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31a42d93954389f236ae7ef8451f9c08866786ff0971d6aa4e60760280ec97a7 | Text | 178 | 13 | # Pretrain Roost
## Enviroment Set up
```sh
conda env create -f environment.yml
```
## Example of SSL
```sh
cd /path/to/pretrain_roost/
python roost-pretrain_config_ssl.py
``` |
911b859436e49f212652da4be39e9d1a79fe915f9b5229b412b33e22c3a5ed3f | Text | 181 | 2 | # ExSenescence
Analysis codes and documentations for "Unmasking the heterogeneities in transcriptomic and evolutionary trajectories of cell cycle re-engaging post-mitotic neurons".
|
df17a9ab0270be568e9f7b0cda738cc89dc61b461be0a0223fad3e39b1ac043f | Text | 190 | 3 | # FedEYE
This is the repository that contains source code for the [FedEYE: A Scalable and Flexible End-to-end Federated Learning Platform for Ophthalmology.](https://fedeye.aierchina.com/)
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1b16ed5c632311d6c22b8b3877a41db3f4a0a3fa38dd1c2d254dd4875f18dcff | Text | 208 | 5 | # BrainAveraging
Scripts and data files for Tlaie et al. 2023
You can use this scripts without any warranty.
I am not responsible for potential issues that may arise due to any malfunction of these scripts.
|
aba5dda15c4df6987772f93f36a1c7c7726031f6fcf3aaeac849c1473ed1b94d | Text | 208 | 2 | # opm_meld_simulations
Scripts to simulate the data and reproduce the figures from *Combining OPM and lesion mapping data for epilepsy surgery planning: a simulation study* (doi: 10.1038/s41598-024-51857-3).
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48c8ecea794c14b4c66f25fc46e122ab00838795d4a0322148d8812dd58c0633 | Text | 214 | 2 | # Xenoturbella_sc_atlas
Input data and code to reproduce analyses in Robertson et al. "Single cell atlas of Xenoturbella bocki highlights the limited cell-type complexity of a non-vertebrate deuterostome lineage "
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8be3114bee9143df94e01bbd415fc9a873ab4e74443e9c0615abbdc2c15448de | Text | 222 | 1 | This repository contains analysis code and pre-processed data for the following paper "Accelerated epigenetic age is associated with whole-brain functional connectivity and impaired cognitive performance in older adults".
|
1fdcfdcc40e1ec5a979e43a1a14e5ad205702b053a951b28d115859c8cb52741 | Text | 224 | 14 | # neuronbridge-vol-viewer
Website incorporating @janelia/web-vol-viewer for direct volume rendering of neuronbridge matches
## Development
```
npm install
HTTPS=true npm run start
```
## Deployment
```
npm run deploy
```
|
5c9abeb0579bd36bac85520339bb9d641e6dc5fe839c77c9faf4b66e79d801ba | Text | 225 | 5 | # TeenScience
TennScience Platform
TennScience is a hardware and software platform based in Arduino and Teensy 3.6 for science research involving behavioral neuroscience, robotics, sound analysis, and more.
Testing Hardware
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cb145a792ee48561c59e4c027a73d21e273ec5d792236028c58d2a847c7988f7 | Text | 230 | 2 | R code used for analyzing the single-cell RNA-seq data for Royan et al., Photoperiod regulates gonadotrope cell division in medaka via melatonin, Tsh and folliculostellate cells.
BioRxiv https://doi.org/10.1101/2023.06.09.544159
|
1fe7cbcc130404bae6d5a4653a87806e41a52e9dc0c24ad2ad6b04cd1bc82944 | Text | 236 | 4 | This data is part of the OpenScience tera-PROMISE repository, a long-term hosting
solution for software engineering research data.
More information about this dataset can be found at http://openscience.us/repo/effort/cobol/miyazaki94
|
fc325b1fcbb1573ead66b6bb1c72166ae4bd67f4502c823091dcffd26464b9fd | Text | 240 | 4 | This data is part of the OpenScience tera-PROMISE repository, a long-term hosting
solution for software engineering research data.
More information about this dataset can be found at http://openscience.us/repo/effort/other-effort/maxwell
|
7d0b867ef0dc817a96b14e3dc03b87488c37289afb73a6c45c14bfeb8bac11df | Text | 246 | 4 | # DharmasriLevy-PNAS-2024
Code associated with "Differential nanoscale organization of excitatory synapses onto excitatory vs inhibitory neurons", Dharmasri, Levy and Blanpied et al. PNAS 2024
Please cite https://doi.org/10.1073/pnas.2315379121
|
b5846b124215498ecda74fd09294ffb4f2c94ba343dd7697b846898badcd01a9 | Text | 246 | 5 | # Audio forgery detection model sources (colab link)
learn model: https://drive.google.com/file/d/1Rgm8hVXivI2d0CkZ0cO8LVXcDfQlSOAm/view?usp=sharing
inference : https://drive.google.com/file/d/1vX6z-VBRDqSiAM2EANiFhgEJlfcOX-34/view?usp=sharing
|
528fab2c166cb773cf0a9c3c61effd1ad540d3a8d55bc9b435342ac429828987 | Text | 252 | 3 | # AngelikaZa-PoorOutcomeBiomarkersPD
This repository contains a jupyter notebook with all analyses code used in: Zarkali et al. Neuroimaging and plasma evidence of early white matter loss in Parkinson’s disease with poor outcomes, Brain Comms 2024.
