Update course book

neuromatch · Aug 30, 2024 · fd3e3e7 · fd3e3e7
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diff --git a/_sources/projects/project-notebooks/ComparingNetworks.ipynb b/_sources/projects/project-notebooks/ComparingNetworks.ipynb
diff --git a/_sources/projects/project-notebooks/Macrocircuits.ipynb b/_sources/projects/project-notebooks/Macrocircuits.ipynb
diff --git a/projects/project-notebooks/ComparingNetworks.html b/projects/project-notebooks/ComparingNetworks.html
@@ -1223,7 +1223,7 @@ <h3>Install and import feedback gadget<a class="headerlink" href="#install-and-i
 <h3>Project Background<a class="headerlink" href="#project-background" title="Permalink to this heading">#</a></h3>
 <div class="cell tag_remove-input docutils container">
 <div class="cell_output docutils container">
-<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "c1fdf823c0f742a5b4bb8a9d62ac8fea"}</script></div>
+<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "858d8663c2f34998ba8f802b16ea3834"}</script></div>
 </div>
 </section>
 <section id="submit-your-feedback">
@@ -1242,7 +1242,7 @@ <h3>Submit your feedback<a class="headerlink" href="#submit-your-feedback" title
 </div>
 </details>
 <div class="cell_output docutils container">
-<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "14df630b76af436b9ce32479d837b85a"}</script></div>
+<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "d5e22ae6aca24718a8bf30d2b748ce50"}</script></div>
 </div>
 </section>
 <section id="project-slides">
@@ -1305,7 +1305,7 @@ <h3>Submit your feedback<a class="headerlink" href="#id1" title="Permalink to th
 </div>
 </details>
 <div class="cell_output docutils container">
-<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "d9398321b5544f8aad3dab8382e2f788"}</script></div>
+<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "91eb56a917c34a37a7916ed27e7dd8b9"}</script></div>
 </div>
 <p>In this notebook, we are going to provide code to get you started on Q1-Q3 of this project!</p>
 <p>The basic outline looks like this:</p>
@@ -1335,6 +1335,7 @@ <h3>Submit your feedback<a class="headerlink" href="#id1" title="Permalink to th
 <hr class="docutils" />
 <section id="section-1-preparing-the-environment">
 <h2>Section 1: Preparing the environment<a class="headerlink" href="#section-1-preparing-the-environment" title="Permalink to this heading">#</a></h2>
+<p>Disclaimer: As an alternative to Google Colab, Kaggle, and local installation, we have prepared a Dockerfile with the instructions on the virtual environment setup. It will allow you to work locally with no interventions into already installed packages (you will just need to install Docker and run two commands). Grab a <a class="reference external" href="https://osf.io/b4yfa">Dockerfile</a>, put it in the same folder as this notebook, and follow the instructions in <a class="reference external" href="https://osf.io/qtezf">README</a> file.</p>
 <p><strong>IF USING COLAB // KAGGLE</strong>:</p>
 <p>Uncomment the lines of code below and run them in order. The top, the second, and the last cells only need to be run once, but <strong>the third cells (envStr) need to be re-run if the Colab // Kaggle notebook crashes</strong>. These blocks install the needed dependencies and set up your environment. Notice that the first and third cell contents depend on whether you use Colab or Kaggle.</p>
 <p>⏳⏳⏳</p>
@@ -1495,7 +1496,7 @@ <h3>Submit your feedback<a class="headerlink" href="#id2" title="Permalink to th
 </div>
 </details>
 <div class="cell_output docutils container">
-<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "b8312c5ddf144953ad1dfcd6258289e5"}</script></div>
+<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "97b30e9647cd4427a8edea08c2d2facb"}</script></div>
 </div>
 </section>
 </section>
@@ -1562,7 +1563,7 @@ <h3>Submit your feedback<a class="headerlink" href="#id3" title="Permalink to th
 </div>
 </details>
 <div class="cell_output docutils container">
-<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "5b2abf0c923843d3bb9e819b4189e3cb"}</script></div>
+<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "a0174611fe714dca88ef2f3639731afe"}</script></div>
 </div>
 </section>
 </section>
@@ -1597,7 +1598,7 @@ <h2>Section 3: Understanding the Three-Bit Flip-Flop task (3BFF)<a class="header
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../../_images/29a08c08a3b7fbd1c355eb267884ec858ab9af2dec4884da28b2ce8b33c104e2.png" src="../../_images/29a08c08a3b7fbd1c355eb267884ec858ab9af2dec4884da28b2ce8b33c104e2.png" />
+<img alt="../../_images/64851534192abe04b98743ed5ef55c19f13580f33d693612bda54f64c9aaeafd.png" src="../../_images/64851534192abe04b98743ed5ef55c19f13580f33d693612bda54f64c9aaeafd.png" />
 </div>
 </div>
 <p>Above, we are plotting the inputs and outputs of the 3BFF task. One trial is 500 time steps, each with a 1% probability of getting an “up” or “down” pulse on each of its 3 input channels. When the task receives an “up” pulse, the state corresponding to that input channel moves from zero to one (if possible), and if a state at one receives a “down” pulse, it goes to zero. In this way, this system acts as 3 bits of memory, encoding 8 potential system states (2^3 states). We add noise to the inputs of the system so that it better reflects realistic computations that a neural circuit might perform.</p>
