Moreover, we observed greater inter-subject correlations in functional connectivity than in activity late in learning. 
Later stages of learning recruits individualized patterns of activity, likely reflecting subject-specific processes that help optimize behavior. Common patterns of functional connectivity are still present during late learning, suggesting a role of connectivity in consolidation of the learned information. Our findings demonstrate that subjects undergoing value learning express common stimulus-induced activity and connectivity that evolves based on the stage of the learning process.

Intersubject brain network pattern during value learning

Are some cognitive systems more constrained in their activity and connectivity than others? We identified several cognitive systems – visual, sensorimotor and default mode – that demonstrated significantly greater intersubject correlation and intersubject functional connectivity than other systems. In particular, we observed significantly high ISC and ISFC within lateral occipital cortex, lingual gyrus, fusiform gyrus and pericalcalrine, and all of the occipital lobe, which suggests that value learning commonly recruits brain regions responsible for visual perception, visual memory and decision making based on chosen value \cite{kuai2013learning}. We also observed significantly higher ISC and ISFC in temporal and parietal regions, suggesting that brain regions involved in attention, mentalization, and the attribution of self-belief are also commonly involved in value learning \cite{corbetta2002control,corbetta2011spatial}. While the group level constaints on visual and sensory motor systems are likely a result of similar sensory inputs, the default mode network is equidistant and maximally distant from primary visual and motor networks based on both functional connectivity and anatomical geodesic distance; moreover, a meta-analysis of human brain imaging data showed that the default-mode network is involved in tasks unrelated to immediate stimulus input, such as daydreaming or mind-wandering\cite{Margulies_2016}. Finally, the default mode nodes typically have high degree and constitute a large subset of the rich club \cite{Bertolero_2017}. Thus, the default-mode might form a stable core of nodes that exhibit similar activity and connectivity across subjects during learning. 
Interestingly, we found select brain regions whose ISFC exceeded their ISC – including frontal  regions, amygdala, thalamus, precuneus, cuneus and cingulate gyrus. These areas are commonly associated with higher cognitive functions such as flexibility of thinking, problem solving, cognitive inhibition and attentional control\cite{corbetta2002control}. One explanation for the high ISFC exhibited by these brain regions is that they represent important cognitive control areas that are likely to act as functional hubs which may be commonly integrated with other brain regions across subjects\cite{Hwang_2016,Bertolero_2017,Bertolero_2015}. Specifically, frontal pole frequently interacts with the anterior cingulate gyrus during reward-guided learning \cite{rushworth2011frontal} and precuneus – although widely known to play an important hub in the default mode network (DMN) \cite{raichle2001default} – is often activated during episodic memory retrieval and self-processing operations \cite{cavanna2006precuneus}. The higher ISFC at the precuneus might be related to higher reaction time in chosen correct value during value learning task\cite{oishi2005activation} which relate to subject memory of previous similar task. In summary, more constrained brain activity appears to occur within predominantly sensory-specific brain regions and more constrained functional connectivity appears to occur in integrative nodes commonly associated with higher cognitive function.

Dynamic intersubject learning curve

An advantage of our experimental approach is the ability to examine changes in neuronal processes throughout different phases of value learning – that is, we were able to track intersubject relationships dynamically. During early stages of learning, we observed similar patterns of brain activity across subjects, suggesting that participants generally exhibit similar temporal course of BOLD activation in response to value learning task stimuli. During later stages of learning, we observed a decrease in the ISC across subjects, suggesting that participants may adapt to the procedures of the task. We speculate that this dynamical shift in ISC also supports a mechanism in which individualized pattern of activity supports inter-individual variability in learning strategies. The ISFC gradually increased between the first and second day and subsequently decreased in day 3 but there was no difference between day 3 and day 4. This trajectory is reminiscent of the typical shape of a traditional learning curve \cite{rescorla1971variation}. Indeed, the empirically observed trajectory of ISFC suggests that the functional connectivity within and between brain networks of all the participants points to its role in an adaptive mechanism for value learning \cite{baeg2007learning, fatima2016dynamic, patel2013functional}. The changes in the intersubject large-scale functional brain networks may also provide important neural markers of goal-directed training performance irrespective of training platform and may give more information about the specific changes in brain activity and connectivity that affect behavioral outcomes.
Importantly, we found that cognitive systems were heterogeneously influential in the learning-induced ISFC and ISC. The higher ISFC (compared to ISC)  of the sensorimotor system could be attributed to common inputs to the sensory system for processing of stimulus information. The complimentary increase in the ISFC of the visual and sensorimotor systems may result from  trained motor coordination of hand and finger movement to perform the button-pushing during task response \cite{bassett2011dynamic,toni2001learning}. The resulting changes suggest a role in visual and sensorimotor systems in supporting visual identification of objects, interpretation of value, and motor coordination of hand-finger movement to guide more accurate and efficient decision making after the critical learning period. The lower ISC in the later stage of learning could not be ascribed to reduced neural activity at the visual and sensorimotor regions rather than individual differences in temporal time courses of BOLD signals after adaptation to the task and once the procedure is over learned and mastered in the early stage \cite{bastian2008understanding,keller2017stimulus}. On the other hand, ISFC remained higher than ISC in all systems, potentially because functional connectivity represents longer term neural adaptations to learning. Interestingly, our findings demonstrated involvement of DMN, such that over the course of value learning connectivity within DMN becomes more generalized across subjects and activity within DMN become more individualized across subjects. Although DMN is often viewed as a task-negative system that is typically more active during resting state processes, here we report evidence that the architecture of this system is highly involved in the learning of value.

Functional network drivers of value learning

Once the learning is achieved, what mechanisms optimize the organization of learned information for task performance? We showed evidence that visual and sensorimotor systems are involved in encoding task mechanics and value learning. First, ISFC was significantly correlated with task accuracy, suggesting that behavior might be improved when the functional network reorganizes according to a subject-general neural constraints. Furthermore, individual variation in stimulus-induced functional activity might be responsible for modulating subject-specific behavior during the value learning tasks \cite{gerraty2014transfer,laird2011behavioral,yamashita2015predicting} . Our observation that the relationship between ISFC and task accuracy was driven by the sensorimotor, DMN, and subcortical regions including putamen thalamus and caudate agrees with previous findings that these region are critical to various forms of reward-based learning, such as value learning \cite{haruno2004neural}. The putamen and caudate nucleus are part of dorsal striatum, that play an important role in decision making, a cognitive capability that requires determining the values objects \cite{delgado2008role}. In particular, the positive relationship between ISFC and caudate that offers a role for dorsal striatum is one of the intrinsic neural drivers that modulate the subject behavior to increase the performance accuracy by interacting with other brain systems especially the feedback-related learning\cite{seger2005roles}. Our results findings suggest that interregional coupling of brain activity with the dorsal striatum may be promising focal point of future work in the identification of target brain areas that contribute to individual deficits in general learning.