Atypical Functional Connectivity in Tourette Syndrome Differs Between Children and Adults

Deep brain stimulation for Tourette's syndrome

OBJECTIVES

This is a protocol for a Cochrane Review (intervention). The objectives are as follows: To assess the efficacy and harm of deep brain stimulation for motor symptoms, with psychiatric and behavioural comorbidities, either individually or in combination, in adults and adolescents with Tourette's syndrome compared to placebo, sham intervention, or the best available behavioural and pharmacological treatment.

Functional brain networks associated with the urge for action: Implications for pathological urge

Tics in Tourette syndrome (TS) are often preceded by sensory urges that drive the motor and vocal symptoms. Many everyday physiological behaviors are associated with sensory phenomena experienced as an urge for action, which may provide insight into the neural correlates of this pathological urge to tic that remains elusive. This study aimed to identify a brain network common to distinct physiological behaviors in healthy individuals, and in turn, examine whether this network converges with a network we previously localized in TS, using novel 'coordinate network mapping' methods. Systematic searches were conducted to identify functional neuroimaging studies reporting correlates of the urge to micturate, swallow, blink, or cough. Using activation likelihood estimation meta-analysis, we identified an 'urge network' common to these physiological behaviors, involving the bilateral insula/claustrum/inferior frontal gyrus/supplementary motor area, mid-/anterior- cingulate cortex (ACC), right postcentral gyrus, and left thalamus/precentral gyrus. Similarity between the urge and TS networks was identified in the bilateral insula, ACC, and left thalamus/claustrum. The potential role of the insula/ACC as nodes in the network for bodily representations of the urge to tic are discussed.

Review of the Brain's Behaviour after Injury and Disease for Its Application in an Agent-Based Model (ABM)

The brain is the most complex organ in the human body and, as such, its study entails great challenges (methodological, theoretical, etc.). Nonetheless, there is a remarkable amount of studies about the consequences of pathological conditions on its development and functioning. This bibliographic review aims to cover mostly findings related to changes in the physical distribution of neurons and their connections-the connectome-both structural and functional, as well as their modelling approaches. It does not intend to offer an extensive description of all conditions affecting the brain; rather, it presents the most common ones. Thus, here, we highlight the need for accurate brain modelling that can subsequently be used to understand brain function and be applied to diagnose, track, and simulate treatments for the most prevalent pathologies affecting the brain.

Predictors of Impairment and Self-Concept in Children and Adolescents with Persistent Tic Disorder

This study examined predictors of, and associations between, self-concept, demographic variables, and clinical measures in fifty-eight children and adolescents with Persistent Tic Disorder (PTD; 44 males, Mage = 11.9 years, SD = 2.74). Participants completed measures that assessed self-concept, tic severity, tic-related impairment, and comorbid psychological symptoms. Results showed that generalized anxiety disorder, major depressive disorder, persistent depressive disorder, total tic severity, number and complexity of tics, and total and social tic-related impairment were associated with self-concept. Tic-related social impairment mediated the relationship between tic severity and self-concept. Exploratory analyses found that total tic severity, motor tic severity, and vocal tic severity, as well as the number, intensity, and interference of tics predicted social tic-related impairment. Results suggest that treatments to reduce the number and complexity of tics, with additional focus on navigating social interactions, may serve to decrease tic severity and impairment, and in turn, improve self-concept.

Exploring protocol development: Implementing systematic contextual memory to enhance real-time fMRI neurofeedback

Objective

The goal of this study was to explore the development and implementation of a protocol for real-time fMRI neurofeedback (rtfMRI-nf) and to assess the potential for enhancing the selective brain activation using stimuli from Virtual Reality (VR). In this study we focused on two specific brain regions, supplementary motor area (SMA) and right inferior frontal gyrus (rIFG). Publications by other study groups have suggested impaired function in these specific brain regions in patients with the diagnoses Attention Deficit Hyperactivity Disorder (ADHD) and Tourette's Syndrome (TS). This study explored the development of a protocol to investigate if attention and contextual memory may be used to systematically strengthen the procedure of rtfMRI-nf.

Methods

We used open-science software and platforms for rtfMRI-nf and for developing a simulated repetition of the rtfMRI-nf brain training in VR. We conducted seven exploratory tests in which we updated the protocol at each step. During rtfMRI-nf, MRI images are analyzed live while a person is undergoing an MRI scan, and the results are simultaneously shown to the person in the MRI-scanner. By focusing the analysis on specific regions of the brain, this procedure can be used to help the person strengthen conscious control of these regions. The VR simulation of the same experience involved a walk through the hospital toward the MRI scanner where the training sessions were conducted, as well as a subsequent simulated repetition of the MRI training. The VR simulation was a 2D projection of the experience.The seven exploratory tests involved 19 volunteers. Through this exploration, methods for aiming within the brain (e.g. masks/algorithms for coordinate-system control) and calculations for the analyses (e.g. calculations based on connectivity versus activity) were updated by the project team throughout the project. The final procedure involved three initial rounds of rtfMRI-nf for learning brain strategies. Then, the volunteers were provided with VR headsets and given instructions for one week of use. Afterward, a new session with three rounds of rtfMRI-nf was conducted.

