In neurobiology, imbalances in neurotransmitters are known to be a major contributor in disturbances with sleep, memory, and other realms of cognitive and motor function. Chronic pain also has demonstrated correlation with imbalanced neurotransmission that is caused by the dysregulation of neuropath balances. Some previous scientific experiments have shown that these neuro-clusters are also involved in impaired hedonic capacity and compulsive reward seeking. Therefore, it is suggested that improving the reward deficiency through inhibitory learning control can potentially improve the impaired neuroadaptations and pain handling disorders, according to theory of Spike-timing-dependent plasticity (STDP).
Very similarly, trans-relational inferences in the STDP model of artificial cortical neurons is conceived by an artificial model of chronic pain. Recent experiment explains that in a recurring network, with a very high training rate, the recurrent synaptic connections can cause strong feedback loops that interrupt the normal network dynamic by emerging of the weight attractors. This effect eventually leads to creating a significant number of weight clusters. Weight cluster characterizes the typical chronic pain in many basic ways, which significantly reduces the infer-ability of the network.
Recent research suggests that to prevent the weight clustering, a simple wake-sleep algorithm can be potentially useful for both bio and artificial neuron models. The wake phase is the normal training or learning phase, while during the sleep phase system dreams using an inter-generative model. The dreams are purposefully designed to activate specific attractor states during the sleep phase, by introducing specific synaptic activation. The sleep process then enables the system to capture the entire attractor activation, feedback generation and therefore understand how to unlearn the process states and eventually learn how to avoid weight clusters during the wake phase.
Neurobiology research also suggests using a similar methodology to reduce brain sensitization to chronic pain, recover hedonic mechanism and regain homeostasis by unlearning the neurotransmitters clustering in antinociceptive phase.
