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Novel NIBS in psychiatry: Unveiling TUS and TI for research and treatment.
Mental disorders pose a significant global burden and constitute a major cause of disability worldwide. Despite strides in treatment, a substantial number of patients do not respond adequately, underscoring the urgency for innovative approaches. Traditional non-invasive brain stimulation techniques show promise, yet grapple with challenges regarding efficacy and specificity. Variations in mechanistic understanding and reliability among non-invasive brain stimulation methods are common, with limited spatial precision and physical constraints hindering the ability to target subcortical areas often implicated in the disease aetiology. Novel techniques such as transcranial ultrasonic stimulation and temporal interference stimulation have gained notable momentum in recent years, possibly addressing these shortcomings. Transcranial ultrasonic stimulation (TUS) offers exceptional spatial precision and deeper penetration compared with conventional electrical and magnetic stimulation techniques. Studies targeting a diverse array of brain regions have shown its potential to affect neuronal excitability, functional connectivity and symptoms of psychiatric disorders such as major depressive disorder. Nevertheless, challenges such as target planning and addressing acoustic interactions with the skull must be tackled for its widespread adoption in research and potentially clinical settings. Similar to transcranial ultrasonic stimulation, temporal interference (TI) stimulation offers the potential to target deeper subcortical areas compared with traditional non-invasive brain stimulation, albeit requiring a comparatively higher current for equivalent neural effects. Promising yet still sparse research highlights TI's potential to selectively modulate neuronal activity, showing potential for its utility in psychiatry. Overall, recent strides in non-invasive brain stimulation methods like transcranial ultrasonic stimulation and temporal interference stimulation not only open new research avenues but also hold potential as effective treatments in psychiatry. However, realising their full potential necessitates addressing practical challenges and optimising their application effectively.
The cognitive neuroscience of ketamine in major depression.
Ketamine's potential as a rapid-acting antidepressant was first identified in 2000, despite its long-standing use as an anesthetic agent. Clinically, ketamine alleviates depressive symptoms, including the difficult to treat symptom of anhedonia, within hours, with the effects of a single dose lasting for days. Since then, research has focused on uncovering the mechanisms underlying its rapid antidepressant effects in both humans and animal models. While its molecular and cellular effects have been extensively characterized, its impact on cognitive and neuropsychological mechanisms - potential mediators of its clinical efficacy - remains an area of ongoing investigation. Preclinical studies suggest that ketamine rapidly influences the lateral habenula (involved in punishment processing) and fronto-striatal (reward) systems, reverses negative affective biases in established memories, and promotes long-term stress resilience. Translating these findings to human models is crucial, and emerging evidence suggests that ketamine engages similar mechanisms in healthy volunteer and patient groups. However, its clinical application is constrained by acute side effects and an unknown long-term safety profile. Further research into ketamine's mechanisms of action will be essential to inform the development of novel, safer, and more accessible rapid-acting antidepressants.
Linking microscopy to diffusion MRI with degenerate biophysical models: an application of the Bayesian EstimatioN of CHange (BENCH) framework
Abstract Biophysical modelling of diffusion MRI (dMRI) is used to non-invasively estimate microstructural features of tissue, particularly in the brain. However, meaningful description of tissue requires many unknown parameters, resulting in a model that is often ill-posed. The Bayesian EstimatioN of CHange (BENCH) framework was specifically designed to circumvent parameter fitting for ill-conditioned models when one is simply interested in interpreting signal changes related to some variable of interest. To understand the biological underpinning of some observed change in MR signal between different conditions, BENCH predicts which model parameter, or combination of parameters, best explains the observed change, without having to invert the model. BENCH has been previously used to identify which biophysical parameters could explain group-wise dMRI signal differences (e.g. patients vs. controls); here, we adapt BENCH to interpret dMRI signal changes related to continuous variables. We investigate how parameters from the dMRI standard model of white matter, with an additional sphere compartment to represent glial cell bodies, relate to tissue microstructure quantified from histology. We validate BENCH using synthetic dMRI data from numerical simulations. We then apply it to ex-vivo macaque brain data with dMRI and microscopy metrics of glial density, axonal density, and axonal dispersion in the same brain. We found that (i) increases in myelin density are primarily associated with an increased intra-axonal volume fraction and (ii) changes in the orientation dispersion derived from myelin microscopy are linked to variations in the orientation dispersion index. Finally, we found that the dMRI signal is sensitive to changes in glial cell load in the brain white matter, though no single parameter in the extended standard model was able to explain this observed signal change.
