Malaria parasite clag3 genes determine channel-mediated nutrient uptake by infected red blood cells.

Development of malaria parasites within vertebrate erythrocytes requires nutrient uptake at the host cell membrane. The plasmodial surface anion channel (PSAC) mediates this transport and is an antimalarial target, but its molecular basis is unknown. We report a parasite gene family responsible for PSAC activity. We used high-throughput screening for nutrient uptake inhibitors to identify a compound highly specific for channels from the Dd2 line of the human pathogen P. falciparum. Inheritance of this compound's affinity in a Dd2 × HB3 genetic cross maps to a single parasite locus on chromosome 3. DNA transfection and in vitro selections indicate that PSAC-inhibitor interactions are encoded by two clag3 genes previously assumed to function in cytoadherence. These genes are conserved in plasmodia, exhibit expression switching, and encode an integral protein on the host membrane, as predicted by functional studies. This protein increases host cell permeability to diverse solutes.

Using in vivo functional and structural connectivity to predict chronic stroke aphasia deficits.

Focal brain damage caused by stroke can result in aphasia and advances in cognitive neuroscience suggest that impairment may be associated with network-level disorder rather than just circumscribed cortical damage. Several studies have shown meaningful relationships between brain-behaviour using lesions; however, only a handful of studies have incorporated in vivo structural and functional connectivity. Patients with chronic post-stroke aphasia were assessed with structural (n = 68) and functional (n = 39) MRI to assess whether predicting performance can be improved with multiple modalities and if additional variance can be explained compared to lesion models alone. These neural measurements were used to construct models to predict four key language-cognitive factors: (i) phonology; (ii) semantics; (iii) executive function; and (iv) fluency. Our results showed that each factor (except executive ability) could be significantly related to each neural measurement alone; however, structural and functional connectivity models did not explain additional variance above the lesion models. We did find evidence that the structural and functional predictors may be linked to the core lesion sites. First, the predictive functional connectivity features were found to be located within functional resting-state networks identified in healthy controls, suggesting that the result might reflect functionally specific reorganization (damage to a node within a network can result in disruption to the entire network). Second, predictive structural connectivity features were located within core lesion sites, suggesting that multimodal information may be redundant in prediction modelling. In addition, we observed that the optimum sparsity within the regularized regression models differed for each behavioural component and across different imaging features, suggesting that future studies should consider optimizing hyperparameters related to sparsity per target. Together, the results indicate that the observed network-level disruption was predicted by the lesion alone and does not significantly improve model performance in predicting the profile of language impairment.

[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.

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.

Direct Neural Evidence for the Contrastive Roles of the Complementary Learning Systems in Adult Acquisition of Native Vocabulary.

The Complementary Learning Systems (CLS) theory provides a powerful framework for considering the acquisition, consolidation, and generalization of new knowledge. We tested this proposed neural division of labor in adults through an investigation of the consolidation and long-term retention of newly learned native vocabulary with post-learning functional neuroimaging. Newly learned items were compared with two conditions: 1) previously known items to highlight the similarities and differences with established vocabulary and 2) unknown/untrained items to provide a control for non-specific perceptual and motor speech output. Consistent with the CLS, retrieval of newly learned items was supported by a combination of regions associated with episodic memory (including left hippocampus) and the language-semantic areas that support established vocabulary (left inferior frontal gyrus and left anterior temporal lobe). Furthermore, there was a shifting division of labor across these two networks in line with the items' consolidation status; faster naming was associated with more activation of language-semantic areas and lesser activation of episodic memory regions. Hippocampal activity during naming predicted more than half the variation in naming retention 6 months later.

Biobehavioral Assessments in BACPAC: Recommendations, Rationale, and Methods.

