scholarly journals Neural Tracking in Infants – an Analytical Tool for Multisensory Social Processing in Development

2021 ◽  
Author(s):  
Sarah Jessen ◽  
Jonas Obleser ◽  
Sarah Tune
Keyword(s):  
Cognitive Neuroscience ◽  
Sensory Input ◽  
Linear Models ◽  
Neural Responses ◽  
Data Set ◽  
Generic Models ◽  
The Past ◽  
Social Processing ◽  
Eeg Data ◽  
Continuous Dynamic

Humans are born into a social environment and from early on possess a range of abilities to detect and respond to social cues. In the past decade, there has been a rapidly increasing interest in investigating the neural responses underlying such early social processes under naturalistic conditions. However, the investigation of neural responses to continuous dynamic input poses the challenge of how to link neural responses back to continuous sensory input. In the present tutorial, we provide a step-by-step introduction to one approach to tackle this issue, namely the use of linear models to investigate neural tracking responses in electroencephalographic (EEG) data. While neural tracking has gained increasing popularity in adult cognitive neuroscience over the past decade, its application to infant EEG is still rare and comes with its own challenges. After introducing the concept of neural tracking, we discuss and compare the use of forward vs. backward models and individual vs. generic models using an example data set of infant EEG data. Each section comprises a theoretical introduction as well as a concrete example using MATLAB code. We argue that neural tracking provides a promising way to investigate early (social) processing in an ecologically valid setting.

scholarly journals Replicability of neural responses to speech accent is driven by study design and analytical parameters

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
C. Benjamin Strauber ◽  
Lestat R. Ali ◽  
Takako Fujioka ◽  
Candace Thille ◽  
Bruce D. McCandliss
Keyword(s):  
Experimental Design ◽  
Study Design ◽  
Semantic Processing ◽  
American English ◽  
Neural Correlates ◽  
Event Related Potential ◽  
Neural Responses ◽  
Data Set ◽  
Design Variables ◽  
Eeg Data

AbstractRecent studies have reported evidence that listeners' brains process meaning differently in speech with an in-group as compared to an out-group accent. However, among studies that have used electroencephalography (EEG) to examine neural correlates of semantic processing of speech in different accents, the details of findings are often in conflict, potentially reflecting critical variations in experimental design and/or data analysis parameters. To determine which of these factors might be driving inconsistencies in results across studies, we systematically investigate how analysis parameter sets from several of these studies impact results obtained from our own EEG data set. Data were collected from forty-nine monolingual North American English listeners in an event-related potential (ERP) paradigm as they listened to semantically congruent and incongruent sentences spoken in an American accent and an Indian accent. Several key effects of in-group as compared to out-group accent were robust across the range of parameters found in the literature, including more negative scalp-wide responses to incongruence in the N400 range, more positive posterior responses to congruence in the N400 range, and more positive posterior responses to incongruence in the P600 range. These findings, however, are not fully consistent with the reported observations of the studies whose parameters we used, indicating variation in experimental design may be at play. Other reported effects only emerged under a subset of the analytical parameters tested, suggesting that analytical parameters also drive differences. We hope this spurs discussion of analytical parameters and investigation of the contributions of individual study design variables in this growing field.

Machine Learning Verdict of EEG Signals in Brain Computer Interface

2018 ◽  
pp. 429-441
Author(s):  
M. Jeyanthi ◽  
C. Velayutham
Keyword(s):  
Nearest Neighbor ◽  
Technology Development ◽  
Vital Role ◽  
Svm Classifier ◽  
K Nearest Neighbor ◽  
Data Mining Technique ◽  
Data Set ◽  
Eeg Data ◽  
Irrelevant Attributes

In Science and Technology Development BCI plays a vital role in the field of Research. Classification is a data mining technique used to predict group membership for data instances. Analyses of BCI data are challenging because feature extraction and classification of these data are more difficult as compared with those applied to raw data. In this paper, We extracted features using statistical Haralick features from the raw EEG data . Then the features are Normalized, Binning is used to improve the accuracy of the predictive models by reducing noise and eliminate some irrelevant attributes and then the classification is performed using different classification techniques such as Naïve Bayes, k-nearest neighbor classifier, SVM classifier using BCI dataset. Finally we propose the SVM classification algorithm for the BCI data set.

