fffb

type Bg struct {

	// enable adaptive layer inhibition gain as stored in layer GiCur value
	On bool `desc:"enable adaptive layer inhibition gain as stored in layer GiCur value"`

	// [def: .1] [viewif: On=true] level of inhibition as proporition of FFFB Gi value -- will need to reduce FFFB level to compensate for this additional source of inhibition
	Gi float32 `` /* 173-byte string literal not displayed */

	// [def: 10] [viewif: On=true] time constant for integrating background inhibition (tau is roughly how long it takes for value to change significantly -- 1.4x the half-life)
	Tau float32 `` /* 175-byte string literal not displayed */

	// [view: -] rate = 1 / tau
	Dt float32 `inactive:"+" view:"-" json:"-" xml:"-" desc:"rate = 1 / tau"`
}

type Inhib struct {

	// computed feedforward inhibition
	FFi float32 `desc:"computed feedforward inhibition"`

	// computed feedback inhibition (total)
	FBi float32 `desc:"computed feedback inhibition (total)"`

	// overall value of the FFFB computed inhibition -- this is what is added into the unit Gi inhibition level (along with  GiBg and any synaptic unit-driven inhibition)
	Gi float32 `` /* 170-byte string literal not displayed */

	// original value of the inhibition (before pool or other effects)
	GiOrig float32 `desc:"original value of the inhibition (before pool or other effects)"`

	// for pools, this is the layer-level inhibition that is MAX'd with the pool-level inhibition to produce the net inhibition
	LayGi float32 `` /* 127-byte string literal not displayed */

	// average and max Ge excitatory conductance values, which drive FF inhibition
	Ge minmax.AvgMax32 `desc:"average and max Ge excitatory conductance values, which drive FF inhibition"`

	// average and max Act activation values, which drive FB inhibition
	Act minmax.AvgMax32 `desc:"average and max Act activation values, which drive FB inhibition"`
}

type Inhibs []Inhib

type Params struct {

	// enable this level of inhibition
	On bool `desc:"enable this level of inhibition"`

	// [def: 1.1] [viewif: On] [min: 0] [0.8-1.5 typical, can go lower or higher as needed] overall inhibition gain -- this is main parameter to adjust to change overall activation levels -- it scales both the the ff and fb factors uniformly
	Gi float32 `` /* 238-byte string literal not displayed */

	// [def: 1] [viewif: On] [min: 0] overall inhibitory contribution from feedforward inhibition -- multiplies average Ge (i.e., synaptic drive into layer) -- this anticipates upcoming changes in excitation, but if set too high, it can make activity slow to emerge -- see also ff0 for a zero-point for this value
	FF float32 `` /* 310-byte string literal not displayed */

	// [def: 1] [viewif: On] [min: 0] overall inhibitory contribution from feedback inhibition -- multiplies average activation -- this reacts to layer activation levels and works more like a thermostat (turning up when the 'heat' in the layer is too high)
	FB float32 `` /* 253-byte string literal not displayed */

	// [def: 1.4,3,5] [viewif: On] [min: 0] time constant in cycles, which should be milliseconds typically (tau is roughly how long it takes for value to change significantly -- 1.4x the half-life) for integrating feedback inhibitory values -- prevents oscillations that otherwise occur -- the fast default of 1.4 should be used for most cases but sometimes a slower value (3 or higher) can be more robust, especially when inhibition is strong or inputs are more rapidly changing
	FBTau float32 `` /* 477-byte string literal not displayed */

	// [def: 0,0.5,1] [viewif: On] what proportion of the maximum vs. average Ge to use in the feedforward inhibition computation -- 0 = all average, 1 = all max, and values in between = proportional mix between average and max (ff_netin = avg + ff_max_vs_avg * (max - avg)) -- including more max can be beneficial especially in situations where the average can vary significantly but the activity should not -- max is more robust in many situations but less flexible and sensitive to the overall distribution -- max is better for cases more closely approximating single or strictly fixed winner-take-all behavior -- 0.5 is a good compromise in many cases and generally requires a reduction of .1 or slightly more (up to .3-.5) from the gi value for 0
	MaxVsAvg float32 `` /* 749-byte string literal not displayed */

	// [def: 0.1] [viewif: On] feedforward zero point for average Ge -- below this level, no FF inhibition is computed based on avg Ge, and this value is subtraced from the ff inhib contribution above this value -- the 0.1 default should be good for most cases (and helps FF_FB produce k-winner-take-all dynamics), but if average Ges are lower than typical, you may need to lower it
	FF0 float32 `` /* 380-byte string literal not displayed */

	// [def: 0,0.05] [viewif: On] extra feedforward inhibition applied when average Ge exceeds a higher threshold -- produces a nonlinear inhibition effect that is consistent with a wide range of neuroscience data, including popout and the Reynolds & Heeger, 2009 attention model
	FFEx float32 `` /* 277-byte string literal not displayed */

	// [def: 0.15] [viewif: On] point of average Ge at which extra inhibition based on feedforward level starts
	FFEx0 float32 `viewif:"On" def:"0.15" desc:"point of average Ge at which extra inhibition based on feedforward level starts"`

	// [view: -] rate = 1 / tau
	FBDt float32 `inactive:"+" view:"-" json:"-" xml:"-" desc:"rate = 1 / tau"`
}