Electrophysiological underpinnings of reward processing: Are we exploiting the full potential of EEG?

Theta-Gamma Decoupling - A neurophysiological marker of impaired reward processing in Parkinson's disease

Individuals with Parkinson's disease (PD) exhibit altered reward processing, reflected by a decreased amplitude of an event-related potential (ERP) marker called reward positivity (RewP). Most studies have used RewP to investigate reward behavior due to the high temporal resolution of EEG and its high sensitivity. However, traditional single-electrode ERP analyses often overlook the intricate dynamics of non-phase-locked oscillatory activity and the complex interactions within these neural oscillatory patterns. Studying oscillatory activity is crucial as it provides mechanistic insights into the functional, spatial, and temporal aspects of neuronal processing. To address this gap, we employed a data-driven approach to identify EEG-based markers associated with PD reward processing deficits. Using an openly available 64-channel EEG dataset of 28 age- and sex-matched PD and control participants during a reinforcement learning task, we conducted a comprehensive secondary analysis. First, we employed a cluster-based permutation method to extract ERP markers, finding a consistent decrease in reward positivity in PD, regardless of medication status. Additionally, through region of interest (ROI) analysis on time-frequency data, we identified specific oscillatory patterns during reward processing. PD patients exhibited attenuated theta power and increased gamma power compared to healthy controls (HC). Notably, within the PD group, those off medication showed anterior localization of high gamma power, while those on medication displayed higher posterior gamma power. Building upon these findings, we explored phase-amplitude coupling between theta phase and gamma amplitude measured by the modulation index. We observed a trend of decreased theta-gamma coupling in PD patients, with statistically significant differences between on and off medication conditions. These results highlight the potential role of theta-gamma coupling as a neuromodulatory target for improving goal-oriented behavior in PD. Our correlation analyses suggest that high gamma power is linked to longer disease duration, while reduced reward positivity and low theta-gamma coupling may serve as markers of the dopaminergic impact on reward processing. Thus, our study unveils the intricate time-frequency dynamics underlying reward processing deficits in PD, emphasizing the utility of a data-driven approach to elucidate neural mechanisms and to identify potential therapeutic targets.

Mechanisms of Proactive Adaptation in a Rewarded Response Inhibition Task: Executive, Motor, or Attentional Effects?

A growing number of studies have demonstrated the effects of reward motivation on inhibitory control performance. However, the exact neurocognitive mechanisms supporting these effects are not fully elucidated. In this preregistered study, we test the hypothesis that changes in speed-accuracy trade-off across contexts that alternatively incentivize fast responses versus accurate inhibition rely on a modulation of proactive inhibitory control, a mechanism intended to lock movement initiation in anticipation of stimulus presentation. Thirty healthy participants performed a modified Go/NoGo task in which the motivation to prioritize Go vs. NoGo successes was manipulated using monetary rewards of different magnitudes. High-density EEG was recorded throughout the task. Source-space analyses were performed to track brain oscillatory activities consistent with proactive inhibitory control. We observed that participants adapted their behavior to the motivational context but found no evidence that this adaptation relied on a modulation of proactive inhibitory control, hence failing to provide support for our pre-registered hypothesis. Unplanned analyses of brain-behavior relationships suggested an association between faster reaction times and enhanced top-down attention to the stimuli associated with larger rewards, as well as between increased commission error rates and stronger motor activations when Go stimuli were associated with larger rewards. The latter was related to inter-individual differences in trait reward responsiveness. These results highlight the need to carefully parse the different contributing mechanisms when studying the influence of reward motivation on inhibitory performance in impulsivity disorders. Exploratory results suggest alternative mechanisms that may be directly tested in further studies.

Intrinsic brain activity differences in drug-resistant epilepsy and well-controlled epilepsy patients: an EEG microstate analysis

Background

Drug-resistant epilepsy (DRE) patients exhibit aberrant large-scale brain networks.

Objective

The purpose of investigation is to explore the differences in resting-state electroencephalogram (EEG) microstates between patients with DRE and well-controlled (W-C) epilepsy.

