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By Annemari de Silva Supervised by Prof. Peter Robinson
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Corticothalamic Model: A Simple Model to explain the Alpha Rhythm EEG: measures electrical activity of brain. Driving Questions: Why this behaviour at ~10Hz? Is there a simple model to describe it? What mainly contributes to it? Different explanatory models Our simplified model – Corticothalamic Resonance Fig 1. Robinson, P.A. et al. Multiscale brain Modelling 2005 Image 1. The VibSec-method prevents traffic accidents, caused by sleepy drivers. http://www.vibsec.se/solution.html α rhythm Fig 1. Power Spectrum from EEG (electroencephalogram) CORTEX THALAMUS
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G ee – Gain from activity in cortex G esn – Gain from incoming signals G ese – Gain from cortex-thalamus travel CORTEX (e) THALAMUS (s) Mechanism of Resonance sensory neurons (n) ‘Spreading out’ term
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Frequency (Hz) Mathematical Model: Transfer Function, q 2 and Power Spectrum. Using mathematical model, vary parameters Observe effects on graphs and find physiological correspondence
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Fig 6: a) Imaginary (q 2 ) vs. Real (q 2 ) b) Power vs. Frequency t 0 low t 0 high Varying t 0 (time delay for cortex-thalamus travel) Real (q 2 ) Frequency (Hz) Fig 5: a) Imaginary (q 2 ) vs. Real (q 2 ) b) Power vs. Frequency
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Varying gamma, alpha and gains Fig 3. Power Spectrum – GAINS varied Fig 2. Power Spectrum – ALPHA varied low high G ese high G ee low G ese low G ee high Frequency (Hz) low Fig 1. Power Spectrum – GAMMA varied high Frequency (Hz) ‘Spreading out’ term Damping term G ee – Gain from activity in cortex G ese – Gain from cortex-thalamus travel
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Overview What causes alpha rhythm? Resonance effect between cortex and thalamus. Many physical factors involved in total time delay and amplitude in feedback mechanism. How good is corticothalamic model? Very! Look at graph! Our version is simplified to get basic gist of contribution of parameters. Efficiency in explaining most aspects of EEG power spectrum Maths corresponds to physiology Simplicity of model Relevance to other fields. Local vs global connections
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