Most current methods for assessing pain in animals are based on reflexive measures and require constant interaction between the observer and the animal. Here we explore two new fully automated methods to quantify the impact of pain on the overall behavior of the organism. Both methods take advantage of the animals' natural preference for a dark environment. We used a box divided into two compartments: dark and bright. In the motoric operant task, "AngleTrack", one end of the box was raised so that the animals had to climb uphill to go from the light to the dark compartment. In the thermal operant task, "ThermalTrack", the floor of the dark compartment was heated to a given temperature, while the light compartment remained at 25 degrees C. Rats were individually placed in the light box and their crossing between chambers monitored automatically for 30 minutes. The angle of the box, or the temperature of the dark compartment, was altered to challenge the animals' natural preference. We test the hypothesis that different models of pain (inflammatory or neuropathic) can be differentiated based on performance on these devices. Three groups of rats were tested at five different challenge levels on both tasks: 1) normal, 2) neuropathic injury pain (Spared Nerve Injury), and 3) inflammatory pain (intraplantar injection of Carrageenan). We monitored the position of the animals as well as their rate of switching between compartments. We find significant differences between the three groups and between the challenge levels both in their average position with respect to time, and in their switching rates. This suggests that the angle-track and thermal-track may be useful in assessing automatically the global impact of different types of pain on behavior.