Brain and muscle chemistry in myalgic encephalitis/chronic fatigue syndrome (ME/CFS) and long COVID: a 7T magnetic resonance spectroscopy study.
Myalgic encephalitis/chronic fatigue syndrome (ME/CFS) is a common debilitating medical condition, whose main symptoms - fatigue, post-exertional malaise and cognitive dysfunction - are also present in many cases of long COVID. Magnetic resonance spectroscopy (MRS) allows the insight into their pathophysiology through exploration of a range of biochemicals putatively relevant to aetiological processes, in particular mitochondrial dysfunction and energy metabolism. 24 patients with ME/CFS, 25 patients with long COVID and 24 healthy controls (HC) underwent brain (pregenual and dorsal anterior cingulate cortex, respectively, pgACC and dACC) and calf muscle MRS scanning at 7 Tesla, followed by a computerised cognitive assessment. Compared to HC, ME/CFS patients had elevated levels of lactate in both pgACC and dACC, while long COVID patients had lowered levels of total choline in dACC. By contrast, skeletal muscle metabolites at rest did not significantly differ between the groups. The changes in lactate in ME/CFS are consistent with the presence of energetic stress and mitochondrial dysfunction. A reduction in total choline in long COVID is of interest in the context of the recently reported association between blood clots and 'brain fog', and earlier animal studies showing that choline might prevent intravascular coagulation. Importantly, differences in findings between ME/CFS and long COVID suggest that the underlying neurobiological mechanisms, while leading to similar clinical presentations, may differ. An important implication is that patients with ME/CFS and those with fatigue in the course of long COVID should not be studied as a single group, at least until the mechanisms are better understood.
Multi-site feasibility and reproducibility study on UTE 3D phosphorous MRSI using novel rosette trajectory (PETALUTE).
PURPOSE: This study aims (1) to implement a robust acquisition, fully automated reconstruction, and processing pipeline using a novel rosette k-space pattern for UTE 31P 3D MRSI and (2) to evaluate the clinical applicability and reproducibility at different experimental setups. METHODS: A multi-center feasibility/reproducibility study was conducted for the novel UTE 31P 3D MRSI sequence with rosette petal trajectory (PETALUTE) at three institutions with different experimental setups (Siemens Prisma with volume head coil or surface coil, Siemens Biograph mMR with volume head coil). Five healthy subjects at each site were measured with an acquisition delay of 65 μs and a final resolution of 10 × 10 × 10 mm3 in 9 min. The measurement was repeated three times and averaged for the spectral analysis using the LCModel package. The potential for acceleration was assessed using compressed sensing on retrospectively undersampled data. Reproducibility at each site was evaluated using the inter-subject coefficient of variance. RESULTS: This novel acquisition and advanced processing techniques yielded high-quality spectra and enabled the detection of the critical brain metabolites at three different sites with different hardware specifications. In vivo, feasibility with an acceleration factor of 4 in 6.75 min resulted in a mean Cramér-Rao lower bounds below 20% for phosphocreatine (PCr), adenosine triphosphate (ATP), phosphomonoesters (PME), and a mean coefficient of variation for ATP/PCr below 20%. CONCLUSION: We demonstrated that UTE 31P 3D rosette MRSI acquisition, combined with compressed sensing and LCModel analysis, allows clinically feasible, robust, high-resolution 31P MRSI to be acquired at clinical setups.
