Biomedical subjects

Edward W Large

Publications and source records attributed to Edward W Large.

2 recordsLinked to original sources

PubMed2002

Tracking simple and complex sequences.

We address issues of synchronization to rhythms of musical complexity. In two experiments, synchronization to simple and more complex rhythmic sequences was investigated. Experiment 1 examined responses to phase and tempo perturbations within simple, structurally isochronous sequences, presented at different base rates. Experiment 2 investigated responses to similar perturbations embedded within more complex, metrically structured sequences; participants were explicitly instructed to synchronize at different metrical levels (i.e., tap at different rates to the same rhythmic patterns) on different trials. We found evidence that (1) the intrinsic tapping frequency adapts in response to temporal perturbations in both simple (isochronous) and complex (metrically structured) rhythms, (2) people can synchronize with unpredictable, metrically structured rhythms at different metrical levels, with qualitatively different patterns of synchronization seen at higher versus lower levels of metrical structure, and (3) synchronization at each tapping level reflects information from other metrical levels. The latter finding provides evidence for a dynamic and flexible internal representation of the sequence's metrical structure.

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PubMedDate not supplied

Auditory temporal computation: interval selectivity based on post-inhibitory rebound.

The measurement of time is fundamental to the perception of complex, temporally structured acoustic signals such as speech and music, yet the mechanisms of temporal sensitivity in the auditory system remain largely unknown. Recently, temporal feature detectors have been discovered in several vertebrate auditory systems. For example, midbrain neurons in the fish Pollimyrus are activated by specific rhythms contained in the simple sounds they use for communication. This poses the significant challenge of uncovering the neuro-computational mechanisms that underlie temporal feature detection. Here we describe a model network that responds selectively to temporal features of communication sounds, yielding temporal selectivity in output neurons that matches the selectivity functions found in the auditory system of Pollimyrus. The output of the network depends upon the timing of excitatory and inhibitory input and post-inhibitory rebound excitation. Interval tuning is achieved in a behaviorally relevant range (10 to 40 ms) using a biologically constrained model, providing a simple mechanism that is suitable for the neural extraction of the relatively long duration temporal cues (i.e. tens to hundreds of ms) that are important in animal communication and human speech.

Acoustic Stimulation↗