scholarly journals Like/Dislike Prediction for Sport Shoes With Electroencephalography: An Application of Neuromarketing

2022 ◽  
Vol 15 ◽  
Author(s):  
Li Zeng ◽  
Mengsi Lin ◽  
Keyang Xiao ◽  
Jigan Wang ◽  
Hui Zhou
Keyword(s):  
Brain Region ◽  
Prediction Accuracy ◽  
Recognition Accuracy ◽  
Brain Regions ◽  
Research Field ◽  
Power Spectral ◽  
Self Reports ◽  
Product Sales ◽  
Future Work ◽  
Region Information

Neuromarketing is an emerging research field for prospective businesses on consumer’s preference. Consumer’s preference prediction based on electroencephalography (EEG) can reliably predict likes or dislikes of a product. However, the current EEG prediction and classification accuracy have yet to reach ideal level. In addition, it is still unclear how different brain region information and different features such as power spectral density, brain asymmetry, differential entropy, and Hjorth parameters affect the prediction accuracy. Our study shows that by taking footwear products as an example, the recognition accuracy of product likes or dislikes reaches 94.22%. Compared with other brain regions, the features of the frontal and occipital brain region obtained a higher prediction accuracy, but the fusion of the features of the whole brain region could improve the prediction accuracy of likes or dislikes even further. Future work would be done to correlate the EEG-based like or dislike prediction results with product sales and self-reports.

scholarly journals The Kynurenic Acid Analog SZR72 Enhances Neuronal Activity after Asphyxia but Is Not Neuroprotective in a Translational Model of Neonatal Hypoxic Ischemic Encephalopathy

2021 ◽  
Vol 22 (9) ◽  
pp. 4822
Author(s):  
Viktória Kovács ◽  
Gábor Remzső ◽  
Tímea Körmöczi ◽  
Róbert Berkecz ◽  
Valéria Tóth-Szűki ◽  
...  
Keyword(s):  
Neuronal Activity ◽  
Kynurenic Acid ◽  
Neuronal Damage ◽  
Brain Regions ◽  
Hypoxic Ischemic Encephalopathy ◽  
Hippocampal Field ◽  
Power Spectral ◽  
Density Values ◽  
Ischemic Encephalopathy

Hypoxic–ischemic encephalopathy (HIE) remains to be a major cause of long-term neurodevelopmental deficits in term neonates. Hypothermia offers partial neuroprotection warranting research for additional therapies. Kynurenic acid (KYNA), an endogenous product of tryptophan metabolism, was previously shown to be beneficial in rat HIE models. We sought to determine if the KYNA analog SZR72 would afford neuroprotection in piglets. After severe asphyxia (pHa = 6.83 ± 0.02, ΔBE = −17.6 ± 1.2 mmol/L, mean ± SEM), anesthetized piglets were assigned to vehicle-treated (VEH), SZR72-treated (SZR72), or hypothermia-treated (HT) groups (n = 6, 6, 6; Tcore = 38.5, 38.5, 33.5 °C, respectively). Compared to VEH, serum KYNA levels were elevated, recovery of EEG was faster, and EEG power spectral density values were higher at 24 h in the SZR72 group. However, instantaneous entropy indicating EEG signal complexity, depression of the visual evoked potential (VEP), and the significant neuronal damage observed in the neocortex, the putamen, and the CA1 hippocampal field were similar in these groups. In the caudate nucleus and the CA3 hippocampal field, neuronal damage was even more severe in the SZR72 group. The HT group showed the best preservation of EEG complexity, VEP, and neuronal integrity in all examined brain regions. In summary, SZR72 appears to enhance neuronal activity after asphyxia but does not ameliorate early neuronal damage in this HIE model.

scholarly journals Categorisation of EEG suppression using enhanced feature extraction for SUDEP risk assessment

2020 ◽  
Vol 20 (S12) ◽  
Author(s):  
Juan C. Mier ◽  
Yejin Kim ◽  
Xiaoqian Jiang ◽  
Guo-Qiang Zhang ◽  
Samden Lhatoo
Keyword(s):  
Sensitivity Analysis ◽  
Feature Extraction ◽  
Random Forest ◽  
Window Size ◽  
Extraction Process ◽  
Unexpected Death ◽  
Power Spectral ◽  
Eeg Data ◽  
Boosted Decision Trees ◽  
Future Work

