Project Summary
Electrical stimulation of deep brain structures is an essential tool for the causal investigation of neural systems
that regulate learning and decision making. Deep brain electrical stimulation is also a valuable tool for treating
neurological disorders such as Parkinson's disease and tremor, and recent data suggests that electrical brain
stimulation may effectively treat epilepsy and severe depression. Despite its scientific and translational
applications, little is known about how electrical stimulation affects the ongoing activities of neurons or the
release of neuromodulators such as dopamine. Understanding how electrical stimulation affects dopamine
release is particularly important given dopamine's involvement in learning, motor control, decision making, and
neuroplasticity. There is considerable evidence that dopamine's function is determined by the time course of
release. For example, fast, “phasic” release (~1-2 seconds) is involved in neuroplasticity and reward-guided
learning while slow, “tonic” release (tens of seconds) is involved in motor control and motivation. Little is known
about how the brain selectively regulates tonic and phasic release, and few methods exist for controlling the
time course of dopamine release. Developing such methods could result in 1) new experimental approaches
for the causal investigation of the roles phasic and tonic release play in motivation and motor control, and 2)
translational tools to correct disrupted patterns of dopamine release in disorders such as Parkinson's disease,
schizophrenia, addiction, and depression. Towards these goals, evidence from our group suggests that the
frequency and duration of electrical brain stimulation allows selective control of the time course of dopamine
release. Our general objective is to characterize how parameters of brain stimulation such as stimulation
frequency, variability, and the brain region targeted impacts the time-course of dopamine release and
dopamine's role in reward-guided learning. Our experimental objectives are to determine (1) how the frequency
and variability of the sequence of pulses delivered during brain stimulation affects phasic and tonic dopamine
release, (2) how brain stimulation and tonic and phasic signaling interact to affect reward-driven learning, and
(3) and how tonic and phasic signaling affect interactions between neurons and shape neuroplasticity. Our
experimental approaches involve voltammetry for dopamine measurement, neural ensemble recordings for
measurement of neural coordination, optogenetics, and on-line optimization of dopamine release in
anesthetized and behaving rats. Our computational objective is to use data collected to develop multi-scale
systems and cellular models that describe how stimulation frequency and variance affect the time course of
dopamine release. We predict that multi-scale models will outperform current synaptic models and improve the
capacity of scientists and clinicians to control dopamine release in experimental and therapeutic settings.
These models may also explain clinical effects such as recent data from human patients suggesting that
electrical stimulation of deep brain regions reduces depression.
