Patterns of co-altered brain structure and function underlying neurological soft signs in schizophrenia spectrum disorders

Deciphering the interplay between psychopathological symptoms, sensorimotor, cognitive and global functioning: a transdiagnostic network analysis

BACKGROUND

Understanding the relationship between psychopathology and major domains of human neurobehavioral functioning may identify new transdiagnostic treatment targets. However, studies examining the interrelationship between psychopathological symptoms, sensorimotor, cognitive, and global functioning in a transdiagnostic sample are lacking. We hypothesized a close relationship between sensorimotor and cognitive functioning in a transdiagnostic patient sample.

METHODS

We applied network analysis and community detection methods to examine the interplay and centrality [expected influence (EI) and strength] between psychopathological symptoms, sensorimotor, cognitive, and global functioning in a transdiagnostic sample consisting of 174 schizophrenia spectrum (SSD) and 38 mood disorder (MOD) patients. All patients (n = 212) were examined with the Positive and Negative Syndrome Scale (PANSS), the Heidelberg Neurological Soft Signs Scale (NSS), the Global Assessment of Functioning (GAF), and the Brief Cognitive Assessment Tool for Schizophrenia consisted of trail making test B (TMT-B), category fluency (CF) and digit symbol substitution test (DSST).

RESULTS

NSS showed closer connections with TMT-B, CF, and DSST than with GAF and PANSS. DSST, PANSS general, and NSS motor coordination scores showed the highest EI. Sensory integration, DSST, and CF showed the highest strength.

CONCLUSIONS

The close connection between sensorimotor and cognitive impairment as well as the high centrality of sensorimotor symptoms suggests that both domains share aspects of SSD and MOD pathophysiology. But, because the majority of the study population was diagnosed with SSD, the question as to whether sensorimotor symptoms are really a transdiagnostic therapeutic target needs to be examined in future studies including more balanced diagnostic groups.

Spontaneous Brain Activity Alterations in First-Episode Psychosis: A Meta-analysis of Functional Magnetic Resonance Imaging Studies

BACKGROUND AND HYPOTHESIS

Several studies have shown that spontaneous brain activity, including the total and fractional amplitude of low-frequency fluctuations (LFF) and regional homogeneity (ReHo), is altered in psychosis. Nonetheless, neuroimaging results show a high heterogeneity. For this reason, we gathered the extant literature on spontaneous brain activity in first-episode psychosis (FEP), where the effects of long-term treatment and chronic disease are minimal.

STUDY DESIGN

A systematic research was conducted on PubMed, Scopus, and Web of Science to identify studies exploring spontaneous brain activity and local connectivity in FEP estimated using functional magnetic resonance imaging. 20 LFF and 15 ReHo studies were included. Coordinate-Based Activation Likelihood Estimation Meta-Analyses stratified by brain measures, age (adolescent vs adult), and drug-naïve status were performed to identify spatially-convergent alterations in spontaneous brain activity in FEP.

STUDY RESULTS

We found a significant increase in LFF in FEP compared to healthy controls (HC) in the right striatum and in ReHo in the left striatum. When pooling together all studies on LFF and ReHo, spontaneous brain activity was increased in the bilateral striatum and superior and middle frontal gyri and decreased in the right precentral gyrus and the right inferior frontal gyrus compared to HC. These results were also replicated in the adult and drug-naïve samples.

CONCLUSIONS

Abnormalities in the frontostriatal circuit are present in early psychosis independently of treatment status. Our findings support the view that altered frontostriatal can represent a core neural alteration of the disorder and could be a target of treatment.

Data-driven multimodal fusion: approaches and applications in psychiatric research

In the era of big data, where vast amounts of information are being generated and collected at an unprecedented rate, there is a pressing demand for innovative data-driven multi-modal fusion methods. These methods aim to integrate diverse neuroimaging perspectives to extract meaningful insights and attain a more comprehensive understanding of complex psychiatric disorders. However, analyzing each modality separately may only reveal partial insights or miss out on important correlations between different types of data. This is where data-driven multi-modal fusion techniques come into play. By combining information from multiple modalities in a synergistic manner, these methods enable us to uncover hidden patterns and relationships that would otherwise remain unnoticed. In this paper, we present an extensive overview of data-driven multimodal fusion approaches with or without prior information, with specific emphasis on canonical correlation analysis and independent component analysis. The applications of such fusion methods are wide-ranging and allow us to incorporate multiple factors such as genetics, environment, cognition, and treatment outcomes across various brain disorders. After summarizing the diverse neuropsychiatric magnetic resonance imaging fusion applications, we further discuss the emerging neuroimaging analyzing trends in big data, such as N-way multimodal fusion, deep learning approaches, and clinical translation. Overall, multimodal fusion emerges as an imperative approach providing valuable insights into the underlying neural basis of mental disorders, which can uncover subtle abnormalities or potential biomarkers that may benefit targeted treatments and personalized medical interventions.

