Chuong T. Nguyen

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In the brain, high cognitive functions are encoded by coherent network oscillations. Key players are inhibitory interneurons that, by releasing GABA into principal cells, pace targeted cells. Among these, oriens-lacunosum moleculare (O-LM) interneurons that provide a theta frequency patterned output to distal dendrites of pyramidal cells are endowed with(More)
Genetic mutations in leucine-rich repeat kinase 2 (LRRK2) have been linked to autosomal dominant Parkinson's disease. The most prevalent mutation, G2019S, results in enhanced LRRK2 kinase activity that potentially contributes to the etiology of Parkinson's disease. Consequently, disease progression is potentially mediated by poorly characterized(More)
We introduce a multicomponent invertible AM-FM image transform and use it to define new nonlinear AM-FM filters for performing modulation domain image processing. The key elements of the transform are analysis and synthesis filterbanks based on the steerable image pyramid and perfect reconstruction demodulation algorithms based on analytic differentiation(More)
We combine an adaptation of the steerable image pyramid sub-band decomposition with a spline-based perfect reconstruction de-modulation algorithm to obtain an invertible AM-FM image transform. For the first time, we achieve perceptually-based signal processing goals by applying filtering operations directly to the computed subband amplitude and frequency(More)
Understanding how ligands bind to G-protein coupled receptors (GPCRs) provides insights into a myriad of cell processes and is crucial for drug development. Here we extend a hybrid molecular mechanics/coarse-grained (MM/CG) approach applied previously to enzymes to GPCR/ligand complexes. The accuracy of this method for structural predictions is established(More)
For the first time, we compute modulation domain features for infrared targets and backgrounds, including dominant modulations that characterize the local texture contrast, orientation, and granularity. We present a practical computational approach and introduce a new FM algorithm designed to reduce the approximation errors characteristic of many existing(More)
For the first time, we demonstrate modulation domain image filters that achieve perceptually motivated image processing goals by directly manipulating the FM functions in a multi-component AM-FM image model. The action of previous modulation domain filters has been limited to modification of the AM functions based on the values of the AM and FM functions.(More)
Challenging infrared data sequences such as the well-known AMCOM closure sequences are characterized by highly nonsta-tionary, evolutionary target and clutter signatures, poor target-to-clutter ratios, and complex kinematics arising from both the target motion and the motion of the sensor platform itself. In such cases, track consistency checks can provide(More)
We compute AM-FM models for infrared video frames depicting military targets immersed in structured clutter backgrounds. We show that independent correlation based detection processes can be implemented in the pixel and modulation domains and used to construct useful online track consistency checks that indicate when the detection process has been degraded(More)