التفاصيل البيبلوغرافية
| العنوان: |
Application of the recommended analysis pipeline to three sets of real neural recordings. |
| المؤلفون: |
Ege Altan (11768156), Sara A. Solla (8163024), Lee E. Miller (11768159), Eric J. Perreault (11768162) |
| سنة النشر: |
2021 |
| المجموعة: |
Smithsonian Institution: Digital Repository |
| مصطلحات موضوعية: |
Neuroscience, Pharmacology, Biotechnology, Mathematical Sciences not elsewhere classified, Information Systems not elsewhere classified, specific function controlled, massive redundancy implies, several representative algorithms, linear algorithms overestimate, manifold underlying multi, nonlinearly embedded data, neural activity within, analyzing neural activity, important challenges associated, denoising algorithm based, algorithms &# 8217, dimensional manifold within, known intrinsic dimensionality, neural activity, population activity, many algorithms, intrinsic dimensionality, dimensional recordings, algorithms overestimated, algorithms failed, &# 8220, free data, experimental data, available data, %22">xlink "> |
| الوصف: |
The parallel analysis (PA) estimates of the dimensionality are shown for each of the datasets J1, J2, and J3. These values determined the dimensionality to be used for denoising each dataset. The PCA-based denoising yielded reconstructions with 53%, 51%, and 56% VAF. The JAE-based denoising was slightly better for all datasets, with 61%, 59%, and 62% VAF. The better performance of the JAE-based denoising is indicative of modest nonlinearity in all three datasets. Once each dataset had been denoised using JAE, the corresponding dimensionalities were estimated using MLE and TNN. These results motivated our choice of d = 6 for the intrinsic dimensionality of most of our simulated datasets. (DOCX) |
| نوع الوثيقة: |
article in journal/newspaper |
| اللغة: |
unknown |
| Relation: |
https://figshare.com/articles/journal_contribution/_Application_of_the_recommended_analysis_pipeline_to_three_sets_of_real_neural_recordings_/17096228 |
| DOI: |
10.1371/journal.pcbi.1008591.s001 |
| الاتاحة: |
https://doi.org/10.1371/journal.pcbi.1008591.s001 |
| Rights: |
CC BY 4.0 |
| رقم الانضمام: |
edsbas.7EA5BFBB |
| قاعدة البيانات: |
BASE |