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Structurally restricted message-passing within shallow architectures for explainable network-level brain decoding on small cohorts

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Paper

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The authors' code

Python · 455 lines · 13 KB · MIT

  1. #!/usr/bin/env python3
  2. #
  3. # SHAP documentation build configuration file, created by
  4. # sphinx-quickstart on Tue May 22 10:44:55 2018.
  5. #
  6. # This file is execfile()d with the current directory set to its
  7. # containing dir.
  8. #
  9. # Note that not all possible configuration values are present in this
  10. # autogenerated file.
  11. #
  12. # All configuration values have a default; values that are commented out
  13. # serve to show the default.
  14. # If extensions (or modules to document with autodoc) are in another directory,
  15. # add these directories to sys.path here. If the directory is relative to the
  16. # documentation root, use os.path.abspath to make it absolute, like shown here.
  17. #
  18. import os
  19. import shutil
  20. import sys
  21. import requests
  22. print(os.path.abspath("./shap"))
  23. sys.path.insert(0, os.path.abspath(".."))
  24. # make copy of notebooks in docs folder, as they must be here for sphinx to
  25. # pick them up properly.
  26. NOTEBOOKS_DIR = os.path.abspath("example_notebooks")
  27. if os.path.exists(NOTEBOOKS_DIR):
  28. import warnings
  29. warnings.warn("example_notebooks directory exists, replacing...")
  30. shutil.rmtree(NOTEBOOKS_DIR)
  31. shutil.copytree(os.path.abspath("../notebooks"), NOTEBOOKS_DIR)
  32. if os.path.exists(NOTEBOOKS_DIR + "/local_scratch"):
  33. shutil.rmtree(NOTEBOOKS_DIR + "/local_scratch")
  34. # -- General configuration ------------------------------------------------
  35. # If your documentation needs a minimal Sphinx version, state it here.
  36. #
  37. # needs_sphinx = '1.0'
  38. # Add any Sphinx extension module names here, as strings. They can be
  39. # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
  40. # ones.
  41. extensions = [
  42. "sphinx.ext.autodoc",
  43. "sphinx.ext.autosectionlabel",
  44. "sphinx.ext.autosummary",
  45. "sphinx.ext.intersphinx",
  46. "sphinx_rtd_theme",
  47. "numpydoc",
  48. "nbsphinx", # Allows parsing Jupyter notebooks
  49. "myst_parser", # Allows parsing Markdown, such as CONTRIBUTING.md
  50. "sphinx_github_changelog",
  51. ]
  52. # --- Extension options
  53. # [autodoc]
  54. autodoc_default_options = {"members": True, "inherited-members": True}
  55. # [autosectionlabel]
  56. # Make sure the autogenerated targets are unique
  57. autosectionlabel_prefix_document = True
  58. # [autosummary]
  59. autosummary_generate = True
  60. # [intersphinx]
  61. intersphinx_mapping = {
  62. # "stdlib": ("https://docs.python.org/3", None),
  63. "mpl": (
  64. "https://matplotlib.org/stable/",
  65. "https://matplotlib.org/stable/objects.inv",
  66. ),
  67. "scikit-learn": (
  68. "https://scikit-learn.org/stable/",
  69. "https://scikit-learn.org/stable/objects.inv",
  70. ),
  71. "scipy": ("https://docs.scipy.org/doc/scipy", None),
  72. }
  73. # Sphinx defaults to automatically resolve *unresolved* labels using all your Intersphinx mappings.
  74. # This behavior has unintended side-effects, namely that documentations local references can
  75. # suddenly resolve to an external location.
  76. # See also:
  77. # https://www.sphinx-doc.org/en/master/usage/extensions/intersphinx.html#confval-intersphinx_disabled_reftypes
  78. intersphinx_disabled_reftypes = ["*"]
  79. # [numpydoc]
  80. numpydoc_show_class_members = False
  81. # ---
  82. # Do not create toctree entries for each class/function
  83. toc_object_entries = False
  84. # Add any paths that contain templates here, relative to this directory.
