the sleep-wake cycle: constraining steady states by electroencephalogram analysis modelling neurons...

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The sleep-wake cycle: constraining steady states by electroencephalogram analysis Modelling neurons and the brain EEG and stability analysis Constraints on sleep-wake states Physiology and the sleep-wake cycle Anthony L. Krensel

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Page 1: The sleep-wake cycle: constraining steady states by electroencephalogram analysis  Modelling neurons and the brain  EEG and stability analysis  Constraints

The sleep-wake cycle:constraining steady states by

electroencephalogram analysis

Modelling neurons and the brainEEG and stability analysisConstraints on sleep-wake statesPhysiology and the sleep-wake cycle

Anthony L. Krensel

Page 2: The sleep-wake cycle: constraining steady states by electroencephalogram analysis  Modelling neurons and the brain  EEG and stability analysis  Constraints

The brain:

Cortex: “higher order” functions... Thalamus: filters information to cortex Brainstem: functions include arousal

Continuum Modelling: Modelling neural populations by

average properties and significant connections

Page 3: The sleep-wake cycle: constraining steady states by electroencephalogram analysis  Modelling neurons and the brain  EEG and stability analysis  Constraints

Neuronal signalling

Receives

signal

Propagates

down axon

Synapse:

Terminals transmit

neurochemicals,

onto next neuron

Response to

Signal

Page 4: The sleep-wake cycle: constraining steady states by electroencephalogram analysis  Modelling neurons and the brain  EEG and stability analysis  Constraints

Neuronal signalling

Receives

signal

Propagates

down axon

Synapse:

Terminals transmit

neurochemicals,

onto next neuron

Response to

Signal

Page 5: The sleep-wake cycle: constraining steady states by electroencephalogram analysis  Modelling neurons and the brain  EEG and stability analysis  Constraints

The EEG

S2

Spectrum

EC Spectrum

Awake, eyes closed (EC)

•Enhancement at low f (gold)

•1/f behaviour (green)

•Strong alpha peak (red)

•Small beta peak (orange)

Sleep, stage 2 (S2)

•Enhancement at low f (gold)

•1/f behaviour (green)

•Spindle peak/peaks (blue)

3

Page 6: The sleep-wake cycle: constraining steady states by electroencephalogram analysis  Modelling neurons and the brain  EEG and stability analysis  Constraints

The EIRS Model

Cortex: ● Excitatory (e)● Inhibitory (i)

Thalamus:● Reticular nucleus (r)● Relay nuclei (s)

Subthalamic Input (n)

Can find steady state firing rates

Page 7: The sleep-wake cycle: constraining steady states by electroencephalogram analysis  Modelling neurons and the brain  EEG and stability analysis  Constraints

Steady State

Steady state firing rates d/dt = 0

so , , , can be computed.

Nonlinear relationship: and

The linear gains are

Page 8: The sleep-wake cycle: constraining steady states by electroencephalogram analysis  Modelling neurons and the brain  EEG and stability analysis  Constraints

The EEG spectrum and Stability

Instability = power in single frequency diverges

First approximation to spectrum: given by squared modulus of

transfer function:

Page 9: The sleep-wake cycle: constraining steady states by electroencephalogram analysis  Modelling neurons and the brain  EEG and stability analysis  Constraints

Stability Analysis Instability Dispersion relation Most unstable case: k = 0

Page 10: The sleep-wake cycle: constraining steady states by electroencephalogram analysis  Modelling neurons and the brain  EEG and stability analysis  Constraints

EEG analysis

Examine very low

frequency regime

,

, ,

Page 11: The sleep-wake cycle: constraining steady states by electroencephalogram analysis  Modelling neurons and the brain  EEG and stability analysis  Constraints

A constrained parameter space (EC)

Page 12: The sleep-wake cycle: constraining steady states by electroencephalogram analysis  Modelling neurons and the brain  EEG and stability analysis  Constraints

Constraining EC

Page 13: The sleep-wake cycle: constraining steady states by electroencephalogram analysis  Modelling neurons and the brain  EEG and stability analysis  Constraints

Constrained parameter space (S2)

Page 14: The sleep-wake cycle: constraining steady states by electroencephalogram analysis  Modelling neurons and the brain  EEG and stability analysis  Constraints

Constraining S2

Page 15: The sleep-wake cycle: constraining steady states by electroencephalogram analysis  Modelling neurons and the brain  EEG and stability analysis  Constraints

Qualitative Results

Firing rates change as expected

Reticular sleep-wake switch: active in sleep

Relay nuclei inputs increase

Strong intra-cortical connectivity increase

Page 16: The sleep-wake cycle: constraining steady states by electroencephalogram analysis  Modelling neurons and the brain  EEG and stability analysis  Constraints

Arousal projection to the cortex

Page 17: The sleep-wake cycle: constraining steady states by electroencephalogram analysis  Modelling neurons and the brain  EEG and stability analysis  Constraints

Inputs to the model

Page 18: The sleep-wake cycle: constraining steady states by electroencephalogram analysis  Modelling neurons and the brain  EEG and stability analysis  Constraints

Summary and the Future

Constrained EC/S2 states in x,y,z Demonstrated links to physiology of sleep-wake Found a thalamic reticular sleep-wake switch

Extend this work to encompass sleep cycle Results guide modelling of sleep-wake inputs Ultimately link EIRS model to existing brainstem

models: e.g. the Phillips-Robinson model, the Circadian Oscillator, etc.

Page 19: The sleep-wake cycle: constraining steady states by electroencephalogram analysis  Modelling neurons and the brain  EEG and stability analysis  Constraints

Acknowledgements

Prof. Peter Robinson Dr. Peter Drysdale

Page 20: The sleep-wake cycle: constraining steady states by electroencephalogram analysis  Modelling neurons and the brain  EEG and stability analysis  Constraints

Extra equations (basic model equations)

Page 21: The sleep-wake cycle: constraining steady states by electroencephalogram analysis  Modelling neurons and the brain  EEG and stability analysis  Constraints

More equations