The Biobehavioral Working Group of BACPAC was charged to evaluate a range of psychosocial, psychophysical, and behavioral domains relevant to chronic low back pain, and recommend specific assessment tools and procedures to harmonize biobehavioral data collection across the consortium. Primary references and sources for measure selection were the Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials, the Minimum Data Set from the National Institutes of Health (NIH) Research Task Force on Standards for Chronic Low Back Pain, the Patient-Reported Outcomes Measurement Information System, and NeuroQOL. The questionnaire's recommendations supplemented the NIH HEAL Common Data Elements and BACPAC Minimum Data Set. Five domains were identified for inclusion: Pain Characteristics and Qualities; Pain-Related Psychosocial/Behavioral Factors; General Psychosocial Factors; Lifestyle Choices; and Social Determinants of Health/Social Factors. The Working Group identified best practices for required and optional Quantitative Sensory Testing of psychophysical pain processing for use in BACPAC projects.

The Back Pain Consortium (BACPAC) Research Program Data Harmonization: Rationale for Data Elements and Standards.

OBJECTIVE: One aim of the Back Pain Consortium (BACPAC) Research Program is to develop an integrated model of chronic low back pain that is informed by combined data from translational research and clinical trials. We describe efforts to maximize data harmonization and accessibility to facilitate Consortium-wide analyses. METHODS: Consortium-wide working groups established harmonized data elements to be collected in all studies and developed standards for tabular and nontabular data (eg, imaging and omics). The BACPAC Data Portal was developed to facilitate research collaboration across the Consortium. RESULTS: Clinical experts developed the BACPAC Minimum Dataset with required domains and outcome measures to be collected by use of questionnaires across projects. Other nonrequired domain-specific measures are collected by multiple studies. To optimize cross-study analyses, a modified data standard was developed on the basis of the Clinical Data Interchange Standards Consortium Study Data Tabulation Model to harmonize data structures and facilitate integration of baseline characteristics, participant-reported outcomes, chronic low back pain treatments, clinical exam, functional performance, psychosocial characteristics, quantitative sensory testing, imaging, and biomechanical data. Standards to accommodate the unique features of chronic low back pain data were adopted. Research units submit standardized study data to the BACPAC Data Portal, developed as a secure cloud-based central data repository and computing infrastructure for researchers to access and conduct analyses on data collected by or acquired for BACPAC. CONCLUSIONS: BACPAC harmonization efforts and data standards serve as an innovative model for data integration that could be used as a framework for other consortia with multiple, decentralized research programs.

Back Pain Consortium (BACPAC): Protocol and Pilot Study Results for a Randomized Comparative-Effectiveness Trial of Antidepressants, Fear Avoidance Rehabilitation, or the Combination for Chronic Low Back Pain and Comorbid High Negative Affect.

OBJECTIVE: Patients with chronic low back pain (CLBP) and comorbid depression or anxiety disorders are highly prevalent. Negative affect (NA) refers to a combination of negative thoughts, emotions, and behaviors. Patients with CLBP with high NA have greater pain, worse treatment outcomes, and greater prescription opioid misuse. We present the protocol for SYNNAPTIC (SYNergizing Negative Affect & Pain Treatment In Chronic pain). DESIGN: A randomized comparative-effectiveness study of antidepressants, fear-avoidance rehabilitation, or their combination in 300 patients with CLBP with high NA. In the antidepressant- or rehabilitation-only arms, SYNNAPTIC includes an adaptive design of re-randomization after 4 months for nonresponders. SETTING: A multisite trial conducted in routine pain clinical treatment settings: pain clinics and physical and occupational therapy treatment centers. METHODS: Inclusion criteria include CLBP with elevated depression and anxiety symptoms. Antidepressant and rehabilitation treatments follow validated and effective protocols for musculoskeletal pain in patients with high NA. Power and sample size are based on superior outcomes of combination therapy with these same treatments in a 71-subject 4-arm pilot randomized controlled trial. CONCLUSIONS: SYNNAPTIC addresses the lack of evidence-based protocols for the treatment of the vulnerable subgroup of patients with CLBP and high NA. We hypothesize that combination therapy of antidepressants plus fear-avoidance rehabilitation will be more effective than each treatment alone. TRIAL REGISTRATION: ClinicalTrials.gov ID: NCT04747314.

The Back Pain Consortium (BACPAC) Research Program: Structure, Research Priorities, and Methods.

