377 research outputs found
Subthreshold features of visual objects: Unseen but not unbound
AbstractThe object is a basic unit that is thought to organize the way in which we perceive and think about the world. According to theories of object-based attention, perception of unified objects depends on the binding together of the disparate features of each object via attention. Here we show that a visual feature that is not consciously perceived is nonetheless modulated by object-based attention: the influence of a subthreshold motion signal (prime) on subsequent motion perception depended critically on whether it was associated with the attended object or another, spatially overlapping object. These results show that invisibly weak features of attended objects are not lost, but are organized by and selected together with the object by attention
Dissociation between spatial and temporal integration mechanisms in Vernier fusion
AbstractThe visual system constructs a percept of the world across multiple spatial and temporal scales. This raises the questions of whether different scales involve separate integration mechanisms and whether spatial and temporal factors are linked via spatio-temporal reference frames. We investigated this using Vernier fusion, a phenomenon in which the features of two Vernier stimuli presented in close spatio-temporal proximity are fused into a single percept. With increasing spatial offset, perception changes dramatically from a single percept into apparent motion and later, at larger offsets, into two separately perceived stimuli. We tested the link between spatial and temporal integration by presenting two successive Vernier stimuli presented at varying spatial and temporal offsets. The second Vernier either had the same or the opposite offset as the first. We found that the type of percept depended not only on spatial offset, as reported previously, but interacted with the temporal parameter as well. At temporal separations around 30–40ms the majority of trials were perceived as motion, while above 70ms predominantly two separate stimuli were reported. The dominance of the second Vernier varied systematically with temporal offset, peaking around 40ms ISI. Same-offset conditions showed increasing amounts of perceived separation at large ISIs, but little dependence on spatial offset. As subjects did not always completely fuse stimuli, we separated trials by reported percept (single/fusion, motion, double/segregation). We found systematic indications of spatial fusion even on trials in which subjects perceived temporal segregation. These findings imply that spatial integration/fusion may occur even when the stimuli are perceived as temporally separate entities, suggesting that the mechanisms responsible for temporal segregation and spatial integration may not be mutually exclusive
Model updating of a wind turbine blade finite element Timoshenko beam model with invertible neural networks
Digitalization, especially in the form of a digital twin, is fast becoming a key instrument for the monitoring of a product's life cycle from manufacturing to operation and maintenance and has recently been applied to wind turbine blades. Here, model updating plays an important role for digital twins, in the form of adjusting the model to best replicate the corresponding real-world counterpart. However, classical updating methods are generally limited to a reduced parameter space due to low computational efficiency. Moreover, these approaches most likely lack a probabilistic evaluation of the result. The purpose of this paper is to extend a previous feasibility study to a finite element Timoshenko beam model of a full blade for which the model updating process is conducted through the novel approach with invertible neural networks (INNs). This type of artificial neural network is trained to represent an inversion of the physical model, which in general is complex and non-linear. During the updating process, the inverse model is evaluated based on the target model's modal responses. It then returns the posterior prediction for the input parameters. In advance, a global sensitivity study will reduce the parameter space to a significant subset on which the updating process will focus. The finally trained INN excellently predicts the input parameters' posterior distributions of the proposed generic updating problem. Moreover, intrinsic model ambiguities, such as material densities of two closely located laminates, are correctly captured. A robustness analysis with noisy response reveals a few sensitive parameters, though most can still be recovered with equal accuracy. And, finally, after the resimulation analysis with the updated model, the modal response perfectly matches the target values. Thus, we successfully confirmed that INNs offer an extraordinary capability for structural model updating of even more complex and larger models of wind turbine blades
Intermodulation electrostatic force microscopy for imaging surface photo-voltage
We demonstrate an alternative to Kelvin Probe Force Microscopy for imaging
surface potential. The open-loop, single-pass technique applies a low-frequency
AC voltage to the atomic force microscopy tip while driving the cantilever near
its resonance frequency. Frequency mixing due to the nonlinear capacitance
gives intermodulation products of the two drive frequencies near the cantilever
resonance, where they are measured with high signal to noise ratio. Analysis of
this intermodulation response allows for quantitative reconstruction of the
contact potential difference. We derive the theory of the method, validate it
with numerical simulation and a control experiment, and we demonstrate its
utility for fast imaging of the surface photo-voltage on an organic
photo-voltaic material.Comment: 4 pages, 3 figures, peer-reviewed, preprin
Implicit Attentional Selection of Bound Visual Features
SummaryTraditionally, research on visual attention has been focused on the processes involved in conscious, explicit selection of task-relevant sensory input. Recently, however, it has been shown that attending to a specific feature of an object automatically increases neural sensitivity to this feature throughout the visual field. Here we show that directing attention to a specific color of an object results in attentional modulation of the processing of task-irrelevant and not consciously perceived motion signals that are spatiotemporally associated with this color throughout the visual field. Such implicit cross-feature spreading of attention takes place according to the veridical physical associations between the color and motion signals, even under special circumstances when they are perceptually misbound. These results imply that the units of implicit attentional selection are spatiotemporally colocalized feature clusters that are automatically bound throughout the visual field
Perceptual averaging in individuals with autism spectrum disorder
