{
  "id": 7613,
  "title": "Synaptic Models used in simulations",
  "url": "/competitions/connectomics/discussion/7613",
  "author_name": "",
  "post_date": "2014-04-04T14:01:29.850Z",
  "votes": null,
  "comment_count": 3,
  "views": 940,
  "content": "<p>From previous forum posts I understand that the neuron model used to generate the data is a leaky integrate and fire model, and that the synapses don't change over time.&nbsp;Can you also explain what is the synaptic model used to generate the data?<br><br>to further clarify the question: what is the relationship between a pre-synaptic action potential and a post-synaptic input current/voltage to the post synaptic cell? (according to the simulator)<br><br>Also, can you comment of whether all simulated neurons have the same membrane Capacitance and Resistance or there exists some variation between neurons in that regard? Also, same question about the synapses. do&nbsp;all synapses have same parameters or there are variations there too (i.e. stronger and weaker synapses)?<br><br>Thanks a lot in advance, any comment will be much appreciated.</p>",
  "messages": [
    {
      "id": "41484",
      "postDate": "04/04/2014 14:01:29",
      "content": "<p>From previous forum posts I understand that the neuron model used to generate the data is a leaky integrate and fire model, and that the synapses don't change over time.&nbsp;Can you also explain what is the synaptic model used to generate the data?<br><br>to further clarify the question: what is the relationship between a pre-synaptic action potential and a post-synaptic input current/voltage to the post synaptic cell? (according to the simulator)<br><br>Also, can you comment of whether all simulated neurons have the same membrane Capacitance and Resistance or there exists some variation between neurons in that regard? Also, same question about the synapses. do&nbsp;all synapses have same parameters or there are variations there too (i.e. stronger and weaker synapses)?<br><br>Thanks a lot in advance, any comment will be much appreciated.</p>",
      "rawMarkdown": "",
      "votes": null
    },
    {
      "id": "41620",
      "postDate": "04/09/2014 13:18:17",
      "content": "<p>Hi,</p>\n<p>The synapses are short-term depressing.</p>\n<p>All neurons&nbsp;have the same parameters, but not all synapses might have the same strength. However I don't think there are big differences between them.</p>\n<p>You can find estimates of the parameters, models and equations&nbsp;used in&nbsp;Methods section of the following paper:</p>\n<p>http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002653</p>\n<p>Basically, everything you might want to know about the challenge design is there. However, there are some new additions and differences, otherwise it would be quite easy to reverse-engineer the data.</p>",
      "rawMarkdown": "",
      "votes": null
    },
    {
      "id": "41622",
      "postDate": "04/09/2014 15:52:06",
      "content": "<p>Will&nbsp;'leaky integrate and fire model' neurons fire spontaneously?&nbsp;</p>",
      "rawMarkdown": "",
      "votes": null
    },
    {
      "id": "41703",
      "postDate": "04/11/2014 10:24:56",
      "content": "<p>There's a noise source in each neuron (with poisson statistics) that allows the neurons to fire spontaneously. Without it, the neurons would not fire.</p>",
      "rawMarkdown": "",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 41620,
      "author_name": "orlandi",
      "author_url": "",
      "post_date": "04/09/2014 13:18:17",
      "content": "<p>Hi,</p>\n<p>The synapses are short-term depressing.</p>\n<p>All neurons&nbsp;have the same parameters, but not all synapses might have the same strength. However I don't think there are big differences between them.</p>\n<p>You can find estimates of the parameters, models and equations&nbsp;used in&nbsp;Methods section of the following paper:</p>\n<p>http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002653</p>\n<p>Basically, everything you might want to know about the challenge design is there. However, there are some new additions and differences, otherwise it would be quite easy to reverse-engineer the data.</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 41622,
      "author_name": "idaniboy",
      "author_url": "",
      "post_date": "04/09/2014 15:52:06",
      "content": "<p>Will&nbsp;'leaky integrate and fire model' neurons fire spontaneously?&nbsp;</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 41703,
      "author_name": "orlandi",
      "author_url": "",
      "post_date": "04/11/2014 10:24:56",
      "content": "<p>There's a noise source in each neuron (with poisson statistics) that allows the neurons to fire spontaneously. Without it, the neurons would not fire.</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "41484": "",
    "41620": "",
    "41622": "",
    "41703": ""
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  "source": "meta"
}