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Two Seconds to Speak:Increasing Communication Speed for fMRI-Based Brain-Computer Interfaces
No full textBackground: Brain-computer interfaces (BCIs) can provide alternative, motor-independent means of communication for people who have lost motor function. A promising variant is the functional magnetic resonance imaging (fMRI)-based BCI, which exploits information on hemodynamic brain activity evoked by performing different mental tasks. However, due to the sluggish nature of the hemodynamic response, a current challenge is to make these BCIs as efficient and fast as possible to allow useful clinical application. Furthermore, there is yet no consensus on optimal mental-task selection for multi-voxel pattern analysis-based decoding, nor whether certain tasks generalize well across users, or if individualized task selection would yield a higher decoding accuracy.Methods: To increase BCI efficiency, we tested whether distributed patterns of 3T-fMRI brain activation evoked by two-second mental tasks could be reliably discriminated in 2- to 7-class classification. In addition, we identified optimal mental-task combinations for high-accuracy classification across all classes. Finally, we examined whether individualized task selection-based on subjects' previous decoding performance (accuracy-based tasks) or their subjective preference (preference-based tasks)-was superior to the other in a yes/no communication paradigm.Results: The 2-class decoding resulted in a mean accuracy of 78% and 3- to 7-class accuracies were above chance level. Mental calculation and spatial navigation were most frequently associated with the highest decoding accuracy. Furthermore, subjects could encode yes/no answers using their accuracy-based and preference-based tasks with mean accuracies of 83% and 81%, respectively. This implies that this paradigm, using short encoding durations, is well-suited to the diversity of patients and could greatly increase BCI efficiency.Impact Statement This study advances functional magnetic resonance imaging (fMRI)-based brain-computer interfaces (BCIs) by showing that brain activation evoked by two-second mental tasks can be reliably decoded with multi-voxel pattern analysis, significantly improving fMRI-BCI efficiency while still achieving high accuracy. By exploring the differentiability of seven different mental tasks, using binary and multiclass classification of up to seven classes, and individualized task selection, we provide insights into optimizing mental-task paradigms for patient-tailored fMRI-BCIs. Given the variability of cognitive abilities in motor-impaired individuals, patient-tailored BCIs with a diverse range of mental tasks are highly welcome. These findings contribute to faster, more intuitive, and less cognitively demanding hemodynamic BCIs
Willingness to pay for animal welfare across labels, products, consumers, and time
No full textIn recent years, the number of labels indicating improved animal welfare conditions on meat products has increased making it difficult for consumers to understand, evaluate, and compare husbandry conditions across products. Based on a discrete choice experiment implemented in three cross-section surveys over a period of 15 months with a total of 6000 German respondents, we estimate the willingness to pay (WTP) for various levels of animal welfare associated with different meat products. We use three existing labels with overlapping animal welfare requirements mimicking the situation in the German meat market: The well-established organic label as well as a binary animal welfare label by the Animal Welfare Initiative and a multi-level animal husbandry label which were introduced in Germany in 2015 and 2019, respectively. We show that the multi-level label scheme leads to more product differentiation and, subsequently, higher WTP estimates. WTP further depends on meat type, where animal welfare improvements for beef and chicken products are valued much higher compared to those for pork. WTP for the organic and the highest level of the husbandry label increases with higher household incomes. WTP for these labels on chicken is also higher among women
Brain development and musical skills:A longitudinal twin study on brain developmental trajectories and sensorimotor synchronization
No full textThere are individual differences in brain developmental patterns, yet it is unknown to what extent these may be driven by enriched experiences. Moreover, it is not well known whether enriched experiences may result in attenuated or accelerated brain development. Studying the relation between music performance and the brain using a large longitudinal twin study provides a framework for better understanding the genetic and environmental effects on brain development in childhood. The present region-of-interest study tested whether individual differences in sensorimotor synchronization with an auditorily cued finger tapping task are related to individual differences in developmental brain trajectories and if this relation was genetically or environmentally driven. The present study included a longitudinal twin design with up to 3 MRI waves of data (7–14 years old; N<inf>t1</inf> = 418, N<inf>T2</inf> = 367, N<inf>T3</inf> = 228). In line with our preregistered hypotheses, results showed that attenuated patterns of brain development in 27 % of motor and affective ROIs were associated with SMS performance independent of socio-economic status effects. Furthermore, brain-behavior associations were at least partly driven by shared and unique environmental/measurement error effects, in addition to genetic influences. Possibly, attenuated brain development may be indicative of prolonged brain plasticity related to enriched environmental experiences, such as musical training, in addition to predisposing genetic factors
From cells to circuits:Transdiagnostic mechanisms of dysfunction in pompe disease and niemann-pick disease type c
Get PDFMet onderdanigheid bouw je geen Europese defensie
No full textEuropa moet een onafhankelijke defensie durven bouwen die niet onderhevig is aan de Amerikaanse grillen. Zonder strategische assertiviteit dreigt Europa machteloos te zijn in een gevaarlijke wereld
Minimum sample size calculation for radiomics-based binary outcome prediction models:Theoretical framework and practical example
No full textBACKGROUND AND PURPOSE: Determining the appropriate sample size for developing robust radiomics-based binary outcome prediction models and identifying the maximum number of predictors safely allowable within a fixed dataset size remain critical yet challenging tasks. This study aims to propose and demonstrate a structured method for addressing these issues, enhancing methodological rigor and practicality in radiomics research. MATERIALS AND METHODS: We introduce a comprehensive sample size calculation framework for binary outcome prediction models in radiomic studies. The proposed approach integrates three key criteria: (1) maintaining a global shrinkage factor (S) = 0.9 to control model overfitting, (2) ensuring a minimal absolute difference between apparent and adjusted performance metrics, and (3) precisely estimating the overall outcome risk. Additionally, we develop an accessible online calculation tool enabling researchers to efficiently determine either the minimum sample size or the maximum number of predictors permissible, based on clearly defined statistical parameters. RESULTS: The presented method systematically addresses model overfitting by integrating a global shrinkage factor into the calculation, providing robust estimates compared with traditional heuristic approaches ("rules of thumb"). Practical examples demonstrate that this structured method effectively balances predictive accuracy and generalizability, while the online tool provides researchers with a user-friendly platform to perform the necessary calculations. CONCLUSION: Clear justification of sample size decisions is essential for developing reliable predictive models in radiomics research. By adopting a structured and rigorous calculation method, researchers can effectively minimize overfitting, ensure accurate risk estimation, and substantially enhance the reliability and validity of their predictive models
Slimme huizen in een empathische zorgomgeving?
