Ramani S. Pilla

Changes in the amplitude and timing of the hemodynamic response associated with prepulse inhibition of acoustic startle

Disruption of the early stages of information processing in limbic brain circuits may underlie symptoms of severe neuropsychiatric disorders. Prepulse inhibition of acoustic startle (PPI) is diminished in many of these disorders and may reflect the disruption of this CNS function. PPI is associated with brain activity in many of the same regions in humans as it is in laboratory animals, suggesting that neuroimaging studies in humans may help localize deficits that can then be elucidated in animal models. In this article, we employed a rapid presentation event-related design during continuous EPI BOLD scanning to examine hemodynamic response functions (HRFs) associated with PPI. Fourteen healthy participants listened to 100 pulse alone and 100 prepulse combined with pulse (prepulse-pulse) trials. PPI is the normalized difference in the startle response to the two trial types. Following the prepulse-pulse trials, the amplitudes of the HRFs in auditory cortices and in the anterior insula were increased, while in the cerebellum, thalamus and anterior cingulate, they were decreased, relative to the pulse alone trials. In addition, the timing of the prepulse-pulse responses was delayed in the auditory cortices, anterior insula and cerebellum. Finally, PPI measured outside the scanner was predicted by the difference in BOLD responses between trial types in the anterior insula and in the cerebellum. The results suggest that prepulse inhibition, and by extension early stages of information processing, modulate both the amplitude as well as timing of neural activity.

New technique for finding needles in haystacks : Geometric approach to distinguishing between a new source and random fluctuations

We propose a new test statistic based on a score process for determining the statistical significance of a putative signal that may be a small perturbation to a noisy experimental background. We derive the reference distribution for this score test statistic; it has an elegant geometrical interpretation as well as broad applicability. We illustrate the technique in the context of a model problem from high-energy particle physics. Monte Carlo experimental results confirm that the score test results in a significantly improved rate of signal detection.

Iteratively Reweighted Generalized Least Squares for Estimation and Testing With Correlated Data: An Inference Function Framework

The focus of this article is on fitting regression models and testing of general linear hypotheses for correlated data using quasi-likelihood based techniques. The class of generalized method of moments or GMMs provides an elegant approach for estimating a vector of regression parameters from a set of score functions. Extending the principle of the GMMs, in the generalized estimating equation framework, leads to a quadratic inference function or QIF approach for the analysis of correlated data. We derive an iteratively reweighted generalized least squares or IRGLS algorithm for finding the QIF estimator and establish its convergence properties. A software library implementing the techniques is demonstrated through several datasets.