scholarly journals EEG Data Quality: Determinants and Impact in a Multicenter Study of Children, Adolescents, and Adults with Attention-Deficit/Hyperactivity Disorder (ADHD)

2021 ◽  
Vol 11 (2) ◽  
pp. 214
Author(s):  
Anna Kaiser ◽  
Pascal-M. Aggensteiner ◽  
Martin Holtmann ◽  
Andreas Fallgatter ◽  
Marcel Romanos ◽  
...  
Keyword(s):  
Data Quality ◽  
Large Scale ◽  
Linear Models ◽  
Spectral Power ◽  
Control Group ◽  
Continuous Performance Task ◽  
Related Data ◽  
Eyes Closed ◽  
Eeg Data ◽  
Eyes Open

Electroencephalography (EEG) represents a widely established method for assessing altered and typically developing brain function. However, systematic studies on EEG data quality, its correlates, and consequences are scarce. To address this research gap, the current study focused on the percentage of artifact-free segments after standard EEG pre-processing as a data quality index. We analyzed participant-related and methodological influences, and validity by replicating landmark EEG effects. Further, effects of data quality on spectral power analyses beyond participant-related characteristics were explored. EEG data from a multicenter ADHD-cohort (age range 6 to 45 years), and a non-ADHD school-age control group were analyzed (ntotal = 305). Resting-state data during eyes open, and eyes closed conditions, and task-related data during a cued Continuous Performance Task (CPT) were collected. After pre-processing, general linear models, and stepwise regression models were fitted to the data. We found that EEG data quality was strongly related to demographic characteristics, but not to methodological factors. We were able to replicate maturational, task, and ADHD effects reported in the EEG literature, establishing a link with EEG-landmark effects. Furthermore, we showed that poor data quality significantly increases spectral power beyond effects of maturation and symptom severity. Taken together, the current results indicate that with a careful design and systematic quality control, informative large-scale multicenter trials characterizing neurophysiological mechanisms in neurodevelopmental disorders across the lifespan are feasible. Nevertheless, results are restricted to the limitations reported. Future work will clarify predictive value.

scholarly journals Relationship between Cycling Infrastructure and Transportation Cycling in a Small Urban Area

2021 ◽  
Vol 1 (1) ◽  
pp. 99-112
Author(s):  
Richard Larouche ◽  
Nimesh Patel ◽  
Jennifer L. Copeland
Keyword(s):  
Generalized Linear Models ◽  
Qualitative Data ◽  
Linear Models ◽  
The Other ◽  
Small City ◽  
The Road ◽  
The Past ◽  
Low Prevalence ◽  
The Relationship

The role of infrastructure in encouraging transportation cycling in smaller cities with a low prevalence of cycling remains unclear. To investigate the relationship between the presence of infrastructure and transportation cycling in a small city (Lethbridge, AB, Canada), we interviewed 246 adults along a recently-constructed bicycle boulevard and two comparison streets with no recent changes in cycling infrastructure. One comparison street had a separate multi-use path and the other had no cycling infrastructure. Questions addressed time spent cycling in the past week and 2 years prior and potential socio-demographic and psychosocial correlates of cycling, including safety concerns. Finally, we asked participants what could be done to make cycling safer and more attractive. We examined predictors of cycling using gender-stratified generalized linear models. Women interviewed along the street with a separate path reported cycling more than women on the other streets. A more favorable attitude towards cycling and greater habit strength were associated with more cycling in both men and women. Qualitative data revealed generally positive views about the bicycle boulevard, a need for education about sharing the road and for better cycling infrastructure in general. Our results suggest that, even in smaller cities, cycling infrastructure may encourage cycling, especially among women.

scholarly journals Change in mean and extreme temperature at Yingkou station in Northeast China from 1904 to 2017

