High_Resolution_Cortical_Spikes/datacite.yml

# Metadata for DOI registration according to DataCite Metadata Schema 4.1.
# For detailed schema description see https://doi.org/10.5438/0014

## Required fields

# The main researchers involved. Include digital identifier (e.g., ORCID)
# if possible, including the prefix to indicate its type.
authors:
  -
    firstname: "Csaba"
    lastname: "Horváth"
    affiliation: "Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Eötvös Loránd Research Network, Budapest, Hungary"
  -
    firstname: "Lili Fanni"
    lastname: "Tóth"
    affiliation: "Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary"
  -
    firstname: "István"
    lastname: "Ulbert"
    affiliation: "Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Eötvös Loránd Research Network, Budapest, Hungary and Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary"
    id: "ORCID:0000-0001-9941-9159"
  -
    firstname: "Richárd"
    lastname: "Fiáth"
    affiliation: "Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Eötvös Loránd Research Network, Budapest, Hungary and Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary"
    id: "ORCID:0000-0001-8732-2691"

# A title to describe the published resource.
title: "Dataset of cortical activity recorded with high spatial resolution from anesthetized rats"

# Additional information about the resource, e.g., a brief abstract.
description: |
  Publicly available neural recordings obtained with high spatial resolution are scarce. 
  Here, we present an electrophysiological dataset recorded from the neocortex of twenty rats 
  anesthetized with ketamine/xylazine. The wideband, spontaneous recordings were acquired with a 
  single-shank silicon-based probe having 128 densely packed recording sites arranged in a 32x4 
  array. Using spike sorting, the activity of a total of 7126 single units was extracted from all 
  layers of the cortex. Here, we share raw neural recordings, as well as spike times, extracellular 
  spike waveforms and several properties of units packaged in a standardized electrophysiological data
  format. For technical validation of our dataset, we provide the distributions of derived single unit
  properties along with various spike sorting quality metrics.  

# Lit of keywords the resource should be associated with.
# Give as many keywords as possible, to make the resource findable.
keywords:
  - Neuroscience
  - Silicon probe
  - High density recording
  - High spatial resolution
  - Electrophysiology
  - Neurophysiology
  - Neural recording
  - Extracellular action potential
  - Single unit activity
  - Spike sorting
  - Slow oscillation
  - Slow wave activity
  - Rat
  - Ketamine/xylazine anesthesia
  - Neocortex

# License information for this resource. Please provide the license name and/or a link to the license.
# Please add also a corresponding LICENSE file to the repository.
license:
  name: "CC-BY"
  url: "http://creativecommons.org/licenses/by/4.0/"



## Optional Fields

# Funding information for this resource.
# Separate funder name and grant number by comma.
funding:
  - "Hungarian Brain Research Program; 2017-1.2.1-NKP-2017-00002"
  - "Hungarian National Research, Development and Innovation Office; PD124175"
  - "Hungarian National Research, Development and Innovation Office; PD134196"
  - "Hungarian National Research, Development and Innovation Office; TUDFO/51757-1/2019-ITM"


# Related publications. reftype might be: IsSupplementTo, IsDescribedBy, IsReferencedBy.
# Please provide digital identifier (e.g., DOI) if possible.
# Add a prefix to the ID, separated by a colon, to indicate the source.
# Supported sources are: DOI, arXiv, PMID
# In the citation field, please provide the full reference, including title, authors, journal etc.
references:
  -
    id: "doi:10.xxx/zzzz"
    reftype: "IsSupplementTo"
    citation: "Citation1"
  -
    id: "arxiv:mmmm.nnnn"
    reftype: "IsSupplementTo"
    citation: "Citation2"
  -
    id: "pmid:nnnnnnnn"
    reftype: "IsReferencedBy"
    citation: "Citation3"


# Resource type. Default is Dataset, other possible values are Software, DataPaper, Image, Text.
resourcetype: Dataset

# Do not edit or remove the following line
templateversion: 1.2