Design

Retrospective study.

Methods

Clinical data of epilepsy patients treated at the Epilepsy Center of Fujian Medical University Union Hospital from January 2020 to May 2023 were collected for a minimum follow-up period of 2 years. Participants meeting inclusion and exclusion criteria were categorized into two groups based on follow-up records: W-C group and DRE group. To ensure that the recorded EEG data were not influenced by medication, all EEG recordings were collected before patients commenced any antiepileptic drug treatment. Resting-state EEG datasets of all participants underwent microstate analysis. This study comprehensively compared the average duration, frequency per second, coverage, and transition probabilities (TPs) of each microstate between the two groups.

Results

A total of 289 individuals who met the criteria were included, categorized into the W-C group (n = 112) and the DRE group (n = 177). EEG microstate analysis revealed substantial variances between the two groups. The analysis highlights differences in three of four microstate classifications. Microstate transition analysis demonstrated altered probabilities in DRE patients. Increased probabilities were observed in TPAB, TPBA, TPBC, TPCB, TPBD, and TPDB. Decreased probabilities included TPCA, TPDA, TPAC, TPAD, TPCD, and TPDC.

Conclusion

This study highlights distinctive EEG microstate parameters and TPs in DRE patients compared to those with W-C epilepsy. The results may potentially advance the clinical application of EEG microstates.

Frontal midline theta power during the cue-target-interval reflects increased cognitive effort in rewarded task-switching

Cognitive performance largely depends on how much effort is invested during task-execution. This also means that we rarely perform as good as we could. Cognitive effort is adjusted to the expected outcome of performance, meaning that it is driven by motivation. The results from recent studies suggest that the expenditure of cognitive control is particularly prone to being affected by modulations of cognitive effort. Although recent EEG studies investigated the neural underpinnings of the interaction of effort and control, reports on how cognitive effort is reflected by oscillatory activity of the EEG are quite sparse. It is the goal of the present study to bridge this gap by performing an exploratory analysis of high-density EEG data from a switching-task using manipulations of monetary incentives. A beamformer approach is used to localize the sensor-level effects in source-space. The results indicate that the manipulation of cognitive effort was successful. The participants reported significantly higher motivation and cognitive effort in high versus low reward trials. Performance was also significantly increased. The analysis of the EEG data revealed that the increase of cognitive effort was reflected by an increased mid-frontal theta activity during the cue-target interval, suggesting an increased use of proactive control. This interpretation is supported by the result from a regression analysis performed on single-trial data, showing higher mid-frontal theta power prior to target-onset being associated with faster responses. Alpha-desynchronization throughout the trial was also more pronounced in high reward trials, signaling a bias of attention towards the processing of external stimuli. Source reconstruction suggests that these effects are located in areas related to cognitive control, and visual processing.

Neural dynamics underlying the illusion of control during reward processing

The illusion of control refers to a behavioral bias in which people believe they have greater control over completely stochastic events than they actually do, leading to an inflated estimate of reward probability than objective probability warrants. In this study, we examined how reward system is modulated by the illusion of control through the lens of neural dynamics. Participants in a behavioral task exhibited a classical illusion of control, assigning a higher value to the gambling wheels they picked themselves than to those given randomly. An event-related potential study of the same task revealed that this behavioral bias is associated with reduced reward anticipation, as indexed by the stimulus-preceding negativity, diminished positive prediction error signals, as reflected by the reward positivity, and enhanced motivational salience, as revealed by the P300. Our findings offer a mechanistic understanding of the illusion of control in terms of reward dynamics.