2021 ◽  
Vol 164 (3-4) ◽  
Author(s):  
Xiaoying Xue ◽  
Guoyu Ren ◽  
Xiubao Sun ◽  
Panfeng Zhang ◽  
Yuyu Ren ◽  
...  
Keyword(s):  
Northeast China ◽  
Extreme Temperature ◽  
Maximum Temperature ◽  
Data Set ◽  
The Past ◽  
Significant Downward Trend ◽  
Cold Events ◽  
Temperature Indices ◽  
Increasing Trends ◽  
Change In Mean

AbstractThe understanding of centennial trends of extreme temperature has been impeded due to the lack of early-year observations. In this paper, we collect and digitize the daily temperature data set of Northeast China Yingkou meteorological station since 1904. After quality control and homogenization, we analyze the changes of mean and extreme temperature in the past 114 years. The results show that mean temperature (Tmean), maximum temperature (Tmax), and minimum temperature (Tmin) all have increasing trends during 1904–2017. The increase of Tmin is the most obvious with the rate of 0.34 °C/decade. The most significant warming occurs in spring and winter with the rate of Tmean reaching 0.32 °C/decade and 0.31 °C/decade, respectively. Most of the extreme temperature indices as defined using absolute and relative thresholds of Tmax and Tmin also show significant changes, with cold events witnessing a more significant downward trend. The change is similar to that reported for global land and China for the past six decades. It is also found that the extreme highest temperature (1958) and lowest temperature (1920) records all occurred in the first half of the whole period, and the change of extreme temperature indices before 1950 is different from that of the recent decades, in particular for diurnal temperature range (DTR), which shows an opposite trend in the two time periods.

scholarly journals Self-reflectivity: a moment of professionalization in psychotherapy training

2018 ◽  
Vol 21 (3) ◽  
Author(s):  
Margarete Finger-Ossinger ◽  
Henriette Löffler-Stastka
Keyword(s):  
Thematic Analysis ◽  
European Association ◽  
Psychotherapy Training ◽  
Self Awareness ◽  
Clear Indication ◽  
Learning Program ◽  
Data Set ◽  
Self Reflection ◽  
The Past ◽  
Essential Prerequisite

The required basic skills of European psychotherapists were published by the European Association of Psychotherapy in 2013. One of these abilities is self-reflection. To mentalize oneself, to reflect on what circumstances and experiences in the past and present have led to the present desires, thoughts and convictions is an essential prerequisite for professional work in the psychosocial field. With the help of the thematic analysis a data set of 41 self-reflection reports of students is analysed at the end of the training. Since the training should be evaluated and if necessary optimized, it should be examined which elements of the online preparation course make the selfreflection ability visible. The analysis of the students’ texts gives a clear indication of existing self-reflection skills. It was surprising that for some students, besides the great importance of self-awareness lessons, affective integration into the blended learning program was an essential impulse for self-reflection.

Disorders of Musical Cognition

2012 ◽  
Author(s):  
Lauren Stewart ◽  
Katharina von Kriegstein ◽  
Simone Dalla Bella ◽  
Jason D. Warren ◽  
Timothy D. Griffiths
Keyword(s):  
Case Studies ◽  
Cognitive Neuroscience ◽  
Cognitive Architecture ◽  
Critical Role ◽  
Theoretical Models ◽  
Systematic Evaluation ◽  
Neural Basis ◽  
The Past ◽  
Musical Cognition ◽  
Musical Listening

This article presents an overview of case studies of acquired disorders of musical listening. Like any cognitive faculty, music is multifaceted, and the identification of the neural basis of any complex faculty must proceed, hand in hand, with an elucidation of its cognitive architecture. The past decade has seen an evolution in the theoretical models of musical processing, allowing the development of theoretically motivated instruments for the systematic evaluation of musical disorders. Such developments have allowed reports of musical disorders to evolve from historical anecdotes to systematic, verifiable accounts that can play a critical role in contributing to our understanding of the cognitive neuroscience of music.

scholarly journals Augmented Data Selector to Initiate Text-Based CAPTCHA Attack

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Aolin Che ◽  
Yalin Liu ◽  
Hong Xiao ◽  
Hao Wang ◽  
Ke Zhang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Training Data ◽  
Accuracy Rate ◽  
Data Set ◽  
Research Directions ◽  
Training Models ◽  
The Past ◽  
Future Work ◽  
Design Cost ◽  
Accuracy Rates

