Mismatch between clinically defined classification of ALS stage and the burden of cerebral pathology.

This study aimed to investigate the clinical stratification of amyotrophic lateral sclerosis (ALS) patients in relation to in vivo cerebral degeneration. One hundred forty-nine ALS patients and one hundred forty-four healthy controls (HCs) were recruited from the Canadian ALS Neuroimaging Consortium (CALSNIC). Texture analysis was performed on T1-weighted scans to extract the texture feature "autocorrelation" (autoc), an imaging biomarker of cerebral degeneration. Patients were stratified at baseline into early and advanced disease stages based on criteria adapted from ALS clinical trials and the King's College staging system, as well as into slow and fast progressors (disease progression rates, DPR). Patients had increased autoc in the internal capsule. These changes extended beyond the internal capsule in early-stage patients (clinical trial-based criteria), fast progressors, and in advanced-stage patients (King's staging criteria). Longitudinal increases in autoc were observed in the postcentral gyrus, corticospinal tract, posterior cingulate cortex, and putamen; whereas decreases were observed in corpus callosum, caudate, central opercular cortex, and frontotemporal areas. Both longitudinal increases and decreases of autoc were observed in non-overlapping regions within insula and precentral gyrus. Within-criteria comparisons of autoc revealed more pronounced changes at baseline and longitudinally in early- (clinical trial-based criteria) and advanced-stage (King's staging criteria) patients and fast progressors. In summary, comparative patterns of baseline and longitudinal progression in cerebral degeneration are dependent on sub-group selection criteria, with clinical trial-based stratification insufficiently characterizing disease stage based on pathological cerebral burden.

SF2Former: Amyotrophic lateral sclerosis identification from multi-center MRI data using spatial and frequency fusion transformer.

Amyotrophic Lateral Sclerosis (ALS) is a complex neurodegenerative disorder characterized by motor neuron degeneration. Significant research has begun to establish brain magnetic resonance imaging (MRI) as a potential biomarker to diagnose and monitor the state of the disease. Deep learning has emerged as a prominent class of machine learning algorithms in computer vision and has shown successful applications in various medical image analysis tasks. However, deep learning methods applied to neuroimaging have not achieved superior performance in classifying ALS patients from healthy controls due to insignificant structural changes correlated with pathological features. Thus, a critical challenge in deep models is to identify discriminative features from limited training data. To address this challenge, this study introduces a framework called SF2Former, which leverages the power of the vision transformer architecture to distinguish ALS subjects from the control group by exploiting the long-range relationships among image features. Additionally, spatial and frequency domain information is combined to enhance the network's performance, as MRI scans are initially captured in the frequency domain and then converted to the spatial domain. The proposed framework is trained using a series of consecutive coronal slices and utilizes pre-trained weights from ImageNet through transfer learning. Finally, a majority voting scheme is employed on the coronal slices of each subject to generate the final classification decision. The proposed architecture is extensively evaluated with multi-modal neuroimaging data (i.e., T1-weighted, R2*, FLAIR) using two well-organized versions of the Canadian ALS Neuroimaging Consortium (CALSNIC) multi-center datasets. The experimental results demonstrate the superiority of the proposed strategy in terms of classification accuracy compared to several popular deep learning-based techniques.

Motor cortex functional connectivity is associated with underlying neurochemistry in ALS.

OBJECTIVE: To identify structural and neurochemical properties that underlie functional connectivity impairments of the primary motor cortex (PMC) and how these relate to clinical findings in amyotrophic lateral sclerosis (ALS). METHODS: 52 patients with ALS and 52 healthy controls, matched for age and sex, were enrolled from 5 centres across Canada for the Canadian ALS Neuroimaging Consortium study. Resting-state functional MRI, diffusion tensor imaging and magnetic resonance spectroscopy data were acquired. Functional connectivity maps, diffusion metrics and neurometabolite ratios were obtained from the analyses of the acquired multimodal data. A clinical assessment of foot tapping (frequency) was performed to examine upper motor neuron function in all participants. RESULTS: Compared with healthy controls, the primary motor cortex in ALS showed reduced functional connectivity with sensory (T=5.21), frontal (T=3.70), temporal (T=3.80), putaminal (T=4.03) and adjacent motor (T=4.60) regions. In the primary motor cortex, N-acetyl aspartate (NAA, a neuronal marker) ratios and diffusion metrics (mean, axial and radial diffusivity, fractional anisotropy (FA)) were altered. Within the ALS cohort, foot tapping frequency correlated with NAA (r=0.347) and white matter FA (r=0.537). NAA levels showed associations with disturbed functional connectivity of the motor cortex. CONCLUSION: In vivo neurochemistry may represent an effective imaging marker of impaired motor cortex functional connectivity in ALS.

