Local network connectivity disruptions in Alzheimer's disease patients have been found using graph analysis in BOLD fMRI. Other studies using MEG and cortical thickness measures, however, show more ...global long distance connectivity changes, both in functional and structural imaging data. The form and role of functional connectivity changes thus remains ambiguous. The current study shows more conclusive data on connectivity changes in early AD using graph analysis on resting-state condition fMRI data.
18 mild AD patients and 21 healthy age-matched control subjects without memory complaints were investigated in resting-state condition with MRI at 1.5 Tesla. Functional coupling between brain regions was calculated on the basis of pair-wise synchronizations between regional time-series. Local (cluster coefficient) and global (path length) network measures were quantitatively defined. Compared to controls, the characteristic path length of AD functional networks is closer to the theoretical values of random networks, while no significant differences were found in cluster coefficient. The whole-brain average synchronization does not differ between Alzheimer and healthy control groups. Post-hoc analysis of the regional synchronization reveals increased AD synchronization involving the frontal cortices and generalized decreases located at the parietal and occipital regions. This effectively translates in a global reduction of functional long-distance links between frontal and caudal brain regions.
We present evidence of AD-induced changes in global brain functional connectivity specifically affecting long-distance connectivity. This finding is highly relevant for it supports the anterior-posterior disconnection theory and its role in AD. Our results can be interpreted as reflecting the randomization of the brain functional networks in AD, further suggesting a loss of global information integration in disease.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Resting-state (RS) functional magnetic resonance (MR) imaging constitutes a novel paradigm that examines spontaneous brain function by using blood oxygen level-dependent contrast in the absence of a ...task. Spatially distributed networks of temporal synchronization can be detected that can characterize RS networks (RSNs). With a short acquisition time of less than 10 minutes, RS functional MR imaging can be applied in special populations such as children and patients with dementia. Some RSNs are already present in utero, while others mature in childhood. Around 10 major RSNs are consistently found in adults, but their exact spatial extent and strength of coherence are affected by physiologic parameters and drugs. Though the acquisition and analysis methods are still evolving, new disease insights are emerging in a variety of neurologic and psychiatric disorders. The default mode network is affected in Alzheimer disease and various other diseases of cognitive impairment. Alterations in RSNs have been identified in many diseases, in the absence of evident structural modifications, indicating a high sensitivity of the method. Moreover, there is evidence of correlation between RSN alterations and disease progression and severity. However, different diseases often affect the same RSN, illustrating the limited specificity of the findings. This suggests that neurologic and psychiatric diseases are characterized by altered interactions between RSNs and therefore the whole brain should be examined as an integral network (with subnetworks), for example, using graph analysis. A challenge for clinical applications of RS functional MR imaging is the potentially confounding effect of aging, concomitant vascular diseases, or medication on the neurovascular coupling and consequently the functional MR imaging response. Current investigation combines RS functional MR imaging and other methods such as electroencephalography or magnetoencephalography to better understand the vascular and neuronal contributions to alterations in functional connectivity.
Functional MRI (fMRI) can be applied to study the functional connectivity of the human brain. It has been suggested that fluctuations in the blood oxygenation level-dependent (BOLD) signal during ...rest reflect the neuronal baseline activity of the brain, representing the state of the human brain in the absence of goal-directed neuronal action and external input, and that these slow fluctuations correspond to functionally relevant resting-state networks. Several studies on resting fMRI have been conducted, reporting an apparent similarity between the identified patterns. The spatial consistency of these resting patterns, however, has not yet been evaluated and quantified. In this study, we apply a data analysis approach called tensor probabilistic independent component analysis to resting-state fMRI data to find coherencies that are consistent across subjects and sessions. We characterize and quantify the consistency of these effects by using a bootstrapping approach, and we estimate the BOLD amplitude modulation as well as the voxel-wise cross-subject variation. The analysis found 10 patterns with potential functional relevance, consisting of regions known to be involved in motor function, visual processing, executive functioning, auditory processing, memory, and the socalled default-mode network, each with BOLD signal changes up to 3%. In general, areas with a high mean percentage BOLD signal are consistent and show the least variation around the mean. These findings show that the baseline activity of the brain is consistent across subjects exhibiting significant temporal dynamics, with percentage BOLD signal change comparable with the signal changes found in task-related experiments.
