Continuous decision to wait for a future reward is guided by fronto-hippocampal anticipatory dynamics.

Deciding whether to wait for a future reward is crucial for surviving in an uncertain world. While seeking rewards, agents anticipate a reward in the present environment and constantly face a trade-off between staying in their environment or leaving it. It remains unclear, however, how humans make continuous decisions in such situations. Here, we show that anticipatory activity in the anterior prefrontal cortex, ventrolateral prefrontal cortex, and hippocampus underpins continuous stay-leave decision-making. Participants awaited real liquid rewards available after tens of seconds, and their continuous decision was tracked by dynamic brain activity associated with the anticipation of a reward. Participants stopped waiting more frequently and sooner after they experienced longer delays and received smaller rewards. When the dynamic anticipatory brain activity was enhanced in the anterior prefrontal cortex, participants remained in their current environment, but when this activity diminished, they left the environment. Moreover, while experiencing a delayed reward in a novel environment, the ventrolateral prefrontal cortex and hippocampus showed anticipatory activity. Finally, the activity in the anterior prefrontal cortex and ventrolateral prefrontal cortex was enhanced in participants adopting a leave strategy, whereas those remaining stationary showed enhanced hippocampal activity. Our results suggest that fronto-hippocampal anticipatory dynamics underlie continuous decision-making while anticipating a future reward.

Healthy dietary choices involve prefrontal mechanisms associated with long-term reward maximization but not working memory.

Taste and health are critical factors to be considered when choosing foods. Prioritizing healthiness over tastiness requires self-control. It has also been suggested that self-control is guided by cognitive control. We then hypothesized that neural mechanisms underlying healthy food choice are associated with both self-control and cognitive control. Human participants performed a food choice task and a working memory task during functional MRI scanning. Their degree of self-control was assessed behaviorally by the value discount of delayed monetary rewards in intertemporal choice. Prioritizing healthiness in food choice was associated with greater activity in the superior, dorsolateral, and medial prefrontal cortices. Importantly, the prefrontal activity was greater in individuals with smaller delay discounting (i.e. high self-control) who preferred a delayed larger reward to an immediate smaller reward in intertemporal choice. On the other hand, working memory activity did not show a correlation with delay discounting or food choice activity, which was further supported by supplementary results that analyzed data from the Human Connectome Project. Our results suggest that the prefrontal cortex plays a critical role in healthy food choice, which requires self-control, but not working memory, for maximization of reward attainments in a remote future.

Perceptual Uncertainty Alternates Top-down and Bottom-up Fronto-Temporal Network Signaling during Response Inhibition.

Response inhibition is a primary executive control function that allows the withholding of inappropriate responses, and requires appropriate perception of the external environment to achieve a behavioral goal. It remains unclear, however, how response inhibition is achieved when goal-relevant information involves perceptual uncertainty. Twenty-six human participants of both sexes performed a go/no-go task where visually presented random-dot motion stimuli involved perceptual uncertainties. The right inferior frontal cortex (rIFC) was involved in response inhibition, and the middle temporal (MT) region showed greater activity when dot motions involved less uncertainty. A neocortical temporal region in the superior temporal sulcus (STS) specifically showed greater activity during response inhibition in more perceptually certain trials. In this STS region, activity was greater when response inhibition was successful than when it failed. Directional effective connectivity analysis revealed that, in more coherent trials, the MT and STS regions showed enhanced connectivity to the rIFC, whereas in less coherent trials, the signal direction was reversed. These results suggest that a reversible fronto-temporal functional network guides response inhibition and perceptual decision-making under perceptual uncertainty, and in this network, perceptual information in the MT is converted to control information in the rIFC via STS, enabling achievement of response inhibition.SIGNIFICANCE STATEMENT Response inhibition refers to withholding inappropriate behavior and is important for achieving goals. Often, however, decision must be made based on limited environmental evidence. We showed that successful response inhibition is guided by a neocortical temporal region that plays a hub role in converting perceived information coded in a posterior temporal region to control information coded in the PFC. Interestingly, when a perceived stimulus becomes more uncertain, the PFC supplements stimulus encoding in the temporal regions. Our results highlight fronto-temporal mechanisms of response inhibition in which conversion of stimulus-control information is regulated based on the uncertainty of environmental evidence.

