Marina Diachenko

Functional excitation-inhibition ratio indicates near-critical oscillations across frequencies

Diachenko, M., Sharma, A., Smit, D. J. A., Mansvelder, H. D., Bruining, H., de Geus, E., Avramiea, A.-E. & Linkenkaer-Hansen, K., 2024, In: Imaging Neuroscience. 2, p. 1-17 17 p.

Research output: Contribution to journal › Article* › Academic › peer-review

Robin’s Viewer: Using deep-learning predictions to assist EEG annotation

Weiler, R., Diachenko, M., Juarez-Martinez, E. L., Avramiea, A. E., Bloem, P. & Linkenkaer-Hansen, K., 19 Jan 2023, In: Frontiers in neuroinformatics. 16, 1025847.

Research output: Contribution to journal › Article* › Academic › peer-review

Improved Manual Annotation of EEG Signals through Convolutional Neural Network Guidance

Diachenko, M., Houtman, S. J., Juarez-Martinez, E. L., Ramautar, J. R., Weiler, R., Mansvelder, H. D., Bloem, P. & Linkenkaer-Hansen, K., Oct 2022, In: eNeuro. 9, 5, p. 1-14 14 p., ENEURO.0160-22.2022.

Research output: Contribution to journal › Article* › Academic › peer-review

Specialization

Focus of research

Functional excitation-inhibition ratio indicates near-critical oscillations across frequencies

Robin’s Viewer: Using deep-learning predictions to assist EEG annotation

Improved Manual Annotation of EEG Signals through Convolutional Neural Network Guidance

Marina Diachenko

Specialization

Focus of research

Functional excitation-inhibition ratio indicates near-critical oscillations across frequencies

Robin’s Viewer: Using deep-learning predictions to assist EEG annotation

Improved Manual Annotation of EEG Signals through Convolutional Neural Network Guidance

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