1. A method of operating a computerized spiking neuron operable in accordance with a process characterized by a learning parameter, said method comprising: modifying said learning parameter based at least in part on a reinforcement signal and a quantity relating to a first adjustment and a second adjustment; wherein: said reinforcement signal is configured based at least in part on a performance measure determined based at least in part on a present performance and a target performance associated with said process; said reinforcement signal comprises a negative reward determined based at least in part on said present performance being outside a predetermined measure from said target performance; said modifying said learning parameter is based at least in part on said reinforcement signal and is effectuated based at least in part on a spiking input received via an interface: said second adjustment is configured to increase a probability of said computerized spiking neuron generating a spiking output based on said spiking input; and said second adjustment is determined based at least in part on said computerized spiking neuron being previously inactive in response to receiving said spiking input.