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Machine learning‐based classifying of risk‐takers and risk‐aversive individuals using resting‐state EEG data: A pilot feasibility study

https://doi.org/10.1002/brb3.3139
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/brb3.3139openalex-snapshot
Machine learning‐based classifying of risk‐takers and risk‐aversive individuals using resting‐state EEG data: A pilot feasibility study
inferredcites →https://doi.org/10.1002/cne.902930211openalex-snapshot
Supplementary eye field as defined by intracortical microstimulation: Connections in macaques
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Exploring Gender Differences in Online Consumer Purchase Decision Making: An Online Product Presentation Perspective
inferredcites →https://doi.org/10.1007/s11571-016-9416-yopenalex-snapshot
An EEG-based machine learning method to screen alcohol use disorder
inferredcites →https://doi.org/10.1007/s40622-020-00252-8openalex-snapshot
Gender-based differences in consumer decision-making styles: implications for marketers
inferredcites →https://doi.org/10.1016/0167-8655(94)90127-9openalex-snapshot
Floating search methods in feature selection
inferredcites →https://doi.org/10.1016/j.cmpb.2012.10.008openalex-snapshot
Classifying depression patients and normal subjects using machine learning techniques and nonlinear features from EEG signal
inferredcites →https://doi.org/10.1016/j.cogbrainres.2005.04.002openalex-snapshot
Electrophysiological ratio markers for the balance between reward and punishment
inferredcites →https://doi.org/10.1016/j.drugalcdep.2020.107884openalex-snapshot
Common and distinct brain activity associated with risky and ambiguous decision-making
inferredcites →https://doi.org/10.1016/j.ijpsycho.2013.10.013openalex-snapshot
Resting-state EEG theta activity and risk learning: sensitivity to reward or punishment?
inferredcites →https://doi.org/10.1016/j.jneumeth.2003.10.009openalex-snapshot
EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis
inferredcites →https://doi.org/10.1016/j.jneumeth.2007.09.022openalex-snapshot
Machine learning for real-time single-trial EEG-analysis: From brain–computer interfacing to mental state monitoring
inferredcites →https://doi.org/10.1016/j.neunet.2019.12.006openalex-snapshot
A novel multi-modal machine learning based approach for automatic classification of EEG recordings in dementia
inferredcites →https://doi.org/10.1016/j.neuroimage.2006.02.047openalex-snapshot
Distinct neural mechanisms of risk and ambiguity: A meta-analysis of decision-making
inferredcites →https://doi.org/10.1016/j.neuroimage.2010.02.024openalex-snapshot
Association of individual resting state EEG alpha frequency and cerebral blood flow
inferredcites →https://doi.org/10.1016/j.neuroimage.2012.10.034openalex-snapshot
Resting-state EEG power predicts conflict-related brain activity in internally guided but not in externally guided decision-making
inferredcites →https://doi.org/10.1016/j.neuroimage.2013.02.063openalex-snapshot
The valuation system: A coordinate-based meta-analysis of BOLD fMRI experiments examining neural correlates of subjective value
inferredcites →https://doi.org/10.1016/j.neuroimage.2018.12.029openalex-snapshot
Single-trial EEG dissociates motivation and conflict processes during decision-making under risk
inferredcites →https://doi.org/10.1016/j.neuroimage.2019.116333openalex-snapshot
Predicting individual decision-making responses based on single-trial EEG
inferredcites →https://doi.org/10.1016/j.neuropsychologia.2020.107526openalex-snapshot
Common and distinct electrophysiological correlates of feedback processing during risky and ambiguous decision making
inferredcites →https://doi.org/10.1016/j.parkreldis.2020.08.001openalex-snapshot
Linear predictive coding distinguishes spectral EEG features of Parkinson's disease
inferredcites →https://doi.org/10.1016/j.tics.2011.07.011openalex-snapshot
A unified framework for inhibitory control
inferredcites →https://doi.org/10.1016/s1057-0810(99)00041-4openalex-snapshot
Financial risk tolerance revisited
inferredcites →https://doi.org/10.1088/1741-2552/ab0ab5openalex-snapshot
Deep learning for electroencephalogram (EEG) classification tasks: a review
inferredcites →https://doi.org/10.1088/1741-2552/ab260copenalex-snapshot
Deep learning-based electroencephalography analysis: a systematic review
inferredcites →https://doi.org/10.1088/1741-2552/ab39ceopenalex-snapshot
Predicting individual decision-making responses based on the functional connectivity of resting-state EEG
inferredcites →https://doi.org/10.1108/qrfm-10-2019-0127openalex-snapshot
What’s in the brain for us: a systematic literature review of neuroeconomics and neurofinance
inferredcites →https://doi.org/10.1109/access.2020.2998934openalex-snapshot
Machine Learning Algorithms and Quantitative Electroencephalography Predictors for Outcome Prediction in Traumatic Brain Injury: A Systematic Review
inferredcites →https://doi.org/10.1109/rbme.2020.3008792openalex-snapshot
Machine Learning for Predicting Epileptic Seizures Using EEG Signals: A Review
inferredcites →https://doi.org/10.1111/j.1467-9280.2008.02260.xopenalex-snapshot
