Merge pull request dylansdaniels#14 from asoplata/add-adapted-under-t…

…he-hood

content: add under the hood sections

content/01_overview/challange.html

@@ -53,10 +53,10 @@
 				<a href="/website_redesign/content/03_assumptions/template_model.html">3.1 Template Model</a>
 				<a href="/website_redesign/content/03_assumptions/cortical_column_structure.html">3.2 Cortical Column Structure</a>
 				<a href="/website_redesign/content/03_assumptions/primary_electric_currents.html">3.3 Primary Electrical Currents</a>
-				<a href="/website_redesign/content/03_assumptions/neuron_morphology.html">3.4 Neuron Morphology and Physiology</a>
+				<a href="/website_redesign/content/03_assumptions/neurons_morphology_and_physiology.html">3.4 Neurons: Morphology and Physiology</a>
 				<a href="/website_redesign/content/03_assumptions/synaptic_connectivity.html">3.5 Synaptic Connectivity</a>
-				<a href="/website_redesign/content/03_assumptions/evoked_rhythmic_inputs.html">3.6 Evoked and Rhythmic Driving Inputs</a>
-				<a href="/website_redesign/content/03_assumptions/tonic_noisy.html">3.7 Tonic and Noisy Driving Inputs</a>
+				<a href="/website_redesign/content/03_assumptions/evoked_and_rhythmic_driving_inputs.html">3.6 Evoked and Rhythmic Driving Inputs</a>
+				<a href="/website_redesign/content/03_assumptions/tonic_and_noisy_driving_inputs.html">3.7 Tonic and Noisy Driving Inputs</a>
 			</div>
 		</div>
 		<div class="sidebar-list">

content/01_overview/sample_workflow.html

@@ -53,10 +53,10 @@
 				<a href="/website_redesign/content/03_assumptions/template_model.html">3.1 Template Model</a>
 				<a href="/website_redesign/content/03_assumptions/cortical_column_structure.html">3.2 Cortical Column Structure</a>
 				<a href="/website_redesign/content/03_assumptions/primary_electric_currents.html">3.3 Primary Electrical Currents</a>
-				<a href="/website_redesign/content/03_assumptions/neuron_morphology.html">3.4 Neuron Morphology and Physiology</a>
+				<a href="/website_redesign/content/03_assumptions/neurons_morphology_and_physiology.html">3.4 Neurons: Morphology and Physiology</a>
 				<a href="/website_redesign/content/03_assumptions/synaptic_connectivity.html">3.5 Synaptic Connectivity</a>
-				<a href="/website_redesign/content/03_assumptions/evoked_rhythmic_inputs.html">3.6 Evoked and Rhythmic Driving Inputs</a>
-				<a href="/website_redesign/content/03_assumptions/tonic_noisy.html">3.7 Tonic and Noisy Driving Inputs</a>
+				<a href="/website_redesign/content/03_assumptions/evoked_and_rhythmic_driving_inputs.html">3.6 Evoked and Rhythmic Driving Inputs</a>
+				<a href="/website_redesign/content/03_assumptions/tonic_and_noisy_driving_inputs.html">3.7 Tonic and Noisy Driving Inputs</a>
 			</div>
 		</div>
 		<div class="sidebar-list">

content/01_overview/using_hnn.html

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 				<a href="/website_redesign/content/03_assumptions/template_model.html">3.1 Template Model</a>
 				<a href="/website_redesign/content/03_assumptions/cortical_column_structure.html">3.2 Cortical Column Structure</a>
 				<a href="/website_redesign/content/03_assumptions/primary_electric_currents.html">3.3 Primary Electrical Currents</a>
-				<a href="/website_redesign/content/03_assumptions/neuron_morphology.html">3.4 Neuron Morphology and Physiology</a>
+				<a href="/website_redesign/content/03_assumptions/neurons_morphology_and_physiology.html">3.4 Neurons: Morphology and Physiology</a>
 				<a href="/website_redesign/content/03_assumptions/synaptic_connectivity.html">3.5 Synaptic Connectivity</a>
-				<a href="/website_redesign/content/03_assumptions/evoked_rhythmic_inputs.html">3.6 Evoked and Rhythmic Driving Inputs</a>
-				<a href="/website_redesign/content/03_assumptions/tonic_noisy.html">3.7 Tonic and Noisy Driving Inputs</a>
+				<a href="/website_redesign/content/03_assumptions/evoked_and_rhythmic_driving_inputs.html">3.6 Evoked and Rhythmic Driving Inputs</a>
+				<a href="/website_redesign/content/03_assumptions/tonic_and_noisy_driving_inputs.html">3.7 Tonic and Noisy Driving Inputs</a>
 			</div>
 		</div>
 		<div class="sidebar-list">

