Functional connectivity with distinct neural networks tracks fluctuations in gain/loss framing susceptibility

Social feedback promotes positive social sharing, trust, and closeness

Positive social sharing is an interpersonal emotion regulation strategy that enhances positive affect and social belonging, particularly when met with positive social feedback. Despite the ubiquity of positive social sharing both in person and online, what drives this behavior is not well understood. We hypothesized that positive social feedback serves as a reward that reinforces sharing behavior and strengthens social bonds. Participants made trial-by-trial choices about whether to share social media photos with peers who returned positive ("likes") or negative ("dislikes") feedback. Unbeknownst to participants, peer conditions were manipulated to yield varying amounts of positive and negative feedback. Social bonding was subsequently measured using a trust game and subjective closeness ratings. Participants shared more with peers who provided greater rates of positive feedback. This effect generalized to trust decisions and subjective feelings of closeness and varied individually as a function of interpersonal emotion regulation in daily life. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Instructed motivational states bias reinforcement learning and memory formation

Motivation influences goals, decisions, and memory formation. Imperative motivation links urgent goals to actions, narrowing the focus of attention and memory. Conversely, interrogative motivation integrates goals over time and space, supporting rich memory encoding for flexible future use. We manipulated motivational states via cover stories for a reinforcement learning task: The imperative group imagined executing a museum heist, whereas the interrogative group imagined planning a future heist. Participants repeatedly chose among four doors, representing different museum rooms, to sample trial-unique paintings with variable rewards (later converted to bonus payments). The next day, participants performed a surprise memory test. Crucially, only the cover stories differed between the imperative and interrogative groups; the reinforcement learning task was identical, and all participants had the same expectations about how and when bonus payments would be awarded. In an initial sample and a preregistered replication, we demonstrated that imperative motivation increased exploitation during reinforcement learning. Conversely, interrogative motivation increased directed (but not random) exploration, despite the cost to participants' earnings. At test, the interrogative group was more accurate at recognizing paintings and recalling associated values. In the interrogative group, higher value paintings were more likely to be remembered; imperative motivation disrupted this effect of reward modulating memory. Overall, we demonstrate that a prelearning motivational manipulation can bias learning and memory, bearing implications for education, behavior change, clinical interventions, and communication.

Asthma's effect on brain connectivity and cognitive decline

Objective

To investigate the changes in dynamic voxel mirror homotopy connection (dVMHC) between cerebral hemispheres in patients with asthma.

Methods

Our study was designed using a case-control method. A total of 31 subjects with BA and 31 healthy subjects with matching basic information were examined using rsfMRI. We also calculated and obtained the dVMHC value between the cerebral cortexes.

Results

Compared with the normal control group, the dVMHC of the lingual gyrus (Ling) and the calcarine sulcus (CAL), which represented the visual network (VN), increased significantly in the asthma group, while the dVMHC of the medial superior frontal gyrus (MSFG), the anterior/middle/posterior cingulate gyrus (A/M/PCG), and the supplementary motor area (SMA) of the sensorimotor network decreased significantly in the asthma group.

Conclusion

This study showed that the ability of emotion regulation and the efficiency of visual and cognitive information processing in patients with BA was lower than in those in the HC group. The dVMHC analysis can be used to sensitively evaluate oxygen saturation, visual function changes, and attention bias caused by emotional disorders in patients with asthma, as well as to predict airway hyperresponsiveness, inflammatory progression, and dyspnea.

Reward enhances connectivity between the ventral striatum and the default mode network

The default mode network (DMN) has been theorized to participate in a range of social, cognitive, and affective functions. Yet, previous accounts do not consider how the DMN contributes to other brain regions depending on psychological context, thus rendering our understanding of DMN function incomplete. We addressed this gap by applying a novel network-based psychophysiological interaction (nPPI) analysis to the reward task within the Human Connectome Project. We first focused on the task-evoked responses of the DMN and other networks involving the prefrontal cortex, including the executive control network (salience network) and the left and right frontoparietal networks. Consistent with a host of prior studies, the DMN exhibited a relative decrease in activation during the task, while the other networks exhibited a relative increase during the task. Next, we used nPPI analyses to assess whether these networks exhibit task-dependent changes in connectivity with other brain regions. Strikingly, we found that the experience of reward enhances task-dependent connectivity between the DMN and the ventral striatum, an effect that was specific to the DMN. Surprisingly, the strength of DMN-VS connectivity was correlated with personality characteristics relating to openness. Taken together, these results advance models of DMN by demonstrating how it contributes to other brain systems during task performance and how those contributions relate to individual differences.

