Update course book

neuromatch · Jul 15, 2024 · 5c1b3fc · 5c1b3fc
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diff --git a/_images/fd7702a2e831d720d3905a58c1f4760f2e067597ac07c43e7f261a3f1153ba78.png b/_images/fd7702a2e831d720d3905a58c1f4760f2e067597ac07c43e7f261a3f1153ba78.png
diff --git a/_images/fe2fe73423e057d96a206a3584da8a0c24b52df75c987ab87e098a0ed0711493.png b/_images/fe2fe73423e057d96a206a3584da8a0c24b52df75c987ab87e098a0ed0711493.png
diff --git a/_images/ff1f97f7ca2a90876824965b6be17b68849a91af1d3b27a394547eacfc765c60.png b/_images/ff1f97f7ca2a90876824965b6be17b68849a91af1d3b27a394547eacfc765c60.png
diff --git a/_images/ffe87fd26b2cd605f29bff6cdfa8f8991b127de18dbbdb8373362ae409577230.png b/_images/ffe87fd26b2cd605f29bff6cdfa8f8991b127de18dbbdb8373362ae409577230.png
diff --git a/_sources/prereqs/NeuroAI.md b/_sources/prereqs/NeuroAI.md
@@ -5,6 +5,7 @@ This is a more advanced course than other Neuromatch courses so far. We will be
   * Have taken Neuromatch courses in [computational neuroscience](https://compneuro.neuromatch.io/tutorials/intro.html) and [deep learning](https://deeplearning.neuromatch.io/), or the equivalent
   * Have intermediate proficiency in Python
   * Some core math concepts
+
 Below are more details on the prerequisites. 
 ### Neuroscience
 You should have some exposure to computational neuroscience, such as through our Neuromatch course. A rudimentary familiarity with neurobiology is fine.

diff --git a/_sources/projects/project-notebooks/Macrocircuits.ipynb b/_sources/projects/project-notebooks/Macrocircuits.ipynb
diff --git a/_sources/tutorials/W1D1_Generalization/student/W1D1_Tutorial3.ipynb b/_sources/tutorials/W1D1_Generalization/student/W1D1_Tutorial3.ipynb
@@ -1066,7 +1066,7 @@
     "\n",
     "The result is a highly structured Bayesian generative model containing both discrete components (e.g. strokes) and continuous components (e.g. the location of the next stroke is a continuous variable). It combines symbolic primitives (strokes) as well as standard ANN components. This combination of using symbols and neural networks is known as a **neuro-symbolic** approach.\n",
     "\n",
-    "This is an example of a model with **strong inductive biases**. Watch the video to learn more about how such a model might explain the perception of characters."
+    "This is an example of a model with **strong inductive biases**."
    ]
   },
   {

diff --git a/_sources/tutorials/W1D2_ComparingTasks/student/W1D2_Tutorial1.ipynb b/_sources/tutorials/W1D2_ComparingTasks/student/W1D2_Tutorial1.ipynb
@@ -3052,7 +3052,7 @@
     "execution": {}
    },
    "source": [
-    "## Transfer example 2: regression to autoencoder"
+    "## Transfer example 2: autoencoder to classification"
    ]
   },
   {

diff --git a/_sources/tutorials/W1D2_ComparingTasks/student/W1D2_Tutorial2.ipynb b/_sources/tutorials/W1D2_ComparingTasks/student/W1D2_Tutorial2.ipynb
@@ -130,12 +130,12 @@
     "from vibecheck import DatatopsContentReviewContainer\n",
     "def content_review(notebook_section: str):\n",
     "    return DatatopsContentReviewContainer(\n",
-    "        \"\",  # No text prompt - leave this as is\n",
+    "        \"\",  # No text prompt\n",
     "        notebook_section,\n",
     "        {\n",
-    "        \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
-    "        \"name\": \"sciencematch_sm\", # change the name of the course : neuromatch_dl, climatematch_ct, etc\n",
-    "        \"user_key\": \"y1x3mpx5\",\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"neuromatch_neuroai\",\n",
+    "            \"user_key\": \"wb2cxze8\",\n",
     "        },\n",
     "    ).render()\n",
     "\n",

