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Hippocampal Subfield Volumes and Spatial Memory Performance in Older Adults At-Risk for Type 2 Diabetes.

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Paper

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The authors' code

Python · 196 lines · 6.6 KB · other-open

  1. ##############################################################################
  2. # Kivy Launcher Interface #
  3. # by: Daniel Palmer PhD #
  4. # Version: 2.0 #
  5. ##############################################################################
  6. # Setup#
  7. from kivy.config import Config
  8. import os
  9. import configparser
  11. main_path = os.getcwd()
  12. config_path = main_path + '/Screen.ini'
  13. config_file = configparser.ConfigParser()
  14. config_file.read(config_path)
  15. x_dim = config_file['Screen']['x']
  16. y_dim = config_file['Screen']['y']
  17. fullscreen = int(config_file['Screen']['fullscreen'])
  19. if fullscreen == 0:
  20. Config.set('graphics', 'width', str(x_dim))
  21. Config.set('graphics', 'height', str(y_dim))
  22. Config.set('graphics', 'fullscreen', '0')
  23. Config.set('graphics', 'position', 'custom')
  24. Config.set('graphics', 'top', 0)
  25. Config.set('graphics', 'left', 0)
  26. Config.set('kivy', 'keyboard_mode', 'systemandmulti')
  27. elif fullscreen == 1:
  28. Config.set('graphics', 'width', str(x_dim))
  29. Config.set('graphics', 'height', str(y_dim))
  30. Config.set('graphics', 'position', 'custom')
  31. Config.set('graphics', 'top', 0)
  32. Config.set('graphics', 'left', 0)
  33. Config.set('graphics', 'fullscreen', True)
  34. Config.set('kivy', 'keyboard_mode', 'systemandmulti')
  36. # Imports #
  37. import kivy
  38. import zipimport
  39. import sys
  40. import os
  41. import configparser
  42. from kivy.app import App
  43. from kivy.uix.widget import Widget
  44. from kivy.uix.button import Button
  45. from kivy.uix.image import Image
  46. from kivy.uix.label import Label
  47. from kivy.core.window import Window
  48. from kivy.uix.floatlayout import FloatLayout
  49. from kivy.uix.gridlayout import GridLayout
  50. # from win32api import GetSystemMetrics
  51. from kivy.uix.behaviors import ButtonBehavior
  52. from kivy.clock import Clock
  53. from kivy.uix.textinput import TextInput
  54. from kivy.uix.vkeyboard import VKeyboard
  55. from kivy.uix.screenmanager import ScreenManager, Screen
  56. from kivy.config import Config
  57. from functools import partial
  59. Window.borderless = True
  62. # from Protocol_Configure import Protocol_Select
  64. # General Functions #
  65. def os_folder_modifier():
  66. os_platform = sys.platform
  67. if os_platform == "linux":
  68. mod = "/"
  69. elif os_platform == "darwin":
  70. mod = "/"
  71. elif os_platform == "win32":
  72. mod = "\\"
  73. else:
  74. mod = "/"
  75. return mod
  78. # Class Objects #
  79. class ImageButton(ButtonBehavior, Image):
  80. def __init__(self, **kwargs):
  81. super(ImageButton, self).__init__(**kwargs)
  84. # Class Screen Manager #
  86. class Screen_Manager(ScreenManager):
  87. def __init__(self, **kwargs):
  88. super(Screen_Manager, self).__init__(**kwargs)
  91. # Class Task Selection #
  92. class Main_Menu(Screen):
  93. def __init__(self, **kwargs):
  94. super(Main_Menu, self).__init__(**kwargs)
  95. self.Menu_Layout = FloatLayout()
  96. self.add_widget(self.Menu_Layout)
  97. launch_button = Button(text="Start Session")
  98. launch_button.size_hint = (0.3, 0.2)
  99. launch_button.pos_hint = {"x": 0.35, "y": 0.6}