Potential Role of Smartphone Technology in Advancing Work on Neurological Soft Signs with a Focus on Schizophrenia

LEARNING OBJECTIVE AFTER PARTICIPATING IN THIS CME ACTIVITY, THE PSYCHIATRIST SHOULD BE BETTER ABLE TO

• Outline and Identify potential benefits of using neurological soft signs (NSS) as biomarkers of schizophrenia.

ABSTRACT

Since the late 1960s, NSS have been a focus of study across psychiatric illnesses, including depression, bipolar disorder, and schizophrenia in particular. Utilizing these subtle neurological impairments as biomarkers of illness has numerous benefits; NSS offer a direct connection between clinical presentation and neurological functioning, and assessments are cost-effective. However, incongruent measurement scales, confounding variables, and rating system subjectivity have hindered the advancement and scalability of NSS research and clinical implementation. This article provides a brief overview of the literature on NSS as related to schizophrenia, and proposes utilizing smartphone sensing technology to create standardized NSS assessments with objective scoring. Incorporating digital phenotyping into NSS assessment offers the potential to make measurement more scalable, accessible, and directly comparable across locations, cultures, and demographics. We conducted a narrative search in PubMed and APA PsycInfo using the following keywords: neurological soft signs, schizophrenia spectrum disorders, and psychotic illnesses. No date limitations were used. There is no other direct work on NSS and new smartphone methods like digital phenotyping; though, there is related work in neurology. Harnessing advances in smartphone technology could provide greater insight into and further our understanding of specific aspects of the NSS field. For instance, it could help us distinguish trait vs. state markers and better understand how distinct groups of signs may reflect different aspects of psychiatric illness and neurological impairment. In addition, such technology can help advance research on the capabilities of NSS as an effective diagnostic tool.

A tablet-based quantitative assessment of manual dexterity for detection of early psychosis

Background

We performed a pilot study on whether tablet-based measures of manual dexterity can provide behavioral markers for detection of first-episode psychosis (FEP), and whether cortical excitability/inhibition was altered in FEP.

Methods

Behavioral and neurophysiological testing was undertaken in persons diagnosed with FEP (N = 20), schizophrenia (SCZ, N = 20), autism spectrum disorder (ASD, N = 20), and in healthy control subjects (N = 20). Five tablet tasks assessed different motor and cognitive functions: Finger Recognition for effector (finger) selection and mental rotation, Rhythm Tapping for temporal control, Sequence Tapping for control/memorization of motor sequences, Multi Finger Tapping for finger individuation, and Line Tracking for visuomotor control. Discrimination of FEP (from other groups) based on tablet-based measures was compared to discrimination through clinical neurological soft signs (NSS). Cortical excitability/inhibition, and cerebellar brain inhibition were assessed with transcranial magnetic stimulation.

Results

Compared to controls, FEP patients showed slower reaction times and higher errors in Finger Recognition, and more variability in Rhythm Tapping. Variability in Rhythm Tapping showed highest specificity for the identification of FEP patients compared to all other groups (FEP vs. ASD/SCZ/Controls; 75% sensitivity, 90% specificity, AUC = 0.83) compared to clinical NSS (95% sensitivity, 22% specificity, AUC = 0.49). Random Forest analysis confirmed FEP discrimination vs. other groups based on dexterity variables (100% sensitivity, 85% specificity, balanced accuracy = 92%). The FEP group had reduced short-latency intra-cortical inhibition (but similar excitability) compared to controls, SCZ, and ASD. Cerebellar inhibition showed a non-significant tendency to be weaker in FEP.

Conclusion

FEP patients show a distinctive pattern of dexterity impairments and weaker cortical inhibition. Easy-to-use tablet-based measures of manual dexterity capture neurological deficits in FEP and are promising markers for detection of FEP in clinical practice.

Neurological Soft Signs in Schizophrenia, a Picture of the Knowledge in the Last Decade: A Scoping Review

(1) Background: Neurological Soft Signs (NSS) are subtle neurological abnormalities that are more common in schizophrenia patients than in healthy individuals and have been regularly observed in neuroleptic-naive first-episode patients, supporting the hypothesis that they are an intrinsic component of schizophrenia. (2) Methods: a review of articles published in the last ten years (from January 2013 to January 2023) was carried out on articles published in ScienceDirect and PubMed, by following the PRISMA Statement extension for scoping reviews (PRISMA-ScR), which evaluated the impact of NSS in correlation with the symptomatology, neuroleptic treatment, and the cerebral structural changes of patients with schizophrenia. (3) Results: thirty articles were included, among them twelve included MRI structural evaluation and four studies with a longitudinal design. (4) Conclusions: interest in researching NSS has increased in recent years, but questions remain about their origin and relationship to schizophrenia symptoms, thus this study aims to fill in information gaps in the hope that future research will help provide individualized treatment. It is suggested that NSS in schizophrenia might have an inherited genetic relationship pattern, thus being in line with a trait viewpoint. Most of the research revealed that schizophrenia patients had higher NSS scores than healthy controls, however, they were rather similar to their first-degree relatives, thus, also arguing in favor of a trait perspective. The greatest improvement in scores is seen in those with a remitting course, as shown by declining NSS ratings concurrent with symptomatology.