Copyright © 2016 Corbett, Venuti and Melcher. There is mounting evidence that observers rely on statistical summaries of visual information to maintain stable and coherent perception. Sensitivity to the mean (or other prototypical value) of a visual feature (e.g., mean size) appears to be a pervasive process in human visual perception. Previous studies in individuals diagnosed with Autism Spectrum Disorder (ASD) have uncovered characteristic patterns of visual processing that suggest they may rely more on enhanced local representations of individual objects instead of computing such perceptual averages. To further explore the fundamental nature of abstract statistical representation in visual perception, we investigated perceptual averaging of mean size in a group of 12 high-functioning individuals diagnosed with ASD using simplified versions of two identification and adaptation tasks that elicited characteristic perceptual averaging effects in a control group of neurotypical participants. In Experiment 1, participants performed with above chance accuracy in recalling the mean size of a set of circles (mean task) despite poor accuracy in recalling individual circle sizes (member task). In Experiment 2, their judgments of single circle size were biased by mean size adaptation. Overall, these results suggest that individuals with ASD perceptually average information about sets of objects in the surrounding environment. Our results underscore the fundamental nature of perceptual averaging in vision, and further our understanding of how autistic individuals make sense of the external environment.This research was supported by the Autonomous Province of Trento through the call “Grandi Progetti 2012”, project “Characterizing and improving brain mechanisms of attention – ATTEND”, and the Fondazione Cassa di Risparmio di Trento e Rovereto
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Global statistical regularities modulate the speed of visual search in patients with focal attentional deficits
There is growing evidence that the statistical properties of ensembles of similar objects are processed in a qualitatively different manner than the characteristics of individual items. It has recently been proposed that these types of perceptual statistical representations are part of a strategy to complement focused attention in order to circumvent the visual system’s limited capacity to represent more than a few individual objects in detail. Previous studies have demonstrated that patients with attentional deficits are nonetheless sensitive to these sorts of statistical representations. Here, we examined how such global representations may function to aid patients in overcoming focal attentional limitations by manipulating the statistical regularity of a visual scene while patients performed a search task. Three patients previously diagnosed with visual neglect searched for a target Gabor tilted to the left or right of vertical in displays of horizontal distractor Gabors. Although the local sizes of the distractors changed on every trial, the mean size remained stable for several trials. Patients made faster correct responses to targets in neglected regions of the visual field when global statistics remained constant over several trials, similar to age-matched controls. Given neglect patients’ attentional deficits, these results suggest that stable perceptual representations of global statistics can establish a context to speed search without the need to represent individual elements in detail
Intercepting the First Pass: Rapid Categorization is Suppressed for Unseen Stimuli
The operations and processes that the human brain employs to achieve fast visual categorization remain a matter of debate. A first issue concerns the timing and place of rapid visual categorization and to what extent it can be performed with an early feed-forward pass of information through the visual system. A second issue involves the categorization of stimuli that do not reach visual awareness. There is disagreement over the degree to which these stimuli activate the same early mechanisms as stimuli that are consciously perceived. We employed continuous flash suppression (CFS), EEG recordings, and machine learning techniques to study visual categorization of seen and unseen stimuli. Our classifiers were able to predict from the EEG recordings the category of stimuli on seen trials but not on unseen trials. Rapid categorization of conscious images could be detected around 100 ms on the occipital electrodes, consistent with a fast, feed-forward mechanism of target detection. For the invisible stimuli, however, CFS eliminated all traces of early processing. Our results support the idea of a fast mechanism of categorization and suggest that this early categorization process plays an important role in later, more subtle categorizations, and perceptual processes
Predictions as a window into learning: Anticipatory fixation offsets carry more information about environmental statistics than reactive stimulus-responses
published February 19, 2019A core question underlying neurobiological and computational models of behavior is how individuals learn environmental statistics and use them to make predictions. Most investigations of this issue have relied on reactive paradigms, in which inferences about predictive processes are derived by modeling responses to stimuli that vary in likelihood. Here we deployed a novel anticipatory oculomotor metric to determine how input statistics impact anticipatory behavior that is decoupled from target-driven-response. We implemented transition constraints between target locations, so that the probability of a target being presented on the same side as the previous trial was 70% in one condition (pret70) and 30% in the other (pret30). Rather than focus on responses to targets, we studied subtle endogenous anticipatory fixation offsets (AFOs) measured while participants fixated the screen center, awaiting a target. These AFOs were small (<0.4° from center on average), but strongly tracked global-level statistics. Speaking to learning dynamics, trial-by-trial fluctuations in AFO were well-described by a learning model, which identified a lower learning rate in pret70 than pret30, corroborating prior suggestions that pret70 is subjectively treated as more regular. Most importantly, direct comparisons with saccade latencies revealed that AFOs: (a) reflected similar temporal integration windows, (b) carried more information about the statistical context than did saccade latencies, and (c) accounted for most of the information that saccade latencies also contained about inputs statistics. Our work demonstrates how strictly predictive processes reflect learning dynamics, and presents a new direction for studying learning and prediction.We thank Leonardo Chelazzi for his comments. UH's work was conducted in part while serving at and with support of the National Science Foundation. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the NSF. The study was partially funded by a European Research Council grant to UH (ERC-STG 263318)
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