Changes
On December 12, 2023 at 4:13:48 PM +0800, Albert Yang:
-
Updated description of Taiwan Aging and Mental Illness Cohort from
##Overview## The Taiwan Aging and Mental Illness Cohort (TAMI) presents a detailed and extensive Magnetic Resonance Imaging (MRI) study dataset, spearheaded by Professor Albert C. Yang. This project, initiated in 2012, is a collaboration between Taipei Veterans General Hospital and National Yang Ming Chiao Tung University, Yangming campus. It focuses on providing valuable insights into various mental illnesses and their impact on brain structure and function. ##Dataset Composition## __Participants__: The study includes 1,265 participants, encompassing 587 healthy individuals and 678 patients diagnosed with mental illnesses such as schizophrenia, bipolar disorder, and depression. __Imaging Data__: Participants have undergone comprehensive brain imaging scans at the MRI facility located at the Yangming campus. __Types of MRI Data__: __Structural MRI__: Includes data from Structural and Diffusion Tensor Imaging. __Functional MRI__: Provides data on brain activity and function. ##Dataset Scope and Objectives## To understand the neurological impacts of aging and mental illnesses. To explore the structural and functional brain changes associated with schizophrenia, bipolar disorder, and depression. Additional Data: Along with the MRI scans, the dataset also contains: Demographic information of participants. Detailed clinical data for each participant.
to##Overview## The Taiwan Aging and Mental Illness Cohort (TAMI) presents a detailed and extensive Magnetic Resonance Imaging (MRI) study dataset, spearheaded by Professor Albert C. Yang. This project, initiated in 2012, is a collaboration between Taipei Veterans General Hospital and National Yang Ming Chiao Tung University, Yangming campus. It focuses on providing valuable insights into various mental illnesses and their impact on brain structure and function. ##Dataset Composition## __Participants__: The study includes 1,265 participants, encompassing 587 healthy individuals and 678 patients diagnosed with mental illnesses such as schizophrenia, bipolar disorder, and depression. __Imaging Data__: Participants have undergone comprehensive brain imaging scans at the MRI facility located at the Yangming campus. __Types of MRI Data__: __Structural MRI__: Includes data from Structural and Diffusion Tensor Imaging. __Functional MRI__: Provides data on brain activity and function. ##Dataset Scope and Objectives## To understand the neurological impacts of aging and mental illnesses. To explore the structural and functional brain changes associated with schizophrenia, bipolar disorder, and depression. Additional Data: Along with the MRI scans, the dataset also contains: Demographic information of participants. Detailed clinical data for each participant. ##Citation Guidelines for Using the TAMI Dataset## When utilizing data from the TAMI in your research, please cite the following paper in your published materials https://www.nature.com/articles/s41398-023-02379-5 https://www.sciencedirect.com/science/article/pii/S019745801200276X
f | 1 | { | f | 1 | { |
2 | "author": "Albert C. Yang, MD", | 2 | "author": "Albert C. Yang, MD", | ||
3 | "author_email": "accyang@nycu.edu.tw", | 3 | "author_email": "accyang@nycu.edu.tw", | ||
4 | "creator_user_id": "1d214521-cf55-43ab-8a2a-1d7307cf05e7", | 4 | "creator_user_id": "1d214521-cf55-43ab-8a2a-1d7307cf05e7", | ||