Normal aging is associated with cognitive decline. Functions such as attention, information processing, and working memory are compromised. It has been hypothesized that not only regional changes, ...but also alterations in the integration of regional brain activity (functional brain connectivity) underlie the observed age-related deficits. Here, we examined the functional properties of brain networks based on spontaneous fluctuations within brain systems using functional magnetic resonance imaging. We hypothesized that functional connectivity of intrinsic brain activity in the “default-mode” network (DMN) is affected by normal aging and that this relates to cognitive function. Ten younger and 22 older subjects were scanned at “rest,” that is, lying awake with eyes closed. Our results show decreased activity in older versus younger subjects in 2 resting-state networks (RSNs) resembling the previously described DMN, containing the superior and middle frontal gyrus, posterior cingulate, middle temporal gyrus, and the superior parietal region. These results remain significant after correction for RSN-specific gray matter volume. The relevance of these findings is illustrated by the correlation between reduced activity of one of these RSNs and less effective executive functioning/processing speed in the older group.
Background Oxytocin facilitates parental caregiving and mother–infant bonding and might be involved in responses to infant crying. Infant crying provides information about the physical status and ...mood of the infant and elicits parental proximity and caregiving. Oxytocin might modulate the activation of brain structures involved in the perception of cry sounds—specifically the insula, the amygdala, and the thalamocingulate circuit—and thereby affect responsiveness to infant crying. Method In a randomized controlled trial we investigated the influence of intranasally administered oxytocin on neural responses to infant crying with functional magnetic resonance imaging. Blood oxygenation level–dependent responses to infant crying were measured in 21 women who were administered oxytocin and 21 women who were administered a placebo. Results Induced oxytocin levels reduced, experimentally, activation in the amygdala and increased activation in the insula and inferior frontal gyrus pars triangularis. Conclusions Our findings suggest that oxytocin promotes responsiveness to infant crying by reducing activation in the neural circuitry for anxiety and aversion and increasing activation in regions involved in empathy.
Dopaminergic medications, used to treat neurochemical pathology and resultant symptoms in neuropsychiatric disorders, are of mixed efficacy and regularly associated with behavioural side effects. The ...possibility that dopamine exerts both linear and nonlinear (‘inverted U-shaped’) effects on cognitive neurocircuitry may explain this outcome variability. However, it has proven to be difficult to characterise neural manifestations of psychopharmacological effects in humans. We hypothesised that diverse effects of dopamine neuromodulation could be characterised using systems-level neuroimaging approaches. Using ‘resting-state’ functional magnetic resonance imaging (FMRI), combined with dopaminergic challenges, we examined the dopamine-dependent functional connectivity of brain ‘resting-state networks’ (RSNs). We compared RSN connectivity in 3 groups of healthy volunteers given dopamine antagonist (haloperidol; N=18) or agonistic (levodopa; N=16) drugs, or a placebo (N=15). As RSNs have been shown to be relevant for numerous psychological functions and dysfunctions, we investigated both linear and nonlinear effects on RSN connectivity of manipulating dopamine neurotransmission pharmacologically. A basal ganglia RSN displayed both linear and nonlinear effects of dopamine manipulation on functional connectivity, respectively, with lateral frontoparietal and medial frontal neocortical areas. Conversely, a cognitive ‘default mode’ network showed only linear dopaminergic effects on connectivity with lateral frontal and parietal cortices. Our findings highlight diverse functional effects of dopamine neuromodulations on systems-level neural interactions. The observation that dopamine modulates distinct large-scale network connectivity patterns differentially, in both linear and nonlinear fashions, provides support for the objective utility of RSN metrics in classifying the effects and efficacy of psychopharmacological medications.
