Research Areas

Parkinson's Disease and Addiction Modeling/Software Synaptic Plasticity in the Hippocampus

Theoretical and Experimental Investigations of the Basal Ganglia

How does the lack of dopamine produce the symptoms of Parkinson's Disease?
How does excessive dopamine in response to drugs of abuse produce addiction?

We utilize electrophysiology, optogenetics and behavior to investigate how dopamine and other neuromodulators controls the synaptic plasticity that underlies learning.

We created a theta burst stimulation paradigm for inducing LTP in normal magnesium. We demonstrated changes in the ability to induce striatal synaptic plasticity in rats that have learned to navigate a T-maze, and found changes correlated with training stage.

Using optogenetics, we showed that activation of striatal projection neurons inhibits LTP reducing dopamine release.

	We develop single neuron models with sophisticated calcium dynamics in order to investigate how temporal stimulation patterns control synaptic plasticity. We demonstrated that calcium dynamics predicts the change in synaptic weight for three different STDP protocols.
We create biophysically realistic, computational models of striatal neuronal networks to investigate how dopamine depletion produces abnormal brain rhythms and oscillations. Large scale simulations of striatal network models reveals that the abnormal connectivity between striatal neurons causes beta oscillations. Dopamine depletion weakens the lateral inhibitory connections, and strengthens the feedforward inhibition from fast spiking interneurons. Synchronizing input to the gap junction connected FSIs produces beta band oscillations. A prediction of the model is that blocking gap junctions will normalize striatal activity and restore normal movement in Parkinson's Disease. Read more about this research here.	Striatal Network Model
Mechanisms underlying Hippocampal LTP
A unifying model of signaling pathways underlying hippocampal LTP predicts the plasticity outcome of numerous stimulation paradigms. A combination of Epac, CamKII and PKA predicts whether long lasting LTP will occur. Next stop: ERK and actin control of spine size

Open Source Software Development

We have developed new software for computationally efficient modeling of stochastic reaction-diffusion systems. An explanation of the algorithm used in this new version can be found here. The software is available on github. Get the latest release here. A tutorial and tutorial files explain how to create and simulate signaling pathway models. A useful listing of other software for simulating stochastic reaction-diffusion systems We have developed parameter optimization software (in Python3) for matching neuron models in MOOSE to electrophysiology data. The optimization software works with moose_nerp - a declarative format for model specification. Here is in depth tutorial on creating MOOSE models using the python interface.

Other useful neural modeling software:

Our favorite neural simulator: MOOSE

GENESIS Home Page

Chemesis libraries for modeling biochemical reactions and calcium dynamics.

NEURON Home Page

XPP (Bard Home Page)

Research

Personnel

Publications

Software

Positions

Avrama Blackwell