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Introduction

• Chemical signaling probably accounts for a hundred times as much computation as electrical signaling.
• What is involved in these computations? There are over 1400 distinct proteins in the post synaptic region.
• Chemical computation includes:
  • presynaptic signaling
  • bistability from chemical feedback loops
  • bistability from receptor trafficking
  • 'off' state with few receptors
  • synaptic tagging and local activity spread
  • spine structural change in plasticity
  • input patterns control plasticity
  • activity controls gene expression

Review

Pattern selectivity

• Calcium influx can trigger both increased or decreased synaptic efficacy, and there may be local as well as global differences throughout the neuron
• Mitogen-activated protein kinase (MAPK) cascade shows preference for bursts that are spaced by 5-10 min
• Kinase cascades have the ability to respond to a range of time-scales from seconds to minutes
• After all, the spike-timing dependent plasticity (STDP) is a direct result of channel biophysics

Spatial models and spatial pattern selectivity

• Synaptic tagging - strong activity at one synapse enables the potentiation of a nearby synapse receiving much weaker input
• Reaction-diffusion models demonstrate how long term potentiation and long term depression spreads to neighboring spines
• The spatial spread of calmodulin (CaM) plays a role in decoding synaptic input patterns

Signal Propagation

• Precision in spatial signaling can be achieved through chemistry via diffusion but perhaps through other complex means
• Chemical signaling might support long range signal propagation such as through active transport via cellular motors
• Many chemical computations can occur in parallel in each neuron

Long-term storage: biochemical bistability

• Three processes act against the stable long-term storage abilities of synapses: turnover, diffusion, and stochasticity.
• It has been showed that bistability, which is often a demonstration of how a positive feedback loop may strengthen memories, has a very narrow range in synaptic/dendritic protein synthesis.
• There are many biochemically plausible candidates for memory storage at the synapse.

Plasticity and molecular traffic

• How does a synapse retain its state given diffusion processes that occur?
• One idea is molecular crowding that can preserve receptors in the synapse for periods of hours
• It is the molecular movement of receptors as opposed to their signaling identity that is needed for LTP, for example.

Losing state: stochasticity and bistability

• Given how small a synapse is, and that there are only one to two hundred calcium receptors, there are strong fluctuations in chemical activity. Such "noise" affects state transitions.
• These stochastic fluctuations may even be sufficient to cause state flips in biochemical bistables, erasing any memories they store. Many bistable models fail the stochasticity test.

Continuous synaptic strengths

• Most studies report continuous plasticity (as opposed to bistable states) without explicitly addressing whether this is at the single synapse level.
• Continuous states could be accomplished by having many stable states, which are indeed possible, but only through using many bistable states to accomplish a multistate system.

Conclusion

• Most computation at the neuron level is chemical, such as the roles of pattern decoding and memory storage
• It may be advantageous to use electrical computation when it is a higher level that encompasses much low level chemical computation

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