scholarly journals Music with Concurrent Saliences of Musical Features Elicits Stronger Brain Responses

2021 ◽  
Vol 11 (19) ◽  
pp. 9158
Author(s):  
Lorenzo J. Tardón ◽  
Ignacio Rodríguez-Rodríguez ◽  
Niels T. Haumann ◽  
Elvira Brattico ◽  
Isabel Barbancho
Keyword(s):  
Statistical Analysis ◽  
Real Life ◽  
Acoustic Features ◽  
Eeg Signals ◽  
Experimental Conditions ◽  
Brain Responses ◽  
Spectral Flux ◽  
Initial Hypothesis ◽  
Brain Reaction

Brain responses are often studied under strictly experimental conditions in which electroencephalograms (EEGs) are recorded to reflect reactions to short and repetitive stimuli. However, in real life, aural stimuli are continuously mixed and cannot be found isolated, such as when listening to music. In this audio context, the acoustic features in music related to brightness, loudness, noise, and spectral flux, among others, change continuously; thus, significant values of these features can occur nearly simultaneously. Such situations are expected to give rise to increased brain reaction with respect to a case in which they would appear in isolation. In order to assert this, EEG signals recorded while listening to a tango piece were considered. The focus was on the amplitude and time of the negative deflation (N100) and positive deflation (P200) after the stimuli, which was defined on the basis of the selected music feature saliences, in order to perform a statistical analysis intended to test the initial hypothesis. Differences in brain reactions can be identified depending on the concurrence (or not) of such significant values of different features, proving that coterminous increments in several qualities of music influence and modulate the strength of brain responses.

scholarly journals How Relevant Is It to Use Mineral Proxies to Mimic the Atmospheric Reactivity of Natural Dust Samples? A Reactivity Study Using SO2 as Probe Molecule

Minerals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 282
Author(s):  
Darya Urupina ◽  
Manolis N. Romanias ◽  
Frederic Thevenet
Keyword(s):  
High Performance ◽  
Real Life ◽  
Complex Mixtures ◽  
Experimental Conditions ◽  
The Real ◽  
Atmospheric Processes ◽  
Real Effects ◽  
Mineral Aerosols ◽  
Life Impact ◽  
Reactivity Study

The experimental investigation of heterogeneous atmospheric processes involving mineral aerosols is extensively performed in the literature using proxy materials. In this work we questioned the validity of using proxies such as Fe2O3, FeOOH, Al2O3, MgO, CaO, TiO2, MnO2, SiO2, and CaCO3 to represent the behavior of complex mixtures of minerals, such as natural desert and volcanic dusts. Five volcanic dusts and three desert dusts were compared to a number of metal oxides, commonly used in the literature to mimic the behavior of desert dusts in the ability to form sulfites and sulfates on the surface exposed to SO2 gas. First, all samples were aged at room temperature, atmospheric pressure, under controlled experimental conditions of 175 ppm SO2 for 1 h under 30% of relative humidity. Second, they were extracted with 1% formalin and analyzed by High-Performance Liquid Chromatography (HPLC) to quantify and compare the amount of sulfites and sulfates formed on their surfaces. It was evidenced that under the experimental conditions of this study neither one selected pure oxide nor a mixture of oxides can adequately typify the behavior of complex mixtures of natural minerals. Therefore, to evaluate the real-life impact of natural dust on atmospheric processes it is of vital importance to work directly with the natural samples, both to observe the real effects of desert and volcanic dusts and to evaluate the relevancy of proposed proxies.

Information-based decoding of the coupling among human brain activity and movement paths

2021 ◽  
pp. 1-10
Author(s):  
Shahul Mujib Kamal ◽  
Norazryana Mat Dawi ◽  
Hamidreza Namazi
Keyword(s):  
Brain Activity ◽  
Point Of View ◽  
Physiological Signals ◽  
Human Walking ◽  
Eeg Signals ◽  
Rehabilitation Science ◽  
Information Contents ◽  
First Time ◽  
The Brain ◽  
Brain Reaction

