Fix grammar

Author: tsbinns

paper/paper.md

@@ -71,7 +71,7 @@ Non-sinusoidal signal characteristics can indicate particular properties of inte
 
 Two common issues faced in the analysis of electrophysiology data are dealing with a limited signal-to-noise ratio, and obtaining interpretable results from high-dimensional data [@Cohen2022]. Spatio-spectral decomposition is a multivariate technique that addresses these problems, using linear filters to capture the key aspects of frequency band-specific information in a high signal-to-noise ratio, low-dimensional space [@Nikulin2011]. This decomposition can be applied for the multivariate analysis of non-sinusoidal waveshape properties, with extensions like harmonic power maximisation available to more specifically target non-sinusoidal information [@Bartz2019]. `PyBispectra` provides tools for using spatio-spectral filtering to enhance the signal-to-noise ratio and reduce the dimensionality of electrophysiology data.
 
-Other practical features of `PyBispectra` includes dedicated plotting tools for the visualisation of results from phase-amplitude coupling, time delay, and non-sinusoidal waveshape analyses to aid interpretability. Furthermore, other cross-frequency tools for amplitude-amplitude coupling and phase-phase coupling are also provided, recommended for use in identifying genuine phase-amplitude coupling [@Giehl2021]. Finally, the various forms of analysis are accompanied by detailed tutorials, helping to facilitate an understanding of how these tools can be used to analyse electrophysiology data.
+Other practical features of `PyBispectra` include dedicated plotting tools for the visualisation of results from phase-amplitude coupling, time delay, and non-sinusoidal waveshape analyses to aid interpretability. Furthermore, other cross-frequency tools for amplitude-amplitude coupling and phase-phase coupling are also provided, recommended for use in identifying genuine phase-amplitude coupling [@Giehl2021]. Finally, the various forms of analysis are accompanied by detailed tutorials, helping to facilitate an understanding of how these tools can be used to analyse electrophysiology data.
 
 # Conclusion