  85. templates_path = ["_templates"]
  86. # The suffix(es) of source filenames.
  87. # You can specify multiple suffix as a list of string:
  88. #
  89. # source_suffix = ['.rst', '.md']
  90. source_suffix = ".rst"
  91. # The encoding of source files.
  92. #
  93. # source_encoding = 'utf-8-sig'
  94. # The master toctree document.
  95. master_doc = "index"
  96. # General information about the project.
  97. project = "SHAP"
  98. copyright = "2018, Scott Lundberg"
  99. author = "Scott Lundberg"
  100. # The version info for the project you're documenting, acts as replacement for
  101. # |version| and |release|, also used in various other places throughout the
  102. # built documents.
  103. #
  104. # The short X.Y version.
  105. version = "latest"
  106. # The full version, including alpha/beta/rc tags.
  107. release = "latest"
  108. # The language for content autogenerated by Sphinx. Refer to documentation
  109. # for a list of supported languages.
  110. #
  111. # This is also used if you do content translation via gettext catalogs.
  112. # Usually you set "language" from the command line for these cases.
  113. language = "en"
  114. # There are two options for replacing |today|: either, you set today to some
  115. # non-false value, then it is used:
  116. #
  117. # today = ''
  118. #
  119. # Else, today_fmt is used as the format for a strftime call.
  120. #
  121. # today_fmt = '%B %d, %Y'
  122. # List of patterns, relative to source directory, that match files and
  123. # directories to ignore when looking for source files.
  124. # This patterns also effect to html_static_path and html_extra_path
  125. exclude_patterns = [
  126. "_build",
  127. "Thumbs.db",
  128. ".DS_Store",
  129. "example_notebooks/tabular_examples/tree_based_models/tree_shap_paper",
  130. "user_studies",
  131. "local",
  132. ]
  133. # The reST default role (used for this markup: `text`) to use for all
  134. # documents.
  135. #
  136. # default_role = None
  137. # If true, '()' will be appended to :func: etc. cross-reference text.
  138. #
  139. # add_function_parentheses = True
  140. # If true, the current module name will be prepended to all description
  141. # unit titles (such as .. function::).
  142. #
  143. # add_module_names = True
  144. # If true, sectionauthor and moduleauthor directives will be shown in the
  145. # output. They are ignored by default.
  146. #
  147. # show_authors = False
  148. # The name of the Pygments (syntax highlighting) style to use.
  149. pygments_style = "sphinx"
  150. # A list of ignored prefixes for module index sorting.
  151. # modindex_common_prefix = []
  152. # If true, keep warnings as "system message" paragraphs in the built documents.
  153. # keep_warnings = False
  154. # If true, `todo` and `todoList` produce output, else they produce nothing.
  155. todo_include_todos = False
  156. # -- Release notes configuration ------------------------------------------
  157. # Make available a URL that points to the latest unreleased changes
  158. def get_latest_tag() -> str:
  159. """Query GitHub API to get the most recent git tag"""
  160. url = "https://api.github.com/repos/shap/shap/releases/latest"
  161. response = requests.get(url)
  162. response.raise_for_status()
  163. return response.json()["tag_name"]
  164. _latest_tag = get_latest_tag()
  165. _url = f"https://github.com/shap/shap/compare/{_latest_tag}...main"
  166. # Make an RST substitution that inserts the correct hyperlink
  167. rst_epilog = f"""
  168. .. |unreleasedchanges| replace:: {_latest_tag}...main
  169. .. _unreleasedchanges: {_url}
  170. """
  171. # -- Options for HTML output ----------------------------------------------
  172. # The theme to use for HTML and HTML Help pages. See the documentation for
  173. # a list of builtin themes.
  174. #