Decision neuroscience and neuroeconomics: Recent progress and ongoing challenges

In the past decade, decision neuroscience and neuroeconomics have developed many new insights in the study of decision making. This review provides an overarching update on how the field has advanced in this time period. Although our initial review a decade ago outlined several theoretical, conceptual, methodological, empirical, and practical challenges, there has only been limited progress in resolving these challenges. We summarize significant trends in decision neuroscience through the lens of the challenges outlined for the field and review examples where the field has had significant, direct, and applicable impacts across economics and psychology. First, we review progress on topics including reward learning, explore-exploit decisions, risk and ambiguity, intertemporal choice, and valuation. Next, we assess the impacts of emotion, social rewards, and social context on decision making. Then, we follow up with how individual differences impact choices and new exciting developments in the prediction and neuroforecasting of future decisions. Finally, we consider how trends in decision-neuroscience research reflect progress toward resolving past challenges, discuss new and exciting applications of recent research, and identify new challenges for the field. This article is categorized under: Psychology > Reasoning and Decision Making Psychology > Emotion and Motivation.

Social dysfunction is transdiagnostically associated with default mode network dysconnectivity in schizophrenia and Alzheimer's disease

OBJECTIVES

Social dysfunction is one of the most common signs of major neuropsychiatric disorders. The Default Mode Network (DMN) is crucially implicated in both psychopathology and social dysfunction, although the transdiagnostic properties of social dysfunction remains unknown. As part of the pan-European PRISM (Psychiatric Ratings using Intermediate Stratified Markers) project, we explored cross-disorder impact of social dysfunction on DMN connectivity.

METHODS

We studied DMN intrinsic functional connectivity in relation to social dysfunction by applying Independent Component Analysis and Dual Regression on resting-state fMRI data, among schizophrenia (SZ; N = 48), Alzheimer disease (AD; N = 47) patients and healthy controls (HC; N = 55). Social dysfunction was operationalised via the Social Functioning Scale (SFS) and De Jong-Gierveld Loneliness Scale (LON).

RESULTS

Both SFS and LON were independently associated with diminished DMN connectional integrity within rostromedial prefrontal DMN subterritories (p_corrected range = 0.02-0.04). The combined effect of these indicators (Mean.SFS + LON) on diminished DMN connectivity was even more pronounced (both spatially and statistically), independent of diagnostic status, and not confounded by key clinical or sociodemographic effects, comprising large sections of rostromedial and dorsomedial prefrontal cortex (p_corrected=0.01).

CONCLUSIONS

These findings pinpoint DMN connectional alterations as putative transdiagnostic endophenotypes for social dysfunction and could aid personalised care initiatives grounded in social behaviour.

Arbitration between insula and temporoparietal junction subserves framing-induced boosts in generosity during social discounting

Generosity toward others declines across the perceived social distance to them. Here, participants chose between selfish and costly generous options in two conditions: in the gain frame, a generous choice yielded a gain to the other; in the loss frame, it entailed preventing the loss of a previous endowment to the other. Social discounting was reduced in the loss compared to the gain frame, implying increased generosity toward strangers. Using neuroimaging tools, we found that while activity in the temporoparietal junction (TPJ) and the ventromedial prefrontal cortex (VMPFC) was associated with generosity in the gain frame, the insular cortex was selectively recruited during generous choices in the loss frame. We provide support for a network-model according to which TPJ and insula differentially subserve generosity by modulating value signals in the VMPFC in a frame-dependent fashion. These results extend our understanding of the insula role in nudging prosocial behavior in humans.

