organism/neuron/postsynapse.md

# postsynapse.md

Qui comprendiamo:

- BEH-POST: Postsynapse
- BEH-POST-AMPA: AMPA receptors (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors)

## BEH-POST: Container

**Simplified Behaviors**:

— ms:

- NT arrives in cleft → AMPA receptors bind NT (receptor availability constant, no desensitization)
- V_post rises with AMPA conductance, decays passively each ms
- bAP arrives → V_post receives additional depolarisation boost
- NMDA gate checks coincidence: NT_cleft AND V_post both non-zero
- Mg_block_removal = V_post / (V_post + V_NMDA_half) — sigmoid of V_post
- Ca²⁺ enters spine via NMDA: Ca_post += k_NMDA × NT_cleft × Mg_block_removal
- Ca_post decays slowly each ms (single exponential, no pump detail)
- Ca_post_history updated every ms (feeds seconds loop)
- V_post_history updated every ms (retained for reference)

— seconds:

- Ca_post_history mean computed over past 2 s
- eCB synthesised when Ca_post_history mean exceeds eCB threshold
- eCB_level decays when Ca_post_history mean falls below threshold
- eCB_level written → read by presynapse as retrograde brake on VGCCs
- Ca_post_history compared to LTP/LTD thresholds → plasticity tag set

— mins:

- If Plasticity_LTP tagged → AMPA density increases
- If Plasticity_LTD tagged → AMPA density decreases
- AMPA density feeds back into receptor_conductance ceiling for next cycle

---

**G expression**:
```Gen
POSTSYNAPSE
  - bAP_ctx
    -- Ca Influx
    CaNDMAEnterMax: interacting 
    CaNDMAEnterMed: interacting
    -- Ca Clearence
    AP-CaClearanceHigh: interacting
    AP-CaClearanceMedium: interacting

  - NOT bAP_ctx:
    -- Ca Influx
    CaNDMAEnterMedNotBap: interacting
    CaNDMAEnterLow: interacting

  - Fixed??
    -- V Influx
    VPostMax: interacting
    VPostMed: interacting
    VPostLow: interacting
    -- V Clearence
    VPostClearance: interacting

POST-AMPA
  - Fixed??
    -- Na Influx
    NaAMPAEnterMax: interacting
    NaAMPAEnterMed: interacting

POST-NA-CLEAR
  - Fixed??
    -- Na Clearence
    NaClearanceHigh: interacting
    NaClearanceLow: interacting

```


**Tubs:**

- **Na**: Ioni entranti tramite AMPA receptors

- **NT**:

- **Ca2+**: Ioni entranti tramite NMDA

- **VPost**: il voltage che viene sentito in DB

- **eCB**:

- **Nox**:?

---

```Gen
container: BEH-POST

 expansion: 
  - POST-AMPA ( full: 10x, active: 5x, empty: 2x )
   # modulated_by: TUN-POST-IC # possible/actual

  - POST-NA-CLEAR ( full: 1x, active: 1x, empty: 0x )

 tub_local:
  - Ca2+ ( full: 60x, active: 30x, empty: 0x )

  - Na ( full: 60x, active: 30x, empty: 0x )

  - Nox ( full: 100x, active: 20x, empty: 0x ) # Nitric Oxide (NO):  A gas that diffuses freely.

  - eCB ( full: 100x, active: 20x, empty: 0x ) # Endocannabinoids (e.g., 2-AG)

 tub_intricated:
  - Nt ( contained_by: BEH-SYN )
  - VPost ( contained_by: BEH-BD )

 context_intricated:
  - bAp ( contained_by: BEH-SOMA )
```

### ms: behaviors POST

![post-ltp-ltd.png](.attachments/post-ltp-ltd.png)

#### CheckNa: Context

Contestualizziamo in maniera Fixed?

```Gen
context: CheckNa
  contained_by: BEH-POST

  in_context: Fixed
  rf: ( active: 60x )

  condition: (Na fullness)
    out_context: NaMax

  condition: (Na mediumness)
    out_context: NaMedium 

  condition: (Na emptiness)
    out_context: NaLow
```

##### CaNDMAEnterMax: Episode

```Gen
episode: CaNDMAEnterMax
  contained_by: BEH-POST

  in_context: bAp AND (NaMax OR NaMedium)
  rf: ( active: 2x )

 hypothesis: NOT (Ca2+ full)
  action: [Ca2+ increase]
  trace: 
```

##### CaNDMAEnterMed: Episode

```Gen
episode: CaNDMAEnterMed
  contained_by: BEH-POST

  in_context: (bAp AND NaLow) OR (NOT bAP AND NaMax) 
  rf: ( active: 4x )

 hypothesis: NOT (Ca2+ full)
  action: [Ca2+ increase]
  trace: 
```

