Serine 1283 in extracellular matrix glycoprotein Reelin is crucial for Reelin′s function in brain development

Deficiency in the extracellular matrix glycoprotein Reelin severely affects migration of neurons during development. The function of serine at position 1283 in Reelin has remained uncertain. To explore its relevance we generated rlnA/A mice that carry alanine instead of serine at position 1283, thereby disrupting the putative casein kinase 2 (CK2) phosphorylation site S1283DGD. Mutated mice displayed reeler-like locomotor behavior, abnormal brain anatomy and decrease of Reelin RNA and protein levels during development and in adulthood. Since serine 1283 was previously proposed to mediate proteolysis of adhesion molecules, we investigated proteolysis of cell adhesion molecule L1 and found it normal in rlnA/A mice. Neuronal migration in the embryonic rlnA/A cerebral cortex was impaired, but rescued by in utero electroporation of the Reelin fragment N-R6 containing the putative CK2 phosphorylation site. In rlnA/A mice migration of cerebellar granule cells in vitro was promoted by application of wild-type but not by mutated Reelin. In cerebellar neuron cultures, Reelin expression was decreased upon inhibition of ecto-phosphorylation by CK2. Biochemically purified wild-type, but not mutated Reelin was found phosphorylated. Altogether, the results indicate that ecto-phosphorylation at serine 1283 rather than proteolytic processing of adhesion molecules by Reelin plays an important role in Reelin functions.

Neurodevelopmental Trajectories Following Prenatal Alcohol Exposure

Prenatal alcohol exposure (PAE) interferes with neurodevelopment. The brain is particularly susceptible to the adverse consequences of prenatal alcohol exposure, and numerous studies have documented changes to brain anatomy and function, as well as consequences for cognition, behavior, and mental health. Studies in typically developing individuals have shown that the brain undergoes dynamic developmental processes over an individual’s lifespan. Furthermore, magnetic resonance imaging (MRI) studies in other neurodevelopmental and psychiatric disorders have shown that their developmental trajectories differ from the typical pattern. Therefore, to understand long-term clinical outcomes of fetal alcohol spectrum disorders (FASD), it is necessary to investigate changes in neurodevelopmental trajectories in this population. Here we review studies that have used MRI to evaluate changes in brain structure and function over time via cross-sectional or longitudinal methods in individuals with PAE. Research demonstrates that individuals with PAE have atypical cortical and white matter microstructural developmental trajectories through childhood and adolescence. More research is needed to understand how factors such as sex and postnatal experiences may further mediate these trajectories. Furthermore, nothing is known about the trajectories beyond young adulthood.

Bremelanotide for Treatment of Female Hypoactive Sexual Desire

Hypoactive sexual desire disorder (HSDD) is a persistent deficiency or absence of sexual fantasies and desire resulting in significant distress or interpersonal difficulty. Women with this disorder may display a lack of motivation for sexual activity, reduced responsiveness to erotic cues, a loss of interest during sexual activity, and avoidance of situations that could lead to sexual activity. The pathophysiology of HSDD is thought to be centered around inhibitory and excitatory hormones, neurotransmitters, and specific brain anatomy. Due to the multifactorial nature of HSDD, treatment can be complex and must attempt to target the biological and psychosocial aspects of the disorder. Bremelanotide is a melanocortin receptor agonist and has been recently approved by the FDA to treat HSDD. Bremelanotide is administered intranasally or as a subcutaneous injection. The recommended dosage of bremelanotide is 1.75 mg injected subcutaneously in the abdomen or thigh at least 45 min before sexual activity. Studies showed improvements in desire, arousal, and orgasm scores when 1.75 mg of bremelanotide was administered before sexual activity compared to a placebo. Bremelanotide is a promising way to treat HSDD.

Prenatal and Early-Life Environmental Factors, Family Demographics and Cortical Brain Anatomy in 5-Year-Olds: An MRI Study From FinnBrain Birth Cohort

The human brain develops dynamically during early childhood, when the child is sensitive to both genetic programming and extrinsic exposures. Recent studies have found links between prenatal and early life environmental factors, family demographics and the cortical brain morphology in newborns measured by surface area, volume and thickness. Here in this magnetic resonance imaging study, we evaluated whether a similar set of variables associates with cortical surface area and volumes measured in a sample of 170 healthy 5-year-olds from the FinnBrain Birth Cohort Study. We found that child sex, maternal pre-pregnancy body mass index, 5min APGAR score, neonatal intensive care admission and maternal smoking during pregnancy associated with surface areas. Furthermore, child sex, maternal age and maternal level of education associated with brain volumes. Expectedly, many variables deemed important for neonatal brain anatomy (such as birth weight and gestational age at birth) in earlier studies did not associate with brain metrics in our study group of 5-year-olds, which implies that their effects on brain anatomy are age-specific. Future research may benefit from including pre- and perinatal covariates in the analyses when such data are available. Finally, we provide evidence for right lateralization for surface area and volumes except for the temporal lobes. These subtle differences between hemispheres are variable across individuals and may be interesting brain metrics in future studies.

