Animals, including humans, are constantly engaged in making decisions, possibly, often without knowing about it. For instance, in a rich visual scene (like when driving through a busy street), our mind will inevitable select certain parts of the scene to which we will attend (and possibly remember later) whilst ignoring a vast majority of the remaining visual input. Alternatively, consider approaching someone in foggy weather, and you have decide whether this is a stranger or someone you know and would want to greet. Such kinds of choices are often referred to as perceptual decision making. Other decisions that come to mind are selecting a restaurant for dinner, a holiday destination, a career path, or whom to marry. Such decisions are referred to as value- or reward-guided, because we decide between the options based on how valuable ("rewarding") they appear to us.
The key parameters for decision making are thought to be carried in neuronal oscillations, rhythmic fluctuations in the activitiy of populations of neurons. Neuronal oscillations are thought be a key mode of information processing in the brain. While there have now been a number of studies investigating the relationship between neuronal oscillations and decision making, it is still rather unknown how the activity of neurotransmitters (chemical messengers between neurons) at the level of synapses translates into oscillations in ensembles of neurons and ultimately into decision making. These represent two different levels of investigation: neurotransmitter effects are usually assessed with respect to their effects at the synaptic or cellular level, while network dynamics (neuronal oscillations) are related to decision behaviour. Notably, a number of psychiatric disorders, such as major depressive disorders are characterized both by anomalies in neuronal oscillations, aberrant neurochemistry, and impairments in decision making. The impairments in decision making may even be a factor that supports persistence of a disorder, when individuals engage in self-defeating behavioural patterns. Notably, the neurochemical systems implicated in these disorders, and the targets of the drugs used for treatment are also heavily implicated in decision making. It is therefore important to understand how neurochemical activity translates into larger-scale dynamics (rhythmic activity of populations of thousands of neurons) to guide decision making.
This project will use non-invasive brain imaging (magnetoencephalography, MEG) to study neuronal oscillations in healthy humans while they engage in different decisions. This will allow us to investigate how the relevant parameters underlying a decision are represented in large-scale neuronal dynamics. To relate this to cortical neurochemistry, the activity of neurochemical systems will either be measured using magnetic resonance spectroscopy or manipulated by using drugs that target the neurochemical systems of interest. The wiring of brain micocircuits and their physiological properties turn them into a dynamical system, the behaviour of which can be challenging to predict intuitively. Therefore, neurochemical effects on large-scale dynamics and on behaviour are often hard to understand without an appropriate theoretical framework. To bridge the levels of investigation, biophysically detailed models of cortical circuits will be used. Variants of these models have been successfully used to understand neural dynamics and choice behaviour. The models can be used to simulate the effects of neurochemical manipulations to predict the effects at the level of large-scale dynamics and on behaviour. Thus, the aim of the project is to obtain a mechanistic understanding of the processes that translate the action of a neurotransmitter at a particular receptor into large-scale dynamics that carries information about choice-relevant parameters, and ultimately into the choice patterns we can observe in our human volunteers.
