BEH-SOMA.md

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BEH-SOMA: il soma

BEH-SOMA: Container

Discursive description:

The soma is the cell body of the neuron — a roughly spherical structure, typically 10 to 30 micrometres across, that sits at the convergence point of all dendritic branches and at the origin of the axon. It is the decision-making centre of the neuron: its job is to continuously monitor the summed electrical input arriving from the dendrites and decide, moment by moment, whether that input is strong enough to warrant sending a signal forward. That decision takes the form of an action potential — a brief, explosive electrical event that propagates down the axon to the next neuron in the circuit and simultaneously backward up the dendrites as the bAP that enables postsynaptic plasticity.

The soma receives V_dend — the summed dendritic potential — as a continuous input. This potential reflects the aggregate activity of every active spine on every dendritic branch, weighted by the electrical properties of each branch. The soma integrates this input across time through its own membrane capacitance: it accumulates charge when depolarising currents arrive and loses charge continuously through passive membrane leak. The result is a somatic membrane potential, V_soma, that rises when dendritic input is strong and sustained, and falls when input weakens or stops. V_soma is not a simple sum of inputs — it is a leaky integrator, always decaying toward rest, always requiring ongoing input to stay elevated.

The critical site of decision is not the soma body itself but the axon hillock — the narrow region where the soma tapers into the beginning of the axon. The axon hillock has the lowest threshold for firing of any part of the neuron, because it has the highest density of voltage-gated sodium channels. These channels are sensitive to voltage: when V_soma at the hillock crosses the firing threshold — typically about 15 millivolts above the resting membrane potential — they open explosively, allowing a massive inward rush of sodium that drives V_soma rapidly to its peak. This is the action potential. It is an all-or-nothing event: once the threshold is crossed, the AP fires to its full amplitude regardless of how far above threshold the triggering input was. The size of the AP does not encode the strength of the input — only whether it was strong enough to cross the threshold at all.

Immediately after firing, the soma enters a refractory period. The same sodium channels that opened to produce the AP become inactivated — they cannot reopen until the membrane has repolarised past its resting level, which requires the delayed activation of potassium channels that pull V_soma below rest into a brief hyperpolarisation. During this absolute refractory period, no input, however strong, can trigger another AP. During the subsequent relative refractory period, firing is possible but requires a stronger-than-normal input because the membrane is recovering. This refractory mechanism sets the maximum firing rate of the neuron and ensures that APs are discrete, separated events rather than a continuous depolarisation.

The metabolic cost of all this activity falls heavily on the soma. Every action potential disturbs the sodium and potassium gradients across the entire soma membrane — sodium rushes in during the rising phase, potassium rushes out during repolarisation. The Na/K-ATPase pump must then restore these gradients by actively moving three sodium ions out for every two potassium ions in, at the cost of one ATP molecule per pump cycle. At high firing rates this cost is substantial — a neuron firing at 100 Hz consumes ATP at a rate that would exhaust its local reserves in seconds without continuous resupply. The astrocyte network surrounding the soma provides this supply through glucose delivery and lactate shuttling, making the soma's ability to sustain firing directly dependent on the metabolic health of its supporting glial environment.

The soma also integrates neuromodulatory signals. Receptors on the somatic membrane respond to dopamine, serotonin, acetylcholine, and other modulatory transmitters that arrive not from specific synapses but diffusely from distant projection neurons. These signals do not directly trigger APs — they adjust the threshold, the gain, and the temporal dynamics of the soma's integrative process. A dopamine signal might lower the firing threshold, making the neuron more likely to fire in response to the same dendritic input. A serotonin signal might increase the afterhyperpolarisation, reducing the maximum firing rate. These modulatory influences are the mechanism through which global brain states — arousal, attention, motivation, stress — shape the input-output relationship of individual neurons. They are not modelled in the current simplified framework but represent an entire layer of regulation that sits above the three-loop structure of the tripartite synapse.

The action potential the soma generates has two destinations. Forward, it travels down the axon to the presynaptic terminal of the next neuron, where it will trigger the calcium influx and vesicle release that we have already modelled as the presynaptic AP. Backward, it propagates up all dendritic branches as the bAP, arriving at every postsynaptic spine and providing the postsynaptic depolarisation that enables NMDA coincidence detection. The soma is therefore simultaneously the output of the dendritic integration process and the source of the feedback signal that enables plasticity at every spine that contributed to its firing. It is both the conclusion of one cycle and the beginning of the next.

The soma does not fire randomly or continuously. Under no input it sits at rest, its membrane potential held near -70 mV by the balance of passive leak and active pump activity. Under weak sustained input it may oscillate just below threshold, generating subthreshold oscillations that modulate its sensitivity without triggering APs. Under strong sustained input it fires repetitively at a rate that reflects the intensity of that input — stronger input produces higher firing rates, up to the limit set by the refractory period. Under brief strong input it fires a single AP and then returns to rest. The relationship between input intensity and output firing rate — the neuron's input-output curve, or f-I curve — is one of the most fundamental characterisations of a neuron's computational properties, and it is shaped by the properties of every channel on the somatic membrane.