diff --git a/...rces/tutorials/W1D3_ComparingArtificialAndBiologicalNetworks/student/W1D3_Tutorial3.ipynb b/...rces/tutorials/W1D3_ComparingArtificialAndBiologicalNetworks/student/W1D3_Tutorial3.ipynb
@@ -1756,7 +1756,7 @@
    },
    "source": [
     "---\n",
-    "# Section 3. Create representational dissimilarity matrices (RDMs)\n",
+    "# Section 3: Create representational dissimilarity matrices (RDMs)\n",
     "\n",
     "Estimated timing to here from start of tutorial: 20 minutes\n"
    ]
@@ -2580,7 +2580,7 @@
    },
    "source": [
     "---\n",
-    "# Section 5. Model Comparison Using Two-factor Bootstrap\n",
+    "# Section 5: Model Comparison Using Two-factor Bootstrap\n",
     "\n",
     "Estimated timing to here from start of tutorial: 45 minutes\n"
    ]

diff --git a/_sources/tutorials/W1D5_Microcircuits/student/W1D5_Tutorial1.ipynb b/_sources/tutorials/W1D5_Microcircuits/student/W1D5_Tutorial1.ipynb
@@ -971,14 +971,14 @@
    },
    "source": [
     "---\n",
-    "# Section 2.1: Sparsity via nonlinearity"
+    "## Section 2.1: Sparsity via nonlinearity"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "##  Video 2: Natural sparsity\n"
+    "###  Video 2: Natural sparsity\n"
    ]
   },
   {
@@ -1044,7 +1044,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "##  Submit your feedback\n"
+    "###  Submit your feedback\n"
    ]
   },
   {
@@ -1069,7 +1069,7 @@
     "execution": {}
    },
    "source": [
-    "## Coding Exercise 2.1: Sparsity as the result of thresholding\n",
+    "### Coding Exercise 2.1: Sparsity as the result of thresholding\n",
     "\n",
     "In this exercise, we will understand how a nonlinearity can increase sparsity."
    ]
@@ -1089,7 +1089,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "###  Execute the cell to see the interactive widget!\n"
+    "####  Execute the cell to see the interactive widget!\n"
    ]
   },
   {
@@ -1124,7 +1124,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "###  Plot of change in pixel's value over time\n"
+    "####  Plot of change in pixel's value over time\n"
    ]
   },
   {
@@ -1222,7 +1222,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "###  Plot your results\n"
+    "####  Plot your results\n"
    ]
   },
   {
@@ -1255,7 +1255,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "###  Threshold value impact on ReLU version of the signal\n"
+    "####  Threshold value impact on ReLU version of the signal\n"
    ]
   },
   {
@@ -1291,7 +1291,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "###  Kurtosis value comparison\n"
+    "####  Kurtosis value comparison\n"
    ]
   },
   {
@@ -1316,7 +1316,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "###  Submit your feedback\n"
+    "####  Submit your feedback\n"
    ]
   },
   {
@@ -1447,7 +1447,7 @@
     "execution": {}
    },
    "source": [
-    "## Coding Exercise 2.2: Temporal differencing signal"
+    "### Coding Exercise 2.2: Temporal differencing signal"
    ]
   },
   {
@@ -1493,7 +1493,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "###  Observe the result\n"
+    "####  Observe the result\n"
    ]
   },
   {
@@ -1525,7 +1525,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "###  Histograms for the signal and its temporal differences\n"
+    "####  Histograms for the signal and its temporal differences\n"
    ]
   },
   {
@@ -1548,7 +1548,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "###  Kurtosis values for the signal and its temporal differences\n"
+    "####  Kurtosis values for the signal and its temporal differences\n"
    ]
   },
   {
@@ -1571,7 +1571,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "###  Submit your feedback\n"
+    "####  Submit your feedback\n"
    ]
   },
   {
@@ -3007,7 +3007,7 @@
    },
    "source": [
     "---\n",
-    "# Section 5: Identifying sparse visual fields in natural images using sparse coding\n",
+    "# Section 4: Identifying sparse visual fields in natural images using sparse coding\n",
     "\n",
     "*Estimated timing to here from start of tutorial: 1 hour 5 minutes.*\n",
     "\n",

