Establishing and evaluating the gradient of item naming difficulty in post-stroke aphasia and semantic dementia.

Anomia is a common consequence following brain damage and a central symptom in semantic dementia (SD) and post-stroke aphasia (PSA), for instance. Picture naming tests are often used in clinical assessments and experience suggests that items vary systematically in their difficulty. Despite clinical intuitions and theoretical accounts, however, the existence and determinants of such a naming difficulty gradient remain to be empirically established and evaluated. Seizing the unique opportunity of two large-scale datasets of semantic dementia and post-stroke aphasia patients assessed with the same picture naming test, we applied an Item Response Theory (IRT) approach and we (a) established that an item naming difficulty gradient exists, which (b) partly differs between patient groups, and is (c) related in part to a limited number of psycholinguistic properties - frequency and familiarity for SD, frequency and word length for PSA. Our findings offer exciting future avenues for new, adaptive, time-efficient, and patient-tailored approaches to naming assessment and therapy.

The impact of bilateral versus unilateral anterior temporal lobe damage on face recognition, person knowledge and semantic memory.

The functional importance of the anterior temporal lobes (ATLs) has come to prominence in two active, albeit unconnected literatures-(i) face recognition and (ii) semantic memory. To generate a unified account of the ATLs, we tested the predictions from each literature and examined the effects of bilateral versus unilateral ATL damage on face recognition, person knowledge, and semantic memory. Sixteen people with bilateral ATL atrophy from semantic dementia (SD), 17 people with unilateral ATL resection for temporal lobe epilepsy (TLE; left = 10, right = 7), and 14 controls completed tasks assessing perceptual face matching, person knowledge and general semantic memory. People with SD were impaired across all semantic tasks, including person knowledge. Despite commensurate total ATL damage, unilateral resection generated mild impairments, with minimal differences between left- and right-ATL resection. Face matching performance was largely preserved but slightly reduced in SD and right TLE. All groups displayed the familiarity effect in face matching; however, it was reduced in SD and right TLE and was aligned with the level of item-specific semantic knowledge in all participants. We propose a neurocognitive framework whereby the ATLs underpin a resilient bilateral representation system that supports semantic memory, person knowledge and face recognition.

Fostering Innovation in Medical Education: Addressing the Void of Entrepreneurship Education in Anesthesiology and Pain Medicine Through Incubator Clubs.

Fewer than 30% of all medical schools have programs that encourage medical design innovation or entrepreneurship at the trainee level. This is particularly evident in the fields of anesthesiology and pain medicine, where utilizing medical devices constitutes a significant part of a clinician's daily practice. To fix this gap, our institution has developed an incubator club where trainees can learn about medical devices and entrepreneurship. Our goal is to present how this can be incorporated at other institutions because these clubs are a low resource utilization investment that can teach trainees valuable skills in innovation and entrepreneurship.

Use of corticosteroids for adult chronic pain interventions: sympathetic and peripheral nerve blocks, trigger point injections - guidelines from the American Society of Regional Anesthesia and Pain Medicine, the American Academy of Pain Medicine, the American Society of Interventional Pain Physicians, the International Pain and Spine Intervention Society, and the North American Spine Society.

BACKGROUND: There is potential for adverse events from corticosteroid injections, including increase in blood glucose, decrease in bone mineral density and suppression of the hypothalamic-pituitary axis. Published studies note that doses lower than those commonly injected provide similar benefit. METHODS: Development of the practice guideline was approved by the Board of Directors of American Society of Regional Anesthesia and Pain Medicine with several other societies agreeing to participate. The scope of guidelines was agreed on to include safety of the injection technique (landmark-guided, ultrasound or radiology-aided injections); effect of the addition of the corticosteroid on the efficacy of the injectate (local anesthetic or saline); and adverse events related to the injection. Based on preliminary discussions, it was decided to structure the topics into three separate guidelines as follows: (1) sympathetic, peripheral nerve blocks and trigger point injections; (2) joints; and (3) neuraxial, facet, sacroiliac joints and related topics (vaccine and anticoagulants). Experts were assigned topics to perform a comprehensive review of the literature and to draft statements and recommendations, which were refined and voted for consensus (≥75% agreement) using a modified Delphi process. The United States Preventive Services Task Force grading of evidence and strength of recommendation was followed. RESULTS: This guideline deals with the use and safety of corticosteroid injections for sympathetic, peripheral nerve blocks and trigger point injections for adult chronic pain conditions. All the statements and recommendations were approved by all participants after four rounds of discussion. The Practice Guidelines Committees and Board of Directors of the participating societies also approved all the statements and recommendations. The safety of some procedures, including stellate blocks, lower extremity peripheral nerve blocks and some sites of trigger point injections, is improved by imaging guidance. The addition of non-particulate corticosteroid to the local anesthetic is beneficial in cluster headaches but not in other types of headaches. Corticosteroid may provide additional benefit in transverse abdominal plane blocks and ilioinguinal/iliohypogastric nerve blocks in postherniorrhaphy pain but there is no evidence for pudendal nerve blocks. There is minimal benefit for the use of corticosteroids in trigger point injections. CONCLUSIONS: In this practice guideline, we provided recommendations on the use of corticosteroids in sympathetic blocks, peripheral nerve blocks, and trigger point injections to assist clinicians in making informed decisions.

