2008
DOI: 10.1121/1.2933955
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Acoustics of shape recognition by a dolphin in a cross-modal matching-to-sample paradigm

Abstract: A pacific bottlenose dolphin was trained in a two-alternative cross-modal matching-to-sample paradigm. The animal was able to inspect complex PVC-pipe shapes through echolocation or vision but never through both senses simultaneously. Acoustic data was collected through a 3-channel high-frequency recording system while the dolphin performed one of the following tasks: (1) match a complex shape with its sonar only (pure echoic matching), (2) match from vision to echolocation and (3) match from echolocation to v… Show more

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Cited by 3 publications
(2 citation statements)
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“…Probably the best-studied example of cross-modal perception in dolphins concerns their ability to link auditory and visual cues. Dolphins are able to recognize objects visually that were previously inspected by echolocation and vice versa (e.g., Herman et al, 1998;DeLong et al, 2000;Hoffmann-Kuhnt et al, 2008). Furthermore, dynamic information about movement, in addition to stationary objects, can be perceived across those two senses .…”
Section: Further Questions and Potentially Promising Approaches On Pementioning
confidence: 99%
“…Probably the best-studied example of cross-modal perception in dolphins concerns their ability to link auditory and visual cues. Dolphins are able to recognize objects visually that were previously inspected by echolocation and vice versa (e.g., Herman et al, 1998;DeLong et al, 2000;Hoffmann-Kuhnt et al, 2008). Furthermore, dynamic information about movement, in addition to stationary objects, can be perceived across those two senses .…”
Section: Further Questions and Potentially Promising Approaches On Pementioning
confidence: 99%
“…To our surprise despite the change in setup the dolphin was still able to perform the task. This would lead to the conclusion that the dolphin might not (2), bubble screen (3), bite-plate (4), frame (5), stimulus (6), object holder (7) and position of the hydrophone array frame in red (8). One side panel is removed to see the placement of the object.…”
Section: Introductionmentioning
confidence: 99%