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The reciprocal interaction between pain and negative affect is acknowledged but pain-related alterations in brain circuits involved in this interaction, such as the mediodorsal thalamus (MDThal), still require a better understanding. We sought to investigate the relationship between MDThal circuitry, negative affect and pain severity in chronic musculoskeletal pain. For these analyses, participants with chronic knee pain (CKP, n = 74) and without (n = 36) completed magnetic resonance imaging scans and questionnaires. Seed-based MDThal functional connectivity (FC) was compared between groups. Within CKP group, we assessed the interdependence of MDThal FC with negative affect. Finally, post hoc moderation analysis explored whether burden of pain influences affect-related MDThal FC. The CKP group showed altered MDThal FC to hippocampus, ventromedial prefrontal cortex and subgenual anterior cingulate. Furthermore, in CKP group, MDThal connectivity correlated significantly with negative affect in several brain regions, most notably the medial prefrontal cortex, and this association was stronger with increasing pain burden and absent in pain-free controls. In conclusion, we demonstrate mediodorsal thalamo-cortical dysconnectivity in chronic pain with areas linked to mood disorders and associations of MDThal FC with negative affect. Moreover, burden of pain seems to enhance affect sensitivity of MDThal FC. These findings suggest mediodorsal thalamic network changes as possible drivers of the detrimental interplay between chronic pain and negative affect.

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BACKGROUND: Depression is a substantial health and economic burden. In approximately one-third of patients, depression is resistant to first-line treatment; therefore, it is essential to find alternative treatments. Transcranial magnetic stimulation (TMS) is a neuromodulatory treatment involving the application of magnetic pulses to the brain that is approved in the United Kingdom and the United States in treatment-resistant depression. This trial aims to compare the clinical effectiveness, cost-effectiveness, and mechanism of action of standard treatment repetitive TMS (rTMS) targeted at the F3 electroencephalogram site with a newer treatment-a type of TMS called theta burst stimulation (TBS) targeted based on measures of functional brain connectivity. This protocol outlines brain imaging acquisition and analysis for the Brain Imaging Guided Transcranial Magnetic Stimulation in Depression (BRIGhTMIND) study trial that is used to create personalized TMS targets and answer the proposed mechanistic hypotheses. OBJECTIVE: The aims of the imaging arm of the BRIGhTMIND study are to identify functional and neurochemical brain signatures indexing the treatment mechanisms of rTMS and connectivity-guided intermittent theta burst TMS and to identify imaging-based markers predicting response to treatment. METHODS: The study is a randomized double-blind controlled trial with 1:1 allocation to either 20 sessions of TBS or standard rTMS. Multimodal magnetic resonance imaging (MRI) is acquired for each participant at baseline (before TMS treatment) with T1-weighted and task-free functional MRI during rest used to estimate TMS targets. For participants enrolled in the mechanistic substudy, additional diffusion-weighted sequences are acquired at baseline and at posttreatment follow-up 16 weeks after treatment randomization. Core data sets of T1-weighted and task-free functional MRI during rest are acquired for all participants and are used to estimate TMS targets. Additional sequences of arterial spin labeling, magnetic resonance spectroscopy, and diffusion-weighted images are acquired depending on the recruitment site for mechanistic evaluation. Standard rTMS treatment is targeted at the F3 electrode site over the left dorsolateral prefrontal cortex, whereas TBS treatment is guided using the coordinate of peak effective connectivity from the right anterior insula to the left dorsolateral prefrontal cortex. Both treatment targets benefit from the level of MRI guidance, but only TBS is provided with precision targeting based on functional brain connectivity. RESULTS: Recruitment began in January 2019 and is ongoing. Data collection is expected to continue until January 2023. CONCLUSIONS: This trial will determine the impact of precision MRI guidance on rTMS treatment and assess the neural mechanisms underlying this treatment in treatment-resistant depressed patients. TRIAL REGISTRATION: ISRCTN Registry ISRCTN19674644; https://www.isrctn.com/ISRCTN19674644. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/31925.

