Identifying neurons in pvc-2 data

Hi,

A paper (Y Dan 2005) that goes with the pvc-2 data mentions there are 36 complex and 14 simple neurons.  How do we distinguish the neurons in the .log files?  By 'distinguish' I mean not only simple/complex but other characteristics as well, like perhaps recording location, depth, etc.

Thanks!

Mark,

Unfortunately you can't distinguish between simple and complex in the log file. One of the papers associated with this data (Touryan, 2005) uses the below criterion. However, the CRCNS data does not include the drifting gratings component. Since the distinction is somewhat arbitrary, there are other was to distinguish simple from complex cells (including number of significant eigenvectors in spike-triggered covariance matrix). The log file only contains information about the stimulus configuration. 

"Cells were classified as simple if their RFs had clear ON and OFF subregions (Hubel and Wiesel, 1962) and if the ratio of the first harmonic to the DC component of the response to an optimally oriented drifting grating was >1 (Skottun et al., 1991). All cells included in this study were complex cells." (Touryan, 2005)

- Jon Touryan

Previously Mark Rogers wrote:

Hi,

 

A paper (Y Dan 2005) that goes with the pvc-2 data mentions there are 36 complex and 14 simple neurons.  How do we distinguish the neurons in the .log files?  By 'distinguish' I mean not only simple/complex but other characteristics as well, like perhaps recording location, depth, etc.

 

Thanks!