Effect of Intranasal Oxytocin on Resting-state Effective Connectivity in Schizophrenia.

OBJECTIVES: Evidence from several lines of research suggests the critical role of neuropeptide oxytocin in social cognition and social behavior. Though a few studies have examined the effect of oxytocin on clinical symptoms of schizophrenia, the underlying neurobiological changes are underexamined. Hence, in this study, we examined the effect of oxytocin on the brain's effective connectivity in schizophrenia. METHODS: 31 male patients with schizophrenia (SCZ) and 21 healthy male volunteers (HV) underwent resting functional magnetic resonance imaging scans with intra-nasal oxytocin (24 IU) and placebo administered in counterbalanced order. We conducted a whole-brain effective connectivity analysis using a multivariate vector autoregressive granger causality model. We performed a conjunction analysis to control for spurious changes and canonical correlation analysis between changes in connectivity and clinical and demographic variables. RESULTS: Three connections, sourced from the left caudate survived the FDR correction threshold with the conjunction analysis; connections to the left supplementary motor area, left precentral gyrus, and left frontal inferior triangular gyrus. At baseline, SCZ patients had significantly weaker connectivity from caudate to these three regions. Oxytocin, but not placebo, significantly increased the strength of connectivity in these connections. Better cognitive insight and lower negative symptoms were associated with a greater increase in connectivity with oxytocin. CONCLUSIONS: These findings provide a preliminary mechanistic understanding of the effect of oxytocin on brain connectivity in schizophrenia. The study findings provide the rationale to examine the potential utility of oxytocin for social cognitive deficits in schizophrenia.

Conceptual disorganization and redistribution of resting-state cortical hubs in untreated first-episode psychosis: A 7T study.

Network-level dysconnectivity has been studied in positive and negative symptoms of schizophrenia. Conceptual disorganization (CD) is a symptom subtype that predicts impaired real-world functioning in psychosis. Systematic reviews have reported aberrant connectivity in formal thought disorder, a construct related to CD. However, no studies have investigated whole-brain functional correlates of CD in psychosis. We sought to investigate brain regions explaining the severity of CD in patients with first-episode psychosis (FEPs) compared with healthy controls (HCs). We computed whole-brain binarized degree centrality maps of 31 FEPs, 25 HCs, and characterized the patterns of network connectivity in the 2 groups. In FEPs, we related these findings to the severity of CD. We also studied the effect of positive and negative symptoms on altered network connectivity. Compared to HCs, reduced centrality of a right superior temporal gyrus (rSTG) cluster was observed in the FEPs. In patients exhibiting high CD, increased centrality of a medial superior parietal (mSPL) cluster was observed, compared to patients exhibiting low CD. This cluster was strongly correlated with CD scores but not with other symptom scores. Our observations are congruent with previous findings of reduced but not increased centrality. We observed increased centrality of mSPL suggesting that cortical reorganization occurs to provide alternate routes for information transfer. These findings provide insight into the underlying neural processes mediating the presentation of symptoms in untreated FEP. Longitudinal tracking of the symptom course will be useful to assess the mechanisms underlying these compensatory changes.

Mixed pathologies mimicking motor neuron disease: a case report and review of the literature.

Amyotrophic lateral sclerosis (ALS) is classified as a motor neuron disease (MND) that can present with both upper and lower motor neuron signs. Concurrent ALS and frontotemporal dementia (FTD) is also a well-known phenomenon. Examples of other primary disorders mimicking ALS or ALS-FTD have been reported in the literature and recognition of these entities is important to ensure proper clinical management. We present here an unusual case of an 86-year-old male patient, clinically diagnosed with ALS and severe cognitive impairment thought to be due to FTD. Postmortem neuropathological examination of his brain and spinal cord did not reveal the typical findings of ALS or FTD. Rather, it revealed multiple non-ALS pathologies including argyrophilic grain disease (AGD), cerebrovascular disease, and Alzheimer's type pathology. This case raises the possibility that mixed pathologies could mimic motor neuron disease.

Cultural differences and neural correlates of cognitive insight in schizophrenia.

