Literature DB >> 7623084

Dynamics of neurons controlling movements of a locust hind leg: Wiener kernel analysis of the responses of proprioceptive afferents.

Y Kondoh1, J Okuma, P L Newland.   

Abstract

1. The response properties of proprioceptive sensory neurons providing input to the local circuits controlling leg movements of the locust have been analysed by the Wiener kernel method. The proprioceptor, the femoral chordotonal organ, encodes the position and movements of the tibia about the femorotibial joint. 2. Intracellular recordings were made from sensory neurons while the apodeme of the organ was moved with a band-limited Gaussian white noise signal with a cutoff frequency of 27, 58, or 117 Hz. To define the input-output characteristics of the neurons, the first- and second-order Wiener kernels were computed by a cross-correlation between the spike response of the afferents and the white noise stimulus. 3. White noise stimulation elicited sustained spiking in 50 out of 54 afferents throughout the 20 s periods of stimulation and recording. The first-order kernels, the linear response properties, of these afferents were of six basic types that were dependent on the cutoff frequency of the white noise stimulus. These included 1) flexion-sensitive afferents that were primarily position sensitive irrespective of stimulus frequency, 2) flexion-sensitive afferents that were position sensitive at low frequencies but also coded velocity at higher frequencies, 3) flexion-sensitive afferents that coded velocity at all stimulus frequencies, 4) flexion-sensitive afferents that coded velocity at low stimulus frequencies but also acceleration at high frequencies, 5) extension-sensitive afferents that coded velocity at all stimulus frequencies, and 6) extension-sensitive afferents that coded velocity at low stimulus frequencies and acceleration at high frequencies. A seventh type contained the four remaining afferents that adapted rapidly to the stimulus within 3-5 s. These were all extension-acceleration sensitive irrespective of stimulus frequency. 4. The gain curves (produced by Fourier transform of the 1st-order kernels) and the power spectra of the linear models (produced by convolving the 1st-order kernels with the white noise) demonstrated that responses in the position-sensitive afferents are representative of a constant gain low-pass filter with a cutoff frequency of approximately 80 Hz, whereas those in the velocity- and acceleration-sensitive afferents are band passed, having peaks at 80 Hz. 5. The main nonlinearity was a signal compression in which the diagonal peak(s) of the second-order nonlinear kernels offset one or more peaks of the first-order kernels and represents a rectification or directional sensitivity of the afferents.(ABSTRACT TRUNCATED AT 400 WORDS)

Mesh:

Year:  1995        PMID: 7623084     DOI: 10.1152/jn.1995.73.5.1829

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


  9 in total

1.  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

2.  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

3.  Neural circuitry underlying linear representation of wind information in a nonspiking local interneuron of the cockroach.

Authors:  J Okuma; Y Kondoh
Journal:  J Comp Physiol A       Date:  1996-12       Impact factor: 1.836

4.  Characterization of the encoding properties of intraspinal mechanosensory neurons in the lamprey.

Authors:  Nicole Massarelli; Allan L Yau; Kathleen A Hoffman; Tim Kiemel; Eric D Tytell
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2017-07-12       Impact factor: 1.836

5.  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

6.  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

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

Authors:  Alicia Costalago-Meruelo; David M Simpson; Sandor M Veres; Philip L Newland
Journal:  J Comput Neurosci       Date:  2017-04-22       Impact factor: 1.621

Review 8.  Mechanosensation and Adaptive Motor Control in Insects.

Authors:  John C Tuthill; Rachel I Wilson
Journal:  Curr Biol       Date:  2016-10-24       Impact factor: 10.834

9.  Neural Coding of Leg Proprioception in Drosophila.

Authors:  Akira Mamiya; Pralaksha Gurung; John C Tuthill
Journal:  Neuron       Date:  2018-10-04       Impact factor: 18.688

  9 in total

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