ArticleBrain sciences2022
Central EEG Beta/Alpha Ratio Predicts the Population-Wide Efficiency of Advertisements.
Article in Brain sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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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.
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Who cites it
10 citing papers in PubMed.
- EEG-Based Engagement Monitoring in Cognitive Games.Sensors (Basel, Switzerland) · 2025Article
- Effects of green-wall layouts on psychological and physiological responses in office environments: a virtual-environment study.Frontiers in psychology · 2025Article
- Machine learning-based viewers' preference prediction on social awareness advertisements using EEG.Frontiers in human neuroscience · 2025Article
- Multidimensional on-site perception study of stairway spaces in mountain city parks among young and older adult people: a case study of Pipa Mountain Park, Chongqing, China.Frontiers in psychology · 2025Article
- Neuroergonomic Attention Assessment in Safety-Critical Tasks: EEG Indices and Subjective Metrics Validation in a Novel Task-Embedded Reaction Time Paradigm.Brain sciences · 2024Article
- Effects of Vibroacoustic Stimulation on Psychological, Physiological, and Cognitive Stress.Sensors (Basel, Switzerland) · 2024Article
- A systematic review on EEG-based neuromarketing: recent trends and analyzing techniques.Brain informatics · 2024Review
- The N270 as an index of consumer commodity color preference in the S1-S2 paradigm.Frontiers in psychology · 2024Article
- Real-time EEG-based emotion recognition for neurohumanities: perspectives from principal component analysis and tree-based algorithms.Frontiers in human neuroscience · 2024Article
- Understanding the role of emotion in decision making process: using machine learning to analyze physiological responses to visual, auditory, and combined stimulation.Frontiers in human neuroscience · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent studies have demonstrated that the brain activity of a group of people can be used to forecast choices at the population level. In this study, we attempted to neuroforecast aggregate consumer behavior of Internet users. During our electroencephalography (EEG) and eye-tracking study, participants were exposed to 10 banners that were also used in the real digital marketing campaign. In the separate online study, we additionally collected self-reported preferences for the same banners. We explored the relationship between the EEG, eye-tracking, and behavioral indexes obtained in our studies and the banners' aggregate efficiency provided by the large food retailer based on the decisions of 291,301 Internet users. An EEG-based engagement index (central beta/alpha ratio) significantly correlated with the aggregate efficiency of banners. Furthermore, our multiple linear regression models showed that a combination of eye-tracking, EEG and behavioral measurements better explained the market-level efficiency of banner advertisements than each measurement alone. Overall, our results confirm that neural signals of a relatively small number of individuals can forecast aggregate behavior at the population level.
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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.