analysis:course-w16:week11
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analysis:course-w16:week11 [2016/02/23 11:33] mvdm [Phase-slope index] |
analysis:course-w16:week11 [2018/07/07 10:19] (current) |
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| ~~DISCUSSION~~ | ~~DISCUSSION~~ | ||
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| - | :!: **Under construction, please do not use yet!** :!: | ||
| ===== Interactions between multiple signals: coherence, Granger causality, and phase-slope index ===== | ===== Interactions between multiple signals: coherence, Granger causality, and phase-slope index ===== | ||
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| * (background reading, a brief review) [[http://www.ncbi.nlm.nih.gov/pubmed/16150631 | Fries (2005) ]] Communication through coherence paper | * (background reading, a brief review) [[http://www.ncbi.nlm.nih.gov/pubmed/16150631 | Fries (2005) ]] Communication through coherence paper | ||
| * (optional, a nice example application) [[http://www.ncbi.nlm.nih.gov/pubmed/17372196 | deCoteau et al. (2007)]] hippocampus-striatum coherence changes with learning | * (optional, a nice example application) [[http://www.ncbi.nlm.nih.gov/pubmed/17372196 | deCoteau et al. (2007)]] hippocampus-striatum coherence changes with learning | ||
| + | * (technical background) [[http://arxiv.org/pdf/q-bio/0608035v1.pdf | Ding et al. (2006)]] theory of Granger causality and applications to neuroscience | ||
| ==== Introduction ==== | ==== Introduction ==== | ||
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| === Spectrally resolved Granger causality === | === Spectrally resolved Granger causality === | ||
| - | Given how ubiquitous oscillations are in neural data, it is often informative to not fit VAR models directly in the time domain (as we did in the previous section) but go to the frequency domain. Intuitively, //spectrally resolved// Granger causality measures how much of the power in $X$, not accounted for by $X$ itself, can be attributed to $Y$. To explore this, we'll generate some more artificial data: | + | Given how ubiquitous oscillations are in neural data, it is often informative to not fit VAR models directly in the time domain (as we did in the previous section) but go to the frequency domain. Intuitively, //spectrally resolved// Granger causality measures how much of the power in $X$, not accounted for by $X$ itself, can be attributed to $Y$ ([[http://www.sciencedirect.com/science/article/pii/S1053811908001328 | technical paper]]). To explore this, we'll generate some more artificial data: |
| <code matlab> | <code matlab> | ||
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| ☛ Reverse the two signals and compute Granger cross-spectra, both for the zero-delay artifact case and for the true causal case above. Verify that this reverse-Granger test accurately distinguishes the two cases. [[http://www.sciencedirect.com/science/article/pii/S105381191401009X | This paper]] discusses these issues in more detail and has thoughtful discussion. | ☛ Reverse the two signals and compute Granger cross-spectra, both for the zero-delay artifact case and for the true causal case above. Verify that this reverse-Granger test accurately distinguishes the two cases. [[http://www.sciencedirect.com/science/article/pii/S105381191401009X | This paper]] discusses these issues in more detail and has thoughtful discussion. | ||
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| ==== Phase-slope index ==== | ==== Phase-slope index ==== | ||
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| ==== Challenges ==== | ==== Challenges ==== | ||
| - | ★ If you have your own data with at least two signals that you suspect may be related, identify an appropriate functional connectivity analysis and apply it to the data. | + | ★ If you have your own data with at least two signals that you suspect may be related, identify an appropriate functional connectivity analysis and apply it to the data. Comment on why the chosen method was used. |
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| + | ★ The "theta" rhythm, which is about 8 Hz in moving rodents, is important in coordinating the spike timing of hippocampal neurons. However, theta frequencies also appear in LFPs recorded from other brain areas, including the prefrontal cortex and the ventral striatum. One hypothesis is that those areas simply "inherit" theta activity from their hippocampal inputs. Test this idea using data from R020, which has electrodes in hippocampus and ventral striatum, and your chosen connectivity analysis method. | ||
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analysis/course-w16/week11.1456245197.txt.gz · Last modified: 2018/07/07 10:19 (external edit)
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