The interplay between social motivation, social experience, and developmental neural specialization for social perception

From birth, infants preferentially attend to human motion, which allows them to learn to interpret other peoples’ facial expressions and mental states. Evidence from adults shows that selectivity of the amygdala and the posterior superior temporal sulcus (pSTS) to biological motion correlates with social network size. Social motivation—one’s desire to orient to the social world, to seek and find reward in social interaction, and to maintain social relationships—may also contribute to neural specialization for biological motion and to social network characteristics. The current study aimed to determine whether neural selectivity for biological motion relates to social network characteristics, and to gain preliminary evidence as to whether social motivation plays a role in this relation. Findings suggest that neural selectivity for biological motion in the pSTS is positively related to social network size in middle childhood and that this relation is moderated by social motivation.

Developmental Neural Correlates of Social Interaction

Children develop in a sea of reciprocal social interaction, but their brain development is predominately studied in non-interactive contexts (e.g., viewing photographs of faces). This dissertation investigated how the developing brain supports social interaction. Specifically, novel paradigms were used to target two facets of social experience—social communication and social motivation—across three studies in children and adults. In Study 1, adults listened to short vignettes—which contained no social information—that they believed to be either prerecorded or presented over an audio-feed by a live social partner. Simply believing that speech was from a live social partner increased activation in the brain’s mentalizing network—a network involved in thinking about others’ thoughts. Study 2 extended this paradigm to middle childhood, a time of increasing social competence and social network complexity, as well as structural and functional social brain development. Results showed that, as in adults, regions of the mentalizing network were engaged by live speech. Taken together, these findings indicate that the mentalizing network may support the processing of interactive communicative cues across development. Given this established importance of social-interactive context, Study 3 examined children’s social motivation when they believed they were engaged in a computer-based chat with a peer. Children initiated interaction via sharing information about their likes and hobbies and received responses from the peer. Compared to a non-social control, in which children chatted with a computer, peer interaction increased activation in mentalizing regions and reward circuitry. Further, within mentalizing regions, responsivity to the peer increased with age. Thus, across all three studies, social cognitive regions associated with mentalizing supported real-time social interaction. In contrast, the specific social context appeared to influence both reward circuitry involvement and age-related changes in neural activity. Future studies should continue to examine how the brain supports interaction across varied real-world social contexts. In addition to illuminating typical development, understanding the neural bases of interaction will offer insight into social disabilities such as autism, where social difficulties are often most acute in interactive situations. Ultimately, to best capture human experience, social neuroscience ought to be embedded in the social world.

ENGINEERING DIGITAL SHARING PLATFORM TO CREATE SOCIAL CONTAGION: EVIDENCE FROM LARGE SCALE RANDOMIZED FIELD EXPERIMENTS

Peer-to-peer information sharing has fundamentally changed customer decision-making process. Recent developments in information technologies have enabled digital sharing platforms to influence various granular aspects of the information sharing process. Despite the growing importance of digital information sharing, little research has examined the optimal design choices for a platform seeking to maximize returns from information sharing. My dissertation seeks to fill this gap. Specifically, I study novel interventions that can be implemented by the platform at different stages of the information sharing. In collaboration with a leading for-profit platform and a non-profit platform, I conduct three large-scale field experiments to causally identify the impact of these interventions on customers’ sharing behaviors as well as the sharing outcomes. The first essay examines whether and how a firm can enhance social contagion by simply varying the message shared by customers with their friends. Using a large randomized field experiment, I find that i) adding only information about the sender’s purchase status increases the likelihood of recipients’ purchase; ii) adding only information about referral reward increases recipients’ follow-up referrals; and iii) adding information about both the sender’s purchase as well as the referral rewards increases neither the likelihood of purchase nor follow-up referrals. I then discuss the underlying mechanisms. The second essay studies whether and how a firm can design unconditional incentive to engage customers who already reveal willingness to share. I conduct a field experiment to examine the impact of incentive design on sender’s purchase as well as further referral behavior. I find evidence that incentive structure has a significant, but interestingly opposing, impact on both outcomes. The results also provide insights about senders’ motives in sharing. The third essay examines whether and how a non-profit platform can use mobile messaging to leverage recipients’ social ties to encourage blood donation. I design a large field experiment to causally identify the impact of different types of information and incentives on donor’s self-donation and group donation behavior. My results show that non-profits can stimulate group effect and increase blood donation, but only with group reward. Such group reward works by motivating a different donor population. In summary, the findings from the three studies will offer valuable insights for platforms and social enterprises on how to engineer digital platforms to create social contagion. The rich data from randomized experiments and complementary sources (archive and survey) also allows me to test the underlying mechanism at work. In this way, my dissertation provides both managerial implication and theoretical contribution to the phenomenon of peer-to-peer information sharing.

