FIGURE 2.1-4 Block diagram of a nonlinear, time-variable system in which the input is a random point process, yt. yt is weighted and passed through a simple, one-pole low-pass filter. After having "membrane noise" added to it, the signal u2 is the input to an RPFM spike generator with a variable firing threshold, q>2. is the sum of a dc level, q>20, and q2, the output of a two-pole low-pass filter whose input is the RPFM system output pulses. Thus, the faster the RPFM spike generator fires, the larger the Thus, if the system is firing on the peaks of Vmn alone, q>2 increases to minimize noise-induced firing.
" IPFM VPC GENERATES RANDOM QUM EVENTS: dv1 = rin - z1 z1 = y1*phi1/tau w1 = IF v1 > phi1 THEN 1 ELSE 0 s 1 = DELAY (w1, tau) x1 = w1 - s1
" THE RPFM SGL
dv2 = -c2*v2 + c2*ein + vmn - z2 " Vmn added to v2 = Vm. z2 = y2*phi2/tau w2 = IF v2 > phi 2 THEN 1 ELSE 0 s2 = DELAY (w2, tau) x2 = w2 - s2
" NOISE GENERATION:
dr1 = -b1*r1 + SD1*NORM(t) " Membrane noise, 2-pole filtered.
dr2 = -b3*r2 + SD2*NORM(t + Td) " Input noise = in drive input events, din = -b4*in + r2
rin = IF in > 0 THEN in ELSE 0 " Rectified input noise to IPFM random " event generator.
dp2 = -a2*p2 + z2 *K2 " 2-pole ballistic LPF for threshold feedback dq2 = -a3*q2 + p2
dein = -a1*ein + el " LPF to condition random event impulses.
" Sensory neuron SGL threshold is sum of membrane noise + slow NFB term.
" CONSTANTS: phi1:2.5 phi20:0.75 Do1:15.
K2 : . 2 " Adjusts gain of BF. Kf: 1" Kf = 0 turns off NFB. a1:1.
a2:.1" a,b,c units are radians/s. a3:.05 b1:1 b2:2 b3:1. b4:1. c2:.05 Td:100 tau:.001 SD1:50 SD2:8. O1:-1.5 O2:-1 zero:0
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