Altered Connectivity Pattern of Hubs in Default-Mode Network with Alzheimer's Disease: An Granger Causality Modeling Approach

Background: Evidences from normal subjects suggest that the default-mode network (DMN) has posterior cingulate cortex (PCC), medial prefrontal cortex (MPFC) and inferior parietal cortex (IPC) as its hubs; meanwhile, these DMN nodes are often found to be abnormally recruited in Alzheimer’s disease (AD) patients. The issues on how these hubs interact to each other, with the rest nodes of the DMN and the altered pattern of hubs with respect to AD, are still on going discussion for eventual final clarification. Principal Findings: To address these issues, we investigated the causal influences between any pair of nodes within the DMN using Granger causality analysis and graph-theoretic methods on resting-state fMRI data of 12 young subjects, 16 old normal controls and 15 AD patients respectively. We found that: (1) PCC/MPFC/IPC, especially the PCC, showed the widest and distinctive causal effects on the DMN dynamics in young group; (2) the pattern of DMN hubs was abnormal in AD patients compared to old control: MPFC and IPC had obvious causal interaction disruption with other nodes; the PCC showed outstanding performance for it was the only region having causal relation with all other nodes significantly; (3) the altered relation between hubs and other DMN nodes held potential as a noninvasive biomarker of AD. Conclusions: Our study, to the best of our knowledge, is the first to support the hub configuration of the DMN from the perspective of causal relationship, and reveal abnormal pattern of the DMN hubs in AD. Findings from young subject

Network Analysis of Intrinsic Functional Brain Connectivity in Alzheimer's Disease

Functional brain networks detected in task-free (“resting-state”) functional magnetic resonance imaging (fMRI) have a small-world architecture that reflects a robust functional organization of the brain. Here, we examined whether this functional organization is disrupted in Alzheimer's disease (AD). Task-free fMRI data from 21 AD subjects and 18 age-matched controls were obtained. Wavelet analysis was applied to the fMRI data to compute frequency-dependent correlation matrices. Correlation matrices were thresholded to create 90-node undirected-graphs of functional brain networks. Small-world metrics (characteristic path length and clustering coefficient) were computed using graph analytical methods. In the low frequency interval 0.01 to 0.05 Hz, functional brain networks in controls showed small-world organization of brain activity, characterized by a high clustering coefficient and a low characteristic path length. In contrast, functional brain networks in AD showed loss of small-world properties, characterized by a significantly lower clustering coefficient (p<0.01), indicative of disrupted local connectivity. Clustering coefficients for the left and right hippocampus were significantly lower (p<0.01) in the AD group compared to the control group. Furthermore, the clustering coefficient distinguished AD participants from the controls with a sensitivity of 72% and specificity of 78%. Our study provides new evidence that there is disrupted organization of functional brain networks in AD. Small-world metrics can characterize the functional organization of the brain in AD, and our findings further suggest that these network measures may be useful as an imaging-based biomarker to distinguish AD from healthy aging

Visual Personal Familiarity in Amnestic Mild Cognitive Impairment

BACKGROUND: Patients with amnestic mild cognitive impairment are at high risk for developing Alzheimer's disease. Besides episodic memory dysfunction they show deficits in accessing contextual knowledge that further specifies a general concept or helps to identify an object or a person. METHODOLOGY/PRINCIPAL FINDINGS: Using functional magnetic resonance imaging, we investigated the neural networks associated with the perception of personal familiar faces and places in patients with amnestic mild cognitive impairment and healthy control subjects. Irrespective of stimulus type, patients compared to control subjects showed lower activity in right prefrontal brain regions when perceiving personally familiar versus unfamiliar faces and places. Both groups did not show different neural activity when perceiving faces or places irrespective of familiarity. CONCLUSIONS/SIGNIFICANCE: Our data highlight changes in a frontal cortical network associated with knowledge-based personal familiarity among patients with amnestic mild cognitive impairment. These changes could contribute to deficits in social cognition and may reduce the patients' ability to transition from basic to complex situations and tasks

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

Large-Scale Brain Networks in Board Game Experts: Insights from a Domain-Related Task and Task-Free Resting State

Cognitive performance relies on the coordination of large-scale networks of brain regions that are not only temporally correlated during different tasks, but also networks that show highly correlated spontaneous activity during a task-free state. Both task-related and task-free network activity has been associated with individual differences in cognitive performance. Therefore, we aimed to examine the influence of cognitive expertise on four networks associated with cognitive task performance: the default mode network (DMN) and three other cognitive networks (central-executive network, dorsal attention network, and salience network). During fMRI scanning, fifteen grandmaster and master level Chinese chess players (GM/M) and fifteen novice players carried out a Chinese chess task and a task-free resting state. Modulations of network activity during task were assessed, as well as resting-state functional connectivity of those networks. Relative to novices, GM/Ms showed a broader task-induced deactivation of DMN in the chess problem-solving task, and intrinsic functional connectivity of DMN was increased with a connectivity pattern associated with the caudate nucleus in GM/Ms. The three other cognitive networks did not exhibit any difference in task-evoked activation or intrinsic functional connectivity between the two groups. These findings demonstrate the effect of long-term learning and practice in cognitive expertise on large-scale brain networks, suggesting the important role of DMN deactivation in expert performance and enhanced functional integration of spontaneous activity within widely distributed DMN-caudate circuitry, which might better support high-level cognitive control of behavior

Age-related memory impairment associated with loss of parietal deactivation but preserved hippocampal activation