diff --git a/_sources/tutorials/W2D4_Macrolearning/student/W2D4_Tutorial4.ipynb b/_sources/tutorials/W2D4_Macrolearning/student/W2D4_Tutorial4.ipynb
@@ -1203,7 +1203,7 @@
    "source": [
     "---\n",
     "\n",
-    "# Section 3: Baldwin Effect\n",
+    "# Section 2: Baldwin Effect\n",
     "\n",
     "*Estimated timing to here from start of tutorial: 20 minutes*\n",
     "\n",
@@ -1798,7 +1798,7 @@
    "source": [
     "---\n",
     "\n",
-    "# Section 4: Newbie & Experienced Bird\n",
+    "# Section 3: Newbie & Experienced Bird\n",
     "\n",
     "*Estimated timing to here from start of tutorial: 50 minutes*\n",
     "\n",
@@ -1890,7 +1890,7 @@
    "source": [
     "---\n",
     "\n",
-    "# Section 5: An alternative model of how the brain solves the Harlow experiment\n",
+    "# Section 4: An alternative model of how the brain solves the Harlow experiment\n",
     "\n",
     "*Estimated timing to here from start of tutorial: 60 minutes*\n",
     "\n",

diff --git a/genindex.html b/genindex.html
@@ -668,7 +668,6 @@
 
 
 
-
 <li class="toctree-l2"><a class="reference internal" href="tutorials/W1D5_Microcircuits/student/W1D5_Tutorial2.html">Tutorial 2: Normalization</a></li>
 
 

diff --git a/prereqs/NeuroAI.html b/prereqs/NeuroAI.html
@@ -675,7 +675,6 @@
 
 
 
-
 <li class="toctree-l2"><a class="reference internal" href="../tutorials/W1D5_Microcircuits/student/W1D5_Tutorial2.html">Tutorial 2: Normalization</a></li>
 
 
@@ -1058,9 +1057,9 @@ <h2>Preparing yourself for the course<a class="headerlink" href="#preparing-your
 <ul class="simple">
 <li><p>Have taken Neuromatch courses in <a class="reference external" href="https://compneuro.neuromatch.io/tutorials/intro.html">computational neuroscience</a> and <a class="reference external" href="https://deeplearning.neuromatch.io/">deep learning</a>, or the equivalent</p></li>
 <li><p>Have intermediate proficiency in Python</p></li>
-<li><p>Some core math concepts
-Below are more details on the prerequisites.</p></li>
+<li><p>Some core math concepts</p></li>
 </ul>
+<p>Below are more details on the prerequisites.</p>
 <section id="neuroscience">
 <h3>Neuroscience<a class="headerlink" href="#neuroscience" title="Permalink to this heading">#</a></h3>
 <p>You should have some exposure to computational neuroscience, such as through our Neuromatch course. A rudimentary familiarity with neurobiology is fine.</p>

diff --git a/projects/README.html b/projects/README.html
@@ -671,7 +671,6 @@
 
 
 
-
 <li class="toctree-l2"><a class="reference internal" href="../tutorials/W1D5_Microcircuits/student/W1D5_Tutorial2.html">Tutorial 2: Normalization</a></li>
 
 

diff --git a/projects/docs/datasets_overview.html b/projects/docs/datasets_overview.html
@@ -671,7 +671,6 @@
 
 
 
-
 <li class="toctree-l2"><a class="reference internal" href="../../tutorials/W1D5_Microcircuits/student/W1D5_Tutorial2.html">Tutorial 2: Normalization</a></li>
 