Concurrent behavioral modeling and multimodal neuroimaging reveals how feedback affects the performance of decision making in internet gaming disorder

Internet gaming disorder (IGD) prompts inquiry into how feedback from prior gaming rounds influences subsequent risk-taking behavior and potential neural mechanisms. Forty-two participants, including 15 with IGD and 27 health controls (HCs), underwent a sequential risk-taking task. Hierarchy Bayesian modeling was adopted to measure risky propensity, behavioral consistence, and affection by emotion ratings from last trial. Concurrent electroencephalogram and functional near-infrared spectroscopy (EEG-fNIRS) recordings were performed to demonstrate when, where and how the previous-round feedback affects the decision making to the next round. We discovered that the IGD illustrated heightened risk-taking propensity as compared to the HCs, indicating by the computational modeling (p = 0.028). EEG results also showed significant time window differences in univariate and multivariate pattern analysis between the IGD and HCs after the loss of the game. Further, reduced brain activation in the prefrontal cortex during the task was detected in IGD as compared to that of the control group. The findings underscore the importance of understanding the aberrant decision-making processes in IGD and suggest potential implications for future interventions and treatments aimed at addressing this behavioral addiction.

Loneliness and brain rhythmic activity in resting state: an exploratory report

Recent studies using resting-state functional magnetic resonance imaging have shown that loneliness is associated with altered blood oxygenation in several brain regions. However, the relationship between loneliness and changes in neuronal rhythm activity in the brain remains unclear. To evaluate brain rhythm, we conducted an exploratory resting-state electroencephalogram (EEG) study of loneliness. We recorded resting-state EEG signals from 139 participants (94 women; mean age = 19.96 years) and analyzed power spectrum density (PSD) and functional connectivity (FC) in both the electrode and source spaces. The PSD analysis revealed significant correlations between loneliness scores and decreased beta-band powers, which may indicate negative emotion, attention, reward, and/or sensorimotor processing. The FC analysis revealed a trend of alpha-band FC associated with individuals' loneliness scores. These findings provide new insights into the neural basis of loneliness, which will facilitate the development of neurobiologically informed interventions for loneliness.

Feedback negativity and feedback-related P3 in individuals at risk for depression: Comparing surface potentials and current source densities

Blunted responses to reward feedback have been linked to major depressive disorder (MDD) and depression risk. Using a monetary incentive delay task (win, loss, break-even), we investigated the impact of family risk for depression and lifetime history of MDD and anxiety disorder with 72-channel electroencephalograms (EEG) recorded from 29 high-risk and 32 low-risk individuals (15-58 years, 30 male). Linked-mastoid surface potentials (ERPs) and their corresponding reference-free current source densities (CSDs) were quantified by temporal principal components analysis (PCA). Each PCA solution revealed a midfrontal feedback negativity (FN; peak around 310 ms) and a posterior feedback-P3 (fb-P3; 380 ms) as two distinct reward processing stages. Unbiased permutation tests and multilevel modeling of component scores revealed greater FN to loss than win and neutral for all stratification groups, confirming FN sensitivity to valence. Likewise, all groups had greater fb-P3 to win and loss than neutral, confirming that fb-P3 indexes motivational salience and allocation of attention. By contrast, group effects were subtle, dependent on data transformation (ERP, CSD), and did not confirm reduced FN or fb-P3 for at-risk individuals. Instead, CSD-based fb-P3 was overall reduced in individuals with than without MDD history, whereas ERP-based fb-P3 was greater for high-risk individuals than for low-risk individuals for monetary, but not neutral outcomes. While the present findings do not support blunted reward processing in depression and depression risk, our side-by-side comparison underscores how the EEG reference choice affects the characterization of subtle group differences, strongly advocating the use of reference-free techniques.

Intrinsic brain activity differences in perampanel-responsive and non-responsive drug-resistant epilepsy patients: an EEG microstate analysis

Background

Drug-resistant epilepsy (DRE) patients exhibit aberrant large-scale brain networks. Perampanel may be a therapeutic option for controlling seizures in these patients.

Objective

We aim to explore the differences of resting-state electroencephalogram (EEG) microstate in perampanel-responsive and non-responsive DRE patients.

Design

Retrospective study.

