Adjunct Professor, Dept. of Physiology and Pharmacology
Adjunct Associate Professor, Biomedical Engineering
To develop appropriate mathematical methods, both analytical and computational, to study the dynamics of neural activity patterns, and to help understand the relationship between these dynamics and behavior. Using mathematical methods drawn from statistical physics and dynamical systems, the specific areas of research are as follows:
- Computational Pharmacology
Given that many biological mechanisms of schizophrenia are now understood, and that computational power and technique has reached the point for practical modeling of pathologies of schizophrenia, In Silico Biosciences, Inc is developing a computational platform to bridge the gap from pre-clinical and clinical trials. Computational models can combine the information from animal studies of brain circuitry with data from human clinical trials of drug actions. Furthermore, complex interactions of multiple receptor targets can be predicted by a biophysical model of brain function. We develop computational models of neural micro-circuits to predict the efficacy of drug actions on symptoms of mental diseases such as schizophrenia and Alzheimer's disease.
- Learning algorithms of cerebellum-like structures
We are investigating the dynamics of synaptic plasticity at the site of initial electrosensory information processing in mormyrid electric fish and mammalian dorsal cochlear nucleus. Using mathematical analyses and computer simulations, results from different experiments performed in electrophysiology labs are combined to predict changes in responses of neurons during changing sensory conditions.
- Dynamics of neural activity in the auditory system
This collaborative projects investigated various hypothetical mechanisms underlying neuronal activity patterns in the auditory pathways of the brainstem and midbrain. The modeling effort will help to bridge the gap between cellular- and systems-level experimental findings.
- Biological learning rules
A research program is presently underway to analyze the neural dynamics that result from different biological learning rules. Since the timing relations of biological learning rules result from molecular events at the synapse, this line of research helps to link the implications of dynamics at the molecular level, through dynamics at the network level, to the behavior of whole organisms.
- L. Holmstrom, L.B.M. Eeuwes, P.D. Roberts, C.V. Portfors (2010) Efficient encoding of vocalizations in the auditory midbrain. J Neurosci 30: 802-819.
- Roberts P.D. and Leen T.K. (2010) Anti-Hebbian spike-timing-dependent plasticity and adaptive sensory processing. Front. Comput. Neurosci. 4:156.
- C.V. Portfors, P.D. Roberts (2009) Over-representation of species-specific vocalizations in the awake mouse inferior colliculus. Neuroscience 162: 486-500.
- V. Balakrishnan, S.P. Kuo, P.D. Roberts and L.O. Trussel (2009) Slow glycinergic transmission mediated by transmitter pooling. Nature Neuroscience 12: 286-294.
- P.D. Roberts, C.V. Portfors (2008) Design principles of sensory processing in cerebellum-like structures. Early stage processing of electrosensory and auditory objects. Biol Cybern. 98: 491-507.