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b49f0afbb737aedd6cafa59307913c3b7a73ec4e7d96002274c3db763de1e68b | Text | 254 | 6 | Files codification follows the nomenclature 'ANIMAL_RECORDINGDAY.mat'.
Control mice: 17511, 17531, 17532, 17551, 17552
EPO-injected mice: 17494, 17513, 17533, 17534
e.g. 17531_1.mat corresponds to the first day of recording of 17531 (Control) mouse.
|
f5afa85109df6346585f3042bcad9ee630d8c50b4b424ed6b60cd015880eacd1 | Text | 266 | 1 | This repository contains the analysis code for the manuscript ["A Latent Clinical-anatomical Dimension Relating Metabolic Syndrome to Brain Morphology - Evidence from a Multivariate Imaging Analysis of 40,087 Individuals"](https://elifesciences.org/articles/93246).
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96e216570c2e3126d39f8d09ac0c41d7f4ac63beb2bdc536ad668ada278f32dc | Text | 272 | 4 | # Bioresorb_MATLAB
Fully Bioresorbable Hybrid Opto-Electronic Neural Implant System for Simultaneous Electrophysiological Recording and Optogenetic Stimulation - MATLAB code
[](https://zenodo.org/doi/10.5281/zenodo.10581398)
|
2e4de37ab26a4aa682c61aeea20144fcf27ecf31b24eb4cf13974fe1d1fcceb2 | Text | 276 | 5 | # Speech-encoding
## About
Python codes used to analyse the representation of speech features in EEG signal.
Gonzalez JE, Nieto N, Brusco P, Gravano A, Kamienkowski JE (2021) Brain representation of acoustic features during goal oriented dialogue. JAIIO 50 Proceedings
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c772d2c9da1c9b57f89461ae43466ec8400a53df52764190c878a3d73d8233f9 | Text | 280 | 5 | # Szczepanska_2024_accompanying_data
Data accompanying "Pheromone-based communication influences the production of somatic extracellular vesicles in C. elegans" article.
[](https://doi.org/10.5281/zenodo.10718455)
|
62c79268cdcebd75e670182fc4a31078c520d6310eafb7a3b03e45f30fa6386d | Text | 296 | 3 | # ann_brain_alignment
code accompanying the article: Artificial neural network language models predict human brain responses to language even after a developmentally realistic amount of training.
the data for recreating the main figures are located at : [https://osf.io/](https://osf.io/6bd85/)
|
8f48fa91e9bc015522a59c2bfc7348ecac1dee2cdb89bc24cc655c677b27db82 | Text | 318 | 14 | [](https://zenodo.org/badge/latestdoi/490810361)
# neuronbridge-vol-viewer
Website incorporating @janelia/web-vol-viewer for direct volume rendering of neuronbridge matches
## Development
```
npm install
HTTPS=true npm run start
```
## Deployment
```
npm run deploy
```
|
6b94a009be54009541220a43b98ee46704cd28f6550b799701a0eed1815f8509 | Text | 320 | 2 | # In-season-cotton-yield-prediction-with-CNN-models
In season cotton yield prediction with CNN regression models and high-resolution UAV RGB images. Part of the code was uploaded here for demonstration. The journal is currenly under review. A fully modulized package will be uploaded here once the journal is published.
|
5c965215e71fcb8b23578a78d9e76dc169e44b319246d145e047417530dd58e5 | Text | 330 | 13 | # CR-for-Promoter
## Data from "Cell reports, 31, 107663"
CR-1: -7kbp to +3.5kbp
CR-2: -400bp to +400bp
CR-3: -200bp to +200bp
CR-4: -144bp to +56bp
CR-5: -112bp to -12bp
CR-6: -92bp to -42bp
CR-7-G: +17~+35bp (DPR in core promoters)
## Data from "Nature, 585, 459-463"
CR-7-S: +17~+35bp (DPR in core pro... |
057968394ba10e5219b5e165a2cf2e8ca3074e173b9eb7db4ca663694789c1f6 | Text | 336 | 4 | # About
This model, created by Z. Huang, was intricately crafted to specialize in the analysis of ECG data, with a primary focus on detecting cardiac abnormalities
### Efficient Edge-AI Models for Robust ECG Abnormality Detection on Resource-Constrained Hardware ([Paper](https://link.springer.com/article/10.1007/s1226... |
fbad5bf71b3dd2f5d5d37b394cf4494babdb4b3423a1f796e2a5fe58b85baa4b | Text | 336 | 5 | # Network topology of the marmoset connectome
This repository contains processing scripts in support of the paper:
Liu, Z.-Q., Zheng, Y.-Q., & Misic, B. (2020). Network topology of the marmoset connectome. _Network Neuroscience_, _4_(4), 1181–1196. [https://doi.org/10.1162/netn_a_00159](https://doi.org/10.1162/n... |
ecec46ed19a71f07fdf4cad70e36f828ade8c3ca358f42ffa52e945506822292 | Text | 339 | 5 | # reidentification-simulations
Simulations of classification accuracy for reidentification as a function of population size, for Jwa et al. manuscript.