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9 | "license_id": "cc-by", | 9 | "license_id": "cc-by", | ||
10 | "license_title": "Creative Commons Attribution", | 10 | "license_title": "Creative Commons Attribution", | ||
11 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | 11 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | ||
12 | "maintainer": "I-Jou Chi", | 12 | "maintainer": "I-Jou Chi", | ||
13 | "maintainer_email": "irene159irene159.md10@nycu.edu.tw", | 13 | "maintainer_email": "irene159irene159.md10@nycu.edu.tw", | ||
14 | "metadata_created": "2023-12-06T01:48:03.763872", | 14 | "metadata_created": "2023-12-06T01:48:03.763872", | ||
n | 15 | "metadata_modified": "2023-12-12T08:07:04.485738", | n | 15 | "metadata_modified": "2023-12-12T08:13:48.463180", |
16 | "name": "taiwan-aging-and-mental-illness-cohort-tami", | 16 | "name": "taiwan-aging-and-mental-illness-cohort-tami", | ||
17 | "notes": "##Overview##\r\n\r\nThe Taiwan Aging and Mental Illness | 17 | "notes": "##Overview##\r\n\r\nThe Taiwan Aging and Mental Illness | ||
18 | Cohort (TAMI) presents a detailed and extensive Magnetic Resonance | 18 | Cohort (TAMI) presents a detailed and extensive Magnetic Resonance | ||
19 | Imaging (MRI) study dataset, spearheaded by Professor Albert C. Yang. | 19 | Imaging (MRI) study dataset, spearheaded by Professor Albert C. Yang. | ||
20 | This project, initiated in 2012, is a collaboration between Taipei | 20 | This project, initiated in 2012, is a collaboration between Taipei | ||
21 | Veterans General Hospital and National Yang Ming Chiao Tung | 21 | Veterans General Hospital and National Yang Ming Chiao Tung | ||
22 | University, Yangming campus. It focuses on providing valuable insights | 22 | University, Yangming campus. It focuses on providing valuable insights | ||
23 | into various mental illnesses and their impact on brain structure and | 23 | into various mental illnesses and their impact on brain structure and | ||
24 | function.\r\n\r\n##Dataset Composition##\r\n\r\n__Participants__: The | 24 | function.\r\n\r\n##Dataset Composition##\r\n\r\n__Participants__: The | ||
25 | study includes 1,265 participants, encompassing 587 healthy | 25 | study includes 1,265 participants, encompassing 587 healthy | ||
26 | individuals and 678 patients diagnosed with mental illnesses such as | 26 | individuals and 678 patients diagnosed with mental illnesses such as | ||
27 | schizophrenia, bipolar disorder, and depression.\r\n\r\n__Imaging | 27 | schizophrenia, bipolar disorder, and depression.\r\n\r\n__Imaging | ||
28 | Data__: Participants have undergone comprehensive brain imaging scans | 28 | Data__: Participants have undergone comprehensive brain imaging scans | ||
29 | at the MRI facility located at the Yangming campus.\r\n\r\n__Types of | 29 | at the MRI facility located at the Yangming campus.\r\n\r\n__Types of | ||
30 | MRI Data__:\r\n\r\n__Structural MRI__: Includes data from Structural | 30 | MRI Data__:\r\n\r\n__Structural MRI__: Includes data from Structural | ||
31 | and Diffusion Tensor Imaging.\r\n\r\n__Functional MRI__: Provides data | 31 | and Diffusion Tensor Imaging.\r\n\r\n__Functional MRI__: Provides data | ||
32 | on brain activity and function.\r\n\r\n##Dataset Scope and | 32 | on brain activity and function.\r\n\r\n##Dataset Scope and | ||