  175. # html_theme = 'alabaster'
  176. html_theme = "sphinx_rtd_theme"
  177. # Theme options are theme-specific and customize the look and feel of a theme
  178. # further. For a list of options available for each theme, see the
  179. # documentation.
  180. #
  181. html_theme_options = {
  182. #'canonical_url': '',
  183. "logo_only": True,
  184. "display_version": True,
  185. "prev_next_buttons_location": "bottom",
  186. "style_external_links": False,
  187. "style_nav_header_background": "#343131",
  188. # Toc options
  189. "collapse_navigation": True,
  190. "sticky_navigation": True,
  191. "navigation_depth": 4,
  192. "includehidden": True,
  193. "titles_only": False,
  194. }
  195. # The name of an image file (relative to this directory) to place at the top
  196. # of the sidebar.
  197. html_logo = "artwork/shap_logo_white.png"
  198. # Add any paths that contain custom themes here, relative to this directory.
  199. # html_theme_path = []
  200. # The name for this set of Sphinx documents.
  201. # "<project> v<release> documentation" by default.
  202. #
  203. # html_title = 'SHAP v0.16'
  204. # A shorter title for the navigation bar. Default is the same as html_title.
  205. #
  206. # html_short_title = None
  207. # The name of an image file (relative to this directory) to use as a favicon of
  208. # the docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32
  209. # pixels large.
  210. #
  211. html_favicon = "artwork/favicon.ico"
  212. # Add any paths that contain custom static files (such as style sheets) here,
  213. # relative to this directory. They are copied after the builtin static files,
  214. # so a file named "default.css" will overwrite the builtin "default.css".
  215. html_static_path = ["_static"]
  216. # Add any extra paths that contain custom files (such as robots.txt or
  217. # .htaccess) here, relative to this directory. These files are copied
  218. # directly to the root of the documentation.
  219. #
  220. # html_extra_path = []
  221. # If not None, a 'Last updated on:' timestamp is inserted at every page
  222. # bottom, using the given strftime format.
  223. # The empty string is equivalent to '%b %d, %Y'.
  224. #
  225. # html_last_updated_fmt = None
  226. # If true, SmartyPants will be used to convert quotes and dashes to
  227. # typographically correct entities.
  228. #
  229. # html_use_smartypants = True
  230. # Custom sidebar templates, maps document names to template names.
  231. #
  232. # html_sidebars = {}
  233. # Additional templates that should be rendered to pages, maps page names to
  234. # template names.
  235. #
  236. # html_additional_pages = {}
  237. # If false, no module index is generated.
  238. #
  239. # html_domain_indices = True
  240. # If false, no index is generated.
  241. #
  242. # html_use_index = True
  243. # If true, the index is split into individual pages for each letter.
  244. #
  245. # html_split_index = False
  246. # If true, links to the reST sources are added to the pages.
  247. #
  248. # html_show_sourcelink = True
  249. # If true, "Created using Sphinx" is shown in the HTML footer. Default is True.
  250. #
  251. # html_show_sphinx = True
  252. # If true, "(C) Copyright ..." is shown in the HTML footer. Default is True.
  253. #
  254. # html_show_copyright = True
  255. # If true, an OpenSearch description file will be output, and all pages will
  256. # contain a <link> tag referring to it. The value of this option must be the
  257. # base URL from which the finished HTML is served.
  258. #
  259. # html_use_opensearch = ''
  260. # This is the file name suffix for HTML files (e.g. ".xhtml").
  261. # html_file_suffix = None
  262. # Language to be used for generating the HTML full-text search index.
  263. # Sphinx supports the following languages:
  264. # 'da', 'de', 'en', 'es', 'fi', 'fr', 'h', 'it', 'ja'
