Robert Cudmore

Research Interests

In vivo structural plasticity

How does the structure of the brain change with experience? I am approaching this broad question by imaging neurons, vasculature, and astrocytes in living mice over time-scales of minutes to months.

See the images.

Plasticity of intrinsic excitability

The way a neuron integrates incoming synaptic input to generate action potential output (a neurons intrinsic excitability) is critical for the functioning of the central nervous system. This integration is by no means fixed, it can be modified by activity. These modifications arise via changes in the expression level, location, or the biophysical properties of ion channel proteins (For a review, see Cudmore and Desai, Scholarpedia (2008)).

plasticity of intrinsic excitability

Long-term potentiation of intrinsic excitability. A brief period of high-frequency firing caused a long-lasting potentiation of intrinsic excitability (LTP-IE) in LV pyramidal neurons. This LTP-IE requires postsynaptic Ca++ and the activation of PKA. Given the similarities between synaptic and intrinsic plasticity in both the induction stimulus and expression mechanisms, raises the possibility that intrinsic plasticity is occuring wherever there is synaptic plasticity. See Cudmore and Turrigiano (2004).

Action potential precision

Once a neuron is activated by a synapse, what determines the precision of its output action-potential? One obvious determinant is the suite of ion-channels the neurons expresses, their location, and their biophysical properties.

plasticity of intrinsic excitability 2

Ion channels control action potential precision. The response of an organotypic cultured CA3 neuron to repeated current injections is noisy in that the arrival time of the action-potential is wide (left). Following the pharmacological block of a specific voltage-dependent K+ channel (in this case Kv1.2) the same neuron responds with more precise action-potentials (right). See Cudmore et al. (2010).

A single neuron stochastic model of action-potential precision

stochastic model of action-potential precision

Stochastic ion channel model and action-potential precision. A detailed model of a CA3 neuron with stochastic ion channels (to introduce biophysically realistic noise) shows that reducing one type of ion channel (ID, center column) is sufficient to improve action-potential precision while the reduction of another type of ion channel (IA, right column) has no effect on action-potential precision. See Cudmore et al. (2010).

Hybrid networks and network synchrony

Studying how individual neurons contribute to the behavior of networks of neurons is difficult because there are many variables that cannot be experimentally controlled. Hybrid modeling is a technique where a real neuron is recorded from and its input/output is used to construct a modeled network of neurons. See Reyes (2003).

hybrid network

The role of ion channles in sculpting network synchronization. A hybrid network of real neurons and modeled synapses is constructed (A). The constructed network is feed-forward with 200 neurons per layer. The game is to look at the synchrony across neurons within a layer and see how it develops as a function of layer. See Cudmore et al. (2010).

Modeling single neurons and networks of neurons

Modeling neurons and networks of neurons has a dual purpose (i) models can be used to determine if the parameters you have measured in an experiment are sufficient to explain your observations, and (ii) models can be used to make predictions that drive further experiments.

Dept. of Neuroscience, Linden Lab Johns Hopkins Medicine © 2008-2016