fMRIflows: A Consortium of Fully Automatic Univariate and Multivariate fMRI Processing Pipelines.

How functional magnetic resonance imaging (fMRI) data are analyzed depends on the researcher and the toolbox used. It is not uncommon that the processing pipeline is rewritten for each new dataset. Consequently, code transparency, quality control and objective analysis pipelines are important for improving reproducibility in neuroimaging studies. Toolboxes, such as Nipype and fMRIPrep, have documented the need for and interest in automated pre-processing analysis pipelines. Recent developments in data-driven models combined with high resolution neuroimaging dataset have strengthened the need not only for a standardized preprocessing workflow, but also for a reliable and comparable statistical pipeline. Here, we introduce fMRIflows: a consortium of fully automatic neuroimaging pipelines for fMRI analysis, which performs standard preprocessing, as well as 1st- and 2nd-level univariate and multivariate analyses. In addition to the standardized pre-processing pipelines, fMRIflows provides flexible temporal and spatial filtering to account for datasets with increasingly high temporal resolution and to help appropriately prepare data for advanced machine learning analyses, improving signal decoding accuracy and reliability. This paper first describes fMRIflows' structure and functionality, then explains its infrastructure and access, and lastly validates the toolbox by comparing it to other neuroimaging processing pipelines such as fMRIPrep, FSL and SPM. This validation was performed on three datasets with varying temporal sampling and acquisition parameters to prove its flexibility and robustness. fMRIflows is a fully automatic fMRI processing pipeline which uniquely offers univariate and multivariate single-subject and group analyses as well as pre-processing.

From Visual Perception to Aesthetic Appeal: Brain Responses to Aesthetically Appealing Natural Landscape Movies.

During aesthetically appealing visual experiences, visual content provides a basis for computation of affectively tinged representations of aesthetic value. How this happens in the brain is largely unexplored. Using engaging video clips of natural landscapes, we tested whether cortical regions that respond to perceptual aspects of an environment (e.g., spatial layout, object content and motion) were directly modulated by rated aesthetic appeal. Twenty-four participants watched a series of videos of natural landscapes while being scanned using functional magnetic resonance imaging (fMRI) and reported both continuous ratings of enjoyment (during the videos) and overall aesthetic judgments (after each video). Although landscape videos engaged a greater expanse of high-level visual cortex compared to that observed for images of landscapes, independently localized category-selective visual regions (e.g., scene-selective parahippocampal place area and motion-selective hMT+) were not significantly modulated by aesthetic appeal. Rather, a whole-brain analysis revealed modulations by aesthetic appeal in ventral (collateral sulcus) and lateral (middle occipital sulcus, posterior middle temporal gyrus) clusters that were adjacent to scene and motion selective regions. These findings suggest that aesthetic appeal per se is not represented in well-characterized feature- and category-selective regions of visual cortex. Rather, we propose that the observed activations reflect a local transformation from a feature-based visual representation to a representation of "elemental affect," computed through information-processing mechanisms that detect deviations from an observer's expectations. Furthermore, we found modulation by aesthetic appeal in subcortical reward structures but not in regions of the default-mode network (DMN) nor orbitofrontal cortex, and only weak evidence for associated changes in functional connectivity. In contrast to other visual aesthetic domains, aesthetically appealing interactions with natural landscapes may rely more heavily on comparisons between ongoing stimulation and well-formed representations of the natural world, and less on top-down processes for resolving ambiguities or assessing self-relevance.

Continuous ratings of movie watching reveal idiosyncratic dynamics of aesthetic enjoyment.

Visual aesthetic experiences unfold over time, yet most of our understanding of such experiences comes from experiments using static visual stimuli and measuring static responses. Here, we investigated the temporal dynamics of subjective aesthetic experience using temporally extended stimuli (movie clips) in combination with continuous behavioral ratings. Two groups of participants, a rate group (n = 25) and a view group (n = 25), watched 30-second video clips of landscapes and dance performances in test and retest blocks. The rate group reported continuous ratings while watching the videos, with an overall aesthetic judgment at the end of each video, in both test and retest blocks. The view group, however, passively watched the videos in the test block, reporting only an overall aesthetic judgment at the end of each clip. In the retest block, the view group reported both continuous and overall judgments. When comparing the two groups, we found that the task of making continuous ratings did not influence overall ratings or agreement across participants. In addition, the degree of temporal variation in continuous ratings over time differed substantially by observer (from slower "integrators" to "fast responders"), but less so by video. Reliability of continuous ratings across repeated exposures was in general high, but also showed notable variance across participants. Together, these results show that temporally extended stimuli produce aesthetic experiences that are not the same from person to person, and that continuous behavioral ratings provide a reliable window into the temporal dynamics of such aesthetic experiences while not materially altering the experiences themselves.

