Example of the results of the model fitting in the 103-dimensional parameter space.
<p>Boxplots illustrate the distributions of the values for the optimal <b>(A)</b> delay , <b>(B)</b> coupling , <b>(C)</b> noise intensity , <b>(D)</b> goodness-of-fit (GoF) and <b>(E,F)</b> frequency parameters found in 30 executions...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | , , |
| Published: |
2025
|
| Subjects: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1852020458026696704 |
|---|---|
| author | Kevin J. Wischnewski (21354521) |
| author2 | Florian Jarre (2902498) Simon B. Eickhoff (8355852) Oleksandr V. Popovych (7866194) |
| author2_role | author author author |
| author_facet | Kevin J. Wischnewski (21354521) Florian Jarre (2902498) Simon B. Eickhoff (8355852) Oleksandr V. Popovych (7866194) |
| author_role | author |
| dc.creator.none.fl_str_mv | Kevin J. Wischnewski (21354521) Florian Jarre (2902498) Simon B. Eickhoff (8355852) Oleksandr V. Popovych (7866194) |
| dc.date.none.fl_str_mv | 2025-05-13T23:51:37Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0322983.g002 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Example_of_the_results_of_the_model_fitting_in_the_103-dimensional_parameter_space_/29057978 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biophysics Medicine Genetics Neuroscience Sociology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified mathematical challenges originating coupled phase oscillators 103 parameters simultaneously simulated functional connectivity dimensional parameter spaces dimensional approaches unanswered exploring dynamical whole dimensional model fitting dimensional spaces model fitting dimensional cases parameter optimizations dynamical whole model validation thoroughly documented thereby optimized sex classification results elucidate reliable together practical benefits phenotypical data modeling results individual variability improved considerably empirical data bayesian optimization 272 subjects |
| dc.title.none.fl_str_mv | Example of the results of the model fitting in the 103-dimensional parameter space. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>Boxplots illustrate the distributions of the values for the optimal <b>(A)</b> delay , <b>(B)</b> coupling , <b>(C)</b> noise intensity , <b>(D)</b> goodness-of-fit (GoF) and <b>(E,F)</b> frequency parameters found in 30 executions (with random initial data) of the CMAES algorithm for one subject. The considered modeling quantities are indicated in the titles of each plot, while their considered ranges are given on the vertical axes. Plot <b>(E)</b> shows the first half of the frequency parameters, belonging to the brain regions in the left hemisphere in the Schaefer atlas, and <b>(F)</b> shows the second half, which represents the right hemisphere. This figure was created with MATLAB R2021a (<a href="http://www.mathworks.com" target="_blank">www.mathworks.com</a>).</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_f80da2e81fceeb6a7c4b281c78091905 |
| identifier_str_mv | 10.1371/journal.pone.0322983.g002 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/29057978 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Example of the results of the model fitting in the 103-dimensional parameter space.Kevin J. Wischnewski (21354521)Florian Jarre (2902498)Simon B. Eickhoff (8355852)Oleksandr V. Popovych (7866194)BiophysicsMedicineGeneticsNeuroscienceSociologyBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedmathematical challenges originatingcoupled phase oscillators103 parameters simultaneouslysimulated functional connectivitydimensional parameter spacesdimensional approaches unansweredexploring dynamical wholedimensional model fittingdimensional spacesmodel fittingdimensional casesparameter optimizationsdynamical wholemodel validationthoroughly documentedthereby optimizedsex classificationresults elucidatereliable togetherpractical benefitsphenotypical datamodeling resultsindividual variabilityimproved considerablyempirical databayesian optimization272 subjects<p>Boxplots illustrate the distributions of the values for the optimal <b>(A)</b> delay , <b>(B)</b> coupling , <b>(C)</b> noise intensity , <b>(D)</b> goodness-of-fit (GoF) and <b>(E,F)</b> frequency parameters found in 30 executions (with random initial data) of the CMAES algorithm for one subject. The considered modeling quantities are indicated in the titles of each plot, while their considered ranges are given on the vertical axes. Plot <b>(E)</b> shows the first half of the frequency parameters, belonging to the brain regions in the left hemisphere in the Schaefer atlas, and <b>(F)</b> shows the second half, which represents the right hemisphere. This figure was created with MATLAB R2021a (<a href="http://www.mathworks.com" target="_blank">www.mathworks.com</a>).</p>2025-05-13T23:51:37ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0322983.g002https://figshare.com/articles/figure/Example_of_the_results_of_the_model_fitting_in_the_103-dimensional_parameter_space_/29057978CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/290579782025-05-13T23:51:37Z |
| spellingShingle | Example of the results of the model fitting in the 103-dimensional parameter space. Kevin J. Wischnewski (21354521) Biophysics Medicine Genetics Neuroscience Sociology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified mathematical challenges originating coupled phase oscillators 103 parameters simultaneously simulated functional connectivity dimensional parameter spaces dimensional approaches unanswered exploring dynamical whole dimensional model fitting dimensional spaces model fitting dimensional cases parameter optimizations dynamical whole model validation thoroughly documented thereby optimized sex classification results elucidate reliable together practical benefits phenotypical data modeling results individual variability improved considerably empirical data bayesian optimization 272 subjects |
| status_str | publishedVersion |
| title | Example of the results of the model fitting in the 103-dimensional parameter space. |
| title_full | Example of the results of the model fitting in the 103-dimensional parameter space. |
| title_fullStr | Example of the results of the model fitting in the 103-dimensional parameter space. |
| title_full_unstemmed | Example of the results of the model fitting in the 103-dimensional parameter space. |
| title_short | Example of the results of the model fitting in the 103-dimensional parameter space. |
| title_sort | Example of the results of the model fitting in the 103-dimensional parameter space. |
| topic | Biophysics Medicine Genetics Neuroscience Sociology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified mathematical challenges originating coupled phase oscillators 103 parameters simultaneously simulated functional connectivity dimensional parameter spaces dimensional approaches unanswered exploring dynamical whole dimensional model fitting dimensional spaces model fitting dimensional cases parameter optimizations dynamical whole model validation thoroughly documented thereby optimized sex classification results elucidate reliable together practical benefits phenotypical data modeling results individual variability improved considerably empirical data bayesian optimization 272 subjects |