Abstract Background Sudden Unexpected Death in Epilepsy (SUDEP) has increased in awareness considerably over the last two decades and is acknowledged as a serious problem in epilepsy. However, the scientific community remains unclear on the reason or possible bio markers that can discern potentially fatal seizures from other non-fatal seizures. The duration of postictal generalized EEG suppression (PGES) is a promising candidate to aid in identifying SUDEP risk. The length of time a patient experiences PGES after a seizure may be used to infer the risk a patient may have of SUDEP later in life. However, the problem becomes identifying the duration, or marking the end, of PGES (Tomson et al. in Lancet Neurol 7(11):1021–1031, 2008; Nashef in Epilepsia 38:6–8, 1997). Methods This work addresses the problem of marking the end to PGES in EEG data, extracted from patients during a clinically supervised seizure. This work proposes a sensitivity analysis on EEG window size/delay, feature extraction and classifiers along with associated hyperparameters. The resulting sensitivity analysis includes the Gradient Boosted Decision Trees and Random Forest classifiers trained on 10 extracted features rooted in fundamental EEG behavior using an EEG specific feature extraction process (pyEEG) and 5 different window sizes or delays (Bao et al. in Comput Intell Neurosci 2011:1687–5265, 2011). Results The machine learning architecture described above scored a maximum AUC score of 76.02% with the Random Forest classifier trained on all extracted features. The highest performing features included SVD Entropy, Petrosan Fractal Dimension and Power Spectral Intensity. Conclusion The methods described are effective in automatically marking the end to PGES. Future work should include integration of these methods into the clinical setting and using the results to be able to predict a patient’s SUDEP risk.

Semiautomatic brain region extraction: a method of parcellating brain regions from structural magnetic resonance images

NeuroImage ◽  
2004 ◽  
Vol 22 (4) ◽  
pp. 1492-1502 ◽  
Author(s):  
L.A Dade ◽  
F.Q Gao ◽  
N Kovacevic ◽  
P Roy ◽  
C Rockel ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Brain Region ◽  
Brain Regions ◽  
Magnetic Resonance Images ◽  
Region Extraction

scholarly journals Contextual Determinants of Employee Entrepreneurial Behavior in Support of Corporate Entrepreneurship: A Systematic Review and Research Agenda

2018 ◽  
Vol 26 (03) ◽  
pp. 285-326 ◽  
Author(s):  
Michael Mustafa ◽  
Fiona Gavin ◽  
Mathew Hughes
Keyword(s):  
Corporate Entrepreneurship ◽  
Research Field ◽  
Complex Nature ◽  
Contextual Influences ◽  
Entrepreneurial Behavior ◽  
Firm Level ◽  
Contextual Determinants ◽  
The Individual ◽  
Job Role ◽  
Future Work

The individual entrepreneurial behavior of employees represents one of the primary antecedents of Corporate Entrepreneurship. The complex nature of ‘employee entrepreneurial behavior’ suggests that a myriad of contextual influences act on the emergence of such behavior. It is imperative that theorists and practitioners alike understand both the subtle and sophisticated ways in which context influences employee entrepreneurial behavior. To address these issues and encourage future work, this study performs a systematic literature review to provide an overview of the field and examines the influence of the job/role, organizational/work and external contexts on employee entrepreneurial behavior. Findings suggest that employee entrepreneurial behavior is an emergent research field and that its behaviors can manifest themselves in different ways compared to firm-level entrepreneurial behaviors. We also show the sophisticated manner in which different types of context influence employee entrepreneurial behavior.

scholarly journals Convergent mosaic brain evolution is associated with the evolution of novel electrosensory systems in teleost fishes

2021 ◽  
Author(s):  
Erika L. Schumacher ◽  
Bruce A. Carlson
Keyword(s):  
Brain Region ◽  
Brain Size ◽  
Brain Evolution ◽  
Brain Regions ◽  
Torus Semicircularis ◽  
Micro Computed Tomography ◽  
Electrosensory System ◽  
Electric Fishes ◽  
Weakly Electric ◽  
Region Size