The soma is therefore not a simple threshold device. It is a dynamic integrator with memory encoded in its current membrane potential, a nonlinear decision mechanism encoded in its channel kinetics, a refractory mechanism that shapes its temporal output, and a metabolic dependence that links its firing capacity to the health of its local environment. It is, in miniature, a complete signal processing unit — and the action potential it produces is the one binary output that all of this continuous analogue computation ultimately reduces to.

Simplified comprehension:

In this model we decide to simplify:

We do not model the axon hillock as a separate compartment — threshold crossing is computed directly from V_soma
We do not model neuromodulatory inputs — threshold and gain are fixed parameters
We do not model subthreshold oscillations — V_soma is a simple leaky integrator
We do not model somatic ATP

The simplifications imply that:

Removing the axon hillock as a separate compartment means the threshold comparison is applied directly to V_soma rather than to a spatially distinct zone with its own channel density. In biology the hillock has a lower threshold than the soma body because of its higher Na⁺ channel density — this gradient is absent here. A single fixed threshold applied to V_soma is a reasonable approximation for a single-compartment model, but it means the model cannot capture phenomena that depend on the hillock's spatial separation from the dendritic integration zone, such as the ability of strong distal dendritic inputs to bypass somatic inhibition.

Removing neuromodulatory inputs means the threshold and gain of the soma are fixed across the entire simulation. In biology dopamine, serotonin, and acetylcholine continuously adjust V_soma_threshold and the shape of the f-I curve in response to behavioural state. A neuron in an attentive animal fires more readily to the same input than the same neuron in a drowsy animal. This state-dependence is entirely absent — the soma responds identically to a given V_dend at all times.

Removing subthreshold oscillations means V_soma behaves as a simple leaky integrator between APs. In some neuron types, voltage-gated channels produce rhythmic subthreshold fluctuations that bias the timing of AP generation toward specific phases of network oscillations. These are not modelled — V_soma decays smoothly toward rest between threshold crossings.

ATP is a simplification of convenience — at this stage we do not comprehend the total metabolic load.

Simplified behaviors:

— ms:

VDB is integrated (each Dendrites acts as leaky integrator)
Threshold check - condition VDB fullness - (only when not in AP waveform phase and not in absolute refractory) -- AP -- bAP -- VSOMA --- tau_AP_rise = 0.5 ms - Na⁺ channels open — explosive depolarisation --- (tau_AP_fall = 1.5 ms) - V_soma falls toward V_AHP - K⁺ channels open — repolarisation --- (tau_AHP = 5.0 ms) - V_soma recovers from V_AHP toward V_soma_reset - K⁺ channels close — after-hyperpolarisation
V_bAP as a context is active during ?
SpikeTrainTraces ? -- creation -- destruction
SOMA-VCGG servono a modificare il comportamento del SOMA: refractory period.
threshold AP: da capire come lo modifico, forse con una modifica ad una fullness

— seconds:

nothing — no slow integration in the soma (firing rate statistics could be computed here as a diagnostic but they do not feed back into any other variable)

— mins:

nothing in the simplified model (homeostatic threshold regulation would live here if added: sustained low firing rate → V_soma_threshold decreases sustained high firing rate → V_soma_threshold increases this is the somatic equivalent of postsynaptic AMPA scaling — the neuron adjusts its own excitability to maintain a target firing rate in the face of changing input statistics)

Tubs:

SpikeTrainTraces: sono le tracce che consentono al neurone di far partire il Tuning neuronale, quando e' lontano da uno spike-train, ovvero e' in riposo.
??: ...

container: BEH-SOMA

  expansion: 
    - BEH-SOMA-VGSC ( fullness: 50x, active: 20x, emptiness: 10x ) 
      # modulated_by: TUN-SOMA-VCGG # possible/actual

  tub_local:

    - VDB

    - VSOMA

    - AP

    - bAP

  tub_intricated:
    - SpikeTrainTraces ( contained_by: TUN-N )

: Context

Qui mettiamo lo spike Dendritico. Sempre se vogliamo comprenderlo.

context: ???...
 contained_by: BEH-SOMA

 in_context: Fixed
 rf: 60x

 condition: 
  activate: xxx

: Episode

episode: ??
  contained_by: BEH-SOMA

  in_context: xxx
  rf: ( active: 1x )

  hypothesis:  
  action: 
  trace: None

BEH-SOMA-VCGG: Container

Voltage Gated Sodium Channel

container: BEH-SOMA-VGSC

Episode1

episode: ??
  contained_by: BEH-SOMA-VGSC

  in_context: xxx
  rf: ( active: 1x )

  hypothesis:  
  action: 
  trace: None

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