Mouse-threat-and-escape-CBRAIN/datacite.yml

authors:
  -
    firstname: "Hio-Been"
    lastname: "Han"
    affiliation: "Massachusetts Institute of Technology; Korea Institute of Science and Technology"
    id: "ORCID:0000-0001-5669-4054"
  -
    firstname: "SungJun"
    lastname: "Cho"
    affiliation: "Oxford University; Korea Institute of Science and Technology"
  -
    firstname: "DaYoung"
    lastname: "Jung"
    affiliation: "Korea University; Korea Institute of Science and Technology"
  -
    firstname: "Jee Hyun"
    lastname: "Choi"
    affiliation: "Korea Institute of Science and Technology; Korea University of Science and Technology"
    id: "ORCID:0000-0003-1901-6144"

title: "Dataset of Mouse Escape Responses and mPFC-BLA LFP recordings"

description: |
The structure of our dataset follows the BIDS-EEG format introduced by Pernet et al. (2019). Within the top-level directory data_BIDS, the LFP data are organized by the path names starting with sub-*. These LFP recordings (n = 8 mice) were recorded under the threat-and-escape experimental paradigm, which involves dynamic interactions with a spider robot (Kim et al., 2020).
This experiment was conducted in two separate conditions: (1) the solitary condition (denoted as "Single"), in which a mouse was exposed to a robot alone in the arena, and (2) the group condition (denoted as "Group"), in which a group of mice encountered a robot together. A measurement device called the CBRAIN headstage was used to record LFP data at a sampling rate of 1024 Hz. The recordings were taken from the medial prefrontal cortex (Channel 1) and the basolateral amygdala (Channel 2).
For a more comprehensive understanding of the experimental methods and procedures, please refer to Kim et al. (2020).

keywords:
  - Neuroscience
  - Electrophysiology
  - EEG
  - Mouse EEG
  - Brain oscillations

license:
  name: "Creative Commons Attribution 4.0 International Public License"
  url: "https://creativecommons.org/licenses/by/4.0/"

funding:
  - "KIST Intramural Grant, 2E31511-KIST"
  - "ETRI Non-CMOS Neuromorphic Device Basic Technology Grant, 21YB3210-ETRI"
  - "National Research Foundation (NRF) of Korea, 2022R1A2C3003901"
  - "National Research Foundation (NRF) of Korea, 2022R1A6A3A01085957"

references:
  -
    id: "doi:10.1038/s41597-019-0104-8"
    reftype: "IsSupplementTo"
    citation: "Pernet, C. R., Appelhoff, S., Gorgolewski, K. J., Flandin, G., Phillips, C., Delorme, A., Oostenveld, R. (2019). EEG-BIDS, an extension to the brain imaging data structure for electroencephalography. Scientific Data, 6(1):103."
  -
    id: "doi:10.1126/sciadv.abb9841"
    reftype: "IsSupplementTo"
    citation: "Kim, J., Kim, C., Han, H. B., Cho, C. J., Yeom, W., Lee, S. Q., Choi, J. H. (2020). A bird’s-eye view of brain activity in socially interacting mice through mobile edge computing (MEC). Science Advances, 6(49):eabb9841."
  -
    id: "doi:10.1007/978-3-319-24574-4_28"
    reftype: "IsSupplementTo"
    citation: "Ronneberger, O., Fischer, P., Brox, T. (2015). U-net: Convolutional networks for biomedical image segmentation. In Medical Image Computing and Computer-Assisted Intervention–MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III 18 (pp. 234-241). Springer International Publishing."
  -
    id: "doi:10.1073/pnas.2308762120"
    reftype: "IsSupplementTo"
    citation: "Han, H. B., Shin H. S., Jeong Y., Kim, J., Choi, J. H. (2023). Dynamic switching of neural oscillations in the prefrontal–amygdala circuit for naturalistic freeze-or-flight. Proceedings of the National Academy of Sciences, 120(37):e230876212."
  -
    id: "doi:10.1088/1741-2552/acdffd"
    reftype: "IsSupplementTo"
    citation: "Cho, S., Choi, J. H. (2023). A guide towards optimal detection of transient oscillatory bursts with unknown parameters. Journal of Neural Engineering, 20:046007."
    
resourcetype: Dataset

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