scholarly journals The Story of Taste: Using EEGs and Self-Reports to Understand Consumer Choice

2012 ◽  
Vol 2 (1) ◽  
Author(s):  
Charnetta Brown ◽  
◽  
Adriane Randolph ◽  
Janee Burkhalter ◽  
◽  
...  
Keyword(s):  
Cost Saving ◽  
Consumer Choice ◽  
Brain Activity ◽  
Private Label ◽  
Consumer Decisions ◽  
Electrical Brain Activity ◽  
Self Reports ◽  
Manufacturer Brand ◽  
Reported Data

The authors investigate consumers’ willingness to switch from a preferred manufacturer brand to an unfamiliar private-label brand if taste is perceived as identical. Consumer decisions are examined through recordings of electrical brain activity in the form of electroencephalograms (EEGs) and self-reported data captured in surveys. Results reveal a willingness of consumers to switch to a less-expensive brand when the quality is perceived to be the same as the more expensive counterpart. Cost saving options for consumers and advertising considerations for managers are discussed.

scholarly journals Personalized Biometrics of Physical Pain Agree with Psychophysics by Participants with Sensory over Responsivity

2021 ◽  
Vol 11 (2) ◽  
pp. 93
Author(s):  
Jihye Ryu ◽  
Tami Bar-Shalita ◽  
Yelena Granovsky ◽  
Irit Weissman-Fogel ◽  
Elizabeth B. Torres
Keyword(s):  
General Population ◽  
Brain Activity ◽  
A Priori ◽  
Summary Statistics ◽  
Physical Pain ◽  
New Methods ◽  
Self Reports ◽  
Theoretical Population ◽  
The Moment ◽  
Reported Data

The study of pain requires a balance between subjective methods that rely on self-reports and complementary objective biometrics that ascertain physical signals associated with subjective accounts. There are at present no objective scales that enable the personalized assessment of pain, as most work involving electrophysiology rely on summary statistics from a priori theoretical population assumptions. Along these lines, recent work has provided evidence of differences in pain sensations between participants with Sensory Over Responsivity (SOR) and controls. While these analyses are useful to understand pain across groups, there remains a need to quantify individual differences more precisely in a personalized manner. Here we offer new methods to characterize pain using the moment-by-moment standardized fluctuations in EEG brain activity centrally reflecting the person’s experiencing temperature-based stimulation at the periphery. This type of gross data is often disregarded as noise, yet here we show its utility to characterize the lingering sensation of discomfort raising to the level of pain, individually, for each participant. We show fundamental differences between the SOR group in relation to controls and provide an objective account of pain congruent with the subjective self-reported data. This offers the potential to build a standardized scale useful to profile pain levels in a personalized manner across the general population.

scholarly journals Towards a Brain-Sensitive Intelligent Tutoring System: Detecting Emotions from Brainwaves

2011 ◽  
Vol 2011 ◽  
pp. 1-13 ◽  
Author(s):  
Alicia Heraz ◽  
Claude Frasson
Keyword(s):  
Brain Activity ◽  
Intelligent Tutoring ◽  
Intelligent Tutoring System ◽  
Emotional Valence ◽  
Tutoring System ◽  
Electrical Brain Activity ◽  
Self Reports ◽  
Natural Data ◽  
Emotional Dimensions ◽  
The Individual

This paper proposes and evaluates a multiagents system called NORA that predicts emotional attributes from learners' brainwaves within an intelligent tutoring system. The measurements from the electrical brain activity of the learner are combined with information about the learner's emotional attributes. Electroencephalogram was used to measure brainwaves and self-reports to measure the three emotional dimensions: pleasure, arousal, and dominance, the eight emotions occurring during learning: anger, boredom, confusion, contempt curious, disgust, eureka, and frustration, and the emotional valence positive for learning and negative for learning. The system is evaluated on natural data, and it achieves an accuracy of over 63%, significantly outperforming classification using the individual modalities and several other combination schemes.

