Divergent network connectivity changes in behavioural variant frontotemporal dementia and Alzheimer’s disease

Abstract

Resting-state or intrinsic connectivity network functional magnetic resonance imaging provides a new tool for mapping large-scale neural network function and dysfunction. Recently, we showed that behavioural variant frontotemporal dementia and Alzheimer's disease cause atrophy within two major networks, an anterior 'Salience Network' (atrophied in behavioural variant frontotemporal dementia) and a posterior 'Default Mode Network' (atrophied in Alzheimer's disease). These networks exhibit an anti-correlated relationship with each other in the healthy brain. The two diseases also feature divergent symptom-deficit profiles, with behavioural variant frontotemporal dementia undermining social-emotional function and preserving or enhancing visuospatial skills, and Alzheimer's disease showing the inverse pattern. We hypothesized that these disorders would exert opposing connectivity effects within the Salience Network (disrupted in behavioural variant frontotemporal dementia but enhanced in Alzheimer's disease) and the Default Mode Network (disrupted in Alzheimer's disease but enhanced in behavioural variant frontotemporal dementia). With task-free functional magnetic resonance imaging, we tested these ideas in behavioural variant frontotemporal dementia, Alzheimer's disease and healthy age-matched controls (n = 12 per group), using independent component analyses to generate group-level network contrasts. As predicted, behavioural variant frontotemporal dementia attenuated Salience Network connectivity, most notably in frontoinsular, cingulate, striatal, thalamic and brainstem nodes, but enhanced connectivity within the Default Mode Network. Alzheimer's disease, in contrast, reduced Default Mode Network connectivity to posterior hippocampus, medial cingulo-parieto-occipital regions and the dorsal raphe nucleus, but intensified Salience Network connectivity. Specific regions of connectivity disruption within each targeted network predicted intrinsic connectivity enhancement within the reciprocal network. In behavioural variant frontotemporal dementia, clinical severity correlated with loss of right frontoinsular Salience Network connectivity and with biparietal Default Mode Network connectivity enhancement. Based on these results, we explored whether a combined index of Salience Network and Default Mode Network connectivity might discriminate between the three groups. Linear discriminant analysis achieved 92% clinical classification accuracy, including 100% separation of behavioural variant frontotemporal dementia and Alzheimer's disease. Patients whose clinical diagnoses were supported by molecular imaging, genetics, or pathology showed 100% separation using this method, including four diagnostically equivocal 'test' patients not used to train the algorithm. Overall, the findings suggest that behavioural variant frontotemporal dementia and Alzheimer's disease lead to divergent network connectivity patterns, consistent with known reciprocal network interactions and the strength and deficit profiles of the two disorders. ...

Spontaneous brain activity observed with functional magnetic resonance imaging as a potential biomarker in neuropsychiatric disorders

“…Different types of properties, such as local spontaneous activity (ReHo), local network (DMN and/or its anti-correlated network), and whole brain network, derived from SLFF have been taken as features to discriminate patients from normal controls (Table 4). In general, both the sensitivity and specificity of these studies has been above 80% (Greicius et al 2004;Song et al 2006;Wang et al 2006a;Calhoun et al 2008a;Shi et al 2007;Shen et al 2010;Zhou et al 2010), suggesting that the activity patterns of SLFF have the potential to become brain imaging biomarkers to improve the sensitivity and specificity of the current clinical diagnosis of neuropsychiatric disorders. And compared to task-related fMRI, the SLFF within the resting-state network may be more effective at identifying functional pathology associated with AD risk (Fleisher et al 2009).…”

Heightened emotional contagion in mild cognitive impairment and Alzheimer’s disease is associated with temporal lobe degeneration

“…Individuals with MCI who have comorbid emotional complaints are more likely to progress to dementia than those without such symptoms (9)(10)(11)(12)(13). Taken together, these studies suggest that a clinical presentation that includes both cognitive decline and emotion dysregulation may point to an underlying AD process and that emotional symptoms themselves may portend or even exacerbate disease progression (9,11,14).…”

“…Individuals with MCI who have comorbid emotional complaints are more likely to progress to dementia than those without such symptoms (9-13). Taken together, these studies suggest that a clinical presentation that includes both cognitive decline and emotion dysregulation may point to an underlying AD process and that emotional symptoms themselves may portend or even exacerbate disease progression (9,11,14).The medial temporal lobe is among the earliest sites of disease in MCI and AD (2, 15), and hippocampal atrophy is associated with worse episodic memory performance on standardized neuropsychological testing (16) and predicts conversion from MCI to AD (17). Similarly, functional imaging studies reveal diminished intrinsic connectivity, the degree to which distributed brain structures fluctuate in synchrony in the absence of a structured task, in the default mode network in MCI and AD (18,19).…”

Aging and large-scale functional networks: White matter integrity, gray matter volume, and functional connectivity in the resting state

“…In addition, an emerging view suggests that cognitive performance in general might rely on the dynamic interaction between the DMN and two other large-scale neural networks: the fronto-parietal task-positive network (FPN), which is associated with attention and cognitive control, and the salience network (SN) in anterior cingulate and fronto-insular cortex, which is involved in the selection of emotionally and motivationally relevant stimuli (Andrews-Hanna et al, 2014;Chen et al, 2013;Fox et al, 2005;Seeley et al, 2007;Sridharan et al, 2008;Spreng et al, 2013). These three neural networks are central to cognition, as they are engaged in a large number of functions, and their disruption has been associated with a variety of clinical syndromes, such as schizophrenia, traumatic brain injury, and Alzheimer's disease (Manoliu et al, 2014;Sharp et al, 2014;Zhou et al, 2010). In addition, evidence suggests that the disruption of the dynamic coordination of these large-scale networks constitutes one of the main causes of cognitive decline associated with ageing (Andrews-Hanna et al, 2007;Sambataro et al, 2010), as shown by reduced neural activity in the DMN and SN at rest (Allen et al, 2011;Onoda et al, 2012) and RESTING STATE NETWORKS IN THE AGEING BRAIN 4 increased activity in the FPN of older adults during visual tasks .…”