Electrophysiological correlates of target eccentricity in texture segmentation - Meinecke Berndts, Cristina; Schaffer, Susann; Scubö, Anna (International Journal of Psychophysiology, 2011)
Event-related potentials and behavioural performance as a function of target eccentricity were measured while subjects performed a texture segmentation task. Fit-of-structures, i.e. easiness of target detection was varied: in Experiment 1, a texture with peripheral fit (easier detection of peripheral presented targets) and in Experiment 2, a texture with foveal fit (easier detection of foveal presented targets) was used. In the two experiments, the N2p was sensitive to target eccentricity showing larger amplitudes for foveal targets compared to peripheral targets, and at the foveal position, a reversal of the N2p differential amplitude effect was found. The anterior P2 seemed sensitive to the easiness of target detection. In both experiments the N2pc varied as a function of eccentricity. However, the P3 was neither sensitive to target eccentricity nor to the fit-of-structures. Results show the existence of a P2/N2 complex (Potts and Tucker, 2001) indicating executive functions located in the anterior cortex and perceptual processes located in the posterior cortex. Furthermore, the N2p might indicate the existence of a foveal vs. peripheral subsystem in visual processin
Keywords: Early vision Texture segmentation Retinal eccentricity ERP

Spatial competition on the master-saliency map - Schade, Ursula; Meinecke Berndts, Cristina (Frontiers in Psychology, 2013)
The saliency map model (Itti and Koch, 2000) is a hierarchically structured computational model, simulating visual saliency processing. Iso-feature processing on feature maps and conspicuity maps precedes cross-dimensional signal processing on the master map, where the most salient location of the visual field is selected. This texture segmentation study focuses on a possible spatial structure on the master map. In four experiments the spatial distance between a texture irregularity in the stimulus ("target") and a cross-dimensional task irrelevant texture irregularity in the backward mask ("patch") was varied. The results show that the target-patch distance modulates target detection, and that this modulation is limited to critical distances around the target. We conclude that the signals from different feature dimensions compete on a spatial master map. There is first evidence that the critical distances increase with target eccentricity. © 2013 Schade and Meinecke.
Keywords: Critical distance; Early vision; Master map; Non-classical receptive fields; Retinal eccentricity; Saliency map; Texture segmentation

Spatial distance between target and irrelevant patch modulates detection in a texture segmentation task - Meinecke Berndts, Cristina; Schade, Ursula (Spatial vision, 2009)

Texture segmentation: Do the processing units on the saliency map increase with eccentricity? - Schade, Ursula; Meinecke Berndts, Cristina (Vision research, 2011)
The saliency map is a computational model and has been constructed for simulating human saliency processing, e.g. pop-out target detection (e.g. Itti & Koch, 2000). In this study the spatial structure on the saliency map was investigated. It is proposed that the saliency map is structured into processing units whose size is increasing with retinal eccentricity. In two experiments the distance between a target in the stimulus and an irrelevant structure in the mask was varied systematically. Our findings had two main points. Firstly, in texture segmentation tasks the saliency signals from two texture irregularities interfere, when these irregularities appear within a critical spatial distance. Second, the critical distances increase with target eccentricity. The eccentricity-dependent critical distances can be interpreted as crowding effects. It is assumed that additionally to the target eccentricity, also the strength of a saliency signal can determine the spatial area of its impairing influence. © 2010 Elsevier Ltd.
Keywords: Critical distance; Crowding; Detection; Early vision; Eccentricity; Saliency map; Texture segmentation