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Emotion processing dysfunction in Alzheimer's disease: an overview of behavioral findings, systems neural correlates, and underlying neural biology
We described behavioral studies to highlight emotional processing deficits in Alzheimer's
disease (AD). The findings suggest prominent deficit in recognizing negative emotions …
disease (AD). The findings suggest prominent deficit in recognizing negative emotions …
Use of autobiographical stimuli as a mood manipulation procedure: Systematic map** review
Background In recent years, mood induction procedures have been developed in
experimental settings that are designed to facilitate studying the impact of mood states on …
experimental settings that are designed to facilitate studying the impact of mood states on …
Non-linear processing and reinforcement learning to predict rTMS treatment response in depression
Background Forecasting the efficacy of repetitive transcranial magnetic stimulation (rTMS)
therapy can lead to substantial time and cost savings by preventing futile treatments. To …
therapy can lead to substantial time and cost savings by preventing futile treatments. To …
Maximum weight multi-modal information fusion algorithm of electroencephalographs and face images for emotion recognition
M Wang, Z Huang, Y Li, L Dong, H Pan - Computers & Electrical …, 2021 - Elsevier
In view of the low accuracy of the traditional emotion recognition methods based on facial
expressions, an emotion recognition method based on maximum weight multi-modal …
expressions, an emotion recognition method based on maximum weight multi-modal …
[HTML][HTML] Neural modulation enhancement using connectivity-based EEG neurofeedback with simultaneous fMRI for emotion regulation
Emotion regulation plays a key role in human behavior and overall well-being.
Neurofeedback is a non-invasive self-brain training technique used for emotion regulation to …
Neurofeedback is a non-invasive self-brain training technique used for emotion regulation to …
[HTML][HTML] Comparing EEG-based epilepsy diagnosis using neural networks and wavelet transform
Epilepsy is a common neurological disorder characterized by the recurrence of seizures,
which can significantly impact the lives of patients. Electroencephalography (EEG) can …
which can significantly impact the lives of patients. Electroencephalography (EEG) can …
Enhancing the accuracy of electroencephalogram-based emotion recognition through Long Short-Term Memory recurrent deep neural networks
Introduction Emotions play a critical role in human communication, exerting a significant
influence on brain function and behavior. One effective method of observing and analyzing …
influence on brain function and behavior. One effective method of observing and analyzing …
Source localization and functional network analysis in emotion cognitive reappraisal with EEG-fMRI integration
W Li, W Zhang, Z Jiang, T Zhou, S Xu… - Frontiers in Human …, 2022 - frontiersin.org
Background The neural activity and functional networks of emotion-based cognitive
reappraisal have been widely investigated using electroencephalography (EEG) and …
reappraisal have been widely investigated using electroencephalography (EEG) and …
A methodology for emotional intelligence testing in elderly people with low-cost EEG and PPG devices
Emotional intelligence (EI) is a basic concept in psychology that is gaining social
importance. According to Goleman, it refers to the ability to be aware of and to handle one's …
importance. According to Goleman, it refers to the ability to be aware of and to handle one's …
Probing fMRI brain connectivity and activity changes during emotion regulation by EEG neurofeedback
Despite the existence of several emotion regulation studies using neurofeedback,
interactions among a small number of regions were evaluated, and therefore, further …
interactions among a small number of regions were evaluated, and therefore, further …