Results

Through our exploration of the indirect effect parameters - brain region activity (directed oxygenated blood flow), connectivity (degree of correlated activity in different regions), and neurofeedback score - the volunteers tended to increase activity in the reinforced brain regions through our seven tests. Updates of procedures and analyses were always conducted between pilots, and never within. The VR simulated repetition was tested in pilot 7, but the role of the VR contribution in this setting is unclear due to underpowered testing.

Conclusion

This proof-of-concept protocol implies how rtfMRI-nf may be used to selectively train two brain regions (SMA and rIFG). The method may likely be adapted to train any given region in the brain, but readers are advised to update and adapt the procedure to experimental needs.

An Update on the Diagnosis and Management of Tic Disorders

Tic disorders (TDs) are a group of common neuropsychiatric disorders of childhood and adolescence. TDs may impact the physical, emotional, and social well-being of the affected person. In this review, we present an update on the clinical manifestations, pathophysiology, diagnosis, and treatment of TDs. We searched the PubMed database for articles on tics and Tourette syndrome. More than 400 articles were reviewed, of which 141 are included in this review. TDs are more prevalent in children than in adults and in males than in females. It may result from a complex interaction between various genetic, environmental, and immunological factors. Dysregulation in the cortico-striato-pallido-thalamo-cortical network is the most plausible pathophysiology resulting in tics. TD is a clinical diagnosis based on clinical features and findings on neurological examination, especially the identification of tic phenomenology. In addition to tics, TD patients may have sensory features, including premonitory urge; enhanced and persistent sensitivity to non-noxious external or internal stimuli; and behavioral manifestations, including attention deficit hyperactivity disorders, obsessive-compulsive disorders, and autism spectrum disorders. Clinical findings of hyperkinetic movements that usually mimic tics have been compared and contrasted with those of TD. Patients with TD may not require specific treatment if tics are not distressing. Psychoeducation and supportive therapy can help reduce tics when combined with medication. Dispelling myths and promoting acceptance are important to improve patient outcomes. Using European, Canadian, and American guidelines, the treatment of TD, including behavioral therapy, medical therapy, and emerging/experimental therapy, has been discussed.

Decision-making under risk and ambiguity in adults with Tourette syndrome

BACKGROUND

Tourette syndrome (TS) as well as its most common comorbidities are associated with a higher propensity for risky behaviour in everyday life. However, it is unclear whether this increased risk propensity in real-life contexts translates into a generally increased attitude towards risk. We aimed to assess decision-making under risk and ambiguity based on prospect theory by considering the effects of comorbidities and medication.

METHODS

Fifty-four individuals with TS and 32 healthy controls performed risk and ambiguity decision-making tasks under both gains and losses conditions. Behavioural and computational parameters were evaluated using (i) univariate analysis to determine parameters difference taking independently; (ii) supervised multivariate analysis to evaluate whether our parameters could jointly account for between-group differences (iii) unsupervised multivariate analysis to explore the potential presence of sub-groups.

RESULTS

Except for general 'noisier' (less consistent) decisions in TS, we showed no specific risk-taking behaviour in TS or any relation with tics severity or antipsychotic medication. However, the presence of comorbidities was associated with distortion of decision-making. Specifically, TS with obsessive-compulsive disorder comorbidity was associated with a higher risk-taking profile to increase gain and a higher risk-averse profile to decrease loss. TS with attention-deficit hyperactivity disorder comorbidity was associated with risk-seeking in the ambiguity context to reduce a potential loss.

CONCLUSIONS

Impaired valuation of risk and ambiguity was not related to TS per se. Our findings are important for clinical practice: the involvement of individuals with TS in real-life risky situations may actually rather result from other factors such as psychiatric comorbidities.

Treatment of Tourette syndrome by acupuncture combined with Chinese medicine based on syndrome differentiation: A review

Tourette syndrome (TS) is a chronic neurodevelopmental disorder characterized by involuntary motor and speech tics, which can greatly reduce the quality of life of patients. The pathophysiology of TS involves both genetic and environmental factors. Assessing TS pathogenesis is complex, and its underlying pathophysiology is not fully understood. It is gratifying that the research in the past 5 years has brought new research progress on the genetic, neurophysiological and brain network changes of TS. However, despite the progress of research, the treatment methods and drugs of modern medicine are still unsatisfactory, and it is difficult to achieve satisfactory results. Traditional Chinese medicine, as a part of complementary and alternative medicine, has unique efficacy in the treatment of TS, and the safety of its treatment is also worthy of attention. Based on the latest achievements in the pathophysiology of TS, this article will discuss the treatment of TS by acupuncture combined with medicine.

