Multiphasic neuronal transfer functions for representing temporal structure

Second-order temporal modulation transfer functions.

Detection thresholds were measured for a sinusoidal modulation applied to the modulation depth of a sinusoidally amplitude-modulated (SAM) white noise carrier as a function of the frequency of the modulation applied to the modulation depth (referred to as f'm). The SAM noise acted therefore as a "carrier" stimulus of frequency fm, and sinusoidal modulation of the SAM-noise modulation depth gene...

Spectro - Temporal Modulation Transfer Functions and Speech

Temporal coherence structure rapidly shapes neuronal interactions

Perception of segregated sources is essential in navigating cluttered acoustic environments. A basic mechanism to implement this process is the temporal coherence principle. It postulates that a signal is perceived as emitted from a single source only when all of its features are temporally modulated coherently, causing them to bind perceptually. Here we report on neural correlates of this proc...

On Representing the Temporal Structure of a Natural Language Text

A proposal to deal with tenses in the framework of Discourse Representat ion Theory is presented, ms it has been implemented for a fragment a t the IMS for the project LILOG. It is based on the theory of tenses of H. K a m p and Ch. Rohrer. The system uses tile tense and aspect information, the information about the tempora l discourse s t ruc ture of tile preceding text stored in a specific li...

Representing local structure in Bayesian networks by Boolean functions

A number of studies on learning Bayesian networks have emphasized the importance of exploiting regularities in conditional probability distributions, i.e., local structure. In this paper, we encode local structures as linear combinations of Boolean functions. By using Lasso, we can simultaneously estimate the structure and parameters of the networks from limited data. We demonstrate that the me...