The primary analyses are found in Classification_by_Population_Size.ipynb. The results can be visualized via [this web site](https://poldrack.github.io/reidentificat... |
e566878f094811d05d251cf00447ae14dd1e55f7a68af3e28934034838b4dd19 | Text | 348 | 2 | # Ruggiero-eLife2024
This repository contains the code used to perform the analyses and generate the figures presented in the paper titled "Dysfunctional Hippocampal-Prefrontal Network Underlies a Multidimensional Neuropsychiatric Phenotype following Early-Life Seizure", published in eLife (https://elifesciences.org/re... |
f75107a6fb7719fac38f7b3dbefb27f8218127ab85fcaef94655b2ee2a893f6a | Text | 349 | 2 | # Conjunctive-encoding-of-exploratory-intentions-and-spatial-information-in-the-hippocampus
This repository contains code for analysis and representative data for the manuscript Conjunctive-encoding-of-exploratory-intentions-and-spatial-information-in-the-hippocampus. You are required to use the Matlab program (The Mat... |
d2d21676eed97e088983b7e9e62c08a892565bf3677863b7088883e7a9718373 | Text | 352 | 1 | This repository contains code for the paper "Dendritic morphology affects the neuronal excitability type and the network state", Gowers and Schreiber (2024). All data used for the figures as well as the figures themselves can be generated using the scripts contained within the repository. Python and Julia requirement... |
edd07ea560bf5234ffddcf61ec99cb582d596538390f851863da2a2a293d3b01 | Text | 358 | 5 | # ROI-tSSS
Implementation of the tSSS algorithm for brain regions of interest
For a good place to start I would suggest going through the function rsquared_phantom. This will require the SPM toolbox and the SPM DAiSS toolbox. Phantom data can be downloaded here: https://figshare.com/articles/dataset/phantom090715_Brai... |
a4c3f8bbe2f14e50883bdb035a0e7c11a5f6b9c7893bff783ea096f1119b1b96 | Text | 361 | 3 | Any .csv file starting with 'SPK' represents a two-column file containing the neuron's ID in the first column and its corresponding timestamp in seconds in the second column.
Other .csv files beginning with 'WS' denote the wheel speed for a specific recording. The first column represents time, and the second column re... |
8057b1e9c46c09828a73b52cbc79dc3c57eaac04f8dae3d251cef06eeaf5d359 | Text | 362 | 4 | This is the dataset for Barglazan, Adrian-Alin, Remus Brad, and Constantin Constantinescu. 2024. "Image Inpainting Forgery Detection: A Review" Journal of Imaging 10, no. 2: 42. https://doi.org/10.3390/jimaging10020042
The link to the first version of the dataset is here: https://drive.google.com/drive/folders/12PETdZ... |
20ccdea4ea4ca7b3581ad2f02ee7539f998f9724c52d4baff6750b1abbf6d6cf | Text | 368 | 11 | ### TransPTM
A Transformer-Based Model for Non-Histone Acetylation Site Prediction
Welcome to the TransPTM project!
### Dataset
The dataset provided in this repository includes the data used for training and evaluating TransPTM.
### Coming Soon
We are currently upgrading and refining this work. The full codebase and... |
7b02c8752594a9a202bdaffd054b33bb53aefda28a206ac10555198a5b43c9ec | Text | 369 | 7 | # perlmann_lab_eLife2024
## Article Title: Transcriptomic atlas of midbrain dopamine neurons uncovers differential vulnerability in a Parkinsonism lesion model
### you can find the paper at: https://doi.org/10.7554/eLife.89482.2
### Code for reproducing datasets & plots in Yaghmaeian Salmani et al. eLi... |
afa4f4e98a7534ff4975d3282ab4a0ccf456994f851fb0979ee481d3edb9a940 | Text | 380 | 5 | # Hill2023Code
This is analysis code and raw data that is used in the paper "Feedforward and feedback mechanisms cooperatively regulate rapid experience-dependent response adaptation in a single thermosensory neuron type", Authored by Tyler Hill and Piali Sengupta
Includes Calcium/FlincG3 imaging code and behavioral ... |
c463eb4c9c80844da42c84b6dc86b734ee8f312c03d38582b2683eaee9ac9df7 | Text | 383 | 7 | # Top-down-modulation-with-iSTP
This repository contains the code from the publication:
Waitzmann F, Wu YK, Gjorgjieva J (2024) Top-down modulation in canonical cortical circuits with short-term plasticity.
We provide the code for each (sub)figure and supplementary (sub)figure from the publication seperatly. Runnin... |
283cb92c19f55b433cbb7ca19510c6d08f71fb567610bc3741e9cd22ce606ab8 | Text | 384 | 7 | # Obesity_maps
Scrtips to extract and analyse data for the project 'Neural correlates of obesity across the lifespan"
- Jupyter: Scripts written in jupyter notebooks for python and R; includes data extraction and data analysis
- MATLAB: matlab scripts for PLS analyses and extraction of significant genes
- Plotting: s... |
30956967c5d4747800003b2d97254757f91f6e0a6799d104e2cc297cdb7db65b | Text | 390 | 5 | # Nutil-To-Usable
Please read the N2U protocol if it is your first time using the app as it will guide you step by step in how to use the app. It will also provide descriptions on the more specific/confusing elements so please refer to it if you get lost.