Mapping a network for tics in Tourette syndrome using causal lesions and structural alterations

Tics are sudden stereotyped movements or vocalizations. Cases of lesion-induced tics are invaluable, allowing for causal links between symptoms and brain structures. While a lesion network for tics has recently been identified, the degree to which this network translates to Tourette syndrome has not been fully elucidated. This is important given that patients with Tourette syndrome make up a large portion of tic cases; therefore, existing and future treatments should apply to these patients. The aim of this study was to first localize a causal network for tics from lesion-induced cases and then refine and validate this network in patients with Tourette syndrome. We independently performed 'lesion network mapping' using a large normative functional connectome (n = 1000) to isolate a brain network commonly connected to lesions causing tics (n = 19) identified through a systematic search. The specificity of this network to tics was assessed through comparison to lesions causing other movement disorders. Using structural brain coordinates from prior neuroimaging studies (n = 7), we then derived a neural network for Tourette syndrome. This was done using standard anatomical likelihood estimation meta-analysis and a novel method termed 'coordinate network mapping', which uses the same coordinates, yet maps their connectivity using the aforementioned functional connectome. Conjunction analysis was used to refine the network for lesion-induced tics to Tourette syndrome by identifying regions common to both lesion and structural networks. We then tested whether connectivity from this common network is abnormal in a separate resting-state functional connectivity MRI data set from idiopathic Tourette syndrome patients (n = 21) and healthy controls (n = 25). Results showed that lesions causing tics were distributed throughout the brain; however, consistent with a recent study, these were part of a common network with predominant basal ganglia connectivity. Using conjunction analysis, coordinate network mapping findings refined the lesion network to the posterior putamen, caudate nucleus, globus pallidus externus (positive connectivity) and precuneus (negative connectivity). Functional connectivity from this positive network to frontal and cingulate regions was abnormal in patients with idiopathic Tourette syndrome. These findings identify a network derived from lesion-induced and idiopathic data, providing insight into the pathophysiology of tics in Tourette syndrome. Connectivity to our cortical cluster in the precuneus offers an exciting opportunity for non-invasive brain stimulation protocols.

Multivariate classification provides a neural signature of Tourette disorder

BACKGROUND

Tourette disorder (TD), hallmarks of which are motor and vocal tics, has been related to functional abnormalities in large-scale brain networks. Using a fully data driven approach in a prospective, case-control study, we tested the hypothesis that functional connectivity of these networks carries a neural signature of TD. Our aim was to investigate (i) the brain networks that distinguish adult patients with TD from controls, and (ii) the effects of antipsychotic medication on these networks.

METHODS

Using a multivariate analysis based on support vector machine (SVM), we developed a predictive model of resting state functional connectivity in 48 patients and 51 controls, and identified brain networks that were most affected by disease and pharmacological treatments. We also performed standard univariate analyses to identify differences in specific connections across groups.

RESULTS

SVM was able to identify TD with 67% accuracy (p = 0.004), based on the connectivity in widespread networks involving the striatum, fronto-parietal cortical areas and the cerebellum. Medicated and unmedicated patients were discriminated with 69% accuracy (p = 0.019), based on the connectivity among striatum, insular and cerebellar networks. Univariate approaches revealed differences in functional connectivity within the striatum in patients v. controls, and between the caudate and insular cortex in medicated v. unmedicated TD.

CONCLUSIONS

SVM was able to identify a neuronal network that distinguishes patients with TD from control, as well as medicated and unmedicated patients with TD, holding a promise to identify imaging-based biomarkers of TD for clinical use and evaluation of the effects of treatment.

Maturation of large-scale brain systems over the first month of life

The period immediately after birth is a critical developmental window, capturing rapid maturation of brain structure and a child's earliest experiences. Large-scale brain systems are present at delivery, but how these brain systems mature during this narrow window (i.e. first weeks of life) marked by heightened neuroplasticity remains uncharted. Using multivariate pattern classification techniques and functional connectivity magnetic resonance imaging, we detected robust differences in brain systems related to age in newborns (n = 262; R2 = 0.51). Development over the first month of life occurred brain-wide, but differed and was more pronounced in brain systems previously characterized as developing early (i.e. sensorimotor networks) than in those characterized as developing late (i.e. association networks). The cingulo-opercular network was the only exception to this organizing principle, illuminating its early role in brain development. This study represents a step towards a normative brain "growth curve" that could be used to identify atypical brain maturation in infancy.

Masked features of task states found in individual brain networks

Completing complex tasks requires that we flexibly integrate information across brain areas. While studies have shown how functional networks are altered during different tasks, this work has generally focused on a cross-subject approach, emphasizing features that are common across people. Here we used extended sampling "precision" fMRI data to test the extent to which task states generalize across people or are individually specific. We trained classifiers to decode state using functional network data in single-person datasets across 5 diverse task states. Classifiers were then tested on either independent data from the same person or new individuals. Individualized classifiers were able to generalize to new participants. However, classification performance was significantly higher within a person, a pattern consistent across model types, people, tasks, feature subsets, and even for decoding very similar task conditions. Notably, these findings also replicated in a new independent dataset. These results suggest that individual-focused approaches can uncover robust features of brain states, including features obscured in cross-subject analyses. Individual-focused approaches have the potential to deepen our understanding of brain interactions during complex cognition.