scholarly journals Personalized Biometrics of Physical Pain Agree with Its Psychological Perception by Participants with Sensory Over Responsivity

2020 ◽  
Author(s):  
Jihye Ryu ◽  
Tami Bar-Shalita ◽  
Yelena Granovsky ◽  
Irit Weissman-Fogel ◽  
Elizabeth B. Torres
Keyword(s):  
General Population ◽  
Brain Activity ◽  
A Priori ◽  
Summary Statistics ◽  
Physical Pain ◽  
New Methods ◽  
Self Reports ◽  
Theoretical Population ◽  
The Moment ◽  
Reported Data

The study of pain requires a balance between subjective methods that rely on self-reports and complementary objective biometrics that ascertain physical signals associated with subjective accounts. There are at present no objective scales that enable the personalized assessment of pain, as most work involving electrophysiology rely on summary statistics from a priori theoretical population assumptions. Along these lines, recent work has provided evidence of differences in pain sensations between participants with Sensory Over Responsivity (SOR) and controls. While these analyses are useful to understand pain across groups, there remains a need to quantify individual differences more precisely in a personalized manner. Here we offer new methods to characterize pain using the moment-by-moment standardized fluctuations in EEG brain activity centrally reflecting the person’s experiencing temperature-based stimulation at the periphery. This type of gross data is often disregarded as noise, yet here we show its utility to characterize the lingering sensation of discomfort raising to the level of pain, individually, for each participant. We show fundamental differences between the SOR group in relation to controls and provide an objective account of pain congruent with the subjective self-reported data. This offers the potential to build a standardized scale useful to profile pain levels in a personalized manner across the general population.

Skipping Breakfast Affects the Early Steps of Cognitive Processing

2019 ◽  
Vol 33 (2) ◽  
pp. 109-118
Author(s):  
Andrés Antonio González-Garrido ◽  
Jacobo José Brofman-Epelbaum ◽  
Fabiola Reveca Gómez-Velázquez ◽  
Sebastián Agustín Balart-Sánchez ◽  
Julieta Ramos-Loyo
Keyword(s):  
Working Memory ◽  
Cognitive Processing ◽  
Task Difficulty ◽  
Brain Activity ◽  
Reaction Times ◽  
Brain Potentials ◽  
Brain Functioning ◽  
Attentional Processes ◽  
Electrical Brain Activity ◽  
Skipping Breakfast

Abstract. It has been generally accepted that skipping breakfast adversely affects cognition, mainly disturbing the attentional processes. However, the effects of short-term fasting upon brain functioning are still unclear. We aimed to evaluate the effect of skipping breakfast on cognitive processing by studying the electrical brain activity of young healthy individuals while performing several working memory tasks. Accordingly, the behavioral results and event-related brain potentials (ERPs) of 20 healthy university students (10 males) were obtained and compared through analysis of variances (ANOVAs), during the performance of three n-back working memory (WM) tasks in two morning sessions on both normal (after breakfast) and 12-hour fasting conditions. Significantly fewer correct responses were achieved during fasting, mainly affecting the higher WM load task. In addition, there were prolonged reaction times with increased task difficulty, regardless of breakfast intake. ERP showed a significant voltage decrement for N200 and P300 during fasting, while the amplitude of P200 notably increased. The results suggest skipping breakfast disturbs earlier cognitive processing steps, particularly attention allocation, early decoding in working memory, and stimulus evaluation, and this effect increases with task difficulty.