Joint Optimization for Social Content Delivery in Wireless Networks

Over the last decade, success of social networks has significantly reshaped how people consume information. Recommendation of contents based on user profiles is well-received. However, as users become dominantly mobile, little is done to consider the impacts of the wireless environment, especially the capacity constraints and changing channel. In this dissertation, we investigate a centralized wireless content delivery system, aiming to optimize overall user experience given the capacity constraints of the wireless networks, by deciding what contents to deliver, when and how. We propose a scheduling framework that incorporates content-based reward and deliverability. Our approach utilizes the broadcast nature of wireless communication and social nature of content, by multicasting and precaching. Results indicate this novel joint optimization approach outperforms existing layered systems that separate recommendation and delivery, especially when the wireless network is operating at maximum capacity. Utilizing limited number of transmission modes, we significantly reduce the complexity of the optimization. We also introduce the design of a hybrid system to handle transmissions for both system recommended contents ('push') and active user requests ('pull'). Further, we extend the joint optimization framework to the wireless infrastructure with multiple base stations. The problem becomes much harder in that there are many more system configurations, including but not limited to power allocation and how resources are shared among the base stations ('out-of-band' in which base stations transmit with dedicated spectrum resources, thus no interference; and 'in-band' in which they share the spectrum and need to mitigate interference). We propose a scalable two-phase scheduling framework: 1) each base station obtains delivery decisions and resource allocation individually; 2) the system consolidates the decisions and allocations, reducing redundant transmissions. Additionally, if the social network applications could provide the predictions of how the social contents disseminate, the wireless networks could schedule the transmissions accordingly and significantly improve the dissemination performance by reducing the delivery delay. We propose a novel method utilizing: 1) hybrid systems to handle active disseminating requests; and 2) predictions of dissemination dynamics from the social network applications. This method could mitigate the performance degradation for content dissemination due to wireless delivery delay. Results indicate that our proposed system design is both efficient and easy to implement.

Too Busy to Be Fair? The Effect of Managers’ Perceived Workload on Their Core Technical Performance and Justice Rule Adherence

Despite the organizational benefits of treating employees fairly, both anecdotal and empirical evidence suggest that managers do not behave fairly towards their employees in a consistent manner. As treating employees fairly takes up personal resources such as time, effort, and attention, I argue that when managers face high workloads (i.e., high amounts of work and time pressure), they are unable to devote such personal resources to effectively meet both core technical task requirements and treat employees fairly. I propose that in general, managers tend to view their core technical task performance as more important than being fair in their dealings with employees; as a result, when faced with high workloads, they tend to prioritize the former at the expense of the latter. I also propose that managerial fairness will suffer more as a result of heightened workloads than will core technical task performance, unless managers perceive their organization to explicitly reward fair treatment of employees. I find support for my hypotheses across three studies: two experimental studies (with online participants and students respectively) and one field study of managers from a variety of organizations. I discuss the implications of studying fairness in the wider context of managers’ complex role in organizations to the fairness and managerial work demands literatures.

Generating Discriminative Objective Proposals via Submodular Ranking

Object recognition has long been a core problem in computer vision. To improve object spatial support and speed up object localization for object recognition, generating high-quality category-independent object proposals as the input for object recognition system has drawn attention recently. Given an image, we generate a limited number of high-quality and category-independent object proposals in advance and used as inputs for many computer vision tasks. We present an efficient dictionary-based model for image classification task. We further extend the work to a discriminative dictionary learning method for tensor sparse coding. In the first part, a multi-scale greedy-based object proposal generation approach is presented. Based on the multi-scale nature of objects in images, our approach is built on top of a hierarchical segmentation. We first identify the representative and diverse exemplar clusters within each scale. Object proposals are obtained by selecting a subset from the multi-scale segment pool via maximizing a submodular objective function, which consists of a weighted coverage term, a single-scale diversity term and a multi-scale reward term. The weighted coverage term forces the selected set of object proposals to be representative and compact; the single-scale diversity term encourages choosing segments from different exemplar clusters so that they will cover as many object patterns as possible; the multi-scale reward term encourages the selected proposals to be discriminative and selected from multiple layers generated by the hierarchical image segmentation. The experimental results on the Berkeley Segmentation Dataset and PASCAL VOC2012 segmentation dataset demonstrate the accuracy and efficiency of our object proposal model. Additionally, we validate our object proposals in simultaneous segmentation and detection and outperform the state-of-art performance. To classify the object in the image, we design a discriminative, structural low-rank framework for image classification. We use a supervised learning method to construct a discriminative and reconstructive dictionary. By introducing an ideal regularization term, we perform low-rank matrix recovery for contaminated training data from all categories simultaneously without losing structural information. A discriminative low-rank representation for images with respect to the constructed dictionary is obtained. With semantic structure information and strong identification capability, this representation is good for classification tasks even using a simple linear multi-classifier.

