FACULTY
Associate Professor
Ludwig-Maximilians-Universität,
München, Germany
Ph.D. in Physics and Computer Science, 1996
Office: Steinman Hall, T-403C
Phone: 212.650.7211
Email: parra@ccny.cuny.edu
• Research Interests:Probabilistic modeling of biological signals with particular focus on novel brain imaging modalities.
Neural Signals Research at CCNY
We are interested in the analysis and modeling of neuronal signals. We emphasize multivariate probabilistic modeling and state-of-the-art machine learning techniques. Our research addresses the following fundamental question: how does the central nervous system encode and process temporal information? Current project areas include:
Hearing and Speech Perception: We are performing psycho-acoustics experiments to confirm prediction from models on auditory perception. For example, one model explains tinnitus and the Zwicker phantom tone as the consequence of a simple temporal adaptation of power gains. In a second experiment we are testing predictions on the integration of auditory and visual information during speech understanding in noisy environments. Our hypothesis goes beyond the conventional interpretation that the visual modality is used for lip-reading. We argue instead that the temporal correlation between sound and vision is critical for improved understanding.
Models of Spike-Time Encoding: We study the importance of precise spike timing in computational models of spiking neural networks. Current projects study the effect of timing on information transmission during normal function or model the mechanism of pathological synchronization during epilepsy.
Electro-encephalography (EEG): We develop methods to interpret human EEG signals in real-time. In our high-density EEG lab we design novel motion control for prosthetics, explore the utility of neurophysiology to augment human-computer interfaces, and experiment with real-time feedback stimulation during human perception.
Magnetic Resonance Spectroscopy (MRS): We are also developing tools for the analysis of MRS images. The goal of this clinical research project is to identify markers of metabolic function indicative of brain tumors.
For more details consult the list of publications.
