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Information processing in the human brain arises from both interactions between adjacent areas and from distant projections that form distributed brain systems. Here we map interactions across different spatial scales by estimating the degree of intrinsic functional connectivity for the local (14 mm) interactions. The balance between local and distant functional interactions measured at rest forms a map that separates sensorimotor cortices from heteromodal association areas and further identifies regions that possess both high local and distant cortical-cortical interactions. Map estimates of network measures demonstrate that high local connectivity is most often associated with a high clustering coefficient, long path length, and low physical cost. Task performance changed the balance between local and distant functional coupling in a subset of regions, particularly, increasing local functional coupling in regions engaged by the task. The observed properties suggest that the brain has evolved a balance that optimizes information-processing efficiency across different classes of specialized areas as well as mechanisms to modulate coupling in support of dynamically changing processing demands. We discuss the implications of these observations and applications of the present method for exploring normal and atypical brain function.

Recently, many researchers have used graph theory to study the aberrant brain structures in Alzheimer's disease (AD) and have made great progress. However, the characteristics of the cortical network in Mild Cognitive Impairment (MCI) are still largely unexplored. In this study, the gray matter volumes obtained from magnetic resonance imaging (MRI) for all brain regions except the cerebellum were parcellated into 90 areas using the automated anatomical labeling (AAL) template to construct cortical networks for 98 normal controls (NCs), 113 MCIs and 91 ADs. The measurements of the network properties were calculated for each of the three groups respectively. We found that all three cortical networks exhibited small-world properties and those strong interhemispheric correlations existed between bilaterally homologous regions. Among the three cortical networks, we found the greatest clustering coefficient and the longest absolute path length in AD, which might indicate that the organization of the cortical network was the least optimal in AD. The small-world measures of the MCI network exhibited intermediate values. This finding is logical given that MCI is considered to be the transitional stage between normal aging and AD. Out of all the between-group differences in the clustering coefficient and absolute path length, only the differences between the AD and normal control groups were statistically significant. Compared with the normal controls, the MCI and AD groups retained their hub regions in the frontal lobe but showed a loss of hub regions in the temporal lobe. In addition, altered interregional correlations were detected in the parahippocampus gyrus, medial temporal lobe, cingulum, fusiform, medial frontal lobe, and orbital frontal gyrus in groups with MCI and AD. Similar to previous studies of functional connectivity, we also revealed increased interregional correlations within the local brain lobes and disrupted long distance interregional correlations in groups with MCI and AD.

There is a considerable contrast between the various functions assigned to Broca's region and its relatively simple subdivision into two cytoarchitectonic areas (44 and 45). Since the regional distribution of transmitter receptors in the cerebral cortex has been proven a powerful indicator of functional diversity, the subdivision of Broca's region was analyzed here using a multireceptor approach. The distribution patterns of six receptor types using in vitro receptor autoradiography revealed previously unknown areas: a ventral precentral transitional cortex 6r1, dorsal and ventral areas 44d and 44v, anterior and posterior areas 45a and 45p, and areas op8 and op9 in the frontal operculum. A significant lateralization of receptors was demonstrated with respect to the cholinergic M(2) receptor, particularly in area 44v+d. We propose a new concept of the anterior language region, which elucidates the relation between premotor cortex, prefrontal cortex, and Broca's region. It offers human brain homologues to the recently described subdivision of area 45, and the segregation of the ventral premotor cortex in macaque brains. The results provide a novel structural basis of the organization of language regions in the brain.

The purpose of this study was to examine neural network properties at separate time-points during recovery from traumatic brain injury (TBI) using graph theory. Whole-brain analyses of the topological properties of the fMRI signal were conducted in 6 participants at 3 months and 6 months following severe TBI. Results revealed alterations of network properties including a change in the degree distribution, reduced overall strength in connectivity, and increased \"small-worldness\" from 3 months to 6 months post injury. The findings here indicate that, during recovery from injury, the strength but not the number of network connections diminishes, so that over the course of recovery, the network begins to approximate what is observed in healthy adults. These are the first data examining functional connectivity in a disrupted neural system during recovery.

fMRI Resting State Networks (RSNs) have gained importance in the present fMRI literature. Although their functional role is unquestioned and their physiological origin is nowadays widely accepted, little is known about their relationship to neuronal activity. The combined recording of EEG and fMRI allows the temporal correlation between fluctuations of the RSNs and the dynamics of EEG spectral amplitudes. So far, only relationships between several EEG frequency bands and some RSNs could be demonstrated, but no study accounted for the spatial distribution of frequency domain EEG. In the present study we report on the topographic association of EEG spectral fluctuations and RSN dynamics using EEG covariance mapping. All RSNs displayed significant covariance maps across a broad EEG frequency range. Cluster analysis of the found covariance maps revealed the common standard EEG frequency bands. We found significant differences between covariance maps of the different RSNs and these differences depended on the frequency band. Our data supports the physiological and neuronal origin of the RSNs and substantiates the assumption that the standard EEG frequency bands and their topographies can be seen as electrophysiological signatures of underlying distributed neuronal networks.

Diffusion MRI (dMRI) is widely used to measure microstructural features of brain white matter, but commonly used dMRI measures have limited capacity to resolve the orientation structure of complex fiber architectures. While several promising new approaches have been proposed, direct quantitative validation of these methods against relevant histological architectures remains missing. In this study, we quantitatively compare neuronal fiber orientation distributions (FODs) derived from ex vivo dMRI data against histological measurements of rat brain myeloarchitecture using manual recordings of individual myelin stained fiber orientations. We show that accurate FOD estimates can be obtained from dMRI data, even in regions with complex architectures of crossing fibers with an intrinsic orientation error of approximately 5-6 degrees in these regions. The reported findings have implications for both clinical and research studies based on dMRI FOD measures, and provide an important biological benchmark for improved FOD reconstruction and fiber tracking methods.