In 2019, the National Health Interview survey found that nearly 59% of adults reported pain some, most, or every day in the past 3 months, with 39% reporting back pain, making back pain the most prevalent source of pain, and a significant issue among adults. Often, identifying a direct, treatable cause for back pain is challenging, especially as it is often attributed to complex, multifaceted issues involving biological, psychological, and social components. Due to the difficulty in treating the true cause of chronic low back pain (cLBP), an over-reliance on opioid pain medications among cLBP patients has developed, which is associated with increased prevalence of opioid use disorder and increased risk of death. To combat the rise of opioid-related deaths, the National Institutes of Health (NIH) initiated the Helping to End Addiction Long-TermSM (HEAL) initiative, whose goal is to address the causes and treatment of opioid use disorder while also seeking to better understand, diagnose, and treat chronic pain. The NIH Back Pain Consortium (BACPAC) Research Program, a network of 14 funded entities, was launched as a part of the HEAL initiative to help address limitations surrounding the diagnosis and treatment of cLBP. This paper provides an overview of the BACPAC research program's goals and overall structure, and describes the harmonization efforts across the consortium, define its research agenda, and develop a collaborative project which utilizes the strengths of the network. The purpose of this paper is to serve as a blueprint for other consortia tasked with the advancement of pain related science.

Offset analgesia is associated with opposing modulation of medial versus dorsolateral prefrontal cortex activations: A functional near-infrared spectroscopy study.

Offset analgesia is defined by a dramatic drop in perceived pain intensity with a relatively small decrease in noxious input. Although functional magnetic resonance imaging studies implicate subcortical descending inhibitory circuits during offset analgesia, the role of cortical areas remains unclear. The current study identifies cortical correlates of offset analgesia using functional near infrared spectroscopy (fNIRS). Twenty-four healthy volunteers underwent fNIRS scanning during offset (OS) and control (Con) heat stimuli applied to the forearm. After controlling for non-neural hemodynamic responses in superficial tissues, widespread increases in cortical oxygenated hemoglobin concentration were observed, reflecting cortical activation during heat pain. OS-Con contrasts revealed deactivations in bilateral medial prefrontal cortex (mPFC) and bilateral somatosensory cortex (SSC) associated with offset analgesia. Right dorsolateral prefrontal cortex (dlPFC) showed activation only during OS. These data demonstrate opposing cortical activation patterns during offset analgesia and support a model in which right dlPFC underlies ongoing evaluation of pain intensity change. With predictions of decreasing pain intensity, right dlPFC activation likely inhibits ascending noxious input via subcortical pathways resulting in SSC and mPFC deactivation. This study identifies cortical circuitry underlying offset analgesia and introduces the use of fNIRS to study pain modulation in an outpatient clinical environment.

Complex nutrient channel phenotypes despite Mendelian inheritance in a Plasmodium falciparum genetic cross.

Malaria parasites activate a broad-selectivity ion channel on their host erythrocyte membrane to obtain essential nutrients from the bloodstream. This conserved channel, known as the plasmodial surface anion channel (PSAC), has been linked to parasite clag3 genes in P. falciparum, but epigenetic switching between the two copies of this gene hinders clear understanding of how the encoded protein determines PSAC activity. Here, we used linkage analysis in a P. falciparum cross where one parent carries a single clag3 gene to overcome the effects of switching and confirm a primary role of the clag3 product with high confidence. Despite Mendelian inheritance, CLAG3 conditional knockdown revealed remarkably preserved nutrient and solute uptake. Even more surprisingly, transport remained sensitive to a CLAG3 isoform-specific inhibitor despite quantitative knockdown, indicating that low doses of the CLAG3 transgene are sufficient to confer block. We then produced a complete CLAG3 knockout line and found it exhibits an incomplete loss of transport activity, in contrast to rhoph2 and rhoph3, two PSAC-associated genes that cannot be disrupted because nutrient uptake is abolished in their absence. Although the CLAG3 knockout did not incur a fitness cost under standard nutrient-rich culture conditions, this parasite could not be propagated in a modified medium that more closely resembles human plasma. These studies implicate oligomerization of CLAG paralogs encoded by various chromosomes in channel formation. They also reveal that CLAG3 is dispensable under standard in vitro conditions but required for propagation under physiological conditions.