@@ -1610,7 +1611,7 @@ <h2>Section 3: Understanding the Three-Bit Flip-Flop task (3BFF)<a class="header
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../../_images/500d3e5668d9440f586decc939ee3b5e63c7d23ecd45f033d358e64d9b6264f3.png" src="../../_images/500d3e5668d9440f586decc939ee3b5e63c7d23ecd45f033d358e64d9b6264f3.png" />
+<img alt="../../_images/83e7df60d3a7d613ee5813049ff69caf139c3239343ace2d965f697062d92422.png" src="../../_images/83e7df60d3a7d613ee5813049ff69caf139c3239343ace2d965f697062d92422.png" />
 </div>
 </div>
 <p>Now that we can see the basic logic of the task, let’s do a basic overview of what task training is!</p>
@@ -1634,7 +1635,7 @@ <h3>Submit your feedback<a class="headerlink" href="#id4" title="Permalink to th
 </div>
 </details>
 <div class="cell_output docutils container">
-<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "2bd3b26062ac4f0493841acc5fcb4931"}</script></div>
+<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "5caa4a2c6ebc446e98313b8552ff9a7c"}</script></div>
 </div>
 </section>
 </section>
@@ -1757,7 +1758,7 @@ <h3>Submit your feedback<a class="headerlink" href="#id5" title="Permalink to th
 </div>
 </details>
 <div class="cell_output docutils container">
-<script type="application/vnd.jupyter.widget-view+json">{"model_id": "64be44e91da74d9aa50ab145c4a711b4", "version_major": 2, "version_minor": 0}</script></div>
+<script type="application/vnd.jupyter.widget-view+json">{"model_id": "cccb37f642bd4f119f72372e217f3e4f", "version_major": 2, "version_minor": 0}</script></div>
 </div>
 </section>
 </section>
@@ -1793,7 +1794,7 @@ <h3>Part 1: Visualizing latent activity<a class="headerlink" href="#part-1-visua
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../../_images/f53d9f96511408459499d1eb88d6a7b01dac545184c7977aa2838eb7e5626511.png" src="../../_images/f53d9f96511408459499d1eb88d6a7b01dac545184c7977aa2838eb7e5626511.png" />
+<img alt="../../_images/8ba4155ceb022209d14ec46eae087569729d3cbc359ab6b1de94b68e9f802499.png" src="../../_images/8ba4155ceb022209d14ec46eae087569729d3cbc359ab6b1de94b68e9f802499.png" />
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 <div class="cell docutils container">
@@ -1809,7 +1810,7 @@ <h3>Part 1: Visualizing latent activity<a class="headerlink" href="#part-1-visua
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../../_images/0167c4d30f249ea938da64814fcddaafb8ca6c5c2bbc0bd77561337d17e3a0e4.png" src="../../_images/0167c4d30f249ea938da64814fcddaafb8ca6c5c2bbc0bd77561337d17e3a0e4.png" />
+<img alt="../../_images/5823ed35f3805bd9c66a46ded3caabc60cb6d2d3bda32fbc02a755eab29465a4.png" src="../../_images/5823ed35f3805bd9c66a46ded3caabc60cb6d2d3bda32fbc02a755eab29465a4.png" />
 </div>
 </div>
 <p>There are also useful data visualization functions, such as visualizing a scree plot of the latent activity.</p>
@@ -1821,11 +1822,11 @@ <h3>Part 1: Visualizing latent activity<a class="headerlink" href="#part-1-visua
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>array([0.32841057, 0.27514544, 0.26159662, 0.02224682, 0.01923219,
-       0.01717032, 0.00614414, 0.00561094, 0.00498556, 0.00466619])
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>array([0.48745748, 0.23808762, 0.12121433, 0.02579751, 0.02215279,
+       0.02057775, 0.01052088, 0.00839948, 0.00731314, 0.00564797])
 </pre></div>
 </div>
-<img alt="../../_images/4bccc9231401df140b0e33764d4fc4b79a20d497ab35e211e15ba3a6a0e655a8.png" src="../../_images/4bccc9231401df140b0e33764d4fc4b79a20d497ab35e211e15ba3a6a0e655a8.png" />
+<img alt="../../_images/f9fadec6dd9f58d1e54234b06db4d894b537c9eafd1abf70b248530888f94de6.png" src="../../_images/f9fadec6dd9f58d1e54234b06db4d894b537c9eafd1abf70b248530888f94de6.png" />
 </div>
 </div>
 <p>Importantly, the analysis object also provides functions that give access to the raw latent activity, predicted outputs, etc. of the trained models! All of these functions accept a “phase” variable that designates whether to return the training and/or validation datasets.
@@ -1880,7 +1881,7 @@ <h3>Submit your feedback<a class="headerlink" href="#id6" title="Permalink to th
 </div>
 </details>
 <div class="cell_output docutils container">
-<script type="application/vnd.jupyter.widget-view+json">{"model_id": "aebfa13cdb68409f8a4e067af203c004", "version_major": 2, "version_minor": 0}</script></div>
+<script type="application/vnd.jupyter.widget-view+json">{"model_id": "4c4570d5d1434bc2b91b26ca8658452b", "version_major": 2, "version_minor": 0}</script></div>
 </div>
 </section>
 <section id="part-2-using-affine-transformations-to-compare-latent-activity">
@@ -1952,8 +1953,8 @@ <h3>Part 2: Using affine transformations to compare latent activity<a class="hea
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>R2 of linear regression fit: [0.68010143 0.42213313 0.27201338]
-Variance-weighted R2 of linear regression fit: 0.6624338067445769
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>R2 of linear regression fit: [0.80023307 0.52220986 0.77564701]
+Variance-weighted R2 of linear regression fit: 0.7076211324642876
 </pre></div>
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