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Introduction: The purpose of this study was to investigate the neural effects of brand social responsibility (BSR) on consumer behavior. In the version of third marketing, consideration of the human spirit and its responsibility as a competitive strategy has been proposed. Materials and Methods: The investigation method was an exploratory-laboratory. Electrocardiographic instruments were used to record brain signals through the EEG EPOC + 14 Electrode wireless device (emotive. co). After cleaning of signals by independent component analysis with EEGLAB software through the LORETA algorithm, the brain activity was localized. The study was performed on a population of a scent consumers. An advertise with the nature of the social responsibility of the brand was shown to the experimental group. Brand consumers were selected as the control group. This group was not aware of the social responsibility. Results: The results showed that the left hemisphere was mostly activated in the experimental group, whereas different regions in right hemisphere was activated in the control group. Conclusion: This study suggested that the behavior triggered by sensory stimuli is due to the activation of both left-orientation and right-orientation of the brain. The localization of the brain activity (left or right) can be regulated in favor of a brand with respect to social responsibility.

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Introduction: The purpose of the research is to model visual behavior through machine learning methods, analyzing visual data to increase recognition and accuracy of decision-making is one of the important aspects of this research. Materials and Methods: The research method is an exploratory-laboratory type, which has extracted visual data using the GAZEPOINT eye tracker analyzed and modeled by the multi-layer perceptron neural network algorithm in the Python environment. The statistical population consists of consumers of a bag brand with natural fiber materials, which is shown to 30 women in the form of three images, the tasks are designed for choice/choices and non-choice/non-choices. Results: Based on the confusion matrix, Kappa index, and recall metrics, the results indicate that the model provides a robust prediction for general visual behavior across various types of images. Based on the confusion matrix, Kappa index (K=0.34), and recall (R=66), the results suggest that visual behavior modeling is generally effective across different image categories, with an overall accuracy of 66.8%. The model shows higher accuracy when predicting visual behavior for specific image types, indicating that the performance of the model improves when tailored to individual image categories (Accuracy: 67.8, 76.9, 73, k= 0.35, 0.53, 0.46, R= 68, 75, 78). Conclusion: Visual behavior modeling provides behavioral science researchers and product design experts a proactive approach by predicting consumer choices and non-choices. This ability enhances the accuracy of studies and allows for more informed decisions.

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Introduction: Games have demonstrated significant success when they are purposefully created to tackle particular issues or educational needs. Consequently, recent research has focused on exploring a background game that incorporates visual logic therapy. This investigation employs the methodology of examining brain rhythms and their alterations through visual behavior, leading to the development of a game known as Visual Game Therapy (VGT), which may offer therapeutic benefits. Materials and Methods: The method is exploratory-laboratory as well as descriptive-survey, which was tested with the design of the laboratory through the design of the web game of the subjects. After checking the ability of the game as a measurement tool through eye tracking and electroencephalography. A sample of 457 participants was recruited using the snowball sampling method. Key metrics analyzed included memory score index, image recognition score, and memory response time. Data collection and analysis were conducted online, with correlations between game performance and memory metrics evaluated using the Pearson Correlation test in the MINITAB 18 software environment. Results: The findings revealed a significant correlation between the number of game rounds completed and both the memory score and image recognition score, indicating that increased engagement with the game positively influenced these cognitive measures. However, no significant correlation was observed between memory response time and memory score. Conclusion: VGT offers significant potential for improving and strengthening memory. Their effectiveness is rooted in the integration of study-based approaches and carefully designed visual patterns, which have been shown to influence brainwave activity, particularly by enhancing Theta power.