No full textDoor de combinatie van Informatie en Communicatie Technologie (ICT), slimme sensoren, big data en Artificiële Intelligentie (AI) lijkt het mogelijk om mensen met een beginnende maar snel toenemende zorgvraag (cognitief, fysiek of in combinatie) te ondersteunen. Er wordt in dit verband wel gesproken over slimme huizen die een onderdeel vormen van een ‘empathische omgeving’, waarbij een huis, mantelzorgers en professionele verzorgers samen een optimale combinatie van autonomie, zelfredzaamheid en zorg mogelijk proberen te maken
Making the Invisible Visible: Opportunities and points of contention arising from partnerships for the detection and investigation of human trafficking victims
No full textMensenhandel blijft zowel in Nederland als wereldwijd ondergedetecteerd en ondervervolgd. Opsporingsdiensten en banken hebben elk wettelijke plichten en expertise met betrekking tot de detectie van slachtoffers van dit misdrijf, maar hun inspanningen zijn vooralsnog voornamelijk gericht op de aanpak van andere winstgevende vormen van criminaliteit, zoals witwassen en het financieren van terrorisme. Hierdoor worden de mogelijkheden die ontstaan uit samenwerkingsverbanden tussen deze publieke en private instellingen op het tevens lucratieve maar vaker meer verborgen misdrijf mensenhandel onvoldoende verkend of benut. Door de sterke punten van beide partijen te combineren binnen publiek-private samenwerkingsverbanden, kunnen opsporingsdiensten en banken bijdragen aan de proactieve detectie van slachtoffers van mensenhandel. Banken kunnen zoeken naar slachtoffers binnen realtime gegevens en melden ongebruikelijke transacties omtrent mensenhandel aan opsporingsdiensten, waardoor politie en justitie minder afhankelijk zijn van aangiften van slachtoffers en verklaringen van getuigen. Daarbij is het belangrijk dat deze partijen bewust zijn van de mogelijke twistpunten die kunnen ontstaan door de dubbele rol van banken als publieke poortwachter en private winstmaker. Dit artikel presenteert een eerste, verkennende analyse van de kansen en twistpunten die voortkomen uit publiek-private samenwerkingen aangaande mensenhandel. Het doel is om allen aan te moedigen door te gaan met het verkennen van innovatieve manieren om het veelal onzichtbare mensenhandel zichtbaarder te maken
Routine RNA-based analysis of potential splicing variants facilitates genomic diagnostics and reveals limitations of in silico prediction tools
No full textDNA variants affecting pre-mRNA splicing are an important cause of genetic disorders and remain challenging to interpret without experimental data. Although variant classification guidelines recommend experimental characterization of variant splicing effects, the added value of routine diagnostic investigation of patient mRNA splicing has not been systematically described. Here, we assessed the utility of pre-mRNA splicing analysis in a diagnostic setting for 202 suspected splice-altering variants from individuals referred for genetic testing. Pre-mRNA splicing was assessed in patient cells by RT-PCR, followed by agarose gel electrophoresis and Sanger sequencing and/or exon trapping assays. An effect on pre-mRNA splicing was demonstrated in 63% (n = 128/202) of the tested variants. Among the 177 variants initially classified as variants of uncertain significance (VUS), 54% (n = 96/177) were reclassified based on pre-mRNA splicing analysis, including 48% (n = 85/177) that were upgraded to likely pathogenic or pathogenic. We benchmarked the splice prediction algorithms SpliceAI, SQUIRLS, SPiP, and Pangolin, the tools integrated in Alamut on this clinically relevant and experimentally validated dataset, and the CAGI6 splicing VUS dataset and found variable performance dependent on variant type and location. No single tool classified all variants equally well. We describe several examples of hard-to-predict effects and unexpected results highlighting the limitations of prediction tools, including a not previously described variant type affecting U12-splice site subtype. In summary, we provide a framework for RNA-based analysis in a molecular diagnostic setting, demonstrate the added value of routine testing of RNA from individuals with suspected splice-altering variants, and highlight the limitations of in silico prediction tools.</p