Abstract not found

of rewards, and rons show phasic activations after primary liquid and food rewards and conditioned, reward-predicting visual and auditory stimuli. the availability of rewards determines some of the basic They show biphasic, activation-depression responses after stimuli parameters of the subject’s life

The lateral intraparietal area (area LIP) contains a multimodal repre-sentation of extra-personal space. To further examine this represen-tation, we trained rhesus monkeys on the predictive-cueing task. During this task, monkeys shifted their gaze to a visual target whose location was predicted

information from visual and auditory systems is integrated so as to reduce the variance in localization. (2) The effects of a remapping in the relation between visual and auditory space can be predicted from a simple learning rule. (3) The temporal propagation of errors in estimating the hand

, and the mean frequency of the EEG spectrum (MF), was found to be the best combination for predicting the auditory alertness level. In the visual task study, the mean frequency of the beta band (Fβ, 13 – 32 Hz) was the only EEG feature selected. The application of an averaging subwindow procedure within a

ABSTRACT Individuals typically derive substantial benefit to speech recognition from combining auditory (A) and visual (V) cues. However, there is considerable variability in AV speech recognition, even when individual differences in A and V performance are taken into account. In this paper

Attention modulates auditory perception, but there are currently no simple tests that specifically quantify this modulation. To fill the gap, we developed a new, easy-to-use test of attention in listening (TAIL) based on reaction time. On each trial, two clearly audible tones were presented

We interpret the sound reaching our ears as the combined effect of independent, sound-producing entities in the external world; hearing would have limited usefulness if were defeated by overlapping sounds. Computer systems that are to interpret real-world sounds for speech recognition or for multimedia indexing must similarly interpret complex mixtures. However, existing functional models of audition employ only data-driven processing incapable of making context-dependent inferences in the face of interference. We propose aprediction-driven approach to this problem, raising numerous issues including the need to represent any kind of sound, and to handle multiple competing hypotheses. Results from an implementation of this approach illustrate its ability to analyze complex, ambient sound scenes that would confound previous systems.

not explain speech intelligiblity for “auditory chimaeras ” [8] where speech information is primarily in the TFS [4], motivating the inclusion of TFS neural cues in the predictive models. A speech corpus of 1,750 sentences divided into five chimaera types, subjectively scored by 5 normal hearing listeners

Predicting auditory space calibration from recent multisensory experience