A Treatment-Response Comparison Study of Resting-State Functional Magnetic Resonance Imaging Between Standard Treatment of SSRI and Standard Treatment of SSRI Plus Non-dominant Hand-Writing Task in Patients With Major Depressive Disorder

Background: Researches have recently shifted from functional/structural imaging studies to functional connectivity (FC) studies in major depressive disorder (MDD). We aimed to compare treatment response of two treatment groups before and after treatment, in terms of both with psychiatric evaluation scales and resting-state functional connectivity (RSFC) changes in order to objectively demonstrate the possible contribution of the non-dominant hand-writing exercise (NHE) effect on depression treatment. Methods: A total of 26 patients who were right-handed women with similar sociodemographic characteristics were enrolled. Their pre-treatment resting-state functional magnetic resonance imaging (rs-fMRI) and neuropsychiatric tests were recorded, and then, patients were divided into two groups randomly. A standard treatment (ST) (fix sertraline 50 mg/day) was given to both groups. One randomly selected group was given the NHE in addition to the ST. After 8 weeks of treatment, all patients were reevaluated with rs-fMRI and neuropsychiatric tests. Pre- and post-treatment FC changes within the groups and post-treatment connectivity changes between groups were evaluated. Results: Post-treatment neuropsychiatric tests were significantly different in both groups. Post-treatment, two brain regions' connectivity changed in the ST group, whereas 10 brain regions' connectivity changed significantly in the ST + NHE group. When treatment groups were compared with each other after the treatment, the FC of 13 regions changed in the ST + NHE group compared to the ST group (p-unc/p-PFD <0.05). The density of connectivity changes in the frontal and limbic regions, especially connectivities shown to change in depression treatment, in the ST + NHE group indicates a positive contribution to depression treatment, which is also supported by neuropsychiatric scale changes. Conclusion: NHE, which we developed with inspiration from the Eye Movement Desensitization and Reprocessing (EMDR) method, showed significantly more connecitivity changes related with MDD treatment. Beyond offering a new additional treatment method, our study will also contribute to the current literature with our efforts to evaluate all brain regions and networks that may be related to MDD and its treatment together, without being limited to a few regions. Trial Registration: The rs-fMRI and treatment registers were recorded in the BizMed system, which is the patient registration system of Bezmialem Vakif University Medicine Faculty, under the BAP support project approval code and the registration number 3.2018/8.

Functional parcellation of the default mode network: a large-scale meta-analysis

The default mode network (DMN) consists of several regions that selectively interact to support distinct domains of cognition. Of the various sites that partake in DMN function, the posterior cingulate cortex (PCC), temporal parietal junction (TPJ), and medial prefrontal cortex (MPFC) are frequently identified as key contributors. Yet, it remains unclear whether these subcomponents of the DMN make unique contributions to specific cognitive processes and health conditions. To address this issue, we applied a meta-analytic parcellation approach used in prior work. This approach used the Neurosynth database and classification methods to quantify the association between PCC, TPJ, and MPFC activation and specific topics related to cognition and health (e.g., decision making and smoking). Our analyses replicated prior observations that the PCC, TPJ, and MPFC collectively support multiple cognitive functions such as decision making, memory, and awareness. To gain insight into the functional organization of each region, we parceled each region based on its coactivation pattern with the rest of the brain. This analysis indicated that each region could be further subdivided into functionally distinct subcomponents. Taken together, we further delineate DMN function by demonstrating the relative strengths of association among subcomponents across a range of cognitive processes and health conditions. A continued attentiveness to the specialization within the DMN allows future work to consider the nuances in sub-regional contributions necessary for healthy cognition, as well as create the potential for more targeted treatment protocols in various health conditions.

Default Mode Network Connectivity and Social Dysfunction in Major Depressive Disorder