Methods

Clinical data were collected from DRE patients who received perampanel treatment at the Fujian Medical University Union Hospital from June 2020 to September 2021, with a minimum follow-up of 6 months. Patients were classified into three groups based on the extent of reduction in seizure frequency: non-responsive (seizure reduction <50%), responsive (seizure reduction >50% but not seizure-free), and seizure-free. Resting-state EEG data sets of all participants were subjected to EEG microstate analysis. The study comprehensively compared the mean duration, frequency per second, and temporal coverage of each microstate among the three groups.

Results

A total of 76 perampanel-treated DRE patients were categorized into three groups based on their response to treatment: non-responsive (n = 20), responsive (n = 36), and seizure-free (n = 20), according to the degree of seizure frequency reduction. The results of EEG microstate analysis revealed no statistically significant distinctions in frequency, duration, and coverage of microstate D in these DRE patients. However, the seizure-free group showed significantly increased duration and coverage of microstate A, frequency and coverage of microstate B, and significantly decreased duration, frequency, and coverage of microstate C when compared with the other groups.

Conclusion

Microstate A, B, and D is associated with the sensorimotor network, visual network, salience network, and attention network, respectively. This study demonstrates statistically significant differences in the sensorimotor, visual, and salience networks, but not in the attention network, between perampanel-responsive and non-responsive DRE patients.

Dissociable neural after-effects of cognitive and physical effort expenditure during reward evaluation

The reward after-effect of effort expenditure refers to the phenomenon that previous effort investment changes the subjective value of rewards when obtained. However, the neural mechanisms underlying the after-effects of effort exertion are still not fully understood. We investigated the modulation of reward after-effects by effort type (cognitive vs. physical) through the lens of neural dynamics. Thirty-two participants performed a physically or cognitively demanding task during an effort phase and then played a simple gambling game during a subsequent reward phase to earn monetary rewards while their electroencephalogram (EEG) was recorded. We found that previous effort expenditure decreased electrocortical activity during feedback evaluation. Importantly, this effort effect occurred in a domain-general manner during the early stage (as indexed by the reward positivity) but in a domain-specific manner during the later and more elaborative stage (as indexed by the P3 and delta oscillation) of reward evaluation. Additionally, effort expenditure enhanced P3 sensitivity to feedback valence regardless of effort type. Our findings suggest that cognitive and physical effort, although bearing some surface resemblance to each other, may have dissociable neural influences on the reward after-effects.

Comparing monetary gain and loss in the monetary incentive delay task: EEG evidence

What is more effective to guide behavior: The desire to gain or the fear to lose? Electroencephalography (EEG) studies have yielded inconsistent answers. In a systematic exploration of the valence and magnitude parameters in monetary gain and loss processing, we used time-domain and time-frequency-domain analyses to uncover the underlying neural processes. A group of 24 participants performed a monetary incentive delay (MID) task in which cue-induced anticipation of a high or low magnitude of gain or loss was manipulated trial-wise. Behaviorally, the anticipation of both gain and loss expedited responses, with gain anticipation producing greater facilitation than loss anticipation. Analyses of cue-locked P2 and P3 components revealed the significant valence main effect and valence × magnitude interaction: amplitude differences between high and low incentive magnitudes were larger with gain vs. loss cues. However, the contingent negative variation component was sensitive to incentive magnitude but did not vary with incentive valence. In the feedback phase, the RewP component exhibited reversed patterns for gain and loss trials. Time-frequency analyses revealed a large increase in delta/theta-ERS oscillatory activity in high- vs. low-magnitude conditions and a large decrease of alpha-ERD oscillatory activity in gain vs. loss conditions in the anticipation stage. In the consumption stage, delta/theta-ERS turned out stronger for negative than positive feedback, especially in the gain condition. Overall, our study provides new evidence for the neural oscillatory features of monetary gain and loss processing in the MID task, suggesting that participants invested more attention under gain and high-magnitude conditions vs. loss and low-magnitude conditions.