Tonic Activity Level in the Right Prefrontal Cortex Predicts Individuals' Risk Taking
inferredcites →https://doi.org/10.1142/s0129065721300023openalex-snapshot
Machine Learning Algorithms and Statistical Approaches for Alzheimer’s Disease Analysis Based on Resting-State EEG Recordings: A Systematic Review
inferredcites →https://doi.org/10.1152/jn.90989.2008openalex-snapshot
Using a Common Average Reference to Improve Cortical Neuron Recordings From Microelectrode Arrays
inferredcites →https://doi.org/10.1155/2018/1613456openalex-snapshot
Diagnosis of Encephalopathy Based on Energies of EEG Subbands Using Discrete Wavelet Transform and Support Vector Machine
inferredcites →https://doi.org/10.1155/2021/2053795openalex-snapshot
Facial Emotion Recognition Predicts Alexithymia Using Machine Learning
inferredcites →https://doi.org/10.1177/1550059417744890openalex-snapshot
Automatic Seizure Detection Based on Morphological Features Using One-Dimensional Local Binary Pattern on Long-Term EEG
inferredcites →https://doi.org/10.1186/s40708-022-00159-3openalex-snapshot
Seizure classification with selected frequency bands and EEG montages: a Natural Language Processing approach
inferredcites →https://doi.org/10.1257/aer.91.2.73openalex-snapshot
In Search of Homo Economicus: Behavioral Experiments in 15 Small-Scale Societies
inferredcites →https://doi.org/10.1371/journal.pone.0076861openalex-snapshot
Predicting Risk-Taking Behavior from Prefrontal Resting-State Activity and Personality
inferredcites →https://doi.org/10.14704/nq.2018.16.3.1202openalex-snapshot
Decision-Making Mechanism under Economic Management Risk Based on Event-related Potential Neuroimaging Technique
inferredcites →https://doi.org/10.1523/jneurosci.1342-12.2013openalex-snapshot
Resting-State Functional Connectivity Predicts Impulsivity in Economic Decision-Making
inferredcites →https://doi.org/10.1556/2006.6.2017.055openalex-snapshot
Resting-state EEG activity related to impulsivity in gambling disorder
inferredcites →https://doi.org/10.19080/pbsij.2019.11.555814openalex-snapshot
Parietal EEG Theta/Beta Ratio as an Electrophysiological Marker for Extraversion-Related Differences
inferredcites →https://doi.org/10.24193/cbb.2017.21.03openalex-snapshot
Gender Differences in Brain Activity during Exposure to Emotional Film Clips: an EEG Study
inferredcites →https://doi.org/10.26599/bsa.2020.9050019openalex-snapshot
Demystifying signal processing techniques to extract resting-state EEG features for psychologists
inferredcites →https://doi.org/10.3389/fninf.2019.00073openalex-snapshot
Analysis of Decision-Making Process Using Methods of Quantitative Electroencephalography and Machine Learning Tools
inferredcites →https://doi.org/10.3389/fnins.2018.00138openalex-snapshot
Frontal Brain Asymmetry and Willingness to Pay
inferredcites →https://doi.org/10.3389/fnins.2018.00776openalex-snapshot
Power of Feedback-Induced Beta Oscillations Reflect Omission of Rewards: Evidence From an EEG Gambling Study
inferredcites →https://doi.org/10.3389/fnins.2020.00053openalex-snapshot
Editorial: Application of Neural Technology to Neuro-Management and Neuro-Marketing
inferredcites →https://doi.org/10.3389/fpsyt.2018.00239openalex-snapshot
Decision-Making Under Risk, but Not Under Ambiguity, Predicts Pathological Gambling in Discrete Types of Abstinent Substance Users
inferredcites →https://doi.org/10.3390/app10238662openalex-snapshot
Machine Learning Approaches for Detecting Parkinson’s Disease from EEG Analysis: A Systematic Review
inferredcites →https://doi.org/10.3390/app7121239openalex-snapshot
Review and Classification of Emotion Recognition Based on EEG Brain-Computer Interface System Research: A Systematic Review
inferredcites →https://doi.org/10.5296/jmr.v9i1.10374openalex-snapshot
Process Evaluation of an Applied Neuroeconomics Extension Course in Consulting and Management Based on Kirkpatrick's Model
inferredcites →https://doi.org/10.5772/intechopen.94398openalex-snapshot
Wavelets for EEG Analysis

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4779158openalex-extracted
Advancing Mobile Neurofinance: Eeg-Based User Authentication and Financial Advisory
inferred← citeshttps://doi.org/10.1007/s10072-026-08996-4openalex-snapshot
Machine-learning methods for epilepsy diagnosis and therapeutic prevention: advances, setbacks, and opportunities
inferred← citeshttps://doi.org/10.1016/j.apnr.2023.151723openalex-snapshot
Effectiveness of the acceptance and commitment therapy on resilience and quality of life in patients with post-acute COVID-19 syndrome
inferred← citeshttps://doi.org/10.1016/j.bandc.2024.106136openalex-snapshot
Electrophysiological correlates of cognitive control and performance monitoring in risk propensity: An event-related potential study
inferred← citeshttps://doi.org/10.1016/j.bspc.2023.105888openalex-snapshot
GA-CNN: Analyzing student’s cognitive skills with EEG data using a hybrid deep learning approach
inferred← citeshttps://doi.org/10.1038/s41598-025-19167-4openalex-snapshot
A machine learning approach for detection of claustrophobic brain activity in electroencephalography
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