Though social functioning is often hampered in Major Depressive Disorder (MDD), we lack a complete and integrated understanding of the underlying neurobiology. Connectional disturbances in the brain's Default Mode Network (DMN) might be an associated factor, as they could relate to suboptimal social processing. DMN connectional integrity, however, has not been explicitly studied in relation to social dysfunctioning in MDD patients. Applying Independent Component Analysis and Dual Regression on resting-state fMRI data, we explored DMN intrinsic functional connectivity in relation to social dysfunctioning (i.e. composite of loneliness, social disability, small social network) among 74 MDD patients (66.2% female, Mean age = 36.9, SD = 11.9). Categorical analyses examined whether DMN connectivity differs between high and low social dysfunctioning MDD groups, dimensional analyses studied linear associations between social dysfunction and DMN connectivity across MDD patients. Threshold-free cluster enhancement (TFCE) with family-wise error (FWE) correction was used for statistical thresholding and multiple comparisons correction (P < 0.05). The analyses cautiously linked greater social dysfunctioning among MDD patients to diminished DMN connectivity, specifically within the rostromedial prefrontal cortex and posterior superior frontal gyrus. These preliminary findings pinpoint DMN connectional alterations as potentially germane to social dysfunction in MDD, and may as such improve our understanding of the underlying neurobiology.

Individual differences in pain sensitivity are associated with cognitive network functional connectivity following one night of experimental sleep disruption

Previous work suggests that sleep disruption can contribute to poor pain modulation. Here, we used experimental sleep disruption to examine the relationship between sleep disruption-induced pain sensitivity and functional connectivity (FC) of cognitive networks contributing to pain modulation. Nineteen healthy individuals underwent two counterbalanced experimental sleep conditions for one night each: uninterrupted sleep versus sleep disruption. Following each condition, participants completed functional MRI including a simple motor task and a noxious thermal stimulation task. Pain ratings and stimulus temperatures from the latter task were combined to calculate a pain sensitivity change score following sleep disruption. This change score was used as a predictor of simple motor task FC changes using bilateral executive control networks (RECN, LECN) and the default mode network (DMN) masks as seed regions of interest (ROIs). Increased pain sensitivity after sleep disruption was positively associated with increased RECN FC to ROIs within the DMN and LECN (F_(4,14) = 25.28, pFDR = 0.05). However, this pain sensitivity change score did not predict FC changes using LECN and DMN masks as seeds (pFDR > 0.05). Given that only RECN FC was associated with sleep loss-induced hyperalgesia, findings suggest that cognitive networks only partially contribute to the sleep-pain dyad.

Omission of temporal nuisance regressors from dual regression can improve accuracy of fMRI functional connectivity maps

Functional connectivity (FC) maps from brain fMRI data can be derived with dual regression, a proposed alternative to traditional seed-based FC (SFC) methods that detect temporal correlation between a predefined region (seed) and other regions in the brain. As with SFC, incorporating nuisance regressors (NR) into the dual regression must be done carefully, to prevent potential bias and insensitivity of FC estimates. Here, we explore the potentially untoward effects on dual regression that may occur when NR correlate highly with the signal of interest, using both synthetic and real fMRI data to elucidate mechanisms responsible for loss of accuracy in FC maps. Our tests suggest significantly improved accuracy in FC maps derived with dual regression when highly correlated temporal NR were omitted. Single-map dual regression, a simplified form of dual regression that uses neither spatial nor temporal NR, offers a viable alternative whose FC maps may be more easily interpreted, and in some cases be more accurate than those derived with standard dual regression.

The intrinsic neural architecture of inhibitory control: The role of development and emotional experience

Inhibitory control is a key determinant of goal-directed behavior. Its susceptibility to reward implies that its variations may not only reflect cognitive ability, but also sensitivity to goal-relevant information. Since cognitive ability and motivational sensitivity vary as a function of age and mood, we hypothesized that their relevance for predicting individual differences in inhibition would similarly vary. Here, we tested this prediction with respect to the brain's intrinsic functional architecture. Specifically, we reasoned that age and affective functioning would both moderate the relationship between inhibition and resting state expression of the dynamic neural organization patterns linked to engaging in cognitive effort versus those involved in manipulating motivationally salient information. First, we used task fMRI data from the Human Connectome Project (N = 359 participants) to identify the brain organization patterns unique to effortful cognitive processing versus manipulation of motivationally relevant information. We then assessed the association between inhibitory control and relative expression of these two neural patterns in an independent resting state dataset from the Nathan Kline Institute-Rockland lifespan sample (N = 247). As hypothesized, the relation between inhibition and intrinsic functional brain architecture varied as a function of age and affective functioning. Among those with superior affective functioning, better inhibitory control in adolescence and early adulthood was associated with stronger resting state expression of the brain pattern that typified processing of motivationally salient information. The opposite effect emerged beyond the age of 49. Among individuals with poorer affective functioning, a significant link between inhibition and brain architecture emerged only before the age of 28. In this group, superior inhibition was associated with stronger resting state expression of the neural pattern that typified effortful cognitive processing. Our results thus imply that motivational relevance makes a unique contribution to superior cognitive functioning during earlier life stages. However, its relevance to higher-order mentation decreases with aging and increased prevalence of mood-related problems, which raises the possibility that patterns of neurobehavioral responsiveness to motivational salience may constitute sensitive markers of successful lifespan development.

