scholarly journals Continuous Flash Suppression Known and Unknowns

2019 ◽  
Author(s):  
Ali Pournaghdali ◽  
Bennett L Schwartz

Studies utilizing continuous flash suppression (CFS) provide valuable information regarding conscious and nonconscious perception. There are, however, crucial unanswered questions regarding the mechanisms of suppression and the level of visual processing in the absence of consciousness with CFS. Research suggests that the answers to these questions depend on the experimental configuration and how we assess consciousness in these studies. The aim of this review is to evaluate the impact of different experimental configurations and the assessment of consciousness on the results of the previous CFS studies. We review studies that evaluated the influence of different experimental configuration on the depth of suppression with CFS and discuss how different assessments of consciousness may impact the results of CFS studies. Finally, we review behavioral and brain recording studies of CFS. In conclusion, previous studies provide evidence for survival of low-level visual information and complete impairment of high-level visual information under the influence of CFS. That is, studies suggest that nonconscious perception of lower-level visual information happens with CFS but there is no evidence for nonconscious highlevel recognition with CFS.

2017 ◽  
Author(s):  
D. Pascucci ◽  
G. Mancuso ◽  
E. Santandrea ◽  
C. Della Libera ◽  
G. Plomp ◽  
...  

AbstractEvery instant of perception depends on a cascade of brain processes calibrated to the history of sensory and decisional events. In the present work, we show that human visual perception is constantly shaped by two contrasting forces, exerted by sensory adaptation and past decisions. In a series of experiments, we used multilevel modelling and cross-validation approaches to investigate the impact of previous stimuli and responses on current errors in adjustment tasks. Our results revealed that each perceptual report is permeated by opposite biases from a hierarchy of serially dependent processes: low-level adaptation repels perception away from previous stimuli; high-level, decisional traces attract perceptual reports toward previous responses. Contrary to recent claims, we demonstrated that positive serial dependence does not result from continuity fields operating at the level of early visual processing, but arises from the inertia of decisional templates. This finding is consistent with a Two-process model of serial dependence in which the persistence of read-out weights in a decision unit compensates for sensory adaptation, leading to attractive biases in sequential responses. We propose the first unified account of serial dependence in which functionally distinct mechanisms, operating at different stages, promote the differentiation and integration of visual information over time.


Author(s):  
Richard Stone ◽  
Minglu Wang ◽  
Thomas Schnieders ◽  
Esraa Abdelall

Human-robotic interaction system are increasingly becoming integrated into industrial, commercial and emergency service agencies. It is critical that human operators understand and trust automation when these systems support and even make important decisions. The following study focused on human-in-loop telerobotic system performing a reconnaissance operation. Twenty-four subjects were divided into groups based on level of automation (Low-Level Automation (LLA), and High-Level Automation (HLA)). Results indicated a significant difference between low and high word level of control in hit rate when permanent error occurred. In the LLA group, the type of error had a significant effect on the hit rate. In general, the high level of automation was better than the low level of automation, especially if it was more reliable, suggesting that subjects in the HLA group could rely on the automatic implementation to perform the task more effectively and more accurately.


2015 ◽  
Vol 28 (17) ◽  
pp. 6743-6762 ◽  
Author(s):  
Catherine M. Naud ◽  
Derek J. Posselt ◽  
Susan C. van den Heever

Abstract The distribution of cloud and precipitation properties across oceanic extratropical cyclone cold fronts is examined using four years of combined CloudSat radar and CALIPSO lidar retrievals. The global annual mean cloud and precipitation distributions show that low-level clouds are ubiquitous in the postfrontal zone while higher-level cloud frequency and precipitation peak in the warm sector along the surface front. Increases in temperature and moisture within the cold front region are associated with larger high-level but lower mid-/low-level cloud frequencies and precipitation decreases in the cold sector. This behavior seems to be related to a shift from stratiform to convective clouds and precipitation. Stronger ascent in the warm conveyor belt tends to enhance cloudiness and precipitation across the cold front. A strong temperature contrast between the warm and cold sectors also encourages greater post-cold-frontal cloud occurrence. While the seasonal contrasts in environmental temperature, moisture, and ascent strength are enough to explain most of the variations in cloud and precipitation across cold fronts in both hemispheres, they do not fully explain the differences between Northern and Southern Hemisphere cold fronts. These differences are better explained when the impact of the contrast in temperature across the cold front is also considered. In addition, these large-scale parameters do not explain the relatively large frequency in springtime postfrontal precipitation.


