Intelligent Networks Laboratory

AI and graph-based systems.


Computational Neuroscience.

The genesis of our laboratory is the marriage of computers and nervous systems in computational neuroscience research. We have investigated questions of neural function since our founding, and this work is still a core aspect of our lab. You can see past projects under the "Projects/Completed" menu item; here we present our current work-in-progress.

Development in Cortical Cultures.

Some of the central questions in neuroscience include how the activities and connectivities of individual cells in cortex contribute to its development and operation as a computational mechanism. A powerful experimental approach for investigating these questions is the use of cultured dissociated cortical cells grown into networks on a multi-electrode array. Such preparations allow investigation of network development, activity, plasticity, responses to stimuli, the effects of pharmacological agents, etc.

A common behavioral feature of such preparations is the occurrence of whole-culture pathological (in the sense that it does not occur in vivo) bursting that oftentimes interferes with the experimental goals. This bursting is interesting from both a theoretical point of view, as well as a clinical one (as it has been proposed as a model for epilepsy). Understanding the mechanisms that underlie bursting could allow creation of more useful cell cultures and possibly have medical applications.

In this project, we are performing a computational study of the interplay of individual neuron activity, cell culture development, and the network behavior. This is very large computing task, as we need to simulate each neuron's activity at sub-millisecond accuracy while performing simulations of weeks of cortical development. Moreover, we must do this for networks of thousands to tens of thousands of cells.

Spike Timing Dependent Plasticity.

Synaptic plasticity is an important part of the functioning and growth of neural networks, and spike-time-dependent plasticity (STDP) has emerged as one of the most widely modeled plasticity mechanisms due to its physiological realistic induction and evidence of its presence in vivo. We have been modeling STDP to investigate how it could tune already-developed networks. Among the sub-projects that we are working on include how STDP changes network behavior, how STDP alters the graph structure of such networks, and what role STDP might play during the ongoing network damage produced by Alzheimer's Disease.