Disruption of neural periodicity predicts clinical response after deep brain stimulation for obsessive-compulsive disorder.

Recent advances in surgical neuromodulation have enabled chronic and continuous intracranial monitoring during everyday life. We used this opportunity to identify neural predictors of clinical state in 12 individuals with treatment-resistant obsessive-compulsive disorder (OCD) receiving deep brain stimulation (DBS) therapy ( NCT05915741 ). We developed our neurobehavioral models based on continuous neural recordings in the region of the ventral striatum in an initial cohort of five patients and tested and validated them in a held-out cohort of seven additional patients. Before DBS activation, in the most symptomatic state, theta/alpha (9 Hz) power evidenced a prominent circadian pattern and a high degree of predictability. In patients with persistent symptoms (non-responders), predictability of the neural data remained consistently high. On the other hand, in patients who improved symptomatically (responders), predictability of the neural data was significantly diminished. This neural feature accurately classified clinical status even in patients with limited duration recordings, indicating generalizability that could facilitate therapeutic decision-making.

Methods for pragmatic randomized clinical trials of pain therapies: IMMPACT statement.

ABSTRACT: Pragmatic, randomized, controlled trials hold the potential to directly inform clinical decision making and health policy regarding the treatment of people experiencing pain. Pragmatic trials are designed to replicate or are embedded within routine clinical care and are increasingly valued to bridge the gap between trial research and clinical practice, especially in multidimensional conditions, such as pain and in nonpharmacological intervention research. To maximize the potential of pragmatic trials in pain research, the careful consideration of each methodological decision is required. Trials aligned with routine practice pose several challenges, such as determining and enrolling appropriate study participants, deciding on the appropriate level of flexibility in treatment delivery, integrating information on concomitant treatments and adherence, and choosing comparator conditions and outcome measures. Ensuring data quality in real-world clinical settings is another challenging goal. Furthermore, current trials in the field would benefit from analysis methods that allow for a differentiated understanding of effects across patient subgroups and improved reporting of methods and context, which is required to assess the generalizability of findings. At the same time, a range of novel methodological approaches provide opportunities for enhanced efficiency and relevance of pragmatic trials to stakeholders and clinical decision making. In this study, best-practice considerations for these and other concerns in pragmatic trials of pain treatments are offered and a number of promising solutions discussed. The basis of these recommendations was an Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT) meeting organized by the Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks.

Hierarchical Clustering Applied to Chronic Pain Drawings Identifies Undiagnosed Fibromyalgia: Implications for Busy Clinical Practice.

Currently-used assessments for fibromyalgia require clinicians to suspect a fibromyalgia diagnosis, a process susceptible to unintentional bias. Automated assessments of standard patient-reported outcomes (PROs) could be used to prompt formal assessments, potentially reducing bias. We sought to determine whether hierarchical clustering of patient-reported pain distribution on digital body map drawings predicted fibromyalgia diagnosis. Using an observational cohort from the University of Pittsburgh's Patient Outcomes Repository for Treatment registry, which contains PROs and electronic medical record data from 21,423 patients (March 17, 2016-June 25, 2019) presenting to pain management clinics, we tested the hypothesis that hierarchical clustering subgroup was associated with fibromyalgia diagnosis, as determined by ICD-10 code. Logistic regression revealed a significant relationship between the body map cluster subgroup and fibromyalgia diagnosis. The cluster subgroup with the most body areas selected was the most likely to receive a diagnosis of fibromyalgia when controlling for age, gender, anxiety, and depression. Despite this, more than two-thirds of patients in this cluster lacked a clinical fibromyalgia diagnosis. In an exploratory analysis to better understand this apparent underdiagnosis, we developed and applied proxies of fibromyalgia diagnostic criteria. We found that proxy diagnoses were more common than ICD-10 diagnoses, which may be due to less frequent clinical fibromyalgia diagnosis in men. Overall, we find evidence of fibromyalgia underdiagnosis, likely due to gender bias. Coupling PROs that take seconds to complete, such as a digital pain body map, with machine learning is a promising strategy to reduce bias in fibromyalgia diagnosis and improve patient outcomes. PERSPECTIVE: This investigation applies hierarchical clustering to patient-reported, digital pain body maps, finding an association between body map responses and clinical fibromyalgia diagnosis. Rapid, computer-assisted interpretation of pain body maps would be clinically useful in prompting more detailed assessments for fibromyalgia, potentially reducing gender bias.