BACKGROUND: Walking like many other actions of a human is controlled by the brain through the nervous system. In fact, if a problem occurs in our brain, we cannot walk correctly. Therefore, the analysis of the coupling of brain activity and walking is very important especially in rehabilitation science. The complexity of movement paths is one of the factors that affect human walking. For instance, if we walk on a path that is more complex, our brain activity increases to adjust our movements. OBJECTIVE: This study for the first time analyzed the coupling of walking paths and brain reaction from the information point of view. METHODS: We analyzed the Shannon entropy for electroencephalography (EEG) signals versus the walking paths in order to relate their information contents. RESULTS: According to the results, walking on a path that contains more information causes more information in EEG signals. A strong correlation (p= 0.9999) was observed between the information contents of EEG signals and walking paths. Our method of analysis can also be used to investigate the relation among other physiological signals of a human and walking paths, which has great benefits in rehabilitation science.

Brain responses to peer feedback in social media are modulated by valence and personality dimensions in late adolescence

2021 ◽  
Author(s):  
Patrik Wikman ◽  
Mona Moisala ◽  
Artturi Ylinen ◽  
Jallu Lindblom ◽  
Sointu Leikas ◽  
...  
Keyword(s):  
Social Media ◽  
Prefrontal Cortex ◽  
Negative Feedback ◽  
Media Use ◽  
Peer Feedback ◽  
Real Life ◽  
Superior Temporal Gyrus ◽  
Occipital Cortex ◽  
Social Media Use ◽  
Brain Responses

Previous studies have examined the neural correlates of receiving negative feedback from peers during virtual social interaction in young people. However, there is a lack of studies using platforms adolescents use in daily life. In the present study, 92 participants ages 17 to 20 performed a task that involved receiving positive and negative feedback from peers in a Facebook-like platform, while brain activity was measured using functional magnetic resonance imaging (fMRI). We also studied the effects of real-life habits of social media use on neural sensitivity to negative feedback. Peer feedback was shown to activate clusters in the ventrolateral prefrontal cortex (VLPFC), the medial prefrontal cortex (MPFC), superior temporal gyrus and sulcus (STG/STS), and occipital cortex (OC). Negative feedback was related to greater activity in the VLPFC, MPFC, and anterior insula than positive feedback, replicating previous findings on peer feedback and social rejection. Habits of social media use did not correlate with brain responses to negative feedback.

Improving Emotion Analysis for Speech-Induced EEGs Through EEMD-HHT-Based Feature Extraction and Electrode Selection

2021 ◽  
Vol 12 (2) ◽  
pp. 1-18
Author(s):  
Jing Chen ◽  
Haifeng Li ◽  
Lin Ma ◽  
Hongjian Bo
Keyword(s):  
Feature Extraction ◽  
Statistical Analysis ◽  
Orbitofrontal Cortex ◽  
Mental States ◽  
Emotion Detection ◽  
Emotional Speech ◽  
Eeg Signals ◽  
Cognitive Response ◽  
Extensive Analysis ◽  
Electrode Selection

Emotion detection using EEG signals has advantages in eliminating social masking to obtain a better understanding of underlying emotions. This paper presents the cognitive response to emotional speech and emotion recognition from EEG signals. A framework is proposed to recognize mental states from EEG signals induced by emotional speech: First, speech-evoked emotion cognitive experiment is designed, and EEG dataset is collected. Second, power-related features are extracted using EEMD-HHT, which is more accurate to reflect the instantaneous frequency of the signal than STFT and WT. An extensive analysis of relationships between frequency bands and emotional annotation of stimulus are presented using MIC and statistical analysis. The strongest correlations with EEG signals are found in lateral and medial orbitofrontal cortex (OFC). Finally, the performance of different feature set and classifier combinations are evaluated, and the experiments show that the framework proposed in this paper can effectively recognize emotion from EEG signals with accuracy of 75.7% for valence and 71.4% for arousal.