•Dopamine agonism and antagonism differentially affect large-scale brain networks.•The same drugs can also exert comparable modulations over distinct neurocircuitry.•Network-level drug effects are relevant for impulsive personality characteristics.•Resting-state FMRI may stratify psychopharmacological responses across individuals.
The relation between brain development across adolescence and adolescent risky behavior has attracted increasing interest in recent years. It has been proposed that adolescents are hypersensitive to ...reward because of an imbalance in the developmental pattern followed by the striatum and prefrontal cortex. To date, it is unclear if adolescents engage in risky behavior because they overestimate potential rewards or respond more to received rewards and whether these effects occur in the absence of decisions. In this study, we used a functional magnetic resonance imaging paradigm that allowed us to dissociate effects of the anticipation, receipt, and omission of reward in 10- to 12-year-old, 14- to 15-year-old, and 18- to 23-year-old participants. We show that in anticipation of uncertain outcomes, the anterior insula is more active in adolescents compared with young adults and that the ventral striatum shows a reward-related peak in middle adolescence, whereas young adults show orbitofrontal cortex activation to omitted reward. These regions show distinct developmental trajectories. This study supports the hypothesis that adolescents are hypersensitive to reward and adds to the current literature in demonstrating that neural activation differs in adolescents even for small rewards in the absence of choice. These findings may have important implications for understanding adolescent risk-taking behavior.
Cognitive impairment affects a large proportion of patients with multiple sclerosis (MS) and has a profound impact on their daily-life activities. Improving the knowledge of the pathophysiology of ...cognitive impairment in MS and of the mechanisms responsible for its evolution over time might contribute to development of better outcome measures and targets for innovative treatment strategies. Due to their ability to detect MS-related abnormalities, MRI techniques are a valuable tool to achieve these goals. Following an updated overview of the assessment methods and profile of cognitive impairment in patients with MS, this review provides a state-of-the-art summary of the main results obtained from the application of conventional and modern magnetic resonance- based techniques to quantify MS-related damage, in terms of macroscopic lesions, as well as involvement of the normal-appearing white matter and gray matter and their association with cognitive impairment. The possible role of brain cortical reorganization in limiting the clinical consequences of disease-related damage is also discussed. Finally, the utility of the previous techniques to monitor the progression of cognitive deficits over time and the efficacy of possible therapeutic strategies is considered.
Alzheimer's disease (AD) patients show altered patterns of functional connectivity (FC) on resting state functional magnetic resonance imaging (RSfMRI) scans. It is yet unclear which RSfMRI measures ...are most informative for the individual classification of AD patients. We investigated this using RSfMRI scans from 77 AD patients (MMSE = 20.4 ± 4.5) and 173 controls (MMSE = 27.5 ± 1.8). We calculated i) FC matrices between resting state components as obtained with independent component analysis (ICA), ii) the dynamics of these FC matrices using a sliding window approach, iii) the graph properties (e.g., connection degree, and clustering coefficient) of the FC matrices, and iv) we distinguished five FC states and administered how long each subject resided in each of these five states. Furthermore, for each voxel we calculated v) FC with 10 resting state networks using dual regression, vi) FC with the hippocampus, vii) eigenvector centrality, and viii) the amplitude of low frequency fluctuations (ALFF). These eight measures were used separately as predictors in an elastic net logistic regression, and combined in a group lasso logistic regression model. We calculated the area under the receiver operating characteristic curve plots (AUC) to determine classification performance. The AUC values ranged between 0.51 and 0.84 and the highest were found for the FC matrices (0.82), FC dynamics (0.84) and ALFF (0.82). The combination of all measures resulted in an AUC of 0.85. We show that it is possible to obtain moderate to good AD classification using RSfMRI scans. FC matrices, FC dynamics and ALFF are most discriminative and the combination of all the resting state measures improves classification accuracy slightly.
•We calculated resting state fMRI measures for Alzheimer patients and controls.•The resting state measures were used in elastic net classification analyses.•Functional connectivity and functional connectivity dynamics perform best.•Classification performance improves slightly when combining all measures.
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