Multimodal deep neural decoding reveals highly resolved spatiotemporal profile of visual object representation in humans.

Perception and categorization of objects in a visual scene are essential to grasp the surrounding situation. Recently, neural decoding schemes, such as machine learning in functional magnetic resonance imaging (fMRI), has been employed to elucidate the underlying neural mechanisms. However, it remains unclear as to how spatially distributed brain regions temporally represent visual object categories and sub-categories. One promising strategy to address this issue is neural decoding with concurrently obtained neural response data of high spatial and temporal resolution. In this study, we explored the spatial and temporal organization of visual object representations using concurrent fMRI and electroencephalography (EEG), combined with neural decoding using deep neural networks (DNNs). We hypothesized that neural decoding by multimodal neural data with DNN would show high classification performance in visual object categorization (faces or non-face objects) and sub-categorization within faces and objects. Visualization of the fMRI DNN was more sensitive than that in the univariate approach and revealed that visual categorization occurred in brain-wide regions. Interestingly, the EEG DNN valued the earlier phase of neural responses for categorization and the later phase of neural responses for sub-categorization. Combination of the two DNNs improved the classification performance for both categorization and sub-categorization compared with fMRI DNN or EEG DNN alone. These deep learning-based results demonstrate a categorization principle in which visual objects are represented in a spatially organized and coarse-to-fine manner, and provide strong evidence of the ability of multimodal deep learning to uncover spatiotemporal neural machinery in sensory processing.

Reversible Fronto-occipitotemporal Signaling Complements Task Encoding and Switching under Ambiguous Cues.

Adaptation to changing environments involves the appropriate extraction of environmental information to achieve a behavioral goal. It remains unclear how behavioral flexibility is guided under situations where the relevant behavior is ambiguous. Using functional brain mapping of machine learning decoders and directional functional connectivity, we show that brain-wide reversible neural signaling underpins task encoding and behavioral flexibility in ambiguously changing environments. When relevant behavior is cued ambiguously during behavioral shifting, neural coding is attenuated in distributed cortical regions, but top-down signals from the prefrontal cortex complement the coding. When behavioral shifting is cued more explicitly, modality-specialized occipitotemporal regions implement distinct neural coding about relevant behavior, and bottom-up signals from the occipitotemporal region to the prefrontal cortex supplement the behavioral shift. These results suggest that our adaptation to an ever-changing world is orchestrated by the alternation of top-down and bottom-up signaling in the fronto-occipitotemporal circuit depending on the availability of environmental information.

Cross-Hemispheric Complementary Prefrontal Mechanisms during Task Switching under Perceptual Uncertainty.

Flexible adaptation to changing environments is a representative executive control function implicated in the frontoparietal network that requires appropriate extraction of goal-relevant information through perception of the external environment. It remains unclear, however, how the flexibility is achieved under situations where goal-relevant information is uncertain. To address this issue, the current study examined neural mechanisms for task switching in which task-relevant information involved perceptual uncertainty. Twenty-eight human participants of both sexes alternated behavioral tasks in which they judged motion direction or color of visually presented colored dot stimuli that moved randomly. Task switching was associated with frontoparietal regions in the left hemisphere, and perception of ambiguous stimuli involved contralateral homologous frontoparietal regions. On the other hand, in stimulus-modality-dependent occipitotemporal regions, task coding information was increased during task switching. Effective connectivity analysis revealed that the frontal regions signaled toward the modality-dependent occipitotemporal regions when a relevant stimulus was more ambiguous, whereas the occipitotemporal regions signaled toward the frontal regions when the stimulus was more distinctive. These results suggest that complementary prefrontal mechanisms in the left and right hemispheres help to achieve a behavioral goal when the external environment involves perceptual uncertainty.SIGNIFICANCE STATEMENT In our daily life, environmental information to achieve a goal is not always certain, but we make judgments in such situations, and change our behavior accordingly. This study examined how the flexibility of behavior is achieved in a situation where goal-relevant information involves perceptual uncertainty. fMRI revealed that the lateral prefrontal cortex (PFC) in the left hemisphere is associated with behavioral flexibility, and the perception of ambiguous stimuli involves the PFC in the right hemisphere. These bilateral PFC signaled to stimulus-modality-dependent occipitotemporal regions, depending on perceptual uncertainty and the task to be performed. These top-down signals supplement task coding in the occipitotemporal regions, and highlight interhemispheric prefrontal mechanisms involved in executive control and perceptual decision-making.

