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Calls have therefore been made to use multiple connectivity estimates to adequately capture periodic (e.g., seasonal) temporal changes.
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This finding also suggests that it will be possible to combine connectivity estimates from multiple recording techniques.
We found that the variation in connectivity estimates between seasons increased with temporal variability.
Indices derived from the coefficient estimates can also be used to relate effective connectivity estimates to behavioral or clinical measures.
Incorrect grain size had the largest overall effect on the accuracy of connectivity estimates.
Landscape connectivity estimates are widely used to inform species conservation management.
Correlations between these two functional connectivity estimates imply that functional connectivity calculated from filtered signals is predictive of functional connectivity at fast timescales.
We find that connectivity estimates are fairly robust to temporal filtering (Fig. 3).
Some previous evidence exists for an agreement between connectivity estimates across timescales.
See the supplemental material for extension to multiple connectivity matrices.
Connectivity estimates were used to populate a 296 × 296 weighted, directed, connectivity matrix.
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