Artificial intelligence in ophthalmology: an insight into neurodegenerative disease.

PURPOSE OF REVIEW: The aging world population accounts for the increasing prevalence of neurodegenerative diseases such as Alzheimer's and Parkinson's which carry a significant health and economic burden. There is therefore a need for sensitive and specific noninvasive biomarkers for early diagnosis and monitoring. Advances in retinal and optic nerve multimodal imaging as well as the development of artificial intelligence deep learning systems (AI-DLS) have heralded a number of promising advances of which ophthalmologists are at the forefront. RECENT FINDINGS: The association among retinal vascular, nerve fiber layer, and macular findings in neurodegenerative disease is well established. In order to optimize the use of these ophthalmic parameters as biomarkers, validated AI-DLS are required to ensure clinical efficacy and reliability. Varied image acquisition methods and protocols as well as variability in neurogenerative disease diagnosis compromise the robustness of ground truths that are paramount to developing high-quality training datasets. SUMMARY: In order to produce effective AI-DLS for the diagnosis and monitoring of neurodegenerative disease, multicenter international collaboration is required to prospectively produce large inclusive datasets, acquired through standardized methods and protocols. With a uniform approach, the efficacy of resultant clinical applications will be maximized.

Comparison of test-retest reliability of BOLD and pCASL fMRI in a two-center study.

BACKGROUND: The establishment of test-retest reliability and reproducibility (TRR) is an important part of validating any research tool, including functional magnetic resonance imaging (fMRI). The primary objective of this study is to investigate the reliability of pseudo-Continuous Arterial Spin Labeling (pCASL) and Blood Oxygen Level Dependent (BOLD) fMRI data acquired across two different scanners in a sample of healthy adults. While single site/single scanner studies have shown acceptable repeatability, TRR of both in a practical multisite study occurring in two facilities spread out across the country with weeks to months between scans is critically needed. METHODS: Ten subjects were imaged with similar 3 T MRI scanners at the University of Pittsburgh and Massachusetts General Hospital. Finger-tapping and Resting-state data were acquired for both techniques. Analysis of the resting state data for functional connectivity was performed with the Functional Connectivity Toolbox, while analysis of the finger tapping data was accomplished with FSL. pCASL Blood flow data was generated using AST Toolbox. Activated areas and networks were identified via pre-defined atlases and dual-regression techniques. Analysis for TRR was conducted by comparing pCASL and BOLD images in terms of Intraclass correlation coefficients, Dice Similarity Coefficients, and repeated measures ANOVA. RESULTS: Both BOLD and pCASL scans showed strong activation and correlation between the two locations for the finger tapping tasks. Functional connectivity analyses identified elements of the default mode network in all resting scans at both locations. Multivariate repeated measures ANOVA showed significant variability between subjects, but no significant variability for location. Global CBF was very similar between the two scanning locations, and repeated measures ANOVA showed no significant differences between the two scanning locations. CONCLUSIONS: The results of this study show that when similar scanner hardware and software is coupled with identical data analysis protocols, consistent and reproducible functional brain images can be acquired across sites. The variability seen in the activation maps is greater for pCASL versus BOLD images, as expected, however groups maps are remarkably similar despite the low number of subjects. This demonstrates that multi-site fMRI studies of task-based and resting state brain activity is feasible.

Content Word Production during Discourse in Aphasia: Deficits in Word Quantity, Not Lexical-Semantic Complexity.

