NeuroImage
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Studies have suggested that the default mode network is active during mind wandering, which is often experienced intermittently during sustained attention tasks. Conversely, an anticorrelated task-positive network is thought to subserve various forms of attentional processing. Understanding how these two systems work together is central for understanding many forms of optimal and sub-optimal task performance. ⋯ Elements of the executive network were active during shifting and sustained attention. Furthermore, activations during these cognitive phases were modulated by lifetime meditation experience. These findings support and extend theories about cognitive correlates of distributed brain networks.
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Group decisions and even aggregation of multiple opinions lead to greater decision accuracy, a phenomenon known as collective wisdom. Little is known about the neural basis of collective wisdom and whether its benefits arise in late decision stages or in early sensory coding. Here, we use electroencephalography and multi-brain computing with twenty humans making perceptual decisions to show that combining neural activity across brains increases decision accuracy paralleling the improvements shown by aggregating the observers' opinions. ⋯ Estimation of the potential for the collective to execute fast decisions by combining information across numerous brains, a strategy prevalent in many animals, shows large time-savings. Together, the findings suggest that for perceptual decisions the neural activity supporting collective wisdom and decisions arises in early sensory stages and that many properties of collective cognition are explainable by the neural coding of information across multiple brains. Finally, our methods highlight the potential of multi-brain computing as a technique to rapidly and in parallel gather increased information about the environment as well as to access collective perceptual/cognitive choices and mental states.
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There are a number of symptoms, both neurological and behavioral, associated with a single episode of r mild traumatic brain injury (mTBI). Neuropsychological testing and conventional neuroimaging techniques are not sufficiently sensitive to detect these changes, which adds to the complexity and difficulty in relating symptoms from mTBI to their underlying structural or functional deficits. With the inability of traditional brain imaging techniques to properly assess the severity of brain damage induced by mTBI, there is hope that more advanced neuroimaging applications will be more sensitive, as well as specific, in accurately assessing mTBI. ⋯ Connections between the left dorso-lateral prefrontal cortex and left lateral parietal cortex showed a significant reduction in magnitude as the number of concussions increased. Regression analysis also indicated an overall loss of connectivity as the number of mTBI episodes increased. Our findings indicate that alterations in the brain resting state default mode network in the subacute phase of injury may be of use clinically in assessing the severity of mTBI and offering some insight into the pathophysiology of the disorder.
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The five-factor model organizes personality traits into five factors: Neuroticism, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness. Measures of these personality traits predict people's behaviors and important outcomes of their lives. Therefore, understanding the neural correlates of these personality traits is important. ⋯ Furthermore, Neuroticism correlated positively with MD in the anterior cingulum and uncinate fasciculus, tracts interconnecting PFC and amygdala. Openness correlated negatively with MD of WM adjacent to the dorsolateral PFC in both hemispheres. These findings suggest that greater Neuroticism associates with worse integrity of WM interconnecting extensive cortical and subcortical structures including the PFC and amygdala and that greater Openness associates with better integrity of WM interconnecting extensive cortical and subcortical structures including the dorsolateral PFC.
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Magnetization transfer (MT) reflects the exchange of magnetization between protons bound to macromolecules, such as lipids and proteins, and protons in free liquid, and thus might be an early marker for subtle and undetermined pathologic changes in tissue. Detailed analysis of the entire MT phenomenon, however, commonly requires extensive data acquisition and scanning time, and hence is only of limited clinical interest. Therefore, in practice, magnetization transfer effects are commonly confined into a simple ratio measure, the so-called magnetization transfer ratio (MTR), calculated from a MT-weighted and a non-MT-weighted image. ⋯ Structures with highly similar MTR-values, such as the crus cerebri and the anterior commissure in the WM, or the pallidum and the amygdala in the GM, however, were also found that showed significant differences in most quantitative parameters. This observation was confirmed from simulations revealing that the overall effect on MTR from an increase (decrease) in relaxation times may be counterbalanced with a decrease (increase) in MT parameters. These findings corroborate the expectation that qMT is superior to MTR imaging, especially for the evaluation and assessment of pathologic or physiological changes in healthy and pathologic brain tissue.