2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Stelios A. Mitilineos ◽  
Stelios M. Potirakis ◽  
Nicolas-Alexander Tatlas ◽  
Maria Rangoussi

STORM is an ongoing European research project that aims at developing an integrated platform for monitoring, protecting, and managing cultural heritage sites through technical and organizational innovation. Part of the scheduled preventive actions for the protection of cultural heritage is the development of wireless acoustic sensor networks (WASNs) that will be used for assessing the impact of human-generated activities as well as for monitoring potentially hazardous environmental phenomena. Collected sound samples will be forwarded to a central server where they will be automatically classified in a hierarchical manner; anthropogenic and environmental activity will be monitored, and stakeholders will be alarmed in the case of potential malevolent behavior or natural phenomena like excess rainfall, fire, gale, high tides, and waves. Herein, we present an integrated platform that includes sound sample denoising using wavelets, feature extraction from sound samples, Gaussian mixture modeling of these features, and a powerful two-layer neural network for automatic classification. We contribute to previous work by extending the proposed classification platform to perform low-level classification too, i.e., classify sounds to further subclasses that include airplane, car, and pistol sounds for the anthropogenic sound class; bird, dog, and snake sounds for the biophysical sound class; and fire, waterfall, and gale for the geophysical sound class. Classification results exhibit outstanding classification accuracy in both high-level and low-level classification thus demonstrating the feasibility of the proposed approach.


2020 ◽  
Vol 9 (2) ◽  
pp. 108-120
Author(s):  
Nguyen Thi Minh Tram ◽  
Bui Thi Thuc Quyen

Nurturing critical thinking (CT) has been acknowledged as a core objective of tertiary education, and drawn attention from academia of teaching English as a Foreign Language (EFL), particularly in EFL argumentative writing. It has been claimed that collaborative learning which stimulates the active exchange of ideas within small groups not only increases interest among the participants but also promotes critical thinking. One of the important aspects of learning and teaching through collaboration is the group composition or grouping “who with whom”. The present study was an attempt to investigate the impact of homogeneous and heterogeneous groupings on critical thinking in collaborative writing. Having been required to write an argumentative essay as a pre-test, 75 participants, who were categorized by their prior critical thinking levels, were assigned into three group types: heterogeneous, homogeneous high and homogeneous low groups. As a consequence, four types of students were considered their improvement before and after the experiment: high-level students in heterogeneous groups, lowlevel students in heterogeneous groups, high-level students in homogeneous groups, low-level students in homogeneous groups. The results demonstrated that learners improved their critical thinking level through collaborative writing, whether working with stronger or weaker peers. However, heterogeneous grouping showed superiority over homogeneous grouping at the low level. The results revealed that cooperative learning could be especially beneficial for low students. It is hoped that the findings of the present study will give teachers deep insights into group compositions in collaborative learning courses, and will help them make better group experiences for students.


2021 ◽  
Author(s):  
Ning Mei ◽  
Roberto Santana ◽  
David Soto

AbstractDespite advances in the neuroscience of visual consciousness over the last decades, we still lack a framework for understanding the scope of unconscious processing and how it relates to conscious experience. Previous research observed brain signatures of unconscious contents in visual cortex, but these have not been identified in a reliable manner, with low trial numbers and signal detection theoretic constraints not allowing to decisively discard conscious perception. Critically, the extent to which unconscious content is represented in high-level processing stages along the ventral visual stream and linked prefrontal areas remains unknown. Using a within-subject, high-precision, highly-sampled fMRI approach, we show that unconscious contents, even those associated with null sensitivity, can be reliably decoded from multivoxel patterns that are highly distributed along the ventral visual pathway and also involving prefrontal substrates. Notably, the neural representation in these areas generalised across conscious and unconscious visual processing states, placing constraints on prior findings that fronto-parietal substrates support the representation of conscious contents and suggesting revisions to models of consciousness such as the neuronal global workspace. We then provide a computational model simulation of visual information processing/representation in the absence of perceptual sensitivity by using feedforward convolutional neural networks trained to perform a similar visual task to the human observers. The work provides a novel framework for pinpointing the neural representation of unconscious knowledge across different task domains.


