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Investigating spectral state transitions in anesthetized rodent LFP.

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spec-state-trans: Spectral state transitions project

Dependencies:

Current analysis pipeline

See mt_new_2020_recs.m followed by full_analysis_byday.m for an example.

  1. Compute CSDs for each region on each recording day using plot_csd.m

    • Output: <date>/csd_<region>.mat
  2. Use CSDs to assign channel numbers to layers in the CSD matfiles using pick_channels_from_csd.m

    • Output: <date>/csd_<region>.mat
  3. Find burst suppression using find_likely_bs.mat and mark any other artifacts manually in the artifacts option to multitaper_analysis

  4. Do multitaper analyses of each recording's selected channels, with artifact filtering etc. using multitaper_analysis.m

    • Output: <date>/<time>/mt_res_layers.mat
  5. Do NMF and extract classes and transitions for each channel (based on dominant component per time) using concat_and_nmf.m

    • Output: <date>/nmf_res.mat
  6. Generate "null model" score data for each channel (shuffled using Markov chain - negative control for connectivity) using gen_null_model_data.m

    • Output: <date>/nmf_res.mat
  7. Compute Euclidean distance between aligned NMF scores of each directed pair of channels (and plot results) with score_dist_analysis.m

    • Output: <date>/nmf_res.mat
  8. Get normalized mutual information between discrete classes of each channel using class_mut_info.m from Ethan_misc (see full_analysis_byday.m)

  9. Compute a measure of synchrony for each transition and compare to bootstrap with transitions shuffled using get_state_transitions.m and calc_transition_synchrony.m

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Investigating spectral state transitions in anesthetized rodent LFP.

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