scholarly journals A Sound Prediction: EEG-Based Neural Synchrony Predicts Online Music Streams

2021 ◽  
Vol 12 ◽  
Author(s):  
Nikki Leeuwis ◽  
Daniela Pistone ◽  
Niels Flick ◽  
Tom van Bommel
Keyword(s):  
Predictive Value ◽  
Brain Activity ◽  
Music Industry ◽  
Stated Preferences ◽  
Neural Synchrony ◽  
Success Predictors ◽  
Individual Level ◽  
Alpha Asymmetry ◽  
Promising Tool ◽  
True Value

Neuroforecasting predicts population-wide choices based on neural data of individuals and can be used, for example, in neuromarketing to estimate campaign successes. To deliver true value, the brain activity metrics should deliver predictive value above and beyond traditional stated preferences. Evidence from movie trailer research has proposed neural synchrony, which compares the similarity of brain responses across participants and has shown to be a promising tool in neuroforecasting for movie popularity. The music industry might also benefit from these increasingly accurate success predictors, but only one study has been forecasting music popularity, using functional magnetic resonance imaging measures. Current research validates the strength of neural synchrony as a predictive measure for popularity of music, making use of electroencephalogram to capture moment-to-moment neural similarity between respondents while they listen to music. Neural synchrony is demonstrated to be a significant predictor for public appreciation on Spotify 3 weeks and 10 months after the release of the albums, especially when combined with the release of a single. On an individual level, other brain measures were shown to relate to individual subjective likeability ratings, including Frontal Alpha Asymmetry and engagement when combined with the factors artist and single release. Our results show the predictive value of brain activity measures outperforms stated preferences. Especially, neural synchrony carries high predictive value for the popularity on Spotify, providing the music industry with an essential asset for efficient decision making and investments, in addition to other practical implications that include neuromarketing and advertising industries.

scholarly journals Evaluation of Production Lots of a Rapid Point-of-Care Lateral Flow Serological Test Intended for Identification of IgM and IgG against the N-Terminal Part of the Spike Protein (S1) of SARS-CoV-2

Viruses ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1043
Author(s):  
Tove Hoffman ◽  
Linda Kolstad ◽  
Bengt Rönnberg ◽  
Åke Lundkvist
Keyword(s):  
Predictive Value ◽  
Serological Test ◽  
Point Of Care ◽  
External Validation ◽  
High Sensitivity ◽  
Lateral Flow ◽  
Spike Protein ◽  
Individual Level ◽  
Lateral Flow Test ◽  
Production Errors

The potential of rapid point-of-care (POC) tests has been subject of doubt due to an eventual risk of production errors. The aim was therefore to evaluate the two separate production lots of a commercial POC lateral flow test, intended for the detection of IgM and IgG against the SARS-CoV-2 spike protein (S1). Control samples consisted of serum from individuals with confirmed SARS-CoV-2 infection and pre-COVID-19 negative sera gathered from a biobank. The presence of anti-S1 IgM/IgG in the sera was verified by an in-house Luminex-based serological assay (COVID-19 SIA). One hundred samples were verified as positive for anti-S1 IgG and 74 for anti-S1 IgM. Two hundred samples were verified as negative for anti-S1 IgM/IgG. For the two lots of the POC-test, the sensitivities were 93.2% and 87.8% for IgM and 93.0% and 100% for IgG. The specificities were 100% for IgM and 99.5% for IgG. The positive predictive value was 100% for IgM and 98.9% and 99.0% for IgG. The negative predictive value was 97.6% and 95.7% for IgM, and 96.6% and 100% for IgG. The evaluated POC-test is suitable to assess anti-SARS-CoV-2 S1 IgM and IgG, as a measure of previous virus exposure on an individual level. The external validation of separate lots of rapid POC-tests is encouraged to ensure high sensitivity before market introduction.

scholarly journals Diagnostic Performance of Different Thyroid Imaging Reporting and Data Systems (Kwak-TIRADS, EU-TIRADS and ACR TI-RADS) for Risk Stratification of Small Thyroid Nodules (≤10 mm)

2020 ◽  
Vol 9 (1) ◽  
pp. 236 ◽  
Author(s):  
Simone Schenke ◽  
Rigobert Klett ◽  
Philipp Seifert ◽  
Michael C. Kreissl ◽  
Rainer Görges ◽  
...  
Keyword(s):  
Risk Stratification ◽  
Predictive Value ◽  
Diagnostic Performance ◽  
Thyroid Nodules ◽  
Cohort Analysis ◽  
Medullary Carcinoma ◽  
Data Systems ◽  
Thyroid Imaging ◽  
Promising Tool ◽  
Risk Of Malignancy

