Emerging techniques in statistical analysis of neural data
Author:
Publisher
Springer Science and Business Media LLC
Subject
Cellular and Molecular Neuroscience,Cognitive Neuroscience,Sensory Systems
Link
http://link.springer.com/article/10.1007/s10827-019-00709-5/fulltext.html
Reference8 articles.
1. Breault, M., Sacré, P., Gale, J. T., & Sarma, S. V. (2018). An exploratory data analysis method for identifying brain regions of interest and frequency bands of interest from large scale recordings. Journal of Computational Neuroscience. https://doi.org/10.1007/s10827-018-0705-9 .
2. Chen, Y., Xin, Q., Ventura, V., & Kass, R. E. (2018). Stability of point process spiking neuron models. Journal of Computational Neuroscience. https://doi.org/10.1007/s10827-018-0695-7 .
3. Grappe, A., Sarma, S. V., Sacré, P., et al. (2018). An intracerebral exploration of functional connectivity during word production. Journal of Computational Neuroscience. https://doi.org/10.1007/s10827-018-0699-3 .
4. Han, S., Chu, J. U., Park, J. W., & Youn, I. (2018). Linear feature projection-based real-time decoding of limb state from dorsal root ganglion recordings. Journal of Computational Neuroscience. https://doi.org/10.1007/s10827-018-0686-8 .
5. Luckett, P., Pavelescu, E., McDonald, T., Hively, L., & Ochoa, J. (2018). Predicting state transitions in brain dynamics through spectral difference of phase-space graphs. Journal of Computational Neuroscience. https://doi.org/10.1007/s10827-018-0700-1 .
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