Abstract: A method of using spiking neural network delays to represent sequences includes assigning one or more symbol neurons to each symbol in a dictionary. The method also includes assigning a synapse from each symbol neuron in a group to a particular ngram neuron. A set of synapses associated with the group of symbol neurons comprises a bundle of synapses. In addition, the method includes assigning a delay to each synapse in the bundle. The method further includes representing a symbol sequence based on sequential spiking of symbol neurons and ngram neuron spikes in response to detecting inter event intervals.

Abstract: Methods and apparatus are provided for causal learning in which logical causes of events are determined based, at least in part, on causal saliency. One example method for causal learning generally includes observing one or more events with an apparatus, wherein the events are defined as occurrences at particular relative times; selecting a subset of the events based on one or more criteria; and determining a logical cause of at least one of the events based on the selected subset.

Abstract: Methods and apparatus are provided for designing spike-timing dependent plasticity (STDP) curves whose parameter values are based on a set of equations. One example method generally includes operating an artificial nervous system by determining a set of equations based at least in part on a form of an STDP function defined by one or more parameters, determining values of the parameters for the STDP function based at least in part on the set of equations, and operating at least a portion of the artificial nervous system according to the STDP function having the determined parameter values.