Contextual and Developmental Differences in the Neural Architecture of Cognitive Control

Because both development and context impact functional brain architecture, the neural connectivity signature of a cognitive or affective predisposition may similarly vary across different ages and circumstances. To test this hypothesis, we investigated the effects of age and cognitive versus social-affective context on the stable and time-varying neural architecture of inhibition, the putative core cognitive control component, in a subsample (N = 359, 22-36 years, 174 men) of the Human Connectome Project. Among younger individuals, a neural signature of superior inhibition emerged in both stable and dynamic connectivity analyses. Dynamically, a context-free signature emerged as stronger segregation of internal cognition (default mode) and environmentally driven control (salience, cingulo-opercular) systems. A dynamic social-affective context-specific signature was observed most clearly in the visual system. Stable connectivity analyses revealed both context-free (greater default mode segregation) and context-specific (greater frontoparietal segregation for higher cognitive load; greater attentional and environmentally driven control system segregation for greater reward value) signatures of inhibition. Superior inhibition in more mature adulthood was typified by reduced segregation in the default network with increasing reward value and increased ventral attention but reduced cingulo-opercular and subcortical system segregation with increasing cognitive load. Failure to evidence this neural profile after the age of 30 predicted poorer life functioning. Our results suggest that distinguishable neural mechanisms underlie individual differences in cognitive control during different young adult stages and across tasks, thereby underscoring the importance of better understanding the interplay among dispositional, developmental, and contextual factors in shaping adaptive versus maladaptive patterns of thought and behavior.SIGNIFICANCE STATEMENT The brain's functional architecture changes across different contexts and life stages. To test whether the neural signature of a trait similarly varies, we investigated cognitive versus social-affective context effects on the stable and time-varying neural architecture of inhibition during a period of neurobehavioral fine-tuning (age 22-36 years). Younger individuals with superior inhibition showed distinguishable context-free and context-specific neural profiles, evidenced in both static and dynamic connectivity analyses. More mature individuals with superior inhibition evidenced only context-specific profiles, revealed in the static connectivity patterns linked to increased reward or cognitive load. Delayed expression of this profile predicted poorer life functioning. Our results underscore the importance of understanding the interplay among dispositional, developmental, and contextual factors in shaping behavior.

Reason's Enemy Is Not Emotion: Engagement of Cognitive Control Networks Explains Biases in Gain/Loss Framing

In the classic gain/loss framing effect, describing a gamble as a potential gain or loss biases people to make risk-averse or risk-seeking decisions, respectively. The canonical explanation for this effect is that frames differentially modulate emotional processes, which in turn leads to irrational choice behavior. Here, we evaluate the source of framing biases by integrating functional magnetic resonance imaging data from 143 human participants performing a gain/loss framing task with meta-analytic data from >8000 neuroimaging studies. We found that activation during choices consistent with the framing effect were most correlated with activation associated with the resting or default brain, while activation during choices inconsistent with the framing effect was most correlated with the task-engaged brain. Our findings argue against the common interpretation of gain/loss framing as a competition between emotion and control. Instead, our study indicates that this effect results from differential cognitive engagement across decision frames.SIGNIFICANCE STATEMENT The biases frequently exhibited by human decision makers have often been attributed to the presence of emotion. Using a large fMRI sample and analysis of whole-brain networks defined with the meta-analytic tool Neurosynth, we find that neural activity during frame-biased decisions was more significantly associated with default behaviors (and the absence of executive control) than with emotion. These findings point to a role for neuroscience in shaping long-standing psychological theories in decision science.

