ABSTRACT
The durations of animals' brief vocalizations provide conspecifics with important recognition cues. In the present experiments, zebra finches and humans (trained musicians) were rewarded for responding after S+ (standard) auditory signals from 56 to 663 ms and not for responding after shorter or longer S- (comparison) durations from 10 to 3684 ms. With either a single standard (Experiment 1) or multiple standards (Experiment 2), both zebra finches and humans timed brief signals to about the same level of accuracy. The results were in qualitative agreement with predictions from scalar timing theory and its connectionist implementation in both experiments. The connectionist model provides a good quantitative account of temporal gradients with a single standard (Experiment 1) but not with multiple standards (Experiment 2).
Subject(s)
Auditory Perception/physiology , Songbirds/physiology , Time Perception/physiology , Adult , Animals , Female , Humans , Male , Neural Networks, Computer , Time FactorsABSTRACT
The acoustic frequency ranges in birdsongs and human speech can provide important pitch cues for recognition. Zebra finches and humans were trained to sort contiguous frequencies into 3 or 8 ranges, based on associations between the ranges and reward. The 3-range task was conducted separately in 3 spectral regions. Zebra finches discriminated 3 ranges in the medium and high spectral regions faster than in the low region and discriminated 8 ranges with precision. Humans discriminated 3 ranges in all 3 spectral regions to the same modest standard and acquired only a crude discrimination of the lowest and highest of 8 ranges. The results indicate that songbirds have a special sensitivity to the pitches in conspecific songs and, relative to humans, have a remarkable general ability to sort pitches into ranges.
Subject(s)
Auditory Threshold/physiology , Discrimination Learning/physiology , Pitch Discrimination/physiology , Songbirds/physiology , Acoustic Stimulation , Adult , Analysis of Variance , Animals , Communication , Concept Formation/physiology , Female , Generalization, Psychological/physiology , Hearing/physiology , Humans , Male , Memory/physiology , Models, Neurological , Music/psychology , Neural Networks, Computer , Species Specificity , Vocalization, Animal/physiology , Voice/physiologyABSTRACT
Hereditary motor sensory neuropathies (HSMN) encompass a wide range of related neuromuscular disorders. Electrodiagnostic studies are a powerful tool in differentiating between the different types. Timely rehabilitative treatment of the deformities may result in significant functional improvement and delay or obviate need for future surgery. This article outlines types of HSMN, focusing on the electrodiagnosis and treatment of each.
Subject(s)
Charcot-Marie-Tooth Disease/rehabilitation , Adolescent , Adult , Charcot-Marie-Tooth Disease/physiopathology , Child , Child, Preschool , Electrodiagnosis , Female , Foot Deformities, Congenital/physiopathology , Foot Deformities, Congenital/rehabilitation , Hereditary Sensory and Motor Neuropathy/classification , Hereditary Sensory and Motor Neuropathy/diagnosis , Hereditary Sensory and Motor Neuropathy/genetics , Humans , Infant , Male , Orthotic Devices , Physical Therapy Modalities/methodsABSTRACT
We trained songbirds and humans in go/no-go discriminations among 27 tones. In the compact discrimination, S + s formed a contiguous middle range (3080-4040 Hz), and S-s formed contiguous lower (2000-2960 Hz) and upper (4160-5120 Hz) ranges. In the distributed discrimination, S + s were spread across all 3 ranges. Songbirds acquired the compact discrimination more quickly and with higher accuracy than humans. Songbirds acquired the distributed discrimination only after much extended training; humans did not acquire the distributed discrimination. Compact groups (birds and humans) accurately classified test tones spaced 60 Hz from the training tones, but the distributed groups did not. A single reversal in discrimination between tones on the boundary between the lower S- and middle S + ranges did not propagate to all the tones in either range. A neural network model provided an account of the classification of tones in songbirds and humans.