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Chronic musculoskeletal pain is a common problem globally. Current evidence suggests that maladapted central pain pathways are associated with pain chronicity, for example, in postoperative pain after knee replacement. Other factors such as low mood, anxiety, and tendency to catastrophize are also important contributors. We aimed to investigate brain imaging features that underpin pain chronicity based on multivariate pattern analysis of cerebral blood flow (CBF), as a marker of maladaptive brain changes. This was achieved by identifying CBF patterns that discriminate chronic pain from pain-free conditions and by exploring their explanatory power for factors thought to drive pain chronification. In 44 chronic knee pain and 29 pain-free participants, we acquired both CBF and T1-weighted data. Participants completed questionnaires related to affective processes and pressure and cuff algometry to assess pain sensitization. Two factor scores were extracted from these scores representing negative affect and pain sensitization. A spatial covariance principal component analysis of CBF identified 5 components that significantly discriminated chronic pain participants from controls, with the unified network achieving 0.83 discriminatory accuracy (area under the curve). In chronic knee pain, significant patterns of relative hypoperfusion were evident in anterior default-mode and salience network hubs, while hyperperfusion was seen in posterior default mode, thalamus, and sensory regions. One component correlated positively with the pain sensitization score (r = 0.43, P = 0.006), suggesting that this CBF pattern reflects neural activity changes encoding pain sensitization. Here, we report a distinct chronic knee pain-related representation of CBF, pointing toward a brain signature underpinning central aspects of pain sensitization.

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Our social activity is heavily influenced by the process of introspection, with emerging research suggesting a role for the Default Mode Network (DMN) in social cognition. We hypothesize that oxytocin, a neuropeptide with an important role in social behaviour, can effectively alter the connectivity of the DMN. We test this hypothesis using a randomized, double-blind, crossover, placebo-controlled trial where 15 healthy male participants received 24 IU oxytocin or placebo prior to a resting-state functional MRI scan. We used Granger Causality Analysis for the first time to probe the role of oxytocin on brain networks and found that oxytocin reverses the pattern of effective connectivity between the bilateral precuneus and the left dorsolateral prefrontal cortex (dlPFC), a key central executive network (CEN) region. Under placebo, the bilateral precuneus exerted a significant negative causal influence on the left dlPFC and the left dlPFC exerted a significant positive causal influence on the bilateral precuneus. However, under oxytocin, these patterns were reversed, i.e. positive causal influence from the bilateral precuneus to the left dlPFC and negative causal influence from the left dlPFC to the bilateral precuneus (with statistically significant effects for the right precuneus). We propose that these oxytocin-induced effects could be a mechanistic process by which it modulates social cognition. These results provide a measurable target for the physiological effects of oxytocin in the brain and offer oxytocin as a potential agent to enhance the cooperative role of the predominantly 'task-inactive' 'default mode' brain regions in both healthy and patient populations.

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Resting-state functional connectivity (FC) has proven a powerful approach to understand the neural underpinnings of chronic pain, reporting altered connectivity in 3 main networks: the default mode network (DMN), central executive network, and the salience network (SN). The interrelation and possible mechanisms of these changes are less well understood in chronic pain. Based on emerging evidence of its role to drive switches between network states, the right anterior insula (rAI, an SN hub) may play a dominant role in network connectivity changes underpinning chronic pain. To test this hypothesis, we used seed-based resting-state FC analysis including dynamic and effective connectivity metrics in 25 people with chronic osteoarthritis (OA) pain and 19 matched healthy volunteers. Compared with controls, participants with painful knee OA presented with increased anticorrelation between the rAI (SN) and DMN regions. Also, the left dorsal prefrontal cortex (central executive network hub) showed more negative FC with the right temporal gyrus. Granger causality analysis revealed increased negative influence of the rAI on the posterior cingulate (DMN) in patients with OA in line with the observed enhanced anticorrelation. Moreover, dynamic FC was lower in the DMN of patients and thus more similar to temporal dynamics of the SN. Together, these findings evidence a widespread network disruption in patients with persistent OA pain and point toward a driving role of the rAI.

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Information regarding anatomical connectivity in the human brain can be gathered using diffusion tensor imaging (DTI). Fractional anisotropy (FA) is the most commonly derived value, and reflects how strongly directional are the underlying tracts. Differences in FA are thus associated with differences in the underlying microstructure of the brain. The relationships between these differences in microstructure and functional differences in corresponding regions have also been examined. Previous studies have found an effect of handedness on functional lateralization in the brain and corresponding microstructural differences. Here, using tract-based spatial statistics to analyse DTI-derived FA values, we further investigated the structural white matter architecture in the brains of right- and left-handed males. We found significantly higher FA values for left-handed, relatively to right-handed, individuals, in all major lobes, and in the corpus callosum. In support of previous suggestions, we find that there is a difference in the microstructure of white matter in left- and right-handed males that could underpin reduced lateralization of function in left-handed individuals.