Cognitive insight refers to a person's ability to examine their psychotic experiences and the inferences they draw from these experiences. Several studies suggest that cultural factors influence cognitive insight and the processes involved therein; a few studies have suggested differences between Western and Asian societies. However, there are no studies on cognitive insight and its neural correlates in non-Western populations. Hence, we examined factor structure of Beck's cognitive insight scale (BCIS) in a large sample of patients with schizophrenia (SCZ) and healthy volunteers (HV) from India and assessed the relationship between cortical thickness and cognitive insight. We recruited 240 participants (SCZ-140; HV-100). Of these, 58 participants (SCZ-33; HV-25) underwent magnetic resonance imaging. We found a three-factor structure for BCIS which is different from the original two factor structure; self-reflection (SR) of original two-factor structure was sub-divided into- SR1, introspection and SR2, openness to feedback. There was a significant difference between HV and SCZ in the new factors, SR1 and SR2 but not in the original SR factor. Difference was also seen on MRI analysis; while there was a significant positive correlation between original SR factor and thickness of right posterior cingulate cortex, SR2 was positively correlated with thickness of left ventrolateral prefrontal cortex. The difference in factor structure in Indian participants and their distinct neural correlates point to cultural differences in cognitive insight. While in western societies the constructs of introspection and openness to feedback might integrate, they might be separate entities in Asian population.

Antioxidant defense in schizophrenia and bipolar disorder: A meta-analysis of MRS studies of anterior cingulate glutathione.

BACKGROUND: Glutathione [GSH] is a major intracellular antioxidant that disposes peroxides and protects neurons and glial cells from oxidative stress. In both schizophrenia and bipolar disorder, atypical levels of GSH have been demonstrated, particularly in the anterior cingulate cortex (ACC), though no consistent results have emerged due to limitations in sample size. Our objective was to evaluate if GSH levels in the ACC are abnormal in these 2 disorder, when compared to healthy controls. METHODS: We reviewed all 1H-MRS studies reporting GSH values for patients satisfying DSM or ICD based criteria for (1) the psychotic disorders - schizophrenia or schizoaffective disorder or (2) bipolar disorder in comparison to a healthy controls (HC) group in the Anterior Cingulate Cortex (ACC) published until June 2018. A random-effects model was used to calculate the pooled effect size. A meta-regression analysis of moderator variables was also undertaken. RESULTS: The literature search identified 18 studies with a total sample size of 581 controls, 578 patients with schizophrenia or bipolar disorder. There is a small but significant reduction in ACC GSH in patients with schizophrenia compared to HC (N = 13; RFX SMD =0.26; 95% CI [0.07 to 0.44]; p = 0.008; heterogeneity p = 0.11). There is a significant increase in the ACC GSH concentration in bipolar disorder compared to HC (N = 6; RFX SMD = -0.28, 95% CI [-0.09 to -0.47]; p = 0.003; heterogeneity p = 0.95). CONCLUSIONS: We report a small, but significant reduction in GSH concentration in the ACC in schizophrenia, and a similar sized increase in bipolar disorder. A notable limitation is the lack of sufficient data to examine the moderating effect of the symptom profile. Schizophrenia and bipolar disorder have notably different patterns of redox abnormalities in the ACC. Reduced ACC GSH may confer a schizophrenia-like clinical phenotype, while an excess favouring a bipolar disorder-like profile.

Putative Astroglial Dysfunction in Schizophrenia: A Meta-Analysis of 1H-MRS Studies of Medial Prefrontal Myo-Inositol.

Background: Several lines of evidence support a role for astroglial pathology in schizophrenia. Myo-inositol is particularly abundant in astroglia. Many small sized studies have reported on myo-inositol concentration in schizophrenia, but to date these have not been pooled to estimate a collective effect size. Methods: We reviewed all proton magnetic resonance spectroscopy (1H-MRS) studies reporting myo-inositol values for patients satisfying DSM or ICD based criteria for schizophrenia in comparison to a healthy controls group in the medial prefrontal cortex published until February 2018. A random-effects model was used to calculate the pooled effect size using metafor package. A meta-regression analysis of moderator variables was also undertaken. Results: The literature search identified 19 studies published with a total sample size of 585 controls, 561 patients with schizophrenia. Patients with schizophrenia had significantly reduced medial prefrontal myo-inositol compared to controls (RFX standardized mean difference = 0.19, 95% CI [0.05-0.32], z = 2.72, p = 0.0067; heterogeneity p = 0.09). Studies with more female patients reported more notable schizophrenia-related reduction in myo-inositol (z = 2.53, p = 0.011). Discussion: We report a small, but significant reduction in myo-inositol concentration in the medial prefrontal cortex in schizophrenia. The size of the reported effect indicates that the biological pathways affecting the astroglia are likely to operate only in a subset of patients with schizophrenia. MRS myo-inositol could be a useful tool to stratify and investigate such patients.