AbstractBrain region size generally scales allometrically with total brain size, but mosaic shifts in brain region size independent of brain size have been found in several lineages and may be related to the evolution of behavioral novelty. African weakly electric fishes (Mormyroidea) evolved a mosaically enlarged cerebellum and hindbrain, yet the relationship to their behaviorally novel electrosensory system remains unclear. We addressed this by studying South American weakly electric fishes (Gymnotiformes) and weakly electric catfishes (Synodontis spp.), which evolved varying aspects of electrosensory systems, independent of mormyroids. If the mormyroid mosaic increases are related to evolving an electrosensory system, we should find similar mosaic shifts in gymnotiforms and Synodontis. Using micro-computed tomography scans, we quantified brain region scaling for multiple electrogenic, electroreceptive, and non-electrosensing species. We found mosaic increases in cerebellum in all three electrogenic lineages relative to non-electric lineages and mosaic increases in torus semicircularis and hindbrain associated with the evolution of electrogenesis and electroreceptor type. These results show that evolving novel electrosensory systems is repeatedly and independently associated with changes in the sizes of individual brain regions independent of brain size, which suggests that selection can impact structural brain composition to favor specific regions involved in novel behaviors.

Neurocircuitries of Emotion Processing Affected in Major Depressive Disorder

2019 ◽  
pp. 101-114
Author(s):  
Anjali Sankar ◽  
Cynthia H.Y. Fu
Keyword(s):  
Major Depression ◽  
Predictive Accuracy ◽  
Emotion Processing ◽  
Affective State ◽  
Brain Regions ◽  
First Episode ◽  
Neuroimaging Data ◽  
Multivariate Pattern ◽  
Future Work ◽  
Hallmark Feature

Impairments in processing emotions are a hallmark feature of depression. Advances in neuroimaging techniques have rapidly improved our understanding of the pathophysiology underlying major depression. In this chapter, we provide an overview of influential neural models of emotion perception and regulation and discuss the neurocircuitries of emotion processing that are affected. Major depression is characterized by impairments in widespread brain regions that are evident in the first episode. Models have sought to distinguish the neural circuitry associated with recognition of the emotion, integration of somatic responses, and monitoring of the affective state. In particular, there has been a preponderance of research on the neurocircuitries affected during processing of mood-congruent negative emotional stimuli in depression. While neuroimaging correlates have been investigated and models proposed, these findings have had limited clinical applicability to date. Novel methods such as multivariate pattern recognition applied to neuroimaging data might enable identification of reliable, valid, and robust biomarkers with high predictive accuracy that can be applied to an individual. Last, we discuss avenues for extension and future work.

scholarly journals The specific absorption rate in different brain regions of rats exposed to electromagnetic plane waves

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Hao-Yu Wang ◽  
Chun-Fang Li ◽  
Chao Yu ◽  
Ji Dong ◽  
Yong Zou ◽  
...  
Keyword(s):  
Brain Region ◽  
Absorption Rate ◽  
Specific Absorption Rate ◽  
Brain Regions ◽  
Dose Effect ◽  
Whole Body ◽  
Polarization Direction ◽  
Whole Brain ◽  
Specific Absorption ◽  
Effect Relationship

Abstract Accurate dosimetry of a specific brain region in rats exposed to an electromagnetic field (EMF) is essential for studies focusing on dose-effect relationship of the region. However, only dosimetry of whole brain or whole body were evaluated in most of previous studies. In this study, a numerical voxel rat model with 10 segmented brain regions was constructed. Then, the effects of frequency, incidence direction, and E-polarization direction of plane wave EMF on brain region averaged specific absorption rate (BRSAR) of rats were investigated. At last, the reliability of using whole-body averaged SAR (WBDSAR) and whole-brain averaged SAR (WBRSAR) as estimations of BRSAR were also evaluated. Our results demonstrated that the BRSAR depended on the frequency, incidence direction, and E-polarization direction of the EMF. Besides, the largest deviation could be up to 13.1 dB between BRSAR and WBDSAR and 9.59 dB between BRSAR and WBRSAR. The results suggested that to establish an accurate dose-effect relationship, the variance of the BRSAR induced by alteration of frequency, incidence direction, and E-polarization direction of EMF should be avoided or carefully evaluated. Furthermore, the use of WBDSAR and WBRSAR as estimations of BRSAR should be restricted to certain conditions such that the deviations are not too large.

