Brent Winslow

Bio: Brent Winslow is an academic researcher from University of Utah. The author has contributed to research in topics: Mental health & Medicine. The author has an hindex of 8, co-authored 18 publications receiving 2174 citations. Previous affiliations of Brent Winslow include Allen Institute for Brain Science.

A mesoscale connectome of the mouse brain

Abstract: Comprehensive knowledge of the brain's wiring diagram is fundamental for understanding how the nervous system processes information at both local and global scales. However, with the singular exception of the C. elegans microscale connectome, there are no complete connectivity data sets in other species. Here we report a brain-wide, cellular-level, mesoscale connectome for the mouse. The Allen Mouse Brain Connectivity Atlas uses enhanced green fluorescent protein (EGFP)-expressing adeno-associated viral vectors to trace axonal projections from defined regions and cell types, and high-throughput serial two-photon tomography to image the EGFP-labelled axons throughout the brain. This systematic and standardized approach allows spatial registration of individual experiments into a common three dimensional (3D) reference space, resulting in a whole-brain connectivity matrix. A computational model yields insights into connectional strength distribution, symmetry and other network properties. Virtual tractography illustrates 3D topography among interconnected regions. Cortico-thalamic pathway analysis demonstrates segregation and integration of parallel pathways. The Allen Mouse Brain Connectivity Atlas is a freely available, foundational resource for structural and functional investigations into the neural circuits that support behavioural and cognitive processes in health and disease.

The challenge of integrating devices into the central nervous system.

Abstract: Implanted biomedical devices are playing an increasingly important role in the treatment of central nervous system disorders. While devices such as deep brain stimulation electrodes and drug delivery systems have shown clinical success in chronic applications, other devices such as nerve guidance substrates and recording electrodes that operate over a very short length scale have not had the same kind of clinical impact. By reviewing what is currently known about the brain tissue response to implanted electrodes, the authors propose that the foreign-body response, which changes the tissue structure immediately surrounding implanted devices, may be the reason near-function devices are stalled in preclinical development. The article concludes by reviewing recent efforts to reduce the foreign body response, which shows promise to accelerate the clinical development of this new generation of biomedical devices.

Mussel-Inspired Adhesives and Coatings

Abstract: Mussels attach to solid surfaces in the sea. Their adhesion must be rapid, strong, and tough, or else they will be dislodged and dashed to pieces by the next incoming wave. Given the dearth of synthetic adhesives for wet polar surfaces, much effort has been directed to characterizing and mimicking essential features of the adhesive chemistry practiced by mussels. Studies of these organisms have uncovered important adaptive strategies that help to circumvent the high dielectric and solvation properties of water that typically frustrate adhesion. In a chemical vein, the adhesive proteins of mussels are heavily decorated with Dopa, a catecholic functionality. Various synthetic polymers have been functionalized with catechols to provide diverse adhesive, sealant, coating, and anchoring properties, particularly for critical biomedical applications.

The connectomics of brain disorders

Abstract: Pathological perturbations of the brain are rarely confined to a single locus; instead, they often spread via axonal pathways to influence other regions. Patterns of such disease propagation are constrained by the extraordinarily complex, yet highly organized, topology of the underlying neural architecture; the so-called connectome. Thus, network organization fundamentally influences brain disease, and a connectomic approach grounded in network science is integral to understanding neuropathology. Here, we consider how brain-network topology shapes neural responses to damage, highlighting key maladaptive processes (such as diaschisis, transneuronal degeneration and dedifferentiation), and the resources (including degeneracy and reserve) and processes (such as compensation) that enable adaptation. We then show how knowledge of network topology allows us not only to describe pathological processes but also to generate predictive models of the spread and functional consequences of brain disease.

Shared and distinct transcriptomic cell types across neocortical areas

Abstract: The neocortex contains a multitude of cell types that are segregated into layers and functionally distinct areas. To investigate the diversity of cell types across the mouse neocortex, here we analysed 23,822 cells from two areas at distant poles of the mouse neocortex: the primary visual cortex and the anterior lateral motor cortex. We define 133 transcriptomic cell types by deep, single-cell RNA sequencing. Nearly all types of GABA (γ-aminobutyric acid)-containing neurons are shared across both areas, whereas most types of glutamatergic neurons were found in one of the two areas. By combining single-cell RNA sequencing and retrograde labelling, we match transcriptomic types of glutamatergic neurons to their long-range projection specificity. Our study establishes a combined transcriptomic and projectional taxonomy of cortical cell types from functionally distinct areas of the adult mouse cortex.

Modular Brain Networks

Abstract: The development of new technologies for mapping structural and functional brain connectivity has led to the creation of comprehensive network maps of neuronal circuits and systems. The architecture of these brain networks can be examined and analyzed with a large variety of graph theory tools. Methods for detecting modules, or network communities, are of particular interest because they uncover major building blocks or subnetworks that are particularly densely connected, often corresponding to specialized functional components. A large number of methods for community detection have become available and are now widely applied in network neuroscience. This article first surveys a number of these methods, with an emphasis on their advantages and shortcomings; then it summarizes major findings on the existence of modules in both structural and functional brain networks and briefly considers their potential functional roles in brain evolution, wiring minimization, and the emergence of functional specialization...