Transcript of "Neuron-Computer Interface in Dynamic-Clamp Experiments. Models of Neuronal Populations and Visual Cortex"
Neuron-Computer Interface in Dynamic-Clamp Experiments. Models of Neuronal Populations and Visual Cortex. A.V.Chizhov A.F.Ioffe Physical-Technical Institute of RAS, St.-Petersburg, Russia <ul><li>Two-compartment neuron model </li></ul><ul><li>Spiking activity as function of current and conductance in-vivo, in-vitro и in-silico </li></ul><ul><li>“ Firing-clamp” algorithm of estimation of synaptic conductances </li></ul><ul><li>Model of statistical ensemble of Hodgkin-Huxley-like neurons - CBRD </li></ul><ul><li>Model of primary visual cortex. Mappings of models of a hypercolumn. </li></ul>Model Experiment
Models of single neurons and D ynamic- C lamp <ul><li>- Leaky integrate-and-fire model </li></ul><ul><li>- 2-compartmental passive neuron model </li></ul><ul><li>- Hodgkin-Huxley neuron model </li></ul><ul><li>- Control parameters of neuron </li></ul><ul><li>- Dynamic - clamp </li></ul><ul><ul><li>Artificial synaptic current </li></ul></ul><ul><ul><li>Artificial voltage-dependent current </li></ul></ul><ul><ul><li>Synaptic conductance estimation </li></ul></ul>
Leaky Integrate-and-Fire neuron (LIF) E X P E R I M E N T LIF - M O D E L V is the membrane potential ; I is the input (synaptic) current; s is the input (synaptic) conductance; C is the membrane capacity ; g L is the membrane conductance ; V rest is the rest potential ; V T is the threshold potential ; V reset is the reset potential .
Steady-state firing rate dependence on current and conductance LIF, no noise LIF with noise
2-compartmental neuron with somatically registered PSC and PSP Figure Transient activation of somatic and delayed activation of dendritic inhibitory conductances in experiment (solid lines) and in the model (small circles) . A, Experimental configuration. B , Responses to alveus stimulation without (left) and with ( right ) somatic V-clamp. C , In a different cell, responses to dynamic current injection in the dendrite; conductance time course (g) in green, 5-nS peak amplitude , V rev =-85 mV . [F.Pouille, M.Scanziani // Nature , 2004] Parameters of the model: m = 33 ms , = 3.5 , G s = 6 nS in B and 2.4 nS in C <ul><li>Two boundary problems: </li></ul><ul><li>current-clamp to register PSP : </li></ul><ul><li>voltage-clamp to register PSC : </li></ul>Solution: [A.V.Chizhov // Biophysics 2004 ] C V d V d V d V d V s V s I d I s g B A X=0 X=L V d V 0
PSC and PSP: single-compartmental neuron model Parameters found to fit PSC and PSP : How does the model fit to simultaneously recorded PSC and PSP? Parameters found by fitting :
PSC and PSP: Model of concentrated soma and cylindrical dendrite (“model S-D”) [W.Rall, 1959] Two boundary problems: A ) current-clamp to register PSP: B ) voltage-clamp to register PSC, i.e. at the end of dendrite , : Parameters : . at soma , : X=0 X=L X=0 X=L
At dendrite : Subtracting (2), obtain: Eqs. (1),(2) and (3) are equivalent to PSC and PSP: 2- compartmental model B ) Voltage-clamp mode Assume the potential V(X) to be linear, i.e. Model S-D As current through synapse is (1) A ) Current-clamp mode (2) because where is the dendrite conductance Model S-D At soma : (3) At dendrite : V L X=0 X=L V=0 X=0 X=L V L V 0
PSC and PSP: Fitting experimental PSP and PSC from [Karnup and Stelzer, 1999] Parameters found by fitting, given fixed : for 2-compartmental model: for 1-compartmental model: EPSC and EPSP IPSC and IPSP Conclusion. Solution of voltage - and current-clamp boundary problems by 2-compartmental model describes well the PSP-on-PSC dependence.
