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Whereas some older adults show significant cognitive deficits, others perform as well as young adults. We investigated the neural basis of these different aging patterns using positron emission tomography (PET). In PET and functional MRI (fMRI) studies, prefrontal cortex (PFC) activity tends to be less asymmetric in older than in younger adults (Hemispheric(More)
New work suggests that blood oxygen level-dependent (BOLD) signal variability can be a much more powerful index of human age than mean activation, and that older brains are actually less variable than younger brains. However, little is known of how BOLD variability and task performance may relate. In the current study, we examined BOLD variability in(More)
We explored the effects of aging on 2 large-scale brain networks, the default mode network (DMN) and the task-positive network (TPN). During functional magnetic resonance imaging scanning, young and older participants carried out 4 visual tasks: detection, perceptual matching, attentional cueing, and working memory. Accuracy of performance was roughly(More)
Resting-state networks (RSNs), which have become a main focus in neuroimaging research, can be best simulated by large-scale cortical models in which networks teeter on the edge of instability. In this state, the functional networks are in a low firing stable state while they are continuously pulled towards multiple other configurations. Small extrinsic(More)
The brain "reward" system, centered on the limbic ventral striatum, plays a critical role in the response to pleasure and pain. The ventral striatum is activated in animal and human studies during anticipation of appetitive/pleasurable events, but its role in aversive/painful events is less clear. Here we present data from three human fMRI studies based on(More)
Recollecting a past episode involves remembering not only what happened but also when it happened. We used positron emission tomography (PET) to directly contrast the neural correlates of item and temporalorder memory. Subjects studied a list of words and were then scanned while retrieving information about what words were in the list or when they occurred(More)
Confronted with a rich sensory environment, the brain must learn statistical regularities across sensory domains to construct causal models of the world. Here, we used functional magnetic resonance imaging and dynamic causal modeling (DCM) to furnish neurophysiological evidence that statistical associations are learnt, even when task-irrelevant. Subjects(More)
Functional magnetic resonance imaging (fMRI) research often attributes blood oxygen level-dependent (BOLD) signal variance to measurement-related confounds. However, what is typically considered "noise" variance in data may be a vital feature of brain function. We examined fMRI signal variability during fixation baseline periods, and then compared SD- and(More)
Increasing evidence suggests that brain variability plays a number of important functional roles for neural systems. However, the relationship between brain variability and changing cognitive demands remains understudied. In the current study, we demonstrate experimental condition-based modulation in brain variability using functional magnetic resonance(More)
A broad body of experimental work has demonstrated that apparently spontaneous brain activity is not random. At the level of large-scale neural systems, as measured with functional MRI (fMRI), this ongoing activity reflects the organization of a series of highly coherent functional networks. These so-called resting-state networks (RSNs) closely relate to(More)