content/02_background/biophysical_modeling.html

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 				<a href="/website_redesign/content/03_assumptions/template_model.html">3.1 Template Model</a>
 				<a href="/website_redesign/content/03_assumptions/cortical_column_structure.html">3.2 Cortical Column Structure</a>
 				<a href="/website_redesign/content/03_assumptions/primary_electric_currents.html">3.3 Primary Electrical Currents</a>
-				<a href="/website_redesign/content/03_assumptions/neuron_morphology.html">3.4 Neuron Morphology and Physiology</a>
+				<a href="/website_redesign/content/03_assumptions/neurons_morphology_and_physiology.html">3.4 Neurons: Morphology and Physiology</a>
 				<a href="/website_redesign/content/03_assumptions/synaptic_connectivity.html">3.5 Synaptic Connectivity</a>
-				<a href="/website_redesign/content/03_assumptions/evoked_rhythmic_inputs.html">3.6 Evoked and Rhythmic Driving Inputs</a>
-				<a href="/website_redesign/content/03_assumptions/tonic_noisy.html">3.7 Tonic and Noisy Driving Inputs</a>
+				<a href="/website_redesign/content/03_assumptions/evoked_and_rhythmic_driving_inputs.html">3.6 Evoked and Rhythmic Driving Inputs</a>
+				<a href="/website_redesign/content/03_assumptions/tonic_and_noisy_driving_inputs.html">3.7 Tonic and Noisy Driving Inputs</a>
 			</div>
 		</div>
 		<div class="sidebar-list">

content/02_background/glossary.html

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 				<a href="/website_redesign/content/03_assumptions/template_model.html">3.1 Template Model</a>
 				<a href="/website_redesign/content/03_assumptions/cortical_column_structure.html">3.2 Cortical Column Structure</a>
 				<a href="/website_redesign/content/03_assumptions/primary_electric_currents.html">3.3 Primary Electrical Currents</a>
-				<a href="/website_redesign/content/03_assumptions/neuron_morphology.html">3.4 Neuron Morphology and Physiology</a>
+				<a href="/website_redesign/content/03_assumptions/neurons_morphology_and_physiology.html">3.4 Neurons: Morphology and Physiology</a>
 				<a href="/website_redesign/content/03_assumptions/synaptic_connectivity.html">3.5 Synaptic Connectivity</a>
-				<a href="/website_redesign/content/03_assumptions/evoked_rhythmic_inputs.html">3.6 Evoked and Rhythmic Driving Inputs</a>
-				<a href="/website_redesign/content/03_assumptions/tonic_noisy.html">3.7 Tonic and Noisy Driving Inputs</a>
+				<a href="/website_redesign/content/03_assumptions/evoked_and_rhythmic_driving_inputs.html">3.6 Evoked and Rhythmic Driving Inputs</a>
+				<a href="/website_redesign/content/03_assumptions/tonic_and_noisy_driving_inputs.html">3.7 Tonic and Noisy Driving Inputs</a>
 			</div>
 		</div>
 		<div class="sidebar-list">

content/02_background/signal_origins.html

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 				<a href="/website_redesign/content/03_assumptions/template_model.html">3.1 Template Model</a>
 				<a href="/website_redesign/content/03_assumptions/cortical_column_structure.html">3.2 Cortical Column Structure</a>
 				<a href="/website_redesign/content/03_assumptions/primary_electric_currents.html">3.3 Primary Electrical Currents</a>
-				<a href="/website_redesign/content/03_assumptions/neuron_morphology.html">3.4 Neuron Morphology and Physiology</a>
+				<a href="/website_redesign/content/03_assumptions/neurons_morphology_and_physiology.html">3.4 Neurons: Morphology and Physiology</a>
 				<a href="/website_redesign/content/03_assumptions/synaptic_connectivity.html">3.5 Synaptic Connectivity</a>
-				<a href="/website_redesign/content/03_assumptions/evoked_rhythmic_inputs.html">3.6 Evoked and Rhythmic Driving Inputs</a>
-				<a href="/website_redesign/content/03_assumptions/tonic_noisy.html">3.7 Tonic and Noisy Driving Inputs</a>
+				<a href="/website_redesign/content/03_assumptions/evoked_and_rhythmic_driving_inputs.html">3.6 Evoked and Rhythmic Driving Inputs</a>
+				<a href="/website_redesign/content/03_assumptions/tonic_and_noisy_driving_inputs.html">3.7 Tonic and Noisy Driving Inputs</a>
 			</div>
 		</div>
 		<div class="sidebar-list">

