This is an outdated version published on 2024-07-19 04:48:56 UTC. Read the most recent version.
Preprint / Version 1

Data for Brain Reference Architecture of YS24LongitudinallySegmentedDistalCA1andPeriphery

##article.authors##

DOI:

https://doi.org/10.51094/jxiv.819

Keywords:

Brain Reference Architecture, Hippocampal formation, Longitudinal axis, Transverse axis

Abstract

The hippocampal formation plays a crucial role in learning, memory, and spatial navigation. The connections of four regions of the hippocampal formation (DG, CA3, CA1, S) were investigated in longitudinal axis, transverse axis, and laminar organization, respectively. To define uniform circuits, a group of neurons that have the same meaning of the function, the standard division of longitudinal axis, transverse axis, and laminar organization was decided. Using the algorithm of integrating these three directions, the standard organizational circuits and connections of the hippocampal formation were created.

Conflicts of Interest Disclosure

The authors have no competing interests to declare.

Downloads *Displays the aggregated results up to the previous day.

Download data is not yet available.

References

an Allen Brain Reference Atlas. (n.d.). Allen developing human brain atlas ontology. Retrieved from https://atlas.brain-map.org/

Bienkowski, M. S., Bowman, I., Song, M. Y., Gou, L., Ard, T., Cotter, K., ... Dong, H.-W. (2018, October). Integration of gene expression and brain-wide connectivity reveals the multiscale organization of mouse hippocampal networks. Nature Neuroscience, 21(11), 1628-1643. Retrieved from http:// dx.doi.org/10.1038/s41593-018-0241-y DOI: 10.1038/s41593-018-0241-y

Dolorfo, C. L., & Amaral, D. G. (1998, August). Entorhinal cortex of the rat: Organization of in- trinsic connections. The Journal of Comparative Neurology, 398(1), 49-82. Retrieved from http://dx.doi.org/10.1002/(sici)1096-9861(19980817)398:1<49::aid-cne4>3.0.co;2-9 DOI: 10.1002/(sici)1096-9861(19980817)398:1<49::aid-cne4>3.0.co;2-9

Fanselow, M. S., & Dong, H.-W. (2010, January). Are the dorsal and ventral hippocampus functionally distinct structures? Neuron, 65(1), 7-19. Retrieved from http://dx.doi.org/10.1016/j .neuron.2009.11.031 DOI: 10.1016/j.neuron.2009.11.031

Honda, Y., & Ishizuka, N. (2015, March). Topographic distribution of cortical projection cells in the rat subiculum. Neuroscience Research, 92, 1-20. Retrieved from http://dx.doi.org/10.1016/ j.neures.2014.11.011 DOI: 10.1016/j.neures.2014.11.011

Honda, Y., & Shibata, H. (2017). Organizational connectivity among the ca1, subiculum, pre- subiculum, and entorhinal cortex in the rabbit. Journal of Comparative Neurology, 525(17), 3705-3741. Retrieved from https://onlinelibrary.wiley.com/doi/abs/10.1002/cne.24297 DOI: https://doi.org/10.1002/cne.24297

Lee, H., GoodSmith, D., & Knierim, J. J. (2020, October). Parallel processing streams in the hip- pocampus. Current Opinion in Neurobiology, 64, 127-134. Retrieved from http://dx.doi.org/ 10.1016/j.conb.2020.03.004 DOI: 10.1016/j.conb.2020.03.004

Ohara, S., Blankvoort, S., Nair, R. R., Nigro, M. J., Nilssen, E. S., Kentros, C., & Witter, M. P. (2021, March). Local projections of layer vb-to-va are more prominent in lateral than in me- dial entorhinal cortex. eLife, 10. Retrieved from http://dx.doi.org/10.7554/eLife.67262 DOI: 10.7554/elife.67262

Ohara, S., Rannap, M., Tsutsui, K.-I., Draguhn, A., Egorov, A. V., & Witter, M. P. (2023, Jan- uary). Hippocampal-medial entorhinal circuit is differently organized along the dorsoventral axis in rodents. Cell Reports, 42(1), 112001. Retrieved from http://dx.doi.org/10.1016/ j.celrep.2023.112001 DOI: 10.1016/j.celrep.2023.112001

Taniguchi, A., Fukawa, A., & Yamakawa, H. (2022, July). Hippocampal formation-inspired probabilistic generative model. Neural Networks, 151, 317-335. Retrieved from http://dx.doi.org/10.1016/ j.neunet.2022.04.001 DOI: 10.1016/j.neunet.2022.04.001

Witter, M. P. (2007, November). Intrinsic and extrinsic wiring of ca3: Indications for connectional heterogeneity. Learning amp; Memory, 14(11), 705-713. Retrieved from http://dx.doi.org/ 10.1101/lm.725207 DOI: 10.1101/lm.725207

Yamakawa, H. (2021). The whole brain architecture approach: Accelerating the development of artificial general intelligence by referring to the brain. Neural Networks, 144, 478-495. DOI: 10.1016/j.ne- unet.2021.09.004

Yamakawa, H., Arakawa, N., Tawatsuji, Y., Fukawa, A., Ashihara, Y., & Matsuo, Y. (2023). Proposal of an function-oriented scid method for reverse engineering a wide range of brain regions. In 32nd annual computational neuroscience meeting (p. 127).

Downloads

Posted


Submitted: 2024-07-11 09:15:34 UTC

Published: 2024-07-19 04:48:56 UTC

Versions

Reason(s) for revision

Section
Biology, Life Sciences & Basic Medicine

License

Copyright (c) 2024 Yudai Suzuki
Yoshiko Honda
Shinya Ohara
Ayako Fukawa
Hiroshi Yamakawa

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.