The default mode network (DMN) is one of the most studied resting-state networks, and is thought to be involved in the maintenance of consciousness within the alert human brain. Although many studies have examined the functional connectivity (FC) of the DMN, few have investigated its underlying structural connectivity (SC), or the relationship between the two. We investigated this question in fifteen healthy subjects, concentrating on connections to the precuneus/posterior cingulate cortex (PCC), commonly considered as the central node of the DMN. We used group independent component analysis (GICA) and seed-based correlation analysis of fMRI data to quantify FC, and streamline and probabilistic tractography to identify structural tracts from diffusion tensor imaging (DTI) data. We first assessed the presence of structural connections between the DMN regions identified with GICA. Of the 15 subjects, when using the probabilistic approach 15 (15) demonstrated connections between the PCC and mesial prefrontal cortex (mPFC), 11 (15) showed connections from the PCC to the right inferior parietal cortex (rIPC) and 8 (15) to the left IPC. Next, we assessed the strength of FC (magnitude of temporal correlation) and SC (mean fractional anisotropy of reconstructed tracts (streamline), number of super-threshold voxels within the mask region (probabilistic)). The lIPC had significantly reduced FC to the PCC compared to the mPFC and rIPC. No difference in SC strength between connections was found using the streamline approach. For the probabilistic approach, mPFC had significantly lower SC than both IPCs. The two measures of SC strength were significantly correlated, but not for all paired connections. Finally, we observed a significant correlation between SC and FC for both tractography approaches when data were pooled across PCC-lIPL, PCC-rIPL and PCC-mPFC connections, and for some individual paired connections. Our results suggest that the streamline approach is advantageous for characterising the connectivity of long white matter tracts (PCC-mPFC), whilst the probabilistic approach was more reliable at identifying PCC-IPC connections. The direct comparison of FC and SC indicated that pairs of nodes with stronger structural connections also had stronger functional connectivity, and that this was maintained with both tractography approaches. Whilst the definition of SC strength remains controversial, our results could be considered to provide some degree of validation for the measures of SC strength that we have used. Direct comparisons of SC and FC are necessary in order to understand the structural basis of functional connectivity, and to characterise and quantify the changes in the brain's functional architecture that occur as a result of normal physiology or pathology.

Insights into the functional nature and neuroanatomy of spatial attention have come from research in neglect patients but to date many conflicting results have been reported. The novelty of the current study is that we used voxel-wise analyses based on information from segmented grey and white matter tissue combined with diffusion tensor imaging to decompose neural substrates of different neglect symptoms. Allocentric neglect was associated with damage to posterior cortical regions (posterior superior temporal sulcus, angular, middle temporal and middle occipital gyri). In contrast, egocentric neglect was associated with more anterior cortical damage (middle frontal, postcentral, supramarginal, and superior temporal gyri) and damage within subcortical structures. Damage to intraparietal sulcus (IPS) and the temporo-parietal junction (TPJ) was associated with both forms of neglect. Importantly, we showed that both disorders were associated with white matter lesions suggesting damage within long association and projection pathways such as the superior longitudinal, superior fronto-occipital, inferior longitudinal, and inferior fronto-occipital fascicule, thalamic radiation, and corona radiata. We conclude that distinct cortical regions control attention (a) across space (using an egocentric frame of reference) and (b) within objects (using an allocentric frame of reference), while common cortical regions (TPJ, IPS) and common white matter pathways support interactions across the different cortical regions.

Unilateral visual neglect is commonly defined as impaired ability to attend to stimuli presented on the side of visual space contralateral to the brain lesion. However, behavioral analyses indicate that different neglect symptoms can dissociate. The neuroanatomy of the syndrome has been hotly debated. Some groups have argued that the syndrome is linked to posterior parietal cortex lesions, while others report damage within regions including the superior temporal gyrus, insula, and basal ganglia. Several recent neuroimaging studies provide evidence that heterogeneity in the behavioral symptoms of neglect can be matched by variations in the brain lesions, and that some of the discrepancies across earlier findings might have resulted from the use of different neuropsychological tests and/or varied measures within the same task for diagnosing neglect. In this paper, we review the evidence for dissociations between both the symptoms and the neural substrates of unilateral visual neglect, drawing on ALE (anatomic likelihood estimation) meta-analyses of lesion-symptom mapping studies. Specifically, we examine dissociations between neglect symptoms associated with impaired control of attention across space (in an egocentric frame of reference) and within objects (in an allocentric frame of reference). Results of ALE meta-analyses indicated that, while egocentric symptoms are associated with damage within perisylvian network (pre- and postcentral, supramarginal, and superior temporal gyri) and damage within sub-cortical structures, more posterior lesions including the angular, middle temporal, and middle occipital gyri are associated with allocentric symptoms. Furthermore, there was high concurrence in deficits associated with white matter lesions within long association (superior longitudinal, inferior fronto-occipital, and inferior longitudinal fasciculi) and projection (corona radiata and thalamic radiation) pathways, supporting a disconnection account of the syndrome. Using this evidence we argue that different forms of neglect link to both distinct and common patterns of gray and white matter lesions. The findings are discussed in terms of functional accounts of neglect and theoretical models based on computational studies of both normal and impaired attention functions.

Visuospatial attention allows us to select and act upon a subset of behaviorally relevant visual stimuli while ignoring distraction. Bundesen9s theory of visual attention (TVA) (Bundesen, 1990) offers a quantitative analysis of the different facets of attention within a unitary model and provides a powerful analytic framework for understanding individual differences in attentional functions. Visuospatial attention is contingent upon large networks, distributed across both hemispheres, consisting of several cortical areas interconnected by long-association frontoparietal pathways, including three branches of the superior longitudinal fasciculus (SLF I-III) and the inferior fronto-occipital fasciculus (IFOF). Here we examine whether structural variability within human frontoparietal networks mediates differences in attention abilities as assessed by the TVA. Structural measures were based on spherical deconvolution and tractography-derived indices of tract volume and hindrance-modulated orientational anisotropy (HMOA). Individual differences in visual short-term memory (VSTM) were linked to variability in the microstructure (HMOA) of SLF II, SLF III, and IFOF within the right hemisphere. Moreover, VSTM and speed of information processing were linked to hemispheric lateralization within the IFOF. Differences in spatial bias were mediated by both variability in microstructure and volume of the right SLF II. Our data indicate that the microstructural and macrostrucutral organization of white matter pathways differentially contributes to both the anatomical lateralization of frontoparietal attentional networks and to individual differences in attentional functions. We conclude that individual differences in VSTM capacity, processing speed, and spatial bias, as assessed by TVA, link to variability in structural organization within frontoparietal pathways.