====== Differences ====== This shows you the differences between two versions of the page.
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analysis:nsb2016:week10 [2016/07/04 22:42] mvdm created |
analysis:nsb2016:week10 [2018/04/17 15:20] (current) |
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<code matlab> | <code matlab> | ||
LoadMetadata; | LoadMetadata; | ||
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+ | % ENCoding variable names, for data used to estimate tuning curves, which capture | ||
+ | % the relationship between some variable and firing rate (here: "How is position | ||
+ | % (en)coded by the neurons we are recording?"), as opposed to DECoding variable names, | ||
+ | % which are used for data we want to decode (e.g. replay). | ||
ENC_S = restrict(S,metadata.taskvars.trial_iv); | ENC_S = restrict(S,metadata.taskvars.trial_iv); | ||
ENC_pos = restrict(pos,metadata.taskvars.trial_iv); | ENC_pos = restrict(pos,metadata.taskvars.trial_iv); | ||
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The data in this module computes tuning curves for location, but the idea is of course more general. For continuous variables in particular, it is a natural and powerful way to describe the relationship between two quantities -- spikes and location in this case, but there is no reason why you couldn't do something like pupil diameter as a function of arm reaching direction, for instance! | The data in this module computes tuning curves for location, but the idea is of course more general. For continuous variables in particular, it is a natural and powerful way to describe the relationship between two quantities -- spikes and location in this case, but there is no reason why you couldn't do something like pupil diameter as a function of arm reaching direction, for instance! | ||
+ | |||
+ | ☛ Try plotting some place fields for your own data. You might want to restrict the data to those times when the rat is moving around; see [[http://ctnsrv.uwaterloo.ca/vandermeerlab/doku.php?id=analysis:nsb2016:week16&s[]=getlinspd#step_2estimating_place_fields | here]] for an example of how to do this. | ||
==== Bayesian decoding ==== | ==== Bayesian decoding ==== | ||