content/03_assumptions/01_template_model.md

@@ -4,4 +4,33 @@
 #
 # Contributors:
     # Dylan Daniels
--->
+-->
+
+<!-- compare original: https://hnn.brown.edu/under-the-hood/ -->
+
+# 3.1 Template Model
+
+The following sections contain details on the construction of the cells
+and circuits in HNN's canonical **neocortical template model**
+(comprised of a layered cortical column) as well as exogenous driving
+inputs. Each section details the parameters that can currently be
+adjusted in the HHN-GUI for the user's hypothesis testing needs. If
+there are parameters you would like to be able to adjust in the HNN-GUI
+but cannot, we encourage you to submit suggestions to our [Github issues
+page](https://github.com/jonescompneurolab/hnn/issues).
+
+While the adjustable parameters in the HNN-GUI are necessarily limited,
+all parameters and network configurations can be changed based on your
+hypothesis testing goals using NEURON-Python code in our documented and
+supported [HNN-Core repository
+page](https://github.com/jonescompneurolab/hnn-core). Please see
+the ["Getting Started"](https://hnn.brown.edu/getting-started/) page
+for more details on the functionality of HNN-GUI and HNN-Core, and how
+more specialized neocortical template models can be used and developed.
+
+#### [3.2 Cortical Column Structure](./cortical_column_structure.html)
+#### [3.3 Primary Electrical Currents](./primary_electric_currents.html)
+#### [3.4 Neurons: Morphology and Physiology](./neurons_morphology_and_physiology.html)
+#### [3.5 Synaptic Connectivity](./synaptic_connectivity.html)
+#### [3.6 Evoked and Rhythmic Driving Inputs](./evoked_and_rhythmic_driving_inputs.html)
+#### [3.7 Tonic and Noisy Driving Inputs](./tonic_and_noisy_driving_inputs.html)