TRANSFORMATIONS OF TASK-DEPENDENT PLASTICITY FROM A1 TO HIGHER-ORDER AUDITORY CORTEX

Everyday, humans and animals navigate complex acoustic environments, where multiple sound sources overlap. Somehow, they effortlessly perform an acoustic scene analysis and extract relevant signals from background noise. Constant updating of the behavioral relevance of ambient sounds requires the representation and integration of incoming acoustical information with internal representations such as behavioral goals, expectations and memories of previous sound-meaning associations. Rapid plasticity of auditory representations may contribute to our ability to attend and focus on relevant sounds. In order to better understand how auditory representations are transformed in the brain to incorporate behavioral contextual information, we explored task-dependent plasticity in neural responses recorded at four levels of the auditory cortical processing hierarchy of ferrets: the primary auditory cortex (A1), two higher-order auditory areas (dorsal PEG and ventral-anterior PEG) and dorso-lateral frontal cortex. In one study we explored the laminar profile of rapid-task related plasticity in A1 and found that plasticity occurred at all depths, but was greatest in supragranular layers. This result suggests that rapid task-related plasticity in A1 derives primarily from intracortical modulation of neural selectivity. In two other studies we explored task-dependent plasticity in two higher-order areas of the ferret auditory cortex that may correspond to belt (secondary) and parabelt (tertiary) auditory areas. We found that representations of behaviorally-relevant sounds are progressively enhanced during performance of auditory tasks. These selective enhancement effects became progressively larger as you ascend the auditory cortical hierarchy. We also observed neuronal responses to non-auditory, task-related information (reward timing, expectations) in the parabelt area that were very similar to responses previously described in frontal cortex. These results suggests that auditory representations in the brain are transformed from the more veridical spectrotemporal information encoded in earlier auditory stages to a more abstract representation encoding sound behavioral meaning in higher-order auditory areas and dorso-lateral frontal cortex.

THE INFLUENCE OF MOTIVATION ON EMOTION REGULATION AND MOTOR PERFORMANCE: EXAMINATION OF A NEURO-AFFECTIVE MODEL

Mental stress is known to disrupt the execution of motor performance and can lead to decrements in the quality of performance, however, individuals have shown significant differences regarding how fast and well they can perform a skilled task according to how well they can manage stress and emotion. The purpose of this study was to advance our understanding of how the brain modulates emotional reactivity under different motivational states to achieve differential performance in a target shooting task that requires precision visuomotor coordination. In order to study the interactions in emotion regulatory brain areas (i.e. the ventral striatum, amygdala, prefrontal cortex) and the autonomic nervous system, reward and punishment interventions were employed and the resulting behavioral and physiological responses contrasted to observe the changes in shooting performance (i.e. shooting accuracy and stability of aim) and neuro-cognitive processes (i.e. cognitive load and reserve) during the shooting task. Thirty-five participants, aged 18 to 38 years, from the Reserve Officers’ Training Corp (ROTC) at the University of Maryland were recruited to take 30 shots at a bullseye target in three different experimental conditions. In the reward condition, $1 was added to their total balance for every 10-point shot. In the punishment condition, $1 was deducted from their total balance if they did not hit the 10-point area. In the neutral condition, no money was added or deducted from their total balance. When in the reward condition, which was reportedly most enjoyable and least stressful of the conditions, heart rate variability was found to be positively related to shooting scores, inversely related to variability in shooting performance and positively related to alpha power (i.e. less activation) in the left temporal region. In the punishment (and most stressful) condition, an increase in sympathetic response (i.e. increased LF/HF ratio) was positively related to jerking movements as well as variability of placement (on the target) in the shots taken. This, coupled with error monitoring activity in the anterior cingulate cortex, suggests evaluation of self-efficacy might be driving arousal regulation, thus affecting shooting performance. Better performers showed variable, increasing high-alpha power in the temporal region during the aiming period towards taking the shot which could indicate an adaptive strategy of engagement. They also showed lower coherence during hit shots than missed shots which was coupled with reduced jerking movements and better precision and accuracy. Frontal asymmetry measures revealed possible influence of the prefrontal lobe in driving this effect in reward and neutral conditions. The possible interactions, reasons behind these findings and implications are discussed.