Association between resting-state functional connectivity, glucose metabolism and task-related activity of neural networks

The brain is organized into several large-scale functional networks. Such networks are primarily characterized by intrinsic functional connectivity, i.e. temporally synchronous activity between the different brain regions of a network. The functional connectivity of networks can be identified via functional MRI during resting state, i.e. without engaging the subject in a particular task. Resting-state fMRI is thus less demanding on the subject and therefore of particular interest from a clinical point of view to detect alterations in brain function. Applied to neurodegenerative disease including Alzheimer’s disease, resting-state fMRI has shown alterations in several resting-state networks, suggesting that basic network function is altered in AD. However, the interpretation of alterations in resting-state fMRI connectivity is inherently limited since no cognitive states are explicitly expressed during fMRI. In this regard, we aimed to elucidate how resting-state fMRI connectivity relates to 1) cognition-related brain activity and 2) markers of pathologically altered brain function in AD. In order to understand at a more basic level the association between resting-state and task-related fMRI, we first examined, in a group of elderly healthy subjects, the association between functional connectivity of major networks assessed during resting-state fMRI with those acquired during memory-task related fMRI, in the same individuals. Secondly, in order to assess whether alterations in AD are associated with already well-established markers of pathological brain function in AD, we compared resting-state fMRI functional network connectivity with that in FDG-PET metabolism in AD. Project 1: We investigated the association between functional connectivity acquired during rest and the level of activation obtained during an episodic memory task that included the encoding and forced-choice recognition of face-name pairs in elderly cognitively normal subjects. Independent component analysis (ICA) was used to identify major resting-state networks in the brain. Next, we applied ICA to the task-fMRI data to determine the components (networks) that were significantly associated with the task regressors of successful vs unsuccessful learning or recognition trials. Spatial correlation analysis between the resulting extracted resting-state and task-related fMRI components showed a spatial match in several components such as medial temporal lobe centered components and posterior components. However, apart from the spatial correspondence, the level of resting state functional connectivity did not predict the level of task-related functional connectivity in spatially matching components. Together these results suggested that particular resting-state networks are activated during a memory task, however, the level of baseline connectivity does not predict to what extent a network becomes activated during a task. Future studies may assess whether pathological resting-state connectivity predicts altered task-related connectivity in the same networks in AD. Project 2: We examined the association between resting-state fMRI functional connectivity within major functional networks and FDG-PET metabolism in those networks, assessed in elderly healthy controls, subjects with prodromal AD (mild cognitive impairment and amyloid PET biomarker confirmed AD etiology) and AD dementia. We found that FDG-PET was generally reduced in all networks in the course of AD. The main finding was that lower network functional connectivity was associated with lower FDG-PET uptake in the Default mode network and fronto-parietal attention network across the whole group and specifically in prodromal AD, suggesting that both modalities are associated in higher networks affected in the course of AD. These results provide insightful comprehension of the hypometabolism patterns that are typically found in AD

Association between resting-state functional connectivity, glucose metabolism and task-related activity of neural networks

The brain is organized into several large-scale functional networks. Such networks are primarily characterized by intrinsic functional connectivity, i.e. temporally synchronous activity between the different brain regions of a network. The functional connectivity of networks can be identified via functional MRI during resting state, i.e. without engaging the subject in a particular task. Resting-state fMRI is thus less demanding on the subject and therefore of particular interest from a clinical point of view to detect alterations in brain function. Applied to neurodegenerative disease including Alzheimer’s disease, resting-state fMRI has shown alterations in several resting-state networks, suggesting that basic network function is altered in AD. However, the interpretation of alterations in resting-state fMRI connectivity is inherently limited since no cognitive states are explicitly expressed during fMRI. In this regard, we aimed to elucidate how resting-state fMRI connectivity relates to 1) cognition-related brain activity and 2) markers of pathologically altered brain function in AD. In order to understand at a more basic level the association between resting-state and task-related fMRI, we first examined, in a group of elderly healthy subjects, the association between functional connectivity of major networks assessed during resting-state fMRI with those acquired during memory-task related fMRI, in the same individuals. Secondly, in order to assess whether alterations in AD are associated with already well-established markers of pathological brain function in AD, we compared resting-state fMRI functional network connectivity with that in FDG-PET metabolism in AD. Project 1: We investigated the association between functional connectivity acquired during rest and the level of activation obtained during an episodic memory task that included the encoding and forced-choice recognition of face-name pairs in elderly cognitively normal subjects. Independent component analysis (ICA) was used to identify major resting-state networks in the brain. Next, we applied ICA to the task-fMRI data to determine the components (networks) that were significantly associated with the task regressors of successful vs unsuccessful learning or recognition trials. Spatial correlation analysis between the resulting extracted resting-state and task-related fMRI components showed a spatial match in several components such as medial temporal lobe centered components and posterior components. However, apart from the spatial correspondence, the level of resting state functional connectivity did not predict the level of task-related functional connectivity in spatially matching components. Together these results suggested that particular resting-state networks are activated during a memory task, however, the level of baseline connectivity does not predict to what extent a network becomes activated during a task. Future studies may assess whether pathological resting-state connectivity predicts altered task-related connectivity in the same networks in AD. Project 2: We examined the association between resting-state fMRI functional connectivity within major functional networks and FDG-PET metabolism in those networks, assessed in elderly healthy controls, subjects with prodromal AD (mild cognitive impairment and amyloid PET biomarker confirmed AD etiology) and AD dementia. We found that FDG-PET was generally reduced in all networks in the course of AD. The main finding was that lower network functional connectivity was associated with lower FDG-PET uptake in the Default mode network and fronto-parietal attention network across the whole group and specifically in prodromal AD, suggesting that both modalities are associated in higher networks affected in the course of AD. These results provide insightful comprehension of the hypometabolism patterns that are typically found in AD

