Update course book

_sources/tutorials/W1D1_TheEthosOfOpenScience/student/W1D1_Tutorial1.ipynb

@@ -443,7 +443,7 @@
     "\n",
     "- [Sweeney and Clopath, 2020](https://elifesciences.org/articles/56053) used Allen Brain Observatory two-photon imaging data to explore the stability of neural responses over time. The authors found that, indeed, population coupling is correlated with the change in orientation and direction tuning of neurons over the course of a single experiment, an unexpected result linking population activity with individual neural responses.\n",
     "- [Bakhtiari et al., 2021](https://www.biorxiv.org/content/10.1101/2021.06.18.448989v3) examined whether a deep artificial neural network (ANN) could model both the ventral and dorsal pathways of the visual system in a single network with a single cost function. Comparing the representations of these networks with the neural responses in the two-photon imaging dataset, they found that the single pathway produced ventral-like representations but failed to capture the representational similarity of the dorsal areas.\n",
-    "- [Fritsche et al., 2022](https://www.jneurosci.org/content/42/10/1999) analyzed the time course of stimulus-specific adaptation in 2365 neurons in the Neuropixels dataset and discovered that a single presentation of a drifting or static grating in a specific orientation leads to a reduction in the response to the same visual stimulus up to eight trials (22 s) in the future. This stimulus-specific, long-term adaptation persists despite intervening stimuli, and is seen in all six visual cortical areas, but not in visual thalamic areas (LGN and LP), which returned to baseline after one or two trials. This is a remarkable example of a discovery that was not envisioned when designing our survey, but for which our stimulus set was well suited.\n",
+    "- [Fritsche et al., 2022](https://www.jneurosci.org/content/42/10/1999) analyzed the time course of stimulus-specific adaptation in 2365 neurons in the Neuropixels dataset and discovered that a single presentation of a drifting or static grating in a specific orientation leads to a reduction in the response to the same visual stimulus up to eight trials (22 s) in the future. This stimulus-specific, long-term adaptation persists despite intervening stimuli, and is seen in all six visual cortical areas, but not in visual thalamic areas (LGN and LP), which returned to baseline after one or two trials. This is a remarkable example of a discovery that was not envisioned when designing the survey, but for which the stimulus set was well suited.\n",
     "\n",
     "*Information on the case study is taken from 2023 [article](https://elifesciences.org/articles/85550).*\n",
     "\n",

_sources/tutorials/W1D2_OpenToolsAndResources/student/W1D2_Tutorial1.ipynb

@@ -620,7 +620,7 @@
     "execution": {}
    },
    "source": [
-    "## Introduction to Open Data\n",
+    "### Introduction to Open Data\n",
     "\n",
     "Scientific data is any type of information that is collected, observed, or created in the context of research. It can be:\n",
     "\n",
@@ -633,7 +633,7 @@
     "\n",
     "The following sections discuss ways to ensure that data is fully utilized and accessible to the most amount of people. These best practices center around community frameworks and tools that help researchers manage and share open data.\n",
     "\n",
-    "## FAIR Principles\n",
+    "### FAIR Principles\n",
     " \n",
     "Just like driving on the road, if everyone follows agreed-upon rules, everything goes much smoother. The rules don’t need to be exactly the same for every region but share common practices based on insights about safety and efficiency.\n",
     "\n",

_sources/tutorials/W1D3_OpenData/student/W1D3_Tutorial1.ipynb

@@ -1134,7 +1134,7 @@
     "\n",
     "*Estimated time for activity: 15 minutes*\n",
     "\n",
-    "Take a look at the examples of a public data management plan from [New Jersey Institute of Technology](https://dmptool.org/plans/102783/export.pdf?export%5Bpub%5D=true&export%5Bquestion_headings%5D=true) and from [University of California San Diego](https://library.ucsd.edu/research-and-collections/research-data/_files/dmpsample/DMP-Example-Psych.doc).\n",
+    "Take a look at the examples of a public data management plan from [University of North Carolina at Chapel Hill](https://dmptool.org/plans/113336/export.pdf?export%5Bpub%5D=true&export%5Bquestion_headings%5D=true) and from [University of California San Diego](https://library.ucsd.edu/research-and-collections/research-data/_files/dmpsample/DMP-Example-Psych.doc).\n",
     "\n",
     "If direct link for the University of California San Diego doesn't work for you, please visit the [following link](https://library.ucsd.edu/research-and-collections/research-data/plan-and-manage/sample-nsf-data-management-plans.html), scroll to the end of the page and open `DMP Example Psych.doc` document.\n",
     "\n",