The default-mode network represents aesthetic appeal that generalizes across visual domains.

Visual aesthetic evaluations, which impact decision-making and well-being, recruit the ventral visual pathway, subcortical reward circuitry, and parts of the medial prefrontal cortex overlapping with the default-mode network (DMN). However, it is unknown whether these networks represent aesthetic appeal in a domain-general fashion, independent of domain-specific representations of stimulus content (artworks versus architecture or natural landscapes). Using a classification approach, we tested whether the DMN or ventral occipitotemporal cortex (VOT) contains a domain-general representation of aesthetic appeal. Classifiers were trained on multivoxel functional MRI response patterns collected while observers made aesthetic judgments about images from one aesthetic domain. Classifier performance (high vs. low aesthetic appeal) was then tested on response patterns from held-out trials from the same domain to derive a measure of domain-specific coding, or from a different domain to derive a measure of domain-general coding. Activity patterns in category-selective VOT contained a degree of domain-specific information about aesthetic appeal, but did not generalize across domains. Activity patterns from the DMN, however, were predictive of aesthetic appeal across domains. Importantly, the ability to predict aesthetic appeal varied systematically; predictions were better for observers who gave more extreme ratings to images subsequently labeled as "high" or "low." These findings support a model of aesthetic appreciation whereby domain-specific representations of the content of visual experiences in VOT feed in to a "core" domain-general representation of visual aesthetic appeal in the DMN. Whole-brain "searchlight" analyses identified additional prefrontal regions containing information relevant for appreciation of cultural artifacts (artwork and architecture) but not landscapes.

Dynamics of aesthetic experience are reflected in the default-mode network.

Neuroaesthetics is a rapidly developing interdisciplinary field of research that aims to understand the neural substrates of aesthetic experience: While understanding aesthetic experience has been an objective of philosophers for centuries, it has only more recently been embraced by neuroscientists. Recent work in neuroaesthetics has revealed that aesthetic experience with static visual art engages visual, reward and default-mode networks. Very little is known about the temporal dynamics of these networks during aesthetic appreciation. Previous behavioral and brain imaging research suggests that critical aspects of aesthetic experience have slow dynamics, taking more than a few seconds, making them amenable to study with fMRI. Here, we identified key aspects of the dynamics of aesthetic experience while viewing art for various durations. In the first few seconds following image onset, activity in the DMN (and high-level visual and reward regions) was greater for very pleasing images; in the DMN this activity counteracted a suppressive effect that grew longer and deeper with increasing image duration. In addition, for very pleasing art, the DMN response returned to baseline in a manner time-locked to image offset. Conversely, for non-pleasing art, the timing of this return to baseline was inconsistent. This differential response in the DMN may therefore reflect the internal dynamics of the participant's state: The participant disengages from art-related processing and returns to stimulus-independent thought. These dynamics suggest that the DMN tracks the internal state of a participant during aesthetic experience.

Automatized smoking-related action schemata are reflected by reduced fMRI activity in sensorimotor brain regions of smokers.

In the later stages of addiction, automatized processes play a prominent role in guiding drug-seeking and drug-taking behavior. However, little is known about the neural correlates of automatized drug-taking skills and drug-related action knowledge in humans. We employed functional magnetic resonance imaging (fMRI) while smokers and non-smokers performed an orientation affordance task, where compatibility between the hand used for a behavioral response and the spatial orientation of a priming stimulus leads to shorter reaction times resulting from activation of the corresponding motor representations. While non-smokers exhibited this behavioral effect only for control objects, smokers showed the affordance effect for both control and smoking-related objects. Furthermore, smokers exhibited reduced fMRI activation for smoking-related as compared to control objects for compatible stimulus-response pairings in a sensorimotor brain network consisting of the right primary motor cortex, supplementary motor area, middle occipital gyrus, left fusiform gyrus and bilateral cingulate gyrus. In the incompatible condition, we found higher fMRI activation in smokers for smoking-related as compared to control objects in the right primary motor cortex, cingulate gyrus, and left fusiform gyrus. This suggests that the activation and performance of deeply embedded, automatized drug-taking schemata employ less brain resources. This might reduce the threshold for relapsing in individuals trying to abstain from smoking. In contrast, the interruption or modification of already triggered automatized action representations require increased neural resources.