Neural connections, providing the substrate for functional networks, exist whether or not they are functionally active at any given moment. However, it is not known to what extent brain regions are continuously interacting when the brain is ''at rest.'' In this work, we identify the major explicit activation networks by carrying out an image-based activation network analysis of thousands of separate activation maps derived from the BrainMap database of functional imaging studies, involving nearly 30,000 human subjects. Independently, we extract the major covarying networks in the resting brain, as imaged with functional magnetic resonance imaging in 36 subjects at rest. The sets of major brain networks, and their decompositions into subnetworks, show close correspondence between the independent analyses of resting and activation brain dynamics. We conclude that the full repertoire of functional networks utilized by the brain in action is continuously and dynamically ''active'' even when at ''rest.'' brain connectivity ͉ BrainMap ͉ FMRI ͉ functional connectivity ͉ resting-state networks

The APOE 4 allele is a risk factor for late-life pathological changes that is also associated with anatomical and functional brain changes in middle-aged and elderly healthy subjects. We investigated structural and functional effects of the APOE polymorphism in 18 young healthy APOE 4-carriers and 18 matched noncarriers (age range: 20 -35 years). Brain activity was studied both at rest and during an encoding memory paradigm using blood oxygen level-dependent fMRI. Resting fMRI revealed increased ''default mode network'' (involving retrosplenial, medial temporal, and medial-prefrontal cortical areas) coactivation in 4-carriers relative to noncarriers. The encoding task produced greater hippocampal activation in 4-carriers relative to noncarriers. Neither result could be explained by differences in memory performance, brain morphology, or resting cerebral blood flow. The APOE 4 allele modulates brain function decades before any clinical or neurophysiological expression of neurodegenerative processes.hippocampus ͉ memory ͉ neuroimaging ͉ resting connectivity A polipoprotein E (apoE, protein; APOE, gene) is a very-lowdensity lipoprotein that removes cholesterol from the blood and carries it to the liver for processing (1). In the central nervous system, apoE has a key role in coordinating the mobilization and redistribution of cholesterol, phospholipids, and fatty acids, and it is implicated in mechanisms such as neuronal development, brain plasticity, and repair functions (2). The human APOE gene, which is encoded on chromosome 19, has 3 allelic variants ( 2, 3, and 4). The 4 allele has been associated with a higher risk of cardiovascular disease (3), both early-onset (4) and late-onset (5) Alzheimer's disease (AD), poor outcome from traumatic brain injury (6), and age-related cognitive impairment (7).Neuroimaging studies of the APOE polymorphism in healthy subjects have largely focused on gray matter (GM) alterations in middle or late life, particularly in brain regions associated with the greatest AD pathological findings. Even in asymptomatic subjects, hippocampal and frontotemporal GM reduction has been observed in APOE 4-carriers relative to noncarriers (8). Moreover, a reduction of resting glucose metabolism was reported in young and middle-aged cognitively normal APOE 4-carriers in brain regions known to be affected by AD, including the posterior cingulate, parietal, temporal, and prefrontal cortices (9-11). fMRI task-based studies (mainly investigating memory processes) have shown greater activation in middle-aged and elderly APOE 4-carriers relative to noncarriers (12-16). Although these studies suggest an influence of the APOE 4 allele on brain structure and metabolism, they do not make clear at what age these influences initially manifest. Furthermore, although differences in structure, resting metabolism, and function have each been reported in 4-carriers relative to noncarriers, it remains to be established to what extent these characteristics interact.Thus far, reports of structural and functional eff...

The identification of resting state networks (RSNs) and the quantification of their functional connectivity in resting-state fMRI (rfMRI) are seriously hindered by the presence of artefacts, many of which overlap spatially or spectrally with RSNs. Moreover, recent developments in fMRI acquisition yield data with higher spatial and temporal resolutions, but may increase artefacts both spatially and/or temporally. Hence the correct identification and removal of non-neural fluctuations is crucial, especially in accelerated acquisitions. In this paper we investigate the effectiveness of three data-driven cleaning procedures, compare standard against higher (spatial and temporal) resolution accelerated fMRI acquisitions, and investigate the combined effect of different acquisitions and different cleanup approaches. We applied single-subject independent component analysis (ICA), followed by automatic component classification with FMRIB’s ICA-based X-noiseifier (FIX) to identify artefactual components. We then compared two first-level (within-subject) cleaning approaches for removing those artefacts and motion-related fluctuations from the data. The effectiveness of the cleaning procedures were assessed using timeseries (amplitude and spectra), network matrix and spatial map analyses. For timeseries and network analyses we also tested the effect of a second-level cleaning (informed by group-level analysis). Comparing these approaches, the preferable balance between noise removal and signal loss was achieved by regressing out of the data the full space of motion-related fluctuations and only the unique variance of the artefactual ICA components. Using similar analyses, we also investigated the effects of different cleaning approaches on data from different acquisition sequences. With the optimal cleaning procedures, functional connectivity results from accelerated data were statistically comparable or significantly better than the standard (unaccelerated) acquisition, and, crucially, with higher spatial and temporal resolution. Moreover, we were able to perform higher dimensionality ICA decompositions with the accelerated data, which is very valuable for detailed network analyses.

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The human dorsal frontal cortex has been associated with the most sophisticated aspects of cognition, including those that are thought to be especially refined in humans. Here we used diffusion-weighted magnetic resonance imaging (DW-MRI) and functional MRI (fMRI) in humans and macaques to infer and compare the organization of dorsal frontal cortex in the two species. Using DW-MRI tractographybased parcellation, we identified 10 dorsal frontal regions lying between the human inferior frontal sulcus and cingulate cortex. Patterns of functional coupling between each area and the rest of the brain were then estimated with fMRI and compared with functional coupling patterns in macaques. Areas in human medial frontal cortex, including areas associated with high-level social cognitive processes such as theory of mind, showed a surprising degree of similarity in their functional coupling patterns with the frontal pole, medial prefrontal, and dorsal prefrontal convexity in the macaque. We failed to find evidence for "new" regions in human medial frontal cortex. On the lateral surface, comparison of functional coupling patterns suggested correspondences in anatomical organization distinct from those that are widely assumed. A human region sometimes referred to as lateral frontal pole more closely resembled area 46, rather than the frontal pole, of the macaque. Overall the pattern of results suggest important similarities in frontal cortex organization in humans and other primates, even in the case of regions thought to carry out uniquely human functions. The patterns of interspecies correspondences are not, however, always those that are widely assumed.

Phantom pain after arm amputation is widely believed to arise from maladaptive cortical reorganization, triggered by loss of sensory input. We instead propose that chronic phantom pain experience drives plasticity by maintaining local cortical representations and disrupting inter-regional connectivity. Here we show that, while loss of sensory input is generally characterized by structural and functional degeneration in the deprived sensorimotor cortex, the experience of persistent pain is associated with preserved structure and functional organization in the former hand area. Furthermore, consistent with the isolated nature of phantom experience, phantom pain is associated with reduced inter-regional functional connectivity in the primary sensorimotor cortex. We therefore propose that contrary to the maladaptive model, cortical plasticity associated with phantom pain is driven by powerful and long-lasting subjective sensory experience, such as triggered by nociceptive or top–down inputs. Our results prompt a revisiting of the link between phantom pain and brain organization.

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