Functional correlates of neurological soft signs in heavy cannabis users

Sensorimotor dysfunction has been previously reported in persons with cannabis dependence. Such individuals can exhibit increased levels of neurological soft signs (NSS), particularly involving motor coordination, sensorimotor integration and complex motor task performance. Abnormal NSS levels can also be detected in non-dependent individuals with heavy cannabis use (HCU), yet very little is known about the functional correlates underlying such deficits. Here, we used resting-state functional magnetic resonance imaging (MRI) to investigate associations between NSS and intrinsic neural activity (INA) in HCU (n = 21) and controls (n = 26). Compared with controls, individuals with HCU showed significantly higher NSS across all investigated subdomains. Three of these subdomains, that is, motor coordination, sensorimotor integration and complex motor task behaviour, were associated with specific use-dependent variables, particularly age of onset of cannabis use and current cannabis use. Between-group comparisons of INA revealed lower regional homogeneity (ReHo) in left precentral gyrus, left inferior occipital gyrus, right triangular pat of the inferior frontal gyrus and right precentral gyrus in HCU compared with controls. In addition, HCU showed also higher ReHo in right cerebellum and left postcentral gyrus compared with controls. Complex motor task behaviour in HCU was significantly related to INA in postcentral, inferior frontal and occipital cortices. Our findings indicate abnormal ReHo in HCU in regions associated with sensorimotor, executive control and visuomotor-integration processes. Importantly, we show associations between ReHo, cannabis-use behaviour and execution of complex motor tasks. Given convergent findings in manifest psychotic disorders, this study suggests an HCU endophenotype that may present with a cumulative risk for psychosis.

Symmetric data-driven fusion of diffusion tensor MRI: Age differences in white matter

In the past 20 years, white matter (WM) microstructure has been studied predominantly using diffusion tensor imaging (DTI). Decreases in fractional anisotropy (FA) and increases in mean (MD) and radial diffusivity (RD) have been consistently reported in healthy aging and neurodegenerative diseases. To date, DTI parameters have been studied individually (e.g., only FA) and separately (i.e., without using the joint information across them). This approach gives limited insights into WM pathology, increases the number of multiple comparisons, and yields inconsistent correlations with cognition. To take full advantage of the information in a DTI dataset, we present the first application of symmetric fusion to study healthy aging WM. This data-driven approach allows simultaneous examination of age differences in all four DTI parameters. We used multiset canonical correlation analysis with joint independent component analysis (mCCA + jICA) in cognitively healthy adults (age 20-33, n = 51 and age 60-79, n = 170). Four-way mCCA + jICA yielded one high-stability modality-shared component with co-variant patterns of age differences in RD and AD in the corpus callosum, internal capsule, and prefrontal WM. The mixing coefficients (or loading parameters) showed correlations with processing speed and fluid abilities that were not detected by unimodal analyses. In sum, mCCA + jICA allows data-driven identification of cognitively relevant multimodal components within the WM. The presented method should be further extended to clinical samples and other MR techniques (e.g., myelin water imaging) to test the potential of mCCA+jICA to discriminate between different WM disease etiologies and improve the diagnostic classification of WM diseases.

Parkinson's Disease-Related Brain Metabolic Pattern Is Expressed in Schizophrenia Patients during Neuroleptic Drug-Induced Parkinsonism

Drug-induced parkinsonism (DIP) is a frequent parkinsonian syndrome that appears as a result of pharmacotherapy for the management of psychosis. It could substantially hamper treatment and therefore its diagnosis has a direct influence on treatment effectiveness. Although of such high importance, there is a lack of systematic research for developing neuroimaging-based criteria for DIP diagnostics for such patients. Therefore, the current study was aimed at applying a metabolic brain imaging approach using the 18F-FDG positron emission tomography and spatial covariance analysis to reveal possible candidates for DIP markers. As a result, we demonstrated, to our knowledge, the first attempt at the application of the Parkinson's Disease-Related Pattern (PDRP) as a metabolic signature of parkinsonism for the assessment of PDRP expression for schizophrenia patients with DIP. As a result, we observed significant differences in PDRP expression between the control group and the groups with PD and DIP patients. Similar differences in PDRP expression were also found when the non-DIP schizophrenia patients were compared with the PD group. Therefore, our findings made it possible to conclude that PDRP is a promising tool for the development of clinically relevant criteria for the estimation of the risk of developing DIP.

Structural network alterations and their association with neurological soft signs in schizophrenia: Evidence from clinical patients and unaffected siblings

BACKGROUND

Grey matter abnormalities and neurological soft signs (NSS) have been found in schizophrenia patients and their unaffected relatives. Evidence suggested that NSS are associated with grey matter morphometrical alterations in multiple regions in schizophrenia. However, the association between NSS and structural abnormalities at network level remains largely unexplored, especially in the schizophrenia and unaffected siblings.

