Algorithm 1.

The flow of our models which interprets the architecture shown in Figure 6.

1:	Initialize: S ← the parameters of all spiking neurons;
	W ← the weights of each other neuron in our neural circuit;
	T ← An array which contains the time when the external stimulus begins
	to appear;
	r ← drift rate;
	t ← time(ms)
	Iexternal ← the current of external stimulus;
	Vthreshold ← the firing rate threshold of relative-timing cells for TDDM
	Vrelative ← the firing rate of relative-timing cells
2:	while t>0 do
3:	if t in synchronous phase then
4:	if t in T then
5:	Iexternal stimulates the input cells for only 100 ms(gray line)
6:	if t! = 0 AND t in T then
7:	if Vrelative < Vthreshold then
8:	Implement the Equations 4 and 6 to modify r.
9:	else
10:	Implement the equation 6 to modify r.
11:	end if
12:	And then according to equation 7 update w in the connections between absolute-timing cells and relative-timing cells
13:	end if
14:	else
15:	if Vrelative > Vthreshold then
16:	Implement the equation 5 to obtain Δr:
17:	end if
18:	end if
19:	end if
20:	According to the architecture in Figure 6, compute all the neurons.
21:	Compute the state of the input cells using equation 1.
22:	Compute the state of absolute-timing cells using equation 1.
23:	Compute the state of the time-accumulator cells using equation 1.
24:	Compute the state of the relative-timing cells using equation 2.
25:	Compute the state of the motor cells using equation 1.
26:	Compute the state of the other cells using equation 1.
27:	end while