Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Kumar Chandar, S.; Vijayadurai, J.; Palanivel Rajan, M. Title A name given to the resource A Spiking Neural Network Approach to Electroencephalography based Consumer Preference Modeling Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Journal of Innovative Image Processing;Volume;7;Issue;3;pp.725-738 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.36548/jiip.2025.3.009" target="_blank" rel="noreferrer noopener">https://doi.org/10.36548/jiip.2025.3.009</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105016466041?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105016466041?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Kumar Chandar S., School of Business &amp; Management, Christ University, India, Department of Management Studies, Madurai Kamaraj University, Madurai, India; Vijayadurai J., Department of Management Studies, Madurai Kamaraj University, Madurai, India; Palanivel Rajan M., Department of Management Studies, Madurai Kamaraj University, Madurai, India Description An account of the resource Neuromarketing is an emerging interdisciplinary field that applies neuropsychology in marketing to study consumer sensory-motor actions such as cognitive and affective responses to marketing stimuli through Brain Computer Interface (BCI) technology. While marketers spend over 750 billion dollars annually on traditional marketing procedures such as surveys, interviews, and consumers feedback, these methods are often criticized for their inability to capture genuine consumer preferences. Neuromarketing promises to overcome such issues by analyzing neural responses directly. This paper presents a novel framework for predicting consumer preferences by analyzing Electroencephalography (EEG) signals. EEG signals are acquired from 25 volunteers while administering 14 products with three different variations. The EEG signals are preprocessed using Modified Wavelet Thresholding (MWT) to remove noise while preserving neural activity patterns. A third-generation network, Spiking Neural Network (SNN) is designed to recognize consumer preferences based on EEG frequency bands. Unlike conventional models, SNN captures temporal dynamics through spike timing, which is crucial for EEG signals. The efficacy of the model is tested across individual EEG bands to identify the most influential frequency band in decision-making. Simulation outcomes demonstrate that the proposed model can effectively predict consumer preferences. The model achieved an accuracy of 90.91%, recall of 90.7%, a precision of 91.14%, a specificity of 91.12%, and an F1-score of 90.92%. The outcomes highlight the potential of EEG based neuromarketing systems to decode subconscious consumer responses, enabling brands and businesses to design more targeted marketing strategies based on objective neural data. 2025 Inventive Research Organization. Subject The topic of the resource BCI; Consumer Preference; EEG; Neuromarketing; Spiking Neural Network; Wavelet Transform Publisher An entity responsible for making the resource available Inventive Research Organization Relation A related resource ISSN: 25824252; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Gold Open Access Format The file format, physical medium, or dimensions of the resource online