Special Issue “Advances in Neuroimaging Data Processing”
Source abstract
Abstract
The development of in vivo neuroimaging technology has led to an incredible amount of digital information concerning the brain [...]
Only a short abstract or summary was supplied by the source.
Source: crossref · Quality: short
Research context
OpenAlex topics: Functional Brain Connectivity Studies · EEG and Brain-Computer Interfaces · Neural dynamics and brain function
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Baltic Center for Neurotechnology and Artificial Intelligence, Immanuel Kant Baltic Federal University, Kaliningrad 236041, Russia
Center for Biomedical Technology, Technical University of Madrid, Campus Montegancedo, 28223 Madrid, Spain
Funding
Program ‘Priority-2030’ of Immanuel Kant Baltic Federal University of Ministry of Education and Science of Russian Federation
References (18)
Show source-provided references
1. Contribution of Neuroimaging Studies to Understanding Development of Human Cognitive Brain Functions10.3389/fnhum.2016.00464 ↗
2. Physical principles of brain–computer interfaces and their applications for rehabilitation, robotics and control of human brain states10.1016/j.physrep.2021.03.002 ↗
3. The search for imaging biomarkers in psychiatric disorders10.1038/nm.4190 ↗
4. The physics of brain network structure, function and control10.1038/s42254-019-0040-8 ↗
5. Functional networks of the brain: From connectivity restoration to dynamic integration10.3367/UFNe.2020.06.038807 ↗
6. Faes, A., Vantieghem, I., and Van Hulle, M.M. (2022). Neural Networks for Directed Connectivity Estimation in Source-Reconstructed EEG Data. Appl. Sci., 12.10.3390/app12062889 ↗
7. Maher, C., D’Souza, A., Barnett, M., Kavehei, O., Wang, C., and Nikpour, A. (2022). Structure-Function Coupling Reveals Seizure Onset Connectivity Patterns. Appl. Sci., 12.10.1101/2022.09.21.22280190 ↗
8. Chen, X., Xu, G., Zhang, S., Zhang, X., and Teng, Z. (2022). Building Networks with a New Cross-Bubble Transition Entropy for Quantitative Assessment of Mental Arithmetic Electroencephalogram. Appl. Sci., 12.10.3390/app122111165 ↗
9. Pavlov, A., Dubrovskii, A., Pavlova, O., and Semyachkina-Glushkovskaya, O. (2021). Effects of Sleep Deprivation on the Brain Electrical Activity in Mice. Appl. Sci., 11.10.3390/app11031182 ↗
10. Chholak, P., Kurkin, S., Hramov, A., and Pisarchik, A. (2021). Event-Related Coherence in Visual Cortex and Brain Noise: An MEG Study. Appl. Sci., 11.10.3390/app11010375 ↗
11. De La Pava Panche, I., Álvarez-Meza, A., Herrera Gómez, P., Cárdenas-Peña, D., Ríos Patiño, J., and Orozco-Gutiérrez, Á. (2021). Kernel-Based Phase Transfer Entropy with Enhanced Feature Relevance Analysis for Brain Computer Interfaces. Appl. Sci., 11.10.3390/app11156689 ↗
12. Kuc, A., Kurkin, S., Maksimenko, V., Pisarchik, A., and Hramov, A. (2021). Monitoring Brain State and Behavioral Performance during Repetitive Visual Stimulation. Appl. Sci., 11.10.3390/app112311544 ↗
13. Van Den Kerchove, A., Libert, A., Wittevrongel, B., and Van Hulle, M. (2022). Classification of Event-Related Potentials with Regularized Spatiotemporal LCMV Beamforming. Appl. Sci., 12.10.3390/app12062918 ↗
14. Ngo, B., and Nguyen, T. (2022). A Semi-Automatic Wheelchair with Navigation Based on Virtual-Real 2D Grid Maps and EEG Signals. Appl. Sci., 12.10.3390/app12178880 ↗
15. Sánchez-Cifo, M., Montero, F., and López, M. (2021). MuseStudio: Brain Activity Data Management Library for Low-Cost EEG Devices. Appl. Sci., 11.10.3390/app11167644 ↗
16. AI in health and medicine10.1038/s41591-021-01614-0 ↗
17. A survey on explainable artificial intelligence (xai): Toward medical xai10.1109/TNNLS.2020.3027314 ↗
18. Explainable Artificial Intelligence for Medicine