Increased Alpha-Band Connectivity During Tic Suppression in Children With Tourette Syndrome Revealed by Source Electroencephalography Analyses

BACKGROUND

Tourette syndrome (TS) is a neurodevelopmental disorder involving chronic motor and phonic tics. Most individuals with TS can suppress their tics for at least a short period of time. Yet, the brain correlates of tic suppression are still poorly understood.

METHODS

In the current study, high-density electroencephalography was recorded during a resting-state and a tic suppression session in 72 children with TS. Functional connectivity between cortical regions was assessed in the alpha band (8-13 Hz) using an electroencephalography source connectivity method. Graph theory and network-based statistics were used to assess the global network topology and to identify brain regions showing increased connectivity during tic suppression.

RESULTS

Graph theoretical analyses revealed distinctive global network topology during tic suppression, relative to rest. Using network-based statistics, we found a subnetwork of increased connectivity during tic suppression (p < .001). That subnetwork encompassed many cortical areas, including the right superior frontal gyrus and the left precuneus, which are involved in the default mode network. We also found a condition-by-age interaction, suggesting age-mediated increases in connectivity during tic suppression.

CONCLUSIONS

These results suggest that children with TS suppress their tics through a brain circuit involving distributed cortical regions, many of which are part of the default mode network. Brain connectivity during tic suppression also increases as youths with TS mature. These results highlight a mechanism by which children with TS may control their tics, which could be relevant for future treatment studies.

Abnormal dynamics of brain functional networks in children with Tourette syndrome

Tourette syndrome (TS) is a childhood-onset neurodevelopmental disorder characterized by the presence of multiple motor and vocal tics. Research using resting-state functional magnetic resonance imaging (rfMRI) have found aberrant static functional connectivity (FC) and its topological properties in the brain networks of TS. Our study is the first to investigate the dynamic functional connectivity (dFC) in the whole brain network of TS patients, focusing on the temporal properties of dFC states and the temporal variability of topological organization. The rfMRI data of 36 male children with TS and 27 matched healthy controls were collected and further analyzed by group spatial independent component analysis, sliding windows approach based dFC analysis, k-means clustering analysis, and graph theory analysis. The clustering analysis identified three dFC states. Of these states, state 2, characterized by increased inter-network connections in subcortical network (SCN), sensorimotor network (SMN), and default mode network (DMN), and decreased inter-network connections between salience network (SAN) and executive control network (ECN), was found to have higher fractional window and dwell time in TS, which was also positively correlated with tic severity. TS patients also exhibited higher temporal variability of whole-brain-network global efficiency and local efficiency, and higher temporal variability of nodal efficiency and local efficiency in SCN, DMN, ECN, SAN, and SMN. Additionally, temporal variability of the efficiency and local efficiency in insula was positively correlated with tic severity. Our findings revealed abnormal temporal property of dFC states and temporal variability of topological organization in TS, providing new insights into clinical diagnoses and neuropathology of TS.

Tourette syndrome: clinical features, pathophysiology, and treatment

Tourette syndrome is a chronic neurodevelopmental disorder characterised by motor and phonic tics that can substantially diminish the quality of life of affected individuals. Evaluating and treating Tourette syndrome is complex, in part due to the heterogeneity of symptoms and comorbidities between individuals. The underlying pathophysiology of Tourette syndrome is not fully understood, but recent research in the past 5 years has brought new insights into the genetic variations and the alterations in neurophysiology and brain networks contributing to its pathogenesis. Treatment options for Tourette syndrome are expanding with novel pharmacological therapies and increased use of deep brain stimulation for patients with symptoms that are refractory to pharmacological or behavioural treatments. Potential predictors of patient responses to therapies for Tourette syndrome, such as specific networks modulated during deep brain stimulation, can guide clinical decisions. Multicentre data sharing initiatives have enabled several advances in our understanding of the genetics and pathophysiology of Tourette syndrome and will be crucial for future large-scale research and in refining effective treatments.

Trends of Tourette Syndrome in children from 2011 to 2021: A bibliometric analysis

Objective

Analyze the research status of Tourette Syndrome (TS) in children by CiteSpace and determine the current research hotspots and frontiers.

Materials and methods

We chose publications indexed in the Web of Science Core Collection (WoSCC) database for studies related to TS in children from 2011 to 2021. We built online cooperation maps of countries/regions, institutions, authors, journals, references, and keywords by CiteSpace, and identified hotspots and frontiers of study for children’s TS.

Results

A total of 1,232 publications about TS in children were downloaded from the WoSCC. The USA (414) was the country with the highest rate of production, and University College London (87) was the institution that had the highest publication rate. Andrea Eugenio Cavanna was the most prolific author (39 papers). There was inactive cooperation between institutions, countries/regions, and authors. The Journal of European Child &amp; Adolescent Psychiatry was the most active journal. Hot topics focused on epidemiology, comorbidities, deep brain stimulation, behavioral therapy, basal ganglia, pharmacological treatment, and risk factors of TS in children.

