ReviewBrain informatics2024
A systematic review on EEG-based neuromarketing: recent trends and analyzing techniques.
Review in Brain informatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Generative diffusion meets domain adaptation: a framework for EEG cross-subject motor imagery classification.Brain informatics · 2026Article
- Neuroscience meets food choice: Implicit and explicit consumer responses to plant-based vs animal-based foods.Current research in food science · 2026Article
- Exploring neuromarketing's influence on consumer impulsivity through the lens of personality traits.Frontiers in psychology · 2026Article
- Beyond the lab: real-world benchmarking of wearable EEGs for passive brain-computer interfaces.Brain informatics · 2025Article
- The analgesic effect and neural mechanism of spicy food intake.Social cognitive and affective neuroscience · 2025Article
- A framework for analyzing EEG data using high-dimensional tests.Bioinformatics (Oxford, England) · 2025Article
- Editorial: Machine-learning/deep-learning methods in neuromarketing and consumer neuroscience.Frontiers in human neuroscience · 2025Article
- Electroencephalography-based neural indicators of texture preference for cosmetic formulations.Frontiers in neuroscience · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neuromarketing is an emerging research field that aims to understand consumers' decision-making processes when choosing which product to buy. This information is highly sought after by businesses looking to improve their marketing strategies by understanding what leaves a positive or negative impression on consumers. It has the potential to revolutionize the marketing industry by enabling companies to offer engaging experiences, create more effective advertisements, avoid the wrong marketing strategies, and ultimately save millions of dollars for businesses. Therefore, good documentation is necessary to capture the current research situation in this vital sector. In this article, we present a systematic review of EEG-based Neuromarketing. We aim to shed light on the research trends, technical scopes, and potential opportunities in this field. We reviewed recent publications from valid databases and divided the popular research topics in Neuromarketing into five clusters to present the current research trend in this field. We also discuss the brain regions that are activated when making purchase decisions and their relevance to Neuromarketing applications. The article provides appropriate illustrations of marketing stimuli that can elicit authentic impressions from consumers' minds, the techniques used to process and analyze recorded brain data, and the current strategies employed to interpret the data. Finally, we offer recommendations to upcoming researchers to help them investigate the possibilities in this area more efficiently in the future.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.