Automated discovery of algorithms from data.

To automate the discovery of new scientific and engineering principles, artificial intelligence must distill explicit rules from experimental data. This has proven difficult because existing methods typically search through the enormous space of possible functions. Here we introduce deep distilling, a machine learning method that does not perform searches but instead learns from data using symbolic essence neural networks and then losslessly condenses the network parameters into a concise algorithm written in computer code.

Explainable neural networks that simulate reasoning.

The success of deep neural networks suggests that cognition may emerge from indecipherable patterns of distributed neural activity. Yet these networks are pattern-matching black boxes that cannot simulate higher cognitive functions and lack numerous neurobiological features. Accordingly, they are currently insufficient computational models for understanding neural information processing.

Dynamic pupillometry as an autonomic testing tool.

Objective: To determine normal values for pupillometry indices in healthy control subjects and to examine these indices in patients with autonomic dysfunction and healthy controls.

Methods: Infrared video pupillometry was used to investigate the pupil response to a brief light flash in 79 healthy controls, 28 patients with normal autonomic function (composite autonomic severity score, CASS < 2), and 26 patients with moderate to severe autonomic failure (CASS > 4) seen in our autonomic laboratory from January 2008 to June 2011. In six subjects, we examined the effects of varying light stimulus intensity and light stimulus duration.

Objective characterization of the relative afferent pupillary defect in MS.

Objective: To develop an objective and precise neurophysiologic method from which to identify and characterize the presence and magnitude of relative afferent pupillary defects (RAPD) in patients with MS.

Methods: Binocular infrared pupillometry was performed in 40 control subjects and 32 MS patients with RAPDs, using two precisely defined sequences of alternating light flashes (right-left and left-right). We analyzed three distinct pupillary metrics in response to light stimulation.