Exercise 3 - Direction Selective Simple Cells - Population Model

Objectives: References:

Network population models like the one used here have considerably more complex descriptions than the filter models of the earlier exercises. You may need to consult some of the references above for a more complete understanding.

  1. Download the parameter files

    • DS_Simp.moo - Direction Selective Simple Cells.

    • sine_dir_c100.stm - stimulus parameters for a protocol that generates a direction tuning curve at 100% contrast.

    • t_all.rsp - spike responses from DS units.

    • t_cond.rsp - total excitatory and inhibitory conductances to the single DS unit ds_0_1.

  2. Examine the contents of the model parameter file

    Open the model file in a text editor. Note there are several populations:

    • LGN and LGN_D are two LGN populations that differ only in response latency (the temporal filter for LGN_D units is delayed by 20 ms relative to LGN).

    • IN and EX are inhibitory and excitatory V1 units respectively that take input from the LGN population. IN_D and EX_D are V1 units that take input from LGN_D.

    • DS units take input from all 4 IN and EX populations. The phase of the templates that select the inputs differs between each of the four populations, generating direction selective responses.

  3. Visualize the model with the GUI (graphical user interface).

    
  wm mod DS_Simp.moo sine_dir.stm t_all.rsp tn 512 sf 1.2 tf 10 gui_flag 1
    Two windows should appear. The window labeled current layer will be referred to as the main or first window. At the upper left of this window are a set of icons with a variety of colors and shapes. Each icon in this horizontal series represents a population of units defined in the model (.moo) file. You can change which population is displayed in the main window by clicking (left click) on the icons.

    You can also change which population is displayed in the second window by right clicking on the icons (in the main window).

    Once you arrange the windows to display the desired two populations, you can click on a unit in the main window to reveal its pre-synaptic connections from the population in the second window. If you right-click a unit, it will show projections (post-synaptic connections) to the second window.

    You can press h for help in the main window, and a list of commands will print out in the terminal window from which WM was launched.

    When the LGN population is shown in the second window, it is possible to visualize the stimulus by pressing 's' in the main window. (Pressing 's' again will turn off the visual stimulus.) At first, nothing will display, but this is because the stimulus is gray. You can advance through video frames of the stimulus movie by pressing the comma and period keys (, .) and you can advance through the set of stimuli (e.g., through directions) by using the < and > keys. Visusalizing the stimulus like this can help to be sure that there is in fact a stimulus being presented on top of the RFs of the neurons, and that the stimulus is configured in the way you expected from the stimulus (.stm) file.

  4. Run the model using the direction tuning stimulus.

    To look at the direction tuning of spike outputs from the 4 DS units, run: 

    
  wm mod DS_Simp.moo sine_dir.stm t_all.rsp tn 512 sf 1.2 tf 10 stim_nrpt 5 write_ndata ex3.simp.spikes.nd
    and to look at the excitatory and inhibitory conductances to a single DS unit run: 
    
  wm mod DS_Simp.moo sine_dir.stm t_all.rsp tn 512 sf 1.2 tf 10 stim_nrpt 5 write_ndata ex3.simp.cond.nd
    The outputs are written to the .nd files ex3.simp.spikes.nd and ex3.simp.cond.nd.

    Alternatively, if the simulations are too slow and you are running out of time, you can download precomputed .nd files here:

  5. View the response using the nData browser (nd)

    Open one of the data files, 

    
  nd ex3.simp.spikes.nd
    Select the Tuning Curve analysis and set the contrast to 1.0. Verify that all the responses are direction selective.

    Open the file containing the input conductance traces. Observe how excitatory and inhibitory conductances vary with direction. Note how the time course of the conductances changes as you change direction.

  6. Varying the phase of inputs to the DS cells

    This model was inspired by the experimental work of Priebe and Ferster (2005) Direction selectivity of excitation and inhibition in simple cells of the cat primary visual cortex. Neuron 45:133-145. They proposed that direction selectivity is generated by the precise temporal arrangement of excitatory and inhibitory input to DS simple cells.

    In the model this can be tested explicitly by varying the phase relationship between excitatory and inhibitory input to the DS cells, and/or the phase relationship between delayed (EX_D, IN_D) and non-delayed (EX, IN) inputs. This is determined in the model in the input objects to the DS units, and can be varied by changing the phase parameter. Open the model parameter file and scroll down until you find the following lines (in the DS population description): 

          ### Template params, ori taken from orimap
      template Gabor # Use this Gabor template, not 'self_lgn'
      sf       2.0   # (cyc/deg) Spatial frequency
      sd_orth  0.16  # (deg) Gaussian SD for Gabor RF, orthog to ori
      sd_par   0.28  # (deg) Gaussian SD for Gabor RF, parallel to ori
      phase    0     # (deg) phase
    This will appear 4 times in the .moo file, once for each input coming from the EX, EX_D, IN and IN_D populations. Note that for each of these inputs, the parameter differs. The delayed and non-delayed inputs are set to be 90 degrees apart, while the inhibitory and excitatory inputs are set to be 180 degrees apart.

    Try varying the phase difference between these inputs. What is the effect on direction tuning of spikes? How do the conductances to the DS units change? What conclusions can you draw about the importance of the phase relationships between excitation and inhibition and delayed vs. non-delayed input in generating direction selectivity in these simple cells?


    End of Exercise 3