Brain Connectivity Predicts Chronic Pain in Acute Mild Traumatic Brain Injury.

OBJECTIVES: Previous studies have established the role of the cortico-mesolimbic and descending pain modulation systems in chronic pain prediction. Mild traumatic brain injury (mTBI) is an acute pain model where chronic pain is prevalent and complicated for prediction. In this study, we set out to study whether functional connectivity (FC) of the nucleus accumbens (NAc) and the periaqueductal gray matter (PAG) is predictive of pain chronification in early-acute mTBI. METHODS: To estimate FC, resting-state functional magnetic resonance imaging (fMRI) of 105 participants with mTBI following a motor vehicle collision was acquired within 72 hours post-accident. Participants were classified according to pain ratings provided at 12-months post-collision into chronic pain (head/neck pain ≥30/100, n = 44) and recovery (n = 61) groups, and their FC maps were compared. RESULTS: The chronic pain group exhibited reduced negative FC between NAc and a region within the primary motor cortex corresponding with the expected representation of the area of injury. A complementary pattern was also demonstrated between PAG and the primary somatosensory cortex. PAG and NAc also shared increased FC to the rostral anterior cingulate cortex (rACC) within the recovery group. Brain connectivity further shows high classification accuracy (area under the curve [AUC] = .86) for future chronic pain, when combined with an acute pain intensity report. INTERPRETATION: FC features obtained shortly after mTBI predict its transition to long-term chronic pain, and may reflect an underlying interaction of injury-related primary sensorimotor cortical areas with the mesolimbic and pain modulation systems. Our findings indicate a potential predictive biomarker and highlight targets for future early preventive interventions. ANN NEUROL 2022;92:819-833.

Mapping language with resting-state functional magnetic resonance imaging: A study on the functional profile of the language network.

Resting-state functional magnetic resonance imaging (rsfMRI) is a promising technique for language mapping that does not require task-execution. This can be an advantage when language mapping is limited by poor task performance, as is common in clinical settings. Previous studies have shown that language maps extracted with rsfMRI spatially match their task-based homologs, but no study has yet demonstrated the direct participation of the rsfMRI language network in language processes. This demonstration is critically important because spatial similarity can be influenced by the overlap of domain-general regions that are recruited during task-execution. Furthermore, it is unclear which processes are captured by the language network: does it map rather low-level or high-level (e.g., syntactic and lexico-semantic) language processes? We first identified the rsfMRI language network and then investigated task-based responses within its regions when processing stimuli of increasing linguistic content: symbols, pseudowords, words, pseudosentences and sentences. The language network responded only to language stimuli (not to symbols), and higher linguistic content elicited larger brain responses. The left fronto-parietal, the default mode, and the dorsal attention networks were examined and yet none showed language involvement. These findings demonstrate for the first time that the language network extracted through rsfMRI is able to map language in the brain, including regions subtending higher-level syntactic and semantic processes.

Resting-state connectivity reveals a role for sensorimotor systems in vocal emotional processing in children.

Voices are a primary source of emotional information in everyday interactions. Being able to process non-verbal vocal emotional cues, namely those embedded in speech prosody, impacts on our behaviour and communication. Extant research has delineated the role of temporal and inferior frontal brain regions for vocal emotional processing. A growing number of studies also suggest the involvement of the motor system, but little is known about such potential involvement. Using resting-state fMRI, we ask if the patterns of motor system intrinsic connectivity play a role in emotional prosody recognition in children. Fifty-five 8-year-old children completed an emotional prosody recognition task and a resting-state scan. Better performance in emotion recognition was predicted by a stronger connectivity between the inferior frontal gyrus (IFG) and motor regions including primary motor, lateral premotor and supplementary motor sites. This is mostly driven by the IFG pars triangularis and cannot be explained by differences in domain-general cognitive abilities. These findings indicate that individual differences in the engagement of sensorimotor systems, and in its coupling with inferior frontal regions, underpin variation in children's emotional speech perception skills. They suggest that sensorimotor and higher-order evaluative processes interact to aid emotion recognition, and have implications for models of vocal emotional communication.

Temporal reliability of ultra-high field resting-state MRI for single-subject sensorimotor and language mapping.

Resting-state fMRI is a well-suited technique to map functional networks in the brain because unlike task-based approaches it requires little collaboration from subjects. This is especially relevant in clinical settings where a number of subjects cannot comply with task demands. Previous studies using conventional scanner fields have shown that resting-state fMRI is able to map functional networks in single subjects, albeit with moderate temporal reliability. Ultra-high resolution (7T) imaging provides higher signal-to-noise ratio and better spatial resolution and is thus well suited to assess the temporal reliability of mapping results, and to determine if resting-state fMRI can be applied in clinical decision making including preoperative planning. We used resting-state fMRI at ultra-high resolution to examine whether the sensorimotor and language networks are reliable over time - same session and one week after. Resting-state networks were identified for all subjects and sessions with good accuracy. Both networks were well delimited within classical regions of interest. Mapping was temporally reliable at short and medium time-scales as demonstrated by high values of overlap in the same session and one week after for both networks. Results were stable independently of data quality metrics and physiological variables. Taken together, these findings provide strong support for the suitability of ultra-high field resting-state fMRI mapping at the single-subject level.

