Processing in Scene Segmentation: Electroencephalography and Functional Magnetic Resonance Imaging

Feedforward and Recurrent Processing in Scene Segmentation: Electroencephalography and Functional Magnetic Resonance Imaging

The time course of shape discrimination in the human brain

A brief introduction to the use of event-related potentials in studies of perception and attention

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