When is giving an impulse? An ERP investigation of intuitive prosocial behavior

Human prosociality is often assumed to emerge from exerting reflective control over initial, selfish impulses. However, recent findings suggest that prosocial actions can also stem from processes that are fast, automatic and intuitive. Here, we attempt to clarify when prosocial behavior may be intuitive by examining prosociality as a form of reward seeking. Using event-related potentials (ERPs), we explored whether a neural signature that rapidly encodes the motivational salience of an event\u2014the P300\u2014can predict intuitive prosocial motivation. Participants allocated varying amounts of money between themselves and charities they initially labelled as high- or low-empathy targets under conditions that promoted intuitive or reflective decision making. Consistent with our predictions, P300 amplitude over centroparietal regions was greater when giving involved high-empathy targets than low-empathy targets, but only when deciding under intuitive conditions. Reflective conditions, alternatively, elicited an earlier frontocentral positivity related to response inhibition, regardless of target. Our findings suggest that during prosocial decision making, larger P300 amplitude could (i) signal intuitive prosocial motivation and (ii) predict subsequent engagement in prosocial behavior. This work offers novel insight into when prosociality may be driven by intuitive processes and the roots of such behaviors

The contributions of striatal and midbrain dopamine neurons to timing behavior

"To behave adaptively, animals must learn the temporal structure of events in their environment, and they must also predict the sometimes delayed consequences of their own actions. Therefore, to produce adaptive behavior, it is essential that the brain maintains a representation of time. How does the brain represent elapsed time in a manner that supports adaptive behavior, and what are the mechanisms that contribute to variability in subjective time estimates? In this monograph I address the roles of striatal and midbrain dopamine (DA) neurons in timing behavior. First, we recorded the activity of striatal neurons in rats performing an interval production task. We found that these neurons responded at different delays spanning the interval being timed. In addition, individual neurons rescaled their responses in time when intervals changed, indicating that relative time can be decoded from striatal populations. Next, we both measured and manipulated the activity of DA neurons in the substantia nigra pars compacta (SNc) while mice performed a temporal categorization task.(...)

The motivational mechanisms driving the antidepressant effect of ketamine

Ketamine is a rapidly-acting antidepressant and has shown to be effective in depressed individuals who have previously failed to benefit from other available treatments. An important question is how ketamine works. Addressing this might help inform more targeted and efficient treatments in the future. The aim of this thesis was to examine the neural, cognitive, and computational mechanisms underpinning the antidepressant response to ketamine in treatment-resistant depression. The work has specifically focused on motivational processing, since ketamine is particularly effective in alleviating symptoms of anhedonia, which are thought to be related to impaired reward-related function. Following a general introduction (Chapter 1), the first experimental chapter (Chapter 2) focuses on identifying suitable reward and punishment tasks for repeated testing in a clinical trial. Test retest properties of various tasks are explored in healthy individuals, assessed by both traditional measures of task performance (e.g., accuracy) and computational parameters. Chapter 3 outlines a pilot simultaneous EEGfMRI study in healthy individuals probing the neural dynamics of the motivation to exert cognitive effort, an important but understudied process in depression. The third study (Chapter 4) uses resting-state fMRI to examine how ketamine modulates fronto-striatal circuitry, which is known to drive motivational behaviour, in depressed and healthy individuals. The final experimental chapter (Chapter 5) examines which cognitive and computational measures of motivational processing (using tasks identified in Chapter 2) change following a single dose of ketamine compared to placebo in depression, using a crossover design. Based on preliminary findings, it is tentatively proposed that ketamine might affect reward processing by enhancing fronto-striatal circuitry functional connectivity, as well as by increasing exploratory behaviours, and possibly punishment learning rates. The general discussion (Chapter 6) discusses these findings in relation to contemporary models of anhedonia and antidepressant action, considering both the limitations of the work presented and possible future directions

Neural And Behavioural Responses To Rewards And Losses In Early Development: A Functional Magnetic Resonance Imaging Study

Functional magnetic resonance imaging (fMRI) was used to investigate the neural and behavioural correlates of learning from rewards and losses in children. Greater blood-oxygen-level dependent (BOLD) responses in the ventral striatum (VS) and the ventromedial prefrontal cortex (VMPFC) were found when participants received rewards compared to when they missed out on an opportunity to receive rewards. In contrast, greater BOLD responses in the anterior insula (AI) and the anterior cingulate cortex (ACC) were found when participants received losses compared to when they avoided losing. The BOLD response to rewards in the VS and VMPFC correlated positively with the tendency to select rewards. Greater incidence of early life adversity was associated with greater likelihood to select rewarding stimuli and a larger BOLD response in the VS and VMPFC to rewards. Findings suggest that the functional calibration of the mesocorticolimbic pathway is sensitive to the experience of early life adversity