A Programmable Ontology Encompassing the Functional Logic of the Drosophila Brain

The Drosophila brain has only a fraction of the number of neurons of higher organisms such as mice. Yet the sheer complexity of its neural circuits recently revealed by large connectomics datasets suggests that computationally modeling the function of fruit fly brain at this scale posits significant challenges. To address these challenges, we present here a programmable ontology that expands the scope of the current Drosophila brain anatomy ontologies to encompass the functional logic of the fly brain. The programmable ontology provides a language not only for defining functional circuit motifs but also for programmatically exploring their functional logic. To achieve this goal, we tightly integrated the programmable ontology with the workflow of the interactive FlyBrainLab computing platform. As part of the programmable ontology, we developed NeuroNLP++, a web application that supports free-form English queries for constructing functional brain circuits fully anchored on the available connectome/synaptome datasets, and the published worldwide literature. In addition, we present a methodology for including a model of the space of odorants into the programmable ontology, and for modeling olfactory sensory circuits of the antenna of the fruit fly brain that detect odorant sources. Furthermore, we describe a methodology for modeling the functional logic of the antennal lobe circuit consisting of massive local feedback loops, a characteristic feature observed across Drosophila brain regions. Finally, using a circuit library, we demonstrate the power of our methodology for interactively exploring the functional logic of the massive number of feedback loops in the antennal lobe.

New Remains of Scandiavis mikkelseni Inform Avian Phylogenetic Relationships and Brain Evolution

Although an increasing number of studies are combining skeletal and neural morphology data in a phylogenetic context, most studies do not include extinct taxa due to the rarity of preserved endocasts. The early Eocene avifauna of the Fur Formation of Denmark presents an excellent opportunity for further study of extinct osteological and endocranial morphology as fossils are often exceptionally preserved in three dimensions. Here, we use X-ray computed tomography to present additional material of the previously described taxon Scandiavis mikkelseni and reassess its phylogenetic placement using a previously published dataset. The new specimen provides novel insights into the osteological morphology and brain anatomy of Scandiavis. The virtual endocast exhibits a morphology comparable to that of modern avian species. Endocranial evaluation shows that it was remarkably similar to that of certain extant Charadriiformes, yet also possessed a novel combination of traits. This may mean that traits previously proposed to be the result of shifts in ecology later in the evolutionary history of Charadriiformes may instead show a more complex distribution in stem Charadriiformes and/or Gruiformes depending on the interrelationships of these important clades. Evaluation of skeletal and endocranial character state changes within a previously published phylogeny confirms both S. mikkelseni and a putative extinct charadriiform, Nahmavis grandei, as charadriiform. Results bolster the likelihood that both taxa are critical fossils for divergence dating and highlight a biogeographic pattern similar to that of Gruiformes.

Standard Non-Personalized Electric Field Modeling of Twenty Typical tDCS Electrode Configurations via the Computational Finite Element Method: Contributions and Limitations of Two Different Approaches

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation procedure to modulate cortical excitability and related brain functions. tDCS can effectively alter multiple brain functions in healthy humans and is suggested as a therapeutic tool in several neurological and psychiatric diseases. However, variability of results is an important limitation of this method. This variability may be due to multiple factors, including age, head and brain anatomy (including skull, skin, CSF and meninges), cognitive reserve and baseline performance level, specific task demands, as well as comorbidities in clinical settings. Different electrode montages are a further source of variability between tDCS studies. A procedure to estimate the electric field generated by specific tDCS electrode configurations, which can be helpful to adapt stimulation protocols, is the computational finite element method. This approach is useful to provide a priori modeling of the current spread and electric field intensity that will be generated according to the implemented electrode montage. Here, we present standard, non-personalized model-based electric field simulations for motor, dorsolateral prefrontal, and posterior parietal cortex stimulation according to twenty typical tDCS electrode configurations using two different current flow modeling software packages. The resulting simulated maximum intensity of the electric field, focality, and current spread were similar, but not identical, between models. The advantages and limitations of both mathematical simulations of the electric field are presented and discussed systematically, including aspects that, at present, prevent more widespread application of respective simulation approaches in the field of non-invasive brain stimulation.

