Computational capacity of LRC, memristive, and hybrid reservoirs.

Reservoir computing is a machine learning paradigm that uses a high-dimensional dynamical system, or reservoir, to approximate and predict time series data. The scale, speed, and power usage of reservoir computers could be enhanced by constructing reservoirs out of electronic circuits, and several experimental studies have demonstrated promise in this direction. However, designing quality reservoirs requires a precise understanding of how such circuits process and store information.

Global minimization via classical tunneling assisted by collective force field formation.

Simple elements interacting in networks can give rise to intricate emergent behaviors. Examples such as synchronization and phase transitions often apply in many contexts, as many different systems may reduce to the same effective model. Here, we demonstrate such a behavior in a model inspired by memristors.

Conducting-insulating transition in adiabatic memristive networks.

The development of neuromorphic systems based on memristive elements-resistors with memory-requires a fundamental understanding of their collective dynamics when organized in networks. Here, we study an experimentally inspired model of two-dimensional disordered memristive networks subject to a slowly ramped voltage and show that they undergo a discontinuous transition in the conductivity for sufficiently high values of memory, as quantified by the memristive ON-OFF ratio. We investigate the consequences of this transition for the memristive current-voltage characteristics both through simulation and theory, and demonstrate the role of current-voltage duality in relating forward and reverse switching processes.

Predicting cognitive decline in subjects at risk for Alzheimer disease by using combined cerebrospinal fluid, MR imaging, and PET biomarkers.

Purpose: To assess the extent to which multiple Alzheimer disease (AD) biomarkers improve the ability to predict future decline in subjects with mild cognitive impairment (MCI) compared with predictions based on clinical parameters alone.

Materials And Methods: All protocols were approved by the institutional review board at each site, and written informed consent was obtained from all subjects. The study was HIPAA compliant.