Projects
Here is a short list of some of my projects:
1. FAS and functional deficits in neuronal networks
By leveraging biophysical observations of FAS statistics, we develop a theoretical model of functional neural network activity driven by adaptive changes from plasticity. Based upon the FORCE model of Sussillo and Abbott [1], our innovations highlight the role of plasticity in overcoming injuries and degeneration of neurons in a network architecture. We provide a quantitative measure, on a network level, of cognitive deficits arising from injury. We demonstrate that plasticity is capable of overcoming mild injuries while failing to compensate for more severe injuries.
The level of injury dictates the FORCE model’s ability to produce a desired output functionality (and associated behavior) and allows for quantitative metrics for accessing cognitive and behavioral deficits. Thus a direct link between FAS in neural networks and compromised functional response can be established. The theoretical framework developed is a promising computational framework for providing a deeper understanding of the cognitive deficits arising in, for instance, Alzheimer’s, Parkinson’s, Multiple-Sclerosis, and TBI.
2. Diagnostic tools for evaluating the impact of focal axonal swellings
I this joint work with Harvard's Disease Biophysics Group we develop a MATLAB toolbox that extracts meaningful geometrical parameters from sequential images of injured axon segments. The algorithm provides a principled approach for dealing with imaging distortions caused by experimental artifacts in order to extract the cross-section of an axon by detecting local symmetries, turning points and turning regions. It allows for an assessment of its impact on spike propagation, leading to a color coding of the axon that highlights problematic regions for information propagation.
Our MATLAB toolbox thus highlights potential trouble spots of axonal morphology, and similar to car traffic maps, identify blocked or impaired routes for information flow. This computational framework is a promising starting point for diagnosing and assessing the impact of axonal swellings implicated in concussions, Alzheimer’s and Parkinson’s disease, Multiple Sclerosis and other neurological pathologies.
3. Compromised axonal functionality after degeneration, concussion and/or traumatic brain injury.
Using a spike metric analysis, we characterize the effects of axonal varicosities on spike train propagation by comparing Poisson spike train classes before and after propagation through a prototypical axonal enlargement. Misclassification of spike train classes and low-pass filtering of firing rate activity increases with a more pronounced axonal injury. We show that confusion matrices and a calculation of the loss of transmitted information provide a very practical way to characterize how injured neurons compromise the signal processing and faithful conductance of spike trains.
The method demonstrates that (i) neural codes encoded with low firing rates are more robust to injury than those encoded with high firing rates, (ii) classification depends upon the length of the spike train used to encode information, and (iii) axonal injuries reduce the variance of spike trains within a given stimulus class. The work introduces a novel theoretical and computational framework to quantify the interplay between electrophysiological dynamics with focused axonal swellings generated by injury or other neurodegenerative processes. It further suggests how pharmacology and plasticity may play a role in the recovery of neural computation. Ultimately, the work bridges vast experimental observations of in vitro morphological pathologies with post-traumatic cognitive and behavioral dysfunction.
4. Identifying critical regions for spike propagation in axonal segments.
We developed a computational framework to distinguish between axonal enlargements that lead to minor changes in spike propagation from those that result in critical phenomenon such as reflection or blockage of the original traveling spike.
Contrary to earlier notions that large diameter increases mostly lead to blocking, we demonstrate transmission is stable provided the geometrical changes occur in a slow manner. Our method also identifies a narrow range of parameters leading to a reflection regime. The distinction between these three regimes can be evaluated by a simple function of the geometrical parameters inferred through numerical simulations. By evaluating this function along axon segments can detect regions most susceptible to (i) transmission failure due to perturbations, (ii) structural plasticity, (iii) critical swellings caused by brain traumas and/or (iv) neurological disorders associated with the breakdown of spike train propagation.