Microsatellite expansions cause a number of dominantly-inherited neurological diseases. Expansions in coding-regions cause protein gain-of-function effects, while non-coding expansions produce toxic RNAs that alter RNA splicing activities of MBNL and CELF proteins. Bi-directional expression of the spinocerebellar ataxia type 8 (SCA8) CTG CAG expansion produces CUG expansion RNAs (CUG(exp)) from the ATXN8OS gene and a nearly pure polyglutamine expansion protein encoded by ATXN8 CAG(exp) transcripts expressed in the opposite direction. Here, we present three lines of evidence that RNA gain-of-function plays a significant role in SCA8: 1) CUG(exp) transcripts accumulate as ribonuclear inclusions that co-localize with MBNL1 in selected neurons in the brain; 2) loss of Mbnl1 enhances motor deficits in SCA8 mice; 3) SCA8 CUG(exp) transcripts trigger splicing changes and increased expression of the CUGBP1-MBNL1 regulated CNS target, GABA-A transporter 4 (GAT4/Gabt4). In vivo optical imaging studies in SCA8 mice confirm that Gabt4 upregulation is associated with the predicted loss of GABAergic inhibition within the granular cell layer. These data demonstrate that CUG(exp) transcripts dysregulate MBNL/CELF regulated pathways in the brain and provide mechanistic insight into the CNS effects of other CUG(exp) disorders. Moreover, our demonstration that relatively short CUG(exp) transcripts cause RNA gain-of-function effects and the growing number of antisense transcripts recently reported in mammalian genomes suggest unrecognized toxic RNAs contribute to the pathophysiology of polyglutamine CAG CTG disorders.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterised by motor neuron degeneration. How this disease affects the central motor network is largely unknown. Here, we combined for the first time structural and functional imaging measures on the motor network in patients with ALS and healthy controls. Structural measures included whole brain cortical thickness and diffusion tensor imaging (DTI) of crucial motor tracts. These structural measures were combined with functional connectivity analysis of the motor network based on resting state fMRI. Focal cortical thinning was observed in the primary motor area in patients with ALS compared to controls and was found to correlate with disease progression. DTI revealed reduced FA values in the corpus callosum and in the rostral part of the corticospinal tract. Overall functional organisation of the motor network was unchanged in patients with ALS compared to healthy controls, however the level of functional connectedness was significantly correlated with disease progression rate. Patients with increased connectedness appear to have a more progressive disease course. We demonstrate structural motor network deterioration in ALS with preserved functional connectivity measures. The positive correlation between functional connectedness of the motor network and disease progression rate could suggest spread of disease along functional connections of the motor network.

The brainstem contains descending circuitry that can modulate nociceptive processing (neural signals associated with pain) in the dorsal horn of the spinal cord and the medullary dorsal horn. In migraineurs, abnormal brainstem function during attacks suggest that dysfunction of descending modulation may facilitate migraine attacks, either by reducing descending inhibition or increasing facilitation. To determine whether a brainstem dysfunction could play a role in facilitating migraine attacks, we measured brainstem function in migraineurs when they were not having an attack (i.e. the interictal phase). Using fMRI (functional magnetic resonance imaging), we mapped brainstem activity to heat stimuli in 12 episodic migraine patients during the interictal phase. Separate scans were collected to measure responses to 41 degrees C and noxious heat (pain threshold+1 degrees C). Stimuli were either applied to the forehead on the affected side (as reported during an attack) or the dorsum of the hand. This was repeated in 12 age-gender-matched control subjects, and the side tested corresponded to that in the matched migraine patients. Nucleus cuneiformis (NCF), a component of brainstem pain modulatory circuits, appears to be hypofunctional in migraineurs. 3 out of the 4 thermal stimulus conditions showed significantly greater NCF activation in control subjects than the migraine patients. Altered descending modulation has been postulated to contribute to migraine, leading to loss of inhibition or enhanced facilitation resulting in hyperexcitability of trigeminovascular neurons. NCF function could potentially serve as a diagnostic measure in migraine patients, even when not experiencing an attack. This has important implications for the evaluation of therapies for migraine.

The spontaneous component of neuropathic pain (NP) has not been explored sufficiently with neuroimaging techniques, given the difficulty to coax out the brain components that sustain background ongoing pain. Here, we address for the first time the correlates of this component in an fMRI study of a group of eight patients suffering from diabetic neuropathic pain and eight healthy control subjects. Specifically, we studied the functional connectivity that is associated with spontaneous neuropathic pain with spatial independent component analysis (sICA). Functional connectivity analyses revealed a cortical network consisting of two anti-correlated patterns: one includes the left fusiform gyrus, the left lingual gyrus, the left inferior temporal gyrus, the right inferior occipital gyrus, the dorsal anterior cingulate cortex bilaterally, the pre and postcentral gyrus bilaterally, in which its activity is correlated negatively with pain and positively with the controls; the other includes the left precuneus, dorsolateral prefrontal, frontopolar cortex (both bilaterally), right superior frontal gyrus, left inferior frontal gyrus, thalami, both insulae, inferior parietal lobuli, right mammillary body, and a small area in the left brainstem, in which its activity is correlated positively with pain and negatively with the controls. Furthermore, a power spectra analyses revealed group differences in the frequency bands wherein the sICA signal was decomposed: patients' spectra are shifted towards higher frequencies. In conclusion, we have characterized here for the first time a functional network of brain areas that mark the spontaneous component of NP. Pain is the result of aberrant default mode functional connectivity.