content/03_assumptions/02_cortical_column_structure.md

@@ -4,4 +4,42 @@
 #
 # Contributors:
     # Dylan Daniels
--->
+-->
+
+<!-- compare original: https://jonescompneurolab.github.io/hnn-under_the_hood/01_cortical-column-structure/01_cortical-column-structure -->
+
+# 3.2 Cortical Column Structure
+
+Neocortical circuits are organized with remarkably similar features across areas and species. These features include a common laminar structure with generalizable cell classes as well as similar local connectivity and input and output connectivity patterns. We have harnessed this generalization into HNN’s foundational neural model that is provided as a template circuit to work with.
+
+<div style="display:block; width:50%; margin: 0 auto;">
+![](./images/netpyne-schematic-tilted-colored.png)
+</div>
+
+<p style="text-align:justify; display: block; margin: 0 auto;width: 90%; font-size: 1em;">
+**Figure 1**: Most importantly, our model contains multi-compartment pyramidal neurons (PN) in supragranular and infragranular layers (layers 2/3 and 5, respectively), whose apical dendrites are spatially aligned and span the cortical layers as shown in the 3D visualization above. The primary electrical current signals simulated in HNN are derived from the intracellular current flow in the PN dendrites (see [3.3 Primary Electrical Currents][] for details). In the figure above, the green neurons represent the layer 2/3 PN and the blue the the layer 5 PN. Note that in both layers, the PN have two basal, one oblique, and one apical dendrite branch, and the layer 2/3 PN have shorter apical dendrites compared to the layer 5 PN.
+</p>
+
+The PN are synaptically coupled to each other and to a subset of inhibitory neurons in each layer in a 3/1 PN-to-interneuron ratio. The inhibitory neurons are simulated with single compartments and represent fast spiking basket cells, and are shown in red in the figure above. Details of the cells and synaptic connectivity structure are given under [3.4 Neurons: Morphology and Physiology][] and [3.5 Synaptic Connectivity][], respectively.
+
+There are several ways to activate the local cortical column with layer specific synaptic (thalamo-cortical, and/or cortical-cortical) and tonic drive, as detailed in both [3.6 Evoked and Rhythmic Driving Inputs][] and [3.7 Tonic and Noisy Driving Inputs][].
+
+The list below provides an overview of key features of the template model provided, further details are outlined in other pages under [3.1 Template Model][]
+
+1. Supragranular layer (layer 2/3) with multi-compartment pyramidal and single compartment inhibitory neurons
+2. Infragranular layer (layer 5) with multi-compartment pyramidal and single compartment inhibitory neurons
+3. A scalable number of neurons per layer with 3/1 PN-to-interneuron ratio (default network contains 100 PN per layer)
+4. Gabaergic (GABAA/GABAB) & Glutamatergic (AMPA/NMDA) synaptic connectivity between local cortical column cells
+5. Membrane voltages simulated with Hodgkin-Huxley type dynamics, with active ionic currents in somatic and dendritic compartments
+6. Layer specific exogenous driving inputs (synaptic and tonic/noisy)
+7. Primary current dipole calculated as net intracellular current flow in PN dendrites (Units: nano-Ampere-meters (nAm))
+
+Of note, the **granular layer is not explicitly included in the template circuit**. This initial design choice was based on the fact that macroscale current dipoles are dominated by PN activity in supragranular, and intragranular layers. Thalamic input to granular layers is presumed to propagate directly to basal and oblique dendrites of PN in layer 2/3 and 5 (see [3.6 Evoked and Rhythmic Driving Inputs][] for details). As the use of our open-source software grows, we hope that other cells and network configurations will be made available as template models to work with.
+
+[3.1 Template Model]: ./template_model.html
+[3.2 Cortical Column Structure]: ./cortical_column_structure.html
+[3.3 Primary Electrical Currents]: ./primary_electric_currents.html
+[3.4 Neurons: Morphology and Physiology]: ./neurons_morphology_and_physiology.html
+[3.5 Synaptic Connectivity]: ./synaptic_connectivity.html
+[3.6 Evoked and Rhythmic Driving Inputs]: ./evoked_and_rhythmic_driving_inputs.html
+[3.7 Tonic and Noisy Driving Inputs]: ./tonic_and_noisy_driving_inputs.html

content/03_assumptions/03_primary_electric_currents.md

@@ -4,4 +4,15 @@
 #
 # Contributors:
     # Dylan Daniels
--->
+-->
+
+<!-- compare original: https://jonescompneurolab.github.io/hnn-under_the_hood/06_primary-electrical-currents/06_primary-electrical-currents -->
+
+# 3.3 Primary Electrical Currents
+
+Axial current flow between any two neighboring model compartments i,j is defined as iaxial = (vi - vj) / raxial , where vi , vj , and raxial are the voltages in compartment i, j, and the resistance between the compartments, respectively. In order to convert this axial current into a dipole signal, we apply a length scaling where the axial current is scaled by the inter-compartment distance along the vertical axis. The length scaling means that for the longer apical dendrites of layer 5 pyramidal neurons, the contribution will be larger than from the shorter layer 2/3 pyramidal neuron apical dendrites. Note that the orientation of the dendrites relative to the vertical axis also influences the contribution to the dipole signal. For example, the horizontally-oriented oblique dendrites which do not have any vertical length component, do not contribute to the dipole signal, whereas for basal dendrites oriented at 45 degrees from the vertical axis, the scaling is $-\sqrt{2}/2$ (note the negative sign is because these dendrites are pointing downward). The contribution from all neighboring compartments within a neuron is integrated and then added to a value across the set of all pyramidal neurons. As a result of the multiplication between axial current and length, the model dipole output signal has the same units of measure as the experimental data (in units of nano-Ampere-meters) and we are then able to directly compare the two signals, as well as precisely tune model parameters to match characteristics of recorded signals (Okada, Wu, and Kyuhou 1997).
+
+
+## Tutorial References
+
+Okada, Y. C., J. Wu, and S. Kyuhou. 1997. "Genesis of MEG Signals in a Mammalian CNS Structure." Electroencephalography and Clinical Neurophysiology 103 (4): 474–85. <https://doi.org/10.1016/S0013-4694(97)00043-6>