On co-activation pattern analysis and non-stationarity of resting brain activity.

The non-stationarity of resting-state brain activity has received increasing attention in recent years. Functional connectivity (FC) analysis with short sliding windows and coactivation pattern (CAP) analysis are two widely used methods for assessing the dynamic characteristics of brain activity observed with functional magnetic resonance imaging (fMRI). However, the statistical nature of the dynamics captured by these techniques needs to be verified. In this study, we found that the results of CAP analysis were similar for real fMRI data and simulated stationary data with matching covariance structures and spectral contents. We also found that, for both the real and simulated data, CAPs were clustered into spatially heterogeneous modules. Moreover, for each of the modules in the real data, a spatially similar module was found in the simulated data. The present results suggest that care needs to be taken when interpreting observations drawn from CAP analysis as it does not necessarily reflect non-stationarity or a mixture of states in resting brain activity.

Executive control by fronto-parietal activity explains counterintuitive decision behavior in complex value-based decision-making.

In real life, humans make decisions by taking into account multiple independent factors, such as delay and probability. Cognitive psychology suggests that cognitive control mechanisms play a key role when facing such complex task conditions. However, in value-based decision-making, it still remains unclear to what extent cognitive control mechanisms become essential when the task condition is complex. In this study, we investigated decision-making behaviors and underlying neural mechanisms using a multifactor gambling task where participants simultaneously considered probability and delay. Decision-making behavior in the multifactor task was modulated by both probability and delay. The behavioral effect of probability was stronger than delay, consistent with previous studies. Furthermore, in a subset of conditions that recruited fronto-parietal activations, reaction times were paradoxically elongated despite lower probabilistic uncertainty. Notably, such a reaction time elongation did not occur in control tasks involving single factors. Meta-analysis of brain activations suggested an interpretation that the paradoxical increase of reaction time may be associated with strategy switching. Consistent with this interpretation, logistic regression analysis of the behavioral data suggested a presence of multiple decision strategies. Taken together, we found that a novel complex value-based decision-making task cause prominent activations in fronto-parietal cortex. Furthermore, we propose that these activations can be interpreted as recruitment of cognitive control system in complex situations.

Self-Controlled Choice Arises from Dynamic Prefrontal Signals That Enable Future Anticipation.

Self-control allows humans the patience necessary to maximize reward attainment in the future. Yet it remains elusive when and how the preference to self-controlled choice is formed. We measured brain activity while female and male humans performed an intertemporal choice task in which they first received delayed real liquid rewards (forced-choice trial), and then made a choice between the reward options based on the experiences (free-choice trial). We found that, while subjects were awaiting an upcoming reward in the forced-choice trial, the anterior prefrontal cortex (aPFC) tracked a dynamic signal reflecting the pleasure of anticipating the future reward. Importantly, this prefrontal signal was specifically observed in self-controlled individuals, and moreover, interregional negative coupling between the prefrontal region and the ventral striatum (VS) became stronger in those individuals. During consumption of the liquid rewards, reduced ventral striatal activity predicted self-controlled choices in the subsequent free-choice trials. These results suggest that a well-coordinated prefrontal-striatal mechanism during the reward experience shapes preferences regarding the future self-controlled choice.SIGNIFICANCE STATEMENT Anticipating future desirable events is a critical mental function that guides self-controlled behavior in humans. When and how are the self-controlled choices formed in the brain? We monitored brain activity while humans awaited a real liquid reward that became available in tens of seconds. We found that the frontal polar cortex tracked temporally evolving signals reflecting the pleasure of anticipating the future reward, which was enhanced in self-controlled individuals. Our results highlight the contribution of the fronto-polar cortex to the formation of self-controlled preferences, and further suggest that future prospect in the prefrontal cortex (PFC) plays an important role in shaping future choice behavior.

