1/15 Cliff Kerr | Multiscale model of Parkinson’s disease | Jan. 30 th , 2013 How Parkinson’s disease affects cortical information flow: A multiscale model Cliff Kerr Complex Systems Group University of Sydney Neurosimulation Laboratory State University of New
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How Parkinson’s disease affects cortical information flow: A multiscale model
How Parkinson’s disease affects cortical information flow: A multiscale model. Cliff Kerr. Neurosimulation Laboratory State University of New York. Complex Systems Group University of Sydney. Parkinson’s disease. Tremor (typically 3-6 Hz ) Bradykinesia (slowness of movement) - PowerPoint PPT Presentation
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How Parkinson’s disease affects cortical information
flow: A multiscale model
Cliff KerrComplex Systems Group
University of SydneyNeurosimulation
LaboratoryState University of New
York
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Parkinson’s disease
• Tremor (typically 3-6 Hz)
• Bradykinesia (slowness of movement)
• Bradyphrenia (slowness of thought)
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Spiking network model
• Event-driven integrate-and-fire model
• 6-layered cortex, 2 thalamic nuclei
• 15 cell types
• 5000 neurons
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• Anatomy & physiology based on experimental data
• Adaptable to different brain regions based on cell populations/ connectivities
• Model generates realistic neuronal dynamics; demonstrated control of virtual arm
𝑉 𝑛 (𝑡 )=𝑉𝑛 ( 𝑡0 )+𝑤𝑠 (1−𝑉 𝑛 (𝑡 0 )𝐸𝑖
)𝑒(𝑡 0−𝑡 )/𝜏 𝑖
Synaptic input:
𝑤𝑠𝑓=𝑤𝑠
𝑖 +𝛼𝑠 (Δ𝑡 )𝑒−∨𝛥𝑡∨¿𝜏 𝐿
Synaptic plasticity:
Spiking network model
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Spiking network model• Connectivity matrix based on rat, cat, and
macaque data
• Strong intralaminar and thalamocortical connectivity
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Neural field model
• Continuous firing rate model
• 9 neuronal populations
• 26 connections
• Field model activity drives network model
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• Neurons averaged out over 1 mm, allowing the whole brain to be represented by a grid of nodes
• Includes major cortical and thalamic cell populations, plus basal ganglia
• Demonstrated ability to replicate physiological firing rates and spectra:
Population firing response:
Transfer function:
Neural field model
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Neural field model• GPi links basal ganglia to rest of brain:
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• Firing rates in the field model drive an ensemble of Poisson processes, which then drive the network
From field to network
NetworkField
p1
p2
p3
Poisson
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Field model dynamics
• PD disrupts coherence between basal ganglia nuclei
• PD changes spectral power in beta/gamma bands
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Network model dynamics
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Network spectra
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Burst probability
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Granger causality
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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 dynamics–Where possible, realistic inputs should be
used instead of white noise for driving network models
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