Profile analysis in listeners with normal and elevated audiometric thresholds: Behavioral and modeling results.

Profile-analysis experiments measure the ability to discriminate complex sounds based on patterns, or profiles, in their amplitude spectra. Studies of profile analysis have focused on normal-hearing listeners and target frequencies near 1 kHz. To provide more insight into underlying mechanisms, we studied profile analysis over a large target frequency range (0.

Representations of fricatives in subcortical model responses: Comparisons with human consonant perception.

Fricatives are obstruent sound contrasts made by airflow constrictions in the vocal tract that produce turbulence across the constriction or at a site downstream from the constriction. Fricatives exhibit significant intra/intersubject and contextual variability. Yet, fricatives are perceived with high accuracy.

Sensorineural Hearing Loss Diminishes Use of Temporal Envelope Cues: Evidence From Roving-Level Tone-in-Noise Detection.

Objectives: The objective of our study is to understand how listeners with and without sensorineural hearing loss (SNHL) use energy and temporal envelope cues to detect tones in noise. Previous studies of low-frequency tone-in-noise detection have shown that when energy cues are made less reliable using a roving-level paradigm, thresholds of listeners with normal hearing (NH) are only slightly increased. This result is consistent with studies demonstrating the importance of temporal envelope cues for masked detection.

Detection thresholds for amplitude modulations of tones in budgerigar, rabbit, and human.

Envelope fluctuations of complex sounds carry information that is -essential for many types of discrimination and for detection in noise. To study the neural representation of envelope information and mechanisms for processing of this temporal aspect of sounds, it is useful to identify an animal model that can -sensitively detect amplitude modulations (AM). Low modulation frequencies, which dominate speech sounds, are of particular interest.

Semi-supervised spike sorting using pattern matching and a scaled Mahalanobis distance metric.

Sorting action potentials (spikes) from tetrode recordings can be time consuming, labor intensive, and inconsistent, depending on the methods used and the experience of the operator. The techniques presented here were designed to address these issues. A feature related to the slope of the spike during repolarization is computed.