Electrophysiological recordings in human decision-making
Current theories of decision-making postulate that, when faced with a choice, we estimate values for different courses of actions, which are then integrated and compared to generate behavior in a process that engages multiple cortical regions. Such goals can be relatively simple, such as those in basic reward learning scenarios where organisms seek to acquire primary rewards (e.g., food, money, sex). Alternatively, they can be highly complex, requiring complex sequences of actions, such as the pursuit of professional (e.g. tenure) or creative (e.g. publishing a book) goals.
Guidance of behavior in the service of such internally represented goals is conceptualized as cognitive control, and abundant evidence points to the prefrontal cortex (PFC) as a site where representations of goals are actively maintained and used to select goal-directed behaviors. First, PFC regions involved in decision- making and other cognitive functions have undergone the latest and most expansive development in the course of evolution, supporting the notion that PFC is essential for abstract goal-oriented behavior. Furthermore, direct evidence in humans supports the notion that goal representations are actively maintained in PFC and used to select goal-directed behaviors: (1) PFC can support sustained activity and is selectively engaged in numerous goal-oriented tasks; (2) damage to the PFC produces deficits in goal-directed behavior; and (3) psychiatric disorders such as addiction, schizophrenia and major depressive disorders are associated with PFC dysfunction.
Under this view, the PFC acts as a critical control node in neural networks that connect distributed task-relevant processing modules essential for human cognition. Neuronal oscillations, reflecting the dynamic coordination of neuronal ensembles, have been linked to both normal network function and to neurological and psychiatric disorders. Here, sustained activity in PFC is used to select goal-oriented behavior by providing bias signals to other brain regions for guiding the mapping of sensory inputs, internal states, and motor outputs.
I am currently employing electrocorticography (ECoG) in neurosurgical patients to test the hypothesis that PFC-dependent networks cognitive behaviorally neural networks in goal-oriented decision-making. Multi-electrode intracranial recordings in neurosurgical patients (epilepsy, TBI) offer a unique opportunity to investigate the neural and oscillatory basis of reward and social decision-making behavior. I will combine ECoG recordings with behavioral probes of risky decision-making and social norm compliance. I propose that brain oscillations, representing the coordinated activity of large neuronal populations, act in a top-down manner to express functional relationships that allow the coupling of selective neuronal responses to generate adaptive behavior in these settings. The results of this proposal will shed light into the cortical mechanisms underlying risk-taking, social interaction and top-down control, cognitive processes that are significantly disturbed in numerous psychiatric disorders such as addiction, schizophrenia, personality disorders and major depressive disorder.
This work is carried out in the Knight lab at UC Berkeley.
Pharmacological manipulation of social behavior
The presence of other-regarding preferences, such as aversion to inequity and associated prosocial concerns, is widely thought to be instrumental to the development of large-scale cooperation in the human species. For example, in 2013 alone individuals donated over $400 billion to charitable organizations worldwide. At the societal level, failures to mitigate inequity are associated with greater prevalence of health problems and an increased likelihood of violent political conflict. Even controlling for reciprocity and reputation-driven factors that cannot be accounted for in field data, laboratory experiments using social dilemma games have consistently found that individuals are often willing to sacrifice economic self-interest to achieve altruistic or cooperative outcomes.
Only in recent years, however, have scientists begun to characterize the biological underpinnings of human prosociality. Much of this knowledge has come from application of functional neuroimaging to economic games that capture core features of human prosociality, as well as mathematical models that relate brain activity to putative internal values underlying prosocial actions. At the heart of these models is the idea that humans perceive certain actions as more or less rewarding depending upon their effects not only on one’s own economic interests, but also on those of others. That is, prosocial preferences serve to modify the value of a subject’s own actions to account for his or her effect on other people. Using this mathematical formalism, these studies have been highly successful in connecting prosocial preferences to activity in brain regions known to receive abundant dopaminergic projections, particularly frontostriatal circuits, in ways that are consistent with reward-encoding and reinforcement properties of dopaminergic neurons.
Due to the correlational nature of this evidence, however, the role of dopamine in setting or modulating behavioral sensitivity to prosocial concerns remains unclear. In particular, existing neuroimaging evidence leaves open a number of possibilities regarding the specific role of dopamine in human prosociality.
We have recently started addressing these questions by using pharmacological tools to characterize dopaminergic contributions to an important class of prosocial behavior captured by economic games. Specifically, we use Tolcapone, a brain-penetrant drug that enhances dopamine tone by acting as a competitive antagonist of catechol-O-methyl transferase (COMT), one of the main enzymes responsible for dopamine catabolism and signal termination. By enhancing brain dopamine concentration we recently showed a specific effect on inequity aversion; we are currently following up on this study combining tolcapone administration with fMRI to pinpoint the exact locus of tolcapone's modulation of neural activity.
This work is carried out in collaboration with Andrew Kayser at UCSF.
The genetic basis of cognitive phenotypes
Connecting neural mechanisms of behavior (cognitive phenotypes) to their underlying molecular and genetic substrates has important scientific and clinical implications. However, despite rapid growth in our knowledge of the functions and computational properties of neural circuitry underlying behavior in a number of important domains, there has been much less progress in extending this understanding to their molecular and genetic substrates, even in an age marked by exploding availability of genomic data. We have recently developed analytical strategies that aim to overcome two important challenges associated with studying the complex relationship between genes and behavior: (i) reducing distal behavioral phenotypes to a set of molecular, physiological, and neural processes that render them closer to the actions of genetic forces, and (ii) striking a balance between the competing demands of discovery and interpretability when dealing with genomic data containing up to millions of markers.
Our proposed approach involves linking, on one hand, models of neural computations and circuits hypothesized to underlie behavior, and on the other hand, the set of the genes carrying out biochemical processes related to the functioning of these neural systems. In a recent review, we focused on using this strategy using the specific example of value-based decision-making, and discuss how such a combination allows researchers to leverage existing biological knowledge at both neural and genetic levels to advance our understanding of the neurogenetic mechanisms underlying behavior.
We have recently also succesfully employed this approach to characterize the association of strategic behavior with variations in the dopamine pathway and are currently working to expand the approach to other neural pathways.