[Evidence-based interventions to treat chronic low back pain: treatment selection for a personalized medicine approach : German version]. / Evidenzbasierte Interventionen zur Behandlung von chronischem Schmerz im unteren Rücken ­ Therapieauswahl für einen personalisierten Behandlungsansatz : Deutsche Fassung.

INTRODUCTION: Chronic low back pain (cLBP) is highly prevalent in the United States and globally, resulting in functional impairment and lowered quality of life. While many treatments are available for cLBP, clinicians have little information about which specific treatment(s) will work best for individual patients or subgroups of patients. The Back Pain Research Consortium, part of the National Institutes of Health Helping to End Addiction Long-termSM (HEAL) Initiative, will conduct a collaborative clinical trial, which seeks to develop a personalized medicine algorithm to optimize patient and provider treatment selection for patients with cLBP. OBJECTIVE: The primary objective of this article is to provide an update on evidence-based cLBP interventions and describe the process of reviewing and selecting interventions for inclusion in the clinical trial. METHODS: A working group of cLBP experts reviewed and selected interventions for inclusion in the clinical trial. The primary evaluation measures were strength of evidence and magnitude of treatment effect. When available in the literature, duration of effect, onset time, carryover effect, multimodal efficacy, responder subgroups, and evidence for the mechanism of treatment effect or biomarkers were considered. CONCLUSION: The working group selected 4 leading, evidence-based treatments for cLBP to be tested in the clinical trial and for use in routine clinical treatment. These treatments include (1) duloxetine, (2) acceptance and commitment therapy, (3) a classification-based exercise and manual therapy intervention, and (4) a self-management approach. These interventions each had a moderate to high level of evidence to support a therapeutic effect and were from different therapeutic classes.

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.

A Randomized Controlled Neuroimaging Trial of Cognitive Behavioral Therapy for Fibromyalgia Pain.

OBJECTIVE: Fibromyalgia (FM) is characterized by pervasive pain-related symptomatology and high levels of negative affect. Mind-body treatments such as cognitive behavioral therapy (CBT) appear to foster improvement in FM via reductions in pain-related catastrophizing, a set of negative, pain-amplifying cognitive and emotional processes. However, the neural underpinnings of CBT's catastrophizing-reducing effects remain uncertain. This randomized controlled mechanistic trial was designed to assess CBT's effects on pain catastrophizing and its underlying brain circuitry. METHODS: Of 114 enrolled participants, 98 underwent a baseline neuroimaging assessment and were randomized to 8 weeks of individual CBT or a matched FM education control (EDU) condition. RESULTS: Compared with EDU, CBT produced larger decreases in pain catastrophizing post treatment (P < 0.05) and larger reductions in pain interference and symptom impact. Decreases in pain catastrophizing played a significant role in mediating those functional improvements in the CBT group. At baseline, brain functional connectivity between the ventral posterior cingulate cortex (vPCC), a key node of the default mode network (DMN), and somatomotor and salience network regions was increased during catastrophizing thoughts. Following CBT, vPCC connectivity to somatomotor and salience network areas was reduced. CONCLUSION: Our results suggest clinically important and CBT-specific associations between somatosensory/motor- and salience-processing brain regions and the DMN in chronic pain. These patterns of connectivity may contribute to individual differences (and treatment-related changes) in somatic self-awareness. CBT appears to provide clinical benefits at least partially by reducing pain-related catastrophizing and producing adaptive alterations in DMN functional connectivity.

The neural substrates of transdiagnostic cognitive-linguistic heterogeneity in primary progressive aphasia.

