title: Effect of Subliminal Lexical Priming on the Subjective Perception of Images: A Machine Learning Approach.
abstract: The purpose of the study is to examine the effect of subliminal priming in terms of the perception of images influenced by words with positive, negative, and neutral emotional content, through electroencephalograms (EEGs). Participants were instructed to rate how much they like the stimuli images, on a 7-point Likert scale, after being subliminally exposed to masked lexical prime words that exhibit positive, negative, and neutral connotations with respect to the images. Simultaneously, the EEGs were recorded. Statistical tests such as repeated measures ANOVAs and two-tailed paired-samples t-tests were performed to measure significant differences in the likability ratings among the three prime affect types; the results showed a strong shift in the likeness judgment for the images in the positively primed condition compared to the other two. The acquired EEGs were examined to assess the difference in brain activity associated with the three different conditions. The consistent results obtained confirmed the overall priming effect on participants' explicit ratings. In addition, machine learning algorithms such as support vector machines (SVMs), and AdaBoost classifiers were applied to infer the prime affect type from the ERPs. The highest classification rates of 95.0% and 70.0% obtained respectively for average-trial binary classifier and average-trial multi-class further emphasize that the ERPs encode information about the different kinds of primes.
authors: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore.
authors: Dhanya Menoth
authors: DM
authors: Mohan
authors: INRIA Sophia Antipolis, Sophia Antipolis, France.
authors: Parmod
authors: P
authors: Kumar
authors: Okinawa Institute of Science and Technology, Okinawa, Japan.
authors: Faisal
authors: F
authors: Mahmood
authors: Center for Cognitive Neuroscience, Duke-NUS Graduate Medical School, Singapore, Singapore.
authors: Kian Foong
authors: KF
authors: Wong
authors: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore.
authors: Abhishek
authors: A
authors: Agrawal
authors: University of British Columbia, Vancouver, Canada.
authors: Mohamed
authors: M
authors: Elgendi
authors: University of Wisconsin-Madison, Madison, United States of America.
authors: Rohit
authors: R
authors: Shukla
authors: Linguistics and Multilingual Studies, School of Humanities and Social Sciences, Nanyang Technological University, Singapore, Singapore.
authors: Natania
authors: N
authors: Ang
authors: Linguistics and Multilingual Studies, School of Humanities and Social Sciences, Nanyang Technological University, Singapore, Singapore.
authors: April
authors: A
authors: Ching
authors: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore.
authors: Justin
authors: J
authors: Dauwels
authors: Linguistics and Multilingual Studies, School of Humanities and Social Sciences, Nanyang Technological University, Singapore, Singapore.
authors: Alice H D
authors: AH
authors: Chan
mesh_terms: D000328:Adult; D000339:Affect; D000465:Algorithms; D000704:Analysis of Variance; D004569:Electroencephalography / Q000379:methods; D004644:Emotions; D005071:Evoked Potentials / Q000502:physiology*; D005260:Female; D006801:Humans; D007600:Judgment; D007802:Language; D000069550:Machine Learning; D008297:Male; D015233:Models, Statistical; D016011:Normal Distribution; D010364:Pattern Recognition, Visual / Q000502:physiology*; D010465:Perception; D011930:Reaction Time; D013360:Subliminal Stimulation; D060388:Support Vector Machine; D055815:Young Adult