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Tutorials and Guides
Tutorials
Installation
Quickstart
Choosing Models
Working with Units
Building Multi-Region Networks
Adding Coupling
Forward Modeling
Parameter Fitting
Examples
Getting Started with BrainMass
The Wilson-Cowan model
Wilson-Cowan Model: Limit Cycle Oscillations
The Hopf oscillator model
Jansen–Rit Single-Node Simulation
The FitzHugh-Nagumo Model
The Stuart-Landau Oscillator
The Van der Pol Oscillator
Comparing 2D Oscillators
Exploring Harmonic Oscillator Network Dynamics
The Wong-Wang Decision-Making Model
The QIF Mean-Field Model
Comprehensive Wilson-Cowan Model Variants: Simulation & Comparison
Modeling resting-state MEG data
Grid Search using
vmap
Parameter Optimization with
Nevergrad
Parameter Optimization with
Scipy
Developer Guide
Contributing Guide
Architecture
Creating Custom Models
Extending Noise Processes
Testing
Documentation
Additional Resources
FAQ and Troubleshooting
API Reference
Neural Mass Models
HopfStep
VanDerPolStep
StuartLandauStep
KuramotoNetwork
FitzHughNagumoStep
ThresholdLinearStep
WilsonCowanStep
JansenRitStep
WongWangStep
MontbrioPazoRoxinStep
Noise Processes
GaussianNoise
WhiteNoise
OUProcess
BrownianNoise
ColoredNoise
PinkNoise
BlueNoise
VioletNoise
Coupling Mechanisms
DiffusiveCoupling
AdditiveCoupling
brainmass.diffusive_coupling
brainmass.additive_coupling
brainmass.laplacian_connectivity
brainmass.LaplacianConnParam
Forward Models
BOLDSignal
LeadFieldModel
EEGLeadFieldModel
MEGLeadFieldModel
HORN Models
HORNStep
HORNSeqLayer
HORNSeqNetwork
Utility Functions
brainmass.sys2nd
brainmass.sigmoid
brainmass.bounded_input
brainmass.process_sequence
Release Notes
.rst
.pdf
BlueNoise
Contents
BlueNoise
BlueNoise
#
class
brainmass.
BlueNoise
(
*
args
,
**
kwargs
)
#
Blue (1/f^2) noise.
Return type
:
Any
Contents
BlueNoise