The Effect of Lesion Characteristic on Remineralization and Model Sensitivity

1992 ◽  
Vol 71 (3_suppl) ◽  
pp. 811-813 ◽  
Author(s):  
F. Schäfer ◽  
S.J. Raven ◽  
T.A. Parr
Keyword(s):  
Real Life ◽  
High Sensitivity ◽  
Lesion Size ◽  
Experimental Conditions ◽  
Treatment Groups ◽  
Human Enamel ◽  
Enamel Sample ◽  
Two Factors ◽  
Treatment Bias

A major criterion for assessing the value of any experimental model in scientific research is the degree of correspondence between its results and data from the real-life process it is designed to model. Intra-oral models aimed at predicting the anti-caries efficacy of toothpastes or other topical treatments should therefore be calibrated against treatments proven to be effective in a caries clinical trial. For this to be achieved, it is necessary that a model with high sensitivity be designed, while at the same time retaining relevance to the process to be modeled. This means that the effects of the various experimental conditions and parameters of the model on its performance must be understood. The purpose of this paper was to assess the influence of two specific factors on the performance of an in situ enamel remineralization model, which is based on human enamel slabs attached to partial dentures. The two factors are initial lesion severity and origin of enamel sample. The results indicated that initial lesion size affected whether net remineralization or net demineralization occurred during in situ treatment. Samples with an initial range of from 1500 to 2500 (ΔZ) tended more toward demineralization than did samples with ΔZ > 3500. This means that treatment groups must be well-balanced with respect to initial lesion size. Differences in initial demineralization severity between different tooth locations must also be considered so that systematic treatment bias can be avoided. The solution used in the model discussed here is based on a balanced experimental design, which allows this effect to be taken into account in the data analysis.

Microarray analysis of the transcriptome of the subfornical organ in the rat: regulation by fluid and food deprivation

2008 ◽  
Vol 295 (6) ◽  
pp. R1914-R1920 ◽  
Author(s):  
Charles Hindmarch ◽  
Mark Fry ◽  
Song T. Yao ◽  
Pauline M. Smith ◽  
David Murphy ◽  
...  
Keyword(s):  
Gene Expression ◽  
Statistical Analysis ◽  
Food Deprivation ◽  
Subfornical Organ ◽  
Microarray Technology ◽  
Type B ◽  
Bdnf Expression ◽  
Experimental Conditions ◽  
Calcium Sensing ◽  
First Time

We have employed microarray technology using Affymetrix 230 2.0 genome chips to initially catalog the transcriptome of the subfornical organ (SFO) under control conditions and to also evaluate the changes (common and differential) in gene expression induced by the challenges of fluid and food deprivation. We have identified a total of 17,293 genes tagged as present in one of our three experimental conditions, transcripts, which were then used as the basis for further filtering and statistical analysis. In total, the expression of 46 genes was changed in the SFO following dehydration compared with control animals (22 upregulated and 24 downregulated), with the largest change being the greater than fivefold increase in brain-derived neurotrophic factor (BDNF) expression, while significant changes in the expression of the calcium-sensing (upregulated) and apelin (downregulated) receptors were also reported. In contrast, food deprivation caused greater than twofold changes in a total of 687 transcripts (222 upregulated and 465 downregulated), including significant reductions in vasopressin, oxytocin, promelanin concentrating hormone, cocaine amphetamine-related transcript (CART), and the endothelin type B receptor, as well as increases in the expression of the GABAB receptor. Of these regulated transcripts, we identified 37 that are commonly regulated by fasting and dehydration, nine that were uniquely regulated by dehydration, and 650 that are uniquely regulated by fasting. We also found five transcripts that were differentially regulated by fasting and dehydration including BDNF and CART. In these studies we have for the first time described the transcriptome of the rat SFO and have in addition identified genes, the expression of which is significantly modified by either water or food deprivation.

scholarly journals Precipitation Regime and Temporal Changes in the Central Danubian Lowland Region

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Dana Halmova ◽  
Pavla Pekarova ◽  
Juraj Olbrimek ◽  
Pavol Miklanek ◽  
Jan Pekar
Keyword(s):  
Spectral Analysis ◽  
Statistical Analysis ◽  
Daily Precipitation ◽  
Point Of View ◽  
Annual Precipitation ◽  
Annual Maximum ◽  
Precipitation Regime ◽  
Initial Hypothesis ◽  
Frequency Curves

