<?xml version="1.0"?>
<edsp version="3.1" about_me="http://ycmi.med.yale.edu/EAVCR/EDSP" source="Olfactory Receptors Database">
  <source>
    <type>eav/cr</type>
    <name>Data Store:SenseLab</name>
    <location>itts023d.itts.ttu.edu</location>
    <date>4/10/2026 11:41:24 AM</date>
    <query_method>GET</query_method>
    <query_parameter>o=223029</query_parameter>
  </source>
  <metadata type="partial" time="0">
    <datatypes>
      <datatype id="B" name="Boolean" xml_datatype="xs:boolean" />
      <datatype id="C" name="Object/Ref" xml_datatype="xs:long" />
      <datatype id="D" name="Datetime" xml_datatype="xs:dateTime" />
      <datatype id="F" name="Formula(only)" xml_datatype="xs:anyType" />
      <datatype id="H" name="Hierarchy(p)" xml_datatype="xs:long" />
      <datatype id="I" name="Integer" xml_datatype="xs:long" />
      <datatype id="M" name="Memo" xml_datatype="xs:string" />
      <datatype id="R" name="Real" xml_datatype="xs:double" />
      <datatype id="S" name="String" xml_datatype="xs:string" />
      <datatype id="V" name="Object/Value" xml_datatype="xs:long" />
      <datatype id="W" name="Object/Ref(MC)" xml_datatype="xs:long" />
      <datatype id="Y" name="Binary" xml_datatype="xs:base64Binary" />
    </datatypes>
    <metadata_ontology>
      <sem_type_atts />
      <sem_rel_types />
      <sem_rel_att />
    </metadata_ontology>
    <database id="d2" name="modeldb" caption="ModelDB" caption_long="Model Database" description="ModelDB provides an accessible location for storing and efficiently retrieving compartmental neuron models. ModelDB is tightly coupled with NeuronDB. Models can be coded in any language for any environment, though ModelDB has been initially constructed for use with NEURON and GENESIS. Model code can be viewed before downloading and browsers can be set to auto-launch the models" main_class="19" version="3" version_date="4/12/2002 11:28:19 AM">
      <class id="c38" name="model_type" caption="Model Type" description="Physical extent of the model" object_description_hide="false" type="E" is_concept="false" host_concepts="true" uid="" version="3" version_date="6/20/2006 10:13:51 AM" />
    </database>
  </metadata>
  <data time="0">
    <data_database db_id="d2">
      <data_class class_id="c38" version="3">
        <object id="o223029" name="Predictive Coding Network" description="From Whittington and Bogacz 2017 &quot;The predictive coding framework describes a network architecture in which&#xD;&#xA;such learning has a particularly simple neural implementation. The distinguishing&#xD;&#xA;feature of the predictive coding models is that they include additional nodes encoding&#xD;&#xA;the difference between the activity on a given level and that predicted by the higher&#xD;&#xA;level, and that these prediction errors are propagated through the network (Rao and&#xD;&#xA;Ballard, 1999; Friston, 2005)...&quot;" uid="" version="2" version_date="2/21/2017 4:45:27 PM" />
      </data_class>
    </data_database>
  </data>
</edsp>

