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Although dietary decision-making is regulated by multiple interacting neural controllers, their impact on dietary treatment success in obesity has only been investigated individually. Here, we used fMRI to test how well interactions between the Pavlovian system (automatically triggering urges of consumption after food cue exposure) and the goal-directed system (considering long-term consequences of food decisions) predict future dietary success achieved in 39 months. Activity of the Pavlovian system was measured with a cue-reactivity task by comparing perception of food versus control pictures, activity of the goal-directed system with a food-specific delay discounting paradigm. Both tasks were applied in 30 individuals with obesity up to five times: Before a 12-week diet, immediately thereafter, and at three annual follow-up visits. Brain activity was analyzed in two steps. In the first, we searched for areas involved in Pavlovian processes and goal-directed control across the 39-month study period with voxel-wise linear mixed-effects (LME) analyses. In the second, we computed network parameters reflecting the covariation of longitudinal voxel activity (i.e. principal components) in the regions identified in the first step and used them to predict body mass changes across the 39 months with LME models. Network analyses testing the link of dietary success with activity of the individual systems as reference found a moderate negative link to Pavlovian activity primarily in left hippocampus and a moderate positive association to goal-directed activity primarily in right inferior parietal gyrus. A cross-paradigm network analysis that integrated activity measured in both tasks revealed a strong positive link for interactions between visual Pavlovian areas and goal-directed decision-making regions mainly located in right insular cortex. We conclude that adaptation of food cue processing resources to goal-directed control activity is an important prerequisite of sustained dietary weight loss, presumably since the latter activity can modulate Pavlovian urges triggered by frequent cue exposure in everyday life.

Representations of sensory working memory can be found across the entire neocortex. But how are verbal working memory (VWM) contents retained in the human brain? Here we used fMRI and multi-voxel pattern analyses to study Chinese native speakers (15 males, 13 females) memorizing Chinese characters. Chinese characters are uniquely suitable to study VWM because verbal encoding is encouraged by their complex visual appearance and monosyllabic pronunciation. We found that activity patterns in Broca's area and left premotor cortex carried information about the memorized characters. These language-related areas carried (1) significantly more information about cued characters than those not cued for memorization, (2) significantly more information on the left than the right hemisphere and (3) significantly more information about Chinese symbols than complex visual patterns which are hard to verbalize. In contrast, early visual cortex carries a comparable amount of information about cued and uncued stimuli and is thus unlikely to be involved in memory retention. This study provides evidence for verbal working memory maintenance in a distributed network of language-related brain regions, consistent with distributed accounts of WM. The results also suggest that Broca's area and left premotor cortex form the articulatory network which serves articulatory rehearsal in the retention of verbal working memory contents.

There has been a long history of research on visual working memory. Whereas early studies have focused on the role of lateral prefrontal cortex in the storage of sensory information, this has been challenged by research in humans that has directly assessed the encoding of perceptual contents, pointing towards a role of visual and parietal regions during storage. In a previous study we used pattern classification to investigate the storage of complex visual color patterns across delay periods. This revealed coding of such contents in early visual and parietal brain regions. Here we aim to investigate whether the involvement of visual and parietal cortex is also observable for other types of complex, visuo-spatial pattern stimuli. Specifically, we used a combination of fMRI and multivariate classification to investigate the retention of complex flow-field stimuli defined by the spatial patterning of motion trajectories of random dots. Subjects were trained to memorize the precise spatial layout of these stimuli and to retain this information during an extended delay. We used a multivariate decoding approach to identify brain regions where spatial patterns of activity encoded the memorized stimuli. Content-specific memory signals were observable in motion sensitive visual area MT+ and in posterior parietal cortex that might encode spatial information in a modality independent manner. Interestingly, we also found information about the memorized visual stimulus in somatosensory cortex, suggesting a potential crossmodal contribution to memory. Our findings thus indicate that working memory storage of visual percepts might be distributed across unimodal, multimodal and even crossmodal brain regions.

Visual stimuli can "pop out" if they are different to their background. There has been considerable debate as to the role of primary visual cortex (V1) versus higher visual areas (esp. V4) in pop-out processing. Here we parametrically modulated the relative orientation of stimuli and their backgrounds to investigate the neural correlates of pop-out in visual cortex while subjects were performing a demanding fixation task in a scanner. Whole brain and region of interest analyses confirmed a representation of orientation contrast in extrastriate visual cortex (V4), but not in striate visual cortex (V1). Thus, although previous studies have shown that human V1 can be involved in orientation pop-out, our findings demonstrate that there are cases where V1 is "blind" and pop-out detection is restricted to higher visual areas. Pop-out processing is presumably a distributed process across multiple visual regions.

Perceptual decision-making entails the transformation of graded sensory signals into categorical judgments. Often, there is a direct mapping between these judgments and specific motor responses. However, when stimulus-response mappings are fixed, neural activity underlying decision-making cannot be separatedfrom neural activity reflecting motor planning. Several human neuroimaging studies have reported changes in brain activity associated with perceptual decisions. Nevertheless, to date it has remained unknown where and how specific choices are encoded in the human brain when motor planning is decoupled from the decisionprocess. We addressed this question by having subjects judge the direction of motion of dynamic random dot patterns at various levels of motion strength while measuring their brain activity with fMRI. We used multivariate decoding analyses to search the whole brain for patterns of brain activity encoding subjects' choices. To decouple the decision process from motor planning, subjects were informed about the required motor response only after stimulus presentation. Patterns of fMRI signals in early visual and inferior parietal cortex predicted subjects' perceptual choices irrespective of motor planning. This was true across several levels of motion strength and even in the absence of any coherent stimulus motion. We also found that the cortical distribution of choice-selective brain signals depended on stimulus strength: While visual cortex carried most choice-selective information for strong motion, information in parietal cortex decreased with increasing motion coherence. These results demonstrate that human visual and inferior parietal cortexcarry information about the visual decision in a more abstract format than can be explained by simple motor intentions. Both brain regions may be differentially involved in perceptual decision-making in the face of strong and weak sensory evidence.

Focused attention meditations have been shown to improve psychological health and wellbeing and are nowadays an integral part of many psychotherapies. While research on the neural correlates of focused attention meditation is increasing, findings vary on whether meditations are associated with high or low activity in the default mode network (DMN). To clarify the relationship between focused attention meditation and the activity in DMN regions, it may be helpful to distinguish internal and external attention as well as different phases within one meditation: During focused attention meditation, the practitioner switches between mindful attention, mind-wandering and refocusing. Here, we employed a thought-probe paradigm to study the neural correlates of these different phases. Twenty healthy, meditation naive participants were introduced to external (mindfulness of sound) and internal (mindfulness of breathing) attention meditation and then practiced the meditation at home for four consecutive days. They then performed the same focused attention meditations during fMRI scanning, in four runs alternating between internal and external attention. At pseudorandom intervals, participants were asked whether they had just been focused on the task (mindful attention) or had been distracted (mind-wandering). During mindful attention, brain regions typically associated with the DMN, such as the medial prefrontal cortex, posterior cingulate cortex and left temporoparietal junction showed significantly less neural activation compared to mind-wandering phases. Reduced activity of the DMN was found during both external and internal attention, with stronger deactivation in the posterior cingulate cortex during internal attention compared to external attention. Moreover, refocusing after mind-wandering was associated with activity in the left inferior frontal gyrus. Our results support the theory that mindful attention is associated with reduced DMN activity compared to mind-wandering, independent of the practitioner's attention focus (i.e., internal vs. external).