Literature DB >> 9114232

Dynamics of neurons controlling movements of a locust hind leg II. Flexor tibiae motor neurons.

P L Newland1, Y Kondoh.   

Abstract

Imposed movements of a proprioceptor that monitors the relative position of the tibia about the femur, the femorotibial chordotonal organ (FeCO), evoke resistance reflexes in the motor neurons that control the movements of the tibia of the locust. The response dynamics of one pool of motor neurons, the flexor tibiae motor neurons, which are located in three groups (anterior, lateral, and posterior), have been analyzed by the Wiener kernel method. First- and second-order kernels that represent the linear and nonlinear responses, respectively, were computed by a cross-correlation between the intracellularly recorded synaptic responses in the motor neurons and the white noise stimulus applied to the FeCO, and were used to define the input-output characteristics of the motor neurons. The posterior fast, intermediate, and slow and the anterior fast and intermediate flexor tibiae motor neurons had biphasic first-order kernels with initial negative phases, indicating that they are velocity sensitive. The falling phases of the kernels had distinct shoulders, indicating that the responses of the motor neurons also had delayed low-pass components, i.e., position sensitivity. The anterior slow flexor motor neuron had a monophasic, low-passed, first-order kernel, indicating that it is position sensitive. The linear component of the motor neuron responses, predicted by convolving the first-order kernels with the stimulus signal, strongly resembled the actual response, whereas the second-order nonlinear component was small, particularly at > 10 Hz. The power spectra of the fast motor neurons showed that they had the highest cutoff frequencies (at > 8 Hz), whereas the slow flexor motor neurons had a gradual roll-off at 1 Hz. The intermediate flexor motor neuron had an intermediate cutoff frequency of approximately 2-3 Hz. The linear responses of the flexor motor neurons could be decomposed into low- and high-frequency components. The high-frequency components (> 10 Hz) were velocity dependent and linear, whereas the low-frequency components (< 10 Hz) were position dependent and nonlinear. The nonlinearity was a signal compression (or half-wave rectification). The results show that although the flexor motor neurons receive many common inputs during FeCO stimulation, each individual has specific dynamic response properties. The responses of the motor neurons are fractionated so that a given individual within the pool will respond best to position, whereas others will respond better to velocity. Likewise, some motor neurons respond best at low frequencies, whereas others respond best at higher frequencies of stimulation.

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Year:  1997        PMID: 9114232     DOI: 10.1152/jn.1997.77.4.1731

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  7 in total

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2.  A system identification analysis of neural adaptation dynamics and nonlinear responses in the local reflex control of locust hind limbs.

Authors:  Oliver P Dewhirst; Natalia Angarita-Jaimes; David M Simpson; Robert Allen; Philip L Newland
Journal:  J Comput Neurosci       Date:  2012-06-23       Impact factor: 1.621

3.  Coding characteristics of spiking local interneurons during imposed limb movements in the locust.

Authors:  A G Vidal-Gadea; X J Jing; D Simpson; O P Dewhirst; Y Kondoh; R Allen; P L Newland
Journal:  J Neurophysiol       Date:  2009-12-02       Impact factor: 2.714

4.  Delayed mutual information infers patterns of synaptic connectivity in a proprioceptive neural network.

Authors:  Wagner Endo; Fernando P Santos; David Simpson; Carlos D Maciel; Philip L Newland
Journal:  J Comput Neurosci       Date:  2015-02-03       Impact factor: 1.621

5.  Pre-processing and transfer entropy measures in motor neurons controlling limb movements.

Authors:  Fernando P Santos; Carlos D Maciel; Philip L Newland
Journal:  J Comput Neurosci       Date:  2017-08-09       Impact factor: 1.621

6.  Predictive control of intersegmental tarsal movements in an insect.

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7.  A size principle for recruitment of Drosophila leg motor neurons.

Authors:  Anthony W Azevedo; Evyn S Dickinson; Pralaksha Gurung; Lalanti Venkatasubramanian; Richard S Mann; John C Tuthill
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  7 in total

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