F1000Research ◽  
2013 ◽  
Vol 2 ◽  
pp. 58 ◽  
Author(s):  
J Daniel McCarthy ◽  
Colin Kupitz ◽  
Gideon P Caplovitz

Our perception of an object’s size arises from the integration of multiple sources of visual information including retinal size, perceived distance and its size relative to other objects in the visual field. This constructive process is revealed through a number of classic size illusions such as the Delboeuf Illusion, the Ebbinghaus Illusion and others illustrating size constancy. Here we present a novel variant of the Delbouef and Ebbinghaus size illusions that we have named the Binding Ring Illusion. The illusion is such that the perceived size of a circular array of elements is underestimated when superimposed by a circular contour – a binding ring – and overestimated when the binding ring slightly exceeds the overall size of the array. Here we characterize the stimulus conditions that lead to the illusion, and the perceptual principles that underlie it. Our findings indicate that the perceived size of an array is susceptible to the assimilation of an explicitly defined superimposed contour. Our results also indicate that the assimilation process takes place at a relatively high level in the visual processing stream, after different spatial frequencies have been integrated and global shape has been constructed. We hypothesize that the Binding Ring Illusion arises due to the fact that the size of an array of elements is not explicitly defined and therefore can be influenced (through a process of assimilation) by the presence of a superimposed object that does have an explicit size.


2020 ◽  
Author(s):  
Haider Al-Tahan ◽  
Yalda Mohsenzadeh

AbstractWhile vision evokes a dense network of feedforward and feedback neural processes in the brain, visual processes are primarily modeled with feedforward hierarchical neural networks, leaving the computational role of feedback processes poorly understood. Here, we developed a generative autoencoder neural network model and adversarially trained it on a categorically diverse data set of images. We hypothesized that the feedback processes in the ventral visual pathway can be represented by reconstruction of the visual information performed by the generative model. We compared representational similarity of the activity patterns in the proposed model with temporal (magnetoencephalography) and spatial (functional magnetic resonance imaging) visual brain responses. The proposed generative model identified two segregated neural dynamics in the visual brain. A temporal hierarchy of processes transforming low level visual information into high level semantics in the feedforward sweep, and a temporally later dynamics of inverse processes reconstructing low level visual information from a high level latent representation in the feedback sweep. Our results append to previous studies on neural feedback processes by presenting a new insight into the algorithmic function and the information carried by the feedback processes in the ventral visual pathway.Author summaryIt has been shown that the ventral visual cortex consists of a dense network of regions with feedforward and feedback connections. The feedforward path processes visual inputs along a hierarchy of cortical areas that starts in early visual cortex (an area tuned to low level features e.g. edges/corners) and ends in inferior temporal cortex (an area that responds to higher level categorical contents e.g. faces/objects). Alternatively, the feedback connections modulate neuronal responses in this hierarchy by broadcasting information from higher to lower areas. In recent years, deep neural network models which are trained on object recognition tasks achieved human-level performance and showed similar activation patterns to the visual brain. In this work, we developed a generative neural network model that consists of encoding and decoding sub-networks. By comparing this computational model with the human brain temporal (magnetoencephalography) and spatial (functional magnetic resonance imaging) response patterns, we found that the encoder processes resemble the brain feedforward processing dynamics and the decoder shares similarity with the brain feedback processing dynamics. These results provide an algorithmic insight into the spatiotemporal dynamics of feedforward and feedback processes in biological vision.


Author(s):  
N. Sandhya Rani ◽  
M. Sarada Devi

Empowerment of tribal women is one of the central issues in the process of development all over the world. Empowerment is the process that allows one to gain the knowledge and attitude needed to cope with the changing world and the circumstances in which one lives [1]. Women empowerment is a process in which women gain greater share of control over material, human and intellectual resources as well as control over decision-making in their home, community, society and nation. Given the need to analyze the empowerment status of tribal women, the present study aimed to enhance the empowerment status through enhancing decision-making skills of tribal working women in India. The specific objective is to study the impact of intervention on enhancing status of empowerment through decision-making skills of tribal working women in Utnoor Mandal Adilabad district. The total sample population for the study was 50 tribal working women, and data was analyzed using a paired t test. Results revealed that at pretest, majority of the women were at average level of decision-making skills (78%), 12% were at low level and only 10% were at high level. After the intervention, post test results revealed that 74% of the women were high in decision making skills and remaining 26% were at average level. Interestingly, none of the respondents had low level of life skills. Thus, intervention found to be effective among women respondents to develop and enhance their empowerment status through decision-making skills.


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