This app is also hosted as a Shiny application at the followin... |
892a843c2bb75987173dfdfecb6ea3da9d200adaea064cf8d3e98775d5da52d7 | Text | 416 | 1 | This repository is related to the paper by "Ensemble dynamics and information flow deduction from whole-brain imaging data" by Toyoshima et al (2024), (doi://10.1371/journal.pcbi.1011848). Please cite this paper if you use the codes and resources. The dataset and resources relevant to this code will be found in the fig... |
0a8c9cecdcfa4d06450824fe405fabf0823a679dacfa08d308da734f6f794f87 | Text | 421 | 6 | # dHPC-NAc
Repository containing code for [Barnstedt et al., Nature Communications (2024)](https://www.nature.com/articles/s41467-024-47361-x)
All notebooks relate to individual figures or parts of figures of the accompanying manuscript. Source data can be downloaded from https://zenodo.org/doi/10.5281/zenodo.1069856... |
cb9aa9fa2f710fb7b4e02161f4bfddecfd07a7ac40e7a72b6937fdbb49a9953e | Text | 441 | 4 | # LSTM-based-Short-Term-Wind-Power-Forecasting
In this study, an advanced version of RNN known as Long Short-Term Memory (LSTM) networks is used for wind power prediction. This implementation contains stacked LSTM and bidirectional LSTM models for short term (hour a head) wind power forecasting.
Supported Python vers... |
2e9ac18d1bb8114e871a8cdb6088eef9e9ec3650b6959ad9a5fd5a250f1d8f1e | Text | 446 | 5 | # Optimal-reaching
Code for paper "Optimal reaching subject to computational and physical constraints reveals structure of the sensorimotor control system."
## Citation:
P. Greene, A.J. Bastian, M.H. Schieber, & S.V. Sarma, Optimal reaching subject to computational and physical constraints reveals structure of the sen... |
bd71eed66b442ba949b6332634836c856534b332aba7f2b0e70ad6599fe61c22 | Text | 448 | 3 | # CerebellarPurkinjeRFplasticity
Here we provide the source code for the paper "Intrinsic and synaptic determinants of receptive field plasticity in Purkinje cells of the mouse cerebellum". The codes are written in MATLAT R2021b, and used to analyze the data published in Zenodo repository: [https://doi.org/10.5281/zen... |
e81621b197e4bbd9539163e6248dbc3f716251d85ead7ef656f716c64cbd9e88 | Text | 448 | 7 | # AD Rapid Progression Prediction
**Manuscript title:** Deep learning to predict rapid progression of Alzheimer’s disease from pooled clinical trials: A retrospective study
**Autors:** Xiaotian Ma*, Madison Shyer*, Kristofer Harris, Dulin Wang, Yu-Chun Hsu, Christine Farrell, Nathan Goodwin, Sahar Anjum, Avram S. Buk... |
c279dfdf1efc5f82a949fd54ac54fb5a3cd550cdd91a38df62811982f8fba7af | Text | 449 | 6 | # wopodyn: Worm Pose Dynamics
Scott Sterrett | University of Washington
This repository contains code to reproduce analyses from ["Dimensionality of locomotor behaviors in developing *C. elegans*"](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1011906) as well as helpful tutorials to run simil... |
537ee2ab789930dc7d0db1754f2e53cb85474a57b3ce32d9c117d0c673824c49 | Text | 459 | 9 | A repository of MATLAB class definitions to create and analyse hierarchical object structure from .abf files generated with PCLAMP. To get started, see xExampleScript.m and explanatory comments in the class definitions.
Update April 2019:
Added support for NWB (Neurodata without borders, see: https://neurodatawithout... |
aa8efa1491c729e3c4e924d0d7749a01dbb44f5a1aa330b7b44be23d9d1c8438 | Text | 465 | 15 | ## Synthesise Learning Space
Synthesise is a web-based _learning space_. The application is optimised for blended learning scenarios and built upon modern web technologies.
### Installation
Just fork this GitHub repository, run `composer update`, `yarn` and configure the `.env` file(s).
### Deploy
There is a Deplo... |
2fa53e448ab722d2622e90c5db23d151b8bb7e281414f447a883ef53c2cf8e7a | Text | 467 | 12 | # MN-MD
These are data and original codes for two color fiber photometry for MN to MD projection during transition from SWS to wake
# Code author
Wooyeon Shin
Please cite as:
Anna Shin, Seahyung Park, Wooyeon Shin, Jeonghoon Woo, Minju Jeong, Jeongjin Kim, and Daesoo Kim, "A brainstem-to-mediodorsal thalamic pathway... |
13e9ad497dccbff3c189b990cfd99511afa8d63bc06c3bc652cc345231165ada | Text | 490 | 6 | # Emergence of Brain-Like Mirror-Symmetric Viewpoint Tuning in Convolutional Neural Networks
This repository contains the source code for our research paper published in eLife. For a detailed explanation of the methodologies, findings, and implications of our study, please refer to the paper.