Neuropsychology of chronic back pain managed with long-term opioid use.

Chronic pain is commonly treated with long-term opioids, but the neuropsychological outcomes associated with stable long-duration opioid use remain unclear. Here, we contrasted the psychological profiles, brain activity, and brain structure of 70 chronic back pain patients on opioids (CBP+O, average opioid exposure 6.2 years) with 70 patients managing their pain without opioids. CBP+O exhibited moderately worse psychological profiles and small differences in brain morphology. However, CBP+O had starkly different spontaneous brain activity, dominated by increased mesocorticolimbic and decreased dorsolateral-prefrontal activity, even after controlling for pain intensity and duration. These differences strongly reflected cortical opioid and serotonin receptor densities and mapped to two antagonistic resting-state circuits. The circuits' dynamics were explained by mesocorticolimbic activity and reflected negative affect. We reassessed a sub-group of CBP+O after they briefly abstained from taking opioids. Network dynamics, but not spontaneous activity, reflected exacerbated signs of withdrawal. Our results have implications for the management and tapering of opioids in chronic pain.

Mechanical hyperalgesia and neuropathic pain qualities impart risk for chronic postoperative pain after total knee replacement.

Total knee replacement (TKR) is the gold-standard treatment for end-stage chronic osteoarthritis pain, yet many patients report chronic postoperative pain after TKR. The search for preoperative predictors for chronic postoperative pain following TKR has been studied with inconsistent findings. This study investigates the predictive value of quantitative sensory testing (QST) and PainDETECT for postoperative pain 3, 6, and 12 months post-TKR. We assessed baseline and postoperative (3- and 6-months) QST measures in 77 patients with knee OA (KOA) and 41 healthy controls, along with neuropathic pain scores in patients (PainDETECT). QST parameters included pressure pain pressure threshold (PPT), pain tolerance threshold (PTT), conditioned pain modulation (CPM), and temporal summation (TS) using cuff algometry, alongside mechanical hyperalgesia, and mechanical temporal summation to repeated pinprick stimulation. Compared to healthy controls, KOA patients at baseline demonstrated hyperalgesia to pinprick stimulation at the medial OA-affected knee and cuff pressure on the ipsilateral calf. Lower cuff algometry PTT and mechanical pinprick hyperalgesia were associated with baseline KOA pain intensity. Moreover, baseline pinprick pain hyperalgesia explained 25% of variance in pain intensity 12 months post-TKR and preoperative neuropathic pain scores also captured 30% and 20% of the variance in postoperative pain at 6- and 12-months, respectively. A decrease in mechanical pinprick hyperalgesia from before surgery to 3 months after TKR was associated with lower postoperative pain at the 12 months post-TKR follow-up, and vice-versa. Our findings suggest that preoperative pinprick hyperalgesia and PainDETECT neuropathic-like pain symptoms show predictive value for the development of chronic post-TKR pain.

Prognostic value of preoperative mechanical hyperalgesia and neuropathic pain qualities for postoperative pain after total knee replacement.

BACKGROUND: Total knee replacement (TKR) is the gold standard treatment for end-stage chronic osteoarthritis pain, yet many patients report chronic postoperative pain after TKR. The search for preoperative predictors for chronic postoperative pain following TKR has been studied with inconsistent findings. METHODS: This study investigates the predictive value of quantitative sensory testing (QST) and PainDETECT for postoperative pain 3, 6 and 12 months post-TKR. We assessed preoperative and postoperative (3 and 6 months) QST measures in 77 patients with knee OA (KOA) and 41 healthy controls, along with neuropathic pain scores in patients (PainDETECT). QST parameters included pressure pain pressure threshold (PPT), pain tolerance threshold (PTT), conditioned pain modulation (CPM) and temporal summation (TS) using cuff algometry, alongside mechanical hyperalgesia and temporal summation to repeated pinprick stimulation. RESULTS: Compared to healthy controls, KOA patients at baseline demonstrated hyperalgesia to pinprick stimulation at the medial knee undergoing TKR, and cuff pressure at the calf. Lower cuff algometry PTT and mechanical pinprick hyperalgesia were associated with preoperative KOA pain intensity. Moreover, preoperative pinprick pain hyperalgesia explained 25% of variance in pain intensity 12 months post-TKR and preoperative neuropathic pain scores also captured 30% and 20% of the variance in postoperative pain at 6 and 12 months respectively. A decrease in mechanical pinprick hyperalgesia from before surgery to 3 months after TKR was associated with lower postoperative pain at the 12 months post-TKR follow-up. CONCLUSION: Our findings suggest that preoperative pinprick hyperalgesia and neuropathic-like pain symptoms show predictive value for the development of chronic post-TKR pain. SIGNIFICANCE STATEMENT: This study's findings hold significant implications for chronic pain management in knee osteoarthritis patients, particularly those undergoing total knee replacement surgery (TKR). Mechanical hyperalgesia and neuropathic pain-like characteristics predict postoperative pain 1 year after TKR, emphasizing the importance of understanding pain phenotypes in OA for selecting appropriate pain management strategies. The normalization of hyperalgesia after surgery correlates with better long-term outcomes, further highlighting the therapeutic potential of addressing abnormal pain processing mechanisms pre- and post-TKR.

