Progress toward standardized diagnosis of vascular cognitive impairment: Guidelines from the Vascular Impairment of Cognition Classification Consensus Study

INTRODUCTION: Progress in understanding and management of vascular cognitive impairment (VCI) has been hampered by lack of consensus on diagnosis, reflecting the use of multiple different assessment protocols. A large multinational group of clinicians and researchers participated in a two-phase Vascular Impairment of Cognition Classification Consensus Study (VICCCS) to agree on principles (VICCCS-1) and protocols (VICCCS-2) for diagnosis of VCI. We present VICCCS-2. METHODS: We used VICCCS-1 principles and published diagnostic guidelines as points of reference for an online Delphi survey aimed at achieving consensus on clinical diagnosis of VCI. RESULTS: Six survey rounds comprising 65-79 participants agreed guidelines for diagnosis of VICCCS-revised mild and major forms of VCI and endorsed the National Institute of Neurological Disorders-Canadian Stroke Network neuropsychological assessment protocols and recommendations for imaging. DISCUSSION: The VICCCS-2 suggests standardized use of the National Institute of Neurological Disorders-Canadian Stroke Network recommendations on neuropsychological and imaging assessment for diagnosis of VCI so as to promote research collaboration

Resting-State Multi-Spectrum Functional Connectivity Networks for Identification of MCI Patients

In this paper, a high-dimensional pattern classification framework, based on functional associations between brain regions during resting-state, is proposed to accurately identify MCI individuals from subjects who experience normal aging. The proposed technique employs multi-spectrum networks to characterize the complex yet subtle blood oxygenation level dependent (BOLD) signal changes caused by pathological attacks. The utilization of multi-spectrum networks in identifying MCI individuals is motivated by the inherent frequency-specific properties of BOLD spectrum. It is believed that frequency specific information extracted from different spectra may delineate the complex yet subtle variations of BOLD signals more effectively. In the proposed technique, regional mean time series of each region-of-interest (ROI) is band-pass filtered ( Hz) before it is decomposed into five frequency sub-bands. Five connectivity networks are constructed, one from each frequency sub-band. Clustering coefficient of each ROI in relation to the other ROIs are extracted as features for classification. Classification accuracy was evaluated via leave-one-out cross-validation to ensure generalization of performance. The classification accuracy obtained by this approach is 86.5%, which is an increase of at least 18.9% from the conventional full-spectrum methods. A cross-validation estimation of the generalization performance shows an area of 0.863 under the receiver operating characteristic (ROC) curve, indicating good diagnostic power. It was also found that, based on the selected features, portions of the prefrontal cortex, orbitofrontal cortex, temporal lobe, and parietal lobe regions provided the most discriminant information for classification, in line with results reported in previous studies. Analysis on individual frequency sub-bands demonstrated that different sub-bands contribute differently to classification, providing extra evidence regarding frequency-specific distribution of BOLD signals. Our MCI classification framework, which allows accurate early detection of functional brain abnormalities, makes an important positive contribution to the treatment management of potential AD patients

Neuropsychology Central

Neuropsychology Central is devoted to the subject of - "Neuropsychology, a new branch of science with the specific and unique aim of investigating the role of individual brain systems in complex forms of mental activity." - A.R. Luria "The Working Brain" The page aims to describe the importance of neuropsychology as a science of brain and behavior, and to act as a resource for the professional and layperson alike. See links to current technology for brain imaging, and sections covering different aspects of this ever growing field such as cognitive, developmental, and geriatric Neuropsychology. In addition, a reader survey is included to facilitate the expansion of the site

State of the clinical science of perioperative brain health: report from the American Society of Anesthesiologists Brain Health Initiative Summit 2018

Cognitive recovery after anaesthesia and surgery is a concern for older adults, their families, and caregivers. Reports of patients who were ‘never the same’ prompted a scientific inquiry into the nature of what patients have experienced. In June 2018, the ASA Brain Health Initiative held a summit to discuss the state of the science on perioperative cognition, and to create an implementation plan for patients and providers leveraging the current evidence. This group included representatives from the AARP (formerly the American Association of Retired Persons), American College of Surgeons, American Heart Association, and Alzheimer's Association Perioperative Cognition and Delirium Professional Interest Area. This paper summarises the state of the relevant clinical science, including risk factors, identification and diagnosis, prognosis, disparities, outcomes, and treatment of perioperative neurocognitive disorders. Finally, we discuss gaps in current knowledge with suggestions for future directions and opportunities for clinical and translational projects