Linear Filter - lin_01
----------------------

Overview
********

The ``lin_01`` model implements a 1-D linear filter followed by spike 
train generation.  It also may contain any number of units in a second
layer, defined by ``unit`` objects, that combine the spikes from
the linear unit with independently generated Poisson spikes.


Configuring the Model
*********************

``lin_01`` models are defined using the following objects and parameters:

.. parsed-literal::

   #
   # lin_01.moo
   #

   mod_type lin_01

   tscale    0.001	
   tn     1024		

   <filter_>
   ...
   </filter>

   <spike_\_gen>
   ...
   </spike_gen>

   <unit_>			# OPTIONAL
   ...
   </unit>


* ``tscale`` - temporal resolution (samples per second)

* ``tn`` - duration of the model (sampling units)

* |<filter>|_ object that specifies parameters for the temporal filter

* |<spike_gen>|_ object that defines the method of spike generation from the final filter output

* |<unit>|_ objects that specify parameters for 2nd layer units may optionally be included

.. |<filter>| replace:: ``<filter>``
.. _<filter>: ../o/filter.rst
.. _filter: ../o/filter.rst

.. |<spike_gen>| replace:: ``<spike_gen>``
.. _<spike_gen>: ../o/spike_gen.rst
.. _spike: ../o/spike_gen.rst

.. |<unit>| replace:: ``<unit>``
.. _<unit>: ../o/unit.rst
.. _unit: ../o/unit.rst


Model Outputs
*************

Model Components 
~~~~~~~~~~~~~~~~

The following command allows users to output the temporal 
filter itself:

* ``write_dog_temporal [outfile]`` - write the temporal filters.  
This includes the temporal kernel and the Gaussian mask, which multiplies 
the biphasic kernel to adjust the size of the positive and negative lobes.


Model Responses
~~~~~~~~~~~~~~~~

The following response types can be requested:

* ``spikes`` - spike times
* ``f`` - linear filter output
* ``prob`` - probability of spiking (if Poisson spike generation)


Models of This Type
*******************

* `LinearCommon <http://www.imodel.org/m/11/LinearCommon/>`_