mne demo: restructured headings
"\n",
"This step follows the first steps of [https://mne.tools/dev/auto_examples/decoding/decoding_rsa_sgskip.html#sphx-glr-auto-examples-decoding-decoding-rsa-sgskip-py](https://mne.tools/dev/auto_examples/decoding/decoding_rsa_sgskip.html#sphx-glr-auto-examples-decoding-decoding-rsa-sgskip-py)\n",
"\n",
- "## a) loading, downsampling, epoching, equalizing event count"
+ "### 1a) loading, downsampling, epoching, equalizing event count"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "## 1b) simulate multiple subjects\n",
+ "### 1b) simulate multiple subjects\n",
"\n",
"We will simulate multiple subjects as noisy versions of the one subject\n",
"\n",
"cell_type": "markdown",
"metadata": {},
"source": [
- "### compute channel noise precision matrix for single subject"
+ "#### compute channel noise precision matrix for single subject"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "### compute condition averages for single subject"
+ "#### compute condition averages for single subject"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "### simulate multiple subjects"
+ "#### simulate multiple subjects"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "# 4) evaluate RDM movie similarity to model RDMs"
+ "## 4) evaluate RDM movie similarity to model RDMs"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "## 4a) define candidate model RDMs"
+ "### define candidate model RDMs"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "# 5) compute cluster-based permutation statistic\n"
+ "## 5) compute cluster-based permutation statistic\n"
]
},
{