content/03_assumptions/04_neurons_morphology_and_physiology.md

@@ -0,0 +1,64 @@
+<!--
+# Title: 3.4 Neurons: Morphology and Physiology
+# Updated: 2024-01-16
+#
+# Contributors:
+    # Dylan Daniels
+-->
+
+<!-- compare original: https://jonescompneurolab.github.io/hnn-under_the_hood/02_morphology-physiology/02_morphology-physiology -->
+
+# 3.4 Neurons: Morphology and Physiology
+
+The template cortical column model contains the following types of neurons:
+
+1. L2/3 multi-compartment pyramidal neurons (PN)
+2. L2/3 single compartment inhibitory neurons
+3. L5 multi-compartment pyramidal neurons
+4. L5 single compartment inhibitory neurons
+
+Membrane voltages in each simulated compartment are calculated using the standard Hodgkin-Huxley parallel conductance equations. Current flow between compartments are calculated using properties of the cable equation [^1].
+
+### Morphology
+
+- Layer 2/3:
+    - PN: 7 compartments including 3 apical dendrites, 3 basal dendrites, 1 soma
+    - Inhibitory basket neurons: single compartment (soma)
+
+- Layer 5:
+    - PN: 9 compartments including 5 apical dendrites, 3 basal dendrites, 1 soma.
+    - As shown below, L5 PNs have longer dendrites than L2/3 PNs. L5 PN somas based in L5 with long apical dendrites reaching into L2/3.
+    - Inhibitory Basket neurons: single compartment (soma).
+    - L2/3 and L5 basket interneurons are identical but their synaptic parameters and local circuit connectivity differs.
+
+<div style="display:block; width:50%; margin: 0 auto;">
+![](./images/detailed-connectivity.png)
+</div>
+
+<table style="border:none">
+  <tr>
+    <td style="border:none" width=>
+    ![](./images/morph-params-01.png)
+    </td>
+    <td style="border:none; vertical-align:middle;">
+    ![](./images/morph-params-02.png)
+    </td>
+  </tr>
+</table>
+
+### Physiology
+
+The following table displays the ion channels and mechanisms in each cell type in the model (**X** indicates the presence of the channel/mechanism in the cell type; for advanced modelers: to see the NEURON simulator equations used in the channel/mechanism, click on the links in the table).
+
+| Cell Type      | Na (fast) | K (fast) | Km | KCa | Ca (L-type) | Ca (T-type) | Ca (decay) | HCN | Leak | Dipole |
+|:--------------:|----------:|:--------:|:--:|:---:|:-----------:|:-----------:|:----------:|:---:|:----:|:------:|
+| Basket         |         X | X        |    |     |             |             |            |     | X    |        |
+| L2/3 Pyramidal |         X | X        | X  |     |             |             |            |     | X    | X      |
+| P5 Pyramidal   |         X | X        | X  | X   | X           | X           | X          | X   | X    | X      |
+
+In the table above, Na (fast) / K (fast) are the fast sodium and potassium channels responsible for generating action potentials. Km is the muscarine sensitive potassium channel, with a relatively slow time-constant and KCa is the calcium-dependent potassium channel, which contributes to hyperpolarization after calcium influx into the cell. The L- and T-type calcium (Ca) channels represent the high-threshold and low-threshold activated calcium channels which together with the hyperpolarization-activated cyclic nucleotide gated channel (HCN) contribute to bursting. Ca decay represents the calcium extrusion pump, which causes intracellular calcium to decay towards a baseline level. Leak represents the passive channel, with constant conductance. Dipole represents the mechanism that takes into account the primary axial current flow within pyramidal neuron dendrites, responsible for the generation of simulated signals comparable to MEG/EEG recordings. For more details see [^2].
+
+## Tutorial References
+
+[^1]: Dayan, P. & Abbott, L. F. Theoretical neuroscience. 806, (Cambridge, MA: MIT Press, 2001).
+[^2]: Jones, S. R. et al. Quantitative analysis and biophysically realistic neural modeling of the MEG mu rhythm: rhythmogenesis and modulation of sensory-evoked responses. J. Neurophysiol. 102, 3554–3572 (2009).