NumPy Population Simulation

Simulate N=50 neurons using a 2D NumPy array and plot mean ± std.

Your task:
1. V = np.zeros((N, T)) where N=50, T=int(t_max/dt)=150
2. Set initial condition: V[:, 0] = el
3. Double loop — outer over neurons, inner over time steps (range(T-1))
4. Update: V[n, t_step+1] = V[n, t_step] + (dt/tau)*(el - V[n,t_step] + r*i_t)
5. Spike reset: if V[n, t_step+1] >= vth: V[n, t_step+1] = vr
6. After loop:
   - v_mean = np.mean(V, axis=0) * 1000  (mV)
   - v_std = np.std(V, axis=0) * 1000    (mV)
7. Plot mean line + shaded ±std band with ax.fill_between()