BACKGROUND: Clinical variants of primary progressive aphasia (PPA) are diagnosed based on characteristic patterns of language deficits, supported by corresponding neural changes on brain imaging. However, there is (i) considerable phenotypic variability within and between each diagnostic category with partially overlapping profiles of language performance between variants and (ii) accompanying non-linguistic cognitive impairments that may be independent of aphasia magnitude and disease severity. The neurobiological basis of this cognitive-linguistic heterogeneity remains unclear. Understanding the relationship between these variables would improve PPA clinical/research characterisation and strengthen clinical trial and symptomatic treatment design. We address these knowledge gaps using a data-driven transdiagnostic approach to chart cognitive-linguistic differences and their associations with grey/white matter degeneration across multiple PPA variants. METHODS: Forty-seven patients (13 semantic, 15 non-fluent, and 19 logopenic variant PPA) underwent assessment of general cognition, errors on language performance, and structural and diffusion magnetic resonance imaging to index whole-brain grey and white matter changes. Behavioural data were entered into varimax-rotated principal component analyses to derive orthogonal dimensions explaining the majority of cognitive variance. To uncover neural correlates of cognitive heterogeneity, derived components were used as covariates in neuroimaging analyses of grey matter (voxel-based morphometry) and white matter (network-based statistics of structural connectomes). RESULTS: Four behavioural components emerged: general cognition, semantic memory, working memory, and motor speech/phonology. Performance patterns on the latter three principal components were in keeping with each variant's characteristic profile, but with a spectrum rather than categorical distribution across the cohort. General cognitive changes were most marked in logopenic variant PPA. Regardless of clinical diagnosis, general cognitive impairment was associated with inferior/posterior parietal grey/white matter involvement, semantic memory deficits with bilateral anterior temporal grey/white matter changes, working memory impairment with temporoparietal and frontostriatal grey/white matter involvement, and motor speech/phonology deficits with inferior/middle frontal grey matter alterations. CONCLUSIONS: Cognitive-linguistic heterogeneity in PPA closely relates to individual-level variations on multiple behavioural dimensions and grey/white matter degeneration of regions within and beyond the language network. We further show that employment of transdiagnostic approaches may help to understand clinical symptom boundaries and reveal clinical and neural profiles that are shared across categorically defined variants of PPA.

SuRxgWell: study protocol for a randomized controlled trial of telemedicine-based digital cognitive behavioral intervention for high anxiety and depression among patients undergoing elective hip and knee arthroplasty surgery.

BACKGROUND: Mood disorders (anxiety, depression), sleep disorders, and catastrophizing lead to increased post-operative pain perception, increase in postoperative opioid consumption, decreased engagement with physical activity, and increased resource utilization in surgical patients. Psychosocial disorders significantly affect postoperative outcome. Unfortunately, studies focused on perioperative psychological assessment and treatment are scarce. We propose to test whether digital cognitive behavioral intervention (dCBI) can help surgical patients. dCBI such as RxWell™ is a proven treatment for mood disorders in medical patients such as reducing depression in patients with inflammatory bowel disease. We hypothesize that RxWell™ will also be effective in surgical patients. This study aims to test whether RxWell™ can improve preoperative mood disorders and subsequently reduce postoperative pain and opioid requirement in patients scheduled for primary total hip and knee arthroplasty (THA, TKA). We named the trial as the SuRxgWell trial. METHODS: This is a randomized, controlled trial that will enroll primary and unilateral THA or TKA patients with anxiety and/or depression symptoms before surgery to receive the SuRxgWell dCBI program and investigate its impact on postoperative outcomes including postoperative pain, anxiety, depression, sleep disorder, and catastrophizing. After signing an informed consent, subjects will be screened using the PROMIS questionnaires, and subjects with a T-score of ≥ 60 on the short Patient-Reported Outcomes Measurement Information System (PROMIS) 4a Anxiety and/or short PROMIS 4a Depression questionnaires will be randomized to either usual care (control group) or the cognitive behavioral intervention, RxWell™, plus usual care (intervention group). The control group will receive information on how to locate tools to address anxiety and depression, whereas the intervention group will have access to SuRxgWell 1 month prior to surgery and up to 3 months after surgery. The allocation will be 3:1 (intervention to control). Investigators will be blinded, but research coordinators approaching patients and research subjects will not. The primary outcome will be day of surgery anxiety or depression symptoms measured with the PROMIS Short Form v1.0 -Anxiety 4a/Depression and Generalized Anxiety Disorder Measure (GAD-7) and Patient Health Questionnaire (PHQ-8). Secondary end points include measuring other health-related quality of life outcomes including sleep disturbance, fatigue, ability to participate in social roles, pain interference, cognitive function, pain catastrophizing, and physical function. Other secondary outcomes include collecting data about preoperative and postoperative pain scores, and pain medication usage, and orthopedic functional recovery at baseline, day of surgery, and 1, 2, and 3 months after the surgery with the Pain Catastrophizing Scale, the Knee injury and Osteoarthritis Outcome Score (KOOS), and Hip injury and Osteoarthritis Outcome Score (HOOS). In addition, subjects will be asked to complete a GAD-7 and PHQ-8 questionnaires bi-weekly (via the RxWell™ app for the interventional group or REDCAP for the control group). Data about postsurgical complications, and resource utilization will also be recorded. We will also receive monthly reports measuring the usage and engagement of RxWell use for each participant randomized to that arm. The primary hypotheses will be assessed with intention-to-treat estimates, and differences in primary outcome will be tested using independent two sample t-tests. This trial is registered to the ClinicalTrials.gov database (NCT05658796) and supported by the DAPM, UPMC Health Plan, and the NIH. DISCUSSION: Our trial will evaluate the feasibility of digital cognitive behavioral intervention as a perioperative tool to improve anxiety and depression before and after major orthopedic surgery in comparison to education. If digital cognitive behavioral intervention proves to be effective, this might have important clinical implications, reducing the incidence of chronic postsurgical pain and improving outcomes.

