Primary diffuse leptomeningeal atypical teratoid/rhabdoid tumours (ATRT) of childhood: a molecularly characterised case report and literature review.

Background: Atypical teratoid/rhabdoid tumours (ATRTs) are malignant central nervous system tumours, typically presenting in the posterior fossa of very young children. Prognosis remains poor despite current therapy, while tumorigenesis implicates both genomic and epigenetic dysregulation. Primary diffuse leptomeningeal (PDL) ATRT, characterised by the absence of an intraparenchymal mass lesion, is seldom reported but appears associated with a dismal outcome.

Extracting interpretable signatures of whole-brain dynamics through systematic comparison.

The brain's complex distributed dynamics are typically quantified using a limited set of manually selected statistical properties, leaving the possibility that alternative dynamical properties may outperform those reported for a given application. Here, we address this limitation by systematically comparing diverse, interpretable features of both intra-regional activity and inter-regional functional coupling from resting-state functional magnetic resonance imaging (rs-fMRI) data, demonstrating our method using case-control comparisons of four neuropsychiatric disorders. Our findings generally support the use of linear time-series analysis techniques for rs-fMRI case-control analyses, while also identifying new ways to quantify informative dynamical fMRI structures.

A worldwide study of subcortical shape as a marker for clinical staging in Parkinson's disease.

Alterations in subcortical brain regions are linked to motor and non-motor symptoms in Parkinson's disease (PD). However, associations between clinical expression and regional morphological abnormalities of the basal ganglia, thalamus, amygdala and hippocampus are not well established. We analyzed 3D T1-weighted brain MRI and clinical data from 2525 individuals with PD and 1326 controls from 22 global sources in the ENIGMA-PD consortium.

Embracing variability in the search for biological mechanisms of psychiatric illness.

Despite decades of research, we lack objective diagnostic or prognostic biomarkers of mental health problems. A key reason for this limited progress is a reliance on the traditional case-control paradigm, which assumes that each disorder has a single cause that can be uncovered by comparing average phenotypic values of patient and control samples. Here, we discuss the problematic assumptions on which this paradigm is based and highlight recent efforts that seek to characterize, rather than minimize, the inherent clinical and biological variability that underpins psychiatric populations.

Neuroinflammation and blood-brain barrier breakdown in acute, clinical intracerebral hemorrhage.

Neuroinflammation is a promising therapeutic target in intracerebral hemorrhage (ICH), characterized in the brain by microglial activation and blood-brain barrier (BBB) breakdown. In this study, 36 acute, spontaneous, supratentorial ICH patients underwent dynamic contrast-enhanced MRI to measure BBB permeability () 1-3 days post-onset and 16 returned for [C]()-PK11195 PET to quantify microglial activation (), 2-7 days post-onset. We first tested if these markers were increased and co-localized in the perihematomal brain and found that perihematomal and were increased vs.

Evidence for biexponential glutamate T relaxation in human visual cortex at 3T: A functional MRS study.

Functional magnetic resonance spectroscopy (fMRS) measures dynamic changes in metabolite concentration in response to neural stimulation. The biophysical basis of these changes remains unclear. One hypothesis suggests that an increase or decrease in the glutamate signal detected by fMRS could be due to neurotransmitter movements between cellular compartments with different T relaxation times.

Multiscale heterogeneity of white matter morphometry in psychiatric disorders.

Background: Inter-individual variability in neurobiological and clinical characteristics in mental illness is often overlooked by classical group-mean case-control studies. Studies using normative modelling to infer person-specific deviations of grey matter volume have indicated that group means are not representative of most individuals. The extent to which this variability is present in white matter morphometry, which is integral to brain function, remains unclear.

A worldwide study of white matter microstructural alterations in people living with Parkinson's disease.

The progression of Parkinson's disease (PD) is associated with microstructural alterations in neural pathways, contributing to both motor and cognitive decline. However, conflicting findings have emerged due to the use of heterogeneous methods in small studies. Here we performed a large diffusion MRI study in PD, integrating data from 17 cohorts worldwide, to identify stage-specific profiles of white matter differences.

A network control theory pipeline for studying the dynamics of the structural connectome.

Network control theory (NCT) is a simple and powerful tool for studying how network topology informs and constrains the dynamics of a system. Compared to other structure-function coupling approaches, the strength of NCT lies in its capacity to predict the patterns of external control signals that may alter the dynamics of a system in a desired way. An interesting development for NCT in the neuroscience field is its application to study behavior and mental health symptoms.

Shaping dynamical neural computations using spatiotemporal constraints.

Dynamics play a critical role in computation. The principled evolution of states over time enables both biological and artificial networks to represent and integrate information to make decisions. In the past few decades, significant multidisciplinary progress has been made in bridging the gap between how we understand biological versus artificial computation, including how insights gained from one can translate to the other.

Extracting interpretable signatures of whole-brain dynamics through systematic comparison.

The brain's complex distributed dynamics are typically quantified using a limited set of manually selected statistical properties, leaving the possibility that alternative dynamical properties may outperform those reported for a given application. Here, we address this limitation by systematically comparing diverse, interpretable features of both intra-regional activity and inter-regional functional coupling from resting-state functional magnetic resonance imaging (rs-fMRI) data, demonstrating our method using case-control comparisons of four neuropsychiatric disorders. Our findings generally support the use of linear time-series analysis techniques for rs-fMRI case-control analyses, while also identifying new ways to quantify informative dynamical fMRI structures.

