Topic: white matter

Epilepsy is one of the most common neurological diseases according to the World Health Organization (WHO) affecting around 70 million people worldwide [WHO]. Patients who suffer from epilepsy also suffer from a variety of neuro-psychiatric co-morbidities, which they can experience as crippling as the seizure condition itself. Adequate organization of cerebral white matter is utterly important for cognitive development. The failure of integration of neurologic function with cognition is reflected in neuro-psychiatric disease, such as autism spectrum disorder (ASD). However, in epilepsy we know

White matter microstructure underpins cognition and function in the human brain through the facilitation of neuronal communication, and the non-invasive characterization of this structure remains an elusive goal in the neuroscience community. Efforts to assess white matter microstructure are hampered by the sheer amount of information needed for characterization. Current techniques address this problem by representing white matter features with single scalars that are often not easy to interpret. Here, we address these issues by introducing tools from soft matter for the characterization of wh

Brain microstructure plays a key role in driving the transport of drug molecules directly administered to the brain tissue as in Convection-Enhanced Delivery procedures. This study reports the first systematic attempt to characterize the cytoarchitecture of commissural, long association and projection fiber, namely: the corpus callosum, the fornix and the corona radiata. Ovine samples from three different subjects have been imaged using scanning electron microscope combined with focused ion beam milling. Particular focus has been given to the axons. For each tract, a 3D reconstruction of relat

Network analytic methods that are ubiquitous in other areas, such as systems neuroscience, have recently been used to test network theories in psychology, including intelligence research. The network or mutualism theory of intelligence proposes that the statistical associations among cognitive abilities (e.g. specific abilities such as vocabulary or memory) stem from causal relations among them throughout development. In this study, we used network models (specifically LASSO) of cognitive abilities and brain structural covariance (grey and white matter) to simultaneously model brain-behavior r

White matter (WM) tracts shape the brain’s dynamical activity, and their damage (e.g., disconnections) results in functional alterations and cognitive symptoms [1]. Here, we use neural mass modeling to test the in-vivo effects of WM disconnections [2]. We create models of local versus global, and edge versus nodal effects of WM disconnections in a large fMRI dataset comprising individuals affected by varying degrees of white matter hyperintensities (WMH), in order to estimate the impact of WMH on brain dynamics in a data-driven manner. We use a virtual-lesioning (disconnectome [3]) approach in