Project Summary/Abstract
Many functions of the nervous system, such as learning and memory, inferring cause and effect, and predicting
future outcomes, depend upon the brain’s ability to perceive and form memories of the temporal duration of
events. Despite progress in establishing the neural basis of timing on the scale of milliseconds and circadian
timing over hours, many fundamental questions remain about time encoding on the intermediate scale of interval
timing (i.e. seconds to minutes). To investigate how interval time is represented in the brain, I developed a novel
behavioral approach (Heys and Dombeck, 2018) and a novel surgical and optical approach to enable large-
scale, cellular-resolution functional imaging in MEC in the behaving mouse (Heys et al., 2014). By combining
these imaging and behavioral methods, I discovered a previously unknown population of neurons in MEC that
encode interval time, whereby individual time-encoding neurons become regularly activated at a specific moment
during an interval timing task (Heys and Dombeck, 2018). I then established that MEC is critical for interval timing
during learning (Heys et al., In Press). This previous work has positioned my laboratory to address fundamental
questions regarding the neural circuit and synaptic mechanisms underlying interval timing. We will test a novel
conceptual framework, whereby time is encoded through a multi-stage process. In the first stage of this model,
a neural clock generates a context-independent representation of elapsed time. In the second stage, a
downstream circuit reads out the clock and associates time with other features of experience, such as spatial
context. Building upon my published, this proposal will test the hypothesis that the anterior cingulate cortex (ACC)
serves as an upstream neural clock, providing context-independent temporal information to medial entorhinal
cortex (MEC), which in turn integrates elapsed time with spatial context. To test this model, I will apply my cutting-
edge imaging techniques to record and manipulate neural activity from synapses and dendrites, up to thousands
of individual neurons simultaneously in awake behaving mice (Heys et al. 2014) during virtual-reality behavioral
paradigms that allow precise control of timing behavior (Heys and Dombeck, 2018). Using this approach, we will
first evaluate the ability of ACC axons terminating in MEC to serve as a neural clock signal in MEC. Second, we
will determine whether MEC encodes a context-dependent representation of time by integrating synaptic input
from ACC with spatial coding input from other upstream brain regions. Third, we will identify the synaptic and
dendritic mechanisms underlying cellular integration of context-dependent representations of time in MEC. This
proposal will have a far-reaching influence on cellular, systems and cognitive neuroscience. As interval timing is
a fundamental component of essentially all major brain functions, understanding the neural mechanisms of
interval timing, from synaptic to population level neural coding, will provide a basis for understanding how the
brain performs all complex functions that depend upon encoding of time on the scale of seconds to minutes.