Boosting the diagnostic power of amyloid-β PET using a data-driven spatially informed classifier for decision support

Background Amyloid-β (Aβ) PET has emerged as clinically useful for more accurate diagnosis of patients with cognitive decline. Aβ deposition is a necessary cause or response to the cellular pathology of Alzheimer’s disease (AD). Usual clinical and research interpretation of amyloid PET does not fully utilise all information regarding the spatial distribution of signal. We present a data-driven, spatially informed classifier to boost the diagnostic power of amyloid PET in AD. Methods Voxel-wise k-means clustering of amyloid-positive voxels was performed; clusters were mapped to brain anatomy and tested for their associations by diagnostic category and disease severity with 758 amyloid PET scans from volunteers in the AD continuum from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). A machine learning approach based on this spatially constrained model using an optimised quadratic support vector machine was developed for automatic classification of scans for AD vs non-AD pathology. Results This classifier boosted the accuracy of classification of AD scans to 81% using the amyloid PET alone with an area under the curve (AUC) of 0.91 compared to other spatial methods. This increased sensitivity to detect AD by 15% and the AUC by 9% compared to the use of a composite region of interest SUVr. Conclusions The diagnostic classification accuracy of amyloid PET was improved using an automated data-driven spatial classifier. Our classifier highlights the importance of considering the spatial variation in Aβ PET signal for optimal interpretation of scans. The algorithm now is available to be evaluated prospectively as a tool for automated clinical decision support in research settings.

Case Report: Dual Target Deep Brain Stimulation With Externalized Programming for Post-traumatic Complex Movement Disorder

Introduction: Movement disorders can be common, persistent, and debilitating sequelae of severe traumatic brain injury. Post-traumatic movement disorders are usually complex in nature, involving multiple phenomenological manifestations, and can be difficult to control with medical management alone. Deep brain stimulation (DBS) has been used to treat these challenging cases, but distorted brain anatomy secondary to trauma can complicate effective targeting. In such cases, use of diffusion tractography imaging and inpatient testing with externalized DBS leads can be beneficial in optimizing outcomes.Case Description: We present the case of a 42-year-old man with severe, disabling post-traumatic tremor who underwent bilateral, dual target DBS to the globus pallidus internus (GPi) and a combined ventral intermediate nucleus of the thalamus (Vim)/dentato-rubro-thalamic tracts (DRTT) target. DRTT fiber tracts were reconstructed preoperatively to assist in surgical targeting given the patient’s distorted anatomy. Externalization and survey of the four leads extra-operatively with inpatient testing allowed for internalization of the leads that demonstrated benefit. Six months after surgery, the patient’s tremor and dystonic burden had decreased by 67% in the performance sub-score of The Essential Tremor Rating Scale (TETRAS).Conclusion: A patient-tailored approach including target selection guided by individualized anatomy and tractography as well as extra-operative externalized lead interrogation was shown to be effective in optimizing clinical outcome in a patient with refractory post-traumatic tremor.

White matter variability, cognition, and disorders: a systematic review

Inter-individual differences can inform treatment procedures and—if accounted for—have the potential to significantly improve patient outcomes. However, when studying brain anatomy, these inter-individual variations are commonly unaccounted for, despite reports of differences in gross anatomical features, cross-sectional, and connectional anatomy. Brain connections are essential to facilitate functional organization and, when severed, cause impairments or complete loss of function. Hence, the study of cerebral white matter may be an ideal compromise to capture inter-individual variability in structure and function. We reviewed the wealth of studies that associate cognitive functions and clinical symptoms with individual tracts using diffusion tractography. Our systematic review indicates that tractography has proven to be a sensitive method in neurology, psychiatry, and healthy populations to identify variability and its functional correlates. However, the literature may be biased, as the most commonly studied tracts are not necessarily those with the highest sensitivity to cognitive functions and pathologies. Additionally, the hemisphere of the studied tract is often unreported, thus neglecting functional laterality and asymmetries. Finally, we demonstrate that tracts, as we define them, are not correlated with one, but multiple cognitive domains or pathologies. While our systematic review identified some methodological caveats, it also suggests that tract–function correlations might still be a promising tool in identifying biomarkers for precision medicine. They can characterize variations in brain anatomy, differences in functional organization, and predicts resilience and recovery in patients.