Joss review fixes

README.md

@@ -155,8 +155,6 @@ If you use PyGPLA in your research, please cite the original GPLA method paper:
 }
 ```
 
-A dedicated software citation (JOSS) will be added here once the paper is published.
-
 ## License
 
 BSD 2-Clause License. See `LICENSE`.

paper/paper.md

@@ -80,10 +80,14 @@ The `pygpla` package is distributed under the BSD-2-Clause license. PyGPLA follo
 
 ## Use of generative AI
 
-Generative AI tools were used only to assist with drafting documentation and refactoring code for style. All AI-assisted output was reviewed, tested, and validated by the authors, who take full responsibility for the correctness of the software and the content of this paper. The scientific method, algorithmic design, and numerical implementation of GPLA were carried out by the authors.
+Generative AI tools were used only to assist with drafting documentation and
+refactoring code for style. All AI-assisted output was reviewed, tested, and
+validated by the authors, who take full responsibility for the correctness of the
+software and the content of this paper. The scientific method, algorithmic design,
+and numerical implementation of GPLA were carried out by the authors.
 
 ## Acknowledgments
 
-We acknowledge contributions from collaborators who provided feedback during the development of PyGPLA. Shervin Safavi acknowledges the support from the Max Planck Society and an add-on fellowship from the Joachim Herz Foundation.
+We acknowledge contributions from collaborators who provided feedback during the development of pyGPLA. S.S. acknowledges support from the Max Planck Society and an add-on fellowship from the Joachim Herz Foundation. C.B. acknowledges support from the Federal Ministry of Research, Technology and Space (Bundesministerium für Forschung, Technologie und Raumfahrt; BMFTR) as part of the German Center for Child and Adolescent Health (DZKJ) under funding code 01GL2405B.
 
 ## References

src/pygpla/__init__.py

@@ -1,9 +1,35 @@
 """
 PyGPLA: Generalized Phase Locking Analysis tools for Python.
 
-The package is under active development; upcoming releases will expose high-level
-analysis helpers via ``pygpla.gpla`` alongside lower-level preprocessing and
-statistics modules. See the project notes in ``notes/`` for the migration plan.
+GPLA summarizes multichannel spike-LFP coupling by building a complex coupling
+matrix and extracting its dominant low-rank structure via SVD, yielding a scalar
+coupling strength (gPLV) together with an LFP vector and a spike vector.
+
+The main entry point is :func:`pygpla.api.gpla`::
+
+    from pygpla.api import gpla
+
+    result = gpla(spikes, lfp_analytic, stats_config={"testType": "RMT-based"})
+    result.gplv, result.lfp_vector, result.spike_vector
+
+Modules
+-------
+api
+    High-level :func:`~pygpla.api.gpla` entry point and its
+    :class:`~pygpla.api.GPLAResult` container.
+core
+    Coupling-matrix construction, SVD factorization, and PCA whitening.
+preprocessing
+    Trial concatenation, spike-count filtering, and related data preparation.
+simulations
+    Phase-locked, transient-coupling, and Poisson spike-train generators.
+stats
+    RMT-based and spike-jitter surrogate significance testing.
+config
+    Dataclasses describing whitening, preprocessing, and statistical-test options.
+
+The method is described in Safavi et al. (2023), *Uncovering the organization of
+neural circuits with Generalized Phase Locking Analysis*, PLOS Computational Biology.
 """
 
 from ._version import __version__