Linking appearance to neural activity through the study of the perception of lightness in naturalistic contexts

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The present paper deals with the classical question how a psychological experience, in this case apparent lightness, is linked by intervening neural processing to physical variables. We address two methodological issues: (a) how does one know the appropriate physical variable (what is the right x ?) to look at, and (b) how can behavioral measurements be used to probe the internal transformation that leads to psychological experience. We measured so-called lightness transfer functions (LTFs), that is the functions that describe the mapping between retinal luminance and perceived lightness for naturalistic checkerboard stimuli. The LTFs were measured for different illumination situations: plain view, a cast shadow, and an intervening transparent medium. Observers adjusted the luminance of a comparison patch such that it had the same lightness as each of the test patches. When the data were plotted in luminance–luminance space, we found qualitative differences between mapping functions in different contexts. These differences were greatly diminished when the data were plotted in terms of contrast. On contrast–contrast coordinates, the data were compatible with a single linear generative model. This result is an indication that, for the naturalistic scenes used here, lightness perception depends mostly on local contrast. We further discuss that, in addition to the mean adjustments, one may fi nd it useful to consider also the variability of an observer’s adjustments in order to infer the true luminance-to-lightness mapping function.DFG, MA5127/1-1, Die Bestimmung der Beziehung zwischen subjektiver Empfindung und Diskriminationsvermögen durch eine Kombination aus Psychophysik, Computationaler Modellierung und der Messung neuronaler Antworte

Retinotopic Activation in Response to Subjective Contours in Primary Visual Cortex

Objects in our visual environment are arranged in depth and hence there is a considerable amount of overlap and occlusion in the image they generate on the retina. In order to properly segment the image into figure and background, boundary interpolation is required even across large distances. Here we study the cortical mechanisms involved in collinear contour interpolation using fMRI. Human observers were asked to discriminate the curvature of interpolated boundaries in Kanizsa figures and in control configurations, which contained identical physical information but did not generated subjective shapes. We measured a spatially precise spin-echo BOLD signal and found stronger responses to subjective shapes than non-shapes at the subjective boundary locations, but not at the inducer locations. The responses to subjective contours within primary visual cortex were retinotopically specific and analogous to that to real contours, which is intriguing given that subjective and luminance-defined contours are physically fundamentally different. We suggest that in the absence of retinal stimulation, the observed activation changes in primary visual cortex are driven by intracortical interactions and feedback, which are revealed in the absence of a physical stimulus

Exploitation of environmental constraints in human and robotic grasping

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.We investigate the premise that robust grasping performance is enabled by exploiting constraints present in the environment. These constraints, leveraged through motion in contact, counteract uncertainty in state variables relevant to grasp success. Given this premise, grasping becomes a process of successive exploitation of environmental constraints, until a successful grasp has been established. We present support for this view found through the analysis of human grasp behavior and by showing robust robotic grasping based on constraint-exploiting grasp strategies. Furthermore, we show that it is possible to design robotic hands with inherent capabilities for the exploitation of environmental constraints

Exploitation of environmental constraints in human and robotic grasping

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.We investigate the premise that robust grasping performance is enabled by exploiting constraints present in the environment. These constraints, leveraged through motion in contact, counteract uncertainty in state variables relevant to grasp success. Given this premise, grasping becomes a process of successive exploitation of environmental constraints, until a successful grasp has been established. We present support for this view found through the analysis of human grasp behavior and by showing robust robotic grasping based on constraint-exploiting grasp strategies. Furthermore, we show that it is possible to design robotic hands with inherent capabilities for the exploitation of environmental constraints

Maximum likelihood difference scales represent perceptual magnitudes and predict appearance matches

One central problem in perception research is to understand how internal experiences are linked to physical variables. Most commonly, this relationship is measured using the method of adjustment, but this has two shortcomings: The perceptual scales that relate physical and perceptual variables are not measured directly, and the method often requires perceptual comparisons between viewing conditions. To overcome these problems, we measured perceptual scales of surface lightness using maximum likelihood difference scaling, asking observers only to compare the lightness of surfaces presented in the same context. Observers were lightness constant, and the perceptual scales qualitatively and quantitatively predicted perceptual matches obtained in a conventional adjustment experiment. Additionally, we show that a contrast-based model of lightness perception predicted 98% of the variance in the scaling and 88% in the matching data. We suggest that the predictive power was higher for scales because they are closer to the true variables of interest.DFG, 188583648, Die Bestimmung der Beziehung zwischen subjektiver Empfindung und Diskriminationsvermögen durch eine Kombination aus Psychophysik, Computationaler Modellierung und der Messung neuronaler AntwortenDFG, 103586207, GRK 1589: Verarbeitung sensorischer Informationen in neuronalen Systeme

Comparing sensitivity estimates from MLDS and forced-choice methods in a slant-from-texture experiment

Maximum likelihood difference scaling (MLDS) is a method for the estimation of perceptual scales based on the judgment of differences in stimulus appearance (Maloney & Yang, 2003). MLDS has recently also been used to estimate near-threshold discrimination performance (Devinck & Knoblauch, 2012). Using MLDS as a psychophysical method for sensitivity estimation is potentially appealing, because MLDS has been reported to need less data than forced-choice procedures, and particularly naive observers report to prefer suprathreshold comparisons to JND-style threshold tasks. Here we compare two methods, MLDS and two-interval forced-choice (2-IFC), regarding their capability to estimate sensitivity assuming an underlying signal-detection model. We first examined the theoretical equivalence between both methods using simulations. We found that they disagreed in their estimation only when sensitivity was low, or when one of the assumptions on which MLDS is based was violated. Furthermore, we found that the confidence intervals derived from MLDS had a low coverage; i.e., they were too narrow, underestimating the true variability. Subsequently we compared MLDS and 2-IFC empirically using a slant-from-texture task. The amount of agreement between sensitivity estimates from the two methods varied substantially across observers. We discuss possible reasons for the observed disagreements, most notably violations of the MLDS model assumptions. We conclude that in the present example MLDS and 2-IFC could equally be used to estimate sensitivity to differences in slant, with MLDS having the benefit of being more efficient and more pleasant, but having the disadvantage of unsatisfying coverage.DFG, 188583648, Die Bestimmung der Beziehung zwischen subjektiver Empfindung und Diskriminationsvermögen durch eine Kombination aus Psychophysik, Computationaler Modellierung und der Messung neuronaler AntwortenDFG, 103586207, GRK 1589: Verarbeitung sensorischer Informationen in neuronalen Systeme