METHOD

We used source-based morphometry (SBM) to examine the association of structural brain network characteristics with NSS in 62 schizophrenia patients, 25 unaffected siblings, and 60 healthy controls.

RESULTS

Two components, namely the IC-5 (superior temporal gyrus, inferior frontal gyrus and insula network) and the IC-10 (parahippocampal gyrus, fusiform, thalamus and insula network) showed significant grey matter reductions in schizophrenia patients compared to healthy controls and unaffected siblings. Further association analysis demonstrated separate NSS-related grey matter covarying patterns in schizophrenia, unaffected siblings and healthy controls. Specifically, NSS were negatively associated with IC-1 (hippocampus, caudate and thalamus network) and IC-5 in schizophrenia, but with IC-3 (caudate, superior and middle frontal cortices network) in unaffected siblings and with IC-5 in healthy controls.

CONCLUSION

Our results confirmed the key cortical and subcortical network abnormalities and NSS-related grey matter covarying patterns in the schizophrenia and unaffected siblings. Our findings suggest that brain regions implicating genetic liability to schizophrenia are partly separated from brain regions implicating neural abnormalities.

The neural substrates of neurological soft signs in schizophrenia: a systematic review

Neurological soft signs (NSS) are common in patients with schizophrenia. However, the neural substrates of NSS remain poorly understood. Using legacy PubMed, we performed a systematic review and included studies that assessed NSS and obtained neuroimaging data in patients with a schizophrenia spectrum disorder published up to June 2020. We systematically reviewed 35 relevant articles. Studies consistently implicate the basal ganglia and cerebellum as structural substrates of NSS and suggest that somatomotor and somatosensory regions as well as areas involved in visual processing and spatial orientation may underlie NSS in psychosis spectrum disorders. Additionally, dysfunction of frontoparietal and cerebellar networks has been implicated in the pathophysiology of NSS. The current literature outlines several structural and functional brain signatures that are relevant for NSS in schizophrenia spectrum disorder. The majority of studies assessed gray matter structure, but only a few studies leveraged other imaging methods such as diffusion weighted imaging, or molecular imaging. Due to this, it remains unclear if white matter integrity deficits or neurometabolic alterations contribute to NSS in the illness. While a substantial portion of the literature has been conducted in patients in the early illness stages, mitigating confounds of illness chronicity, few studies have been conducted in antipsychotic medication-naïve patients, which is a clear limitation. Furthermore, only little is known about the temporal evolution of NSS and associated brain signatures. Future studies addressing these pivotal gaps in our mechanistic understanding of NSS will be important.

Relationships between early age at onset of psychotic symptoms and treatment resistant schizophrenia

AIM

Early age at schizophrenia onset (EOS) has been associated with a worse clinical course, although previous studies reported substantial heterogeneity. Despite the relevance of the subject, the relationship between the age of onset and treatment resistant schizophrenia (TRS) is less clear.

METHODS

We screened 197 non-affective psychotic patients. Of these, 99 suffered from schizophrenia and were putative TRS and were included in a prospective 4-to-8-week trial to assess their response to antipsychotics. According to status (TRS/nonTRS) and age-at-onset (early: ≤18 years, EOS; adult: >18 years, adult onset schizophrenia [AOS]) patients were subdivided in EOS-TRS, EOS-nonTRS, AOS-TRS, AOS-nonTRS. Multiple clinical variables were measured and compared by analysis of covariance (ANCOVA), using age as a covariate. Two-way analysis of variance (ANOVA) was used to assess whether significant differences were attributable to TRS status or age-at-onset.

RESULTS

The rate of TRS patients was significantly higher in EOS compared to AOS. At the ANCOVA, EOS-TRS had significantly worse clinical, cognitive, and psychosocial outcomes compared to the other groups. Overall, EOS-TRS were more impaired than EOS-nonTRS, while significant differences with AOS-TRS were less consistent, albeit appreciable. Two-way ANOVA demonstrated that, in the majority of the investigated variables, the significant differences among groups were attributable to the TRS status effect rather than to age-at-onset or combined effects.

CONCLUSIONS

These results suggest that refractoriness to antipsychotics may be strongly linked to the early onset of psychotic symptoms, possibly as a result of common neurobiology.