Intertemporal Decision-Making Involves Prefrontal Control Mechanisms Associated with Working Memory.

Intertemporal decision-making involves simultaneous evaluation of both the magnitude and delay to reward, which may require the integrated representation and comparison of these dimensions within working memory (WM). In the current study, neural activation associated with intertemporal decision-making was directly compared with WM load-related activation. During functional magnetic resonance imaging, participants performed an intermixed series of WM trials and intertemporal decision-making trials both varying in load, with the latter in terms of choice difficulty, via options tailored to each participant's subjective value function for delayed rewards. The right anterior prefrontal cortex (aPFC) and dorsolateral prefrontal cortex (dlPFC) showed activity modulation by choice difficulty within WM-related brain regions. In aPFC, these 2 effects (WM, choice difficulty) correlated across individuals. In dlPFC, activation increased with choice difficulty primarily in patient (self-controlled) individuals, and moreover was strongest when the delayed reward was chosen on the most difficult trials. Finally, the choice-difficulty effects in dlPFC and aPFC were correlated across individuals, suggesting a functional relationship between the 2 regions. Together, these results suggest a more precise account of the relationship between WM and intertemporal decision-making that is specifically tied to choice difficulty, and involves the coordinated activation of a lateral PFC circuit supporting successful self-control.

Dynamically Allocated Hub in Task-Evoked Network Predicts the Vulnerable Prefrontal Locus for Contextual Memory Retrieval in Macaques.

Neuroimaging and neurophysiology have revealed that multiple areas in the prefrontal cortex (PFC) are activated in a specific memory task, but severity of impairment after PFC lesions is largely different depending on which activated area is damaged. The critical relationship between lesion sites and impairments has not yet been given a clear mechanistic explanation. Although recent works proposed that a whole-brain network contains hubs that play integrative roles in cortical information processing, this framework relying on an anatomy-based structural network cannot account for the vulnerable locus for a specific task, lesioning of which would bring impairment. Here, we hypothesized that (i) activated PFC areas dynamically form an ordered network centered at a task-specific "functional hub" and (ii) the lesion-effective site corresponds to the "functional hub," but not to a task-invariant "structural hub." To test these hypotheses, we conducted functional magnetic resonance imaging experiments in macaques performing a temporal contextual memory task. We found that the activated areas formed a hierarchical hub-centric network based on task-evoked directed connectivity, differently from the anatomical network reflecting axonal projection patterns. Using a novel simulated-lesion method based on support vector machine, we estimated severity of impairment after lesioning of each area, which accorded well with a known dissociation in contextual memory impairment in macaques (impairment after lesioning in area 9/46d, but not in area 8Ad). The predicted severity of impairment was proportional to the network "hubness" of the virtually lesioned area in the task-evoked directed connectivity network, rather than in the anatomical network known from tracer studies. Our results suggest that PFC areas dynamically and cooperatively shape a functional hub-centric network to reallocate the lesion-effective site depending on the cognitive processes, apart from static anatomical hubs. These findings will be a foundation for precise prediction of behavioral impacts of damage or surgical intervention in human brains.

Impulsivity and self-control during intertemporal decision making linked to the neural dynamics of reward value representation.

A characteristic marker of impulsive decision making is the discounting of delayed rewards, demonstrated via choice preferences and choice-related brain activity. However, delay discounting may also arise from how subjective reward value is dynamically represented in the brain when anticipating an upcoming chosen reward. In the current study, brain activity was continuously monitored as human participants freely selected an immediate or delayed primary liquid reward and then waited for the specified delay before consuming it. The ventromedial prefrontal cortex (vmPFC) exhibited a characteristic pattern of activity dynamics during the delay period, as well as modulation during choice, that is consistent with the time-discounted coding of subjective value. The ventral striatum (VS) exhibited a similar activity pattern, but preferentially in impulsive individuals. A contrasting profile of delay-related and choice activation was observed in the anterior PFC (aPFC), but selectively in patient individuals. Functional connectivity analyses indicated that both vmPFC and aPFC exerted modulatory, but opposite, influences on VS activation. These results link behavioral impulsivity and self-control to dynamically evolving neural representations of future reward value, not just during choice, but also during postchoice delay periods.

