AIMC Topic: Evoked Potentials

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Behavioural and EEG correlates of forward and backward priming-An exploratory study.

PloS one
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...

Neural correlates of the uncanny valley effect for robots and hyper-realistic masks.

PloS one
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
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
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
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
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
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.

Neural correlates of empathy in donation decisions: Insights from EEG and machine learning.

Neuroscience
Empathy is central to individual and societal well-being. Numerous studies have examined how trait of empathy affects prosocial behavior. However, little studies explored the psychological and neural mechanisms by which different dimensions of trait ...

Localized estimation of event-related neural source activity from simultaneous MEG-EEG with a recurrent neural network.

Neural networks : the official journal of the International Neural Network Society
Estimating intracranial current sources underlying the electromagnetic signals observed from extracranial sensors is a perennial challenge in non-invasive neuroimaging. Established solutions to this inverse problem treat time samples independently wi...

Social anxiety prediction based on ERP features: A deep learning approach.

Journal of affective disorders
BACKGROUND: Social Anxiety Disorder is traditionally diagnosed using subjective scales that may lack accuracy. Recently, EEG technology has gained importance for anxiety detection due to its ability to capture stable and objective neurophysiological ...