Although limited and reduced connected speech production is one, if not the most, prominent feature of aphasia, few studies have examined the properties of content words produced during discourse in aphasia, in comparison to the many investigations of single-word production. In this study, we used a distributional analysis approach to investigate the properties of content word production during discourse by 46 participants spanning a wide range of chronic poststroke aphasia and 20 neurotypical adults, using different stimuli that elicited three discourse genres (descriptive, narrative, and procedural). Initially, we inspected the discourse data with respect to the quantity of production, lexical-semantic diversity, and psycholinguistic features (frequency and imageability) of content words. Subsequently, we created a "lexical-semantic landscape," which is sensitive to subtle changes and allowed us to evaluate the pattern of changes in discourse production across groups. Relative to neurotypical adults, all persons with aphasia (both fluent and nonfluent) showed significant reduction in the quantity and diversity of production, but the lexical-semantic complexity of word production directly mirrored neurotypical performance. Specifically, persons with aphasia produced the same rate of nouns/verbs, and their discourse samples covered the full range of word frequency and imageability, albeit with reduced word quantity. These findings provide novel evidence that, unlike in other disorders (e.g., semantic dementia), discourse production in poststroke aphasia has relatively preserved lexical-semantic complexity but demonstrates significantly compromised quantity of content word production. Voxel-wise lesion-symptom mapping using both univariate and multivariate approaches revealed left frontal regions particularly the pars opercularis, insular cortex, and central and frontal opercular cortices supporting word retrieval during connected speech, irrespective of their word class or lexical-semantic complexity.

Graded, multidimensional intra- and intergroup variations in primary progressive aphasia and post-stroke aphasia.

Language impairments caused by stroke (post-stroke aphasia, PSA) and neurodegeneration (primary progressive aphasia, PPA) have overlapping symptomatology, nomenclature and are classically divided into categorical subtypes. Surprisingly, PPA and PSA have rarely been directly compared in detail. Rather, previous studies have compared certain subtypes (e.g. semantic variants) or have focused on a specific cognitive/linguistic task (e.g. reading). This study assessed a large range of linguistic and cognitive tasks across the full spectra of PSA and PPA. We applied varimax-rotated principal component analysis to explore the underlying structure of the variance in the assessment scores. Similar phonological, semantic and fluency-related components were found for PSA and PPA. A combined principal component analysis across the two aetiologies revealed graded intra- and intergroup variations on all four extracted components. Classification analysis was used to test, formally, whether there were any categorical boundaries for any subtypes of PPA or PSA. Semantic dementia formed a true diagnostic category (i.e. within group homogeneity and distinct between-group differences), whereas there was considerable overlap and graded variations within and between other subtypes of PPA and PSA. These results suggest that (i) a multidimensional rather than categorical classification system may be a better conceptualization of aphasia from both causes; and (ii) despite the very different types of pathology, these broad classes of aphasia have considerable features in common.

A unified model of post-stroke language deficits including discourse production and their neural correlates.

The clinical profiles of individuals with post-stroke aphasia demonstrate considerable variation in the presentation of symptoms. Recent aphasiological studies have attempted to account for this individual variability using a multivariate data-driven approach (principal component analysis) on an extensive neuropsychological and aphasiological battery, to identify fundamental domains of post-stroke aphasia. These domains mainly reflect phonology, semantics and fluency; however, these studies did not account for variability in response to different forms of connected speech, i.e. discourse genres. In the current study, we initially examined differences in the quantity, diversity and informativeness between three different discourse genres, including a simple descriptive genre and two naturalistic forms of connected speech (storytelling narrative, and procedural discourse). Subsequently, we provided the first quantitative investigation on the multidimensionality of connected speech production at both behavioural and neural levels. Connected speech samples across descriptive, narrative, and procedural discourse genres were collected from 46 patients with chronic post-stroke aphasia and 20 neurotypical adults. Content analyses conducted on all connected speech samples indicated that performance differed across discourse genres and between groups. Specifically, storytelling narratives provided higher quantities of content words and lexical diversity compared to composite picture description and procedural discourse. The analyses further revealed that, relative to neurotypical adults, patients with aphasia, both fluent and non-fluent, showed reduction in the quantity of verbal production, lexical diversity, and informativeness across all discourses. Given the differences across the discourses, we submitted the connected speech metrics to principal component analysis alongside an extensive neuropsychological/aphasiological battery that assesses a wide range of language and cognitive skills. In contrast to previous research, three unique orthogonal connected speech components were extracted in a unified model, reflecting verbal quantity, verbal quality, and motor speech, alongside four core language and cognitive components: phonological production, semantic processing, phonological recognition, and executive functions. Voxel-wise lesion-symptom mapping using these components provided evidence on the involvement of widespread cortical regions and their white matter connections. Specifically, left frontal regions and their underlying white matter tracts corresponding to the frontal aslant tract and the anterior segment of the arcuate fasciculus were particularly engaged with the quantity and quality of fluent connected speech production while controlling for other co-factors. The neural correlates associated with the other language domains align with existing models on the ventral and dorsal pathways for language processing.

