[HTML][HTML] The role of alpha oscillations among the main neuropsychiatric disorders in the adult and developing human brain: evidence from the last 10 years of …
Alpha oscillations (7–13 Hz) are the dominant rhythm in both the resting and active brain.
Accordingly, translational research has provided evidence for the involvement of aberrant …
Accordingly, translational research has provided evidence for the involvement of aberrant …
[HTML][HTML] Deep learning and machine learning in psychiatry: a survey of current progress in depression detection, diagnosis and treatment
Informatics paradigms for brain and mental health research have seen significant advances
in recent years. These developments can largely be attributed to the emergence of new …
in recent years. These developments can largely be attributed to the emergence of new …
Brain functional networks based on resting-state EEG data for major depressive disorder analysis and classification
B Zhang, G Yan, Z Yang, Y Su… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
If the brain is regarded as a system, it will be one of the most complex systems in the
universe. Traditional analysis and classification methods of major depressive disorder …
universe. Traditional analysis and classification methods of major depressive disorder …
Similarly in depression, nuances of gut microbiota: Evidences from a shotgun metagenomics sequencing study on major depressive disorder versus bipolar disorder …
H Rong, X Xie, J Zhao, W Lai, M Wang, D Xu… - Journal of psychiatric …, 2019 - Elsevier
Background To probe the differences of gut microbiota among major depressive disorder
(MDD), bipolar disorder with current major depressive episode (BPD) and health …
(MDD), bipolar disorder with current major depressive episode (BPD) and health …
Major depressive disorder classification based on different convolutional neural network models: deep learning approach
The human brain is characterized by complex structural, functional connections that
integrate unique cognitive characteristics. There is a fundamental hurdle for the evaluation …
integrate unique cognitive characteristics. There is a fundamental hurdle for the evaluation …
[HTML][HTML] Resting-state EEG signal for major depressive disorder detection: A systematic validation on a large and diverse dataset
Major depressive disorder (MDD) is a global healthcare issue and one of the leading causes
of disability. Machine learning combined with non-invasive electroencephalography (EEG) …
of disability. Machine learning combined with non-invasive electroencephalography (EEG) …
Multivariate pattern analysis of EEG-based functional connectivity: A study on the identification of depression
H Peng, C Xia, Z Wang, J Zhu, X Zhang, S Sun… - Ieee …, 2019 - ieeexplore.ieee.org
Resting-state electroencephalography (EEG) studies have shown significant group
differences in functional connectivity networks between patients with depression and healthy …
differences in functional connectivity networks between patients with depression and healthy …
[HTML][HTML] The role of quantitative EEG in the diagnosis of neuropsychiatric disorders
LL Popa, H Dragos, C Pantelemon… - Journal of medicine …, 2020 - ncbi.nlm.nih.gov
Quantitative electroencephalography (QEEG) is a modern type of electroencephalography
(EEG) analysis that involves recording digital EEG signals which are processed …
(EEG) analysis that involves recording digital EEG signals which are processed …
Machine learning approaches for prediction of bipolar disorder based on biological, clinical and neuropsychological markers: A systematic review and meta-analysis
F Colombo, F Calesella, MG Mazza… - Neuroscience & …, 2022 - Elsevier
Applying machine learning (ML) to objective markers may overcome prognosis uncertainty
due to the subjective nature of the diagnosis of bipolar disorder (BD). This PRISMA …
due to the subjective nature of the diagnosis of bipolar disorder (BD). This PRISMA …
[HTML][HTML] Resting-state EEG power and coherence vary between migraine phases
Background Migraine is characterized by a series of phases (inter-ictal, pre-ictal, ictal, and
post-ictal). It is of great interest whether resting-state electroencephalography (EEG) is …
post-ictal). It is of great interest whether resting-state electroencephalography (EEG) is …