scholarly journals Quantifying the effects of feature similarity on attentional selection using psychophysical scaling

2021 ◽  
Vol 21 (9) ◽  
pp. 2513
Author(s):  
Angus Chapman ◽  
Viola Störmer
Keyword(s):  
Attentional Selection ◽  
Psychophysical Scaling ◽  
Feature Similarity

scholarly journals Does feature similarity facilitate attentional selection?

2010 ◽  
Vol 72 (8) ◽  
pp. 2128-2143 ◽  
Author(s):  
Yariv Festman ◽  
Jochen Braun
Keyword(s):  
Attentional Selection ◽  
Feature Similarity

Magnitude Estimation and Cross-Modal Matching of Lingual Vibrotactile and Auditory Sensation

1989 ◽  
Vol 32 (3) ◽  
pp. 698-702 ◽  
Author(s):  
Daniel Harris ◽  
Donald Fucci ◽  
Linda Petrosino
Keyword(s):  
Auditory Stimulus ◽  
Magnitude Estimation ◽  
Sensory Processing ◽  
Test Site ◽  
Systematic Investigation ◽  
Thenar Eminence ◽  
Stimulus Range ◽  
Psychophysical Scaling ◽  
Scaling Methods ◽  
Response Biases

The present experiment was a preliminary attempt to use the psychophysical scaling methods of magnitude estimation and cross-modal matching to investigate suprathreshold judgments of lingual vibrotactile and auditory sensation magnitudes for 20 normal young adult subjects. A 250-Hz lingual vibrotactile stimulus and a 1000-Hz binaural auditory stimulus were employed. To obtain judgments for nonoral vibrotactile sensory magnitudes, the thenar eminence of the hand was also employed as a test site for 5 additional subjects. Eight stimulus intensities were presented during all experimental tasks. The results showed that the slopes of the log-log vibrotactile magnitude estimation functions decreased at higher stimulus intensity levels for both test sites. Auditory magnitude estimation functions were relatively constant throughout the stimulus range. Cross-modal matching functions for the two stimuli generally agreed with functions predicted from the magnitude estimation data, except when subjects adjusted vibration on the tongue to match auditory stimulus intensities. The results suggested that the methods of magnitude estimation and cross-modal matching may be useful for studying sensory processing in the speech production system. However, systematic investigation of response biases associated with vibrotactile-auditory psychophysical scaling tasks appears to be a prerequisite.

Effects of Retinal Distance and Feature Similarity on Disparity Coding

1973 ◽  
Author(s):  
W. L. Gulick ◽  
W. M. Youngs ◽  
John P. Galla
Keyword(s):  
Feature Similarity

Toward Understanding the Role of Reward in Attentional Selection

2014 ◽  
Vol 22 (10) ◽  
pp. 1573 ◽  
Author(s):  
Lingxia FAN ◽  
Senqing Qi ◽  
Renlu GUO ◽  
Bo HUAGN ◽  
Dong YANG
Keyword(s):  
Attentional Selection

scholarly journals Multi-Scale Aggregation Graph Neural Networks Based on Feature Similarity for Semi-Supervised Learning

Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 403
Author(s):  
Xun Zhang ◽  
Lanyan Yang ◽  
Bin Zhang ◽  
Ying Liu ◽  
Dong Jiang ◽  
...  
Keyword(s):  
Neural Network ◽  
Supervised Learning ◽  
Structured Data ◽  
Similarity Matrix ◽  
Scale Feature ◽  
Multi Scale ◽  
Adjacent Node ◽  
Feature Similarity ◽  
The Mean ◽  
Graph Neural Networks

The problem of extracting meaningful data through graph analysis spans a range of different fields, such as social networks, knowledge graphs, citation networks, the World Wide Web, and so on. As increasingly structured data become available, the importance of being able to effectively mine and learn from such data continues to grow. In this paper, we propose the multi-scale aggregation graph neural network based on feature similarity (MAGN), a novel graph neural network defined in the vertex domain. Our model provides a simple and general semi-supervised learning method for graph-structured data, in which only a very small part of the data is labeled as the training set. We first construct a similarity matrix by calculating the similarity of original features between all adjacent node pairs, and then generate a set of feature extractors utilizing the similarity matrix to perform multi-scale feature propagation on graphs. The output of multi-scale feature propagation is finally aggregated by using the mean-pooling operation. Our method aims to improve the model representation ability via multi-scale neighborhood aggregation based on feature similarity. Extensive experimental evaluation on various open benchmarks shows the competitive performance of our method compared to a variety of popular architectures.

scholarly journals Mind-wandering Is Accompanied by Both Local Sleep and Enhanced Processes of Spatial Attention Allocation

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Christian Wienke ◽  
Mandy V Bartsch ◽  
Lena Vogelgesang ◽  
Christoph Reichert ◽  
Hermann Hinrichs ◽  
...  
Keyword(s):  
Search Task ◽  
Brain Activity ◽  
Target Selection ◽  
Mind Wandering ◽  
Attentional Selection ◽  
Self Report ◽  
Cortical Processing ◽  
High Frequency Activity ◽  
External Stimuli ◽  
Local Sleep

Abstract Mind-wandering (MW) is a subjective, cognitive phenomenon, in which thoughts move away from the task toward an internal train of thoughts, possibly during phases of neuronal sleep-like activity (local sleep, LS). MW decreases cortical processing of external stimuli and is assumed to decouple attention from the external world. Here, we directly tested how indicators of LS, cortical processing, and attentional selection change in a pop-out visual search task during phases of MW. Participants’ brain activity was recorded using magnetoencephalography, MW was assessed via self-report using randomly interspersed probes. As expected, the performance decreased under MW. Consistent with the occurrence of LS, MW was accompanied by a decrease in high-frequency activity (HFA, 80–150 Hz) and an increase in slow wave activity (SWA, 1–6 Hz). In contrast, visual attentional selection as indexed by the N2pc component was enhanced during MW with the N2pc amplitude being directly linked to participants’ performance. This observation clearly contradicts accounts of attentional decoupling that would predict a decrease in attention-related responses to external stimuli during MW. Together, our results suggest that MW occurs during phases of LS with processes of attentional target selection being upregulated, potentially to compensate for the mental distraction during MW.

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