index.qmd

---
title: Video-based analysis of animal behaviour
subtitle: SWC/GCNU Neuroinformatics Unit
author: Niko Sirmpilatze, Chang Huan Lo, Sofía Miñano
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        theme: [default, niu-light.scss]
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        footer: "Sainsbury Wellcome Centre | 2024-10-03"
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links:
  course-webpage: "https://software-skills.neuroinformatics.dev/courses/video-analysis.html"
  gh-repo: "https://github.com/neuroinformatics-unit/course-behavioural-analysis"
  these-slides: "https://neuroinformatics.dev/course-behavioural-analysis/#/title-slide"
  dropbox: "https://tinyurl.com/behav-analysis-course-data"
  menti: "https://www.menti.com/"
  menti-link: "https://www.menti.com/aldg47maopsr"
  menti-code: "`5524 7145`"
papers:
  neuro-needs-behav-title: "Neuroscience Needs Behavior: Correcting a Reductionist Bias"
  neuro-needs-behav-doi: "https://www.sciencedirect.com/science/article/pii/S0896627316310406"
  quant-behav-title: "Quantifying behavior to understand the brain"
  quant-behav-doi: "https://www.nature.com/articles/s41593-020-00734-z"
  open-source-title: "Open-source tools for behavioral video analysis: Setup, methods, and best practices"
  open-source-doi: "https://elifesciences.org/articles/79305"
  moseq-title: "Mapping Sub-Second Structure in Mouse Behavior"
  moseq-doi: "https://doi.org/10.1016/j.neuron.2015.11.031"
  keypoint-moseq-title: "Keypoint-MoSeq: parsing behavior by linking point tracking to pose dynamics"
  keypoint-moseq-doi: "https://doi.org/10.1038/s41592-024-02318-2"
---

# Introductions

[Neuroinformatics Unit (NIU)](https://neuroinformatics.dev/){style="text-align: center"}

:::: {.columns}
::: {.column width="33%"}
![](img/niko_sirmpilatze.png)
Niko Sirmpilatze
:::

::: {.column width="33%"}
![](img/chang_huan_lo.png)
Chang Huan Lo
:::

:::{.column width="33%"}
![](img/sofia_minano.png)
Sofía Miñano
:::
::::

## Course materials

| **Slides** | [neuroinformatics.dev/course-behavioural-analysis]({{< meta links.these-slides >}}) |
|----|------|
| Webpage | [software-skills.neurinformatics.dev/course-behavioural-analysis]({{< meta links.course-webpage >}}) |
| GitHub | [github.com/neuroinformatics-unit/course-behavioural-analysis]({{< meta links.gh-repo >}}) |
| Data* | [tinyurl.com/behav-analysis-course-data]({{< meta links.dropbox >}}) |

::: aside
*Data produced and shared by [*Loukia Katsouri, O'Keefe Lab*](https://www.sainsburywellcome.org/web/people/loukia-katsouri)
:::

## Schedule: morning {.smaller}

| Time | Topic | Goals |
|----|-------|--------|
| 10:00 - 10:20 | Welcome | Introductions, troubleshooting |
| 10:20 - 11:00 | Theory: Quantifying Behaviour | What is behaviour, detection & tracking, pose estimation |
| 11:00 - 12:00 | Practice: SLEAP I | Label data, train models |
| 12:00 - 12:15 | Coffee Break | |
| 12:15 - 13:00 | Practice: SLEAP II | Evaluate models, run inference |
| 13:00 - 14:00 | Lunch break | |

: {.striped}

## Schedule: afternoon {.smaller}

| Time | Topic | Goals |
|----|-------|--------|
| 14:00 - 15:45 | Practice: movement | Load pose tracks into Python, clean and visualise data, compute kinematics |
| 15:45 - 16:00 | Coffee break | |
| 16:00 - 16:30 | Theory: From behaviour to actions | Approaches to action segmentation |
| 16:15 - 17:30 | Demo: Keypoint-MoSeq | Extract behavioural syllables |

: {.striped}

## Install software requirements {.smaller}

You were asked to pre-install two `conda` environments for the practical exercises. Check that you have them installed:

```{.bash code-line-numbers="false"}
$ conda env list
sleap
keypoint_moseq
```

::: {.fragment}
If you don't have them, you can create them as follows:

1. [**SLEAP**](https://sleap.ai/): Use the [conda package method](https://sleap.ai/installation.html#conda-package) from the SLEAP installation guide.
2. [**Keypoint-MoSeq**](https://keypoint-moseq.readthedocs.io): Use the recommended [conda installation method](https://keypoint-moseq.readthedocs.io/en/latest/install.html#install-using-conda).
:::

{{< include slides/quantifying_behaviour.qmd >}}

{{< include slides/SLEAP.qmd >}}

# Lunch break 🍽 {background-color="#1E1E1E"}

{{< include slides/movement.qmd >}}

# Coffee break ☕ {background-color="#1E1E1E"}

{{< include slides/from_behaviour_to_actions.qmd >}}
  
{{< include slides/keypoint_moseq.qmd >}}

# Feedback

Tell us what you think about this course!

Write on [IdeaBoardz](https://ideaboardz.com/for/course-behav-analysis-2024/5391792)
or talk to us anytime.

## Join the movement! {.smaller}

:::: {.columns}

::: {.column width="50%"}
![](img/movement_poses_schematic.png){fig-align="center" height="400px"}
:::

::: {.column width="50%"}
- Contributions to `movement` are absolutely encouraged, whether to fix a bug,
develop a new feature, improve the documentation, or just spark a discussion.

- [Chat with us on Zulip]((https://neuroinformatics.zulipchat.com/#narrow/stream/406001-Movement))

- Or [open an issue on GitHub](https://github.com/neuroinformatics-unit/movement/issues)
:::

::::