_sources/tutorials/W1D5_OpenResults/student/W1D5_Tutorial1.ipynb

@@ -132,13 +132,7 @@
     "\n",
     "**Scientists can share their incremental progress throughout the research process and invite community feedback. Sharing more parts of the research process creates more interactions between researchers and can improve the end result (which may be a peer-reviewed article).**\n",
     "\n",
-    "Throughout this day, we will show you how to use, make, and share open results.\n",
-    "\n",
-    "#### The Practice of 'Open'\n",
-    "\n",
-    "Specifically, the \"Use, Make, Share\" format has been naturally embedded throughout the curriculum and should be a familiar format by now. Section 2 will cover \"Using\". Section 3 will cover \"Making\". Section 4 will cover \"Sharing\". Throughout this module, we will pay particular attention to manuscripts and other research products as examples because the previous modules covered \"Use, Make, Share\" in the context of components with data and software.\n",
-    "\n",
-    "<img src=\"https://github.com/neuromatch/nasa-open-science/blob/main/tutorials/W1D5_OpenResults/static/thepracticeofopen.jpg?raw=true\" width = 500 alt = \"Use, make, share framework.\"/>"
+    "Throughout this day, we will show you how to use, make, and share open results."
    ]
   },
   {

tutorials/W1D1_TheEthosOfOpenScience/student/W1D1_Tutorial1.html

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@@ -957,7 +957,7 @@ <h2>Tutorial Objectives<a class="headerlink" href="#tutorial-objectives" title="
 <p>An introduction to open science, which is the principle and practice of making research products and processes available to all, while respecting diverse cultures, maintaining security and privacy, and fostering collaborations, reproducibility, and equity. In this module, you will take a closer look at what open science is, including the current landscape as well as the benefits and challenges. You then get a glimpse into the practice of open science, including case studies and examples. Lastly, you are presented with actions that you can take starting today, such as exploring communities that they can engage with.</p>
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@@ -1185,7 +1185,7 @@ <h4><span style="color: orange">Case Study:</span> Allen Brain Observatory. When
 <ul class="simple">
 <li><p><a class="reference external" href="https://elifesciences.org/articles/56053">Sweeney and Clopath, 2020</a> used Allen Brain Observatory two-photon imaging data to explore the stability of neural responses over time. The authors found that, indeed, population coupling is correlated with the change in orientation and direction tuning of neurons over the course of a single experiment, an unexpected result linking population activity with individual neural responses.</p></li>
 <li><p><a class="reference external" href="https://www.biorxiv.org/content/10.1101/2021.06.18.448989v3">Bakhtiari et al., 2021</a> examined whether a deep artificial neural network (ANN) could model both the ventral and dorsal pathways of the visual system in a single network with a single cost function. Comparing the representations of these networks with the neural responses in the two-photon imaging dataset, they found that the single pathway produced ventral-like representations but failed to capture the representational similarity of the dorsal areas.</p></li>
-<li><p><a class="reference external" href="https://www.jneurosci.org/content/42/10/1999">Fritsche et al., 2022</a> analyzed the time course of stimulus-specific adaptation in 2365 neurons in the Neuropixels dataset and discovered that a single presentation of a drifting or static grating in a specific orientation leads to a reduction in the response to the same visual stimulus up to eight trials (22 s) in the future. This stimulus-specific, long-term adaptation persists despite intervening stimuli, and is seen in all six visual cortical areas, but not in visual thalamic areas (LGN and LP), which returned to baseline after one or two trials. This is a remarkable example of a discovery that was not envisioned when designing our survey, but for which our stimulus set was well suited.</p></li>
+<li><p><a class="reference external" href="https://www.jneurosci.org/content/42/10/1999">Fritsche et al., 2022</a> analyzed the time course of stimulus-specific adaptation in 2365 neurons in the Neuropixels dataset and discovered that a single presentation of a drifting or static grating in a specific orientation leads to a reduction in the response to the same visual stimulus up to eight trials (22 s) in the future. This stimulus-specific, long-term adaptation persists despite intervening stimuli, and is seen in all six visual cortical areas, but not in visual thalamic areas (LGN and LP), which returned to baseline after one or two trials. This is a remarkable example of a discovery that was not envisioned when designing the survey, but for which the stimulus set was well suited.</p></li>
 </ul>
 <p><em>Information on the case study is taken from 2023 <a class="reference external" href="https://elifesciences.org/articles/85550">article</a>.</em></p>
 </section>