Due to the widespread use of ultrasound, small thyroid nodules (TNs) ≤ 10 mm are common findings. Standardized approaches for the risk stratification of TNs with Thyroid Imaging Reporting and Data Systems (TIRADS) were evaluated for the clinical routine. With TIRADS, the risk of malignancy in TNs is calculated by scoring the number or combination of suspicious ultrasound features, leading to recommendations for further diagnostic steps. However, there are only scarce data on the performance of TIRADS for small TNs. The aim was to compare three different TIRADS for risk stratification of small TNs in routine clinical practice. We conducted a retrospective cohort analysis of TNs ≤ 10 mm and their available histology. Nodules were classified according to three different TIRADS. In the study, 140 patients (n = 113 female) with 145 thyroid nodules (n = 76 malignant) were included. Most of the malignant nodules were papillary carcinoma (97%), and the remaining 3% were medullary carcinoma. For all tested TIRADS, the prevalence of malignancy rose with increasing category levels. The highest negative predictive value was found for ACR TI-RADS and the highest positive predictive value for Kwak-TIRADS. All tested variants of TIRADS showed comparable diagnostic performance for the risk stratification of small TNs. TIRADS seems to be a promising tool to reliably assess the risk of malignancy of small TNs.

scholarly journals XPERT MYCOBACTERIUM TUBERCULOSIS/RIFAMPICIN ASSAY: A BOON IN TUBERCULOSIS DIAGNOSTICS

2016 ◽  
Vol 9 (5) ◽  
pp. 225 ◽  
Author(s):  
Sevitha Bhat ◽  
Kavya Ramamurthy ◽  
Shalini Shenoy ◽  
Aseem Rangnekar
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Predictive Value ◽  
High Sensitivity ◽  
Mortality And Morbidity ◽  
Indicator Tube ◽  
Promising Tool ◽  
Causes Of Mortality ◽  
Conventional Microscopy ◽  
Tb Diagnostics ◽  
Sensitivity Specificity

ABSTRACTObjectives: Mycobacterium tuberculosis (MTB) remains one of the most significant causes of mortality and morbidity in developing countriesespecially India. India has the highest burden of TB, with an estimated incidence figure of 2.1 million cases out of the 9 million cases of TB globally.Diagnosis of TB relies on conventional microscopy and culture with drawbacks related to sensitivity, specificity, turn around time (TAT). The aim ofthis study was to evaluate the performance of Xpert MTB/rifampicin (RIF) assay (GX) for MTB detection in pulmonary and extrapulmonary clinicalsamples.Methods: A total of 209 clinical specimens (182: pulmonary and 27: extrapulmonary) were processed using auramine smear, culture by mycobacteriagrowth indicator tube and GenXpert.Results: The sensitivity of GenXpert was 62.63% for pulmonary and 55% for extrapulmonary samples. The sensitivity and specificity of GX were100% for the smear positive cases. The sensitivity, specificity, positive predictive value, and negative predictive value of the GX for smear negativecases were 67.8%, 97.5%, 90.4%, and 89.6%, respectively. RIF resistance was detected in 3.8% the samples.Conclusion: GenXpert, with short TAT, high sensitivity, specificity and less technical expertise required is a promising tool in TB diagnostics for thefuture.Keywords: GenXpert, Tuberculosis diagnosis, Molecular method, Rifampicin resistance.

scholarly journals Organization of Propagated Intrinsic Brain Activity in Individual Humans

2019 ◽  
Vol 30 (3) ◽  
pp. 1716-1734 ◽  
Author(s):  
Ryan V Raut ◽  
Anish Mitra ◽  
Scott Marek ◽  
Mario Ortega ◽  
Abraham Z Snyder ◽  
...  
Keyword(s):  
Resting State ◽  
Large Scale ◽  
Cortical Excitability ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Brain Organization ◽  
Individual Level ◽  
Slow Activity ◽  
Lag Structure