Neurological Soft Signs in Non-diabetic End Stage Renal Disease Patients: Evaluation and Prediction

Patients on hemodialysis suffer from several serious complex neurological complications resulting in significant disability. Early detection of these complications during the asymptomatic phase may consent to early intervention to prevent or minimize the disability. To assess and predict neurological soft signs (NSS) in non-diabetic end-stage renal disease (ESRD) patients on hemodialysis (HD) who do not suffer any apparent neurological symptoms. An analytical, cross-sectional study was done in Hemodialysis units in the Suez Canal University Hospitals. 96 ESRD adult patients on hemodialysis are exposed to: Medical history was taken via personal interview, laboratory tests, and clinical assessment of NSS using Heidelberg scale, and brain CT was done for 50 high-risk patients (hypertensive or those on dialysis for more than 5 years) to detect the presence of any probable neuro-radiological brain abnormalities. 79.2% of our studied ESRD patients on HD had positive NSS with a mean value of total score 8.5 ± 5.9. Strong positive correlations were present between NSS and Hb levels, duration of hemodialysis, and hypertension. CT had revealed no abnormality. NSS represent a reliable, affordable tool for regular bedside assessment of ESRD patients with HD who do not suffer any neurological symptoms for early detection of asymptomatic neurological lesions, especially since the CT brain scan did not show such changes early. The duration of hemodialysis, Hb level, and hypertension were independent predictors for the occurrence of silent neurological lesions in ESRD patients.

Progress in sensorimotor neuroscience of schizophrenia spectrum disorders: Lessons learned and future directions

The number of neuroimaging studies on movement disorders, sensorimotor, and psychomotor functioning in schizophrenia spectrum disorders (SSD) has steadily increased over the last two decades. Accelerated by the addition of the "sensorimotor domain" to the Research Domain Criteria (RDoC) framework in January 2019, neuroscience research on the role of sensorimotor dysfunction in SSD has gained greater scientific and clinical relevance. To draw attention to recent rapid progress in the field, we performed a triennial systematic review (PubMed search from January 1st^, 2018 through December 31st^, 2020), in which we highlight recent neuroimaging findings and discuss methodological pitfalls as well as challenges for future research. The identified magnetic resonance imaging (MRI) studies suggest that sensorimotor abnormalities in SSD are related to cerebello-thalamo-cortico-cerebellar network dysfunction. Longitudinal and interventional studies highlight the translational potential of the sensorimotor domain as putative biomarkers for treatment response and as targets for non-invasive neurostimulation techniques in SSD.

Structural correlates of sensorimotor dysfunction in heavy cannabis users

Sensorimotor dysfunction has been previously reported in persons with cannabis dependence. Such individuals can exhibit increased levels of neurological soft signs (NSS), particularly involving motor coordination and sensorimotor integration. Whether such abnormalities may also apply to non-dependent individuals with heavy cannabis use (HCU) is unknown, as much as the neural correlates underlying such deficits. In this study, we investigated associations between NSS and gray matter volume (GMV) in males with HCU and male controls. Twenty-four persons with HCU and 17 controls were examined using standardized assessment of NSS and structural magnetic resonance imaging (MRI) at 3 T. GMV was calculated using voxel-based morphometry algorithms provided by the Computational Anatomy Toolbox (CAT12). Individuals with HCU showed higher NSS total scores compared to controls. In particular, significant NSS-subdomain effects were found for "motor coordination" (MoCo), "complex motor tasks" (CoMT), and "hard signs" (HS) expression in HCU (p < 0.05, Bonferroni-corrected). Compared to controls, persons with HCU showed significant NSS/GMV interactions in putamen and inferior frontal cortex (MoCo), right cerebellum (CoMT) and middle and superior frontal cortices, and bilateral precentral cortex and thalamus (HS). In between-group analyses, individuals with HCU showed lower GMV in the right anterior orbital and precentral gyrus, as well as higher GMV in the right superior frontal gyrus and left supplementary motor cortex compared to controls. The data support the notion of abnormal sensorimotor performance associated with HCU. The data also provide a neuromechanistic understanding of such deficits, particularly with respect to aberrant cortical-thalamic-cerebellar-cortical circuit.

Neurological Soft Signs Are Associated With Altered White Matter in Patients With Schizophrenia

Neurological soft signs (NSS) are related to grey matter and functional brain abnormalities in schizophrenia. Studies in healthy subjects suggest, that NSS are also linked to white matter. However, the association between NSS and white matter abnormalities in schizophrenia remains to be elucidated. The present study investigated, if NSS are related to white matter alterations in patients with schizophrenia. The total sample included 42 healthy controls and 41 patients with schizophrenia. We used the Neurological Evaluation Scale (NES), and we acquired diffusion weighted magnetic resonance imaging to assess white matter on a voxel-wise between subject statistic. In patients with schizophrenia, linear associations between NES with fractional anisotropy (FA), radial, axial, and mean diffusivity were analyzed with tract-based spatial statistics while controlling for age, medication dose, the severity of the disease, and motion. The main pattern of results in patients showed a positive association of NES with all diffusion measures except FA in important motor pathways: the corticospinal tract, internal capsule, superior longitudinal fascicle, thalamocortical radiations and corpus callosum. In addition, exploratory tractography analysis revealed an association of the right aslant with NES in patients. These results suggest that specific white matter alterations, that is, increased diffusivity might contribute to NSS in patients with schizophrenia.