**Paper Title:** Emergen... |
48b216873f0c32717d612d1bc6b4078df71cf08c66f5fa842ffea70026c88134 | Text | 495 | 6 | # ObjectCounter
This application takes outputs from the QUINT workflow and counts up the objects and sums the region area for certain mouse brain regions. There is not a detailed protocol for this app, but it functions quite similar to the begining of N2U whcih is another application that has a github page and protoco... |
08996ec40eabcc8561ec60ccdb05af22cba1e8c1c4153af2370211f51caeba1e | Text | 496 | 9 | # deepcellcontrol
`deepcellcontrol` is a package for deep learning-based feedback control of
gene expression in single cells. See our manuscript for more details:
[Lugagne J-B, Blassick CM, & Dunlop MJ (2022) Deep model predictive control of gene expression in thousands of single cells. _bioRxiv_](https://www.biorxi... |
9e179c3f03aa205c8bb957feddc309072a13f1d5a5595a46ab36f0fbf6d2844e | Text | 499 | 15 | # CTH-Net
## Datasets
1. ISIC 2016 : https://challenge.isic-archive.com/data/#2016
2. ISIC 2017 : https://challenge.isic-archive.com/data/#2017
3. ISIC 2018 : https://challenge.isic-archive.com/data/#2018
4. PH<sup>2</sup> : https://www.fc.up.pt/addi/ph2%20database.html
## Experiments
* CUDA/CUDNN
* torch >=1.7.0
## R... |
0665bb385e93ed0d7dff49aaa43289f57c52adcf2575e2fd330b4b18dfa0e941 | Text | 504 | 8 | # Brain_Network_analysis
R tools to analyze correlation networks from microscopic brain imaging
The code can build networks based on the output data from ClearMap ,
or from independent data.
It includes codes to capture network global general features, modularity,
detect community structures based on consensus clusteri... |
84de1b1b8bd3c5d616cb686401bea516c83cd9a6a3f9fb6dabfed72bce2b129a | Text | 506 | 10 | # Parvafox-eLife-2024
This repository contains custom written code genereated for the analysis associated with the following publication:
https://doi.org/10.7554/eLife.86737.1
Raw data used together with the scripts in these depositories are available on Dryad under the following identifier:
https://doi:10.50... |
6dc31a8144b06581f5d4f0a599b20e4d803c0ca877ecb8f4a6f2f16c1c5c12d1 | Text | 517 | 6 | # Utility_Models 1.1.0
MATLAB functions for fitting intertemporal choice (ITC; aka delay discounting) models or risky choice models to choice data.
Generally, running single parameter models are recommended (e.g., exponential or hyperbolic ITC models, or all risky choice models).
Two-parameter models, such as the gene... |
ae42181003f2b44c27280bb77977c7261e2e208721fe8c54ac32f608c564a5b3 | Text | 526 | 4 | # Neural-correlates-of-perspective-taking-at-age-4
This EEG data analysis pipeline was written to process EEG data of a study on neural correlates of perspective-taking in 4-year-old children by Marlene Meyer, Natalie Brezack and Amanda L. Woodward. The analysis was geared towards spectral analysis of the theta frequen... |
4ad47c3be5862385b38960c106d483a2b1d8deecd67a088d25ecc3d056d305d7 | Text | 533 | 8 | # Goes_CP_ASCL1_promotes_SCRT2_expression_in_the_neural_tube
Materials and Methods: Cellular Distance Calculation from the Neural Tube Center in In Situ Hybridization (ISH) Images
This repository contains:
1. Cellpose model to segment the cells in ISH images of neural tubes
2. CellProfiler pipeline to segment the ne... |
5afc5e453d6c67d56fd89e6f390f6b00ed7d0b0b465316b56a4e5cea4d30e3c4 | Text | 555 | 12 | # LFPReconstruction
CSD/LFP analysis and figures from https://www.biorxiv.org/content/10.1101/2023.05.25.541803v1
Package needed to run the code:
- kcsd (from https://github.com/Neuroinflab/kCSD-python)
- scipy >=1.9.1
- mayavi >=4.7.2 - just for visualization
- matplotlib >=3.5.2
- numpy >=1.21.5
To test the recon... |
746afdb45e783c76b87ee11abbe9781261ae67fd0ef9567e378924c4a0f5959d | Text | 557 | 8 | # Maternal dietary fat during lactation shapes single nucleus transcriptomic landscape of postnatal offspring hypothalamus in a sexually dimorphic manner
We have set up a web portal allows you to explore UMAP clustering and gene expression data of the pup hypothalamus at peak lactation(P15) on full dataset and neuron... |
ee5b2a831114764daec333449d8d6b2149334d4cdf5873f032bf72c3e4a8b224 | Text | 558 | 4 | # Optogenetics-Chamber
Arduino Code: This folder contains the code needed to be uploaded to the Arduino Uno in order for the Optogenetics Chamber to work properly. It contains detailed comments throughout the code about how you are able to custimize settings such as the LED light frequency and LED light wavelength with... |
92a9d3a5cbb212d830be38f99e2538e03e3f17999bb53afd3bad0a7f6fedbd46 | Text | 563 | 13 | # Bayesian functional analysis for untargeted metabolomics data with matching uncertainty and small sample sizes
R package for Bayesian Analysis for Untargeted Metabolomics data (BAUM) [https://academic.oup.com/bib/article/25/3/bbae141/7640737]. Please use the following code in R for installation. An example of using ... |
7a142a0ce9d24072c03a141c4b92fd666342d3691bf0d9c431beee49e4d1a5db | Text | 569 | 5 | This script is designed for analyzing electrophysiological signals from the mouse brain and examining c-Fos expression datasets across individual brain regions. The analyses include statistical comparisons with control groups, hierarchical clustering, functional network analysis, and the computation of centrality metri... |
638b2b0459cb44521fc360af950cc3c2f5fc77578d9f51468263080d9d696d76 | Text | 570 | 8 | # Supplemental CODE for CSFpulse calculation from EPI fMRI data
This code is used to process CSFpulse technique proposed to calculate the CSF pulsation using an EPI-based fMRI dataset.
