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analysis:course-w16:week16 [2016/02/29 13:59]
mvdm [Steps 5-7: Get co-activation probabilities]
analysis:course-w16:week16 [2016/02/29 14:13]
mvdm
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 ~~DISCUSSION~~ ~~DISCUSSION~~
- 
-:!: **UNDER CONSTRUCTION,​ PLEASE DO NOT USE YET** :!: 
  
 ===== Pairwise co-occurrence ===== ===== Pairwise co-occurrence =====
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 </​code>​ </​code>​
  
 +This shuffling procedure is an example of **resampling**:​ we create a number of different data sets based on some rearrangement of the original data. In this case, the specific resampling is a shuffle or permutation,​ which breaks any relationship between neurons (because we shuffle each neuron independently) and therefore functions as a control for the amount of co-occurrence we expect by chance (i.e. if the neurons were independently active). In general, a major advantage of resampling methods is that they preserve aspects of the underlying distribution -- in this case, of spike counts -- and make no particular assumptions about its shape, whereas many parametric statistical tests require data to be e.g. normally distributed.
  
 ==== Challenges ==== ==== Challenges ====
  
 ★ Why don't we just look at single-cell activation? Under what conditions would the results from that be the same, or different, from pairwise co-occurrence?​ ★ Why don't we just look at single-cell activation? Under what conditions would the results from that be the same, or different, from pairwise co-occurrence?​
 +
 +★ Comment on the choice of bins used in constructing the Q-matrix. It it reasonable to assume that SWR events are always 100ms in length? Modify the code to use the actual length of SWR events. Is the resampling statistic still doing the right thing in this case?
 +
 +★ Implement co-occurrence analysis on your own data.
  
 ==== Credits ==== ==== Credits ====
  
 This module was developed by [[https://​github.com/​aacarey | Alyssa Carey]]. This module was developed by [[https://​github.com/​aacarey | Alyssa Carey]].
analysis/course-w16/week16.txt · Last modified: 2018/07/07 10:19 (external edit)