Project Summary / Abstract
This grant focuses on how very recent experiences––over the past few seconds to minutes––allow brains to
update expectations about the world and then use these expectations to guide behavior. The ability to flexibly
adjust one's course of action in this manner is a hallmark of adaptive human behavior. At the neural level,
relevant cellular-activity correlates have been described in non-human primates and other vertebrate model
systems. For example, ramping neural activity has been observed in the few hundred milliseconds, or seconds,
leading up to behavioral decisions and the rate of rise of these ramps tracks the gradual accumulation of
information relevant for the decision being made. Ramping activity is thus a correlate of an increasing
expectation that an important decision needs to be made and the moment at which the ramp reaches a
threshold level typically signifies when a final decision is taken. Another salient correlate of internal
expectations are reward-prediction error signals: bursts of dopamine-neuron activity when an animal receives
an unexpected reward or a reward is surprisingly omitted. Reward-prediction error signals seem well poised to
adjust animal and human behavior based on learned expectations. A clearer picture of how quantitative
internal signals––like ramping and reward-prediction error activity––contribute to behavioral flexibility would be
an important step forward for cognitive neuroscience. Here, we propose to develop two new behavioral tasks in
tethered Drosophila, where we can perform simultaneous neurophysiology. Our first aim is to use one of these
tasks to test the hypothesis that ramping neural signals are fundamental in forming behavioral decisions over
tens-of-seconds to minutes timescales in ethologically relevant contexts, rather than just on much shorter
timescales and in laboratory defined tasks (as has been shown to date). Such a discovery would argue that
expectations built over minutes in real-world conditions are ultimately fed into slowly ramping neuronal signals
so as to guide natural decision-making. Our second aim is to discover reward-prediction error signals in fruit
flies actively performing a trial-by-trial conditioning task and to define a circuit mechanism through which such
signals allow brains to form quantitatively precise expectations––updated on a trial-by-trial basis––on the
likelihood of rewards arriving or not arriving in the near future. Such discoveries in a genetically tractable model
will inform our thinking on how our brains generate expectations that allow for flexible, adaptive behaviors,
ultimately informing new therapeutic approaches to neurological conditions in which flexibility is impaired, such
as obsessive-compulsive disorder.