Search results for "EEG"
showing 10 items of 313 documents
Discriminatory Brain Processes of Native and Foreign Language in Children with and without Reading Difficulties
2022
The association between impaired speech perception and reading difficulty has been well established in native language processing, as can be observed from brain activity. However, there has been scarce investigation of whether this association extends to brain activity during foreign language processing. The relationship between reading skills and neuronal speech representation of foreign language remains unclear. In the present study, we used event-related potentials (ERPs) with high-density EEG to investigate this question. Eleven- to 13-year-old children typically developed (CTR) or with reading difficulties (RD) were tested via a passive auditory oddball paradigm containing native (Finn…
Activity level in left auditory cortex predicts behavioral performance in inhibition tasks in children
2022
Funding Information: We are grateful to Hanna-Maija Lapinkero, Suvi Karjalainen, Maria Vesterinen & Janne Rajaniemi for help with data collection and to Amit Jaiswal, Erkka Heinilä and Jukka Nenonen for their help with preprocessing and scripting. This work was supported by EU project ChildBrain (Horizon2020 Marie Skłodowska-Curie Action (MSCA) Innovative Training Network (ITN) – European Training Network (ETN), grant agreement no. 641652) and the Academy of Finland grant number 311877. Publisher Copyright: © 2022 Sensory processing during development is important for the emerging cognitive skills underlying goal-directed behavior. Yet, it is not known how auditory processing in children is…
Neiropsiholoģisko datu statistiskā analīze
2020
Darbs ir veltīts neiropsiholoģisko datu – elektroencefalogrāfijas (EEG) signālu – izpētei. Darba mērķis ir izpētīt galvenās EEG signālu tendenču noteikšanas metodes indivīdam, kā arī salīdzināt EEG signālu jaudu vairākiem subjektiem. Tiek definēti EEG signāli, apskatītas metodes signālu jaudas un signālu kanālu novērošanai – Furjē transformācija, korelācija un koherence. Praktiskajā daļā ir apskatīts hipotēžu testu un regresijas analīzes pielietojums reālu datu modelim, lai atrastu būtiskākās EEG signālu jaudas atšķirības starp indivīdiem, signālu mērīšanas laiku un acu stāvokli.
Channel Increment Strategy-Based 1D Convolutional Neural Networks for Seizure Prediction Using Intracranial EEG
2022
The application of intracranial electroencephalogram (iEEG) to predict seizures remains challenging. Although channel selection has been utilized in seizure prediction and detection studies, most of them focus on the combination with conventional machine learning methods. Thus, channel selection combined with deep learning methods can be further analyzed in the field of seizure prediction. Given this, in this work, a novel iEEG-based deep learning method of One-Dimensional Convolutional Neural Networks (1D-CNN) combined with channel increment strategy was proposed for the effective seizure prediction. First, we used 4-sec sliding windows without overlap to segment iEEG signals. Then, 4-sec …
Viiden opettajan kokemuksia frisbeegolfista
2014
Frisbeegolfin suosio on kasvanut nopeasti 2000-luvun aikana Suomessa. Erityisesti laji on herättänyt kiinnostusta nuorten keskuudessa. Frisbeegolfin suosion kasvusta huolimatta ei suomenkielistä tutkimusta lajista ole aikaisemmin juurikaan tehty. Tämä pro gradu -tutkielma käsittää kirjallisuuskatsauksen frisbeegolfin historiaan, sääntöihin, varusteisiin, kenttiin, ja tekniikoihin. Lisäksi tutkimuksessa haastateltiin viittä liikunnanopettajaa eri puolilta Suomea. Haastateltavaksi valittiin kolme miestä ja kaksi naista. Kaikilla haastatelluilla oli omakohtaisia kokemuksia frisbeegolfin opetuksesta. Saadut vastaukset litteroitiin, jonka jälkeen ne analysoitiin grounded theory -menetelmällä. Gr…
Driver Distraction Detection Using Bidirectional Long Short-Term Network Based on Multiscale Entropy of EEG
2022
Driver distraction diverting drivers' attention to unrelated tasks and decreasing the ability to control vehicles, has aroused widespread concern about driving safety. Previous studies have found that driving performance decreases after distraction and have used vehicle behavioral features to detect distraction. But how brain activity changes while distraction remains unknown. Electroencephalography (EEG), a reliable indicator of brain activities has been widely employed in many fields. However, challenges still exist in mining the distraction information of EEG in realistic driving scenarios with uncertain information. In this paper, we propose a novel framework based on Multi-scale entrop…
The impact of retro-cue validity on working memory representation: Evidence from electroencephalograms.
2022
Visual working memory (VWM) performance can be improved by retrospectively cueing an item. The validity of retro-cues has an impact on the mechanisms underlying the retro-cue effect, but how non-cued representations are handled under different retro-cue validity conditions is not yet clear. Here, we used electroencephalograms to investigate whether retro-cue validity can affect the fate of non-cued representations in VWM. The participants were required to perform a change-detection task using a retro-cue with 80% or 20% validity. Contralateral delay activity and the lateralized alpha power were used to assess memory storage and selective attention, respectively. The retro-cue could redirect…
The Relevance of a Conductor Competition for the Study of Emotional Synchronization Within and Between Groups in a Natural Musical Setting
2020
Group emotional dynamics are a central concern in the study of human interaction and communication. To study group emotions, the social context of a musical event in ecological conditions may overcome several limits of laboratory experiments and could provide a suitable ecological framework. This study aimed to evaluate if cultural events such as a conductor competition could welcome scientific research for the study of group emotional sharing. We led an observational study, which suggests that in this particular context, public, musicians and jury would agree to participate and to wear neurophysiological and physiological devices to monitor their emotional state during the competition. Sel…
Assessment of nonnegative matrix factorization algorithms for electroencephalography spectral analysis.
2020
AbstractBackgroundNonnegative matrix factorization (NMF) has been successfully used for electroencephalography (EEG) spectral analysis. Since NMF was proposed in the 1990s, many adaptive algorithms have been developed. However, the performance of their use in EEG data analysis has not been fully compared. Here, we provide a comparison of four NMF algorithms in terms of accuracy of estimation, stability (repeatability of the results) and time complexity of algorithms with simulated data. In the practical application of NMF algorithms, stability plays an important role, which was an emphasis in the comparison. A Hierarchical clustering algorithm was implemented to evaluate the stability of NM…
METHODOLOGY DEVELOPMENT IN ADULT LEARNING RESEARCH. COMBINING PHYSIOLOGICAL REACTIONS AND LEARNING EXPERIENCES IN SIMULATION-BASED LEARNING ENVIRONME…
2020
We aim to clarify whether physiological measurement technologies can be used in combination with traditional educational research methods to investigate learning experience. We developed an interdisciplinary research design for multilevel investigation of adult learning experience. We collected data in aviation simulations and forestry simulations, to show both similarities and differences between different learning situations. Both settings utilize high quality virtual simulations allowing learning to occur in near authentic situations. The learning situations were structured pedagogically in a similar way. They involve learner-instructor interaction in a one-on-one setting and follow a tr…