Predicting placebo analgesia in patients with chronic pain using natural language processing: a preliminary validation study.

ABSTRACT: Patients with chronic pain show large placebo effects in clinical trials, and inert pills can lead to clinically meaningful analgesia that can last from days to weeks. Whether the placebo response can be predicted reliably, and how to best predict it, is still unknown. We have shown previously that placebo responders can be identified through the language content of patients because they speak about their life, and their pain, after a placebo treatment. In this study, we examine whether these language properties are present before placebo treatment and are thus predictive of placebo response and whether a placebo prediction model can also dissociate between placebo and drug responders. We report the fine-tuning of a language model built based on a longitudinal treatment study where patients with chronic back pain received a placebo (study 1) and its validation on an independent study where patients received a placebo or drug (study 2). A model built on language features from an exit interview from study 1 was able to predict, a priori, the placebo response of patients in study 2 (area under the curve = 0.71). Furthermore, the model predicted as placebo responders exhibited an average of 30% pain relief from an inert pill, compared with 3% for those predicted as nonresponders. The model was not able to predict who responded to naproxen nor spontaneous recovery in a no-treatment arm, suggesting specificity of the prediction to placebo. Taken together, our initial findings suggest that placebo response is predictable using ecological and quick measures such as language use.

Subcortical brain anatomy as a potential biomarker of persistent pain after total knee replacement in osteoarthritis.

ABSTRACT: The neural mechanisms for the persistence of pain after a technically successful arthroplasty in osteoarthritis (OA) remain minimally studied, and direct evidence of the brain as a predisposing factor for pain chronicity in this setting has not been investigated. We undertook this study as a first effort to identify presurgical brain and clinical markers of postarthroplasty pain in knee OA. Patients with knee OA (n = 81) awaiting total arthroplasty underwent clinical and psychological assessment and brain magnetic resonance imagining. Postoperative pain scores were measured at 6 months after surgery. Brain subcortical anatomic properties (volume and shape) and clinical indices were studied as determinants of postoperative pain. We show that presurgical subcortical volumes (bilateral amygdala, thalamus, and left hippocampus), together with shape deformations of the right anterior hippocampus and right amygdala, associate with pain persistence 6 months after surgery in OA. Longer pain duration, higher levels of presurgical anxiety, and the neuropathic character of pain were also prognostic of postsurgical pain outcome. Brain and clinical indices accounted for unique influences on postoperative pain. Our study demonstrates the presence of presurgical subcortical brain factors that relate to postsurgical persistence of OA pain. These preliminary results challenge the current dominant view that mechanisms of OA pain predominantly underlie local joint mechanisms, implying novel clinical management and treatment strategies.

Vertical Slot Fishways: Incremental Knowledge to Define the Best Solution.

River artificial fragmentation is arguably the most imperilling threat for freshwater-dependent fish species. Fish need to be able to freely move along river networks as not only spawning grounds but also refuge and feeding areas may be spatially and temporally separated. This incapacity of free displacement may result in genetic depletion of some populations, density reduction and even community changes, which may in turn affect how meta-community balances are regulated, potentially resulting in functional resilience reduction and ecosystem processes' malfunction. Fishways are the most common and widely used method to improve connectivity for fish species. These structures allow fish to negotiate full barriers, thus reducing their connectivity impairment. Among all technical fishway types, vertical slot fishways (VSF) are considered to be the best solution, as they remain operational even with fluctuating water discharges and allow fish to negotiate each cross-wall at their desired depth. In the present study, we collected both published and original data on fish experiments within VSF, to address two questions, (1) What variables affect fish passage during experimental fishway studies? and (2) What is the best VSF configuration? We used Bayesian Generalized Mixed Models accounting for random effects of non-controlled factors, limiting inherent data dependencies, that may influence the model outcome. Results highlight that fish size, regardless of the species, is a good predictor of fishway negotiation success. Generally, multiple slot fishways with one orifice proved to be the best solution. Future work should be focused on small-sized fish to further improve the design of holistic fishways.