Homesotatic Plasticity
Homoestatic plasticity
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
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