The divided brain : Functional brain asymmetry underlying self-construal

Acknowledgments This research is partly supported by the National Natural Science Foundation of China (62071049, 61801026) & Capital Medical University Advanced Innovation Center for Big Data-Based Precision Medicine Plan (BHME-201907), and the Leverhulme Trust (RPG-2019-010).Peer reviewedPublisher PD

Resolving Structure in Human Brain Organization: Identifying Mesoscale Organization in Weighted Network Representations

Human brain anatomy and function display a combination of modular and hierarchical organization, suggesting the importance of both cohesive structures and variable resolutions in the facilitation of healthy cognitive processes. However, tools to simultaneously probe these features of brain architecture require further development. We propose and apply a set of methods to extract cohesive structures in network representations of brain connectivity using multi-resolution techniques. We employ a combination of soft thresholding, windowed thresholding, and resolution in community detection, that enable us to identify and isolate structures associated with different weights. One such mesoscale structure is bipartivity, which quantifies the extent to which the brain is divided into two partitions with high connectivity between partitions and low connectivity within partitions. A second, complementary mesoscale structure is modularity, which quantifies the extent to which the brain is divided into multiple communities with strong connectivity within each community and weak connectivity between communities. Our methods lead to multi-resolution curves of these network diagnostics over a range of spatial, geometric, and structural scales. For statistical comparison, we contrast our results with those obtained for several benchmark null models. Our work demonstrates that multi-resolution diagnostic curves capture complex organizational profiles in weighted graphs. We apply these methods to the identification of resolution-specific characteristics of healthy weighted graph architecture and altered connectivity profiles in psychiatric disease.Comment: Comments welcom

Alzheimer and vascular brain diseases: Focal and diffuse subforms.

Alois Alzheimer is best known for his description of the pre-senile neurodegenerative disease named after him. However, his previous interest in vascular brain diseases, underlying cognitive and behavioral changes, was very strong. Besides describing the Arteriosclerotic atrophy of the brain and the arteriosclerotic subtype of Senile dementia which he viewed as main forms of vascular brain diseases, he also identified and described a series of conditions he considered subforms. These may be divided, as suggested by the authors of the present paper, into 3 groups: gliosis and sclerosis, subcortical atrophies, and apoplectic. The subforms of the three groups present characteristic neuropathological features and clinical, cognitive and behavioral manifestations. These provide the basis, together with part of the main forms, for the contemporary condition known as Vascular Cognitive Impairment

Brain switch mode: an alternative to drive a brain-controlled wheelchair

To date, different control paradigms of low level navigation have been tested for brain-controlled wheelchairs, mainly divided into continuous or discrete control [1]. However, these paradigms have certain drawbacks such as the need to keep the mental tasks active for a long time, as in continuous mode, or the impossibility to freely choose any distance of the movement or the turn, as in the discrete mode. An alternative paradigm to solve these problems could be the use of the brain switch mode [2], which would allow a more flexible control of the distance, requiring a lower workload for the user.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech