Profiling Transcription Initiation in Peripheral Leukocytes Reveals Severity-Associated Cis-Regulatory Elements in Critical COVID-19

Neuroimaging epicenters as potential sites of onset of the neuroanatomical pathology in schizophrenia

Schizophrenia lacks a clear definition at the neuroanatomical level, capturing the sites of origin and progress of this disorder. Using a network-theory approach called epicenter mapping on cross-sectional magnetic resonance imaging from 1124 individuals with schizophrenia, we identified the most likely "source of origin" of the structural pathology. Our results suggest that the Broca's area and adjacent frontoinsular cortex may be the epicenters of neuroanatomical pathophysiology in schizophrenia. These epicenters can predict an individual's response to treatment for psychosis. In addition, cross-diagnostic similarities based on epicenter mapping over of 4000 individuals diagnosed with neurological, neurodevelopmental, or psychiatric disorders appear to be limited. When present, these similarities are restricted to bipolar disorder, major depressive disorder, and obsessive-compulsive disorder. We provide a comprehensive framework linking schizophrenia-specific epicenters to multiple levels of neurobiology, including cognitive processes, neurotransmitter receptors and transporters, and human brain gene expression. Epicenter mapping may be a reliable tool for identifying the potential onset sites of neural pathophysiology in schizophrenia.

The neurophysiological brain-fingerprint of Parkinson's disease

In this study, we investigate the clinical potential of brain-fingerprints derived from electrophysiological brain activity for diagnostics and progression monitoring of Parkinson's disease (PD). We obtained brain-fingerprints from PD patients and age-matched healthy controls using short, task-free magnetoencephalographic recordings. The rhythmic components of the individual brain-fingerprint distinguished between patients and healthy participants with approximately 90% accuracy. The most prominent cortical features of the Parkinson's brain-fingerprint mapped to polyrhythmic activity in unimodal sensorimotor regions. Leveraging these features, we also show that Parkinson's disease stages can be decoded directly from cortical neurophysiological activity. Additionally, our study reveals that the cortical topography of the Parkinson's brain-fingerprint aligns with that of neurotransmitter systems affected by the disease's pathophysiology. We further demonstrate that the arrhythmic components of cortical activity are more variable over short periods of time in patients with Parkinson's disease than in healthy controls, making individual differentiation between patients based on these features more challenging and explaining previous negative published results. Overall, we outline patient-specific rhythmic brain signaling features that provide insights into both the neurophysiological signature and clinical staging of Parkinson's disease. For this reason, the proposed definition of a rhythmic brain-fingerprint of Parkinson's disease may contribute to novel, refined approaches to patient stratification and to the improved identification and testing of therapeutic neurostimulation targets.

Adverse and compensatory neurophysiological slowing in Parkinson's disease

Patients with Parkinson's disease (PD) exhibit multifaceted changes in neurophysiological brain activity, hypothesized to represent a global cortical slowing effect. Using task-free magnetoencephalography and extensive clinical assessments, we found that neurophysiological slowing in PD is differentially associated with motor and non-motor symptoms along a sagittal gradient over the cortical anatomy. In superior parietal regions, neurophysiological slowing reflects an adverse effect and scales with cognitive and motor impairments, while across the inferior frontal cortex, neurophysiological slowing is compatible with a compensatory role. This adverse-to-compensatory gradient is sensitive to individual clinical profiles, such as drug regimens and laterality of symptoms; it is also aligned with the topography of neurotransmitter and transporter systems relevant to PD. We conclude that neurophysiological slowing in patients with PD signals both deleterious and protective mechanisms of the disease, from posterior to anterior regions across the cortex, respectively, with functional and clinical relevance to motor and cognitive symptoms.

Molecular-enriched functional connectivity in the human brain using multiband multi-echo simultaneous ASL/BOLD fMRI

Receptor-enriched analysis of functional connectivity by targets (REACT) is a strategy to enrich functional MRI (fMRI) data with molecular information on the neurotransmitter distribution density in the human brain, providing a biological basis to the functional connectivity (FC) analysis. Although this approach has been used in BOLD fMRI studies only so far, extending its use to ASL imaging would provide many advantages, including the more direct link of ASL with neuronal activity compared to BOLD and its suitability for pharmacological MRI studies assessing drug effects on baseline brain function. Here, we applied REACT to simultaneous ASL/BOLD resting-state fMRI data of 29 healthy subjects and estimated the ASL and BOLD FC maps related to six molecular systems. We then compared the ASL and BOLD FC maps in terms of spatial similarity, and evaluated and compared the test-retest reproducibility of each modality. We found robust spatial patterns of molecular-enriched FC for both modalities, moderate similarity between BOLD and ASL FC maps and comparable reproducibility for all but one molecular-enriched functional networks. Our findings showed that ASL is as informative as BOLD in detecting functional circuits associated with specific molecular pathways, and that the two modalities may provide complementary information related to these circuits.

Brain compartmentalization based on transcriptome analyses and its gene expression in Octopus minor

Coleoid cephalopods have a high intelligence, complex structures, and large brain. The cephalopod brain is divided into supraesophageal mass, subesophageal mass and optic lobe. Although much is known about the structural organization and connections of various lobes of octopus brain, there are few studies on the brain of cephalopod at the molecular level. In this study, we demonstrated the structure of an adult Octopus minor brain by histomorphological analyses. Through visualization of neuronal and proliferation markers, we found that adult neurogenesis occurred in the vL and posterior svL. We also obtained specific 1015 genes by transcriptome of O. minor brain and selected OLFM3, NPY, GnRH, and GDF8 genes. The expression of genes in the central brain showed the possibility of using NPY and GDF8 as molecular marker of compartmentation in the central brain. This study will provide useful information for establishing a molecular atlas of cephalopod brain.