Abstract Spontaneous infra-slow (<0.1 Hz) fluctuations in functional magnetic resonance imaging (fMRI) signals are temporally correlated within large-scale functional brain networks, motivating their use for mapping systems-level brain organization. However, recent electrophysiological and hemodynamic evidence suggest state-dependent propagation of infra-slow fluctuations, implying a functional role for ongoing infra-slow activity. Crucially, the study of infra-slow temporal lag structure has thus far been limited to large groups, as analyzing propagation delays requires extensive data averaging to overcome sampling variability. Here, we use resting-state fMRI data from 11 extensively-sampled individuals to characterize lag structure at the individual level. In addition to stable individual-specific features, we find spatiotemporal topographies in each subject similar to the group average. Notably, we find a set of early regions that are common to all individuals, are preferentially positioned proximal to multiple functional networks, and overlap with brain regions known to respond to diverse behavioral tasks—altogether consistent with a hypothesized ability to broadly influence cortical excitability. Our findings suggest that, like correlation structure, temporal lag structure is a fundamental organizational property of resting-state infra-slow activity.

scholarly journals The integration of social and neural synchrony: a case for ecologically valid research using MEG neuroimaging

2020 ◽  
Author(s):  
Jonathan Levy ◽  
Kaisu Lankinen ◽  
Maria Hakonen ◽  
Ruth Feldman
Keyword(s):  
Social Interactions ◽  
Developmental Stages ◽  
Ecological Validity ◽  
Real Life ◽  
Recent Decade ◽  
Social Contexts ◽  
Neural Synchrony ◽  
Promising Tool ◽  
Interpersonal Synchrony ◽  
Behavioral Synchrony

Abstract The recent decade has seen a shift from artificial and environmentally deprived experiments in neuroscience to real-life studies on multiple brains in interaction, coordination and synchrony. In these new interpersonal synchrony experiments, there has been a growing trend to employ naturalistic social interactions to evaluate mechanisms underlying synchronous neuronal communication. Here, we emphasize the importance of integrating the assessment of neural synchrony with measurement of nonverbal behavioral synchrony as expressed in various social contexts: relaxed social interactions, planning a joint pleasurable activity, conflict discussion, invocation of trauma, or support giving and assess the integration of neural and behavioral synchrony across developmental stages and psychopathological conditions. We also showcase the advantages of magnetoencephalography neuroimaging as a promising tool for studying interactive neural synchrony and consider the challenge of ecological validity at the expense of experimental rigor. We review recent evidence of rhythmic information flow between brains in interaction and conclude with addressing state-of-the-art developments that may contribute to advance research on brain-to-brain coordination to the next level.

scholarly journals Microcurrent Stimulation at Shenmen Acupoint Facilitates EEG Associated with Sleepiness and Positive Mood: A Randomized Controlled Electrophysiological Study

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Mei-chun Cheung ◽  
Agnes S. Chan ◽  
Joanne Yip
Keyword(s):  
Placebo Group ◽  
Brain Activity ◽  
Frontal Region ◽  
Electrocutaneous Stimulation ◽  
Alpha Power ◽  
Sham Stimulation ◽  
Alpha Asymmetry ◽  
Frontal Alpha Asymmetry ◽  
The Brain ◽  
Experimental Group

To examine the electrophysiological effects of microcurrent stimulation at the Shenmen acupoint, 40 healthy normal subjects were randomly assigned to a placebo group (sham stimulation) and an experimental group (bilateral electrocutaneous stimulation at the Shenmen). The following two electroencephalographic indicators were used to measure brain activity. (1) Arousal level was measured with reference to log-transformed absolute alpha power and power source and analyzed using low-resolution electromagnetic tomography and (2) frontal alpha asymmetry was used as an indicator of mood. After real stimulation for 10 minutes, absolute alpha power was globally reduced in the experimental group, particularly in the anterior and centrotemporal regions of the brain. This indicates a decline in the brain activity associated with arousal. Moreover, the reduction was more prominent in the left frontal region, as compared to the right frontal region, resulting in significant increase from negative to positive frontal alpha asymmetry scores and reflecting an increase in the brain activity associated with enhanced mood. However, the placebo group exhibited no significant changes in two indicators after sham stimulation. This study provides initial electrophysiological evidence of changes in brain activity associated with reduced arousal (and thus greater sleepiness) and enhanced mood after microcurrent stimulation at the Shenmen acupoint.

