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@@ -91,7 +91,7 @@ PyGPLA uses a function-oriented, layered design that separates the main stages o
 
 PyGPLA accepts standard NumPy arrays rather than requiring a package-specific data container, facilitating integration with existing electrophysiology workflows. Frequency selection and conversion of raw LFP voltage to an analytic signal are intentionally left upstream because these operations require experiment-specific filtering choices. PyGPLA therefore operates on a frequency-specific complex analytic signal or phase representation and warns when real-valued input is supplied.
 
-Several numerical and interface conventions preserve continuity with the original MATLAB implementation, facilitating validation against the reference implementation and migration of existing GPLA analyses. These include its normalization alternatives, phase convention, reduced-rank whitening methods, and selected legacy parameter names. Optional PCA-based whitening reduces correlations among LFP channels, while an unwhitening operator maps the resulting coupling modes back to the original channel coordinates. Statistical inference is separated from the deterministic decomposition, allowing users to choose between a computationally inexpensive analytical RMT-based decision and more expensive spike-jitter surrogate tests. The core package depends only on NumPy; SciPy is provided as an optional dependency for documented simulation and signal-processing workflows.
+Several numerical and interface conventions preserve continuity with the original MATLAB implementation, facilitating validation against the reference implementation and migration of existing GPLA analyses. These include its normalization alternatives, phase convention, reduced-rank whitening methods, and selected legacy parameter names. Optional PCA-based whitening reduces correlations among LFP channels, while an unwhitening operator maps the resulting coupling modes back to the original channel coordinates. Statistical inference is separated from the deterministic decomposition, allowing users to choose between a computationally inexpensive analytical RMT-based decision and more expensive spike-jitter surrogate tests. The core package depends only on NumPy. SciPy is available through the optional sim extra for documented signal-processing workflows, including band-pass filtering and Hilbert-transform construction of analytic LFP signals.
 
 ## Research impact statement