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Jonathan & Pooya Computational Neuroscience summer school June 17-29, 2007.

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Presentation on theme: "Jonathan & Pooya Computational Neuroscience summer school June 17-29, 2007."— Presentation transcript:

1 Jonathan & Pooya Computational Neuroscience summer school June 17-29, 2007

2 Intrinsic bursting properties of thalamic relay cells. Low threshold calcium conductance: Whenever the neuron is hyperpolarised, the calcium conductance is de-inactivated and if the membrane potential is depolarised (e.g:by an EPSP), the neuron triggers a calcium spike, on the top of which usually other fast Na-K spikes occurs.

3 Hodgkin-Huxley like models… Dynamics of the membrane potential: … and few parameters to characterise it!!!

4 Leaky integrate-and-fire-or-burst : A simple model for the low-threshold Ca2+ current. 2-D discontinuous flow reproducing the low-threshold Ca2+ current at the origin of the bursting properties of thalamic relay cells. Low Threshold (-65mV) : Boundary under which I T is de- inactivated. Classical Threshold (-45mV) : Boundary where you trigger a usual NaK fast spike and then come back to reset for a refractory time. Dynamic of the model :

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7 LIFB Spontaneous noise LIFB Spontaneous noise Excitatory drive LIFB Spontaneous noiseInhibitory drive Goal: Detecting the existence of the Driver signal. Is there a driver signal there or is the input of the LIFB entirely coming from noise? Independent variables: 1- noise frequency (rate of Poisson process= 10-1000 Hz : 20 log steps) 2- Driver frequency (rate of Poisson process= 10-1000 Hz : 20 log steps) 3- Driver weight (no Driver Or excit. Or inhib.) Trial #100 for each combination of independent variables: different input times Dependant variable: output spike count and its distribution across 100 trials

8 10 100 1000 Logarithmic increase in the frequency of the Driver Spike count in 200 ms Color code: Trial count out of 100 No Driver Excit Inhib

9 10 100 1000 Logarithmic increase in the frequency of the Driver Spike count in 200 ms Color code: Trial count out of 100 No Driver Excit Inhib

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12 10 100 1000 Logarithmic increase in the frequency of the Driver Spike count in 200 ms Color code: Trial count out of 100 No Driver Excit Inhib

13 10 100 1000 Logarithmic increase in the frequency of the Driver Spike count in 200 ms Color code: Trial count out of 100 No Driver Excit Inhib

14 10 100 1000 Logarithmic increase in the frequency of the Driver Spike count in 200 ms Color code: Trial count out of 100 No Driver Excit Inhib

15 10 100 1000 Logarithmic increase in the frequency of the Driver Spike count in 200 ms Color code: Trial count out of 100 No Driver Excit Inhib

16 10 100 1000 Logarithmic increase in the frequency of the Driver Spike count in 200 ms Color code: Trial count out of 100 No Driver Excit Inhib

17 10 100 1000 Logarithmic increase in the frequency of the Driver Spike count in 200 ms Color code: Trial count out of 100 No Driver Excit Inhib

18 10 100 1000 Logarithmic increase in the frequency of the Driver Spike count in 200 ms Color code: Trial count out of 100 No Driver Excit Inhib

19 10 100 1000 Logarithmic increase in the frequency of the Driver Spike count in 200 ms Color code: Trial count out of 100 No Driver Excit Inhib

20 10 100 1000 Logarithmic increase in the frequency of the Driver Spike count in 200 ms Color code: Trial count out of 100 No Driver Excit Inhib

21 10 100 1000 Logarithmic increase in the frequency of the Driver Spike count in 200 ms Color code: Trial count out of 100 No Driver Excit Inhib

22 10 100 1000 Logarithmic increase in the frequency of the Driver Spike count in 200 ms Color code: Trial count out of 100 No Driver Excit Inhib

23 10 100 1000 Logarithmic increase in the frequency of the Driver Spike count in 200 ms Color code: Trial count out of 100 No Driver Excit Inhib

24 10 100 1000 Logarithmic increase in the frequency of the Driver Spike count in 200 ms Color code: Trial count out of 100 No Driver Excit Inhib

25 10 100 1000 Logarithmic increase in the frequency of the Driver Spike count in 200 ms Color code: Trial count out of 100 No Driver Excit Inhib

26 10 100 1000 Logarithmic increase in the frequency of the Driver Spike count in 200 ms Color code: Trial count out of 100 No Driver Excit Inhib

27 10 100 1000 Logarithmic increase in the frequency of the Driver Spike count in 200 ms Color code: Trial count out of 100 No Driver Excit Inhib

28 10 100 1000 Logarithmic increase in the frequency of the Driver Spike count in 200 ms Color code: Trial count out of 100 No Driver Excit Inhib

29 10 100 1000 Logarithmic increase in the frequency of the Driver Spike count in 200 ms Color code: Trial count out of 100 No Driver Excit Inhib

30 10 100 1000 Logarithmic increase in the frequency of the Driver Spike count in 200 ms Color code: Trial count out of 100 No Driver Excit Inhib

31 Area under ROC close to 1 a b cd P FA P hit a b c d P FA P hit Detection: Right Side: spike count larger than criterion= Driver detected. Excitatory driver and Burst-inducing inhibitory driver Detection Rule: Left Side spike count less than criterion= Driver detected. Inhibitory driver abcd abcd

32 Area under ROC close to 0.5 Detection: Right Side: spike count larger than criterion= Driver detected. Excitatory driver and Burst-inducing inhibitory driver Detection Rule: Left Side spike count less than criterion= Driver detected. Inhibitory driver abcd abcd a b c d P FA P hit a b c d P FA P hit

33 The area under the ROC curve was calculated for any combination of noise level with the level of excitatory input. 10 100 1000 1000 100 10 Hz Excitatory Drive Hz Spontaneous noise Results of the original article

34 The area under the ROC curve for any combination of noise level with the level of inhibitory input. Hz Inhibitory Drive Hz Spontaneous noise Results of the original article

35 For calculating the area under the ROC curve for detection of Inhibitory inputs, we calculated with both right-side (burst) and left-side (inhibituion) detection assumptions. For any single data point (noise X driver) the maximum of the two was taken as the result of ROC calculation. We only guessed this should be the methods that the authors have used because they have referred the reader to an internet website that has expired for the details of their methods. Map of the left-side detection versus right-side:

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