Changes in cerebro-cerebellar interaction during response inhibition after performance improvement.

It has been demonstrated that motor learning is supported by the cerebellum and the cerebro-cerebellar interaction. Response inhibition involves motor responses and the higher-order inhibition that controls the motor responses. In this functional MRI study, we measured the cerebro-cerebellar interaction during response inhibition in two separate days of task performance, and detected the changes in the interaction following performance improvement. Behaviorally, performance improved in the second day, compared to the first day. The psycho-physiological interaction (PPI) analysis revealed the interaction decrease from the right inferior frontal cortex (rIFC) to the cerebellum (lobule VII or VI). It was also revealed that the interaction increased from the same cerebellar region to the primary motor area. These results suggest the involvement of the cerebellum in response inhibition, and raise the possibility that the performance improvement was supported by the changes in the cerebro-cerebellar interaction.

Dissociable neural representations of wrist motor coordinate frames in human motor cortices.

There is a growing interest in how the brain transforms body part positioning in the extrinsic environment into an intrinsic coordinate frame during motor control. To explore the human brain areas representing intrinsic and extrinsic coordinate frames, this fMRI study examined neural representation of motor cortices while human participants performed isometric wrist flexions and extensions in different forearm postures, thereby applying the same wrist actions (representing the intrinsic coordinate frame) to different movement directions (representing the extrinsic coordinate frame). Using sparse logistic regression, critical voxels involving pattern information that specifically discriminates wrist action (flexion vs. extension) and movement direction (upward vs. downward) were identified within the primary motor and premotor cortices. Analyses of classifier weights further identified contributions of the primary motor cortex to the intrinsic coordinate frame and the ventral and dorsal premotor cortex and supplementary motor area proper to the extrinsic coordinate frame. These results are consistent with existing findings using non-human primates and demonstrate the distributed representations of independent coordinate frames in the human brain.

Efficiency of go/no-go task performance implemented in the left hemisphere.

It is well known that the efficiency of response inhibition differs from person to person, but the neural mechanism that implements the efficiency is less understood. In the present fMRI study, we devised an index to evaluate the efficiency of response inhibition in the go/no-go task, and investigated the neural correlates of the efficiency of response inhibition. The human subjects who perform the go/no-go task with a shorter reaction time in go trials (Go-RT) and with a higher percentage of correct no-go trials (Nogo-PC) are thought to have the ability to conduct response inhibition more efficiently. To quantify the efficiency, we defined an efficiency index as the difference in the Nogo-PC between each subject and an ordinarily efficient subject, under the same Go-RT. An across-subject correlation analysis revealed that the brain activity in multiple regions in the left frontal and parietal cortex positively correlated with the efficiency index. Moreover, a test of hemispheric asymmetry with regard to the across-subject correlation revealed left-hemispheric dominance. The significant correlation in the left frontal and parietal regions complements the results of previous studies that used the stop-signal reaction time (SSRT), a well known index to evaluate the efficiency of response inhibition used in the stop-signal task. Our results also indicate that, although it is well known that the neural substrates for response inhibition common in a subject group exist dominantly in the right hemisphere, the neural substrates for efficiency exist dominantly in the left hemisphere.

Prefrontal cortex mediation of cognitive enhancement in rewarding motivational contexts.

Increasing the reward value of behavioral goals can facilitate cognitive processes required for goal achievement. This facilitation may be accomplished by the dynamic and flexible engagement of cognitive control mechanisms operating in distributed brain regions. It is still not clear, however, what are the characteristics of individuals, situations, and neural activation dynamics that optimize motivation-linked cognitive enhancement. Here we show that highly reward-sensitive individuals exhibited greater improvement of working memory performance in rewarding contexts, but exclusively on trials that were not rewarded. This effect was mediated by a shift in the temporal dynamics of activation within right lateral prefrontal cortex, from a transient to predominantly tonic mode, with an additional anticipatory transient boost. In contexts with intermittent rewards, a strategy of proactive cognitive control may enable globally optimal performance to facilitate reward attainment. Reward-sensitive individuals appear preferentially motivated to adopt this resource-demanding strategy, resulting in paradoxical benefits selectively for nonrewarded events.

The Stroop effect involves an excitatory-inhibitory fronto-cerebellar loop.