  265. # 'nl', 'no', 'pt', 'ro', 'r', 'sv', 'tr', 'zh'
  266. #
  267. # html_search_language = 'en'
  268. # A dictionary with options for the search language support, empty by default.
  269. # 'ja' uses this config value.
  270. # 'zh' user can custom change `jieba` dictionary path.
  271. #
  272. # html_search_options = {'type': 'default'}
  273. # The name of a javascript file (relative to the configuration directory) that
  274. # implements a search results scorer. If empty, the default will be used.
  275. #
  276. # html_search_scorer = 'scorer.js'
  277. # Output file base name for HTML help builder.
  278. htmlhelp_basename = "SHAPdoc"
  279. # -- Options for LaTeX output ---------------------------------------------
  280. latex_elements = {
  281. # The paper size ('letterpaper' or 'a4paper').
  282. #
  283. # 'papersize': 'letterpaper',
  284. # The font size ('10pt', '11pt' or '12pt').
  285. #
  286. # 'pointsize': '10pt',
  287. # Additional stuff for the LaTeX preamble.
  288. #
  289. # 'preamble': '',
  290. # Latex figure (float) alignment
  291. #
  292. # 'figure_align': 'htbp',
  293. }
  294. # Grouping the document tree into LaTeX files. List of tuples
  295. # (source start file, target name, title,
  296. # author, documentclass [howto, manual, or own class]).
  297. latex_documents = [
  298. (master_doc, "SHAP.tex", "SHAP Documentation", "Scott Lundberg", "manual"),
  299. ]
  300. # The name of an image file (relative to this directory) to place at the top of
  301. # the title page.
  302. #
  303. # latex_logo = None
  304. # For "manual" documents, if this is true, then toplevel headings are parts,
  305. # not chapters.
  306. #
  307. # latex_use_parts = False
  308. # If true, show page references after internal links.
  309. #
  310. # latex_show_pagerefs = False
  311. # If true, show URL addresses after external links.
  312. #
  313. # latex_show_urls = False
  314. # Documents to append as an appendix to all manuals.
  315. #
  316. # latex_appendices = []
  317. # It false, will not define \strong, \code, itleref, \crossref ... but only
  318. # \sphinxstrong, ..., \sphinxtitleref, ... To help avoid clash with user added
  319. # packages.
  320. #
  321. # latex_keep_old_macro_names = True
  322. # If false, no module index is generated.
  323. #
  324. # latex_domain_indices = True
  325. # -- Options for manual page output ---------------------------------------
  326. # One entry per manual page. List of tuples
  327. # (source start file, name, description, authors, manual section).
  328. man_pages = [(master_doc, "shap", "SHAP Documentation", [author], 1)]
  329. # If true, show URL addresses after external links.
  330. #
  331. # man_show_urls = False
  332. # -- Options for Texinfo output -------------------------------------------
  333. # Grouping the document tree into Texinfo files. List of tuples
  334. # (source start file, target name, title, author,
  335. # dir menu entry, description, category)
  336. texinfo_documents = [
  337. (
  338. master_doc,
  339. "SHAP",
  340. "SHAP Documentation",
  341. author,
  342. "SHAP",
  343. "One line description of project.",
  344. "Miscellaneous",
  345. ),
  346. ]
  347. # Documents to append as an appendix to all manuals.
  348. #
  349. # texinfo_appendices = []
  350. # If false, no module index is generated.
  351. #
  352. # texinfo_domain_indices = True
  353. # How to display URL addresses: 'footnote', 'no', or 'inline'.
  354. #
  355. # texinfo_show_urls = 'footnote'
  356. # If true, do not generate a @detailmenu in the "Top" node's menu.
  357. #
  358. # texinfo_no_detailmenu = False
  359. def setup(app):
  360. import shap # noqa: F401
  361. app.connect("build-finished", build_finished)
  362. def build_finished(app, exception):
  363. shutil.rmtree(NOTEBOOKS_DIR)

