Complications and Effects of Dorsal Root Ganglion Stimulation in the Treatment of Chronic Neuropathic Pain: A Nationwide Cohort Study in Denmark.

OBJECTIVES: Dorsal root ganglion (DRG) stimulation is a novel treatment of chronic neuropathic pain and has been shown to be efficacious across several case reports and randomized trials. However, long-term follow-up is limited, as are reports of complication rates. This study presents efficacy and complications for patients treated with DRG stimulation. MATERIALS AND METHODS: We performed an observational, multicenter cohort study of all patients in Denmark implanted with FDA-approved DRG stimulation systems to treat chronic, neuropathic pain between 2014 and 2018. Follow-up period was one to three years. RESULTS: Forty-three patients underwent trial DRG stimulation; 33 were subsequently fully implanted. Pain location: 58% lower extremity; 21% upper extremity; 21% thoracic/abdominal. At the end of the observation period, 58% of fully implanted patients were still implanted; 42% had fully functional systems. In these patients, average Numerical Rating Scale (NRS)-score of pain was reduced from 6.8 to 3.5 (p = 0.00049) and worst NRS-score was reduced from 8.6 to 6.0 (p = 0.0039) at 12 months follow-up. Pain Catastrophizing Score was reduced from 32 to 15 (p = 0.0039). Thirteen patients experienced complications related to defect leads (39% of implanted systems). In four patients (12%), lead removal left fragments in the root canal due to lead fracture, and three patients suffered permanent nerve damage during attempts to replace broken leads. CONCLUSIONS: This study suggests a significant, clinically relevant effect of DRG stimulation on neuropathic pain, but also demonstrates substantial problems with maintenance and revision of currently available systems. Consequently, treatment with equipment marketed specifically for DRG stimulation is currently paused in Denmark.

A Reinforcement Meta-Learning framework of executive function and information demand.

Gathering information is crucial for maximizing fitness, but requires diverting resources from searching directly for primary rewards to actively exploring the environment. Optimal decision-making thus maximizes information while reducing effort costs, but little is known about the neuro-computational implementation of this tradeoff. We present a Reinforcement Meta-Learning (RML) computational model that solves the trade-off between the value and costs of gathering information. We implement the RML in a biologically plausible architecture that links catecholaminergic neuromodulators, the medial prefrontal cortex and topographically organized visual maps and show that it accounts for neural and behavioral findings on information demand motivated by instrumental incentives and intrinsic utility. Moreover, the utility function used by the RML, encoded by dopamine, is an approximation of variational free energy. Thus, the RML presents a biologically plausible mechanism for coordinating motivational, executive and sensory systems generate visual information gathering policies that minimize free energy.

Uncertainty modulates visual maps during noninstrumental information demand.

Animals are intrinsically motivated to obtain information independently of instrumental incentives. This motivation depends on two factors: a desire to resolve uncertainty by gathering accurate information and a desire to obtain positively-valenced observations, which predict favorable rather than unfavorable outcomes. To understand the neural mechanisms, we recorded parietal cortical activity implicated in prioritizing stimuli for spatial attention and gaze, in a task in which monkeys were free (but not trained) to obtain information about probabilistic non-contingent rewards. We show that valence and uncertainty independently modulated parietal neuronal activity, and uncertainty but not reward-related enhancement consistently correlated with behavioral sensitivity. The findings suggest uncertainty-driven and valence-driven information demand depend on partially distinct pathways, with the former being consistently related to parietal responses and the latter depending on additional mechanisms implemented in downstream structures.

Parietal neurons encode information sampling based on decision uncertainty.

During natural behavior, animals actively gather information that is relevant for learning or actions; however, the mechanisms of active sampling are rarely investigated. We tested parietal neurons involved in oculomotor control in a task in which monkeys made saccades to gather visual information relevant to a subsequent action. We show that the neurons encode, before the saccade, the information gain (reduction in decision uncertainty) that the saccade was expected to bring for the following action. Sensitivity to information gain correlates with the monkeys' efficiency at processing the information in the post-saccadic fixation, but is independent of neuronal reward sensitivity. Reward sensitivity, in turn, is unreliable across task contexts, inconsistent with the view that the cells encode economic utility. The findings suggest that parietal cells involved in oculomotor decisions show uncertainty-dependent boosts of neural gain that facilitate the implementation of active sampling policies, including the selection of relevant cues and the efficient use of the information delivered by these cues.

Natural LacI from E. coli yields faster response and higher level of expression than the LVA-tagged LacI.

The lac promoter is one of the most commonly used promoters for expression control of recombinant genes in E. coli. In the absence of galactosides, the lac promoter is repressed by its repressor protein LacI. Since the lac promoter is regulated by a repressor, overexpression of LacI is necessary for regulation when the promoter is introduced on a high-copy plasmid. For that purpose, a modified variant of LacI, a LVA-tagged LacI, was submitted to the Registry of Standard Biological Parts and has been used for more than 500 constructs since then. We have found, however, that natural LacI is superior to the LVA-tagged LacI as controller of expression.