Allostatic-interoceptive anticipation of social rejection

Anticipating social stress evokes strong reactions in the organism, including interoceptive modulations. However, evidence for this claim comes from behavioral studies, often with inconsistent results, and relates almost solely to the reactive and recovery phase of social stress exposure. Here, we adopted an allostatic-interoceptive predictive coding framework to study interoceptive and exteroceptive anticipatory brain responses using a social rejection task. We analyzed the heart-evoked potential (HEP) and task-related oscillatory activity of 58 adolescents via scalp EEG, and 385 human intracranial recordings of three patients with intractable epilepsy. We found that anticipatory interoceptive signals increased in the face of unexpected social outcomes, reflected in larger negative HEP modulations. Such signals emerged from key brain allostatic-interoceptive network hubs, as shown by intracranial recordings. Exteroceptive signals were characterized by early activity between 1-15 Hz across conditions, and modulated by the probabilistic anticipation of reward-related outcomes, observed over distributed brain regions. Our findings suggest that the anticipation of a social outcome is characterized by allostatic-interoceptive modulations that prepare the organism for possible rejection. These results inform our understanding of interoceptive processing and constrain neurobiological models of social stress.

Use of experimental medicine approaches for the development of novel psychiatric treatments based on orexin receptor modulation

Despite progress in understanding the pathological mechanisms underlying psychiatric disorders, translation from animal models into clinical use remains a significant bottleneck. Preclinical studies have implicated the orexin neuropeptide system as a potential target for psychiatric disorders through its role in regulating emotional, cognitive, and behavioral processes. Clinical studies are investigating orexin modulation in addiction and mood disorders. Here we review performance-outcome measures (POMs) arising from experimental medicine research methods which may show promise as markers of efficacy of orexin receptor modulators in humans. POMs provide objective measures of brain function, complementing patient-reported or clinician-observed symptom evaluation, and aid the translation from preclinical to clinical research. Significant challenges include the development, validation, and operationalization of these measures. We suggest that collaborative networks comprising clinical practitioners, academics, individuals working in the pharmaceutical industry, drug regulators, patients, patient advocacy groups, and other relevant stakeholders may provide infrastructure to facilitate validation of experimental medicine approaches in translational research and in the implementation of these approaches in real-world clinical practice.

Exploring Neural Mechanisms of Reward Processing Using Coupled Matrix Tensor Factorization: A Simultaneous EEG-fMRI Investigation

BACKGROUND

It is crucial to understand the neural feedback mechanisms and the cognitive decision-making of the brain during the processing of rewards. Here, we report the first attempt for a simultaneous electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) study in a gambling task by utilizing tensor decomposition.

METHODS

First, the single-subject EEG data are represented as a third-order spectrogram tensor to extract frequency features. Next, the EEG and fMRI data are jointly decomposed into a superposition of multiple sources characterized by space-time-frequency profiles using coupled matrix tensor factorization (CMTF). Finally, graph-structured clustering is used to select the most appropriate model according to four quantitative indices.

RESULTS

The results clearly show that not only are the regions of interest (ROIs) found in other literature activated, but also the olfactory cortex and fusiform gyrus which are usually ignored. It is found that regions including the orbitofrontal cortex and insula are activated for both winning and losing stimuli. Meanwhile, regions such as the superior orbital frontal gyrus and anterior cingulate cortex are activated upon winning stimuli, whereas the inferior frontal gyrus, cingulate cortex, and medial superior frontal gyrus are activated upon losing stimuli.

CONCLUSION

This work sheds light on the reward-processing progress, provides a deeper understanding of brain function, and opens a new avenue in the investigation of neurovascular coupling via CMTF.

