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Journal of Comparative Physiology A-neuroethology Sensory Neural and Behavioral Physiology | 1982

Selective laryngeal neurotomy and the control of phonation by the echolocating bat,Eptesicus

Roderick A. Suthers; James M. Fattu

Summary1.The effect, on the subglottic pressure and on the emitted orientation sounds, of selectively cutting nerves to various laryngeal muscles of the Big Brown Bat,Eptesicus fuscus, was studied.2.Bilateral inferior laryngeal neurotomy caused no change in the repetition rate, duration, initial frequency or bandwidth of downward sweeping frequency modulated (FM) pulses, but after this treatment mean subglottic pressure at pulse onset was lowered 8 to 16 cm H2O and the mean peak pulse intensity was reduced 4 to 5 dB. The relationship of subglottic pressure to the bandwidth of the FM sweep was also altered (Table 1, Figs. 1, 2, 3).3.Inferior laryngeal neurotomy also caused the bat to produce atypical rising FM pulses which began at about 20 kHz and swept upward almost one octave (Table 1, Fig. 2).4.Total bilateral superior laryngeal neurotomy eliminated most of the FM and reduced the fundamental frequency to 7.9 kHz with multiple harmonics (Fig. 4). Pulse duration became highly variable and the peak sound pressure level (SPL) dropped 7 to 13 dB (Table 2). The correlation between subglottic pressure and pulse SPL was also eliminated.5.Bilateral section of only the caudal branch of the superior laryngeal nerve reduced the fundamental frequency of the pulses to 10 kHz and eliminated most of the frequency modulation. Pulse SPL was reduced about 10 dB, but pulse onset subglottic pressure remained correlated with the maximum SPL (Table 2).6.Paralysis of the tongue by bilateral section of the hypoglossal nerves distal to the thyrohyoid twigs had no detectable effect on the downward sweeping FM pulses, but caused the bats to also emit long duration pulses whose frequency rose and fell in a sinusoidal fashion (Figs. 5, 6).7.The muscular control of pulse frequency and intensity is discussed in the light of these data. The aberrant rising FM after section of the inferior laryngeal nerves and sigmoid pulses after hypoglossal neurotomy can be understood as the result of timing errors in the opening and/or closing of the glottis relative to the contraction-relaxation cycle of the cricothyroid muscles.


Journal of Comparative Physiology A-neuroethology Sensory Neural and Behavioral Physiology | 1981

Subglottic pressure and the control of phonation by the echolocating bat,Eptesicus

James M. Fattu; Roderick A. Suthers

Summary1.The respiratory dynamics of phonation, particularly the relationship between subglottic pressure and the sound pressure level (SPL), frequency and duration of vocalizations by nine bats (Eptesicus fuscus) is described.2.Subglottic pressure rises to about 30 or 40 cm H2O immediately prior to emission of a single FM pulse or group of pulses, respectively, and drops 5 to 20 cm H2O during the course of each pulse (Fig. 2).3.The maximum SPL of the echolocative pulse is positively correlated with the magnitude of the subglottic pressure at the onset of phonation in eight bats. The unusually high subglottic pressure in bats is an adaptation for the production of high intensity orientation pulses, thus increasing the range of echolocation.4.The maximum SPL was proportional to the subglottic pressure at the pulse onset raised to a power which ranged from a mean of 0.4 to 1.36 for individualEptesicus (Fig. 3 and Table 1). The approximately linear relationship between sound pressure level and onset subglottic pressure in several bats suggests the vocal tract has a minimal effect on pulse intensity.5.Within a given vocalization, upward sweeping FM is usually associated with either constant or increasing subglottic pressure (Figs. 4 and 5), but the absolute value of the subglottic pressure at pulse onset is correlated with the initial frequency of vocalization in only four of these bats (Table 2).6.Subglottic pressure drops most rapidly during short pulses, but during long vocalizations (exceeding 20 ms) it attains a minimum rate of decline of about 0.2 cm H2O/ms (Fig. 6 and Table 2), which may be determined by the maximum glottal resistance at which phonation can occur.7.The relatively non-compliant lung ofEptesicus (mean static compliance = 0.021 ±0.002 ml/cm H2O) may be an adaptation for the production of the unusually high subglottic pressures needed to produce high intensity echolocative pulses.


annual symposium on computer application in medical care | 1983

Application of a new theorem of a posteriori probabilities of events to medical diagnosis

James M. Fattu; Edward A. Patrick

A posteriori probabilities of events where there are complex classes has recent ly been described by a new theorem [1,2]. The theorem is incorporated in the CONSULT-I language of artificial intelligence and statistical pattern recognition. This paper presents implementation of the CONSULT-I language applied to Thyroid Disorders. Performance is reported and compared to previous versions [3,4].


Archive | 1988

Integrated expert system for medical imaging scan, set-up, and scheduling

Raymond E. Gangarosa; Edward A. Patrick; James M. Fattu; Andrew S. Green


Archive | 1986

Artificial Intelligence with Statistical Pattern Recognition

Edward A. Patrick; James M. Fattu


American Journal of Clinical Pathology | 1987

The Use of an Expert System in the Clinical Laboratory as an Aid in the Diagnosis of Anemia

Blomberg Dj; Ladley Jl; James M. Fattu; Patrick Ea


Computers in Biology and Medicine | 1982

Thyroid disorders: Automatic diagnosis in CONSULT I

James M. Fattu; Edward A. Patrick; William Sutton


annual symposium on computer application in medical care | 1987

Consult Learning System Applied to Early Diagnosis of Chest Pain.

James M. Fattu; David J. Blomberg; Edward A. Patrick


Computer Methods and Programs in Biomedicine | 1986

Evaluation of a new classification system for anemias using consult learning system

David J. Blomberg; Jo Ladley Guth; James M. Fattu; E.A. Patrick


annual symposium on computer application in medical care | 1985

An Expert System Developed from a Hard Data Knowledge Base: Example of a Laboratory Based Anemia Consultant.

James M. Fattu; David J. Blomberg; Edward A. Patrick; Jo Ladley Guth

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Roderick A. Suthers

Indiana University Bloomington

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E.A. Patrick

University of Cincinnati

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