dyconnmap.chronnectomics package¶
Submodules¶
dyconnmap.chronnectomics.dwell_time module¶
Dwell Time
Dwell time measures the time (when used in the context of functional connectivity microstates) a which a state is active consecutive temporal segments (Dimitriadis2019_).
- Dimitriadis2019
Dimitriadis, S. I., López, M. E., Maestu, F., & Pereda, E. (2019). Modeling the Switching behavior of Functional Connectivity Microstates (FCμstates) as a Novel Biomarker for Mild Cognitive Impairment. Frontiers in Neuroscience, 13.
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dyconnmap.chronnectomics.dwell_time.dwell_time(x)[source]¶ Dwell Time
Compute the dwell time for the given symbolic, 1d time series.
- Parameters
x (array-like, shape(N)) – Input symbolic time series.
- Returns
dwell (dictionary) – KVP, where K=symbol id and V=array of dwell time.
mean (dictionary) – KVP, where K=symbol id and V=mean dwell time.
std (dictionary) – KVP, where K=symbol id and V=std dwell time.
dyconnmap.chronnectomics.flexibility_index module¶
Flexibility Index
In the context of graph clustering it was defined in (Basset2011), flexbility is the frequency of a nodea change module allegiance; the transition of brain states between consecutive temporal segments. The higher the number of changes, the larger the FI will be.
- Basset2011
Bassett, D. S., Wymbs, N. F., Porter, M. A., Mucha, P. J., Carlson, J. M., & Grafton, S. T. (2011). Dynamic reconfiguration of human brain networks during learning. Proceedings of the National Academy of Sciences, 108(18), 7641-7646.
dyconnmap.chronnectomics.occupancy_time module¶
Occupancy Time
The fraction of number of distinct symbols occuring in the symbolic time series (Dimitriadis2019_).
- Dimitriadis2019
Dimitriadis, S. I., López, M. E., Maestu, F., & Pereda, E. (2019). Modeling the Switching behavior of Functional Connectivity Microstates (FCμstates) as a Novel Biomarker for Mild Cognitive Impairment. Frontiers in Neuroscience, 13.
Module contents¶
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dyconnmap.chronnectomics.dwell_time(x)[source]¶ Dwell Time
Compute the dwell time for the given symbolic, 1d time series.
- Parameters
x (array-like, shape(N)) – Input symbolic time series.
- Returns
dwell (dictionary) – KVP, where K=symbol id and V=array of dwell time.
mean (dictionary) – KVP, where K=symbol id and V=mean dwell time.
std (dictionary) – KVP, where K=symbol id and V=std dwell time.