The aim of this paper is to investigate the statistical aspects of multiannual variability of precipitation at the Hurbanovo station, Slovakia, over 140 years (1872–2011). We compare the long-term variability of annual precipitation for Hurbanovo (Slovakia), Brno (Czech Republic), Vienna (Austria), and Mosonmagyarovar (Hungary) stations using autocorrelation and spectral analysis methods. From the long-term point of view, there is no consistent trend in the annual precipitation; only a multiannual variability has been detected. Consequently we identify changes in the distribution of annual maximum daily precipitation for Hurbanovo during different periods for winter-spring and summer-autumn seasons using histograms, empirical exceedance curves, and frequency curves of daily precipitation. Next, we calculate the periods of days without precipitation exceeding 29 days between 1872 and 2011. The longest period of days without precipitation was 83 days in 1947. The statistical analysis does not confirm our initial hypothesis that neither high daily precipitation (over 51.2 mm per day) nor long dry periods (more than 50 days without precipitation) would occur more frequently nowadays. We assume that the decrease in annual precipitation over the period 1942–2011 (compared to 1872–1941) is caused by the less frequent occurrence of daily precipitation between 0.4 and 25.6 mm.

scholarly journals An Automatic Epilepsy Detection Method Based on Improved Inductive Transfer Learning

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yufeng Yao ◽  
Zhiming Cui
Keyword(s):  
Transfer Learning ◽  
Real Life ◽  
Eeg Signal ◽  
Signal Recognition ◽  
Least Squares Regression ◽  
Eeg Signals ◽  
Strong Basis ◽  
Inductive Transfer ◽  
Inductive Transfer Learning ◽  
The Impact

Epilepsy is a chronic disease caused by sudden abnormal discharge of brain neurons, causing transient brain dysfunction. The seizures of epilepsy have the characteristics of being sudden and repetitive, which has seriously endangered patients’ health, cognition, etc. In the current condition, EEG plays a vital role in the diagnosis, judgment, and qualitative location of epilepsy among the clinical diagnosis of various epileptic seizures and is an indispensable means of detection. The study of the EEG signals of patients with epilepsy can provide a strong basis and useful information for in-depth understanding of its pathogenesis. Although, intelligent classification technologies based on machine learning have been widely used to the classification of epilepsy EEG signals and show the effectiveness. In fact, it is difficult to ensure that there is always enough EEG data available for training the model in real life, which will affect the performance of the algorithms. In view of this, to reduce the impact of insufficient data on the detection performance of the algorithms, a novel discriminate least squares regression- (DLSR-) based inductive transfer learning method was introduced which is on the basis of DLSR and the inductive transfer learning. And, it is applied to promote the adaptability and accuracy of the epilepsy EEG signal recognition. The proposed method inherits the advantages of DLSR; it can be more suitable for classification scenarios by expanding the interval between different classes. Meanwhile, it can simultaneously use the data of the target domain and the knowledge of the source domain, which is helpful for getting better performance. The results show that the improved method has more advantages in EEG signal recognition comparing to several other representative methods.

Eliciting Negative Affects Using Film Clips and Real-Life Methods

2017 ◽  
Vol 121 (3) ◽  
pp. 527-547 ◽  
Author(s):  
João Carlos Centurion Cabral ◽  
Patrice de Souza Tavares ◽  
Gibson Juliano Weydmann ◽  
Vera Torres das Neves ◽  
Rosa Maria Martins de Almeida
Keyword(s):  
Undergraduate Students ◽  
Negative Emotions ◽  
Real Life ◽  
Experimental Manipulation ◽  
Emotional Reactions ◽  
Experimental Conditions ◽  
Emotion Elicitation ◽  
Negative Affects ◽  
Film Clips ◽  
Cortisol Responses

Although audio-visual stimuli are among the most frequently used methods to elicit emotional reactions in experimental conditions, real-life manipulations have increasingly been used in different countries. However, the applicability of such protocols has not yet been tested in Brazilian Portuguese speakers. Thus, we conducted two experiments to investigate the effectiveness of both methods. In the first experiment, we used film clips to induce negative emotions (i.e., anger, fear, or sadness) or an emotionally neutral condition in 321 undergraduate students. After watching one of the online videos, volunteers completed an emotional assessment. As expected, there were significant differences in all groups. Our results corroborate the relatively discrete patterns in emotion elicitation using films. In the second experiment, anger was elicited in 18 male undergraduates through a hostile social interaction with a confederate and measured by the corrugator muscle activity and cortisol responses. Indeed, there was an increase in corrugator activity in the group exposed to anger induction, even after a few minutes from the end of the experimental manipulation. Implications for experiments on the negative emotions are discussed.

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