Research within the laboratory focuses on the neural mechanisms underlying cognitive control and evaluative behavior in a variety of domains (e.g., affective, social, economic). Below is a sampling of current research within the lab.
Neuronal Mechanisms for Decision Optimization
Decision making is a frequent element of life of animals and humans. The accuracy and speed of the decisions may be crucially important for survival. Therefore, evolutionary pressure promotes animals making optimal decisions, and hence it is plausible that decision networks in the brain have parameters resulting in the optimal performance.
Our research focuses on mathematical analysis of neural network models of decision processes in the brain. We ask what neuronal networks and what values of their parameters allows making decisions with the maximum accuracy and in the shortest time. We seek the network architecture allowing optimal decisions, and the optimal values of parameters such as: decision threshold, neuronal gain, and decision bias.
Executive control refers to our ability to maintain and update abstract goals that guide our behavior at a more concrete level. In a sense, executive control refers to the most abstract goal that binds together concrete sub-goals. Inability to do so has severe consequences for simple every-day behavior, consequences which include distractibility and perseverance. The interplay of these two factors is the focus of our research.
We are interested in mapping out processes that underlie efficient reconfiguration of goals (i.e., ‘task-sets’) when we change the focus of our attention. Of particular relevance to this issue is the task-switching paradigm, which calls on the basic components of executive control (as defined above), maintenance of the relevant task-set and updating to a novel task-set on a switch trial. We are using this paradigm to investigate how, and at what conceptual level, information from the last task is maintained – and how it affects the upcoming trial. We are investigating both behavior and brain activity (fMRI). In conjunction we use connectionist models to simulate the process of interest – to fit data and theory – and to generate empirical predictions.