Supercomputer framework for reverse engineering firing patterns of neuron populations to identify their synaptic inputs.

In this study, we develop new reverse engineering (RE) techniques to identify the organization of the synaptic inputs generating firing patterns of populations of neurons. We tested these techniques in silico to allow rigorous evaluation of their effectiveness, using remarkably extensive parameter searches enabled by massively-parallel computation on supercomputers. We chose spinal motoneurons as our target neural system, since motoneurons process all motor commands and have well-established input-output properties.

Prediction of correlation energies using variational subspace valence bond.

In the variational subspace valence bond (VSVB) [G. D. Fletcher, J.

Duration of symptoms and manometric parameters offer clues to diagnosis of pseudoachalasia.

Background: Pseudoachalasia manifests high-resolution manometry (HRM) findings of achalasia but results from a secondary process. We analyzed clinical and HRM characteristics of pseudoachalasia, including malignant and non-malignant subtypes.

Methods: High-resolution manometry was retrospectively reviewed in patients with confirmed pseudoachalasia, and corroborated with endoscopic and radiographic studies.

Valence : A Massively Parallel Implementation of the Variational Subspace Valence Bond Method.

This work describes the software package, Valence, for the calculation of molecular energies using the variational subspace valence bond (VSVB) method. VSVB is an ab initio electronic structure method based on nonorthogonal orbitals. Important features of practical value include high parallel scalability, wave functions that can be constructed automatically by combining orbitals from previous calculations, and ground and excited states that can be modeled with a single configuration or determinant.