An Adaptive and Learning System for Feedback-Controlled Evoked Response Studies

1981 ◽  
Vol 20 (03) ◽  
pp. 169-173
Author(s):  
J. Wagner ◽  
G. Pfurtscheixer
Keyword(s):  
Brain Activity ◽  
Evoked Response ◽  
Learning System ◽  
Time Interval ◽  
Electrical Brain Activity ◽  
Long Time ◽  
The Subject ◽  
Eeg Power ◽  
Stimulation System ◽  
Background Eeg

The shape, latency and amplitude of changes in electrical brain activity related to a stimulus (Evoked Potential) depend both on the stimulus parameters and on the background EEG at the time of stimulation. An adaptive, learnable stimulation system is introduced, whereby the subject is stimulated (e.g. with light), whenever the EEG power is subthreshold and minimal. Additionally, the system is conceived in such a way that a certain number of stimuli could be given within a particular time interval. Related to this time criterion, the threshold specific for each subject is calculated at the beginning of the experiment (preprocessing) and adapted to the EEG power during the processing mode because of long-time fluctuations and trends in the EEG. The process of adaptation is directed by a table which contains the necessary correction numbers for the threshold. Experiences of the stimulation system are reflected in an automatic correction of this table. Because the corrected and improved table is stored after each experiment and is used as the starting table for the next experiment, the system >learns<. The system introduced here can be used both for evoked response studies and for alpha-feedback experiments.

Automated System for Epileptic Seizures Prediction based on Multi-Channel Recordings of Electrical Brain Activity

2018 ◽  
pp. 115-122 ◽  
Author(s):  
V. A. Maksimenko ◽  
A. A. Harchenko ◽  
A. Lüttjohann
Keyword(s):  
Epileptic Seizure ◽  
Brain Activity ◽  
Epileptic Seizures ◽  
Automated System ◽  
Brain Computer Interfaces ◽  
Electrical Brain Activity ◽  
Computer Interfaces ◽  
Prediction And Prevention ◽  
The Brain

Introduction: Now the great interest in studying the brain activity based on detection of oscillatory patterns on the recorded data of electrical neuronal activity (electroencephalograms) is associated with the possibility of developing brain-computer interfaces. Braincomputer interfaces are based on the real-time detection of characteristic patterns on electroencephalograms and their transformation  into commands for controlling external devices. One of the important areas of the brain-computer interfaces application is the control of the pathological activity of the brain. This is in demand for epilepsy patients, who do not respond to drug treatment.Purpose: A technique for detecting the characteristic patterns of neural activity preceding the occurrence of epileptic seizures.Results:Using multi-channel electroencephalograms, we consider the dynamics of thalamo-cortical brain network, preceded the occurrence of an epileptic seizure. We have developed technique which allows to predict the occurrence of an epileptic seizure. The technique has been implemented in a brain-computer interface, which has been tested in-vivo on the animal model of absence epilepsy.Practical relevance:The results of our study demonstrate the possibility of epileptic seizures prediction based on multichannel electroencephalograms. The obtained results can be used in the development of neurointerfaces for the prediction and prevention of seizures of various types of epilepsy in humans. 

scholarly journals Delta band activity contributes to the identification of command following in disorder of consciousness

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gonzalo Rivera-Lillo ◽  
Emmanuel A. Stamatakis ◽  
Tristan A. Bekinschtein ◽  
David K. Menon ◽  
Srivas Chennu
Keyword(s):  
Functional Neuroimaging ◽  
Brain Activity ◽  
Disorder Of Consciousness ◽  
Fine Grained ◽  
Electrical Brain Activity ◽  
Delta Band ◽  
Delta Modulation ◽  
Command Following ◽  
Band Activity

AbstractThe overt or covert ability to follow commands in patients with disorders of consciousness is considered a sign of awareness and has recently been defined as cortically mediated behaviour. Despite its clinical relevance, the brain signatures of the perceptual processing supporting command following have been elusive. This multimodal study investigates the temporal spectral pattern of electrical brain activity to identify features that differentiated healthy controls from patients both able and unable to follow commands. We combined evidence from behavioural assessment, functional neuroimaging during mental imagery and high-density electroencephalography collected during auditory prediction, from 21 patients and 10 controls. We used a penalised regression model to identify command following using features from electroencephalography. We identified seven well-defined spatiotemporal signatures in the delta, theta and alpha bands that together contribute to identify DoC subjects with and without the ability to follow command, and further distinguished these groups of patients from controls. A fine-grained analysis of these seven signatures enabled us to determine that increased delta modulation at the frontal sensors was the main feature in command following patients. In contrast, higher frequency theta and alpha modulations differentiated controls from both groups of patients. Our findings highlight a key role of spatiotemporally specific delta modulation in supporting cortically mediated behaviour including the ability to follow command. However, patients able to follow commands nevertheless have marked differences in brain activity in comparison with healthy volunteers.