The Effects of Theta-Gamma Peak Stimulation on Sensorimotor Learning during Speech Production
Abstract Transcranial alternating current stimulation (tACS) is a non-invasive neuromodulatory tool that is thought to entrain intrinsic neural oscillations by supplying low electric currents over the scalp. Recent work has demonstrated the efficacy of theta-gamma phase-amplitude coupled tACS over primary motor cortex to enhance motor skill acquisition and motor recovery after stroke. Here, we wished to assess the efficacy of tACS delivered with 75-Hz gamma coupled to the peak of a 6-Hz theta envelope (theta-gamma peak; TGP) at an intensity of 2 mA peak-to-peak to enhance sensorimotor learning during speech production. Sensorimotor learning was measured by shifting the formant frequency of vowels in real-time as speech is produced and measuring the adaptation to this altered feedback. The study was a between-subjects, single-blind, sham-controlled design. We hypothesised that participants who performed the speech task while receiving TGP tACS over the speech motor cortex (N = 30) would show greater adaptation to altered auditory feedback than those receiving sham stimulation (N = 31). Contrary to this hypothesis, there was no effect of TGP tACS on adaption to the upwards F1 shift in auditory feedback in either the final 30 trials of the learning phase or in the first 15 trials of the after-effect phase. However, a trend emerged in the TGP tACS group for greater retention of the adapted state and slower return to baseline F1 values in the after-effect phase. This finding was not predicted, and highlights the need for further investigation to deepen our understanding of the effects of TGP tACS on speech motor learning.
Self-supervised segmentation and characterization of fiber bundles in anatomic tracing data
Anatomic tracing is the gold standard tool for delineating brain connections and for validating more recently developed imaging approaches such as diffusion MRI tractography. A key step in the analysis of data from tracer experiments is the careful, manual charting of fiber trajectories on histological sections. This is a very time-consuming process, which limits the amount of annotated tracer data that are available for validation studies. Thus, there is a need to accelerate this process by developing a method for computer-assisted segmentation. Such a method must be robust to the common artifacts in tracer data, including variations in the intensity of stained axons and background, as well as spatial distortions introduced by sectioning and mounting the tissue. The method should also achieve satisfactory performance using limited manually charted data for training. Here, we propose the first deep-learning method, with a self-supervised loss function, for segmentation of fiber bundles on histological sections from macaque brains that have received tracer injections. We address the limited availability of manual labels with a semi-supervised training technique that takes advantage of unlabeled data to improve performance. We also introduce anatomic and across-section continuity constraints to improve accuracy. We show that our method can be trained on manually charted sections from a single case and segment unseen sections from different cases, with a true positive rate of (Formula presented.) 0.80. We further demonstrate the utility of our method by quantifying the density of fiber bundles as they travel through different white-matter pathways. We show that fiber bundles originating in the same injection site have different levels of density when they travel through different pathways, a finding that can have implications for microstructure-informed tractography methods. The code for our method is available at https://github.com/v-sundaresan/fiberbundle_seg_tracing.
Cryoneurolysis: A Novel Treatment for Management of Spasticity. Presentation of a Case Series
Background: Spasticity is a motor phenomenon occurring in disorders of the central nervous system that impacts on active and passive function, and quality of life. Pharmacological, physical and surgical management options are available, each of which have limitations. Cryoneurolysis is a technique developed for the treatment of pain which involves the controlled freezing and thawing of peripheral nerves. Recent case reports and series have suggested it may offer a novel treatment approach for pain associated with spasticity. Objectives: To report on the evaluation of cryoneurolysis in the first cohort of patients treated in a UK spasticity clinic. Methods: Eight patients with a variety of neurological conditions (aged 25-75 years) underwent cryoneurolysis. Each had been receiving regular botulinum toxin injections and had ongoing treatment goals. All patients first underwent diagnostic nerve blocks with local anaesthetic to determine their appropriateness for the treatment. Cryoneurolysis was then performed with ultrasound and nerve stimulator guidance. Assessments included goal attainment, Modified Ashworth Scale (MAS), ArmA, LegA and the patient reported impact of spasticity scale (PRISM), alongside patient satisfaction and side effect questionnaires. Assessments were at baseline and at regular intervals over 9 to 12 months. Results: All patients attained at least one of their goals, with sustained effect for more than 6 months. MAS demonstrated mixed or modest improvements. Functional outcome measures (ArmA/LegA) showed several meaningful improvements, particularly in passive function. There was an indication of an improvement in PRISM across domains, which plateaued at 6 months. Post-procedure pain was the most common side effect but subsided in all affected patients by 3 months. Patient satisfaction was positive. Conclusions: Our findings contribute to a growing base of case reports and series suggesting that cryoneurolysis could be a potentially useful treatment modality for spasticity. Future controlled studies should aim to evaluate cost-effectiveness and compare with existing treatments.
