deploy: b72537a

_sources/content/Group_Analysis.ipynb

@@ -543,6 +543,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "(content:group_analysis:labels)=\n",
     "## Running a Group Analysis\n",
     "\n",
     "Okay, now let's try and run our own group level analysis with real imaging data using the Pinel Localizer data. I have run a first level model for the first 10 participants using the procedure we used in the single-subject analysis notebook. \n",
@@ -1719,7 +1720,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.12.2"
   },
   "toc": {
    "base_numbering": 1,

_sources/content/RSA.ipynb

@@ -122,7 +122,7 @@
     "### Single Subject Pattern Similarity\n",
     "Recall that in the Single Subject Model Lab that we ran single subject models for 10 different regressors for the Pinel Localizer task.  In this tutorial, we will use our results to learn how to conduct RSA style analyses.\n",
     "\n",
-    "First, let's get a list of all of the subject IDs and load the beta values from each condition for a single subject into a `Brain_Data` object."
+    "First, let's get a list of all of the subject IDs and load the beta values from each condition for a single subject into a `Brain_Data` object. We will be using the output of running a 1st-level model for each participant where we saved a separate file for each task condition. See this [code](content:group_analysis:labels) for reference from the group analysis tutorial."
    ]
   },
   {

content/Group_Analysis.html

@@ -804,7 +804,7 @@ <h3>Mixed Effects Model<a class="headerlink" href="#mixed-effects-model" title="
 </section>
 </section>
 <section id="running-a-group-analysis">
-<h2>Running a Group Analysis<a class="headerlink" href="#running-a-group-analysis" title="Permalink to this heading">#</a></h2>
+<span id="content-group-analysis-labels"></span><h2>Running a Group Analysis<a class="headerlink" href="#running-a-group-analysis" title="Permalink to this heading">#</a></h2>
 <p>Okay, now let’s try and run our own group level analysis with real imaging data using the Pinel Localizer data. I have run a first level model for the first 10 participants using the procedure we used in the single-subject analysis notebook.</p>
 <p>Here is the code I used to complete this for all participants. I wrote all of the betas and also a separate file for each individual regressor of interest.</p>
 <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">os</span>

content/RSA.html

@@ -602,7 +602,7 @@ <h3>Mapping stimuli relationships onto brain<a class="headerlink" href="#mapping
 <section id="single-subject-pattern-similarity">
 <h3>Single Subject Pattern Similarity<a class="headerlink" href="#single-subject-pattern-similarity" title="Permalink to this heading">#</a></h3>
 <p>Recall that in the Single Subject Model Lab that we ran single subject models for 10 different regressors for the Pinel Localizer task.  In this tutorial, we will use our results to learn how to conduct RSA style analyses.</p>
-<p>First, let’s get a list of all of the subject IDs and load the beta values from each condition for a single subject into a <code class="docutils literal notranslate"><span class="pre">Brain_Data</span></code> object.</p>
+<p>First, let’s get a list of all of the subject IDs and load the beta values from each condition for a single subject into a <code class="docutils literal notranslate"><span class="pre">Brain_Data</span></code> object. We will be using the output of running a 1st-level model for each participant where we saved a separate file for each task condition. See this <a class="reference internal" href="Group_Analysis.html#content-group-analysis-labels"><span class="std std-ref">code</span></a> for reference from the group analysis tutorial.</p>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
 <div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">sub</span> <span class="o">=</span> <span class="s1">&#39;S01&#39;</span>