Brain is not hard-wired but is constantly undergoing modifications to store information and adapt to changes in the environment. Nervous systems are thus faced with a fundamental problem: how to allow plastic mechanisms to shape their output and function, without compromising the stability and integrity of the underlying circuits that drive behavior. Homeostatic plasticity mechanisms that allow neurons to sense how active they are and to adjust their properties to maintain stable function Given the complexity of most central neural circuits, maintaining stability in function is a problem that permeates nearly every aspect of circuit development and plasticity: setting excitation and inhibition to the proper levels so that activity can propagate through a network without either dying out or increasing uncontrollably into an epileptic-like state. Learning-related adaptations require neural networks to detect correlations between events in the environment and store these as changes in synaptic strength long-term potentiation (LTP) and long-term depression (LTD) strengthen synaptic inputs that are effective at depolarizing the postsynaptic neuron and weaken inputs that are not, thus reinforcing useful pathways in the brain. Despite their utility these mechanisms synapses that are strengthened become more effective at depolarizing the postsynaptic neuron and will continue to be strengthened in an unconstrained positive feedback cycle, eventually driving neuronal activity to saturation. In addition, because of this positive feedback the synapse-specificity of these synaptic plasticity mechanisms breaks down. As correlated activity of presynaptic and postsynaptic neurons drives strengthening of specific synapses, the postsynaptic neuron will be driven more strongly, and so presynaptic inputs that were initially only poorly correlated with postsynaptic firing will be better able to trigger firing of the postsynaptic neuron, and they too can become strengthened even without a triggering environmental stimulus it makes it easier for other inputs to make the postsynaptic neuron fire, and they begin to undergo LTP as well. Synaptic mechanism able to adjust its synaptic weights up or down to keep this activity close to some set-point value, network activity will remain stable in the face of correlation-based changes in synaptic strength Homeostatic synaptic scaling (“synaptic scaling” because it was observed to globally scale all of a neuron’s synapses up or down in strength in the correct direction to stabilize neuronal firing ) prevents this runaway potentiation. When LTP of one input increases postsynaptic firing, synaptic scaling will reduce the strength of all synaptic inputs until the firing rate returns to control levels. Note that synaptic strengths are reduced proportionally, so that the relative strength of the potentiated synapse remains the same. Relationship between synaptic drive and firing rate for an individual neuron. As synaptic drive increases , through addition or increased strength of excitatory synapses and firing rate rises above the target level, homeostatic mechanisms (arrows) are engaged that reduce the strength of all inputs, thereby moving the neuron down the curve and back into the target zone. Conversely, if synaptic drive falls too low and firing rate falls below the target rate, the homeostatic regulatory process will increase the strength of all inputs and bring the neuron back within the target firing zone.
Synaptic scaling was first described in cultured neocortical neurons, where it was observed that perturbing network activity generated compensatory changes in synaptic strength that returned average firing rates back to control values.
Cultured cortical networks are composed of interconnected excitatory pyramidal and inhibitory interneurons, and develop spontaneous activity after a few days in vitro (control). This activity can be...