The neural underpinnings of age-related memory impairment remain to be fully elucidated. Using a subsequent memory face–name functional MRI (fMRI) paradigm, young and old adults showed a similar magnitude and extent of hippocampal activation during successful associative encoding. Young adults demonstrated greater deactivation (task-induced decrease in BOLD signal) in medial parietal regions during successful compared with failed encoding, whereas old adults as a group did not demonstrate a differential pattern of deactivation between trial types. The failure of deactivation was particularly evident in old adults who performed poorly on the memory task. These low-performing old adults demonstrated greater hippocampal and prefrontal activation to achieve successful encoding trials, possibly as a compensatory response. Findings suggest that successful encoding requires the coordination of neural activity in hippocampal, prefrontal, and parietal regions, and that age-related memory impairment may be primarily related to a loss of deactivation in medial parietal regions

A geopositioned and evidence-graded pan-species compendium of Mayaro virus occurrence

Mayaro Virus (MAYV) is an emerging health threat in the Americas that can cause febrile illness as well as debilitating arthralgia or arthritis. To better understand the geographic distribution of MAYV risk, we developed a georeferenced database of MAYV occurrence based on peer-reviewed literature and unpublished reports. Here we present this compendium, which includes both point and polygon locations linked to occurrence data documented from its discovery in 1954 until 2022. We describe all methods used to develop the database including data collection, georeferencing, management and quality-control. We also describe a customized grading system used to assess the quality of each study included in our review. The result is a comprehensive, evidence-graded database of confrmed MAYV occurrence in humans, non-human animals, and arthropods to-date, containing 262 geo-positioned occurrences in total. This database - which can be updated over time - may be useful for local spill-over risk assessment, epidemiological modelling to understand key transmission dynamics and drivers of MAYV spread, as well as identifcation of major surveillance gaps.Fil: Celone, Michael. Uniformed Services University of the Health Sciences; Estados UnidosFil: Potter, Alexander M.. Walter Reed Army Institute of Research,; Estados Unidos. Walter Reed Biosystematics Unit; Estados UnidosFil: Han, Barbara A.. Cary Institute of Ecosystem Studies; Estados UnidosFil: Beeman, Sean P.. Uniformed Services University of the Health Sciences; Estados UnidosFil: Okech, Bernard. Uniformed Services University of the Health Sciences; Estados UnidosFil: Forshey, Brett. Armed Forces Health Surveillance Center; Estados UnidosFil: Dunford, James. Uniformed Services University of the Health Sciences; Estados UnidosFil: Rutherford, George. University of California; Estados UnidosFil: Mita Mendoza, Neida K.. Wadsworth Center. State of New York Department of Health; Estados UnidosFil: Estallo, Elizabet Lilia. Universidad Nacional de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Biológicas y Tecnológicas. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Instituto de Investigaciones Biológicas y Tecnológicas; ArgentinaFil: Khouri, Ricardo. Instituto Gonçalo Moniz-Fiocruz; BrasilFil: de Siqueira, Isadora Cristina. Instituto Gonçalo Moniz-Fiocruz; BrasilFil: Petersen, Kyle. Uniformed Services University of the Health Sciences; Estados UnidosFil: Maves, Ryan C.. Wake Forest University School Of Medicine; Estados Unidos. Uniformed Services University of the Health Sciences; Estados UnidosFil: Anyamba, Assaf. Oak Ridge National Laboratory; Estados UnidosFil: Pollett, Simon. Henry M. Jackson Foundation for the Advancement of Military Medicine; Estados Unidos. Uniformed Services University of the Health Sciences; Estados Unido

Semantic memory activation in amnestic mild cognitive impairment

Cognitively intact older individuals at risk for developing Alzheimer's disease frequently show increased functional magnetic resonance imaging (fMRI) brain activation presumably associated with compensatory recruitment, whereas mild cognitive impairment (MCI) patients tend not to show increased activation presumably due to reduced neural reserve. Previous studies, however, have typically used episodic memory activation tasks, placing MCI participants at a performance disadvantage relative to healthy elders. In this event-related fMRI study, we employed a low effort, high accuracy semantic memory task to determine if increased activation of memory circuits is preserved in amnestic MCI when task performance is controlled. Fifty-seven participants, aged 65–85 years, comprised three groups (n = 19 each): amnestic MCI patients; cognitively intact older participants at risk for developing Alzheimer's disease based on having at least one ApoE ε4 allele and a positive family history of Alzheimer's disease (At Risk); and cognitively intact participants without Alzheimer's disease risk factors (Control). fMRI was conducted on a 3T MR scanner while participants performed a famous name discrimination task. Participants also underwent neuropsychological testing outside the scanner; whole brain and hippocampal atrophy were assessed from anatomical MRI scans. The three groups did not differ on demographic variables or on fame discrimination performance (>87% correct for all groups). As expected, the amnestic MCI participants demonstrated reduced episodic memory performance. Spatial extent of activation (Fame—Unfamiliar subtraction) differentiated the three groups (Control = 0 ml, At Risk = 9.7 ml, MCI = 34.7 ml). The MCI and At Risk groups showed significantly greater per cent signal change than Control participants in 8 of 14 functionally defined regions, including the medial temporal lobe, temporoparietal junction, and posterior cingulate/precuneus. MCI participants also showed greater activation than Controls in two frontal regions. At Risk, but not MCI, participants showed increased activity in the left hippocampal complex; MCI participants, however, evidenced increased activity in this region when hippocampal atrophy was controlled. When performance is equated, MCI patients demonstrate functional compensation in brain regions subserving semantic memory systems that generally equals or exceeds that observed in cognitively intact individuals at risk for Alzheimer's disease. This hyperactivation profile in MCI is even observed in the left hippocampal complex, but only when the extent of hippocampal atrophy is taken into consideration