Neural Signal Processing Algorithms
technological and experimental advances in the capabilities to record
signals from neural systems have led to an unprecedented increase in
the types and volume of data collected in neuroscience experiments and
hence, in the need for appropriate techniques to analyze them.
Therefore, using combinations of likelihood, Bayesian, state-space,
time-series and point process approaches, a primary focus of the
research in my laboratory is the development of statistical methods and
signal-processing algorithms for neuroscience data analysis.
We have used our methods to:
- characterize how hippocampal neurons represent spatial information in their ensemble firing patterns.
- analyze formation of spatial receptive fields in the hippocampus during learning of novel environments.
- relate changes in hippocampal neural activity to changes in performance during procedural learning.
- improve signal extraction from fMR imaging time-series.
- characterize the spiking properties of neurons in primary motor cortex.
dynamically sources of neural activity in the brain from EEG and MEG
recordings made during cognitive, motor and somatosensory tasks.
- measure the period of the circadian pacemaker (human biological clock) and its sensitivity to light.
- characterize the dynamics of human heart beats in physiological and pathological states.
Understanding General Anesthesia
General anesthesia is a fascinating man-made,
neurophysiological phenomenon that has been developed empirically to enable safe
and humane performance of surgical and non-surgical procedures. The state
consists of unconsciousness, amnesia, analgesia, and immobility along with maintenance
of physiological stability. In the United States, more than 60,000 patients
receive general anesthesia daily. Despite
use of general anesthesia in this country for nearly 166 years, how these drugs
act in the brain and central nervous system to create this state remains poorly
understood. In 2005, Science
considered understanding anesthetic mechanisms to be one of the important unsolved
mysteries of modern medicine.