Chronic pain symptoms often change over time, even in individuals who have had symptoms for years. Studying biological factors that predict trends in symptom change in chronic pain may uncover novel pathophysiological mechanisms and potential therapeutic targets. In this study, we investigated whether brain functional connectivity measures obtained from resting-state functional magnetic resonance imaging at baseline can predict longitudinal symptom change (3, 6, and 12 months after scan) in urologic chronic pelvic pain syndrome. We studied 52 individuals with urologic chronic pelvic pain syndrome (34 women, 18 men) who had baseline neuroimaging followed by symptom tracking every 2 weeks for 1 year as part of the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Research Network study. We found that brain functional connectivity can make a significant prediction of short-term (3 month) pain reduction with 73.1% accuracy (69.2% sensitivity and 75.0% precision). In addition, we found that the brain regions with greatest contribution to the classification were preferentially aligned with the left frontoparietal network. Resting-state functional magnetic resonance imaging measures seemed to be less informative about 6- or 12-month symptom change. Our study provides the first evidence that future trends in symptom change in patients in a state of chronic pain may be linked to functional connectivity within specific brain networks.

Abstract-The correlation structure of natural hand & finger movements suggests that their motion is controlled in a lower-dimensional space than would be possible given their mechanical nature. Yet, it is unclear whether this low dimensional embedding is relevant to how the brain represents motor actions and how we can decode it for Brain-Machine Interface applications. We collected large data set of natural hand movement kinematics and analysed it using a novel sparse coding and dictionary learning approach -Sparse Movement Decomposition (SMD), which captures the embedding of the data in terms of spatial and temporal structure. We show that our sparse codes over natural movement statistics give a more parsimonious representation than the simple correlation structure. This suggest that, like V1 neuron receptive fields can be predicted from sparse code over natural image statistics, motor control may be encoded in such a manner. We further show how our sparse coding can help understand the temporal structure of behaviour, and thus our technique may be used for behavioural fingerprinting in diagnostics and for more naturalistic neuroprosthetic control.

Aims In the human brain, supplementary motor area (SMA) is involved in the control of pelvic floor muscles (PFMs). SMA dysfunction has been implicated in several disorders involving PFMs, including urinary incontinence and urologic pain. Here, we aimed to provide a proof‐of‐concept study to demonstrate the feasibility of modulating resting PFM activity (tone) as well as SMA activity with noninvasive stimulation of SMA. Methods We studied six patients (3 women + 3 men) with Urologic Chronic Pelvic Pain Syndrome. Repetitive transcranial magnetic stimulation (rTMS) was applied to SMA immediately after voiding. We tested two rTMS protocols: high‐frequency (HF‐rTMS) which is generally excitatory, and low‐frequency (LF‐rTMS) which is generally inhibitory. PFM activity was measured during rTMS using electromyography. Brain activity was measured immediately before and after rTMS using functional magnetic resonance imaging. Results The rTMS protocols had significantly different effects on resting activity in PFMs (P = 0.03): HF‐rTMS decreased and LF‐rTMS increased pelvic floor tone. SMA activity showed a clear trend ( P = 0.06) toward the expected differential changes: HF‐rTMS increased and LF‐rTMS decreased SMA activity. Conclusions We interpret the differential effects of rTMS at the brain and muscle level as novel support for an important inhibitory influence of SMA activity on pelvic floor tone after voiding. This preliminary study provides a framework for designing future studies to determine if neuromodulation of SMA could augment therapy for chronic urologic conditions.

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