Neural signatures of experience-based improvements in deterministic decision-making

Feedback about our choices is a crucial part of how we gather information and learn from our environment. It provides key information about decision experiences that can be used to optimize future choices. However, our understanding of the processes through which feedback translates into improved decision-making is lacking. Using neuroimaging (fMRI) and cognitive models of decision-making and learning, we examined the influence of feedback on multiple aspects of decision processes across learning. Subjects learned correct choices to a set of 50 word pairs across eight repetitions of a concurrent discrimination task. Behavioral measures were then analyzed with both a drift-diffusion model and a reinforcement learning model. Parameter values from each were then used as fMRI regressors to identify regions whose activity fluctuates with specific cognitive processes described by the models. The patterns of intersecting neural effects across models support two main inferences about the influence of feedback on decision-making. First, frontal, anterior insular, fusiform, and caudate nucleus regions behave like performance monitors, reflecting errors in performance predictions that signal the need for changes in control over decision-making. Second, temporoparietal, supplementary motor, and putamen regions behave like mnemonic storage sites, reflecting differences in learned item values that inform optimal decision choices. As information about optimal choices is accrued, these neural systems dynamically adjust, likely shifting the burden of decision processing from controlled performance monitoring to bottom-up, stimulus-driven choice selection. Collectively, the results provide a detailed perspective on the fundamental ability to use past experiences to improve future decisions.

All framing effects are not created equal: Low convergent validity between two classic measurements of framing

Human risk-taking attitudes can be influenced by two logically equivalent but descriptively different frames, termed the framing effect. The classic hypothetical vignette-based task (Asian disease problem) and a recently developed reward-based gambling task have been widely used to assess individual differences in the framing effect. Previous studies treat framing bias as a stable trait that has genetic basis. However, these two paradigms differ in terms of task domain (loss vs. gain) and task context (vignette-based vs. reward-based) and the convergent validity of these measurements remains unknown. Here, we developed a vignette-based task and a gambling task in both gain and loss domains and tested correlations of the framing effect among these tasks in 159 young adults. Our results revealed no significant correlation between the vignette-based task in the loss domain and the gambling task in the gain domain, indicating low convergent validity. The current findings raise the question of how to measure the framing effect precisely, especially in individual difference studies using large samples and expensive neuroscience methods. Our results suggest that the framing effect is influenced by both task domain and task context and future research should be cautious about the operationalization of the framing effect.

Toward a cumulative science of functional integration: A meta-analysis of psychophysiological interactions

Much of the work in cognitive neuroscience is shifting from a focus on single brain regions to a focus on the connectivity between multiple brain regions. These inter-regional connectivity patterns contribute to a wide range of behaviors and are studied with models of functional integration. The rapid expansion of the literature on functional integration offers an opportunity to scrutinize the consistency and specificity of one of the most popular approaches for quantifying connectivity: psychophysiological interaction (PPI) analysis. We performed coordinate-based meta-analyses on 284 PPI studies, which allowed us to test (a) whether those studies consistently converge on similar target regions and (b) whether the identified target regions are specific to the chosen seed region and psychological context. Our analyses revealed two key results. First, we found that different types of PPI studies-e.g., those using seeds such as amygdala and dorsolateral prefrontal cortex (DLPFC) and contexts such as emotion and cognitive control, respectively-each consistently converge on similar target regions, thus supporting the reliability of PPI as a tool for studying functional integration. Second, we also found target regions that were specific to the chosen seed region and psychological context, indicating distinct patterns of brain connectivity. For example, the DLPFC seed reliably contributed to a posterior cingulate cortex target during cognitive control but contributed to an amygdala target in other contexts. Our results point to the robustness of PPI while highlighting common and distinct patterns of functional integration, potentially advancing models of brain connectivity. Hum Brain Mapp 37:2904-2917, 2016. © 2016 Wiley Periodicals, Inc.