 

diff --git a/projects/docs/project_guidance.html b/projects/docs/project_guidance.html
@@ -675,7 +675,6 @@
 
 
 
-
 <li class="toctree-l2"><a class="reference internal" href="../../tutorials/W1D5_Microcircuits/student/W1D5_Tutorial2.html">Tutorial 2: Normalization</a></li>
 
 

diff --git a/projects/professional_development/README.html b/projects/professional_development/README.html
@@ -675,7 +675,6 @@
 
 
 
-
 <li class="toctree-l2"><a class="reference internal" href="../../tutorials/W1D5_Microcircuits/student/W1D5_Tutorial2.html">Tutorial 2: Normalization</a></li>
 
 

diff --git a/projects/professional_development/mentorship_program.html b/projects/professional_development/mentorship_program.html
@@ -674,7 +674,6 @@
 
 
 
-
 <li class="toctree-l2"><a class="reference internal" href="../../tutorials/W1D5_Microcircuits/student/W1D5_Tutorial2.html">Tutorial 2: Normalization</a></li>
 
 

diff --git a/projects/project-notebooks/ComparingNetworks.html b/projects/project-notebooks/ComparingNetworks.html
@@ -675,7 +675,6 @@
 
 
 
-
 <li class="toctree-l2"><a class="reference internal" href="../../tutorials/W1D5_Microcircuits/student/W1D5_Tutorial2.html">Tutorial 2: Normalization</a></li>
 
 
@@ -1225,7 +1224,7 @@ <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": "fc6d864974c044508ad178b646ebc335"}</script></div>
+<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "54465c85e6004aa6aa44dba7e07c402c"}</script></div>
 </div>
 </section>
 <section id="submit-your-feedback">
@@ -1244,7 +1243,7 @@ <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": "f8c5a4ad86ca4673ad1661e37ca86913"}</script></div>
+<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "d78d7e60c16c48b39475868ba645704d"}</script></div>
 </div>
 </section>
 <section id="project-slides">
@@ -1307,7 +1306,7 @@ <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": "482a9e580879438abe8653f39fbebe0e"}</script></div>
+<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "d6d0ef8064994a5699e399cc3bb05377"}</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>
@@ -1497,7 +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": "c5d794cbebea4f328330c86159ceb549"}</script></div>
+<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "9972d05c523547dd86702aef6551a90d"}</script></div>
 </div>
 </section>
 </section>
@@ -1564,7 +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": "ba8eea3c7715412289b0111c1a49f7be"}</script></div>
+<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "8282d5fdc4c24917ae1bb48c256a9f61"}</script></div>
 </div>
 </section>
 </section>
@@ -1599,7 +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/2e7c8988acca77a8b70be794d5e14d4052f20d6c50e418b9b453e7918b2b47f9.png" src="../../_images/2e7c8988acca77a8b70be794d5e14d4052f20d6c50e418b9b453e7918b2b47f9.png" />
+<img alt="../../_images/3277a738cfcf39e1c78410c642cedb25b8d35594750e8ce5ccde36617ae69942.png" src="../../_images/3277a738cfcf39e1c78410c642cedb25b8d35594750e8ce5ccde36617ae69942.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>
@@ -1612,7 +1611,7 @@ <h2>Section 3: Understanding the Three-Bit Flip-Flop task (3BFF)<a class="header
 </div>
 </div>
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 <p>Now that we can see the basic logic of the task, let’s do a basic overview of what task training is!</p>
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         "\n",
         "The result is a highly structured Bayesian generative model containing both discrete components (e.g. strokes) and continuous components (e.g. the location of the next stroke is a continuous variable). It combines symbolic primitives (strokes) as well as standard ANN components. This combination of using symbols and neural networks is known as a **neuro-symbolic** approach.\n",
         "\n",
-        "This is an example of a model with **strong inductive biases**. Watch the video to learn more about how such a model might explain the perception of characters."
+        "This is an example of a model with **strong inductive biases**."
        ]
       },
       {
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