33 | Objectives##\r\n\r\nTo understand the neurological impacts of aging | 33 | Objectives##\r\n\r\nTo understand the neurological impacts of aging | ||
34 | and mental illnesses.\r\n\r\nTo explore the structural and functional | 34 | and mental illnesses.\r\n\r\nTo explore the structural and functional | ||
35 | brain changes associated with schizophrenia, bipolar disorder, and | 35 | brain changes associated with schizophrenia, bipolar disorder, and | ||
36 | depression.\r\nAdditional Data:\r\n\r\nAlong with the MRI scans, the | 36 | depression.\r\nAdditional Data:\r\n\r\nAlong with the MRI scans, the | ||
37 | dataset also contains:\r\n\r\nDemographic information of | 37 | dataset also contains:\r\n\r\nDemographic information of | ||
t | 38 | participants.\r\nDetailed clinical data for each participant.", | t | 38 | participants.\r\nDetailed clinical data for each |
39 | participant.\r\n\r\n##Citation Guidelines for Using the TAMI | ||||
40 | Dataset##\r\n\r\nWhen utilizing data from the TAMI in your research, | ||||
41 | please cite the following paper in your published | ||||
42 | nhttps://www.sciencedirect.com/science/article/pii/S019745801200276X", | ||||
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219 | "package_id": "804e1201-067d-4c50-ae36-f549b714a38a", | 223 | "package_id": "804e1201-067d-4c50-ae36-f549b714a38a", | ||
220 | "position": 6, | 224 | "position": 6, | ||
221 | "resource_type": null, | 225 | "resource_type": null, | ||
222 | "size": 33295, | 226 | "size": 33295, | ||
223 | "state": "active", | 227 | "state": "active", | ||
224 | "url": | 228 | "url": | ||
225 | ource/012f1059-1da1-420d-b847-6cf0e621f74d/download/landrvolumes.csv", | 229 | ource/012f1059-1da1-420d-b847-6cf0e621f74d/download/landrvolumes.csv", | ||
226 | "url_type": "upload" | 230 | "url_type": "upload" | ||
227 | }, | 231 | }, | ||
228 | { | 232 | { | ||
229 | "cache_last_updated": null, | 233 | "cache_last_updated": null, | ||
230 | "cache_url": null, | 234 | "cache_url": null, | ||
231 | "created": "2023-12-12T08:02:01.473883", | 235 | "created": "2023-12-12T08:02:01.473883", | ||
232 | "datastore_active": false, | 236 | "datastore_active": false, | ||
233 | "description": "This dataset comprises preprocessed MRI images | 237 | "description": "This dataset comprises preprocessed MRI images | ||
234 | acquired from schizophrenia patients. These images have been processed | 238 | acquired from schizophrenia patients. These images have been processed | ||
235 | using FSL to generate data on cortical thickness.", | 239 | using FSL to generate data on cortical thickness.", | ||
236 | "format": "NIFTI", | 240 | "format": "NIFTI", | ||
237 | "hash": "", | 241 | "hash": "", | ||
238 | "id": "fe45f10d-ea5b-4af7-9a65-b62bd71c60eb", | 242 | "id": "fe45f10d-ea5b-4af7-9a65-b62bd71c60eb", | ||
239 | "last_modified": null, | 243 | "last_modified": null, | ||
240 | "metadata_modified": "2023-12-12T08:02:31.923112", | 244 | "metadata_modified": "2023-12-12T08:02:31.923112", | ||
241 | "mimetype": null, | 245 | "mimetype": null, | ||
242 | "mimetype_inner": null, | 246 | "mimetype_inner": null, | ||
243 | "name": "MRI Cortical Thickness Image Dataset - Schizophrenia", | 247 | "name": "MRI Cortical Thickness Image Dataset - Schizophrenia", | ||
244 | "package_id": "804e1201-067d-4c50-ae36-f549b714a38a", | 248 | "package_id": "804e1201-067d-4c50-ae36-f549b714a38a", | ||
245 | "position": 7, | 249 | "position": 7, | ||
