Neural Substrates and Models of Omission Responses and Predictive Processes.

Predictive coding theories argue that deviance detection phenomena, such as mismatch responses and omission responses, are generated by predictive processes with possibly overlapping neural substrates. Molecular imaging and electrophysiology studies of mismatch responses and corollary discharge in the rodent model allowed the development of mechanistic and computational models of these phenomena. These models enable translation between human and non-human animal research and help to uncover fundamental features of change-processing microcircuitry in the neocortex. This microcircuitry is characterized by stimulus-specific adaptation and feedforward inhibition of stimulus-selective populations of pyramidal neurons and interneurons, with specific contributions from different interneuron types. The overlap of the substrates of different types of responses to deviant stimuli remains to be understood. Omission responses, which are observed both in corollary discharge and mismatch response protocols in humans, are underutilized in animal research and may be pivotal in uncovering the substrates of predictive processes. Omission studies comprise a range of methods centered on the withholding of an expected stimulus. This review aims to provide an overview of omission protocols and showcase their potential to integrate and complement the different models and procedures employed to study prediction and deviance detection.This approach may reveal the biological foundations of core concepts of predictive coding, and allow an empirical test of the framework's promise to unify theoretical models of attention and perception.

Open Issues and Practical Suggestions for Telemedicine in Chronic Pain.

Telemedicine represents a major opportunity to facilitate continued assistance for patients with chronic pain and improve their access to care. Preliminary data show that an improvement can be expected of the monitoring, treatment adherence, assessment of treatment effect including the emotional distress associated with pain. Moreover, this approach seems to be convenient and cost-effective, and particularly suitable for personalized treatment. Nevertheless, several open issues must be highlighted such as identification of assessment tools, implementation of monitoring instruments, and ability to evaluate personal needs and expectations. Open questions exist, such as how to evaluate the need for medical intervention and interventional procedures, and how to define when a clinical examination is required for certain conditions. In this context, it is necessary to establish dynamic protocols that provide the right balance between face-to-face visits and telemedicine. Useful tips are provided to start an efficient experience. More data are needed to develop precise operating procedures. In the meantime, the first experiences from such settings can pave the way to initiate effective care pathways in chronic pain.