Neurological Soft Signs (NSS) in Census-Based, Decade-Adjusted Healthy Adults, 20 to >70 Years of Age

Neurological soft signs (NSS) represent minor neurological features and have been widely studied in psychiatric disease. The assessment is easily performed. Quantity and quality may provide useful information concerning the disease course. Mostly, NSS scores differ significantly between patients and controls. However, literature does not give reference values. In this pilot study, we recruited 120 healthy women and men to build a cross-sectional, census-based sample of healthy individuals, aged 20 to >70 years, subdivided in 10-year blocks for a close approach to the human lifeline. Testing for NSS and neurocognitive functioning was performed following the exclusion of mental and severe physical illness. NSS scores increased significantly between ages 50+ and 60+, which was primarily accountable to motor signs. Gender and cognitive functioning were not related to changes of scores. Although the number of individuals is small, study results may lay a foundation for further validation of NSS in healthy individuals.

[The sensorimotor domain in the research domain criteria system: progress and perspectives]

Over the past three decades research interest in hypokinetic, hyperkinetic, sensorimotor and psychomotor abnormalities in mental disorders has steadily increased. This development has led to an increasing number of scientific initiatives that have not only highlighted the clinical need for early detection of extrapyramidal motor symptoms, tardive dyskinesia and catatonia but also provided numerous neurobiological findings and clinically relevant results based on the pathology of the sensorimotor system in patients with mental disorders. In view of these developments in January 2019 the National Institute of Mental Health (NIMH) research domain criteria (RDoC) initiative introduced a sixth domain called the sensorimotor domain to address deficits in the sensorimotor system and associated behavioral abnormalities. To draw attention to the rapid progress just since the introduction of the sensorimotor domain, a 2-year (1 January 2019-18 February 2021) systematic review is presented highlighting recent neuroimaging findings and discussing challenges for future research. In summary, aberrant sensorimotor processing in mental disorders is associated with dysfunction of the cerebello-thalamo-motor cortex network, which interacts with (social)cognitive and affective systems. Initial longitudinal and interventional studies highlight the translational potential of the sensorimotor domain.

Neurological Soft Signs Are Associated With Altered Cerebellar-Cerebral Functional Connectivity in Schizophrenia

Cerebellar dysfunction is associated with neurological soft signs (NSS), which is a promising endophenotype for schizophrenia spectrum disorders. However, the relationship between cerebellar-cerebral resting-state functional connectivity (rsFC) and NSS is largely unexplored. Moreover, both NSS and cerebellar-cerebral rsFC have been found to be correlated with negative symptoms of schizophrenia. Here, we investigated the correlations between NSS and cerebellar-cerebral rsFC, explored their relationship with negative symptoms in a main dataset, and validated the significant findings in a replication dataset. Both datasets comprised schizophrenia patients and healthy controls. In schizophrenia patients, we found positive correlations between NSS and rsFC of the cerebellum with the inferior frontal gyrus and the precuneus, and negative correlations between NSS and rsFC of the cerebellum with the inferior temporal gyrus. In healthy controls, NSS scores were positively correlated with rsFC of the cerebellum with the superior frontal gyrus and negatively correlated with rsFC between the cerebellum and the middle occipital gyrus. Cerebellar-prefrontal rsFC was also positively correlated with negative symptoms in schizophrenia patients. These findings were validated in the replication dataset. Our results suggest that the uncoupling of rsFC between the cerebellum and the cerebral cortex may underlie the expression of NSS in schizophrenia. NSS-related cerebellar-prefrontal rsFC may be a potential neural pathway for possible neural modulation to alleviate negative symptoms.

Multimodal MRI assessment for first episode psychosis: A major change in the thalamus and an efficient stratification of a subgroup

Multi‐institutional brain imaging studies have emerged to resolve conflicting results among individual studies. However, adjusting multiple variables at the technical and cohort levels is challenging. Therefore, it is important to explore approaches that provide meaningful results from relatively small samples at institutional levels. We studied 87 first episode psychosis (FEP) patients and 62 healthy subjects by combining supervised integrated factor analysis (SIFA) with a novel pipeline for automated structure‐based analysis, an efficient and comprehensive method for dimensional data reduction that our group recently established. We integrated multiple MRI features (volume, DTI indices, resting state fMRI—rsfMRI) in the whole brain of each participant in an unbiased manner. The automated structure‐based analysis showed widespread DTI abnormalities in FEP and rs‐fMRI differences between FEP and healthy subjects mostly centered in thalamus. The combination of multiple modalities with SIFA was more efficient than the use of single modalities to stratify a subgroup of FEP (individuals with schizophrenia or schizoaffective disorder) that had more robust deficits from the overall FEP group. The information from multiple MRI modalities and analytical methods highlighted the thalamus as significantly abnormal in FEP. This study serves as a proof‐of‐concept for the potential of this methodology to reveal disease underpins and to stratify populations into more homogeneous sub‐groups.

