The Relative Contribution of High-Level (Semantic) and Low-Level (Boundary) Information to Object-Based Attentional Guidance

2019 ◽  
Author(s):  
Paul S. Scotti ◽  
Andrew Collegio ◽  
Sarah Shomstein
Keyword(s):  
Semantic Category ◽  
Object Representations ◽  
Attentional Allocation ◽  
Attentional Guidance ◽  
Low Level ◽  
Relative Contribution ◽  
Object Based ◽  
Level Information ◽  
High Level ◽  
Semantic Identity

Attentional selection is constrained by object representations (object-based attention) that consist of low-level (e.g., boundaries signaled by closure) and high-level (e.g., semantic category) properties. Whereas low-level information has repeatedly been shown to constrain object-based attention with the use of simple geometric figures, high-level information (such as meaning) has only recently been shown to be an important factor in object-based guidance of attention. Here, we characterize the relative contributions of object boundaries (low-level) and object semantic identity (high-level) to attentional allocation by systematically reducing the contribution from both levels of description. We directly measure the degree to which attentional allocation is flexibly influenced by a combination of these factors. Object-based attentional guidance was observed only when either boundaries or semantic category was preserved, with a larger contribution for preserved semantic category. When both boundary and semantic category were disturbed, object-based influence was reduced. Object-based attentional guidance was therefore more reliant on high-level than low-level properties, suggesting that object-based attention efficiently guides behavior even in naturalistic conditions with real-world objects and environmental fluctuations (e.g., dim lighting, fog, blurry vision).

B-Spline based globally optimal segmentation combining low-level and high-level information

2018 ◽  
Vol 73 ◽  
pp. 144-157 ◽  
Author(s):  
Shenhai Zheng ◽  
Bin Fang ◽  
Laquan Li ◽  
Mingqi Gao ◽  
Rui Chen ◽  
...  
Keyword(s):  
B Spline ◽  
Low Level ◽  
Level Information ◽  
Optimal Segmentation ◽  
High Level

scholarly journals Spatial variations in the socioeconomic development of rural municipalities in the podkarpackie voivodeship

2021 ◽  
Vol 20 (2) ◽  
Author(s):  
Katarzyna Pawlewicz ◽  
Justyna Flasińska
Keyword(s):  
Socioeconomic Development ◽  
Environmental Issues ◽  
Development Pattern ◽  
Class Iii ◽  
Low Level ◽  
Multidimensional Modeling ◽  
Object Based ◽  
Rural Municipalities ◽  
High Level ◽  
Different Levels

The main goal of all territorial administration units, including municipalities, is to promote socioeconomic development. The implemented actions address a broad range of economic, social, spatial and environmental issues. Therefore, socioeconomic development is a complex and multi-dimensional concept that is difficult to evaluate in an unambiguous and objective manner. Statistical methods in object-based multidimensional modeling support such evaluations by considering numerous attributes/variables, which increases the efficiency of the analytical process. In this article, Hellwig’s development pattern method was applied to classify rural municipalities in Podkarpackie Voivodeship based on their socioeconomic development. Twenty-seven indicators were designed for the needs of the analysis with the use of Statistics Poland data for 2018. Based on the results, the municipalities were grouped into four classes with different levels of socioeconomic development. Class III was the largest group, and it was composed of 39 municipalities with a medium-low level of socioeconomic development. Class II was composed of a similar number of municipalities (38) with a medium-high level of socioeconomic development. The smallest groups were Class I containing 18 municipalities with a high level of socioeconomic development, and class IV containing 14 municipalities with a low level of development.

Does more accessibility lead to more disclosure? Exploring the influence of information accessibility on self-disclosure in online social networks

2019 ◽  
Vol 32 (3) ◽  
pp. 754-780 ◽  
Author(s):  
Shanshan Zhang ◽  
Ron Chi-Wai Kwok ◽  
Paul Benjamin Lowry ◽  
Zhiying Liu
Keyword(s):  
Social Capital ◽  
Social Exchange ◽  
Self Disclosure ◽  
Content Type ◽  
Low Level ◽  
Information Accessibility ◽  
Different Types ◽  
Level Information ◽  
High Level ◽  
Privacy Risks

