Classically, model-based segmentation procedures match magnetic resonance imaging (MRI) volumes to an expertly labeled atlas using nonlinear registration. The accuracy of these techniques are limited due to atlas biases, misregistration, and resampling error. Multi-atlas-based approaches are used as a remedy and involve matching each subject to a number of manually labeled templates. This approach yields numerous independent segmentations that are fused using a voxel-by-voxel label-voting procedure. In this article, we demonstrate how the multi-atlas approach can be extended to work with input atlases that are unique and extremely time consuming to construct by generating a library of multiple automatically generated templates of different brains (MAGeT Brain). We demonstrate the efficacy of our method for the mouse and human using two different nonlinear registration algorithms (ANIMAL and ANTs). The input atlases consist a high-resolution mouse brain atlas and an atlas of the human basal ganglia and thalamus derived from serial histological data. MAGeT Brain segmentation improves the identification of the mouse anterior commissure (mean Dice Kappa values (κ = 0.801), but may be encountering a ceiling effect for hippocampal segmentations. Applying MAGeT Brain to human subcortical structures improves segmentation accuracy for all structures compared to regular model-based techniques (κ = 0.845, 0.752, and 0.861 for the striatum, globus pallidus, and thalamus, respectively). Experiments performed with three manually derived input templates suggest that MAGeT Brain can approach or exceed the accuracy of multi-atlas label-fusion segmentation (κ = 0.894, 0.815, and 0.895 for the striatum, globus pallidus, and thalamus, respectively).

A common emotion regulation strategy, cognitive reappraisal, involves altering the meaning of a situation so that the emotional response to the situation is changed. Most research on reappraisal has focused on down-regulation of negative emotion; few studies exist on reappraisal of positive affect, and even fewer have examined the cognitive reappraisal of craving for energy-dense (e.g., “junk”) foods. In the present study we examined this form of cognitive reappraisal using a new adaptation of a classic emotion regulation task. Subjects chose idiosyncratic categories of craved (and not craved) energy-dense foods as stimuli, and were instructed either to look at the stimulus or to reappraise it in a way that reduced desire to eat the depicted food using a strategy that could be used in the real world. A repeated-measures ANOVA and follow-up tests revealed that reappraisal significantly reduced self-reported desirability of both Craved and Not Craved foods, but for a greater degree in Craved foods. In addition, the degree to which subjects decreased their desire to consume Craved foods positively correlated with the cognitive restraint subscale of the Three-Factor Eating Questionnaire, a measure of self-control of eating in everyday life.

In the present studies, we aimed to understand how approach and avoidance states affect attentional flexibility by examining attentional shifts on a trial-by-trial basis. We also examined how a novel construct in this area, task context, might interact with motivation to influence attentional flexibility. Participants completed a modified composite letter task in which the ratio of global to local targets was varied by block, making different levels of attentional focus beneficial to performance on different blocks. Study 1 demonstrated that, in the absence of a motivation manipulation, switch costs were lowest on blocks with an even ratio of global and local trials and were higher on blocks with an uneven ratio. Other participants completed the task while viewing pictures (Studies 2 and 3) and assuming arm positions (Studies 2 and 4) to induce approach, avoidance, and neutral motivational states. Avoidance motivation reduced switch costs in evenly proportioned contexts, whereas approach motivation reduced switch costs in mostly global contexts. Additionally, approach motivation imparted a similar switch cost magnitude across different contexts, whereas avoidance and neutral states led to variable switch costs depending on the context. Subsequent analyses revealed that these effects were driven largely by faster switching to local targets on mostly global blocks in the approach condition. These findings suggest that avoidance facilitates attentional shifts when switches are frequent, whereas approach facilitates responding to rare or unexpected local stimuli. The main implication of these results is that motivation has different effects on attentional shifts depending on the context.

Dynamic, momentary approach or avoidance motivational states have downstream effects on eventual goal success and overall well being, but there is still uncertainty about how those states affect the proximal neurocognitive processes (e.g., attention) that mediate the longer-term effects. Attentional flexibility, or the ability to switch between different attentional foci, is one such neurocognitive process that influences outcomes in the long run. The present study examined how approach and avoidance motivational states affect the neural processes involved in attentional flexibility using fMRI with the aim of determining whether flexibility operates via different neural mechanisms under these different states. Attentional flexibility was operationalized as subjects’ ability to switch between global and local stimulus features. In addition to subjects’ motivational state, the task context was manipulated by varying the ratio of global to local trials in a block in light of recent findings about the moderating role of context on motivation-related differences in attentional flexibility. The neural processes involved in attentional flexibility differ under approach versus avoidance states. First, differences in the preparatory activity in key brain regions suggested that subjects’ preparedness to switch was influenced by motivational state (anterior insula) and the interaction between motivation and context (superior temporal gyrus, inferior parietal lobule). Additionally, we observed motivation-related differences the anterior cingulate cortex during switching. These results provide initial evidence that motivation-induced behavioral changes may arise via different mechanisms in approach versus avoidance motivational states.

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