Telemedicine-Based Digital Cognitive Behavioral Intervention for Perioperative Anxiety and Depression for Total Knee Arthroplasty.

Introduction: Preoperative anxiety and depression have been shown to increase postoperative pain and opioid consumption by up to 50% in patients undergoing primary unilateral Total Knee Arthroplasty (TKA). We hypothesized that the use of a telemedicine-based digital Cognitive Behavioral Intervention program (RxWell®) started one month prior to surgery would control anxiety and depression prior to surgery. Materials and methods: This was a randomized, controlled trial that enrolled patients undergoing primary unilateral TKA. At least a month prior to surgery, patients who gave consent to participate were asked to complete PROMIS® (Patient-Reported Outcomes Measurement Information System) emotional anxiety short form 8a and PROMIS® emotional depression short form-8a questionnaires. Patients with T-scores of ≥ 57 were randomized to either a no intervention (control group) or a RxWell® program (treatment group) for a month prior to surgery. The primary outcome of this proof-of-concept study was the ability of the RxWell® to normalize patients' PROMIS anxiety T scores. Results: T scores for anxiety and depression among patients randomized to the RxWell® group significantly decreased from 64.3 ± 3.0 at the time of randomization to 58.5 ± 2.6 prior to surgery (n=5, p=0.006), whereas no changes in T scores were recorded in the control group (59.4 ± 4.2 at the time of randomization vs. 57.7 ± 6.2; n=6, p=0.559). Conclusion: These preliminary data suggest that the use of a RxWell® program represents an effective approach to control anxiety and depression prior to surgery. In contrast, it seems that in the absence of treatment, anxiety level remains similar over a month prior to surgery.

Using Natural Language Processing and Machine Learning to Identify Opioids in Electronic Health Record Data.

Purpose: This study evaluates the utility of machine learning (ML) and natural language processing (NLP) in the processing and initial analysis of data within the electronic health record (EHR). We present and evaluate a method to classify medication names as either opioids or non-opioids using ML and NLP. Patients and Methods: A total of 4216 distinct medication entries were obtained from the EHR and were initially labeled by human reviewers as opioid or non-opioid medications. An approach incorporating bag-of-words NLP and supervised ML classification was implemented in MATLAB and used to automatically classify medications. The automated method was trained on 60% of the input data, evaluated on the remaining 40%, and compared to manual classification results. Results: A total of 3991 medication strings were classified as non-opioid medications (94.7%), and 225 were classified as opioid medications by the human reviewers (5.3%). The algorithm achieved a 99.6% accuracy, 97.8% sensitivity, 94.6% positive predictive value, F1 value of 0.96, and a receiver operating characteristic (ROC) curve with 0.998 area under the curve (AUC). A secondary analysis indicated that approximately 15-20 opioids (and 80-100 non-opioids) were needed to achieve accuracy, sensitivity, and AUC values of above 90-95%. Conclusion: The automated approach achieved excellent performance in classifying opioids or non-opioids, even with a practical number of human reviewed training examples. This will allow a significant reduction in manual chart review and improve data structuring for retrospective analyses in pain studies. The approach may also be adapted to further analysis and predictive analytics of EHR and other "big data" studies.