246 | "resource_type": null, | 250 | "resource_type": null, | ||
247 | "size": null, | 251 | "size": null, | ||
248 | "state": "active", | 252 | "state": "active", | ||
249 | "url": | 253 | "url": | ||
250 | hHgmpJx9vJ3E6Hg9dozzyab/uvXeRhty_BrX9JJsvhdi5f-nPPV7Ja7h-GbDA_92r-Ao", | 254 | hHgmpJx9vJ3E6Hg9dozzyab/uvXeRhty_BrX9JJsvhdi5f-nPPV7Ja7h-GbDA_92r-Ao", | ||
251 | "url_type": null | 255 | "url_type": null | ||
252 | } | 256 | } | ||
253 | ], | 257 | ], | ||
254 | "state": "active", | 258 | "state": "active", | ||
255 | "tags": [ | 259 | "tags": [ | ||
256 | { | 260 | { | ||
257 | "display_name": "Mental Health", | 261 | "display_name": "Mental Health", | ||
258 | "id": "7bb6d9bb-aa78-406e-b708-b17c01c16223", | 262 | "id": "7bb6d9bb-aa78-406e-b708-b17c01c16223", | ||
259 | "name": "Mental Health", | 263 | "name": "Mental Health", | ||
260 | "state": "active", | 264 | "state": "active", | ||
261 | "vocabulary_id": null | 265 | "vocabulary_id": null | ||
262 | }, | 266 | }, | ||
263 | { | 267 | { | ||
264 | "display_name": "bipolar disorder", | 268 | "display_name": "bipolar disorder", | ||
265 | "id": "e7c29991-0c6e-4235-b730-8fdacba43171", | 269 | "id": "e7c29991-0c6e-4235-b730-8fdacba43171", | ||
266 | "name": "bipolar disorder", | 270 | "name": "bipolar disorder", | ||
267 | "state": "active", | 271 | "state": "active", | ||
268 | "vocabulary_id": null | 272 | "vocabulary_id": null | ||
269 | }, | 273 | }, | ||
270 | { | 274 | { | ||
271 | "display_name": "brain", | 275 | "display_name": "brain", | ||
272 | "id": "7828821f-c0ef-4377-98c3-4261eee91cf1", | 276 | "id": "7828821f-c0ef-4377-98c3-4261eee91cf1", | ||
273 | "name": "brain", | 277 | "name": "brain", | ||
274 | "state": "active", | 278 | "state": "active", | ||
275 | "vocabulary_id": null | 279 | "vocabulary_id": null | ||
276 | }, | 280 | }, | ||
277 | { | 281 | { | ||
278 | "display_name": "brain image", | 282 | "display_name": "brain image", | ||
279 | "id": "e6e4b86c-3c9b-43a8-9482-f9d6818cbd5d", | 283 | "id": "e6e4b86c-3c9b-43a8-9482-f9d6818cbd5d", | ||
280 | "name": "brain image", | 284 | "name": "brain image", | ||
281 | "state": "active", | 285 | "state": "active", | ||
282 | "vocabulary_id": null | 286 | "vocabulary_id": null | ||
283 | }, | 287 | }, | ||
284 | { | 288 | { | ||
285 | "display_name": "depression", | 289 | "display_name": "depression", | ||
286 | "id": "3263b012-fd20-43ec-8d4b-14d947eb200a", | 290 | "id": "3263b012-fd20-43ec-8d4b-14d947eb200a", | ||
287 | "name": "depression", | 291 | "name": "depression", | ||
288 | "state": "active", | 292 | "state": "active", | ||
289 | "vocabulary_id": null | 293 | "vocabulary_id": null | ||
290 | }, | 294 | }, | ||
291 | { | 295 | { | ||
292 | "display_name": "schizophrenia", | 296 | "display_name": "schizophrenia", | ||
293 | "id": "b8c9c52a-d62f-49eb-9d04-5877b53a2c70", | 297 | "id": "b8c9c52a-d62f-49eb-9d04-5877b53a2c70", | ||
294 | "name": "schizophrenia", | 298 | "name": "schizophrenia", | ||
295 | "state": "active", | 299 | "state": "active", | ||
296 | "vocabulary_id": null | 300 | "vocabulary_id": null | ||
297 | } | 301 | } | ||
298 | ], | 302 | ], | ||
299 | "title": "Taiwan Aging and Mental Illness Cohort", | 303 | "title": "Taiwan Aging and Mental Illness Cohort", | ||
300 | "type": "dataset", | 304 | "type": "dataset", | ||
301 | "url": "", | 305 | "url": "", | ||
302 | "version": "" | 306 | "version": "" | ||
303 | } | 307 | } |