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Repetitive transcranial magnetic stimulation (rTMS) has been used worldwide to treat depression. However, the exact physiological effects are not well understood. Pathophysiology of depression involves crucial limbic structures (e.g. insula), and it is still not clear if these structures can be modulated through neurostimulation of surface regions (e.g. dorsolateral prefrontal cortex, DLPFC), and whether rTMS-induced excitatory/inhibitory transmission alterations relate to fronto-limbic connectivity changes. Therefore, we sought proof-of-concept for neuromodulation of insula via prefrontal intermittent theta-burst stimulation (iTBS), and how these effects relate to GABAergic and glutamatergic systems. In 27 healthy controls, we employed a single-blind crossover randomised-controlled trial comparing placebo and real iTBS using resting-state functional MRI and magnetic resonance spectroscopy. Granger causal analysis was seeded from right anterior insula (rAI) to locate individualized left DLPFC rTMS targets. Effective connectivity coefficients within rAI and DLPFC were calculated, and levels of GABA/Glx, GABA/Cr and Glx/Cr in DLPFC and anterior cingulate voxels were also measured. ITBS significantly dampened fronto-insular connectivity and reduced GABA/Glx in both voxels. GABA/Glx had a significant mediating effect on iTBS-induced changes in DLPFC-to-rAI connectivity. We demonstrate modulation of the rAI using targeted iTBS through alterations of excitatory/inhibitory interactions, which may underlie therapeutic effects of rTMS, offering promise for rTMS treatment optimization.

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An imbalance in neural activity within large-scale networks appears to be an important pathophysiological aspect of depression. Yet, there is little consensus regarding the abnormality within the default mode network (DMN) in major depressive disorder (MDD). In the present study, 16 first-episode, medication-naïve patients with MDD and 16 matched healthy controls underwent functional magnetic resonance imaging (fMRI) at rest. With the precuneus (a central node of the DMN) as a seed region, functional connectivity (FC) was measured across the entire brain. The association between the FC of the precuneus and overall symptom severity was assessed using the Hamilton Depression Rating Scale. Patients with MDD exhibited a more negative relationship between the precuneus and the non-DMN regions, including the sensory processing regions (fusiform gyrus, postcentral gyrus) and the secondary motor cortex (supplementary motor area and precentral gyrus). Moreover, greater severity of depression was associated with greater anti-correlation between the precuneus and the temporo-parietal junction as well as stronger positive connectivity between the precuneus and the dorsomedial prefrontal cortex. These results indicate that dissociated large-scale networks of the precuneus may contribute to the clinical expression of depression in MDD.

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Resting-state fMRI studies investigating the pathophysiology of depression have identified prominent abnormalities in large-scale brain networks. However, it is unclear if localized dysfunction of specialized brain regions contribute to network-level abnormalities. We employed a meta-analytical procedure and reviewed studies conducted in China investigating changes in regional homogeneity (ReHo), a measure of localized intraregional connectivity, from resting-state fMRI in depression. Exploiting the statistical power gained from pooled analysis, we also investigated the effects of age, gender, illness duration and treatment on ReHo. The medial prefrontal cortex (MPFC) showed the most robust and reliable increase in ReHo in depression, with greater abnormality in medication-free patients with multiple episodes. Brain networks that relate to this region have been identified previously to show aberrant connectivity in depression, and we propose that the localized neuronal inefficiency of MPFC exists alongside wider network level disruptions involving this region.

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Previously, differences have been shown in effective connectivity of the salience network between healthy controls and patients with schizophrenia. Specifically, the right anterior insula (rAI) fails to modulate the dorsolateral prefrontal cortex (DLPFC). In 35 controls and 31 patients with schizophrenia, we extended these findings by investigating the white matter connectivity of this pathway using tractography, and its relationship with the disrupted effective connectivity. We showed increased fractional anisotropy in the pathway connecting the rAI with the DLPFC, which related to reduced effective connectivity. This may be due to either secondary changes in white matter or a primary defect in structural integrity resulting from deficient axonal pruning. This novel finding warrants further investigation of white matter connectivity in schizophrenia and the mechanisms underlying this pathophysiology.

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Recent work has identified disruption of several brain networks involving limbic and cortical regions that contribute to the generation of diverse symptoms of major depressive disorder (MDD). Of particular interest are the networks anchored on the right anterior insula, which binds the cortical and limbic regions to enable key functions that integrate bottom-up and top-down information in emotional and cognitive processing. Emotional appraisal has been linked to a presumed hierarchy of processing, from sensory percepts to affective states. But it is unclear whether the network level dysfunction seen in depression relates to a breakdown of this presumed hierarchical processing system from sensory to higher cognitive regions, mediated by core limbic regions (e.g. insula). In 16 patients with current MDD, and 16 healthy controls, we investigated differences in directional influences between anterior insula and the rest of the brain using resting-state functional magnetic resonance imaging (fMRI) and Granger-causal analysis (GCA), using anterior insula as a seed region. Results showed a failure of reciprocal influence between insula and higher frontal regions (dorsomedial prefrontal cortex) in addition to a weakening of influences from sensory regions (pulvinar and visual cortex) to the insula. This suggests dysfunction of both sensory and putative self-processing regulatory loops centered around the insula in MDD. For the first time, we demonstrate a network-level processing defect extending from sensory to frontal regions through insula in depression. Within limitations of inferences drawn from GCA of resting fMRI, we offer a novel framework to advance targeted network modulation approaches to treat depression.