Neurological Soft Signs Predict Auditory Verbal Hallucinations in Patients With Schizophrenia

Neurological soft signs (NSS) are well documented in individuals with schizophrenia (SZ), yet so far, the relationship between NSS and specific symptom expression is unclear. We studied 76 SZ patients using magnetic resonance imaging (MRI) to determine associations between NSS, positive symptoms, gray matter volume (GMV), and neural activity at rest. SZ patients were hypothesis-driven stratified according to the presence or absence of auditory verbal hallucinations (AVH; n = 34 without vs 42 with AVH) according to the Brief Psychiatric Rating Scale. Structural MRI data were analyzed using voxel-based morphometry, whereas intrinsic neural activity was investigated using regional homogeneity (ReHo) measures. Using ANCOVA, AVH patients showed significantly higher NSS in motor and integrative functions (IF) compared with non-hallucinating (nAVH) patients. Partial correlation revealed that NSS IF were positively associated with AVH symptom severity in AVH patients. Such associations were not confirmed for delusions. In region-of-interest ANCOVAs comprising the left middle and superior temporal gyri, right paracentral lobule, and right inferior parietal lobule (IPL) structure and function, significant differences between AVH and nAVH subgroups were not detected. In a binary logistic regression model, IF scores and right IPL ReHo were significant predictors of AVH. These data suggest significant interrelationships between sensorimotor integration abilities, brain structure and function, and AVH symptom expression.

A technical review of canonical correlation analysis for neuroscience applications

Collecting comprehensive data sets of the same subject has become a standard in neuroscience research and uncovering multivariate relationships among collected data sets have gained significant attentions in recent years. Canonical correlation analysis (CCA) is one of the powerful multivariate tools to jointly investigate relationships among multiple data sets, which can uncover disease or environmental effects in various modalities simultaneously and characterize changes during development, aging, and disease progressions comprehensively. In the past 10 years, despite an increasing number of studies have utilized CCA in multivariate analysis, simple conventional CCA dominates these applications. Multiple CCA-variant techniques have been proposed to improve the model performance; however, the complicated multivariate formulations and not well-known capabilities have delayed their wide applications. Therefore, in this study, a comprehensive review of CCA and its variant techniques is provided. Detailed technical formulation with analytical and numerical solutions, current applications in neuroscience research, and advantages and limitations of each CCA-related technique are discussed. Finally, a general guideline in how to select the most appropriate CCA-related technique based on the properties of available data sets and particularly targeted neuroscience questions is provided.

Movement disorder and sensorimotor abnormalities in schizophrenia and other psychoses - European consensus on assessment and perspectives

Over the last three decades, movement disorder as well as sensorimotor and psychomotor functioning in schizophrenia (SZ) and other psychoses has gained greater scientific and clinical relevance as an intrinsic component of the disease process of psychotic illness; this extends to early psychosis prediction, early detection of motor side effects of antipsychotic medication, clinical outcome monitoring, treatment of psychomotor syndromes (e.g. catatonia), and identification of new targets for non-invasive brain stimulation. In 2017, a systematic cooperation between working groups interested in movement disorder and sensorimotor/psychomotor functioning in psychoses was initiated across European universities. As a first step, the members of this group would like to introduce and define the theoretical aspects of the sensorimotor domain in SZ and other psychoses. This consensus paper is based on a synthesis of scientific evidence, good clinical practice and expert opinions that were discussed during recent conferences hosted by national and international psychiatric associations. While reviewing and discussing the recent theoretical and experimental work on neural mechanisms and clinical implications of sensorimotor behavior, we here seek to define the key principles and elements of research on movement disorder and sensorimotor/psychomotor functioning in psychotic illness. Finally, the members of this European group anticipate that this consensus paper will stimulate further multimodal and prospective studies on hypo- and hyperkinetic movement disorders and sensorimotor/psychomotor functioning in SZ and other psychotic disorders.

Neurological Signs at the First Psychotic Episode as Correlates of Long-Term Outcome: Results From the AESOP-10 Study

Minor neurological signs are subtle deficits in sensory integration, motor coordination, and sequencing of complex motor acts present in excess in the early stages of psychosis. Still, it remains unclear whether at least some of these signs represent trait or state markers for psychosis and whether they are markers of long-term disease outcome of clinical utility. We examined the relationship between neurological function at illness onset assessed with the Neurological Evaluation Scale and subsequent illness course in 233 patients from AESOP-10 (Aetiology and Ethnicity in Schizophrenia and Other Psychoses), a 10-year follow-up study of a population-based cohort of individuals recruited at the time of their first episode of psychosis in the United Kingdom. In 56 of these patients, we also explored changes in neurological function over time. We included a group of 172 individuals without psychosis as controls. After 10 years, 147 (63%) patients had developed a non-remitting course of illness, and 86 (37%) a remitting course. Already at first presentation, patients who developed a non-remitting course had significantly more primary, motor coordination, and total signs than both remitting patients and healthy controls. While Motor Coordination signs did not change over time, rates of Primary, Sensory Integration, and Total signs increased, independently of illness course type. These findings suggest that motor coordination problems could be a useful early, quick, and easily detectable marker of subsequent clinical outcome. With other motor abnormalities, a measure of motor incoordination could contribute to the identification of the most vulnerable individuals, who could benefit from targeted and more assertive treatment approaches.