The Stroop effect is a classical, well-known behavioral phenomenon in humans that refers to robust interference between language and color information. It remains unclear, however, when the interference occurs and how it is resolved in the brain. Here we show that the Stroop effect occurs during perception of color-word stimuli and involves a cross-hemispheric, excitatory-inhibitory loop functionally connecting the lateral prefrontal cortex and cerebellum. Participants performed a Stroop task and a non-verbal control task (which we term the Swimmy task), and made a response vocally or manually. The Stroop effect involved the lateral prefrontal cortex in the left hemisphere and the cerebellum in the right hemisphere, independently of the response type; such lateralization was absent during the Swimmy task, however. Moreover, the prefrontal cortex amplified cerebellar activity, whereas the cerebellum suppressed prefrontal activity. This fronto-cerebellar loop may implement language and cognitive systems that enable goal-directed behavior during perceptual conflicts.

Cognitive Dynamics Estimation: A whole-brain spatial regression paradigm for extracting the temporal dynamics of cognitive processes.

Functional MRI (fMRI) has been instrumental in understanding how cognitive processes are spatially mapped in the brain, yielding insights about brain regions and functions. However, in case the orthogonality of behavioral or stimulus timing is not guaranteed, the estimated brain maps fail to dissociate each cognitive process, and the resultant maps become unstable. Also, the brain mapping exercise can not provide temporal information on the cognitive process. Here we propose a qualitatively different approach to fMRI analysis, named Cognitive Dynamics Estimation (CDE), that estimates how multiple cognitive processes change over time even when behavior or stimulus logs are unavailable. This method transposes the conventional brain mapping; the brain activity pattern at each time point is subject to regression analysis with data-driven maps of cognitive processes as regressors, resulting in the time series of cognitive processes. The estimated time series captured the fluctuation of intensity and timing of cognitive processes on a trial-by-trial basis, which conventional analysis could not capture. Notably, the estimated time series predicted participants' cognitive ability to perform each psychological task. As an addition to our fMRI analytic toolkit, these results suggest the potential for CDE to elucidate underexplored cognitive phenomena, especially in the temporal domain.

A method for reconstruction of interpretable brain networks from transient synchronization in resting-state BOLD fluctuations.

Resting-state (rs) fMRI has been widely used to examine brain-wide large-scale spatiotemporal architectures, known as resting-state networks (RSNs). Recent studies have focused on the temporally evolving characteristics of RSNs, but it is unclear what temporal characteristics are reflected in the networks. To address this issue, we devised a novel method for voxel-based visualization of spatiotemporal characteristics of rs-fMRI with a time scale of tens of seconds. We first extracted clusters of dominant activity-patterns using a region-of-interest approach and then used these temporal patterns of the clusters to obtain voxel-based activation patterns related to the clusters. We found that activation patterns related to the clusters temporally evolved with a characteristic temporal structure and showed mutual temporal alternations over minutes. The voxel-based representation allowed the decoding of activation patterns of the clusters in rs-fMRI using a meta-analysis of functional activations. The activation patterns of the clusters were correlated with behavioral measures. Taken together, our analysis highlights a novel approach to examine brain activity dynamics during rest.

Role for presupplementary motor area in inhibition of cognitive set interference.

Proactive interference (PI), which is formed through repetition of certain behavior and lasts for a while, needs to be inhibited in order for subsequent behavior to prevail over the antecedent one. Although the inhibitory mechanisms in the pFC have been reported that are recruited long after one behavior is updated to another, very little is known about the inhibitory mechanisms that are recruited immediately after the update. The WCST was modified in the present fMRI study such that inhibition of PI could be examined both immediately after and long after update of behavior. Use of "dual-match" stimuli allowed us to compare two types of trials where inhibition of PI was and was not required (control and release trials, respectively). Significant activation was observed in the left pre-SMA during control versus release trials. The pre-SMA activation was selective to PI inhibition required immediately after update of behavior, which exhibited marked contrast to the left anterior prefrontal activation selective to PI inhibition required long after the update. These results reveal dissociable inhibitory mechanisms in these two regions that are recruited in the different temporal contexts of the inhibitory demands imposed during performance of the task.