  100. launch_button.bind(on_press=self.load_protocol_menu)
  101. self.Menu_Layout.add_widget(launch_button)
  103. exit_button = Button(text="Close Program")
  104. exit_button.size_hint = (0.3, 0.2)
  105. exit_button.pos_hint = {"x": 0.35, "y": 0.2}
  106. exit_button.bind(on_press=self.exit_program)
  107. self.Menu_Layout.add_widget(exit_button)
  109. def load_protocol_menu(self, *args):
  110. self.protocol_window = Protocol_Menu()
  111. self.manager.add_widget(Protocol_Menu(name='protocolmenu'))
  112. self.manager.current = "protocolmenu"
  114. def exit_program(self, *args):
  115. App.get_running_app().stop()
  116. Window.close()
  119. # Class Protocol Selection #
  120. class Protocol_Menu(Screen):
  121. def __init__(self, **kwargs):
  122. super(Protocol_Menu, self).__init__(**kwargs)
  123. self.Protocol_Layout = FloatLayout()
  125. protocol_list = self.search_protocols()
  126. self.Protocol_List = GridLayout(rows=len(protocol_list), cols=1)
  127. protocol_index = 0
  128. for protocol in protocol_list:
  129. button_func = partial(self.set_protocol, protocol)
  130. self.Protocol_List.add_widget(Button(text=protocol, on_press=button_func))
  131. protocol_index += 1
  133. self.Protocol_List.size_hint = (0.8, 0.7)
  134. self.Protocol_List.pos_hint = {"x": 0.1, "y": 0.3}
  135. self.Protocol_Layout.add_widget(self.Protocol_List)
  137. cancel_button = Button(text="Cancel")
  138. cancel_button.size_hint = (0.2, 0.1)
  139. cancel_button.pos_hint = {"x": 0.4, "y": 0.1}
  140. cancel_button.bind(on_press=self.cancel_protocol)
  141. self.Protocol_Layout.add_widget(cancel_button)
  143. self.add_widget(self.Protocol_Layout)
  145. def set_protocol(self, label, *args):
  146. self.protocol_constructor(label)
  147. self.manager.switch_to(self.Protocol_Configure_Screen)
  149. def cancel_protocol(self, *args):
  150. self.manager.current = "mainmenu"
  152. def search_protocols(self):
  153. cwd = os.getcwd()
  154. mod = os_folder_modifier()
  155. folder = cwd + mod + "Protocol"
  156. task_list = os.listdir(folder)
  157. return task_list
  159. def protocol_constructor(self, protocol):
  160. if protocol == 'iCPT2GStim1':
  161. from Protocol.iCPT2GStim1.Menu import Configure_Screen
  162. self.Protocol_Configure_Screen = Configure_Screen()
  163. elif protocol == 'iCPT2GStim2':
  164. from Protocol.iCPT2GStim2.Menu import Configure_Screen
  165. self.Protocol_Configure_Screen = Configure_Screen()
  166. elif protocol == 'vPRL':
  167. from Protocol.vPRL.Menu import Configure_Screen
  168. self.Protocol_Configure_Screen = Configure_Screen()
  169. elif protocol == 'PAL':
  170. from Protocol.PAL.Menu import Configure_Screen
  171. self.Protocol_Configure_Screen = Configure_Screen()
  172. elif protocol == 'PRHuman':
  173. from Protocol.PRHuman.Menu import Configure_Screen
  174. self.Protocol_Configure_Screen = Configure_Screen()
  175. elif protocol == 'TUNL':
  176. from Protocol.TUNL.Menu import Configure_Screen
  177. self.Protocol_Configure_Screen = Configure_Screen()
  178. elif protocol == 'TUNLProbe':
  179. from Protocol.TUNLProbe.Menu import ConfigureScreen
  180. self.Protocol_Configure_Screen = ConfigureScreen()
  183. # Class App Builder #
  184. class MenuApp(App):
  185. def build(self):
  186. self.s_manager = Screen_Manager()
  187. self.s_manager.add_widget(Main_Menu(name="mainmenu"))
  189. return self.s_manager
  191. def add_screen(self, screen):
  192. self.s_manager.add_widget(screen)
  195. if __name__ == '__main__':
  196. MenuApp().run()