Einstein exponential operation laws of spherical fuzzy sets and aggregation operators in decision making.

The spherical fuzzy set (SFS) model is one of the newly developed extensions of fuzzy sets (FS) for the purpose of dealing with uncertainty or vagueness in decision making. The aim of this paper is to define new exponential and Einstein exponential operational laws for spherical fuzzy sets and their corresponding aggregation operators. We introduce the operational laws for exponential and Einstein exponential SFSs in which the base values are crisp numbers and the exponents (weights) are spherical fuzzy numbers. Some of the properties and characteristics of the proposed operations are then discussed. Based on these operational laws, some new aggregation operators for the SFS model, namely Spherical Fuzzy Weighted Exponential Averaging (SFWEA) and Spherical Fuzzy Einstein Weighted Exponential Averaging (SFEWEA) operators are introduced. Finally, a decision-making algorithm based on these newly introduced aggregation operators is proposed and applied to a multi-criteria decision making (MCDM) problem related to ranking different types of psychotherapy.

Novel techniques for assessment of bone tissue material properties.

PURPOSE OF REVIEW: The purpose of this review will be to shed light on novel techniques for assessment of bone tissue material properties. RECENT FINDINGS: Recently there has been an increase in modalities to investigate bone tissue material properties. Historically, clinicians treating patients with bone disorders have relied upon the use of bone mineral density (BMD) as assessed by dual-energy X-ray absorptiometry (DXA). Although DXA provides an ability to screen at a large-scale population level, it only explains about 60% of the fracture risk. Recent advances include the use of imaging modalities, responses to load, and novel infrared (IR) techniques. SUMMARY: These newer techniques have not reached a point for population level screening; however, they may inform the science of bone biology further and help discern various bone disease states.

Distance-dependent distribution thresholding in probabilistic tractography.

Tractography is widely used in human studies of connectivity with respect to every brain region, function, and is explored developmentally, in adulthood, ageing, and in disease. However, the core issue of how to systematically threshold, taking into account the inherent differences in connectivity values for different track lengths, and to do this in a comparable way across studies has not been solved. By utilising 54 healthy individuals' diffusion-weighted image data taken from HCP, this study adopted Monte Carlo derived distance-dependent distributions (DDDs) to generate distance-dependent thresholds with various levels of alpha for connections of varying lengths. As a test case, we applied the DDD approach to generate a language connectome. The resulting connectome showed both short- and long-distance structural connectivity in the close and distant regions as expected for the dorsal and ventral language pathways, consistent with the literature. The finding demonstrates that the DDD approach is feasible to generate data-driven DDDs for common thresholding and can be used for both individual and group thresholding. Critically, it offers a standard method that can be applied to various probabilistic tracking datasets.

Cannabinoid Therapy: Attitudes and Experiences of People With Chronic Pain.

OBJECTIVE: Clinical trials of cannabinoids for chronic pain have mixed and often inconclusive results. In contrast, many prospective observational studies show the analgesic effects of cannabinoids. This survey study aimed to examine the experiences/attitudes of individuals with chronic pain who are currently taking, have previously taken, or never taken cannabinoids for chronic pain to inform future research. METHODS: This study is based on a cross-sectional, web-based survey of individuals with self-reported chronic pain. Participants were invited to participate through an email that was distributed to the listservs of patient advocacy groups and foundations that engage individuals with chronic pain. RESULTS: Of the 969 respondents, 444 (46%) respondents reported currently taking, 213 (22%) previously taken, and 312 (32%) never taken cannabinoids for pain. Participants reported using cannabinoids to treat a wide variety of chronic pain conditions. Those currently taking cannabinoids (vs previously) more frequently reported: (1) large improvements from cannabinoids in all pain types, including particularly difficult-to-treat chronic overlapping pain conditions (eg, pelvic pain), (2) improvements in comorbid symptoms (eg, sleep), and (3) lower interference from side effects. Those currently taking cannabinoids reported more frequent and satisfactory communication with clinicians regarding cannabinoid use. Those never taken cannabinoids reported a lack of suggestion/approval of a clinician (40%), illegality (25%), and lack of FDA regulation (19%) as reasons for never trying cannabinoids. CONCLUSION: These findings underscore the importance of conducting high-quality clinical trials that include diverse pain populations and clinically relevant outcomes that if successful, could support FDA approval of cannabinoid products. Clinicians could then prescribe and monitor these treatments similarly to other chronic pain medications.