Conclusion

According to the CiteSpace results, this study found that authors, countries/regions, and institutions were not actively working together. Current research hotspots mainly consist of epidemiology, comorbidities, deep brain stimulation, behavior therapy, and basal ganglia. The main research trends include comorbidities, pharmacological treatment, and risk factors. Therefore, international cooperation should be strengthened in the future, and it should be mindful of the psychiatric comorbidities of TS, the choice of intervention measures, and early warning of risk factors.

Tourette syndrome research highlights from 2021

We summarize selected research reports from 2021 relevant to Tourette syndrome that the authors consider most important or interesting. The authors welcome article suggestions and thoughtful feedback from readers.

Recent progress on Tourette syndrome

Tic disorders and Tourette syndrome are the most common movement disorders in children and are characterized by movements or vocalizations. Clinically, Tourette syndrome is frequently associated with comorbid psychiatric symptoms. Although dysfunction of cortical–striatal–thalamic–cortical circuits with aberrant neurotransmitter function has been considered the proximate cause of tics, the mechanism underlying this association is unclear. Recently, many studies have been conducted to elucidate the epidemiology, clinical course, comorbid symptoms, and pathophysiology of tic disorders by using laboratory studies, neuroimaging, electrophysiological testing, environmental exposure, and genetic testing. In addition, many researchers have focused on treatment for tics, including behavioral therapy, pharmacological treatment, and surgical treatment. Here, we provide an overview of recent progress on Tourette syndrome.

What have we really learned from functional connectivity in clinical populations?

Functional connectivity (FC), or the statistical interdependence of blood-oxygen dependent level (BOLD) signals between brain regions using fMRI, has emerged as a widely used tool for probing functional abnormalities in clinical populations due to the promise of the approach across conceptual, technical, and practical levels. With an already vast and steadily accumulating neuroimaging literature on neurodevelopmental, psychiatric, and neurological diseases and disorders in which FC is a primary measure, we aim here to provide a high-level synthesis of major concepts that have arisen from FC findings in a manner that cuts across different clinical conditions and sheds light on overarching principles. We highlight that FC has allowed us to discover the ubiquity of intrinsic functional networks across virtually all brains and clarify typical patterns of neurodevelopment over the lifespan. This understanding of typical FC maturation with age has provided important benchmarks against which to evaluate divergent maturation in early life and degeneration in late life. This in turn has led to the important insight that many clinical conditions are associated with complex, distributed, network-level changes in the brain, as opposed to solely focal abnormalities. We further emphasize the important role that FC studies have played in supporting a dimensional approach to studying transdiagnostic clinical symptoms and in enhancing the multimodal characterization and prediction of the trajectory of symptom progression across conditions. We highlight the unprecedented opportunity offered by FC to probe functional abnormalities in clinical conditions where brain function could not be easily studied otherwise, such as in disorders of consciousness. Lastly, we suggest high priority areas for future research and acknowledge critical barriers associated with the use of FC methods, particularly those related to artifact removal, data denoising and feasibility in clinical contexts.

A Comprehensive Review of Tic Disorders in Children

Tics are characterized by sudden, rapid, recurrent, nonrhythmic movement or vocalization, and are the most common movement disorders in children. Their onset is usually in childhood and tics often will diminish within one year. However, some of the tics can persist and cause various problems such as social embarrassment, physical discomfort, or emotional impairments, which could interfere with daily activities and school performance. Furthermore, tic disorders are frequently associated with comorbid neuropsychiatric symptoms, which can become more problematic than tic symptoms. Unfortunately, misunderstanding and misconceptions of tic disorders still exist among the general population. Understanding tic disorders and their comorbidities is important to deliver appropriate care to patients with tics. Several studies have been conducted to elucidate the clinical course, epidemiology, and pathophysiology of tics, but they are still not well understood. This article aims to provide an overview about tics and tic disorders, and recent findings on tic disorders including history, definition, diagnosis, epidemiology, etiology, diagnostic approach, comorbidities, treatment and management, and differential diagnosis.

Course of tic disorders over the lifespan

PURPOSE OF REVIEW

To summarize and update information on the course of tic disorders from childhood through later life.

RECENT FINDINGS

Tics tend to improve substantially over the first year after they appear. However, contrary to widespread opinion, tics usually last longer than one year, though usually at minimal severity. Tics often wane to clinical insignificance over the teen years, possibly resurging occasionally over the lifespan. However, in an important minority of patients, tics remain clinically relevant throughout life. Tics rarely first come to clinical attention later in adulthood, but new reports describe additional such cases.

SUMMARY

Recent publications have shown tics to persist past a few months more often than previously thought, though often at minimal severity, and recurrence after an asymptomatic period is common. The safety and efficacy of behavior therapy for tics, together with prospective indicators of early prognosis, make feasible the possibility of bettering the lifetime course of tic disorders with early intervention.

