Source code and dataset for paper: Content-related neural representations in the motor cortex facilitate handwriting skill transfer across different effectors
Fuente:
Zenodo
Salvato in:
| Autore principale: | |
|---|---|
| Natura: | Recurso digital |
| Pubblicazione: |
Zenodo
2026
|
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866901287655702528 |
|---|---|
| author | Xiong, Xinzhu |
| author_facet | Xiong, Xinzhu |
| contents | <div> <div>## **Source code and dataset for paper**: *Content-related neural representations in the motor cortex facilitate handwriting skill transfer across different effectors*</div> <br> <div>### **Instructions for Users**</div> <br> <div>### 1. **Dataset** </div> <div>This repository includes two datasets: one for trajectory analyses with healthy participants (located in the **trajectory_analyses** folder), and another for neural analyses, containing invasive brain signals recorded from the left motor cortex of a paralyzed participant (located in the **neural_analyses** folder).</div> <br> <div>- **trajectory_analyses->data**</div> <br> <div> Contains handwriting samples from five healthy participants, each writing three target words using five effectors. The effector abbreviations are as follows:</div> <div> - *'a'* - *'Arm-dominant writing'</div> <div> - *'w'* - *'Wirst-dominant writing'*</div> <div> - *'f1'* - *'Index finger-dominant writing'*</div> <div> - *'f2'* - *'Middle finger-dominant writing'*</div> <div> - *'f3'* - *'Ring finger-dominant writing'*</div> <br> <div>- **neural_analyses->data**</div> <div> </div> <div> Contains invasive neural signal recordings from each session. Two types of data files are provided:</div> <br> <div> - `***-binned-normalized-smoothed-aligned-writing.mat`:</div> <div> </div> <div> Used for all neural analyses except population-level neuronal modulation computation.</div> <div> - `params` - Basic session information.</div> <div> - `spikeunit_***` - Used for plotting the waveform of every single unit (not used in the paper).</div> <div> - `target_label` - Specific movement corresponding to each trial label. A total of 12 movements were executed.</div> <div> - `trial_bin_spike` - Raw neural signals with dimensions $K\times T\times N$ ($K:$ number of trials, $T:$ time bins, $N:$ number of neurons).</div> <div> - `trial_target` - Trial labels, dimensions $1\times K$.</div> <div> - `trial_bin_fr` - Preprocessed neural data (same dimensions as `trial_bin_spike`).</div> <div> - `number_target` - Labels for writing the same content across different effectors.</div> <div> - `effector_target` - Labels for using the same effector across different writing contents.</div> <br> <div> - `***-rest-trial-data.mat`</div> <div> </div> <div> Used for computing population-level neuronal modulation. Fields retain the same meanings as above, with the following additions:</div> <div> - `condition_neural` - Same as `trial_bin_fr`.</div> <div> - `rest_neural` - Neural signals during the 'do nothing' condition, dimensions $N\times T$.</div> <br> <div>### 2. **Trajectory Analyses** </div> <div>Code for trajectory analyses is located in the **trajectory_analyses** folder. Run `statistical_comparison.ipynb` directly to proceed with the analysis.</div> <br> <div>### 3. **Neural Analyses** </div> <div>Code for neural analyses is located in the **neural_analyses** folder. Run `main.m` to begin analysis.</div> </div> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18171227 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Source code and dataset for paper: Content-related neural representations in the motor cortex facilitate handwriting skill transfer across different effectors Xiong, Xinzhu <div> <div>## **Source code and dataset for paper**: *Content-related neural representations in the motor cortex facilitate handwriting skill transfer across different effectors*</div> <br> <div>### **Instructions for Users**</div> <br> <div>### 1. **Dataset** </div> <div>This repository includes two datasets: one for trajectory analyses with healthy participants (located in the **trajectory_analyses** folder), and another for neural analyses, containing invasive brain signals recorded from the left motor cortex of a paralyzed participant (located in the **neural_analyses** folder).</div> <br> <div>- **trajectory_analyses->data**</div> <br> <div> Contains handwriting samples from five healthy participants, each writing three target words using five effectors. The effector abbreviations are as follows:</div> <div> - *'a'* - *'Arm-dominant writing'</div> <div> - *'w'* - *'Wirst-dominant writing'*</div> <div> - *'f1'* - *'Index finger-dominant writing'*</div> <div> - *'f2'* - *'Middle finger-dominant writing'*</div> <div> - *'f3'* - *'Ring finger-dominant writing'*</div> <br> <div>- **neural_analyses->data**</div> <div> </div> <div> Contains invasive neural signal recordings from each session. Two types of data files are provided:</div> <br> <div> - `***-binned-normalized-smoothed-aligned-writing.mat`:</div> <div> </div> <div> Used for all neural analyses except population-level neuronal modulation computation.</div> <div> - `params` - Basic session information.</div> <div> - `spikeunit_***` - Used for plotting the waveform of every single unit (not used in the paper).</div> <div> - `target_label` - Specific movement corresponding to each trial label. A total of 12 movements were executed.</div> <div> - `trial_bin_spike` - Raw neural signals with dimensions $K\times T\times N$ ($K:$ number of trials, $T:$ time bins, $N:$ number of neurons).</div> <div> - `trial_target` - Trial labels, dimensions $1\times K$.</div> <div> - `trial_bin_fr` - Preprocessed neural data (same dimensions as `trial_bin_spike`).</div> <div> - `number_target` - Labels for writing the same content across different effectors.</div> <div> - `effector_target` - Labels for using the same effector across different writing contents.</div> <br> <div> - `***-rest-trial-data.mat`</div> <div> </div> <div> Used for computing population-level neuronal modulation. Fields retain the same meanings as above, with the following additions:</div> <div> - `condition_neural` - Same as `trial_bin_fr`.</div> <div> - `rest_neural` - Neural signals during the 'do nothing' condition, dimensions $N\times T$.</div> <br> <div>### 2. **Trajectory Analyses** </div> <div>Code for trajectory analyses is located in the **trajectory_analyses** folder. Run `statistical_comparison.ipynb` directly to proceed with the analysis.</div> <br> <div>### 3. **Neural Analyses** </div> <div>Code for neural analyses is located in the **neural_analyses** folder. Run `main.m` to begin analysis.</div> </div> |
| title | Source code and dataset for paper: Content-related neural representations in the motor cortex facilitate handwriting skill transfer across different effectors |
| url | https://doi.org/10.5281/zenodo.18171227 |