##### CaNDMAEnterLow: Episode

```Gen
episode: CaNDMAEnterLow
  contained_by: BEH-POST

  in_context: NOT bAP AND NaMedium 
  rf: ( active: 12x )

  hypothesis: NOT (Ca2+ full)
    action: [Ca2+ increase]
    trace: 
```

#### CaClearance: Episode

```Gen
episode: CaClearance
  contained_by: BEH-POST

  in_context: NOT bAP
  rf: ( active: 24x ) # Low

  hypothesis: NOT (Ca2+ empty)
    action: [Ca2+ decrease]
    trace: None
```

#### CheckCaVPost:Context

Contestualizziamo in maniera Fixed?

Qui controlliamo il livello di Ca2+, che e' stato fatto entrare da NMDA, e creaiamo VPost nel DB. Abbiamo fatto una semplificazione, perche' il Ca2+ dovrebbe entrare nel DB in base a V_Post che fa aprire canali in DB. Invece creaimo direttamente il VPost.

```Gen
context: CheckCaVPost
  contained_by: BEH-POST

  in_context: Fixed
  rf: ( active: 60x )

  condition: (Ca2+ fullness)
    out_context: CaMax

  condition: (Ca2+ mediumness)
    out_context: CaMedium 

  condition: (Ca2+ emptiness)
    out_context: CaLow
```

##### VPostMax:Episode

##### VPostMed:Episode

##### VPostMin:Episode

##### VPostClearance:Episode

Il clearance lo facciamo qui nel container dove creaiamo anche i VPost, perche' altrimenti, se lo facessimo in DB, perderemmo l'aspetto temporale della contribuzione dei singoli POST.

### sec: behaviors POST

#### :Context

#### :Episode

### min: behaviors POST

#### TUN-POST-AMPA: Tuner

```Gen
tuner: TUN-POST-AMPA

 contained_by: BEH-POST

 tunes: BEH-POST/expansion/BEH-POST-IC

  tub_modulation: # in TUN agiamo su POS/ACT
   - posMod ( fullness: None, active: BEH-POST-IC/fullness, empty: 0x)  # riferimento a possible di BEH-PRE
   - actMod ( fullness: None, active: BEH-POST-IC/active, empty: BEH-POST-IC/emptiness)  # riferimento a active di BEH-PRE

 context_intricated:
  - TunPossible ( contained_by: DAY-N )

 tub_local:

 tub_intricated:
```

##### Context

```Gen
context: Check
  contained_by: TUN-POST-AMPA

  in_context: TunPossible
  rf: ( active: 60x )

  condition:  
  out_context: TunPostIc
```

##### Episode

```Gen
episode: ?
  contained_by: TUN-POST-AMPA

  in_context: TunPostIc
  rf: ( active: x )

 hypothesis:  
  action: 
  trace: 
```

## BEH-POST-AMPA: Container

```Gen
container: BEH-POST-AMPA

 tub_intricated:
  - Nt ( contained_by: BEH-SYN )

 context_intricated:
  - Na ( contained_by: BEH-POST )
```

### ms: behaviors AMPA

#### CheckNTPost: Context

```Gen
context: CheckNTPost
  contained_by: BEH-POST-AMPA

  in_context: Fixed
  rf: ( active: 8x )

  condition: (NT mediumness) 
    out_context: NTMedium

  condition: (NT fullness) 
    out_context: NTFull
```

##### NaAMPAEnterMax: Episode

```Gen
episode: NaAMPAEnterMax
  contained_by: BEH-POST-AMPA

  in_context: NTFull
  rf: ( active: 2x )

 hypothesis: (NT fullness)
  action: [Na increase]
  trace: 
```

##### NaAMPAEnterMed: Episode

```Gen
episode: NaAMPAEnterMed
  contained_by: BEH-POST-AMPA

  in_context: NTMedium
  rf: ( active: 4x )

 hypothesis: (NT mediumness)
  action: [Na increase]
  trace: 
```

## BEH-POST-NA-CLEAR: Container

Il clearance lo mettiamo qui come container, perche' gli AMPA creano, e questo container pompa fuori. Qui non e' un problema di perdere l'integrazione temporale, perche' gli AMPA sono tutti uguali nel loro behavior. Abbiamo messo gli AMPA come container perche' cosi' possiamo modularne la numerosita'.

```Gen
container: BEH-POST-NA-CLEAR

 context_intricated:
  - Na ( contained_by: BEH-POST )
```

### ms: behaviors NA-CLEAR

#### NaClearanceHigh: Episode

#### NaClearanceLow: Episode