Please cite the following reference if you use these codes:
Kim, J. H., Im, J. G., & Park, S. H. (2022). Measurement of CSF pulsation f... |
31daf4b31c41ee824f4dee6d9390b867de31473cea5e6902732e7abbad80a3cf | Text | 585 | 13 | # ShapeIllusion
Data and code associated with the manuscript "How small changes to one eye’s retinal image can transform the perceived shape of a very familiar object"
McLean, Erkelens, & Cooper PNAS (2024)
The assets are organized into two folders:
**MATLAB_Figures_and_data** contains the data from both studies and... |
b7ed611c46b08be6e125029c99d907d6228634d6f42e6c429dbf4ed44d6b2b72 | Text | 594 | 9 | # optoMCP-FUS
This project consists of a class "MinStack" and an example actuating code for MinStack, which enables TIF loading and particle detection/tracking, ran on MATLAB R2019b. Basically, this class is a reconstitution of following publically accessible codes:
*Reference:* (Particle detection/tracking)
Ian Hose... |
933e480e64e5124c5c19ff6f5d8d8e07c4dfe2dfef9e11474ab5beccccf9b1ac | Text | 599 | 32 | # VOR-model
Hannah Payne, Jennifer Raymond, Mark Goldman
<br />
## To plot existing results
Navigate to `~/VOR-model/src` in Matlab and run:
```
PLOT_MODEL('published')
```
## To run full model from scratch
Run the following to create a new folder `~/VOR-model/results/my_savename` with the results:
```
RUN_MODEL... |
dcb703abc5f78ad8ad731ab7fbc46d15db1a12d4712eb365aaef9b6b29312b2f | Text | 604 | 8 | An Adversarial Example Attack Method Based on Predicted Bounding Box Adaptive Deformation in Optical Remote Sensing Images
==
This code performs the experiments presented in our paper, An Adversarial Example Attack Method Based on Predicted Bounding Box Adaptive Deformation in Optical Remote Sensing Images. The code ... |
7c06064bf41a32cf303dac1b4b09a7dbfe152b62ed5a806f7304d2fb890f2143 | Text | 613 | 4 | # spatial-metaphors
The repository contains 8 CSV files, and two ipynb files with the code. Each file represents the dataset that was used for data analysis in the study. To run the code, you need to download each file and then run a code on your PC through an application applicable to Python e.g., Jupyter Notebook or... |
bac799439f831e31c81e84efd3271be6e7a3d50e8020eda80ebc1ea75ae5c29a | Text | 613 | 14 | # MOSTest-multimodal
## Collaboration project with NORMENT using MOSTest to explore multimodal brain genetic architecture
### Corresponding paper
> Tissink et al. (2024) Abundant pleiotropy across neuroimaging modalities identified through a multimodal multivariate genome-wide association study. bioRxiv, doi: 10.1101... |
b4752b13a72015ea94d43bb2eb37ecdfdf2134bd8b605598f523044b55be2a0b | Text | 614 | 23 | # Sensor Plots
Sensor Plots is a library of scripts for plotting common forms of data associated with genetic biosensors. This library takes a semi-automated approach. The data must be formatted into xlsx sheets that, when passed through the scripts, will automatically plot the data in a standardized format.
Plotting... |
a71f3c4aa6f9962dd3b89b6cc2d05571aa9ca3889f07575f5b6783f1a18ff29a | Text | 617 | 7 | This directory contains relevant codes and data used in "Visual perceptual learning of feature conjunctions leverages non-linear mixed selectivity,
Behnam Karami & Caspar Schwiedrzik, npj science of learning 2024".
It contains the data (look at README_DATA for more info), figures_code (used to generate the figures... |
d8c6feb2870af3ffd42641122434584737c96b63ccafe1d51ed7f20202961697 | Text | 617 | 16 | # eLife_Grid_anchoring_2024
Code for reproducing plots in Clark and Nolan 2024
In order to run the code:
(1) Clone the in_vivo_ephys_openephys (https://github.com/MattNolanLab/in_vivo_ephys_openephys/) repo that contains all code for preprocessing and spike sorting
(2) Clone eLife_Grid_anchoring_2024
(3) Move eLife... |
db38243f6a6a989804ae5988fc00c67b60c9b53b604323c6f331611b3efa07a3 | Text | 620 | 9 | # Gait-Analysis-of-Freely-Walking-Mouse
Analysis script for Long et al. project on striatal neuron phase-locking to the gait cycle.
To replicate data figures from the project:
First, download the script from here and the processed data in pickle files by going to the website: https://zenodo.org/record/8303087
For exam... |
ee895153a34058a13bd6f8877f0fb7430dcd5cc8531b402d5c59ad50a4986fd1 | Text | 620 | 14 | # RetinalSampling
Explore primate visual cortex principles. Repository is linked to the paper "Unlocking the Primate Visual Cortex Secrets," objectively analyzes eccentricity, spatial frequency, and radial bias.
