nearFull, nearEmpty
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@@ -44,14 +44,21 @@ La fullness di un Tub puo' essere cambiata in DEV. Dal punto di vista della comp
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L'assegnazione dei livelli di fullness, active e emptiness viene fatta una volta completata l'espansione come per RF. Infatti l'assegnazione deve essere collegata a RF.
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L'assegnazione dei livelli di fullness, active e emptiness viene fatta una volta completata l'espansione come per RF. Infatti l'assegnazione deve essere collegata a RF.
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#### full, medium and empty
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#### full and empty
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Il controllo della condition in un context o episode viene fatto con 3 "stati".
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Il controllo di condition in un context o hpothesis in un episode viene fatto con:
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- full: se gli actual sono maggiori o uguali a fullness
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- full: se gli actual sono maggiori o uguali a fullness
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- medium: se gli actual sono minori di fullness e maggiori di emptiness
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- empty: se gli actual sono uguali o meno di emptiness
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- empty: se gli actual sono uguali o meno di emptiness
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#### nearFull, medium and nearEmpty
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Il controllo di condition in un context o hpothesis in un episode viene fatto con:
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- nearFull: se gli actual sono almeno 70% di fullness
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- nearEmpty: se gli actual sono almeno 30% di fullness
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- medium: se gli actual sono fra 30% e 70% di fullness
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### RF
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### RF
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Teorema di Shannon inverso. E' come se facessimo un campionamento su un ipotesi di continuita'.
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Teorema di Shannon inverso. E' come se facessimo un campionamento su un ipotesi di continuita'.
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-15
@@ -415,8 +415,8 @@ context: SeContext
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in_context: Fixed
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in_context: Fixed
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rf: ( active: 600x )
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rf: ( active: 600x )
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condition: NOT (Rrp empty)
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condition: NOT (rp empty)
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out_context: RRPNotEmpty
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out_context: RPNotEmpty
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condition: NOT (CaTrace empty)
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condition: NOT (CaTrace empty)
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out_context: CaTracesNotEmpty
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out_context: CaTracesNotEmpty
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@@ -461,21 +461,65 @@ episode: CaTracesClearance
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#### RP->RRP shuttling
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#### RP->RRP shuttling
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How RP is moved to RRP
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This happens in the seconds loop, once per second.
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This happens in the seconds loop, once per second. The recruitment step reads Tr_Ca and moves a fraction of the available RP into the RRP:
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current_recruitment_rate = map_trace_to_speed(Tr_Ca) # /s
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refill_amount = current_recruitment_rate *dt_slow_s* N_RP * (Max_RRP - N_RRP) / Max_RRP
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refill_amount = max(0.0, refill_amount)
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refill_amount = min(refill_amount, N_RP)
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N_RRP = min(N_RRP + refill_amount, Max_RRP)
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##### RP->RRPSlow: Episode
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N_RP = max(0.0, N_RP - refill_amount)
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Three factors multiply together to determine how many vesicles move:
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Recruitment machinery at base speed:
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current_recruitment_rate — set by Tr_Ca history. High recent activity means faster recruitment. This is the only place Tr_Ca has any effect in the model.
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N_RP — how many vesicles are available in the reserve. As N_RP depletes, fewer vesicles are available to move regardless of how fast the rate is. This is the depletion bottleneck — a synapse that has been firing for minutes may have a high Tr_Ca driving fast recruitment, but if N_RP is nearly empty there is nothing left to recruit.
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- Synapse quiet: CaTrace empty
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(Max_RRP - N_RRP) / Max_RRP — the headroom in the RRP, normalised. When the RRP is nearly full, recruitment slows automatically because there is little room to fill. When the RRP is empty after a burst, headroom is maximal and recruitment runs at full speed. This prevents overfilling and makes the system self-regulating — recruitment is fastest precisely when it is most needed.
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- Supply available: RP medium
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The two guard clauses ensure the arithmetic stays physical: refill_amount cannot be negative, and cannot exceed what N_RP actually contains.
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- Headroom available: RRP medium
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```Gen
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episode: RP->RRPSlow
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contained_by: BEH-PRE
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in_context: RPNotEmpty
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rf: ( active: 24x ) # Slow
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hypothesis: (RRP medium) AND (RP Medium) AND (CaTrace empty)
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action: [RP decrease, RRP increase]
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trace: None
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```
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##### RP->RRPFast: Episode
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Recruitment high:
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- Recent activity has primed the machinery: CaTrace medium
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- Supply Available: RP medium or full
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- Headroom available: RRP medium or
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```Gen
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episode: RP->RRPFast
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contained_by: BEH-PRE
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in_context: RPNotEmpty
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rf: ( active: 24x ) # Fast
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hypothesis:
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action: [RP decrease, RRP increase]
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trace: None
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```
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##### RP->RRPMaximal: Episode
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...
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```Gen
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episode: RP->RRPMaximal
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contained_by: BEH-PRE
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in_context: RPNotEmpty
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rf: ( active: 24x ) # Maximal
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hypothesis:
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action: [RP decrease, RRP increase]
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trace: None
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### min: behaviors
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### min: behaviors
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