scholarly journals Prediction of Visual Memorability with EEG Signals: A Comparative Study

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2694
Author(s):  
Sang-Yeong Jo ◽  
Jin-Woo Jeong

Visual memorability is a method to measure how easily media contents can be memorized. Predicting the visual memorability of media contents has recently become more important because it can affect the design principles of multimedia visualization, advertisement, etc. Previous studies on the prediction of the visual memorability of images generally exploited visual features (e.g., color intensity and contrast) or semantic information (e.g., class labels) that can be extracted from images. Some other works tried to exploit electroencephalography (EEG) signals of human subjects to predict the memorability of text (e.g., word pairs). Compared to previous works, we focus on predicting the visual memorability of images based on human biological feedback (i.e., EEG signals). For this, we design a visual memory task where each subject is asked to answer whether they correctly remember a particular image 30 min after glancing at a set of images sampled from the LaMemdataset. During the visual memory task, EEG signals are recorded from subjects as human biological feedback. The collected EEG signals are then used to train various classification models for prediction of image memorability. Finally, we evaluate and compare the performance of classification models, including deep convolutional neural networks and classical methods, such as support vector machines, decision trees, and k-nearest neighbors. The experimental results validate that the EEG-based prediction of memorability is still challenging, but a promising approach with various opportunities and potentials.

1998 ◽  
Vol 79 (3) ◽  
pp. 255-265 ◽  
Author(s):  
Donald M Dougherty ◽  
Joel L Steinberg ◽  
Adel A Wassef ◽  
David Medearis ◽  
Don R Cherek ◽  
...  

2017 ◽  
Author(s):  
Travis Meyer ◽  
Nicole C. Rust

AbstractOur visual memory percepts of whether we have encountered specific objects or scenes before are hypothesized to manifest as decrements in neural responses in inferotemporal cortex (IT) with stimulus repetition. To evaluate this proposal, we recorded IT neural responses as two monkeys performed a single-exposure visual memory task designed to measure the rates of forgetting with time. We found that a weighted linear read-out of IT was a better predictor of the monkeys’ forgetting rates and reaction time patterns than a strict instantiation of the repetition suppression hypothesis, expressed as a total spike count scheme. Behavioral predictions could be attributed to visual memory signals that were reflected as repetition suppression and were intermingled with visual selectivity, but only when combined across the most sensitive neurons.


Author(s):  
Caroline Dakoure ◽  
Mohamed Sahbi Benlamine ◽  
Claude Frasson

It is of great importance to detect users’ confusion in a variety of situations such as orientation, reasoning, learning, and memorization. Confusion affects our ability to make decisions and can lower our cognitive ability. This study examines whether a confusion recognition model based on EEG features, recorded on cognitive ability tests, can be used to detect three levels (low, medium, high) of confusion. This study also addresses the extraction of additional features relevant to classification. We compare the performance of the K-nearest neighbors (KNN), support vector memory (SVM), and long short-term memory (LSTM) models. Results suggest that confusion can be efficiently recognized with EEG signals (78.6% accuracy in detecting a confused/unconfused state and 68.0% accuracy in predicting the level of confusion). Implications for educational situations are discussed.


Author(s):  
BÜLENT YILMAZ ◽  
CENGİZ GAZELOĞLU ◽  
FATİH ALTINDİŞ

Neuromarketing is the application of the neuroscientific approaches to analyze and understand economically relevant behavior. In this study, the effect of loud and rhythmic music in a sample neuromarketing setup is investigated. The second aim was to develop an approach in the prediction of preference using only brain signals. In this work, 19- channel EEG signals were recorded and two experimental paradigms were implemented: no music/silence and rhythmic, loud music using a headphone, while viewing women shoes. For each 10-sec epoch, normalized power spectral density (PSD) of EEG data for six frequency bands was estimated using the Burg method. The effect of music was investigated by comparing the mean differences between music and no music groups using independent two-sample t-test. In the preference prediction part sequential forward selection, k-nearest neighbors (k-NN) and the support vector machines (SVM), and 5-fold cross-validation approaches were used. It is found that music did not affect like decision in any of the power bands, on the contrary, music affected dislike decisions for all bands with no exceptions. Furthermore, the accuracies obtained in preference prediction study were between 77.5 and 82.5% for k-NN and SVM techniques. The results of the study showed the feasibility of using EEG signals in the investigation of the music effect on purchasing behavior and the prediction of preference of an individual.


1970 ◽  
Vol 7 (1) ◽  
pp. 47-50 ◽  
Author(s):  
Frank Tolkmitt ◽  
Richard E. Christ

2004 ◽  
Vol 101 (14) ◽  
pp. 5064-5068 ◽  
Author(s):  
G. T. Prusky ◽  
R. M. Douglas ◽  
L. Nelson ◽  
A. Shabanpoor ◽  
R. J. Sutherland

1972 ◽  
Vol 12 (1) ◽  
pp. 65-68 ◽  
Author(s):  
David W. Martin ◽  
Eileen Richards

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Travis Meyer ◽  
Nicole C Rust

Our visual memory percepts of whether we have encountered specific objects or scenes before are hypothesized to manifest as decrements in neural responses in inferotemporal cortex (IT) with stimulus repetition. To evaluate this proposal, we recorded IT neural responses as two monkeys performed a single-exposure visual memory task designed to measure the rates of forgetting with time. We found that a weighted linear read-out of IT was a better predictor of the monkeys’ forgetting rates and reaction time patterns than a strict instantiation of the repetition suppression hypothesis, expressed as a total spike count scheme. Behavioral predictions could be attributed to visual memory signals that were reflected as repetition suppression and were intermingled with visual selectivity, but only when combined across the most sensitive neurons.


1979 ◽  
Vol 48 (1) ◽  
pp. 195-198 ◽  
Author(s):  
R. Dale Walker ◽  
Michael R. O'Leary ◽  
Edmund F. Chaney ◽  
Thomas M. Fauria

The present study investigated the interaction between cognitive style, imagery, and memory. The Tactual Performance Test Location Score from the Halstead-Reitan battery was used as a measure of incidental tactual memory and mental imagery. The Group Embedded Figures Test was used to assess cognitive style. Results for 38 Caucasian males of mean age 49.9 yr. suggest that cognitive style is related to an individual's ability to perform a non-verbal, non-visual memory task. Further, cognitive style may be an important mediating variable influencing intrapersonal behaviors such as non-verbal memory and mental imagery.


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