conf.py at commit 50be8f4, under MIT · at the source

Overview

Authors: José Diogo Marques dos Santos1,2, Maria Beatriz Ramos3, Luís Paulo Reis1,2,4, José Paulo Marques dos Santos2,3,4,5, Bruno Direito4,6
  1. Faculty of Engineering, University of Porto, Porto, Portugal
  2. LIACC – Artificial Intelligence and Computer Science Laboratory, University of Porto, Porto, Portugal
  3. Faculty of Medicine, University of Porto, Porto, Portugal
  4. LASI – Intelligent Systems Associate Laboratory, Guimarães, Portugal
  5. University of Maia, Maia, Portugal
  6. CISUC – Centre for Informatics and Systems, University of Coimbra, Coimbra, Portugal
Journal: Frontiers in behavioral neuroscience, volume 20, article 1833995
Dates: received 19 March 2026; accepted 20 July 2026; published online 23 September 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI · PMCID PMC13642823
Status: code verified (how the code is found and verified)
Categories: structural MRI / diffusion (modality), fMRI (modality), human (organism)
Methods: Machine learning, Statistics, fMRI & imaging
Keywords: diffusion tensor imaging, explainable artificial intelligence, fMRI, graph neural networks, message-passing, shallow neural networks, structural connectivity, theory of mind
Citations: not cited yet (Europe PMC); 53 references in the paper

Abstract

Introduction: Applying artificial intelligence to functional magnetic resonance imaging (fMRI) has advanced the modelling of neural activity, but deep architectures such as graph neural networks (GNNs) require large samples, limiting their use in the small cohorts typical of task-based fMRI. Shallow neural networks (SNNs) are robust with few samples but treat brain regions independently, overlooking the brain’s network organization. We propose a structurally constrained message-passing framework that integrates diffusion-based structural connectivity, from a previously published group connectome, with region-level fMRI signals in a shallow architecture.

Methods: The task is a binary classification of individual video trials as mentalizing or random, decoded from the fMRI response, in a Theory of Mind paradigm from the Human Connectome Project Young Adult dataset (30 subjects) under subject-wise 3-fold cross-validation. Two shallow classifiers are compared on the same data: the baseline classifies each trial from the regional fMRI signals as independent inputs, whereas the proposed model first applies one message-passing step, replacing each region’s signal with a structurally connected combination of its neighbors’ signals, so that classification operates at the level of anatomically defined networks. Interpretability is assessed using SHAP (SHapley Additive exPlanations).

Results: Across folds, the proposed model matches the baseline (mean retrained accuracy 85.1%; 84.7% on the shared partition), the accuracy lost to pruning being recovered by retraining in every fold. The magnitude of the inputs’ contributions is reproducible across folds, whereas their direction is not. Only about a quarter of the consistently retained inputs also preserve their sign, so a cross-fold sign-consistency criterion is applied to retain reliable explanations. This identifies seven networks contributing robustly to the mentalizing class, located in the temporo-parietal junction, inferior parietal, and medial temporal cortices and overlapping a literature-based mentalizing map (overlap coefficient 0.383). Within these networks, Cohen’s D ranks the relative signal magnitude of the constituent regions.

Discussion: Overall, structural constraints improve biological interpretability without compromising classification performance, while cross-validation establishes which explanations are stable, offering a compact and interpretable approach to network-level brain decoding in small cohorts and a basis that may be applied to connectivity disorders.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repository

Its files are read in the Code ↔ Paper reader above.

shap/shap

License: MIT
State: the link answers, verified on 8 October 2026
Evidence: files inventoried
Commit: 50be8f4fd7031d535d515042741320f53272d211, 4 October 2026
Languages: Python (173), Jupyter (88), JavaScript (16), C/C++ (9), C++ (3), CUDA (1)
Size: 606 files, 290 scripts
Software Heritage: archived
Found in: the end of the paper
Holds: README, license file, environment (pyproject.toml, docs/requirements-docs.txt), tests, continuous integration, documentation, 88 notebooks
Not found: CITATION.cff
Tools: SHAP (37 files), NumPy (16 files), XGBoost (16 files), Keras (7 files), Hugging Face Transformers (7 files), Matplotlib (6 files), PyTorch (5 files), scikit-learn (5 files), TensorFlow (5 files), LightGBM (2 files), pandas (2 files), SciPy (2 files)
Availability: 1 check, the latest on 8 October 2026: the link answers
  • 8 October 2026: the link answers
56 files
At the source: github.com/shap/shap

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 54 scripts, each with its path and the digest of its content;
  • no match between paragraphs and code yet;
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

Data availability statement

Publicly available datasets were analyzed in this study. This data can be found at: HCP-Young Adult 2025 at https://balsa.wustl.edu/project?project=HCP_YA.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 8 October 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 5 authors, 8 keywords, 42 references.

