Pain and self-preservation in autonomous robots: From neurobiological models to psychiatric disease

The use of biologically realistic (brain-like) control systems in autonomous robots offers two potential benefits. For neuroscience, it may provide important insights into normal and abnormal control and decision-making in the brain, by testing whether the computational learning and decision rules proposed on the basis of simple laboratory experiments lead to effective and coherent behaviour in complex environments. For robotics, it may offer new insights into control system designs, for example in the context of threat avoidance and self-preservation. In the brain, learning and decision-making for rewards and punishments (such as pain) are thought to involve integrated systems for innate (Pavlovian) responding, habit-based learning, and goal-directed learning, and these systems have been shown to be well-described by RL models. Here, we simulated this 3-system control hierarchy (in which the innate system is derived from an evolutionary learning model), and show that it reliably achieves successful performance in a dynamic predator-avoidance task. Furthermore, we show situations in which a 3-system architecture provides clear advantages over single or dual system architectures. Finally, we show that simulating a computational model of obsessive compulsive disorder, an example of a disease thought to involve a specific deficit in the integration of habit-based and goal-directed systems, can reproduce the results of human clinical experiments. The results illustrate how robotics can provide a valuable platform to test the validity and utility of computational models of human behaviour, in both health and disease. They also illustrate how bio-inspired control systems might usefully inform self-preservative behaviour in autonomous robots, both in normal and malfunctioning situations

T Regulatory Cells Are Markers of Disease Activity in Multiple Sclerosis Patients

FoxP3+ Treg cells are believed to play a role in the occurrence of autoimmunity and in the determination of clinical recurrences. Contradictory reports are, however, available describing frequency and function of Treg cells during autoimmune diseases. We examined, by both polychromatic flow cytometry, and real-time RT-PCR, several Treg markers in peripheral blood mononuclear cells from patients with multiple sclerosis (MS), an autoimmune disease affecting the central nervous system. We found that Tregs, as defined by CD25, CD39, FoxP3, CTLA4, and GITR expression, were significantly decreased in stable MS patients as compared to healthy donors, but, surprisingly, restored to normal levels during an acute clinical attack. We conclude that Treg cells are not involved in causing clinical relapses, but rather react to inflammation in the attempt to restore homeostasis