AIMC Topic: Evoked Potentials
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How EEG preprocessing shapes decoding performance.
Communications biology
Jul 10, 2025
Electroencephalography (EEG) preprocessing varies widely between studies, but its impact on classification performance remains poorly understood. To address this gap, we analyzed seven experiments with 40 participants drawn from the public ERP CORE d...
Assessing the impact of artifact correction and artifact rejection on the performance of SVM- and LDA-based decoding of EEG signals.
NeuroImage
Jun 3, 2025
Numerous studies have demonstrated that eyeblinks and other large artifacts can decrease the signal-to-noise ratio of EEG data, resulting in decreased statistical power for conventional univariate analyses. However, it is not clear whether eliminatin...
Behavioural and EEG correlates of forward and backward priming-An exploratory study.
PloS one
May 8, 2025
During affective priming, perception of an emotional "prime stimulus" influences the reaction time to the subsequent emotional "target stimulus". If prime and target have the same valence (congruent trials), reactions to the target are faster than if...
Decoding of lexical items and grammatical features in EEG: A cross-linguistic study.
Neuropsychologia
Apr 23, 2025
Diverse evidence supports the theory that bilingual language users have language-invariant representations of concepts and grammatical forms such as argument structure. Here we extend that work to test the representation of morphosyntactic features a...
Neural correlates of the uncanny valley effect for robots and hyper-realistic masks.
PloS one
Mar 18, 2025
Viewing artificial objects and images that are designed to appear human can elicit a sense of unease, referred to as the 'uncanny valley' effect. Here we investigate neural correlates of the uncanny valley, using still images of androids (robots desi...
Machine learning classification of active viewing of pain and non-pain images using EEG does not exceed chance in external validation samples.
Cognitive, affective & behavioral neuroscience
Feb 18, 2025
Previous research has demonstrated that machine learning (ML) could not effectively decode passive observation of neutral versus pain photographs by using electroencephalogram (EEG) data. Consequently, the present study explored whether active viewin...
Beyond averaging: A transformer approach to decoding event related brain potentials.
NeuroImage
Jan 27, 2025
The objective of this study is to assess the potential of a transformer-based deep learning approach applied to event-related brain potentials (ERPs) derived from electroencephalographic (EEG) data. Traditional methods involve averaging the EEG signa...
Machine Learning-Based Diagnosis of Chronic Subjective Tinnitus With Altered Cognitive Function: An Event-Related Potential Study.
Ear and hearing
Jan 20, 2025
OBJECTIVES: Due to the absence of objective diagnostic criteria, tinnitus diagnosis primarily relies on subjective assessments. However, its neuropathological features can be objectively quantified using electroencephalography (EEG). Despite the exis...
Multi-Scale Pyramid Squeeze Attention Similarity Optimization Classification Neural Network for ERP Detection.
Neural networks : the official journal of the International Neural Network Society
Jan 7, 2025
Event-related potentials (ERPs) can reveal brain activity elicited by external stimuli. Innovative methods to decode ERPs could enhance the accuracy of brain-computer interface (BCI) technology and promote the understanding of cognitive processes. Th...
Machine learning based on event-related oscillations of working memory differentiates between preclinical Alzheimer's disease and normal aging.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Nov 24, 2024
OBJECTIVE: To apply machine learning approaches on EEG event-related oscillations (ERO) to discriminate preclinical Alzheimer's disease (AD) from age- and sex-matched controls.
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