Correspondence Between Resting-State and Episodic Memory-Task Related Networks in Elderly Subjects

Resting-state fMRI studies demonstrated temporally synchronous fluctuations in brain activity among ensembles of brain regions, suggesting the existence of intrinsic functional networks. A spatial match between some of the resting-state networks and regional brain activation during cognitive tasks has been noted, suggesting that resting-state networks support particular cognitive abilities. However, the spatial match and predictive value of any resting-state network and regional brain activation during episodic memory is only poorly understood. In order to address this research gap, we obtained fMRI acquired both during rest and a face-name association task in 38 healthy elderly subjects. In separate independent component analyses, networks of correlated brain activity during rest or the episodic memory task were identified. For the independent components identified for task-based fMRI, the design matrix of successful encoding or retrieval trials was regressed against the time course of each of the component to identify significantly activated networks. Spatial regression was used to assess the match of resting-state networks against those related to successful memory encoding or retrieval. We found that resting-state networks covering the medial temporal, middle temporal, and frontal areas showed increased activity during successful encoding. Resting-state networks located within posterior brain regions showed increased activity during successful recognition. However, the level of resting-state network connectivity was not predictive of the task-related activity in these networks. These results suggest that a circumscribed number of functional networks detectable during rest become engaged during successful episodic memory. However, higher intrinsic connectivity at rest may not translate into higher network expression during episodic memory

The left frontal cortex supports reserve in aging by enhancing functional network efficiency

Background: Recent evidence from fMRI studies suggests that functional hubs, i.e. highly connected brain regions, are important for mental health. We found recently that global connectivity of a hub in the left frontal cortex (LFC-connectivity) is associated with relatively preserved memory abilities and higher levels of protective factors (education, IQ) in normal aging and Alzheimer’s disease. These results suggest that LFC-connectivity supports reserve capacity alleviating memory decline. An open question is, however, why LFC-connectivity is beneficial and supports memory function in the face of neurodegeneration. We hypothesized that higher LFCconnectivity is associated with enhanced efficiency in connected major networks involved in episodic memory. We further hypothesized that higher LFC-related network efficiency predicts higher memory abilities. Methods: We assessed fMRI during a face-name association learning task in 26 healthy cognitively normal elderly participants. Using beta-series correlation analysis, we computed task-related LFC-connectivity to key memory networks including the default-mode network (DMN) and dorsal attention network (DAN). Network efficiency within the DMN and DAN was estimated by the graph theoretical small-worldness statistic. We applied linear regression analyses in order to test the association between LFC-connectivity to the DMN/DAN and small-worldness of these networks. Mediation analysis was applied to test LFC-connectivity to the DMN and DAN as a mediator of the association between education and higher DMN and DAN smallworldness. Lastly, we tested network small-worldness as a predictor of memory performance. Results: We found that higher LFC-connectivity to the DMN and DAN during successful memory encoding and recognition was associated with higher small-worldness of those networks. Higher task-related LFC-connectivity mediated the association between education and higher small-worldness in the DMN and DAN. Further, higher small-worldness of these networks predicted better performance in the memory task. Conclusions: The current results suggest that higher education-related LFC-connectivity to key memory networks during a memory task is associated with higher network efficiency and thus enhanced reserve of memory abilities in aging