Inhibitory control in children with tic disorder: aberrant fronto-parietal network activity and connectivity

Chronic tic disorders, including Tourette syndrome, are typically thought to have deficits in cognitive inhibition and top down cognitive control due to the frequent and repetitive occurrence of tics, yet studies reporting task performance results have been equivocal. Despite similar behavioural performance, individuals with chronic tic disorder have exhibited aberrant patterns of neural activation in multiple frontal and parietal regions relative to healthy controls during inhibitory control paradigms. In addition to these top down attentional control regions, widespread alterations in brain activity across multiple neural networks have been reported. There is a dearth, however, of studies examining event-related connectivity during cognitive inhibitory paradigms among affected individuals. The goal of this study was to characterize neural oscillatory activity and effective connectivity, using a case–control design, among children with and without chronic tic disorder during performance of a cognitive inhibition task. Electroencephalogram data were recorded in a cohort of children aged 8–12 years old (60 with chronic tic disorder, 35 typically developing controls) while they performed a flanker task. While task accuracy did not differ by diagnosis, children with chronic tic disorder displayed significant cortical source-level, event-related spectral power differences during incongruent flanker trials, which required inhibitory control. Specifically, attenuated broad band oscillatory power modulation within the anterior cingulate cortex was observed relative to controls. Whole brain effective connectivity analyses indicated that children with chronic tic disorder exhibit greater information flow between the anterior cingulate and other fronto-parietal network hubs (midcingulate cortex and precuneus) relative to controls, who instead showed stronger connectivity between central and posterior nodes. Spectral power within the anterior cingulate was not significantly correlated with any connectivity edges, suggesting lower power and higher connectivity are independent (versus resultant) neural mechanisms. Significant correlations between clinical features, task performance and anterior cingulate spectral power and connectivity suggest this region is associated with tic impairment (r = −0.31, P = 0.03) and flanker task incongruent trial accuracy (r’s = −0.27 to −0.42, P’s = 0.0008–0.04). Attenuated activation of the anterior cingulate along with dysregulated information flow between and among nodes within the fronto-parietal attention network may be neural adaptations that result from frequent engagement of neural pathways needed for inhibitory control in chronic tic disorder.

Correlates and clinical implications of tic suppressibility

Purpose of review

Tic disorders are common in the pediatric population and are differentiated from other movement disorders by tic suppressibility. Understanding the mechanism of tic suppression may provide new insights to the pathophysiology of tic disorders. This article highlights clinical phenomenology and neuronal correlates of tic suppressibility.

Recent findings

Recent studies suggest that tic suppressibility exists in children shortly after onset of their tics. Moreover, those who are better able to suppress their tics have better tic outcomes. Interoceptive awareness and automatic action inhibition may be involved in tic suppression.

Summary

We illustrate a possible underlying mechanism of tic suppressibility and its clinical correlations and implications. New concepts such as interoceptive awareness and action inhibition may help explain tic disorders. Further study will be useful to fill remaining knowledge gaps.

Impulsive prepotent actions and tics in Tourette disorder underpinned by a common neural network

Tourette disorder (TD), which is characterized by motor and vocal tics, is not in general considered as a product of impulsivity, despite a frequent association with attention deficit hyperactivity disorder and impulse control disorders. It is unclear which type of impulsivity, if any, is intrinsically related to TD and specifically to the severity of tics. The waiting type of motor impulsivity, defined as the difficulty to withhold a specific action, shares some common features with tics. In a large group of adult TD patients compared to healthy controls, we assessed waiting motor impulsivity using a behavioral task, as well as structural and functional underpinnings of waiting impulsivity and tics using multi-modal neuroimaging protocol. We found that unmedicated TD patients showed increased waiting impulsivity compared to controls, which was independent of comorbid conditions, but correlated with the severity of tics. Tic severity did not account directly for waiting impulsivity, but this effect was mediated by connectivity between the right orbito-frontal cortex with caudate nucleus bilaterally. Waiting impulsivity in unmedicated patients with TD also correlated with a higher gray matter signal in deep limbic structures, as well as connectivity with cortical and with cerebellar regions on a functional level. Neither behavioral performance nor structural or functional correlates were related to a psychometric measure of impulsivity or impulsive behaviors in general. Overall, the results suggest that waiting impulsivity in TD was related to tic severity, to functional connectivity of orbito-frontal cortex with caudate nucleus and to structural changes within limbic areas.

Tourette syndrome research highlights from 2019

This is the sixth yearly article in the Tourette Syndrome Research Highlights series, summarizing research from 2019 relevant to Tourette syndrome and other tic disorders. The highlights from 2020 is being drafted on the Authorea online authoring platform; readers are encouraged to add references or give feedback on our selections comments feature on this page. After the calendar year ends, this article is submitted as the annual update for the Tics collection F1000Research.

Basal Ganglia Pathways Associated With Therapeutic Pallidal Deep Brain Stimulation for Tourette Syndrome

BACKGROUND

Deep brain stimulation (DBS) targeting the globus pallidus internus (GPi) can improve tics and comorbid obsessive-compulsive behavior (OCB) in patients with treatment-refractory Tourette syndrome (TS). However, some patients' symptoms remain unresponsive, the stimulation applied across patients is variable, and the mechanisms underlying improvement are unclear. Identifying the fiber pathways surrounding the GPi that are associated with improvement could provide mechanistic insight and refine targeting strategies to improve outcomes.