Interactions Between the Basolateral Amygdala and Ventral Striatum During Probabilistic Learning in Children and Associations with Individual Differences in Free Cortisol

Stress can drastically alter the behavioural and functional correlates of feedback learning; however, the functional correlates of these effects are poorly understood, particularly in children. In the present study, typically developing children between the ages of 9- and 11-years-old completed a probabilistic learning task with both appetitive and aversive outcomes in a magnetic resonance imaging scanner. Anticipatory stress to the experimental environment was measured via salivary cortisol at baseline and prior to completion of the task. Although baseline and pre-MRI cortisol values were not reliably different at the group level, subsequent analyses revealed that the basolateral amygdala was less responsive to positive feedback in children with higher pre-MRI cortisol levels. Furthermore, individual differences in feedback-related basolateral amygdala activity were positively associated with differences in striatal activity. Thus, the basolateral amygdala may be particularly sensitive to individual differences in active cortisol levels, and may also modulate striatal feedback sensitivity

Learning and memory systems supporting decision making in the human brain

We successfully navigate the world by making decisions based on what we have learned. In the brain, two prominent learning systems have been identified and each is likely to guide decisions in different ways. Research on decision making has primarily focused on a reward learning system in the striatum. These studies have illuminated the how repeated choices and rewards build representations that guide choices and actions when encountering the same situation again. However, in a constantly changing environment, choices may not repeat themselves. Further, the environment may have more structure than simple reward learning can navigate. In these situations, decisions may be guided by a different learning system, namely a flexible learning system in the hippocampus which encodes episodes, or more broadly, relations between stimuli. However, investigations into the role of a reward learning system and a relational learning system in decision making have developed largely independently of each other. In the studies described below, I explore the function of these learning systems in value-guided decision making. Complementarily, I also explore how ongoing reward learning may modulate memory formation in the hippocampal system. In these studies, I demonstrate that reward learning and decision making is influenced by relational learning, and that these effects are predicted by hippocampal-striatal connectivity during learning. Separately, I establish that episodic memory is, in turn, influenced by ongoing reward learning. Successful memory is predicted by modulations of reward and memory regions including the striatum and hippocampus. Overall, these results provide novel insights into the learning systems encoding memories for future adaptive behavior

How Gains and Losses Influence the Brain and Behavior: Relations to Age, Risk for Depression, and Individual Differences

Behavioral and neural response to rewards and punishments has been the subject of a growing literature with particular interest within developmental, psychopathology, and individual difference domains. There is now mounting evidence suggesting that adolescents show heightened response to reward relative to adults, and that adolescents with Major Depressive Disorder (MDD), elevated depressive symptoms, or at high-risk for depression show reduced response to reward. However, it is unclear whether similar relations between response to incentives and development/psychopathology are observed during childhood. Here we examine behavioral, neural (functional magnetic resonance imaging - fMRI), and self-reported responsiveness to gain and loss of rewards within healthy children and young adults. We relate observed neural/behavioral incentive responsiveness to 1) developmental stage, 2) risk for depression, and 3) self-reported incentive sensitivity. First, studies investigating developmental stage indicated that responsiveness to gain and loss of reward feedback show differing relations with age. Specifically, while children show elevated behavioral and neural (dorsal/posterior insula) response to loss of reward relative to adults, response to reward was similar across age groups. Second, we observed similar levels of both gain approach and loss avoidance behavior between healthy children at relatively high and low-risk for MDD, based on a positive/negative maternal history of MDD respectively. Third, across several studies both elevated gain approach and elevated loss avoidance behavior related to elevated self-reported incentive sensitivity as assessed via different questionnaire types (i.e. hedonic capacity, Behavioral Inhibition System/Behavioral Activation System, and anhedonic depressive scales). Interestingly, gain approach and loss avoidance behavior predicted unique variance in self-reported incentive sensitivity (BAS drive) and relations between incentive sensitivity and behavior did not differ based on age or depression risk status. Together these results highlight the importance of responsiveness to feedback signaling the loss of reward from both developmental and incentive sensitivity perspectives. Future work is needed to examine how gain and loss responsiveness during childhood prospectively predicts changes in incentive responsiveness over development and incidence of depression/changes in depressive symptoms