A Least Squares Procedure for Benefit Segmentation with Conjoint Experiments

1988 ◽  
Vol 25 (2) ◽  
pp. 157-167 ◽  
Author(s):  
Wagner A. Kamakura
Keyword(s):  
Least Squares ◽  
Predictive Accuracy ◽  
Stated Preferences ◽  
Group Level ◽  
Individual Level ◽  
Benefit Segmentation ◽  
Preference Functions ◽  
Aggregation Level

A popular procedure for benefit segmentation based on conjoint experiments has been to estimate individual-level part worths and then form nonoverlapping clusters of consumers with similar estimates. Rather than using these estimates as the criteria for clustering, the least squares procedure discussed in the article attempts to group consumers into homogeneous segments so their stated preferences are explained maximally by their group-level preference functions. This procedure also provides a measure of the expected predictive accuracy that will help the researcher in choosing an adequate aggregation level.

scholarly journals A Synchrony-Based Classification Approach for Predicting Attitudes Using fNIRS

2020 ◽  
Author(s):  
Macrina C Dieffenbach ◽  
Grace S R Gillespie ◽  
Shannon M Burns ◽  
Ian A McCulloh ◽  
Daniel L Ames ◽  
...  
Keyword(s):  
Near Infrared ◽  
Neural Synchrony ◽  
Reference Groups ◽  
Functional Near Infrared Spectroscopy ◽  
Individual Level ◽  
Naturally Occurring ◽  
Neuroscience Research ◽  
Using Data ◽  
The Individual ◽  
Dispositional Differences

Abstract Social neuroscience research has demonstrated that those who are like-minded are also “like-brained.” Studies have shown that people who share similar viewpoints have greater neural synchrony with one another, and less synchrony with people who “see things differently.” Although these effects have been demonstrated at the group level, little work has been done to predict the viewpoints of specific individuals using neural synchrony measures. Furthermore, the studies that have made predictions using synchrony-based classification at the individual level used expensive and immobile neuroimaging equipment (e.g. fMRI) in highly controlled laboratory settings, which may not generalize to real-world contexts. Thus, this study uses a simple synchrony-based classification method, which we refer to as the neural reference groups approach, to predict individuals’ dispositional attitudes from data collected in a mobile “pop-up neuroscience” lab. Using functional near infrared spectroscopy (fNIRS) data, we predicted individuals’ partisan stances on a sociopolitical issue by comparing their neural timecourses to data from two partisan neural reference groups. We found that partisan stance could be identified at above-chance levels using data from dorsomedial prefrontal cortex (dmPFC). These results indicate that the neural reference groups approach can be used to investigate naturally-occurring, dispositional differences anywhere in the world.

Frontal Alpha Asymmetry in Posttraumatic Stress Disorder: Group Differences Among Individuals With and Without PTSD During an Inhibitory Control Task

2021 ◽  
pp. 155005942110467
Author(s):  
Teresa López-Castro ◽  
Laura Martin ◽  
Sean Nickley ◽  
Tanya C. Saraiya ◽  
Robert D. Melara
Keyword(s):  
Posttraumatic Stress Disorder ◽  
Posttraumatic Stress ◽  
Inhibitory Control ◽  
Stress Disorder ◽  
Brain Activity ◽  
Trauma Exposure ◽  
Control Group ◽  
Alpha Asymmetry ◽  
Control Paradigm ◽  
Frontal Alpha Asymmetry

The current study examined frontal alpha asymmetry (FAA) as a marker of approach- and avoidance-related prefrontal activity in participants with and without trauma exposure and posttraumatic stress disorder (PTSD). We investigated FAA in an inhibitory control paradigm (threatening vs nonthreatening cues) under 2 levels of cognitive demand (baseline: images constant within a block of trials; vs filtering: images varied randomly within a block) in 3 groups of participants: individuals with PTSD ( n = 16), exposed to trauma but without PTSD ( n = 14), and a control group without PTSD or trauma exposure ( n = 15). Under low demand (baseline), both PTSD and trauma-exposed participants exhibited significantly greater relative left than right frontal brain activity (approach) to threatening than to nonthreatening images. Under high demand (filtering), no FAA differences were found between threatening and nonthreatening images, but PTSD participants revealed more relative left than right FAA, whereas trauma-exposed participants showed reduced left relative right FAA. In all conditions, healthy controls exhibited reduced left relative to right FAA and no differences between threatening and nonthreatening images. Study findings suggest dysfunctional prefrontal mechanisms of emotion regulation in PTSD, but adaptive prefrontal regulation in trauma-exposed individuals without PTSD.

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