KivyMenuInterface.py, under other-open · at the source

Overview

Authors: Jennifer Hanna Al‐Shaikh1,2, Olivia R. Ghosh‐Swaby1,2, Ali R. Khan2,3, Jane Thornton4, Timothy J. Bussey2,5, Lisa M. Saksida2,5, Daniel Palmer2,5, Teresa Liu‐Ambrose6, Lindsay S. Nagamatsu7
ORCID iDs: Jennifer Hanna Al‐Shaikh, Ali R. Khan, Daniel Palmer, Teresa Liu‐Ambrose, Lindsay S. Nagamatsu
  1. Graduate Program in Neuroscience Western University London Ontario Canada
  2. Robarts Research Institute, Schulich School of Medicine and Dentistry Western University London Ontario Canada
  3. Department of Medical Biophysics Western University London Ontario Canada
  4. Department of Epidemiology & Biostatistics Western University London Ontario Canada
  5. Department of Physiology & Pharmacology Western University London Ontario Canada
  6. Department of Physical Therapy University of British Columbia Vancouver British Columbia Canada
  7. School of Kinesiology Western University London Ontario Canada
Institutions: Western University (Canada); Robarts Research Institute (Canada); University of British Columbia (Canada)
Journal: Hippocampus, volume 36, issue 6, article e70144
Dates: received 29 January 2026; accepted 6 October 2026; published online 28 October 2026; in print November 2026
Type: Research article · Language: English
License: CC BY-NC
Identifiers: DOI 10.1002/hipo.70144 · PMID 42951841 · PMCID PMC13716845 · OpenAlex W7224111531
Open access: hybrid, a free copy (OpenAlex)
Status: code verified (how the code is found and verified)
Categories: structural MRI / diffusion (modality), human (organism), other condition (population)
Methods: Statistics, Machine learning
Keywords: Hippocampal subfield volumes, magnetic resonance imaging, regional brain volume, touchscreen trial‐unique delayed non‐matching to location, type 2 diabetes risk
MeSH: Diabetes Mellitus, Type 2*, Hippocampus*, Spatial Memory*, Aged, Aging, Cross-Sectional Studies, Female, Glycated Hemoglobin, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Neuropsychological Tests, Organ Size (* major topic)
Topic: Dementia and Cognitive Impairment Research (Psychiatry and Mental health, Medicine), according to OpenAlex
Funding: Gouvernement du Canada | Canadian Institutes of Health Research (IRSC); Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada (RGPIN‐2016‐05052)
Citations: not cited yet (Europe PMC); 67 references in the paper

Abstract

Older adults at risk for type 2 diabetes (T2D) are more likely to experience accelerated cognitive aging and neurodegeneration due to impaired metabolism in the hippocampus. However, the precise relationship between T2D risk factors, brain volumes (i.e., gray matter, white matter, hippocampus subfields), and hippocampus‐dependent functions (i.e., spatial pattern separation, a component of spatial memory) remains unexplored. To investigate these relationships in this cross‐sectional study, 60 older adults at risk for T2D (e.g., high BMI or elevated A1c levels) completed a touchscreen‐based spatial pattern separation behavioral task—the Trial‐Unique delayed Nonmatching‐to‐Location (TUNL) and magnetic resonance imaging (MRI). HippUnfold was utilized to segment the hippocampus from high‐resolution, T1‐weighted images. We found positive correlations between A1c levels and volumes of the dentate gyrus (DG) and cornu ammonis (CA) 2, indicating that higher A1c was associated with larger volumes of hippocampal subregions. Additionally, TUNL accuracy was correlated with gray matter and distinct hippocampus subfield volumes (i.e., subiculum, CA1, and CA4), with larger volumes associated with better spatial memory performance. Understanding early structural changes in T2D risk allows us to further characterize changes in brain health associated with metabolic dysfunction.

