Compartments

Compartments

This is code in leabra for treating a particular projection type (emer.Forward) as a separately modulated input. The standard leabra code also contains separate integration of inhibition vs. excitation, which is similar, but this is how you can do it separately:

// RecvGIncPrjn increments the receiver's GeRaw or GiRaw from that of all the projections.
// Increments GeFwd separate from rest of GeRaw.
func (ly *AttnLayer) RecvGIncPrjn(pj *leabra.Prjn, ltime *leabra.Time) {
	if ly.Attn.GeMin < 1 && pj.Typ == emer.Forward {
		for ri := range ly.Neurons {
			gfw := &ly.GeFwds[ri]
			*gfw += pj.GInc[ri]
			pj.GInc[ri] = 0
		}
	} else {
		pj.LeabraPrj.RecvGInc()
	}
}

// RecvGInc rewritten to use the above layer-level method instead of going straight to the Prjn
func (ly *AttnLayer) RecvGInc(ltime *leabra.Time) {
	for _, p := range ly.RcvPrjns {
		if p.IsOff() {
			continue
		}
		ly.RecvGIncPrjn(p.(leabra.LeabraPrjn).AsLeabra(), ltime)
	}
}

// GFmIncNeur is the neuron-level code for GFmInc that integrates overall Ge, Gi values
// from their G*Raw accumulators.
func (ly *AttnLayer) GFmIncNeur(ltime *leabra.Time) {
	for ni := range ly.Neurons {
		nrn := &ly.Neurons[ni]
		if nrn.IsOff() {
			continue
		}
		attn := ly.Attns[nrn.SubPool]
		geRaw := nrn.GeRaw + ly.Attn.GeMod(ly.GeFwds[ni], attn) // separately modulating GeFwds by attention
		ly.Act.GeFmRaw(nrn, geRaw)
		ly.Act.GiFmRaw(nrn, nrn.GiRaw)
	}
}

// GFmInc integrates new synaptic conductances from increments sent during last SendGDelta.
func (ly *AttnLayer) GFmInc(ltime *leabra.Time) {
	ly.RecvGInc(ltime)
	ly.GFmIncNeur(ltime)
}