Integrated Psychosocial Group Treatment: A Randomized Pilot Trial of a Harm Reduction and Preventive Approach for Patients with Chronic Pain at Risk of Opioid Misuse.

OBJECTIVE: To examine the benefits of an integrated psychosocial group treatment (IPGT) model for patients with chronic pain at risk of opioid misuse. DESIGN: This study was a small-scale, single-blinded, two-group randomized controlled trial. SETTING: Outpatient. SUBJECTS: Adults with chronic pain of >3 months' duration who were currently prescribed opioid medication and were at risk of opioid misuse. METHODS: Patients with chronic pain who were at risk of opioid misuse (n = 30) were randomly assigned to IPGT or treatment as usual. IPGT consists of six group sessions of psychoeducation, motivational interviewing, cognitive behavioral therapy, mindfulness, and peer support. Participants were assessed at baseline, first follow-up at 6 weeks, and a posttreatment follow-up at 9 weeks. Outcomes included feasibility, acceptability, and preliminary efficacy. Data were analyzed with descriptive and multivariate analyses. RESULTS: All intervention components were delivered to 87% of the participants, and IPGT recipients reported a high level of satisfaction. Results of the multivariate analyses demonstrated nonsignificant improvements in pain severity (ß = 0.22, 95% CI: -0.24 to 0.66, P = 0.35). However, we observed significant treatment × time interactions on pain interference (ß = 3.32, 95% confidence interval [CI]: 0.01 to 6.65, P = 0.05) and pain catastrophizing (ß = 2.74, 95% CI: 0.49 to 4.99, P = 0.02). Lastly, we detected no significant differences in opioid misuse (adjusted odds ratio = 0.69, 95% CI: -0.26 to 1.64, P = 0.16). CONCLUSION: This study provides support for the IPGT intervention being acceptable and feasible for delivery in patients with chronic pain at risk of opioid misuse. Efficacy was achieved in pain interference and pain catastrophizing.

Reduced tactile acuity in chronic low back pain is linked with structural neuroplasticity in primary somatosensory cortex and is modulated by acupuncture therapy.

Prior studies have shown that patients suffering from chronic Low Back Pain (cLBP) have impaired somatosensory processing including reduced tactile acuity, i.e. reduced ability to resolve fine spatial details with the perception of touch. The central mechanism(s) underlying reduced tactile acuity are unknown but may include changes in specific brain circuitries (e.g. neuroplasticity in the primary somatosensory cortex, S1). Furthermore, little is known about the linkage between changes in tactile acuity and the amelioration of cLBP by somatically-directed therapeutic interventions, such as acupuncture. In this longitudinal neuroimaging study, we evaluated healthy control adults (HC, N â€‹= â€‹50) and a large sample of cLBP patients (N â€‹= â€‹102) with structural brain imaging (T1-weighted MRI for Voxel-Based Morphometry, VBM; Diffusion Tensor Imaging, DTI) and tactile acuity testing using two-point discrimination threshold (2PDT) over the lower back (site of pain) and finger (control) locations. Patients were evaluated at baseline and following a 4-week course of acupuncture, with patients randomized to either verum acupuncture, two different forms of sham acupuncture (designed with or without somatosensory afference), or no-intervention usual care control. At baseline, cLBP patients demonstrated reduced acuity (greater 2PDT, P â€‹= â€‹0.01) over the low back, but not finger (P â€‹= â€‹0.29) locations compared to HC, suggesting that chronic pain affects tactile acuity specifically at body regions encoding the experience of clinical pain. At baseline, Gray Matter Volume (GMV) was elevated and Fractional Anisotropy (FA) was reduced, respectively, in the S1-back region of cLBP patients compared to controls (P â€‹< â€‹0.05). GMV in cLBP correlated with greater 2PDT-back scores (ρ â€‹= â€‹0.27, P â€‹= â€‹0.02). Following verum acupuncture, tactile acuity over the back was improved (reduced 2PDT) and greater improvements were associated with reduced S1-back GMV (ρ â€‹= â€‹0.52, P â€‹= â€‹0.03) and increased S1-back adjacent white matter FA (ρ â€‹= â€‹-0.56, P â€‹= â€‹0.01). These associations were not seen for non-verum control interventions. Thus, S1 neuroplasticity in cLBP is linked with deficits in tactile acuity and, following acupuncture therapy, may represent early mechanistic changes in somatosensory processing that track with improved tactile acuity.