Distinct Reward Properties are Encoded via Corticostriatal Interactions

The striatum serves as a critical brain region for reward processing. Yet, understanding the link between striatum and reward presents a challenge because rewards are composed of multiple properties. Notably, affective properties modulate emotion while informative properties help obtain future rewards. We approached this problem by emphasizing affective and informative reward properties within two independent guessing games. We found that both reward properties evoked activation within the nucleus accumbens, a subregion of the striatum. Striatal responses to informative, but not affective, reward properties predicted subsequent utilization of information for obtaining monetary reward. We hypothesized that activation of the striatum may be necessary but not sufficient to encode distinct reward properties. To investigate this possibility, we examined whether affective and informative reward properties were differentially encoded in corticostriatal interactions. Strikingly, we found that the striatum exhibited dissociable connectivity patterns with the ventrolateral prefrontal cortex, with increasing connectivity for affective reward properties and decreasing connectivity for informative reward properties. Our results demonstrate that affective and informative reward properties are encoded via corticostriatal interactions. These findings highlight how corticostriatal systems contribute to reward processing, potentially advancing models linking striatal activation to behavior.

Using fMRI to study reward processing in humans: past, present, and future

Functional magnetic resonance imaging (fMRI) is a noninvasive tool used to probe cognitive and affective processes. Although fMRI provides indirect measures of neural activity, the advent of fMRI has allowed for1) the corroboration of significant animal findings in the human brain, and2) the expansion of models to include more common human attributes that inform behavior. In this review, we briefly consider the neural basis of the blood oxygenation level dependent signal to set up a discussion of how fMRI studies have applied it in examining cognitive models in humans and the promise of using fMRI to advance such models. Specifically, we illustrate the contribution that fMRI has made to the study of reward processing, focusing on the role of the striatum in encoding reward-related learning signals that drive anticipatory and consummatory behaviors. For instance, we discuss how fMRI can be used to link neural signals (e.g., striatal responses to rewards) to individual differences in behavior and traits. While this functional segregation approach has been constructive to our understanding of reward-related functions, many fMRI studies have also benefitted from a functional integration approach that takes into account how interconnected regions (e.g., corticostriatal circuits) contribute to reward processing. We contend that future work using fMRI will profit from using a multimodal approach, such as combining fMRI with noninvasive brain stimulation tools (e.g., transcranial electrical stimulation), that can identify causal mechanisms underlying reward processing. Consequently, advancements in implementing fMRI will promise new translational opportunities to inform our understanding of psychopathologies.

Neural Correlates of Response to Pharmacotherapy in Obsessive-Compulsive Disorder: Individualized Cortical Morphology-Based Structural Covariance

BACKGROUND

Primary pharmacotherapy regimen for obsessive-compulsive disorder (OCD) named Serotonin reuptake inhibitors (SRIs) does not attain sufficient symptom improvement in 40-60% of OCD. We aimed to decode the differential profile of OCD-related brain pathology per subject in the context of cortical surface area (CSA) or thickness (CT)-based individualized structural covariance (ISC) and to demonstrate the potential of which as a biomarker of treatment response to SRI-based pharmacotherapy in OCD using the support vector machine (SVM).

METHODS

T1-weighted magnetic resonance imaging was obtained at 3T from 56 unmedicated OCD subjects and 75 healthy controls (HCs) at baseline. After 4months of SRI-based pharmacotherapy, the OCD subjects were classified as responders (OCD-R,N=25; ≥35% improvement) or nonresponders (OCD-NR,N=31; <35% improvement) according to the percentage change in the Yale-Brown Obsessive Compulsive Scale total score. Cortical ISCs sustaining between-group difference (p<.001) for every run of leave-one-out group-comparison were packaged as feature set for group classification using the SVM.

RESULTS

An optimal feature set of the top 12 ISCs including a CT-ISC between the dorsolateral prefrontal cortex versus precuneus, a CSA-ISC between the anterior insula versus intraparietal sulcus, as well as perisylvian area-related ISCs predicted the initial prognosis of OCD as OCD-R or OCD-NR with an accuracy of 89.0% (sensitivity 88.4%, specificity 90.1%). Extended sets of ISCs distinguished the OCD subjects from the HCs with 90.7-95.6% accuracy (sensitivity 90.8-96.2%, specificity 91.1-95.0%).

CONCLUSION

We showed the potential of cortical morphology-based ISCs, which reflect dysfunctional cortical maturation process, as a possible biomarker that predicts the clinical treatment response to SRI-based pharmacotherapy in OCD.