The potential application of event-related potentials to enhance research on reward processes in eating disorders

OBJECTIVE

Reward-related processes have been posited as key mechanisms underlying the onset and persistence of eating disorders, prompting a growing body of research in this area. Existing studies have primarily utilized self-report, behavioral, and functional magnetic resonance imaging measures to interrogate reward among individuals with eating disorders. However, limitations inherent in each of these methods (e.g., poor temporal resolution) may obscure distinct neurocognitive reward processes, potentially contributing to underdeveloped models of reward dysfunction within eating disorders. The temporal precision of event-related potentials (ERPs), derived from electroencephalography, may thus offer a powerful complementary tool for elucidating the neurocognitive underpinnings of reward. Indeed, a considerable amount of research in other domains of psychopathology (e.g., depression, substance use disorders), as well as studies investigating food reward among non-clinical samples, highlights the utility of ERPs for probing reward processes. However, no study to date has utilized ERPs to directly examine reward functioning in eating disorders.

METHODS

In this paper, we review evidence underscoring the clinical utility of ERP measures of reward, as well as a variety of reward-related tasks that can be used to elicit specific ERP components with demonstrated relevance to reward processing. We then consider the ways in which these tasks/components may be used to help answer a variety of open questions within the eating disorders literature on reward.

RESULTS/DISCUSSION

Given the promise of ERP measures of reward to the field of eating disorders, we ultimately hope to spur and guide research in this currently neglected area.

PUBLIC SIGNIFICANCE

Abnormalities in reward functioning appear to contribute to eating disorders. Event-related potentials (ERPs) offer temporally precise measures of neurocognitive reward processing and thus may be important tools for understanding the relationship between reward and disordered eating. However, research in this area is currently lacking. This paper attempts to facilitate the use of ERPs to study reward among individuals with eating disorders by reviewing the relevant theories and methods.

Diagnostic and prognostic EEG analysis of critically ill patients: A deep learning study

Visual interpretation of electroencephalography (EEG) is time consuming, may lack objectivity, and is restricted to features detectable by a human. Computer-based approaches, especially deep learning, could potentially overcome these limitations. However, most deep learning studies focus on a specific question or a single pathology. Here we explore the potential of deep learning for EEG-based diagnostic and prognostic assessment of patients with acute consciousness impairment (ACI) of various etiologies. EEGs from 358 adults from a randomized controlled trial (CERTA, NCT03129438) were retrospectively analyzed. A convolutional neural network was used to predict the clinical outcome (based either on survival or on best cerebral performance category) and to determine the etiology (four diagnostic categories). The largest probability output served as marker for the confidence of the network in its prediction ("certainty factor"); we also systematically compared the predictions with raw EEG data, and used a visualization algorithm (Grad-CAM) to highlight discriminative patterns. When all patients were considered, the area under the receiver operating characteristic curve (AUC) was 0.721 for predicting survival and 0.703 for predicting the outcome based on best CPC; for patients with certainty factor ≥ 60 % the AUCs increased to 0.776 and 0.755 respectively; and for certainty factor ≥ 75 % to 0.852 and 0.879. The accuracy for predicting the etiology was 54.5 %; the accuracy increased to 67.7 %, 70.3 % and 84.1 % for patients with certainty factor of 50 %, 60 % and 75 % respectively. Visual analysis showed that the network learnt EEG patterns typically recognized by human experts, and suggested new criteria. This work demonstrates for the first time the potential of deep learning-based EEG analysis in critically ill patients with various etiologies of ACI. Certainty factor and post-hoc correlation of input data with prediction help to better characterize the method and pave the route for future implementations in clinical routine.

Expectations of immediate and delayed reward differentially affect cognitive task performance

The current study used a modified Monetary Incentive Delay task to examine the neural mechanisms underlying anticipating and receiving an immediate or delayed reward and examined the influence of pursuing these rewards on cognitive task performance. A pre-cue indicating the potential of gaining a monetary reward (immediate-, delayed-, vs. no-reward) was followed by a target stimulus requiring a fast and accurate response. Then, response-contingent feedback was presented indicating whether or not the participant would receive the corresponding reward. Linear mixed-effect models revealed the fastest behavioural responses and the strongest neural activity, as reflected in event-related-potentials and event-related-spectral-perturbation responses, for immediate reward, followed by delayed reward, with the slowest behavioural responses and the weakest neural activities observed in the no-reward condition. Expectations related to the cue-P3 component and the cue-delta activities predicted behavioural performance, especially in the immediate reward condition. Moreover, exploratory analyses revealed that depression moderated the relationship between target-locked neural activity and behavioural performance in the delayed reward condition, with lower neural activity being related to worse behavioural performance amongst participants scoring high on depression. These results indicate that differential value representations formed through delay discounting directly affect neural responses in reward processing and directly influence the effort invested in the current task, which is reflected by behavioural responses and is in agreement with the expected value of control theory.