Altered Structural Connectivity and Functional Brain Dynamics in Individuals With Heavy Alcohol Use Elucidated via Network Control Theory.

Background: Heavy alcohol use and its associated conditions, such as alcohol use disorder, impact millions of individuals worldwide. While our understanding of the neurobiological correlates of alcohol use has evolved substantially, we still lack models that incorporate whole-brain neuroanatomical, functional, and pharmacological information under one framework.

Methods: Here, we utilized diffusion and functional magnetic resonance imaging to investigate alterations to brain dynamics in 130 individuals with a high amount of current alcohol use.

Recommendations for quantitative cerebral perfusion MRI using multi-timepoint arterial spin labeling: Acquisition, quantification, and clinical applications.

Accurate assessment of cerebral perfusion is vital for understanding the hemodynamic processes involved in various neurological disorders and guiding clinical decision-making. This guidelines article provides a comprehensive overview of quantitative perfusion imaging of the brain using multi-timepoint arterial spin labeling (ASL), along with recommendations for its acquisition and quantification. A major benefit of acquiring ASL data with multiple label durations and/or post-labeling delays (PLDs) is being able to account for the effect of variable arterial transit time (ATT) on quantitative perfusion values and additionally visualize the spatial pattern of ATT itself, providing valuable clinical insights.

Controlling the human connectome with spatially diffuse input signals.

The human brain is never at "rest"; its activity is constantly fluctuating over time, transitioning from one brain state-a whole-brain pattern of activity-to another. Network control theory offers a framework for understanding the effort - energy - associated with these transitions. One branch of control theory that is especially useful in this context is "optimal control", in which input signals are used to selectively drive the brain into a target state.

Altered structural connectivity and functional brain dynamics in individuals with heavy alcohol use.

Heavy alcohol use and its associated conditions, such as alcohol use disorder (AUD), impact millions of individuals worldwide. While our understanding of the neurobiological correlates of AUD has evolved substantially, we still lack models incorporating whole-brain neuroanatomical, functional, and pharmacological information under one framework. Here, we utilize diffusion and functional magnetic resonance imaging to investigate alterations to brain dynamics in = 130 individuals with a high amount of current alcohol use.

Shaping dynamical neural computations using spatiotemporal constraints.

Dynamics play a critical role in computation. The principled evolution of states over time enables both biological and artificial networks to represent and integrate information to make decisions. In the past few decades, significant multidisciplinary progress has been made in bridging the gap between how we understand biological artificial computation, including how insights gained from one can translate to the other.

Cerebellar Volume and Disease Staging in Parkinson's Disease: An ENIGMA-PD Study.

Background: Increasing evidence points to a pathophysiological role for the cerebellum in Parkinson's disease (PD). However, regional cerebellar changes associated with motor and non-motor functioning remain to be elucidated.

Objective: To quantify cross-sectional regional cerebellar lobule volumes using three dimensional T1-weighted anatomical brain magnetic resonance imaging from the global ENIGMA-PD working group.

Timing and Predictors of Loss of Infectivity Among Healthcare Workers With Mild Primary and Recurrent COVID-19: A Prospective Observational Cohort Study.

Background: There is a need to understand the duration of infectivity of primary and recurrent coronavirus disease 2019 (COVID-19) and identify predictors of loss of infectivity.

Methods: Prospective observational cohort study with serial viral culture, rapid antigen detection test (RADT) and reverse transcription polymerase chain reaction (RT-PCR) on nasopharyngeal specimens of healthcare workers with COVID-19. The primary outcome was viral culture positivity as indicative of infectivity.

Blood-brain barrier water exchange measurements using contrast-enhanced ASL.

A technique for quantifying regional blood-brain barrier (BBB) water exchange rates using contrast-enhanced arterial spin labelling (CE-ASL) is presented and evaluated in simulations and in vivo. The two-compartment ASL model describes the water exchange rate from blood to tissue, , but to estimate in practice it is necessary to separate the intra- and extravascular signals. This is challenging in standard ASL data owing to the small difference in values.

Using network control theory to study the dynamics of the structural connectome.

Network control theory (NCT) is a simple and powerful tool for studying how network topology informs and constrains dynamics. Compared to other structure-function coupling approaches, the strength of NCT lies in its capacity to predict the patterns of external control signals that may alter dynamics in a desired way. We have extensively developed and validated the application of NCT to the human structural connectome.

Alprazolam modulates persistence energy during emotion processing in first-degree relatives of individuals with schizophrenia: a network control study.

Schizophrenia is marked by deficits in facial affect processing associated with abnormalities in GABAergic circuitry, deficits also found in first-degree relatives. Facial affect processing involves a distributed network of brain regions including limbic regions like amygdala and visual processing areas like fusiform cortex. Pharmacological modulation of GABAergic circuitry using benzodiazepines like alprazolam can be useful for studying this facial affect processing network and associated GABAergic abnormalities in schizophrenia.