In the past decades, due to the low design cost and easy maintenance, text-based CAPTCHAs have been extensively used in constructing security mechanisms for user authentications. With the recent advances in machine/deep learning in recognizing CAPTCHA images, growing attack methods are presented to break text-based CAPTCHAs. These machine learning/deep learning-based attacks often rely on training models on massive volumes of training data. The poorly constructed CAPTCHA data also leads to low accuracy of attacks. To investigate this issue, we propose a simple, generic, and effective preprocessing approach to filter and enhance the original CAPTCHA data set so as to improve the accuracy of the previous attack methods. In particular, the proposed preprocessing approach consists of a data selector and a data augmentor. The data selector can automatically filter out a training data set with training significance. Meanwhile, the data augmentor uses four different image noises to generate different CAPTCHA images. The well-constructed CAPTCHA data set can better train deep learning models to further improve the accuracy rate. Extensive experiments demonstrate that the accuracy rates of five commonly used attack methods after combining our preprocessing approach are 2.62% to 8.31% higher than those without preprocessing approach. Moreover, we also discuss potential research directions for future work.

scholarly journals Conceptual Framework for Assessing Process Variables Salient for Service-Learning Experience

2020 ◽  
Author(s):  
Ka Hing Lau ◽  
Robin Snell
Keyword(s):  
Service Learning ◽  
Community Service ◽  
Course Design ◽  
Learning Experience ◽  
Community Partner ◽  
Positive Role ◽  
Data Set ◽  
The Past ◽  
Multi Stakeholder ◽  
Effective Integration

Service-learning is an established pedagogy which integrates experiential learning with community service. It has been widely adopted in higher education around the world including in Hong Kong, yet the key ingredients that determine its successful impacts for its stakeholders have not been fully assessed. This study reviewed the past literature, which indicates the key ingredients that may be found in successful service-learning programmes. We identify six key ingredients: students provide meaningful service; the community partner representative plays a positive role; effective preparation and support for students; effective reflection by students; effective integration of service-learning within the course design; and stakeholder synergy in terms of collaboration, communication and co-ownership. In order to obtain an inter-subjectively fair and trustworthy data set, reflecting the extent to which those key ingredients are perceived to have been achieved, we propose a multi-stakeholder approach for data collection, involving students, instructors and community partner representatives.

scholarly journals The effect of statin treatment on survival and on the use of healthcare resources among patients with acute myocardial infarction

2018 ◽  
pp. 30-48
Author(s):  
Lien Nguyen ◽  
Unto Häkkinen ◽  
Henna Jurvanen
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Linear Models ◽  
Statin Treatment ◽  
Data Set ◽  
Hospitalised Patients ◽  
Life Years ◽  
Matched Data ◽  
The Cost ◽  
Statin Use

The aim of this study was to investigate the cost-effectiveness of statin use by newly hospitalised patients with acute myocardial infarction (AMI) in Finland. The data were from the PERFECT database of patients hospitalised for AMI and discharged in 1998–2012 in Finland. Selected patients had first-time AMI and had not used statins earlier (N=60 404). We generated a matched data set from statin non-users for statin users based on propensity matching analysis (N=28 412), which was also used. Statin use was defined as statins purchased within the first week after hospital discharge. Healthcare costs included costs of inpatient and outpatient hospital care, costs of nursing homes and costs of prescribed medicines (at 2011 prices). The follow-up time was one year. Logit and generalised linear models were used. We measured the effects of statin use as life years (LYs) gained and computed costs per LY gained. Both data were analysed for the entire period and for subperiods 1998–2001, 2002–2007 and 2008–2011, without discount rates and with a 3% discount rate. An average patient would gain 0.26–0.51 more years. The estimated costs per LY gained ranged between EUR 800 and 15 000. They were highest (EUR 12 000–15 000) in 1998–2001 by the matched data, but were actually savings in 2008–2011. The estimated costs indicate that statin use in treating AMI was very cost-effective. However, our rather long study period may suggest that the cost estimates per LY gained could be overestimated, as the life expectancy of AMI patients is likely shorter than that of the general population.Published: Online April 2018.

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