scholarly journals Al-Based Nano-Sized Composite Energetic Materials (Nano-CEMs): Preparation, Characterization, and Performance

Nanomaterials ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 1039 ◽  
Author(s):  
Weiqiang Pang ◽  
Xuezhong Fan ◽  
Ke Wang ◽  
Yimin Chao ◽  
Huixiang Xu ◽  
...  
Keyword(s):  
Energetic Materials ◽  
Recent Progress ◽  
Functional Materials ◽  
Research Field ◽  
Preparation Methods ◽  
Existing Problems ◽  
And Performance ◽  
Future Work ◽  
Application Prospects

As one of the new types of functional materials, nano-sized composite energetic materials (nano-CEMs) possess many advantages and broad application prospects in the research field of explosives and propellants. The recent progress in the preparation and performance characterization of Al-based nano-CEMs has been reviewed. The preparation methods and properties of Al-based nano-CEMs are emphatically analyzed. Special emphasis is focused on the improved performances of Al-based nano-CEMs, which are different from those of conventional micro-sized composite energetic materials (micro-CEMs), such as thermal decomposition and hazardous properties. The existing problems and challenges for the future work on Al-based nano-CEMs are discussed.

Emotional Speech Recognition Based on Weighted Distance Optimization System

2020 ◽  
Vol 34 (11) ◽  
pp. 2050027
Author(s):  
Mona Nagy ElBedwehy ◽  
G. M. Behery ◽  
Reda Elbarougy
Keyword(s):  
Speech Recognition ◽  
Recognition Accuracy ◽  
Gaussian Mixture ◽  
Research Field ◽  
Superior Performance ◽  
Emotional States ◽  
Emotional Speech ◽  
Weighted Distance ◽  
Human Emotion ◽  
Emotional Speech Recognition

Human emotion plays a major role in expressing their feelings through speech. Emotional speech recognition is an important research field in the human–computer interaction. Ultimately, the endowing machines that perceive the users’ emotions will enable a more intuitive and reliable interaction.The researchers presented many models to recognize the human emotion from the speech. One of the famous models is the Gaussian mixture model (GMM). Nevertheless, GMM may sometimes have one or more of its components as ill-conditioned or singular covariance matrices when the number of features is high and some features are correlated. In this research, a new system based on a weighted distance optimization (WDO) has been developed for recognizing the emotional speech. The main purpose of the WDO system (WDOS) is to address the GMM shortcomings and increase the recognition accuracy. We found that WDOS has achieved considerable success through a comparative study of all emotional states and the individual emotional state characteristics. WDOS has a superior performance accuracy of 86.03% for the Japanese language. It improves the Japanese emotion recognition accuracy by 18.43% compared with GMM and [Formula: see text]-mean.

scholarly journals Medial Orbitofrontal Cortex Is Associated with Fatigue Sensation

2010 ◽  
Vol 2010 ◽  
pp. 1-5 ◽  
Author(s):  
Seiki Tajima ◽  
Shigeyuki Yamamoto ◽  
Masaaki Tanaka ◽  
Yosky Kataoka ◽  
Masao Iwase ◽  
...  
Keyword(s):  
Positron Emission Tomography ◽  
Orbitofrontal Cortex ◽  
Brain Region ◽  
Statistical Parametric Mapping ◽  
Brain Regions ◽  
Mapping Method ◽  
Emission Tomography ◽  
Neural Basis ◽  
Positron Emission ◽  
The Brain

Fatigue is an indispensable bioalarm to avoid exhaustive state caused by overwork or stresses. It is necessary to elucidate the neural mechanism of fatigue sensation for managing fatigue properly. We performedH2O  15positron emission tomography scans to indicate neural activations while subjects were performing 35-min fatigue-inducing task trials twice. During the positron emission tomography experiment, subjects performed advanced trail-making tests, touching the target circles in sequence located on the display of a touch-panel screen. In order to identify the brain regions associated with fatigue sensation, correlation analysis was performed using statistical parametric mapping method. The brain region exhibiting a positive correlation in activity with subjective sensation of fatigue, measured immediately after each positron emission tomography scan, was located in medial orbitofrontal cortex (Brodmann's area 10/11). Hence, the medial orbitofrontal cortex is a brain region associated with mental fatigue sensation. Our findings provide a new perspective on the neural basis of fatigue.

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