A Neural Signature of Parkinsonism in Patients With Schizophrenia Spectrum Disorders: A Multimodal MRI Study Using Parallel ICA

Motor abnormalities in schizophrenia spectrum disorders (SSD) have increasingly attracted scientific interest in the past years. However, the neural mechanisms underlying parkinsonism in SSD are unclear. The present multimodal magnetic resonance imaging (MRI) study examined SSD patients with and without parkinsonism, as defined by a Simpson and Angus Scale (SAS) total score of ≥4 (SAS group, n = 22) or <4 (non-SAS group, n = 22). Parallel independent component analysis (p-ICA) was used to examine the covarying components among gray matter volume maps computed from structural MRI (sMRI) and fractional amplitude of low-frequency fluctuations (fALFF) maps computed from resting-state functional MRI (rs-fMRI) patient data. We found a significant correlation (P = .020, false discovery rate [FDR] corrected) between an sMRI component and an rs-fMRI component, which also significantly differed between the SAS and non-SAS group (P = .042, z = -2.04). The rs-fMRI component comprised the cortical sensorimotor network, and the sMRI component included predominantly a frontothalamic/cerebellar network. Across the patient sample, correlations adjusted for the Positive and Negative Syndrome Scale (PANSS) total scores showed a significant relationship between tremor score and loadings of the cortical sensorimotor network, as well as between glabella-salivation score, frontothalamic/cerebellar and cortical sensorimotor network loadings. These data provide novel insights into neural mechanisms of parkinsonism in SSD. Aberrant bottom-up modulation of cortical motor regions may account for these specific motor symptoms, at least in patients with SSD.

Neurological soft signs (NSS) and gray matter volume (GMV) in first-episode psychosis: An analysis of NSS motor subscores

We aimed to study the correlations between gray matter volume and the motor subscores of NSS in first-episode psychosis patients with both, whole brain and region of interest analyses. The structural MRIs of 81 first-episode psychosis patients were analyzed by using voxel-based morphometry (VBM) for SPM. NSS were assessed using the Heidelberg scale. Significant decreases of gray matter volume were correlated to high NSS total scores and, more specifically, frontal, subcortical and cerebellar areas were significantly correlated with increased scores of the subscores Motor Coordination (MoCo) and Complex Motor Tasks (CMT). When applying a stricter statistical correction, only the frontal gyrus and caudate nucleus survived for MoCo; whereas the precentral and superior frontal gyri survived for CMT. When doing regional analyses, using as masks the structures deemed as significant by the whole brain analyses and applying the FWE-correction, the superior frontal gyrus, thalamus and caudate nucleus correlated negatively with MoCo; and the precentral and superior frontal gyri, thalamus and caudate nucleus showed inverse correlations with CMT. These results suggest that cerebral cortex, subcortical structures (thalamus and striatum) and cerebellum are inversely correlated to both motor NSS subscores, the first time a study describes this relationship for all the relevant structures simultaneously. For its part, ROI proves to be effective demonstrating that subcortical structures (thalamus and caudate) are the most affected by motor NSS.

Patterns of co-altered brain structure and function underlying neurological soft signs in schizophrenia spectrum disorders

Neurological soft signs (NSS) comprise a broad range of subtle neurological deficits and are considered to represent external markers of sensorimotor dysfunction frequently found in mental disorders of presumed neurodevelopmental origin. Although NSS frequently occur in schizophrenia spectrum disorders (SSD), specific patterns of co-altered brain structure and function underlying NSS in SSD have not been investigated so far. It is unclear whether gray matter volume (GMV) alterations or aberrant brain activity or a combination of both, are associated with NSS in SSD. Here, 37 right-handed SSD patients and 37 matched healthy controls underwent motor assessment and magnetic resonance imaging (MRI) at 3 T. NSS were examined on the Heidelberg NSS scale. We used a multivariate data fusion technique for multimodal MRI data-multiset canonical correlation and joint independent component analysis (mCCA + jICA)-to investigate co-altered patterns of GMV and intrinsic neural fluctuations (INF) in SSD patients exhibiting NSS. The mCCA + jICA model indicated two joint group-discriminating components (temporoparietal/cortical sensorimotor and frontocerebellar/frontoparietal networks) and one modality-specific group-discriminating component (p < .05, FDR corrected). NSS motor score was associated with joint frontocerebellar/frontoparietal networks in SSD patients. This study highlights complex neural pathomechanisms underlying NSS in SSD suggesting aberrant structure and function, predominantly in cortical and cerebellar systems that critically subserve sensorimotor dynamics and psychomotor organization.