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SummaryData analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed.

Recent findings show that preferences for food items can be modified without external reinforcements using the cue-approach task. In the task, the mere association of food item images with a neutral auditory cue and a speeded button press, resulted in enhanced preferences for the associated stimuli. In a series of 10 independent samples with a total of 255 participants, we show for the first time that using this non-reinforced method we can enhance preferences for faces, fractals and affective images, as well as snack foods, using auditory, visual and even aversive cues. This change was highly durable in follow-up sessions performed one to six months after training. Preferences were successfully enhanced for all conditions, except for negative valence items. These findings promote our understanding of nonreinforced change, suggest a boundary condition for the effect and lay the foundation for development of novel applications.Behavioral change is an essential tool to improve health and quality of life, from treating addictions to eating and mood disorders [1][2][3] . Scientific research on behavioral change mainly focused on the effects of external reinforcements 2,4-7 or altering the presentation of the decision problem [8][9][10] . Recently, the cue-approach training (CAT) 11 paradigm was introduced as a successful method for enhancing preferences for food items, without external reinforcement, context change or self-control. Here, we test multiple hypotheses that are aimed to shed light on this mechanism by studying its generalizability to multiple stimuli and cues, as well as the long-term durability of the effect. In the cue-approach task, participants initially indicated their preferences for a set of snack-food items by specifying their willingness to pay for each item in an auction procedure. Then, in the CAT, some of the items were consistently associated with a neutral auditory cue and a speeded button press response (these stimuli were termed 'Go items'), whereas other stimuli were presented without a cue ('No-Go items'). In the following probe phase, participants were asked to choose a snack they would like to eat at the end of the experiment. Each probe-choice comprised of a pair of items with similar initial values, in which only one of the two snacks was a Go item. Results showed that the mere association of snack-food images with a neutral auditory cue and a speeded button press, resulted in enhanced preferences for Go items over No-Go items. This preference change effect varied across different value categories -resulting in enhanced preferences for snack-food items of initial high-value, yet significantly less prominent change in preferences for low-value items. The effect was maintained two-months following training 11 . Additional studies with the cue-approach task 12 found that for the behavioral change to take place, CAT required the presence of both a speeded button press response and a cue; i.e. CAT had no effect when training was conducted with an early cue onset which was followed with ...

Behavioral change studies and interventions focus on self-control and external reinforcements to influence preferences. Cue-approach training (CAT) has been shown to induce preference changes lasting months by merely associating items with neutral cues and speeded responses. We utilized this paradigm to study neural representation of preferences and their modification without external reinforcements. We scanned 36 participants with fMRI during a novel passive viewing task before, after and 30 days following CAT. We preregistered the predictions that activity in memory, top-down attention, and value-processing regions will underlie preference modification. While most theories associate preferences with prefrontal regions, we found that “bottom-up” perceptual mechanisms were associated with immediate change, whereas reduced “top-down” parietal activity was related to long-term change. Activity in value-related prefrontal regions was enhanced immediately after CAT for trained items and 1 month after for all items. Our findings suggest a novel neural mechanism of preference representation and modification. We suggest that nonreinforced change of preferences occurs initially in perceptual representation of items, putatively leading to long-term changes in “top-down” processes. These findings offer implementation of bottom-up instead of top-down targeted interventions for long-lasting behavioral change.

There is an ongoing debate about the replicability of neuroimaging research. It was suggested that one of the main reasons for the high rate of false positive results is the many degrees of freedom researchers have during data analysis. In the Neuroimaging Analysis Replication and Prediction Study (NARPS), we aim to provide the first scientific evidence on the variability of results across analysis teams in neuroscience. We collected fMRI data from 108 participants during two versions of the mixed gambles task, which is often used to study decision-making under risk. For each participant, the dataset includes an anatomical (T1 weighted) scan and fMRI as well as behavioral data from four runs of the task. The dataset is shared through OpenNeuro and is formatted according to the Brain Imaging Data Structure (BIDS) standard. Data pre-processed with fMRIprep and quality control reports are also publicly shared. This dataset can be used to study decision-making under risk and to test replicability and interpretability of previous results in the field.

Current noninvasive methods to detect structural plasticity in humans are mainly used to study long-term changes. Diffusion magnetic resonance imaging (MRI) was recently proposed as a novel approach to reveal gray matter changes following spatial navigation learning and object-location memory tasks. In the present work, we used diffusion MRI to investigate the short-term neuroplasticity that accompanies motor sequence learning. Following a 45-min training session in which participants learned to accurately play a short sequence on a piano keyboard, changes in diffusion properties were revealed mainly in motor system regions such as the premotor cortex and cerebellum. In a second learning session taking place immediately afterward, feedback was given on the timing of key pressing instead of accuracy, while participants continued to learn. This second session induced a different plasticity pattern, demonstrating the dynamic nature of learning-induced plasticity, formerly thought to require months of training in order to be detectable. These results provide us with an important reminder that the brain is an extremely dynamic structure. Furthermore, diffusion MRI offers a novel measure to follow tissue plasticity particularly over short timescales, allowing new insights into the dynamics of structural brain plasticity.

Developing effective preference modification paradigms is crucial to improve the quality of life in a wide range of behaviors. The cue-approach training (CAT) paradigm has been introduced as an effective tool to modify preferences lasting months, without external reinforcements, using the mere association of images with a cue and a speeded button response. In the current work for the first time, we used fMRI with faces as stimuli in the CAT paradigm, focusing on face-selective brain regions. We found a behavioral change effect of CAT with faces immediately and 1-month after training, however face-selective regions were not indicative of behavioral change and thus preference change is less likely to rely on face processing brain regions.Nevertheless, we found that during training, fMRI activations in the ventral striatum were correlated with individual preference change. We also found a correlation between preference change and activations in the ventromedial prefrontal cortex during the binary choice phase. Functional connectivity among striatum, prefrontal regions, and high-level visual regions was also related to individual preference change. Our work sheds new light on the involvement of neural mechanisms in the process of valuation. This could lead to development of novel real-world interventions.

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