NeuroImage
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Randomized Controlled Trial
Manipulating brain connectivity with δ⁹-tetrahydrocannabinol: a pharmacological resting state FMRI study.
Resting state-functional magnetic resonance imaging (RS-FMRI) is a neuroimaging technique that allows repeated assessments of functional connectivity in resting state. While task-related FMRI is limited to indirectly measured drug effects in areas affected by the task, resting state can show direct CNS effects across all brain networks. Hence, RS-FMRI could be an objective measure for compounds affecting the CNS. ⋯ Clear increases were found for feeling high, external perception, heart rate and cortisol, whereas prolactin decreased. This study shows that THC induces both increases and (to a lesser extent) decreases in functional brain connectivity, mainly in brain regions with high densities of CB(1)-receptors. Some of the involved regions could be functionally related to robust THC-induced CNS-effects that have been found in previous studies (Zuurman et al., 2008), such as postural stability, feeling high and altered time perception.
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We assessed the hypothesis that brain signal variability is a reflection of functional network reconfiguration during memory processing. In the present experiments, we use multiscale entropy to capture the variability of human electroencephalogram (EEG) while manipulating the knowledge representation associated with faces stored in memory. Across two experiments, we observed increased variability as a function of greater knowledge representation. ⋯ In Experiment 2, brain signal variability increased with learning after multiple experimental exposures to previously unfamiliar faces. The results demonstrate that variability increases with face familiarity; cognitive processes during the perception of familiar stimuli may engage a broader network of regions, which manifests as higher complexity/variability in spatial and temporal domains. In addition, effects of repetition suppression on brain signal variability were observed, and the pattern of results is consistent with a selectivity model of neural adaptation.
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Damage to the structural connections of the thalamus is a frequent feature of traumatic brain injury (TBI) and can be a key factor in determining clinical outcome. Until recently it has been difficult to quantify the extent of this damage in vivo. Diffusion tensor imaging (DTI) provides a validated method to investigate traumatic axonal injury, and can be applied to quantify damage to thalamic connections. ⋯ Importantly, we show that this problem increases as tracts become more damaged, and leads to underestimation of the amount of traumatic axonal injury. In contrast, the tract template can be used in these cases, allowing a more accurate assessment of white matter damage. In summary, we propose a method suitable for assessing specific thalamo-cortical white matter connections after TBI that is robust to the presence of varying amounts of traumatic axonal injury, as well as highlighting the potential problems of applying tractography algorithms in patient populations.
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There is a great deal of heterogeneity in the impact of aging on cognition and cerebral functioning. One potential factor contributing to individual differences among the elderly is the cognitive reserve, which designates the partial protection from the deleterious effects of aging that lifetime experience provides. Neuroimaging studies examining task-related activation in elderly people suggested that cognitive reserve takes the form of more efficient use of brain networks and/or greater ability to recruit alternative networks to compensate for age-related cerebral changes. ⋯ Functional connectivity analyses of resting-state fMRI images in a subset of 41 participants indicated that these regions belong to the default mode network and the dorsal attention network respectively. Lower metabolism in the temporoparietal cortex was also associated with better memory abilities. The findings provide evidence for an inverse relationship between cognitive reserve and resting-state activity in key regions of two functional networks respectively involved in internal mentation and goal-directed attention.
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Decision making (DM) in the context of others often entails complex cognition-emotion interaction. While the literature suggests that the ventromedial prefrontal cortex (vmPFC), striatum, and amygdala are involved in valuation-based DM and hippocampus in context processing, how these neural mechanisms subserve the integration of cognitive and emotional values in a social context remains unclear. In this study we addressed this gap by systematically manipulating cognition-emotion interaction in a social DM context, when the participants played a card game with a hypothetical opponent in a behavioral study (n=73) and a functional magnetic-resonance-imaging study (n=16). ⋯ Furthermore, the vmPFC, but not amygdala, not only encoded the opponent's gains as if self's losses, but also represented a "final common currency" during valuation-based decisions. The extent to which emotional input influenced choices was associated with the functional connectivity between the value-signaling amygdala and value integrating vmPFC, and also with the functional connectivity between the context-setting hippocampus and value-signaling amygdala and ventral striatum. These results identify brain pathways through which emotion shapes subjective values in a social DM context.