The application of parametric multichannel spectral estimates in the study of electrical brain activity

1985 ◽  
Vol 51 (4) ◽  
pp. 239-247 ◽  
Author(s):  
P. J. Franaszczuk ◽  
K. J. Blinowska ◽  
M. Kowalczyk
Keyword(s):  
Brain Activity ◽  
Electrical Brain Activity ◽  
Spectral Estimates

scholarly journals Determinants of Ready-to-eat Products Purchase Intentions: An Empirical Study among the Italian Consumers

HortScience ◽  
2018 ◽  
Vol 53 (5) ◽  
pp. 656-660 ◽  
Author(s):  
Filippo Sgroi ◽  
Fabrizio Piraino ◽  
Enrica Donia
Keyword(s):  
Food Consumption ◽  
Consumer Choice ◽  
Recent Literature ◽  
Nuclear Family ◽  
Raw Materials ◽  
Purchase Intentions ◽  
Classical Literature ◽  
Time Saving ◽  
Consumer Decisions ◽  
The City

The considerable diffusion of ready-to-eat products has focused attention on the reasons for their increasingly prominent success in the market. Although their prices are much higher than the prices of simple raw materials, their consumption has increased rapidly and with no end in sight, a situation that has challenged the conclusions of the classical literature on the importance of price and/or income in consumer decisions. In fact, more recent literature has broadened the classical vision by introducing potential additional variables that could influence consumer choice of certain foods. These variables, however, are not always easy and clear to identify because they reflect the cultural characteristics of a society. For this reason, the French scholar Malassis has introduced the concept of a model of food consumption, which, in fact, stems from a concept of food consumption as driven by factors that are not the same for all the societies that might be studied. Among these variables, regarding the consumption of ready-to-eat products, a factor that certainly acts as a driving force in an increasingly frenetic and dynamic society is the time saving that they are able to provide. Thus, it was considered essential to analyze this in a concrete way, through the variance analysis of a sample of 77 subjects resident in the city of Palermo, noting their characteristics in terms of age, education level, and number of nuclear family members. The results obtained indicate that subjects who consumed ready-to-eat products at a higher frequency belonged to a higher age group, had a higher level of education, and belonged to a family that was not particularly numerous. With these results, it can be stated that the consumption of ready-to-eat products is influenced by people’s need to optimize their available time, considered as a real, scarce resource.

Enhancement of Eye Motor Response and Electrical Brain Activity during Noise and Vibration in Rabbits

1982 ◽  
Vol 90 (1) ◽  
pp. 130-138 ◽  
Author(s):  
Ilmari Pyykkö ◽  
Izuru Matsuoka ◽  
Shinsuke Ito ◽  
Manabe Hinoki
Keyword(s):  
Motor Response ◽  
Optokinetic Nystagmus ◽  
Dorsal Hippocampus ◽  
Brain Activity ◽  
Noise And Vibration ◽  
Implanted Electrodes ◽  
Theta Waves ◽  
Electrical Brain Activity ◽  
The Relationship ◽  
Electroencephalogram Eeg

The relationship between electroencephalogram (EEG) and eye movements was studied in rabbits during optokinetic, vestibular, and optovestibular tests. EEG was recorded through permanently implanted electrodes. Exposure to noise and vibration increased the frequency and the velocity of optokinetic nystagmus (OKN). The increase was greater during vibration but greatest during combined noise and vibration. EEG activity was closely linked to changes in OKN and was particularly evident with the appearance of theta waves in the dorsal hippocampus. Also, rotation of the rabbit produced considerable activation in the EEG.

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