Clinical and cost-effectiveness of lithium versus quetiapine augmentation for treatment-resistant depression in adults: LQD a pragmatic randomised controlled trial.
BACKGROUND: Lithium and several atypical antipsychotics are the recommended first-line augmentation options for treatment-resistant depression; however, few studies have compared them directly, and none for longer than 8 weeks. Consequently, there is little evidence-based guidance for clinicians when choosing an augmentation option for patients with treatment-resistant depression. OBJECTIVES: This trial examined whether it is more clinically and cost-effective to prescribe lithium or quetiapine augmentation therapy for patients with treatment-resistant depression over 12 months. DESIGN: This was a parallel group, multicentre, pragmatic, open-label superiority trial comparing the clinical and cost-effectiveness of lithium versus quetiapine augmentation of antidepressant medication in treatment-resistant depression. Participants were randomised 1 : 1 at baseline to the decision to prescribe either lithium or quetiapine. SETTING: Six National Health Service trusts in England. PARTICIPANTS: Eligible participants were aged ≥ 18 years, met Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria for major depressive disorder, scored ≥ 14 on the 17-item Hamilton Depression Rating Scale and whose depression had had an inadequate response to at least two therapeutic antidepressant treatment trials in the current episode, with a current antidepressant treatment at or above the therapeutic dose for ≥ 6 weeks. Patients with a history of psychosis or bipolar disorder were excluded. Patients were judged suitable for either treatment. INTERVENTIONS: After randomisation, pre-prescribing safety checks were undertaken as per standard care and trial clinicians decided whether to proceed with prescribing the allocated medication. Trial clinicians received recommendations for titration and dosing in line with current clinical guidelines; however, dosing regimens could be altered according to tolerability and response. Participants were followed up using weekly self-report questionnaires and 8-, 26- and 52-week research visits. MAIN OUTCOME MEASURES: The co-primary outcome measures were depressive symptom severity over 52 weeks, measured weekly using the self-rated Quick Inventory of Depressive Symptomatology, and time to all-cause treatment discontinuation of the trial medication. Economic analyses compared costs between the two treatment arms over 52 weeks, from a National Health Service and Personal Social Services perspective, and a societal perspective. RESULTS: Two hundred and twelve participants were randomised, 107 to quetiapine and 105 to lithium. The quetiapine arm showed a significantly greater reduction in depressive symptoms than the lithium arm over 52 weeks (quetiapine vs. lithium area under the differences curve = -68.36, 95% confidence interval: -129.95 to -6.76, p = 0.0296). Median days to discontinuation did not significantly differ between the two arms (quetiapine = 365.0, interquartile range = 57.0-365.0, lithium = 212.0, interquartile range = 21.0-365.0), p = 0.1196. Quetiapine was more cost effective than lithium. Thirty-two serious adverse events were recorded, only one of which was deemed possibly related to the intervention (lithium). LIMITATIONS: The trial was unblinded, therefore expectancies regarding the trial medications may have influenced the results. Further, there was substantial missing data for some of the secondary outcome measures. CONCLUSIONS: As well as being more cost-effective, quetiapine may be a more clinically effective augmentation option for treatment-resistant depression. FUTURE WORK: Examining predictors of treatment response, including clinical, sociodemographic and biological factors, will help establish whether there are additional factors to consider when choosing an augmentation treatment for treatment-resistant depression. TRIAL REGISTRATION: This trial is registered as ISRCTN16387615. FUNDING: This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 14/222/02) and is published in full in Health Technology Assessment; Vol. 29, No. 12. See the NIHR Funding and Awards website for further award information.
Negative bias in encoding and recall memory in depressed patients with inadequate response to antidepressant medication.
