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Get Started
Installation
Quickstart
Key Concepts
Learning Paths
Learn
Tutorials
Your First Simulation
Models and Dynamics
Noise and Stochastic Runs
Building a Network
Forward Models
Fitting with Gradients
Gradient-Free Fitting
Training on Tasks
How-To Guides
Choose a Model
Working with Units
Batch and Accelerate
Custom Coupling
Compose a Custom Objective
Run Parameter Sweeps
Analyze Results (FC / FCD / spectra)
Concepts
What Is a Neural Mass Model?
Why Differentiable?
Architecture Overview
Coupling and Delays
From Activity to Signals
Showcase
Data-Driven Modeling
Data-Driven Modeling Roadmap
Gallery
Hopf Oscillator
Van der Pol Oscillator
Stuart-Landau Oscillator
FitzHugh-Nagumo Model
Wilson-Cowan Model
Jansen-Rit Model
Wong-Wang Decision Model
Montbrio-Pazo-Roxin Model
Coombes-Byrne (Next-Generation Neural Mass)
Larter-Breakspear Model
Epileptor (Seizure Dynamics)
Generic 2D Oscillator
Wong-Wang Excitatory-Inhibitory (Dynamic Mean Field)
Lorenz System
Linear Node
Kuramoto Phase Oscillators
Harmonic Oscillator Recurrent Network (HORN)
Resting-State MEG: A Whole-Brain Modeling Pipeline
Fitting an EEG Model with Gradients
Seizure Dynamics with the Epileptor
Perceptual Decision-Making with Wong-Wang
Training a HORN Network on a Cognitive Task
Reference
API Reference
Neural Mass Models
XY_Oscillator
HopfStep
VanDerPolStep
StuartLandauStep
KuramotoNetwork
FitzHughNagumoStep
ThresholdLinearStep
WilsonCowanStep
JansenRitStep
JansenRitTR
WongWangStep
WilsonCowanNoSaturationStep
WilsonCowanSymmetricStep
WilsonCowanSimplifiedStep
WilsonCowanLinearStep
WilsonCowanDivisiveStep
WilsonCowanDivisiveInputStep
WilsonCowanDelayedStep
WilsonCowanAdaptiveStep
WilsonCowanThreePopBase
WilsonCowanThreePopulationStep
MontbrioPazoRoxinStep
CoombesByrneStep
LarterBreakspearStep
EpileptorStep
Generic2dOscillatorStep
WongWangExcInhStep
LorenzStep
LinearStep
Noise Processes
Noise
GaussianNoise
WhiteNoise
OUProcess
BrownianNoise
ColoredNoise
PinkNoise
BlueNoise
VioletNoise
Coupling Mechanisms
DiffusiveCoupling
AdditiveCoupling
SigmoidalCoupling
HyperbolicTangentCoupling
SigmoidalJansenRitCoupling
brainmass.diffusive_coupling
brainmass.additive_coupling
brainmass.sigmoidal_coupling
brainmass.hyperbolic_tangent_coupling
brainmass.sigmoidal_jansen_rit_coupling
brainmass.laplacian_connectivity
brainmass.LaplacianConnParam
Forward Models
BOLDSignal
LeadFieldModel
EEGLeadFieldModel
MEGLeadFieldModel
LeadfieldReadout
Observation Models
HRFKernel
FirstOrderVolterraHRFKernel
GammaHRFKernel
DoubleExponentialHRFKernel
MixtureOfGammasHRFKernel
HRFBold
TemporalAverage
HORN Models
HORNStep
HORNSeqLayer
HORNSeqNetwork
Orchestration
brainmass.Network
brainmass.Simulator
brainmass.Fitter
brainmass.FitResult
brainmass.objectives.timeseries_rmse
brainmass.objectives.fc_corr
brainmass.objectives.fc_rmse
brainmass.objectives.cosine_sim
brainmass.objectives.fcd
brainmass.objectives.fcd_distribution
brainmass.objectives.ks_distance
brainmass.objectives.wasserstein_1d
brainmass.objectives.fcd_ks
brainmass.objectives.fcd_wasserstein
brainmass.objectives.combine
Datasets
brainmass.datasets.register_dataset
brainmass.datasets.list_datasets
brainmass.datasets.load_dataset
brainmass.datasets.Connectome
brainmass.datasets.Signal
brainmass.datasets.delayed_match_task
Visualization
brainmass.viz.plot_timeseries
brainmass.viz.plot_phase_portrait
brainmass.viz.plot_connectivity
brainmass.viz.plot_functional_connectivity
brainmass.viz.plot_power_spectrum
Utilities & Types
brainmass.sys2nd
brainmass.sigmoid
brainmass.bounded_input
brainmass.process_sequence
brainmass.delay_index
brainmass.list_models
brainmass.ModelInfo
Developer Guide
Contributing Guide
Architecture
Creating Custom Models
Building a Data-Driven Workflow
Creating a Coupling
Creating an Objective
Extending Noise Processes
Testing
Documentation
Additional Resources
FAQ and Troubleshooting
Release Notes
.rst
.pdf
Noise
Contents
Noise
Noise
#
class
brainmass.
Noise
(
in_size
,
name
=
None
)
#
Return type
:
Any
Contents
Noise
