A disease-specific metabolic imaging marker for diagnosis and progression evaluation of semantic variant primary progressive aphasia.

Background And Purpose: The diagnosis and monitoring of semantic variant primary progressive aphasia (sv-PPA) are clinically challenging. We aimed to establish a distinctive metabolic pattern in sv-PPA for diagnosis and severity evaluation.

Methods: Fifteen sv-PPA patients and 15 controls were enrolled to identify sv-PPA-related pattern (sv-PPARP) by principal component analysis of F-fluorodeoxyglucose positron emission tomography.

Primarily Disrupted Default Subsystems Cause Impairments in Inter-system Interactions and a Higher Regulatory Burden in Alzheimer's Disease.

Intrinsically organized large-scale brain networks and their interactions support complex cognitive function. Investigations suggest that the default network (DN) is the earliest disrupted network and that the frontoparietal control network (FPCN) and dorsal attention network (DAN) are subsequently impaired in Alzheimer's disease (AD). These large-scale networks comprise different subsystems (DN: medial temporal lobe (MTL), dorsomedial prefrontal cortex (DM) subsystems and a Core; FPCN: FPCNA and FPCNB).

White matter networks dissociate semantic control from semantic knowledge representations: Evidence from voxel-based lesion-symptom mapping.

Although semantic system is composed of two distinctive processes (i.e., semantic knowledge and semantic control), it remains unknown in which way these two processes dissociate from each other.

A unified neurocognitive model of semantics language social behaviour and face recognition in semantic dementia.

The anterior temporal lobes (ATL) have become a key brain region of interest in cognitive neuroscience founded upon neuropsychological investigations of semantic dementia (SD). The purposes of this investigation are to generate a single unified model that captures the known cognitive-behavioural variations in SD and map these to the patients' distribution of frontotemporal atrophy. Here we show that the degree of generalised semantic impairment is related to the patients' total, bilateral ATL atrophy.

White matter basis for the hub-and-spoke semantic representation: evidence from semantic dementia.

The hub-and-spoke semantic representation theory posits that semantic knowledge is processed in a neural network, which contains an amodal hub, the sensorimotor modality-specific regions, and the connections between them. The exact neural basis of the hub, regions and connectivity remains unclear. Semantic dementia could be an ideal lesion model to construct the semantic network as this disease presents both amodal and modality-specific semantic processing (e.

Neural substrates of amodal and modality-specific semantic processing within the temporal lobe: A lesion-behavior mapping study of semantic dementia.

Although the human temporal lobe has been documented to participate in semantic processing of both verbal and nonverbal stimuli, the exact neural basis underlying the common and unique processing of the two modalities is unclear. Semantic dementia (SD), a disease with a semantic-selective deficit due to predominant temporal lobe atrophy is an ideal lesion model to address this issue. However, many previous studies of SD used an impure patient sample or did not appropriately control for common components between tasks.

Multivariate Deep Learning Classification of Alzheimer's Disease Based on Hierarchical Partner Matching Independent Component Analysis.

Machine learning and pattern recognition have been widely investigated in order to look for the biomarkers of Alzheimer's disease (AD). However, most existing methods extract features by seed-based correlation, which not only requires prior information but also ignores the relationship between resting state functional magnetic resonance imaging (rs-fMRI) voxels. In this study, we proposed a deep learning classification framework with multivariate data-driven based feature extraction for automatic diagnosis of AD.

Chinese version of Montreal Cognitive Assessment Basic for discrimination among different severities of Alzheimer's disease.

Objectives: To find out whether the Chinese version of Montreal Cognitive Assessment Basic (MoCA-BC) and its subtests could be applied in discrimination among cognitively normal controls (NC), mild cognitive impairment (MCI), mild and moderate Alzheimer's Disease (AD), and furthermore, to determine the optimal cutoffs most sensitive to distinguish between them.

Design: A cross-sectional validation study.

Setting: Huashan Hospital, Shanghai, China.

The neuropsychological profiles and semantic-critical regions of right semantic dementia.

Introduction: Previous literature has revealed that the anterior temporal lobe (ATL) is the semantic hub of left-sided or mixed semantic dementia (SD), whilst the semantic hub of right-sided SD has not been examined.

Methods: Seventeen patients with right-sided SD, 18 patients with left-sided SD and 20 normal controls (NC) underwent neuropsychological assessments and magnetic resonance imaging scans. We investigated the relationship between the degree of cerebral atrophy in the whole brain and the severity of semantic deficits in left and right-sided SD samples, respectively.

Topological Alterations and Symptom-Relevant Modules in the Whole-Brain Structural Network in Semantic Dementia.

Background: Semantic dementia (SD) is characterized by a selective decline in semantic processing. Although the neuropsychological pattern of this disease has been identified, its topological global alterations and symptom-relevant modules in the whole-brain anatomical network have not been fully elucidated.

Objective: This study aims to explore the topological alteration of anatomical network in SD and reveal the modules associated with semantic deficits in this disease.

Brain Network for the Core Deficits of Semantic Dementia: A Neural Network Connectivity-Behavior Mapping Study.

Individuals with semantic dementia (SD) typically suffer from selective semantic deficits due to degenerative brain atrophy. Although some brain regions have been found to be correlated with the semantic impairments of SD patients, it is unclear if the damage is actually responsible for SD patients' semantic disorders because these findings were primarily obtained by examining the roles of local individual regions themselves without considering the influence of other regions that are functionally or structurally connected to the local individual regions. To resolve this problem, we investigated, from the brain network perspective, the relationship between the brain-network measures of regions and connections with semantic performance in 17 SD patients.

The Left Fusiform Gyrus is a Critical Region Contributing to the Core Behavioral Profile of Semantic Dementia.

Given that extensive cerebral regions are co-atrophic in semantic dementia (SD), it is not yet known which critical regions (SD-semantic-critical regions) are really responsible for the semantic deficits of SD. To identify the SD-semantic-critical regions, we explored the relationship between the degree of cerebral atrophy in the whole brain and the severity of semantic deficits in 19 individuals with SD. We found that the gray matter volumes (GMVs) of two regions [left fusiform gyrus (lFFG) and left parahippocampal gyrus (lPHG)] significantly correlated with the semantic scores of patients with SD.

Short-term delayed recall of auditory verbal learning test is equivalent to long-term delayed recall for identifying amnestic mild cognitive impairment.

Delayed recall of words in a verbal learning test is a sensitive measure for the diagnosis of amnestic mild cognitive impairment (aMCI) and early Alzheimer's disease (AD). The relative validity of different retention intervals of delayed recall has not been well characterized. Using the Auditory Verbal Learning Test-Huashan version, we compared the differentiating value of short-term delayed recall (AVL-SR, that is, a 3- to 5-minute delay time) and long-term delayed recall (AVL-LR, that is, a 20-minute delay time) in distinguishing patients with aMCI (n = 897) and mild AD (n = 530) from the healthy elderly (n = 1215).