RATIONALE: Cognitive theories propose that negative biases in emotional processing contribute to the maintenance of depressive states. Previous studies reported that acute antidepressant treatment in depressed patients reversed negative emotional biases. However, studies addressing the differences in emotional processing between healthy volunteers and clinically depressed patients with inadequate response to standard antidepressant treatments are limited. OBJECTIVES: To investigate the differences in emotional processing domains between depressed patients with inadequate response to current antidepressant treatment and healthy controls. METHODS: Fifty-four medicated patients with major depression and 45 age- and sex-equated healthy volunteers were tested using the Oxford Emotional Testing Battery. RESULTS: There was no difference between the two groups in the accuracy of recognising emotional facial expressions. However, there was a significant difference in the pattern of response times in an emotional categorisation task (F1,97 = 6.44, p = 0.013, partial η2 = 0.017) where healthy controls had faster responses towards positive than negative self-referent words (95%CI: -0.291 - -0.054, p = 0.005). In contrast, patients had no significant differences in reaction time for categorizing positive and negative self-referent descriptors. There was also a significant group interaction in an emotional memory task (F1,91 = 7.90, p = 0.006, partial η2 = 0.080) where healthy volunteers recalled significantly more positively valenced words than depressed patients (95%CI: -2.104 - -0.168, p = 0.022). CONCLUSIONS: Depressed patients with inadequate responses toward antidepressants had negative biases in emotional categorisation and emotional memory. These psychological abnormalities may represent targets for treatment in patients with difficult-to-treat depression.
Using arterial spin labelling to investigate spontaneous and evoked ongoing musculoskeletal pain
Clinical pain is difficult to study using standard Blood Oxy-genation Level Dependent (BOLD) magnetic resonance imaging because it is often ongoing and, if evoked, it is associated with stimulus-correlated motion. Arterial spin labelling (ASL) offers an attractive alternative. This study used arm repositioning to evoke clinically-relevant musculoskeletal pain in patients with shoulder impingement syndrome. Fifty-five patients were scanned using a multi post-labelling delay pseudo-continuous ASL (pCASL) sequence, first with both arms along the body and then with the affected arm raised into a painful position. Twenty healthy volunteers were scanned as a control group. Arm repositioning resulted in increased perfusion in brain regions involved in sensory processing and movement integration, such as the contralateral primary motor and primary somatosensory cortex, mid- and posterior cingulate cortex, and, bilaterally, in the insular cortex/operculum, putamen, thalamus, midbrain and cerebellum. Perfusion in the thalamus, midbrain and cerebellum was larger in the patient group. Results of a post hoc analysis suggested that the observed perfusion changes were related to pain rather than arm repositioning. This study showed that ASL can be useful in research on clinical ongoing musculoskeletal pain but the technique is not sensitive enough to detect small differences in perfusion.
Evaluating functional brain organization in individuals and identifying contributions to network overlap.
Individual differences in the spatial organization of resting-state networks have received increased attention in recent years. Measures of individual-specific spatial organization of brain networks and overlapping network organization have been linked to important behavioral and clinical traits and are therefore potential biomarker targets for personalized psychiatry approaches. To better understand individual-specific spatial brain organization, this paper addressed three key goals. First, we determined whether it is possible to reliably estimate weighted (non-binarized) resting-state network maps using data from only a single individual, while also maintaining maximum spatial correspondence across individuals. Second, we determined the degree of spatial overlap between distinct networks, using test-retest and twin data. Third, we systematically tested multiple hypotheses (spatial mixing, temporal switching, and coupling) as candidate explanations for why networks overlap spatially. To estimate weighted network organization, we adopt the Probabilistic Functional Modes (PROFUMO) algorithm, which implements a Bayesian framework with hemodynamic and connectivity priors to supplement optimization for spatial sparsity/independence. Our findings showed that replicable individual-specific estimates of weighted resting-state networks can be derived using high-quality fMRI data within individual subjects. Network organization estimates using only data from each individual subject closely resembled group-informed network estimates (which was not explicitly modeled in our individual-specific analyses), suggesting that cross-subject correspondence was largely maintained. Furthermore, our results confirmed the presence of spatial overlap in network organization, which was replicable across sessions within individuals and in monozygotic twin pairs. Intriguingly, our findings provide evidence that overlap between 2-network pairs is indicative of coupling. These results suggest that regions of network overlap concurrently process information from both contributing networks, potentially pointing to the role of overlapping network organization in the integration of information across multiple brain systems.