Longitudinal grey matter and metabolic contributions to cognitive changes in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis is characterized by rapidly evolving cognitive and brain impairments. While previous work revealed structural and functional alterations associated with cognitive decline in patients suffering from amyotrophic lateral sclerosis, the relationships between anatomo-functional changes and both disease’s progression and the evolution of cognitive performance remain largely unexplored. Here, we took advantage of repeated multi-modal acquisitions in patients with amyotrophic lateral sclerosis over 1 year to assess the longitudinal sequence of grey matter atrophy, glucose metabolism and cognitive changes. Results revealed metabolic and structural changes over frontal, thalamic and temporal regions. Both cortical hypermetabolism and hypometabolism (right temporal gyrus and right angular gyrus, respectively) were associated with cognitive performance and thalamic hypometabolism during the follow-up testing session. Furthermore, the inferior frontal gyrus atrophy mediated the relation between early hypometabolism in this region and the subsequent decline of the theory of mind abilities. Marked volume loss was associated with larger hypometabolism and impaired cognitive performance. To our knowledge, this is the first study to longitudinally examine both grey matter volume and metabolic alteration patterns in patients with amyotrophic lateral sclerosis, over a mean follow-up time of 1 year. We identify how changes of the inferior frontal gyrus critically underly later cognitive performance, shedding new light on its high prognostic significance for amyotrophic lateral sclerosis-related changes. These results have important implications for our understanding of structural and functional changes associated with amyotrophic lateral sclerosis and how they underly cognitive impairments.

Local molecular and global connectomic contributions to cross-disorder cortical abnormalities

Numerous brain disorders demonstrate structural brain abnormalities, which are thought to arise from molecular perturbations or connectome miswiring. The unique and shared contributions of these molecular and connectomic vulnerabilities to brain disorders remain unknown, and has yet to be studied in a single multi-disorder framework. Using MRI morphometry from the ENIGMA consortium, we construct maps of cortical abnormalities for thirteen neurodevelopmental, neurological, and psychiatric disorders from N = 21,000 participants and N = 26,000 controls, collected using a harmonised processing protocol. We systematically compare cortical maps to multiple micro-architectural measures, including gene expression, neurotransmitter density, metabolism, and myelination (molecular vulnerability), as well as global connectomic measures including number of connections, centrality, and connection diversity (connectomic vulnerability). We find a relationship between molecular vulnerability and white-matter architecture that drives cortical disorder profiles. Local attributes, particularly neurotransmitter receptor profiles, constitute the best predictors of both disorder-specific cortical morphology and cross-disorder similarity. Finally, we find that cross-disorder abnormalities are consistently subtended by a small subset of network epicentres in bilateral sensory-motor, inferior temporal lobe, precuneus, and superior parietal cortex. Collectively, our results highlight how local molecular attributes and global connectivity jointly shape cross-disorder cortical abnormalities.

Null models in network neuroscience

Recent advances in imaging and tracing technology provide increasingly detailed reconstructions of brain connectomes. Concomitant analytic advances enable rigorous identification and quantification of functionally important features of brain network architecture. Null models are a flexible tool to statistically benchmark the presence or magnitude of features of interest, by selectively preserving specific architectural properties of brain networks while systematically randomizing others. Here we describe the logic, implementation and interpretation of null models of connectomes. We introduce randomization and generative approaches to constructing null networks, and outline a taxonomy of network methods for statistical inference. We highlight the spectrum of null models - from liberal models that control few network properties, to conservative models that recapitulate multiple properties of empirical networks - that allow us to operationalize and test detailed hypotheses about the structure and function of brain networks. We review emerging scenarios for the application of null models in network neuroscience, including for spatially embedded networks, annotated networks and correlation-derived networks. Finally, we consider the limits of null models, as well as outstanding questions for the field.

EEG Evidence Reveals Zolpidem-Related Alterations and Prognostic Value in Disorders of Consciousness

Effective treatment and accurate long-term prognostication of patients with disorders of consciousness (DOC) remain pivotal clinical issues and challenges in neuroscience. Previous studies have shown that zolpidem produces paradoxical recovery and induces similar change patterns in specific electrophysiological features in some DOC (∼6%). However, whether these specific features are neural markers of responders, and how neural features evolve over time remain unclear. Here, we capitalized on static and dynamic EEG analysis techniques to fully uncover zolpidem-induced alterations in eight patients with DOC and constructed machine-learning models to predict long-term outcomes at the single-subject level. We observed consistent patterns of change across all patients in several static features (e.g., decreased relative theta power and weakened alpha-band functional connectivity) after zolpidem administration, albeit none zolpidem responders. Based on the current evidence, previously published electrophysiological features are not neural markers for zolpidem responders. Moreover, we found that the temporal dynamics of the brain slowed down after zolpidem intake. Brain states before and after zolpidem administration could be completely characterized by the EEG features. Furthermore, long-term outcomes were accurately predicted using connectivity features. Our findings suggest that EEG neural signatures have huge potential to assess consciousness states and predict fine-grained outcomes. In summary, our results extend the understanding of the effects of zolpidem on the brain and open avenues for the application prospect of zolpidem and EEG in patients with DOC.