Still Wanting to Win: Reward System Stability in Healthy Aging

Healthy aging is accompanied by multi-faceted changes. Especially within the brain, healthy aging exerts substantial impetus on core parts of cognitive and motivational networks. Rewards comprise basic needs, such as food, sleep, and social contact. Thus, a functionally intact reward system remains indispensable for elderly people to cope with everyday life and adapt to their changing environment. Research shows that reward system function is better preserved in the elderly than most cognitive functions. To investigate the compensatory mechanisms providing reward system stability in aging, we employed a well-established reward paradigm (Monetary Incentive Delay Task) in groups of young and old participants while undergoing EEG measurement. As a new approach, we applied EEG connectivity analyses to assess cortical reward-related network connectivity. At the behavioral level, our results confirm that the function of the reward system is preserved in old age. The mechanisms identified for maintaining reward system function in old age do not fit into previously described models of cognitive aging. Overall, older adults exhibit lower reward-related connectivity modulation, higher reliance on posterior and right-lateralized brain areas than younger adults, and connectivity modulation in the opposite direction than younger adults, with usually greater connectivity during non-reward compared to reward conditions. We believe that the reward system has unique compensatory mechanisms distinct from other cognitive functions, probably due to its etymologically very early origin. In summary, this study provides important new insights into cortical reward network connectivity in healthy aging.

Investigating Changes in Reward-Related Neural Correlates After PEERS Intervention in Adolescents With ASD: Preliminary Evidence of a "Precision Medicine" Approach

Background: The Social Motivation Hypothesis proposes that individuals with autism spectrum disorder (ASD) experience social interactions as less rewarding than their neurotypical (TD) peers, which may lead to reduced social initiation. Existing studies of the brain's reward system in individuals with ASD report varied findings for anticipation of and response to social rewards. Given discrepant findings, the anticipation of and response to social rewards should be further evaluated, particularly in the context of intervention outcome. We hypothesized that individual characteristics may help predict neural changes from pre- to post-intervention. Methods: Thirteen adolescents with ASD received the Program for the Education and Enrichment of Relational Skills (PEERS) intervention for 16 weeks; reward-related EEG was collected before and after intervention. Fourteen TD adolescents were tested at two timepoints but did not receive intervention. Event-related potentials were calculated to measure anticipation of (stimulus-preceding negativity; SPN) and response to (reward-related positivity; RewP) social and non-social rewards. Additionally, measures of social responsiveness, social skills, and intervention-engagement were collected. Group differences were analyzed as well as individual differences using prediction models. Result: Parent-reported social responsiveness and social skills improved in adolescents with ASD after participation in PEERS. ASD adolescents displayed marginally decreased anticipation of social rewards at post-intervention compared to pre-intervention. Regression models demonstrated that older adolescents and those with lower parent-reported social motivation prior to participation in PEERS displayed marginally increased social reward anticipation (more robust SPN) from pre- to post-intervention. Participants who displayed more parent-reported social motivation before intervention and were more actively engaged in the PEERS intervention evidenced increased social reward processing (more robust RewP) from pre- to post-intervention. Conclusion: Findings suggest that there may be differences in saliency between wanting/anticipating social rewards vs. liking/responding to social rewards in individuals with ASD. Our findings support the hypothesis that identification of individual differences may predict which adolescents are poised to benefit the most from particular interventions. As such, reported findings set the stage for the advancement of "precision medicine." This investigation is a critical step forward in our ability to understand and predict individual response to interventions in individuals with ASD.