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{"references": ["Kim, G., Norman, K. A., & Turk-Browne, N. B. (2017). Neural Differentiation of Incorrectly Predicted Memories. The Journal of Neuroscience, 37(8), 2022-2031. doi:10.1523/jneurosci.3272-16.2017", "Kriegeskorte, N., Mur, M., Ruff, D. A., Kiani, R., Bodurka, J., Esteky, H., \u2026 Bandettini, P. A. (2008). Matching Categorical Object Representations in Inferior Temporal Cortex of Man and Monkey. Neuron, 60(6), 1126\u20131141. https://doi.org/10.1016/j.neuron.2008.10.043", "Turk-Browne, N. B., Simon, M. G., & Sederberg, P. B. (2012). Scene Representations in Parahippocampal Cortex Depend on Temporal Context. Journal of Neuroscience, 32(21), 7202\u20137207. https://doi.org/10.1523/JNEUROSCI.0942-12.2012", "Hutchinson, J. B., Pak, S. S., & Turk-Browne, N. B. (2016). Biased Competition during Long-term Memory Formation. Journal of Cognitive Neuroscience, 28(1), 187\u2013197. https://doi.org/10.1162/jocn_a_00889", "Haxby, J. V., Guntupalli, J. S., Connolly, A. C., Halchenko, Y. O., Conroy, B. R., Gobbini, M. I., \u2026 Ramadge, P. J. (2011). A common, high-dimensional model of the representational space in human ventral temporal cortex. Neuron, 72(2), 404\u2013416. https://doi.org/10.1016/j.neuron.2011.08.026", "Chen, J., Leong, Y. C., Honey, C. J., Yong, C. H., Norman, K. A., & Hasson, U. (2017). Shared memories reveal shared structure in neural activity across individuals. Nature Neuroscience, 20(1), 115\u2013125. https://doi.org/10.1038/nn.4450", "Simony, E., Honey, C. J., Chen, J., Lositsky, O., Yeshurun, Y., Wiesel, A., & Hasson, U. (2016). Dynamic reconfiguration of the default mode network during narrative comprehension. Nature Communications, 7, 12141. https://doi.org/10.1038/ncomms12141"]}
This is a collection of datasets used by BrainIAK tutorials. These datasets are pre-processed and ready to use. They have been condensed, by reducing the number of subjects from the original studies, to keep the file size small. Each tutorial is paired with a dataset as listed below. The file brainiak_datasets.zip contains the data for all the tutorials, and in unzipped form uses 18GB of space. If you wish to download data for specific tutorials, use the list below to find the correct dataset to download and use. Tutorial 2: VDC (Kim et al., 2017) and 02-data-handling (this is a simulated dataset) Tutorials 3-5: VDC (Kim et al., 2017) Tutorial 6: Ninety Six (Kriegeskorte et al., 2008) Tutorials 7: Face-scene (Turk-Browne et al., 2012). The script for within subject searchlight uses the VDC dataset. Tutorial 9: Face-scene (Turk-Browne et al., 2012) Tutorial 8: Latatt (Hutchinson et al., 2016) Tutorial 10: Pieman2 (Simony et al., 2016) Tutorial 11: Raider (Haxby et al., 2011) and Pieman2 (Simony et al., 2016) Tutorial 12: Sherlock_processed (Chen et al., 2017)
fmri, mvpa, brainiak, rsa, isc, isfc, fcma, real-time
fmri, mvpa, brainiak, rsa, isc, isfc, fcma, real-time
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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