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Multiscale modeling of cortical information flow in Parkins Multiscale modeling of cortical information flow in Parkins

Multiscale modeling of cortical information flow in Parkins - PowerPoint Presentation

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Multiscale modeling of cortical information flow in Parkins - PPT Presentation

disease Cliff Kerr Complex Systems Group University of Sydney Neurosimulation Laboratory State University of New York Parkinsons disease Tremor typically 36 Hz Bradykinesia slowness of movement ID: 560242

network model firing field model network field firing cortical dynamics spiking neural populations brain based cell basal disease coherence

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Slide1

Multiscale modeling of cortical information flow in Parkinson's disease

Cliff Kerr

Complex Systems GroupUniversity of Sydney

Neurosimulation LaboratoryState University of New YorkSlide2
Parkinson’s disease

Tremor (typically 3-6 Hz

)Bradykinesia (slowness of movement)Bradyphrenia (slowness of thought)Slide3

Spiking network model

Event-driven integrate-and-fire model6-layered cortex, 2 thalamic

nuclei15 cell types 5000 neuronsSlide4
A

natomy & physiology based on experimental dataAdaptable to different brain regions based on cell populations/ connectivitiesModel generates realistic neuronal dynamics; demonstrated control of virtual arm

 

Synaptic input:

 

Synaptic plasticity:

Spiking network modelSlide5
Spiking network model

Connectivity matrix based on rat, cat, and macaque data

Strong intralaminar and thalamocortical connectivity Slide6

Neural field model

Continuous firing rate model9 neuronal populations

26 connectionsField model activity drives network modelSlide7

Neurons averaged out over 1 mm, allowing the whole brain to be represented by a grid of nodesIncludes major cortical and thalamic cell populations,

plus basal gangliaDemonstrated ability to replicate physiological firing rates and spectra:Population firing response:

Transfer function:

 

Neural field modelSlide8
Neural field model

GPi links basal ganglia to rest of brain:Slide9
Firing rates in the field model drive an ensemble of Poisson processes, which then drive the network

From field to network

Network

Field

p

1

p

2

p

3

PoissonSlide10

Field model dynamics

PD disrupts coherence between basal ganglia nucleiPD changes spectral power in beta/gamma bandsSlide11

Network model dynamicsSlide12

Network spectraSlide13

Burst probabilitySlide14

Granger causalitySlide15
Summary

Model can reproduce many features of Parkinson’s disease (e.g. reduced cortical firing, increased coherence)Granger causality between cortical layers was markedly reduced in PD – possible explanation of bradyphrenia (…and bradykinesia?)Different input drives had a

major effect on the model dynamicsWhere possible, realistic inputs should be used instead of white noise for driving network models Slide16

Acknowledgements

Sacha J. van Albada Samuel A. NeymotinGeorge

L. Chadderdon III Peter A. RobinsonWilliam W. Lytton