METHODS

Retrospective data were collected for 35 patients who underwent bilateral GPi DBS for TS. Computational models of fiber tract activation were constructed using patient-specific lead locations and stimulation settings to evaluate the effects of DBS on basal ganglia pathways and the internal capsule. We first evaluated the relationship between activation of individual pathways and symptom improvement. Next, linear mixed-effects models with combinations of pathways and clinical variables were compared in order to identify the best-fit predictive models of tic and OCB improvement.

RESULTS

The best-fit model of tic improvement included baseline severity and the associative pallido-subthalamic pathway. The best-fit model of OCB improvement included baseline severity and the sensorimotor pallido-subthalamic pathway, with substantial evidence also supporting the involvement of the prefrontal, motor, and premotor internal capsule pathways. The best-fit models of tic and OCB improvement predicted outcomes across the cohort and in cross-validation.

CONCLUSIONS

Differences in fiber pathway activation likely contribute to variable outcomes of DBS for TS. Computational models of pathway activation could be used to develop novel approaches for preoperative targeting and selecting stimulation parameters to improve patient outcomes.

Artificial intelligence for brain diseases: A systematic review

Artificial intelligence (AI) is a major branch of computer science that is fruitfully used for analyzing complex medical data and extracting meaningful relationships in datasets, for several clinical aims. Specifically, in the brain care domain, several innovative approaches have achieved remarkable results and open new perspectives in terms of diagnosis, planning, and outcome prediction. In this work, we present an overview of different artificial intelligent techniques used in the brain care domain, along with a review of important clinical applications. A systematic and careful literature search in major databases such as Pubmed, Scopus, and Web of Science was carried out using "artificial intelligence" and "brain" as main keywords. Further references were integrated by cross-referencing from key articles. 155 studies out of 2696 were identified, which actually made use of AI algorithms for different purposes (diagnosis, surgical treatment, intra-operative assistance, and postoperative assessment). Artificial neural networks have risen to prominent positions among the most widely used analytical tools. Classic machine learning approaches such as support vector machine and random forest are still widely used. Task-specific algorithms are designed for solving specific problems. Brain images are one of the most used data types. AI has the possibility to improve clinicians' decision-making ability in neuroscience applications. However, major issues still need to be addressed for a better practical use of AI in the brain. To this aim, it is important to both gather comprehensive data and build explainable AI algorithms.

What Does Immunology Have to Do With Normal Brain Development and the Pathophysiology Underlying Tourette Syndrome and Related Neuropsychiatric Disorders?

Objective: The goal of this article is to review the past decade's literature and provide a critical commentary on the involvement of immunological mechanisms in normal brain development, as well as its role in the pathophysiology of Tourette syndrome, other Chronic tic disorders (CTD), and related neuropsychiatric disorders including Obsessive-compulsive disorder (OCD) and Attention deficit hyperactivity disorder (ADHD). Methods: We conducted a literature search using the Medline/PubMed and EMBASE electronic databases to locate relevant articles and abstracts published between 2009 and 2020, using a comprehensive list of search terms related to immune mechanisms and the diseases of interest, including both clinical and animal model studies. Results: The cellular and molecular processes that constitute our "immune system" are crucial to normal brain development and the formation and maintenance of neural circuits. It is also increasingly evident that innate and adaptive systemic immune pathways, as well as neuroinflammatory mechanisms, play an important role in the pathobiology of at least a subset of individuals with Tourette syndrome and related neuropsychiatric disorders In the conceptual framework of the holobiont theory, emerging evidence points also to the importance of the "microbiota-gut-brain axis" in the pathobiology of these neurodevelopmental disorders. Conclusions: Neural development is an enormously complex and dynamic process. Immunological pathways are implicated in several early neurodevelopmental processes including the formation and refinement of neural circuits. Hyper-reactivity of systemic immune pathways and neuroinflammation may contribute to the natural fluctuations of the core behavioral features of CTD, OCD, and ADHD. There is still limited knowledge of the efficacy of direct and indirect (i.e., through environmental modifications) immune-modulatory interventions in the treatment of these disorders. Future research also needs to focus on the key molecular pathways through which dysbiosis of different tissue microbiota influence neuroimmune interactions in these disorders, and how microbiota modification could modify their natural history. It is also possible that valid biomarkers will emerge that will guide a more personalized approach to the treatment of these disorders.

Plasticity and Spontaneous Activity Pulses in Disused Human Brain Circuits

To induce brain plasticity in humans, we casted the dominant upper extremity for 2 weeks and tracked changes in functional connectivity using daily 30-min scans of resting-state functional MRI (rs-fMRI). Casting caused cortical and cerebellar regions controlling the disused extremity to functionally disconnect from the rest of the somatomotor system, while internal connectivity within the disused sub-circuit was maintained. Functional disconnection was evident within 48 h, progressed throughout the cast period, and reversed after cast removal. During the cast period, large, spontaneous pulses of activity propagated through the disused somatomotor sub-circuit. The adult brain seems to rely on regular use to maintain its functional architecture. Disuse-driven spontaneous activity pulses may help preserve functionally disconnected sub-circuits.