Impaired mesocorticolimbic connectivity underlies increased pain sensitivity in chronic low back pain.

Chronic low back pain (cLBP) is a prevalent disorder. A growing body of evidence linking the pathology of the reward network to chronic pain suggests that pain sensitization may contribute to cLBP chronification via disruptions of mesocortical and mesolimbic circuits in the reward system. Resting-state (RS) functional magnetic resonance imaging (fMRI) data was acquired from 90 patients with cLBP and 74 matched pain-free controls (HCs) at baseline and after a manipulation for back pain intensification. The ventral tegmental area (VTA) was chosen as a seed region to perform RS functional connectivity (FC) analysis. Baseline rsFC of both the mesocortical (between the VTA and bilateral rostral anterior cingulate cortex (rACC)/and medial prefrontal cortex (mPFC)) and mesolimbic (between the VTA and bilateral hippocampus/parahippocampus) pathways was reduced in patients with cLBP (vs. HCs). In addition, patients exhibiting higher back pain intensity (compared to the relatively lower back pain intensity condition) also showed increases in both mesocortical and mesolimbic connectivity, implicating these pathways in pain downregulation in cLBP. Mediation analysis further isolated the mesolimbic (VTA-hippocampus/parahippocampus) dysconnectivity as a neural mechanism mediating the association between mechanical pain sensitivity (indexed by P40 pressure) and cLBP severity. In sum, the current study demonstrates deficient mesocorticolimbic connectivity in cLBP, with mesolimbic dysconnectivity potentially mediating the contribution of pain sensitization to pain chronification. These reward network dysfunctions and purportedly, dopaminergic dysregulations, may help us to identify key brain targets of neuromodulation in the treatment of cLBP.

Assessing and mapping language, attention and executive multidimensional deficits in stroke aphasia.

There is growing awareness that aphasia following a stroke can include deficits in other cognitive functions and that these are predictive of certain aspects of language function, recovery and rehabilitation. However, data on attentional and executive (dys)functions in individuals with stroke aphasia are still scarce and the relationship to underlying lesions is rarely explored. Accordingly in this investigation, an extensive selection of standardized non-verbal neuropsychological tests was administered to 38 individuals with chronic post-stroke aphasia, in addition to detailed language testing and MRI. To establish the core components underlying the variable patients' performance, behavioural data were explored with rotated principal component analyses, first separately for the non-verbal and language tests, then in a combined analysis including all tests. Three orthogonal components for the non-verbal tests were extracted, which were interpreted as shift-update, inhibit-generate and speed. Three components were also extracted for the language tests, representing phonology, semantics and speech quanta. Individual continuous scores on each component were then included in a voxel-based correlational methodology analysis, yielding significant clusters for all components. The shift-update component was associated with a posterior left temporo-occipital and bilateral medial parietal cluster, the inhibit-generate component was mainly associated with left frontal and bilateral medial frontal regions, and the speed component with several small right-sided fronto-parieto-occipital clusters. Two complementary multivariate brain-behaviour mapping methods were also used, which showed converging results. Together the results suggest that a range of brain regions are involved in attention and executive functioning, and that these non-language domains play a role in the abilities of patients with chronic aphasia. In conclusion, our findings confirm and extend our understanding of the multidimensionality of stroke aphasia, emphasize the importance of assessing non-verbal cognition in this patient group and provide directions for future research and clinical practice. We also briefly compare and discuss univariate and multivariate methods for brain-behaviour mapping.