All stimuli necessary for conducting the experiments are accessible on OSFHome (https://osf.io/r62j7). Plea... |
7630e8e532d8033a88d34033495bd3955a9b8bdce126dd3fa73cb6d734e3b0ff | Text | 624 | 8 | # Hemispheric Brain Age
Brain asymmetries from midlife to old adulthood and hemispheric brain age
##Overview of files:
1) code (all code used for analyses and plotting is available including global and regional feature analyses, linear and non-linear modelling, model comparisons and associations, as well as sex strati... |
9dd7b0352991b6e4e59af44dbe519c4d058e04c565f239f02a64b935c0e30478 | Text | 638 | 25 | # mesoscope_spontaneous
These files are associated with the following paper (PLEASE CITE - now online both at bioRxiv and as a reviewed preprint at eLife):
bioRxiv:
doi: [https://doi.org/10.1101/2023.10.19.563159]
eLife reviewed preprint:
[https://doi.org/10.7554/eLife.94167]
Publicly available datasets at FigS... |
94c1ce85a58e9a49e3b8443a4d4ce4dee8e009c0b88d75499900641f26007d74 | Text | 643 | 23 | ## MatAL
Codes for "Machine Intelligence-Accelerated Discovery of All-Natural Plastic Substitutes".
### Python environment & JupyterLab setup
```python
cd MatAL
conda env create -f environment.yml
conda activate matal-py10
jupyter lab
```
### Notebooks:
- ```design_boundary.ipynb```: Feasibility design boundary
... |
df40b61a31f18348a5c3f8c1cb5bc4168b9b92c24665652b0930098c692303f1 | Text | 648 | 22 | # npc
Data and Code for Neural Population Control
Data is available at:
https://s3.amazonaws.com/npc-v4-data/npc_v4_data.h5.zip
View [here](notebooks/example.ipynb) for an example code snippet.
# Refernce
If you are using data or code from this repository please refer to our publication:
@article{bashivan2019... |
045a1b5ab4a7ae56813994a2f89e95f94ed563e971a8a2f1529b1ef988dfa0d5 | Text | 671 | 20 | # Seg2Data
Implementation of parallel measuring of segmented nerve fiber morphology.
# Data2Reg
Implementation of SVM for identifying changes in morphology related to stimulation level.
## Installation
To install all necessary packages simply run:
```shell script
pip install -r requirements.txt
```
## Usage
Exampl... |
e37f7c1fd94d04e5f70c97605c1e4537545ef8384e9985d4bdb950306a2c74c2 | Text | 671 | 10 | This includes the code used for the following manuscript:
**Adaptive introgression reveals the genetic basis of a sexually selected syndrome in wall lizards**
Nathalie Feiner, Weizhao Yang, Ignas Bunikis, Geoffrey M While & Tobias Uller
The folder **R_scripts** contains mostly code that was used to analyse phenotyp... |
1ec466bb6840e4e4dfd1512bb1ce8b0f05ae86263db5931e80a115d1f209d570 | Text | 674 | 14 | [](https://zenodo.org/doi/10.5281/zenodo.10634731)
# hagen reproducibility
## Manuscript, code and data
hagen is available as a preprint on bioarXiv and the software package can be found [here](https://github.com/theislab/hagen).
## Navigating this repository
We've org... |
946bd04d7acddf333902e2a4af0267342c32e0c75d8afa5356f3148f214e42b6 | Text | 683 | 16 | # eLife_Grid_anchoring_2024
Code for reproducing plots in Clark and Nolan 2024 (eLife2024;12:RP89356 DOI: https://doi.org/10.7554/eLife.89356.3)
In order to run the code:
(1) Clone the in_vivo_ephys_openephys (https://github.com/MattNolanLab/in_vivo_ephys_openephys/) repo that contains all code for preprocessing and ... |
33c43a248b0a3fee647eacb6a4d86c53dc2827a6e8e48640ed4a0f57ad13d623 | Text | 687 | 13 | # avalanche
Code Authors: Mia Morrell and Audrey Sederberg
Code for analysis of avalanche statistics and calculation of information for "Neural criticality from effective latent variable."
# python_simulation_code
Scripts for simulations that were run for this paper. Uses package 'placerg' for simulations.
# matl... |
ce831817e1144e9bca224c3d1c6848ae22bd8a9cb3c3089d04210d18e2d1af1b | Text | 708 | 13 | # NeuronBridge Precompute Scripts
[](https://github.com/JaneliaSciComp/neuronbridge-backend)
[](https://github.com/tischfieldlab/moseq-reports/actions/workflows/build.yaml)
## Project setup
```
git clone https://github.com/tischfieldlab/moseq-reports.git
cd moseq-reports
npm install
```
### C... |
73c03fcb0ba0e37841b3045fab4526cb37e43da7d80dcd5e7d00aa3a454e675a | Text | 721 | 18 | # FedEYE
This is the repository that contains source code for the [FedEYE: A Scalable and Flexible End-to-end Federated Learning Platform for Ophthalmology.](https://fedeye.aierchina.com/)
Project page: [https://www.bj-yan.top/FedEYE/](https://www.bj-yan.top/FedEYE/)
## Citation
If you find this work useful in your... |
34bc4f2d065754945dd03b55aa9ec46cc8cbda1b0c2b483bae30edda3749fb52 | Text | 734 | 11 | # ABCD-mTBI
R syntax for the processing and analysis of data for the manuscript "Executive functioning, behavior, and white matter microstructure in the chronic phase after pediatric mild traumatic brain injury: results from the adolescent brain cognitive development study" published in Psychological Medicine (https:/... |
f2e81604ecdf2a03bfd37469be774a80ee0fbc0b172453075c16028a4e1b6c0b | Text | 734 | 33 | # STAMovieMaker
This software generates stimulus triggered average movies and images for a variety of stimuli and imaging types.