V – somatic potential; V d – dendritic potential; I s – registered on soma current through synapses located near soma; I d – registered on soma current through synapses located on dendrites; m – membrane time constant; – ratio of dendritic to somatic conductances; G s – specific somatic conductance. C V d V d V d V d V s V s I d I s Figure Transient activation of somatic and delayed activation of dendritic inhibitory conductances in experiment (solid lines) and in the model (small circles) . A, Experimental configuration. B , Responses to alveus stimulation without (left) and with ( right ) somatic V-clamp. C , In a different cell, responses to dynamic current injection in the dendrite; conductance time course (g) in green, 5-nS peak amplitude , V rev =-85 mV . Parameters of the model: m = 33 ms , = 3.5 , G s = 6 nS in B and 2.4 nS in C A B [F.Pouille, M.Scanziani (2004) Nature , v. 429(6993):717-23 ] PSC and PSP: Fitting experimental PSP and PSC from [Pouille and Scanziani, 2004]
h [ Покровский, 19 78] φ ≈0 r V(x) V(x+ Δ x ) i m j m C Внутри Снаружи V g K g Na V Na V rest V K Hodgkin-Huxley model Approximations of ionic channels: Parameters:
Set of experimental data for Hodgkin-Huxley approximations
Approximations for are taken from [L.Graham, 1999]; I AHP is from [N.Kopell et al., 2000] Color noise model for synaptic current I S is the Ornstein-Uhlenbeck process : Model of pyramidal neuron Model with noise E X P Е R I М Е N Т
Control parameters of neuron Property: Neuron is controlled by two parameters [Pokrovskiy , 19 78] [Hodgkin, Huxley, 1952] Voltage-gated channels kinetics : EXPERIMENT
, The case of many voltage-independent synapses
“ Current clamp” , V(t) is registered “ Voltage clamp” , I(t) is registered Whole-cell patch-clamp: Current- and Voltage-Clamp modes const
Warning! The input in current clamp corresponds to negative synaptic conductance! Current-clamp is here!
<ul><li>For artificial passive leaky channel s = const </li></ul><ul><li>For artificial synaptic channel s ( t ) reflects the synaptic kinetics </li></ul><ul><li>For voltage-gated channel s ( V ( t ), t ) is described by ODEs </li></ul>Whole-cell patch-clamp: Dynamic-Clamp mode Conductance clamp (Dynamic clamp): V ( t ) is registered , I ( V,t ) = s ( V,t ) ( V(t) - V us ) + u is injected. 30 μ s Acquisition card
“ Current clamp” Conductance clamp (Dynamic clamp): I ( V(t) )= s ( V(t) - V DC )+u is injected
Dynamic clamp for synaptic current [ Sharp AA, O'Neil MB, Abbott LF, Marder E. Dynamic clamp: computer-generated conductances in real neurons. // J. Neurophysiol. 1993 , 69(3):992-5 ]
Dynamic clamp for spontaneous potassium channels Control artificial K-channels
Experiment : pyramidal cell of visual cortex in vivo Model [Graham, 1999] of CA1 pyramidal neuron Dynamic clamp to study firing properties of neuron
Experiment Model u=7.7 mkA/cm 2 S=0.4 mS/cm 2 u=1.7 mkA/cm 2 S=0.024 mS/cm 2 u=2.7 mkA/cm 2 S=0.06 mS/cm 2 u=4 mkA/cm 2 S=0.15 mS/cm 2 Bottom point Top point
Divisive effect of shunting inhibition is due to spike threshold sensitivity to slow inactivation of sodium channels
Total Response (all spikes during 500ms-step) Only 1 st spikes Only 1 st interspike intervals
Hippocampal Pyramidal Neuron In Vitro Dynamic clamp for voltage-gated current: compensation of I NaP [Vervaeke K, Hu H., Graham L.J., Storm J.F. Contrasting effects of the persistent Na+ current on neuronal excitability and spike timing, Neuron, v49, 2006]
Effect of “negative conductance” by I NaP plays a role of negative conductance
Dynamic clamp for electric couplings between real and modeled neurons Medium electric conductance High electric conductance
Dynamic clamp for synaptic conductance estimations in-vivo 1s 20 mV 10 nS 5 nS Эксперимент [Lyle Graham et al.]: Внутриклеточные измерения patch-clamp в зрительной коре кошки in vivo . Стимул – движущаяся полоска. Preferred direction Null direction
« Firing-Clamp » - method of synaptic conductance estimation Idea : a patched neuron is forced to spike with a constant rate; g E , g I , are estimated from values of subthreshold voltage and spike amplitude . Threshold voltage , V T Peak voltage, V P MODEL 1 ms τ (V)
Measuring system is a neuron: Firing-Clamp EXPERIMENT
Calibration: Firing-Clamp Cell 16_28_28 Cell 16_29_40 Cell 16_33_14 V T V peak EXPERIMENT
Measurements: Firing-Clamp Cell 16_27_50 Cell 16_27_5 V T V peak EXPERIMENT
<ul><li>Dynamic Clamp </li></ul><ul><li>is necessary for measuring firing characteristics of neuron </li></ul><ul><li>helps to create artificial ionic intrinsic or synaptic channels </li></ul><ul><li>is necessary for estimation of input synaptic conductances in-vivo </li></ul>Conclusions
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