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Background: Spinal cord stimulation (SCS) has emerged as an effective treatment for managing chronic pain that is unresponsive to traditional therapies. While SCS is well documented for conditions like failed back surgery syndrome (FBSS) and complex regional pain syndrome (CRPS), its effectiveness in managing pain related to spinal cord injuries (SCI) is less studied. This study aims to assess the efficacy of SCS in alleviating SCI-related pain and improving patients' quality of life, filling a gap in the existing literature. Methods: This cohort study included 15 adult patients with traumatic and non-traumatic SCIs, treated between 2016 and 2022. Patients received SCS implants after either a trial or direct implantation. Pain levels were assessed using visual analog scale (VAS) scores, while quality of life was evaluated using the EuroQol five-dimensional (EQ-5D) scale. The SCS devices were implanted at different spinal levels, with various stimulation protocols applied, including high-frequency stimulation (10 kHz). Results: In patients with traumatic SCI, the mean VAS score decreased from 8.6 to 4.5, with 71% reporting more than 50% pain relief. Non-traumatic SCI patients experienced a reduction from 8.5 to 2.5, with all showing more than 50% pain relief. EQ-5D scores improved in both groups. A 49% reduction in pain medication usage was also observed, though one patient required revision surgery due to an adverse event. Conclusions: SCS significantly reduces pain and improves quality of life for SCI patients, particularly with high-frequency protocols. While promising, further research is needed to optimize patient selection and stimulation parameters for better long-term outcomes. [ABSTRACT FROM AUTHOR]

Economic choice is thought to involve the elicitation of the subjective values of the choice options. Thus far, value estimation in animals has relied on stochastic choices between multiple options presented in repeated trials and expressed from averages of dozens of trials. However, subjective reward valuations are made moment-to-moment and do not always require alternative options; their consequences are usually felt immediately. Here, we describe a Becker–DeGroot–Marschak (BDM) auctionlike mechanism that provides more direct and simple valuations with immediate consequences. The BDM encourages agents to truthfully reveal their true subjective value in individual choices (“incentive compatibility”). Male monkeys reliably placed well-ranked BDM bids for up to five juice volumes while paying from a water budget. The bids closely approximated the average subjective values estimated with conventional binary choices (BCs), thus demonstrating procedural invariance and aligning with the wealth of knowledge acquired with these less direct estimation methods. The feasibility of BDM bidding in monkeys paves the way for an analysis of subjective neuronal value signals in single trials rather than from averages; the feasibility also bridges the gap to the increasingly used BDM method in human neuroeconomics. [ABSTRACT FROM AUTHOR]

The dopamine reward prediction error signal is known to be subjective but has so far only been assessed in aggregate choices. However, personal choices fluctuate across trials and thus reflect the instantaneous subjective reward value. In the well-established Becker-DeGroot-Marschak (BDM) auction-like mechanism, participants are encouraged to place bids that accurately reveal their instantaneous subjective reward value; inaccurate bidding results in suboptimal reward ('incentive compatibility'). In our experiment, male rhesus monkeys became experienced over several years to place accurate BDM bids for juice rewards without specific external constraints. Their bids for physically identical rewards varied trial by trial and increased overall for larger rewards. In these highly experienced animals, responses of midbrain dopamine neurons followed the trial-by-trial variations of bids despite constant, explicitly predicted reward amounts. Inversely, dopamine responses were similar with similar bids for different physical reward amounts. Support Vector Regression demonstrated accurate prediction of the animals' bids by as few as twenty dopamine neurons. Thus, the phasic dopamine reward signal reflects instantaneous subjective reward value.