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

Repositories

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

Zenodo 7577008

License: other-open
State: the link answers, verified on 1 November 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: the text, “Spatial Memory Apparatus and Measures”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: NumPy (7 files)
Availability: 1 check, the latest on 1 November 2026: the link answers (HTTP 200)
  • 1 November 2026: the link answers (HTTP 200)
25 files
At the source: zenodo.org/records/7577008

dpalmer9/touchcog

License: GPL-3.0
State: the link answers, verified on 1 November 2026
Evidence: files inventoried
Commit: f6f059a83e08bdf13a5a2e2e4bfb6b7cf23963d9, 14 October 2026
Languages: Python (28)
Size: 463 files, 28 scripts
Software Heritage: not archived
Found in: the Zenodo archive record
Holds: README, license file, CITATION.cff, environment (requirements.txt)
Not found: tests, continuous integration, documentation
Tools: NumPy (5 files), pandas (4 files)
Availability: 1 check, the latest on 1 November 2026: the link answers
  • 1 November 2026: the link answers
30 files
At the source: github.com/dpalmer9/TouchCog/tree/v0.9.0

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:

  • 2 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 51 scripts, each with its path and the digest of its content;
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Data

No dataset and no data link were found in the paper.

Data Availability Statement

Data is available from the corresponding author upon reasonable request.

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

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Version 1, 1 November 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 9 authors, 5 keywords, 14 MeSH terms, 3 funders, 61 references.

Cite

This paper

Al‐Shaikh, J. H., Ghosh‐Swaby, O. R., Khan, A. R., Thornton, J., Bussey, T. J., Saksida, L. M., Palmer, D., Liu‐Ambrose, T., & Nagamatsu, L. S. (2026). Hippocampal Subfield Volumes and Spatial Memory Performance in Older Adults At-Risk for Type 2 Diabetes. Hippocampus, 36(6), e70144. https://doi.org/10.1002/hipo.70144

BibTeX

@article{alshaikh2026hippocampal,
author = {Al‐Shaikh, Jennifer Hanna and Ghosh‐Swaby, Olivia R. and Khan, Ali R. and Thornton, Jane and Bussey, Timothy J. and Saksida, Lisa M. and Palmer, Daniel and Liu‐Ambrose, Teresa and Nagamatsu, Lindsay S.},
title = {{Hippocampal Subfield Volumes and Spatial Memory Performance in Older Adults At-Risk for Type 2 Diabetes}},
journal = {Hippocampus},
year = {2026},
month = nov,
volume = {36},
number = {6},
pages = {e70144},
publisher = {Wiley},
issn = {1050-9631},
doi = {10.1002/hipo.70144},
url = {https://doi.org/10.1002/hipo.70144},
pmid = {42951841},
pmcid = {PMC13716845}
}

RIS

TY - JOUR
AU - Al‐Shaikh, Jennifer Hanna
AU - Ghosh‐Swaby, Olivia R.
AU - Khan, Ali R.
AU - Thornton, Jane
AU - Bussey, Timothy J.
AU - Saksida, Lisa M.
AU - Palmer, Daniel
AU - Liu‐Ambrose, Teresa
AU - Nagamatsu, Lindsay S.
TI - Hippocampal Subfield Volumes and Spatial Memory Performance in Older Adults At-Risk for Type 2 Diabetes
T2 - Hippocampus
J2 - Hippocampus
PY - 2026
DA - 2026/11/01
VL - 36
IS - 6
SP - e70144
SN - 1050-9631
PB - Wiley
DO - 10.1002/hipo.70144
UR - https://doi.org/10.1002/hipo.70144
LA - en
ER -

CSL-JSON

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"id": "10.1002/hipo.70144",
"type": "article-journal",
"title": "Hippocampal Subfield Volumes and Spatial Memory Performance in Older Adults At-Risk for Type 2 Diabetes",
"container-title": "Hippocampus",
"author": [
{
"family": "Al‐Shaikh",
"given": "Jennifer Hanna"
},
{
"family": "Ghosh‐Swaby",
"given": "Olivia R."
},
{
"family": "Khan",
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{
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"given": "Jane"
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{
"family": "Bussey",
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{
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{
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{
"family": "Liu‐Ambrose",
"given": "Teresa"
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{
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"given": "Lindsay S."
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"container-title-short": "Hippocampus",
"volume": "36",
"issue": "6",
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"DOI": "10.1002/hipo.70144",
"PMID": "42951841",
"PMCID": "PMC13716845",
"ISSN": "1050-9631",
"publisher": "Wiley",
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"language": "en",
"issued": {
"date-parts": [
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1
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}
}

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