Defining Individual-Specific Functional Neuroanatomy for Precision Psychiatry

Studies comparing diverse groups have shown that many psychiatric diseases involve disruptions across distributed large-scale networks of the brain. There is hope that functional magnetic resonance imaging (fMRI) functional connectivity techniques will shed light on these disruptions, providing prognostic and diagnostic biomarkers as well as targets for therapeutic interventions. However, to date, progress on clinical translation of fMRI methods has been limited. Here, we argue that this limited translation is driven by a combination of intersubject heterogeneity and the relatively low reliability of standard fMRI techniques at the individual level. We review a potential solution to these limitations: the use of new "precision" fMRI approaches that shift the focus of analysis from groups to single individuals through the use of extended data acquisition strategies. We begin by discussing the potential advantages of fMRI functional connectivity methods for improving our understanding of functional neuroanatomy and disruptions in psychiatric disorders. We then discuss the budding field of precision fMRI and findings garnered from this work. We demonstrate that precision fMRI can improve the reliability of functional connectivity measures, while showing high stability and sensitivity to individual differences. We close by discussing the application of these approaches to clinical settings.

The New Tics study: A Novel Approach to Pathophysiology and Cause of Tic Disorders

We report on the ongoing project "The New Tics Study: A Novel Approach to Pathophysiology and Cause of Tic Disorders," describing the work completed to date, ongoing studies and long-term goals. The overall goals of this research are to study the pathophysiology of Provisional Tic Disorder, and to study tic remission (or improvement) in a prospective fashion. Preliminary data collection for the project began almost 10 years ago. The current study is nearing completion of its third year, and has already reported several novel and important results. First, surprisingly, at least 90% of children who had experienced tics for only a mean of 3 months still had tics at the 12-month anniversary of their first tic, though in some cases tics were seen only with remote video observation of the child sitting alone. Thus almost all of them now had a DSM-5 diagnosis of Tourette's Disorder or Persistent (Chronic) Tic Disorder. Baseline clinical features that predicted 12-month outcome included tic severity, subsyndromal autism spectrum symptoms, an anxiety disorder, and a history of 3 or more phonic tics. Second, we found that poorer tic suppression ability when immediately rewarded for suppression predicted greater tic severity at follow-up. Third, striatal volumes did not predict outcome as hypothesized, but a larger hippocampus at baseline predicted worse severity at follow-up. Enrollment and data collection continue, including functional connectivity MRI (fcMRI) imaging, and additional analyses are planned once the full sample is enrolled.

A set of functionally-defined brain regions with improved representation of the subcortex and cerebellum

An important aspect of network-based analysis is robust node definition. This issue is critical for functional brain network analyses, as poor node choice can lead to spurious findings and misleading inferences about functional brain organization. Two sets of functional brain nodes from our group are well represented in the literature: (1) 264 volumetric regions of interest (ROIs) reported in Power et al., 2011, and (2) 333 cortical surface parcels reported in Gordon et al., 2016. However, subcortical and cerebellar structures are either incompletely captured or missing from these ROI sets. Therefore, properties of functional network organization involving the subcortex and cerebellum may be underappreciated thus far. Here, we apply a winner-take-all partitioning method to resting-state fMRI data to generate novel functionally-constrained ROIs in the thalamus, basal ganglia, amygdala, hippocampus, and cerebellum. We validate these ROIs in three datasets using several criteria, including agreement with existing literature and anatomical atlases. Further, we demonstrate that combining these ROIs with established cortical ROIs recapitulates and extends previously described functional network organization. This new set of ROIs is made publicly available for general use, including a full list of MNI coordinates and functional network labels.

Machine Learning With Neuroimaging: Evaluating Its Applications in Psychiatry

Psychiatric disorders are complex, involving heterogeneous symptomatology and neurobiology that rarely involves the disruption of single, isolated brain structures. In an attempt to better describe and understand the complexities of psychiatric disorders, investigators have increasingly applied multivariate pattern classification approaches to neuroimaging data and in particular supervised machine learning methods. However, supervised machine learning approaches also come with unique challenges and trade-offs, requiring additional study design and interpretation considerations. The goal of this review is to provide a set of best practices for evaluating machine learning applications to psychiatric disorders. We discuss how to evaluate two common efforts: 1) making predictions that have the potential to aid in diagnosis, prognosis, and treatment and 2) interrogating the complex neurophysiological mechanisms underlying psychopathology. We focus here on machine learning as applied to functional connectivity with magnetic resonance imaging, as an example to ground discussion. We argue that for machine learning classification to have translational utility for individual-level predictions, investigators must ensure that the classification is clinically informative, independent of confounding variables, and appropriately assessed for both performance and generalizability. We contend that shedding light on the complex mechanisms underlying psychiatric disorders will require consideration of the unique utility, interpretability, and reliability of the neuroimaging features (e.g., regions, networks, connections) identified from machine learning approaches. Finally, we discuss how the rise of large, multisite, publicly available datasets may contribute to the utility of machine learning approaches in psychiatry.