Human Neocortical Neurosolver

Investigators
Stephanie Jones, Matti Hamalainen, Michael Hines
Contact info (email)
Stephanie_Jones@Brownedu
1. Define context(s)
identify/explore new therapies
reveal new biological insights
Current Conformance Level / Target Conformance Level
?
Primary goal of the model/tool/database

Human Neocortical Neurosolver is a software tool providing research and clinicians a method to interpret the cellular and network origin of human EEG and MEG signals. HNN provides a graphical user interface to a neocortical circuit model that accounts for biophysical origins of electrical currents generating EEG/MEG. Data can be directly compared to simulated signals and parameters easily manipulated to develop/test hypotheses on a signal’s origin. Tutorials teach users to simulate commonly measured signals, including event related potentials and brain rhythms.

Biological domain of the model
human EEG and MEG
Structure(s) of interest in the model
Neocortical column model
Spatial scales included in the model
individual multi-compartment cells connected within and across layers to represent a patch of neocortex
Time scales included in the model
sub-millisecond
Other uses for the model (optional)

HNN enables visualization of multi-scale signals including primary current dipoles, layer specific responses, individual cell spiking a somatic voltage traces, and both time and frequency domain responses. These features provide several targets for testing model-derived predictions with invasive recordings or other imaging modalities. 

Additional comments about the model’s context (optional)

HNN’s ability to associate signals across scales makes it a unique tool for translational neuroscience research. 

2. Data for building and validating the model
Data for building the model Published? Private? How is credibility checked? Current Conformance Level / Target Conformance Level
in vitro (primary cells cell, lines, etc.)
ex vivo (excised tissues)
in vivo pre-clinical (lower-level organism or small animal)
in vivo pre-clinical (large animal)
Human subjects/clinical X match to data, and animal recordings
Other: ________________________
Data for validating the model Published? Private? How is credibility checked? Current Conformance Level / Target Conformance Level
in vitro (primary cells cell, lines, etc.)
ex vivo (excised tissues)
in vivo pre-clinical (lower-level organism or small animal) X publication
in vivo pre-clinical (large animal)
Human subjects/clinical
Other: ________________________
3. Validate within context(s)
Who does it? When does it happen? How is it done? Current Conformance Level / Target Conformance Level
Verification code after running simulation root mean squared error between model output and human data
Validation
Uncertainty quantification user
Sensitivity analysis user
Other:__________
Additional Comments
4. Limitations
Disclaimer statement (explain key limitations) Who needs to know about this disclaimer? How is this disclaimer shared with that audience? Current Conformance Level / Target Conformance Level
All conclusions are based on templates neocortical model provided all users website and publication
5. Version control
Current Conformance Level / Target Conformance Level
?
Naming Conventions? Repository? Code Review?
individual modeler yes no
within the lab yes yes no
collaborators yes yes no
6. Documentation
Current Conformance Level / Target Conformance Level
Code commented? yes - Github
Scope and intended use described? yes - https://hnn.brown.edu
User’s guide? yes - https://hnn.brown.edu
Developer’s guide? not yet
7. Dissemination
Current Conformance Level / Target Conformance Level
?
Target Audience(s): “Inner circle” Scientific community Public
Simulations
Models
Software https://www.imagwiki.nibib.nih.gov/resources/models-tools-databases/human-neocortical-neurosolver
Results
Implications of results
8. Independent reviews
Current Conformance Level / Target Conformance Level
?
Reviewer(s) name & affiliation: elife journal
When was review performed? Jan 2020
How was review performed and outcomes of the review? DOI: 10.7554/eLife.51214
9. Test competing implementations
Current Conformance Level / Target Conformance Level
?
Yes or No (briefly summarize)
Were competing implementations tested? no
Did this lead to model refinement or improvement?
10. Conform to standards
Current Conformance Level / Target Conformance Level
?
Yes or No (briefly summarize)
Are there operating procedures, guidelines, or standards for this type of multiscale modeling? yes
How do your modeling efforts conform? neuron modeling
11. (optional) Additional information to support items 1-10

I am not sure how to rate the conformance level for each category.