Methods of Neurotherapy

Kropotov, Juri D.

doi:10.1016/b978-0-12-374512-5.00023-2

Cited by 98 publications

(162 citation statements)

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“…The limbic system consists of the orbitofrontal cortex, insular cortex, anterior and posterior cingulate cortices, parahippocampal gyrus, hippocampal formation, amygdala, basal forebrain, and hypothalamus51. This region is in charge of emotions and memory52 and reflects the levels of cognitive activity53. It is speculated that video commercials with a narrative structure can produce high levels of emotion and cognitive activity.…”

Section: Discussionmentioning

confidence: 99%

EEG Spectral Dynamics of Video Commercials: Impact of the Narrative on the Branding Product Preference

Wang

Chang

Chuang

2016

Sci Rep

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Neuromarketing has become popular and received a lot of attention. The quality of video commercials and the product information they convey to consumers is a hotly debated topic among advertising agencies and product advertisers. This study explored the impact of advertising narrative and the frequency of branding product exposures on the preference for the commercial and the branding product. We performed electroencephalography (EEG) experiments on 30 subjects while they watched video commercials. The behavioral data indicated that commercials with a structured narrative and containing multiple exposures of the branding products had a positive impact on the preference for the commercial and the branding product. The EEG spectral dynamics showed that the narratives of video commercials resulted in higher theta power of the left frontal, bilateral occipital region, and higher gamma power of the limbic system. The narratives also induced significant cognitive integration-related beta and gamma power of the bilateral temporal regions and the parietal region. It is worth noting that the video commercials with a single exposure of the branding products would be indicators of attention. These new findings suggest that the presence of a narrative structure in video commercials has a critical impact on the preference for branding products.

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Section: Discussionmentioning

confidence: 99%

EEG Spectral Dynamics of Video Commercials: Impact of the Narrative on the Branding Product Preference

Wang

Chang

Chuang

2016

Sci Rep

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“…is a measure of distance between two normal distributions inspired by the z-score [9]. The distance has large values when the mean difference between two populations is large, and the standard deviations of both distributions are small; the two populations can then be easily distinguished.…”

Section: Separability Criterionmentioning

confidence: 99%

“…An EEG recording is usually characterized by the presence of activity on specific frequency bands: 0.1-4 Hz (), 4-8 Hz (), 8-13 (), 13-30 () and 30-100 () [9,10]. To distinguish between AD patients and healthy patients, studies traditionally analyse the standard frequency bands [11,12], or extend the analysis to the entire frequency range between 4 and 30 Hz [8].…”

Section: Compared To Other Systems Like Functional Magnetic Resonancementioning

confidence: 99%

A hybrid feature selection approach for the early diagnosis of Alzheimer’s disease

Gallego-Jutglà¹,

Solé-Casals²,

Vialatte³

et al. 2015

J. Neural Eng.

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Objective. Recently, significant advances have been made in the early diagnosis of Alzheimer's disease from EEG. However, choosing suitable measures is a challenging task. Among other measures, frequency Relative Power and loss of complexity have been used with promising results. In the present study we investigate the early diagnosis of AD using synchrony measures and frequency Relative Power on EEG signals, examining the changes found in different frequency ranges. Approach. We first explore the use of a single feature for computing the classification rate, looking for the best frequency range. Then, we present a multiple feature classification system that outperforms all previous results using a feature selection strategy.These two approaches are tested in two different databases, one containing MCI and healthy subjects (patients age: 71.9 ± 10.2, healthy subjects age: 71.7 ± 8.3), and the other containing Mild AD and healthy subjects (patients age: 77.6 ± 10.0; healthy subjects age: 69.4± 11.5).Main Results. Using a single feature to compute classification rates we achieve a performance of 78.33% for the MCI data set and of 97.56 % for Mild AD. Results are clearly improved using the multiple feature classification, where a classification rate of 95% is found for the MCI data set using 11 features, and 100% for the Mild AD data set using 4 features. Significance. The new features selection method described in this work may be a reliable tool that could help to design a realistic system that does not require prior knowledge of a patient's status. With that aim, we explore the standardization of features for MCI and Mild AD data sets with promising results.

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“…Additionally, although EEG monitors the ion currents associated with neural activity, both inhibitory and excitatory potentials may be detected as negative or positive depending on where they are generated [32,33]. For each subject and protocol, polarity was typically established from the first repetition and few subjects crossed from negative to positive.…”

Section: Resultsmentioning

confidence: 99%

Cortical Activity during a Highly-Trained Resistance Exercise Movement Emphasizing Force, Power or Volume

et al. 2012

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Cortical activity is thought to reflect the biomechanical properties of movement (e.g., force or velocity of movement), but fatigue and movement familiarity are important factors that require additional consideration in electrophysiological research. The purpose of this within-group quantitative electroencephalogram (EEG) investigation was to examine changes in cortical activity amplitude and location during four resistance exercise movement protocols emphasizing rate (PWR), magnitude (FOR), or volume (VOL) of force production, while accounting for movement familiarity and fatigue. EEG signals were recorded during each complete repetition and were then grouped by functional region, processed to eliminate artifacts, and averaged to compare overall differences in the magnitude and location of cortical activity between protocols over the course of six sets. Biomechanical, biochemical, and exertional data were collected to contextualize electrophysiological data. The most fatiguing protocols were accompanied by the greatest increases in cortical activity. Furthermore, despite non-incremental loading and lower force levels, VOL displayed the largest increases in cortical activity over time and greatest motor and sensory activity overall. Our findings suggest that cortical activity is strongly related to aspects of fatigue during a high intensity resistance exercise movement.

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Methods of Neurotherapy

Cited by 98 publications

References 0 publications

EEG Spectral Dynamics of Video Commercials: Impact of the Narrative on the Branding Product Preference

EEG Spectral Dynamics of Video Commercials: Impact of the Narrative on the Branding Product Preference

A hybrid feature selection approach for the early diagnosis of Alzheimer’s disease

Cortical Activity during a Highly-Trained Resistance Exercise Movement Emphasizing Force, Power or Volume

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