Using optogenetics, we showed that activation of striatal projection neurons inhibits LTP reducing dopamine release.
Theoretical and Experimental Investigations of the Basal
How does the lack of dopamine produce the symptoms of Parkinson's Disease?
We utilize electrophysiology, optogenetics and behavior to investigate how dopamine and other neuromodulators controls the synaptic plasticity that underlies learning.
How does excessive dopamine in response to drugs of abuse produce addiction?
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.
||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)
Revised: 07/2011 - Avrama Blackwell