## User interface
## Examples
<b>Widefield retinotopy</b>
</br>
<img src="/utils/stim1.gif" alt="widefield retinotopy">
<b>Orientation m... |
0e061a1bfe8308d98da832f02d7e2616e02aeeacd6439dcdeaea7c86eba02134 | Text | 743 | 13 | 1. using Flybox or camera to record flie's locomotion (1s / frame)
2. input the "recording data" and "image_stack.ijm" in imagej (The number of pictures must be a multiple of 24)
3. click run (approximately 1.5 hours ending)
4. Export the "output image" as video or "jpg" using imageJ
1. install opencv (https://pypi.or... |
7717da314cd3b7cd8531f27c8bf459640097ae9664f4dacbb41b057ab95f0ec0 | Text | 743 | 16 | ## Context-Aware Deep Learning Enables High-Efficacy Localization of High Concentration Microbubbles for Super-Resolution Ultrasound Localization Microscopy
**Example code for LOCA-ULM simulation pipeline**
Context-Aware Deep Learning Enables High-Efficacy Localization of High Concentration Microbubbles for Super-Res... |
bd902f7bfef2f7082b1d9dcaf0d275f64d71f02202e760004d17de118f87a082 | Text | 778 | 12 | # README #
DBDNMF: A Dual Branch Deep Neural Matrix Factorization Method for Drug Response Prediction
## Instructions ##
main_ccle_kfold.m：DBDNMF for predict CCLE drug prediction(kfold cross-validation)
main_gdsc_kfold.m ：DBDNMF for predict GDSC drug prediction(kfold cross-validation)
main_ccle_ger_kfold.m：DBDNM... |
b57af0f6b1e9379b9990b7f91e90abf11a85e5a00a81c3bec365c5551a8928a5 | Text | 780 | 11 | # NattComms_RCode
This GitHub repo contains all the code used to analyse the data of the Nature Communications paper "Identification of gene regulatory networks affected across drug-resistant epilepsies" (François, Romagnolo et al. (2024)).
- Scripts S01.. detail the module construction and annotation by pathology
- ... |
a8142f9625488deb85d49a7c2c4c86875bdf1492b40e5b2602e603163c25a4c6 | Text | 781 | 21 | # Random Boolean Network Model
This is a model of a Random Boolean Network (BRN) reservoir, with input and readout.
The folder `simulation` contains four jupyter notebooks to reproduce the experiments performed in the following [article](https://manuneuro.github.io/EmmanuelCalvet/assets/publications/2023-12-01_artic... |
cec41f3cd75f840bbccf4604d693a734a2be20bc977f35fe00513d04b51e98e8 | Text | 781 | 15 | ## Context-Aware Deep Learning Enables High-Efficacy Localization of High Concentration Microbubbles for Super-Resolution Ultrasound Localization Microscopy
**Example code for LOCA-ULM simulation pipeline**
Context-Aware Deep Learning Enables High-Efficacy Localization of High Concentration Microbubbles for Super-Res... |
507244155e479ab7a4af514ba187583b4bbeae707d478bc31eea86e5fb0d1738 | Text | 786 | 18 |
## Functional Connectivity Development along the Sensorimotor-Association Axis Enhances the Cortical Hierarchy
**Study preregistration**: [https://osf.io/vf8ew](https://osf.io/vf8ew)
**Preprint**: [https://www.biorxiv.org/content/10.1101/2023.07.20.549090v1](https://www.biorxiv.org/content/10.1101/2023.07.20.549... |
1e327b12ffd0928aeb0a328d1bd9930d1450e2c29c911b93f99558fc9cd6d1fa | Text | 803 | 14 | # NeuronBridge Precompute Scripts
[](https://zenodo.org/badge/latestdoi/380281044)
[](https://github.com/JaneliaSciComp/neuronbridge-backend)
[](https://doi.org/10.5281/zenodo.10932778)
## Installation Instructions
The package "pyRASP" (written in support of [this paper](https://doi.org/10.1021/acs.jpcb.4c00174)) is a set of python classes that can be run from scripts, interactive notebooks... |
65c205ac4b16b4d5de82ad920a82f0638e80529e9ec0465b2084dbb331262f61 | Text | 841 | 1 | subj_id := subject id, session := number of session (1-4 for training, 5 for transfer session), orientation := presented stimulus orientation (CC for counter-clockwise and CL for clockwise in respect to the reference stimulus), difficulty := relative stimulus angle (level1 := smallest angel (hardest condition), ..., le... |
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