Tract-specific white matter hyperintensities disrupt neural network function in Alzheimer's disease

Introduction: White matter hyperintensities (WMHs) increase the risk of Alzheimer's disease (AD). Whether WMHs are associated with the decline of functional neural networks in AD is debated. Method: Resting-state functional magnetic resonance imaging and WMH were assessed in 78 subjects with increased amyloid levels on AV-45 positron emission tomography (PET) in different clinical stages of AD. We tested the association between WMH volume in major atlas-based fiber tract regions of interest (ROIs) and changes in functional connectivity (FC) between the tracts' projection areas within the default mode network (DMN). Results: WMH volume within the inferior fronto-occipital fasciculus (IFOF) was the highest among all tract ROIs and associated with reduced FC in IFOF-connected DMN areas, independently of global AV-45 PET. Higher AV-45 PET contributed to reduced FC in IFOF-connected, temporal, and parietal DMN areas. Conclusions: High fiber tract WMH burden is associated with reduced FC in connected areas, thus adding to the effects of amyloid pathology on neuronal network function

Resting-State Connectivity of the Left Frontal Cortex to the Default Mode and Dorsal Attention Network Supports Reserve in Mild Cognitive Impairment

Reserve refers to the phenomenon of relatively preserved cognition in disproportion to the extent of neuropathology, e.g., in Alzheimer’s disease. A putative functional neural substrate underlying reserve is global functional connectivity of the left lateral frontal cortex (LFC, Brodmann Area 6/44). Resting-state fMRI-assessed global LFC-connectivity is associated with protective factors (education) and better maintenance of memory in mild cognitive impairment (MCI). Since the LFC is a hub of the fronto-parietal control network that regulates the activity of other networks, the question arises whether LFC-connectivity to specific networks rather than the whole-brain may underlie reserve. We assessed resting-state fMRI in 24 MCI and 16 healthy controls (HC) and in an independent validation sample (23 MCI/32 HC). Seed-based LFC-connectivity to seven major resting-state networks (i.e., fronto-parietal, limbic, dorsal-attention, somatomotor, default-mode, ventral-attention, visual) was computed, reserve was quantified as residualized memory performance after accounting for age and hippocampal atrophy. In both samples of MCI, LFC-activity was anti-correlated with the default-mode network (DMN), but positively correlated with the dorsal-attention network (DAN). Greater education predicted stronger LFC-DMN-connectivity (anti-correlation) and LFC-DAN-connectivity. Stronger LFC-DMN and LFC-DAN-connectivity each predicted higher reserve, consistently in both MCI samples. No associations were detected for LFC-connectivity to other networks. These novel results extend our previous findings on global functional connectivity of the LFC, showing that LFC-connectivity specifically to the DAN and DMN, two core memory networks, enhances reserve in the memory domain in MCI

Enhanced resting-state functional connectivity between core memory-task activation peaks is associated with memory impairment in MCI

Resting-state functional connectivity (FC) is altered in Alzheimer's disease (AD) but its predictive value for episodic memory impairment is debated. Here, we aimed to assess whether resting-state FC in core brain regions activated during memory-task functional magnetic resonance imaging is altered and predictive of memory performance in AD and amnestic mild cognitive impairment (aMCI). Twenty-three elderly cognitively healthy controls (HC), 76 aMCI subjects, and 19 AD dementia patients were included. We computed resting-state FC between 18 meta-analytically determined peak coordinates of brain activation during successful memory retrieval. Higher FC between the parahippocampus, parietal cortex, and the middle frontal gyrus was observed in both AD and mild cognitive impairment compared to HC (false-discovery rate—corrected p < 0.05). The increase in FC between the parahippocampus and middle frontal gyrus was associated with reduced episodic memory in aMCI, independent of amyloid-beta positron emission tomography binding and apolipoprotein E ε4-carrier status. In conclusion, increased parahippocampal-prefrontal FC is predictive of impaired episodic memory in aMCI and may reflect a dysfunctional change within the episodic memory–related neural network

Additional file 1: Table S1. of Melanoma genome evolution across species

ZMEL1 whole-genome sequencing. This file contains all of the mutations called by MuTect and Shimmer, along with their associated quality scores and overlapping mutations. (XLSX 6276 kb

Additional file 4: Table S4. of Melanoma genome evolution across species

ZMELR1 vs. ZMEL1 mRNA differential expression. This file contains the differentially expressed genes from RNA-seq of the ZMEL1 line vs. the ZMELR1 line. (XLSX 3569 kb