Purpose Given the importance of online social network (OSN) media features, many studies have focused on how different types of OSNs with various media features influence users’ usage and engagement. However, a recent literature review indicates that few empirical studies have considered how different types of OSNs with different information accessibility levels influence users’ beliefs and self-disclosure. By comparing two OSN platforms (OSNs with high-level information accessibility vs OSNs with low-level information accessibility), the purpose of this paper is to address this opportunity by investigating the differential impacts of the two platforms on individuals’ psychological cognition – particularly users’ social exchange beliefs – and explaining how these beliefs translate into OSN self-disclosure. Design/methodology/approach This study used a factorial design approach in an experimental setting to examine how different levels of information accessibility (high vs low), influence the social exchange beliefs (i.e. perceived social capital bridging, perceived social capital bonding and perceived privacy risks) of OSN users and subsequently influence OSN self-disclosure. Findings The results show that users on OSNs with high-level information accessibility express significantly higher perceived social capital bridging and perceived privacy risks than users on OSNs with low-level information accessibility. However, users on OSNs with low-level information accessibility express higher social bonding beliefs than users on OSNs with high-level information accessibility, indicating that there are different effect mechanisms toward OSN self-disclosure. Originality/value The focus of this research helps unveil the complex relationships between OSN design features (e.g. information accessibility), psychological cognition (e.g. social capital bridging, social capital bonding and privacy risks) and OSN self-disclosure. First, it clarifies the relationship between information accessibility and self-disclosure by examining the mediating effect of three core social exchange beliefs. Second, it uncovers the distinct effects of high-level information-accessible OSNs and low-level information-accessible OSNs on OSN self-disclosure.

scholarly journals The high-level basis of body adaptation

2018 ◽  
Vol 5 (6) ◽  
pp. 172103 ◽  
Author(s):  
Kevin R. Brooks ◽  
Colin W. G. Clifford ◽  
Richard J. Stevenson ◽  
Jonathan Mond ◽  
Ian D. Stephen
Keyword(s):  
The Body ◽  
Minor Role ◽  
Low Level ◽  
Visual Exposure ◽  
Object Based ◽  
High Level ◽  
A Minor

Prolonged visual exposure, or ‘adaptation’, to thin (wide) bodies causes a perceptual aftereffect such that subsequently seen bodies appear wider (thinner) than they actually are. Here, we conducted two experiments investigating the effect of rotating the orientation of the test stimuli by 90° from that of the adaptor. Aftereffects were maximal when adapting and test bodies had the same orientation. When they differed, the axis of the perceived distortion changed with the orientation of the body. Experiment 1 demonstrated a 58% transfer of the aftereffect across orientations. Experiment 2 demonstrated an even greater degree of aftereffect transfer when the influence of low-level mechanisms was reduced further by using adaptation and test stimuli with different sizes. These results indicate that the body aftereffect is mediated primarily by high-level object-based processes, with low-level retinotopic mechanisms playing only a minor role. The influence of these low-level processes is further reduced when test stimuli differ in size from adaptation stimuli.

scholarly journals Experience-dependent reshaping of body gender perception

2021 ◽  
Author(s):  
Giulia D’Argenio ◽  
Alessandra Finisguerra ◽  
Cosimo Urgesi
Keyword(s):  
Individual Characteristics ◽  
Social Deficits ◽  
Male Body ◽  
Relative Contribution ◽  
Gender Perception ◽  
Object Based ◽  
Male Gender Role ◽  
The Individual ◽  
High Level ◽  
Biased Perception

AbstractProtracted exposure to specific stimuli causes biased visual aftereffects at both low- and high-level dimensions of a stimulus. Recently, it has been proposed that alterations of these aftereffects could play a role in body misperceptions. However, since previous studies have mainly addressed manipulations of body size, the relative contribution of low-level retinotopic and/or high-level object-based mechanisms is yet to be understood. In three experiments, we investigated visual aftereffects for body-gender perception, testing for the tuning of visual aftereffects across different characters and orientation. We found that exposure to a distinctively female (or male) body makes androgynous bodies appear as more masculine (or feminine) and that these aftereffects were not specific for the individual characteristics of the adapting body (Exp.1). Furthermore, exposure to only upright bodies (Exp.2) biased the perception of upright, but not of inverted bodies, while exposure to both upright and inverted bodies (Exp.3) biased perception for both. Finally, participants’ sensitivity to body aftereffects was lower in individuals with greater communication deficits and deeper internalization of a male gender role. Overall, our data reveals the orientation-, but not identity-tuning of body-gender aftereffects and points to the association between alterations of the malleability of body gender perception and social deficits.

scholarly journals The temporal evolution of conceptual object representations revealed through models of behavior, semantics and deep neural networks

2017 ◽  
Author(s):  
B. B. Bankson ◽  
M.N. Hebart ◽  
I.I.A. Groen ◽  
C.I. Baker
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Stimulus Onset ◽  
Visual Object ◽  
Object Representations ◽  
Object Processing ◽  
Low Level ◽  
Conceptual Representations ◽  
Brain Responses ◽  
High Level