Cite

This paper

Marques dos Santos, J. D., Ramos, M. B., Reis, L. P., Marques dos Santos, J. P., & Direito, B. (2026). Structurally restricted message-passing within shallow architectures for explainable network-level brain decoding on small cohorts. Frontiers in behavioral neuroscience, 20, 1833995.

BibTeX

@article{marquesdossantos2026structurally,
author = {Marques dos Santos, José Diogo and Ramos, Maria Beatriz and Reis, Luís Paulo and Marques dos Santos, José Paulo and Direito, Bruno},
title = {{Structurally restricted message-passing within shallow architectures for explainable network-level brain decoding on small cohorts}},
journal = {Frontiers in behavioral neuroscience},
year = {2026},
month = oct,
volume = {20},
pages = {1833995},
publisher = {Frontiers Media SA},
issn = {1662-5153},
pmcid = {PMC13642823}
}

RIS

TY - JOUR
AU - Marques dos Santos, José Diogo
AU - Ramos, Maria Beatriz
AU - Reis, Luís Paulo
AU - Marques dos Santos, José Paulo
AU - Direito, Bruno
TI - Structurally restricted message-passing within shallow architectures for explainable network-level brain decoding on small cohorts
T2 - Frontiers in behavioral neuroscience
J2 - Front Behav Neurosci
PY - 2026
DA - 2026/10/08
VL - 20
SP - 1833995
SN - 1662-5153
PB - Frontiers Media SA
LA - en
ER -

CSL-JSON

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"author": [
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"family": "Marques dos Santos",
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{
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{
"family": "Direito",
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"container-title-short": "Front Behav Neurosci",
"volume": "20",
"page": "1833995",
"PMCID": "PMC13642823",
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"publisher": "Frontiers Media SA",
"language": "en",
"issued": {
"date-parts": [
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}
}

The tracing map gets a citation of its own once an author has validated it and it has a DOI.

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Visualizing functional network connectivity differences using an explainable machine-learning method.
Journal: Physiological measurement
In common: LightGBM, Hugging Face Transformers, SHAP, 9 other tools
[6] doi:10.1038/s41597-024-03838-4 [code]
EAV: EEG-Audio-Video Dataset for Emotion Recognition in Conversational Contexts.
Journal: Scientific data
In common: LightGBM, Hugging Face Transformers, SHAP, 9 other tools
[7] doi:10.1016/j.isci.2023.107522 [code]
Deep learning for risk-based stratification of cognitively impaired individuals.
Journal: iScience
In common: LightGBM, Hugging Face Transformers, SHAP, 9 other tools
[8] doi:10.1038/s41531-025-00982-5 [code]
Baseline [&lt;sup&gt;18&lt;/sup&gt;F]FP-CIT PET-based deep learning prediction of levodopa-induced dyskinesia in Parkinson's disease.
Journal: NPJ Parkinson's disease
In common: LightGBM, Hugging Face Transformers, SHAP, 9 other tools
[9] doi:10.3390/diagnostics13172840 [code]
The Diagnostic Accuracy of Artificial Intelligence in Radiological Markers of Normal-Pressure Hydrocephalus (NPH) on Non-Contrast CT Scans of the Brain.
Journal: Diagnostics (Basel, Switzerland)
In common: LightGBM, Hugging Face Transformers, SHAP, 9 other tools
[10] doi:10.1016/j.xpro.2023.102320 [code]
WaveMAP for identifying putative cell types from in vivo electrophysiology.
Journal: STAR protocols
In common: LightGBM, Hugging Face Transformers, SHAP, 9 other tools

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