electronic neuron model
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Electronic Neuron Model
Chapter 10
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Membrane Modeling
• Nernst & Goldman equation – Resting potential
• Cable model of axon: – General cable equation
– Subthreshold response & pulse propagation
• Parallel conductance model – Behavior during activation
– Conductance variation
• Strongly tied to the concepts of electronic circuits
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Physical Realization
• Realize physically the equivalent circuits
1. Analysis to verify model
– Really behave as same as the excitable tissue
– Improve understanding
– Adjust properties of the model
2. Constructing electronic circuits
– Whose behavior similar with real tissue
– Information processing similar with nature • Neuro-computing
cf: computer simulation
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Classification of Neuron Model
• Based on structure of model
– Mathematical, Imaginary construction by physical laws, Physical model
• In conceptual dimensions
– Structure, Function, Evolution, Position in hierarchy
• According to physiological level
– Intraneuronal, Single neuron, Synapse, Neural interaction, Psychophysiological
• According to model parameters
– Resting, Stimulus, Recovery, Adaptation
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Membrane Model
• Electronic realization of membrane excitation mechanism
– Theoretical model of Hodgkin & Huxley model
• Circuit modeling for conductance
– Between two nodes: inside & outside
– By active filters with transistors
• Parameters modification by variable resistors
• Voltage multiplied by 100: (10mV 1V)
– Other quantities in original values
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Lewis Membrane Model
Block diagram of the Lewis membrane model
Circuit for potassium conductance
Circuit for sodium conductance
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Response with Lewis Model
Complete Lewis membrane model
Single action pulse
A series of action pulse
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Roy Membrane Model
• Simplicity than accuracy
• Neurofet
– Simplified with FET for conductance simulation • Easy implementation of amplifier with FET
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Response with Roy Model
• Reasonably close the experimental results
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Lewis Neuron Model
• Inclusion of excitatory & inhibitory synapse
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Responses
Sodium & potassium current
Lewis
H &H
Lewis
H &H
Peak Na+ current
Steady state K+ current
Action pulse & corresponding ion currents
• Very similar with H-H model • Approximate within a order
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Harmon Neuron Model
• Too complex to simulate neural networks
– Internal construction is not important
• Simplified pulse generation with multivibrator – Excitatory/inhibitory
– Drive up to 100 neurons
• Investigated 7 properties of neuron
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Properties of Harmon Model
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Properties of Harmon Model
Pulse obeys all-or-none law Width varies with frequency in some degree
Time from stimulus onset to output Fn of integration & refractory period
Response to constant input voltage
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Propagation Model
• Inclusion of axial resistance
– Electronic realization of linear core-conductor model
6-unit chain
10-unit ring
Simulate pulse propagation in squid axon 17m/s (14~23m/s in experiments)
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IC Realization
• Electronic neuron model in large quantity
– Electronic neuron as processing elements
• Stefan Prange model(1988,1990)
– Neuron with 8 synapses, with 300 transistors
• Misa Mahowald model(1991)
– CMOS and VLSI technology
– Simulated spikes in neocortical neurons accurately
– 0.1mm2 with 60uW power dissipation
– 100~200 neurons in 1cm1cm die