AbstractVisual object representations are commonly thought to emerge rapidly, yet it has remained unclear to what extent early brain responses reflect purely low-level visual features of these objects and how strongly those features contribute to later categorical or conceptual representations. Here, we aimed to estimate a lower temporal bound for the emergence of conceptual representations by defining two criteria that characterize such representations: 1) conceptual object representations should generalize across different exemplars of the same object, and 2) these representations should reflect high-level behavioral judgments. To test these criteria, we compared magnetoencephalography (MEG) recordings between two groups of participants (n = 16 per group) exposed to different exemplar images of the same object concepts. Further, we disentangled low-level from high-level MEG responses by estimating the unique and shared contribution of models of behavioral judgments, semantics, and different layers of deep neural networks of visual object processing. We find that 1) both generalization across exemplars as well as generalization of object-related signals across time increase after 150 ms, peaking around 230 ms; 2) behavioral judgments explain the most unique variance in the response after 150 ms. Collectively, these results suggest a lower bound for the emergence of conceptual object representations around 150 ms following stimulus onset.

scholarly journals Automated Nuclei Segmentation of Breast Cancer Histopathology

2013 ◽  
pp. 168-172
Author(s):  
Vipin Bondre ◽  
Amoli Belsare
Keyword(s):  
Breast Cancer ◽  
Bayesian Classifier ◽  
Segmentation Algorithm ◽  
Specific Information ◽  
Structural Constraints ◽  
Cell Nuclei ◽  
Low Level ◽  
Domain Specific ◽  
Level Information ◽  
High Level

Automated detection and segmentation of cell nuclei is an essential step in breast cancer histopathology, so that there is improved accuracy, speed, level of automation and adaptability to new application. The goal of this paper is to develop efficient and accurate algorithms for detecting and segmenting cell nuclei in 2-D histological images. In this paper we will implement the utility of our nuclear segmentation algorithm in accurate extraction of nuclear features for automated grading of (a) breast cancer, and (b) distinguishing between cancerous and benign breast histology specimens. In order to address the issue the scheme integrates image information across three different scales: (1) low level information based on pixel values, (2) high-level information based on relationships between pixels for object detection, and(3)domain-specific information based on relationships between histological structures. Low-level information is utilized by a Bayesian Classifier to generate likelihood that each pixel belongs to an object of interest. High-level information is extracted in two ways: (i) by a level-set algorithm, where a contour is evolved in the likelihood scenes generated by the Bayesian classifier to identify object boundaries, and (ii) by a template matching algorithm, where shape models are used to identify glands and nuclei from the low-level likelihood scenes. Structural constraints are imposed via domain specific knowledge in order to verify whether the detected objects do indeed belong to structures of interest. The efficiency of our segmentation algorithm is evaluated by comparing breast cancer grading and benign vs. cancer discrimination accuracies with corresponding accuracies obtained via manual detection and segmentation of glands and nuclei.

scholarly journals Multisensory Part-based Representations of Objects in Human Lateral Occipital Cortex

2016 ◽  
Vol 28 (6) ◽  
pp. 869-881 ◽  
Author(s):  
Goker Erdogan ◽  
Quanjing Chen ◽  
Frank E. Garcea ◽  
Bradford Z. Mahon ◽  
Robert A. Jacobs
Keyword(s):  
Occipital Cortex ◽  
Component Part ◽  
Object Representations ◽  
Linear Classifiers ◽  
Neural Data ◽  
Haptic Exploration ◽  
Object Based ◽  
Part Structure ◽  
High Level ◽  
Lateral Occipital Cortex

The format of high-level object representations in temporal-occipital cortex is a fundamental and as yet unresolved issue. Here we use fMRI to show that human lateral occipital cortex (LOC) encodes novel 3-D objects in a multisensory and part-based format. We show that visual and haptic exploration of objects leads to similar patterns of neural activity in human LOC and that the shared variance between visually and haptically induced patterns of BOLD contrast in LOC reflects the part structure of the objects. We also show that linear classifiers trained on neural data from LOC on a subset of the objects successfully predict a novel object based on its component part structure. These data demonstrate a multisensory code for object representations in LOC that specifies the part structure of objects.

scholarly journals Low-Level Information and High-Level Perception: The Case of Speech in Noise

PLoS Biology ◽  
2008 ◽  
Vol 6 (5) ◽  
pp. e126 ◽  
Author(s):  
Mor Nahum ◽  
Israel Nelken ◽  
Merav Ahissar
Keyword(s):  
Low Level ◽  
Speech In Noise ◽  
Level Information ◽  
High Level
Sign in / Sign up

Export Citation Format

Share Document