TITLE Exponential-function synaptic current, with NET_RECEIVE

COMMENT
This model works with variable time-step methods (although it may not
be very accurate) but at the expense of having to maintain the queues
of spike times and weights.
Andrew P. Davison, UNIC, CNRS, May 2006

Note: converted to Exponential current kernel. 

ENDCOMMENT

DEFINE MAX_SPIKES 1000
DEFINE CUTOFF 20

NEURON {
	POINT_PROCESS ExpSynI
	RANGE tau, i, q
	NONSPECIFIC_CURRENT i
}

UNITS {
	(nA) = (nanoamp)
}

PARAMETER {
	tau = 5 (ms) <1e-9,1e9>

}

ASSIGNED {
	i (nA)
	q
	onset_times[MAX_SPIKES] (ms)
	weight_list[MAX_SPIKES] (nA)
}

INITIAL {
	i  = 0
	q  = 0 : queue index
}

BREAKPOINT {
	LOCAL k, expired_spikes, x
	i = 0
	expired_spikes = 0
	FROM k=0 TO q-1 {
		x = (t - onset_times[k])/tau
		if (x > CUTOFF) {
			expired_spikes = expired_spikes + 1
		} else {
			i = i - weight_list[k] * exp_current(x)
		}
	}
	update_queue(expired_spikes)
}

FUNCTION update_queue(n) {
	LOCAL k
	:if (n > 0) { printf("Queue changed. t = %4.2f onset_times=[",t) }
	FROM k=0 TO q-n-1 {
		onset_times[k] = onset_times[k+n]
		weight_list[k] = weight_list[k+n]
		:if (n > 0) { printf("%4.2f ",onset_times[k]) }
	}
	:if (n > 0) { printf("]\n") }
	q = q-n
}

FUNCTION exp_current(x) {
	if (x < 0) {
		exp_current = 0
	} else {
		exp_current = exp(-x)
	}
}

NET_RECEIVE(weight (nA)) {
	onset_times[q] = t
	weight_list[q] = weight
	if (q >= MAX_SPIKES-1) {
		printf("Error in ExpSynI. Spike queue is full\n")
	} else {
		q = q + 1
	}
}