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Machine-learning approaches are becoming commonplace in the neuroimaging literature as potential diagnostic and prognostic tools for the study of clinical populations. However, very few studies provide clinically informative measures to aid in decision-making and resource allocation. Head-to-head comparison of neuroimaging-based multivariate classifiers is an essential first step to promote translation of these tools to clinical practice. We systematically evaluated the classifier performance using back-to-back structural MRI in two field strengths (3- and 7-T) to discriminate patients with schizophrenia (n = 19) from healthy controls (n = 20). Gray matter (GM) and white matter images were used as inputs into a support vector machine to classify patients and control subjects. Seven Tesla classifiers outperformed the 3-T classifiers with accuracy reaching as high as 77% for the 7-T GM classifier compared to 66.6% for the 3-T GM classifier. Furthermore, diagnostic odds ratio (a measure that is not affected by variations in sample characteristics) and number needed to predict (a measure based on Bayesian certainty of a test result) indicated superior performance of the 7-T classifiers, whereby for each correct diagnosis made, the number of patients that need to be examined using the 7-T GM classifier was one less than the number that need to be examined if a different classifier was used. Using a hypothetical example, we highlight how these findings could have significant implications for clinical decision-making. We encourage the reporting of measures proposed here in future studies utilizing machine-learning approaches. This will not only promote the search for an optimum diagnostic tool but also aid in the translation of neuroimaging to clinical use.

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The form of the structural asymmetries across the cerebral hemispheres, that support well-established functional asymmetries, are not well understood. Although, many previous studies have investigated structural differences in areas associated with strong functional asymmetries, such as language processes, regions of the brain with less well established functional laterality have received less attention. The current study aims to address this by exploring global white matter asymmetries of the healthy human brain using diffusion tensor imaging (DTI) and tractography. DTI was conducted on twenty-nine healthy right-handed males, and pathways from the four major lobes were reconstructed using probabilistic tractography. Mean FA, parallel and perpendicular diffusion values were calculated and compared across hemispheres for each pathway generated. Significant asymmetries in the parietal (rightward asymmetry) and occipital (leftward asymmetry) pathways were found in FA measures. However, asymmetric patterns in parallel and/or perpendicular diffusion were observed in all four lobes, even in pathways with symmetrical FA. For instance, significant rightward asymmetry in parallel diffusion was found in the parietal and frontal lobes, whereas significant leftward asymmetry was found in the temporal and occipital lobes. We suggest that these different patterns of diffusion asymmetry reflect differences in microanatomy that support the known patterns of differential functional asymmetry. The different directions of anatomical asymmetry support the notion that there may be a number of different lateralising influences operating in the brain.

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OBJECTIVE: To examine whether or not university mathematics students semantically process gestures depicting mathematical functions (mathematical gestures) similarly to the way they process action gestures and sentences. Semantic processing was indexed by the N400 effect. RESULTS: The N400 effect elicited by words primed with mathematical gestures (e.g. "converging" and "decreasing") was the same in amplitude, latency and topography as that elicited by words primed with action gestures (e.g. drive and lift), and that for terminal words of sentences. SIGNIFICANCE AND CONCLUSION: Findings provide a within-subject demonstration that the topographies of the gesture N400 effect for both action and mathematical words are indistinguishable from that of the standard language N400 effect. This suggests that mathematical function words are processed by the general language semantic system and do not appear to involve areas involved in other mathematical concepts (e.g. numerosity).

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The relative latencies of evoked electroencephalogram potentials to lateralized visual stimuli were used to calculate the interhemispheric transfer time (IHTT) in right-handed and left-handed males. We confirmed earlier observations of a directional asymmetry in right-handed males. That is, IHTT from the right to the left hemisphere is significantly shorter than from the left to the right. We showed for the first time, however, that this directional asymmetry is not seen in left-handed males. It is suggested that differences in the cytoarchitechtonics of the right and left hemisphere (differences that may result in lateralization of function per se) underlie the asymmetric IHTT in right handers, and that these differences are less pronounced in left handers.

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