Literature DB >> 1912007

Linear systems analysis of the relationship between firing of deep cerebellar neurons and the classically conditioned nictitating membrane response in rabbits.

N E Berthier1, A G Barto, J W Moore.   

Abstract

The correlation of the activity of neurons in the interposed and dentate nuclei of the cerebellum with conditioned movements of the nictitating membrane was investigated using linear systems analysis. The activity of single deep cerebellar nuclear cells was assumed to be the input to a linear system that produced nictitating membrane movement. Data were initially analyzed with a causal model to assess the degree to which past neural activity predicted the conditioned response. 55 of 165 cells had correlation coefficients of 0.50 or greater between the model's moment-to-moment output and the actual output, with two interpositus cells having correlation coefficients of greater than 0.90. Double-sided impulse responses indicated that afference from the face and efference copy probably affect deep cerebellar neural activity. Nonlinearities were also found in the relationship between neuronal activity and conditioned movement. It was concluded that cerebellar deep nuclear firing is highly correlated with future nictitating membrane movements but that the firing-movement relationship contains noncausal and nonlinear components.

Entities:  

Mesh:

Year:  1991        PMID: 1912007     DOI: 10.1007/bf00202384

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  16 in total

1.  Activity of deep cerebellar nuclear cells during classical conditioning of nictitating membrane extension in rabbits.

Authors:  N E Berthier; J W Moore
Journal:  Exp Brain Res       Date:  1990       Impact factor: 1.972

2.  The feline oculomotor nucleus: morphological subdivisions and projection to the cerebellar cortex and nuclei.

Authors:  G K Røste; E Dietrichs
Journal:  Anat Embryol (Berl)       Date:  1988

3.  Cerebellar neuronal activity related to whole-arm reaching movements in the monkey.

Authors:  P A Fortier; J F Kalaska; A M Smith
Journal:  J Neurophysiol       Date:  1989-07       Impact factor: 2.714

4.  Neuronal population coding of movement direction.

Authors:  A P Georgopoulos; A B Schwartz; R E Kettner
Journal:  Science       Date:  1986-09-26       Impact factor: 47.728

5.  The formulae-relating slopes, correlation coefficients and variance ratios used to determine stimulus- or movement-related neuronal activity.

Authors:  D Commenges; J Seal
Journal:  Brain Res       Date:  1986-09-24       Impact factor: 3.252

6.  Extraocular muscle afferents to the cerebellum of the cat.

Authors:  A F Fuchs; H H Kornhuber
Journal:  J Physiol       Date:  1969-02       Impact factor: 5.182

7.  Two-sided linear filter identification.

Authors:  I W Hunter; R E Kearney
Journal:  Med Biol Eng Comput       Date:  1983-03       Impact factor: 2.602

8.  Relationships between sensory input, motor output and unit activity in interpositus and red nuclei during intentional movement.

Authors:  J F Soechting; J E Burton; N Onoda
Journal:  Brain Res       Date:  1978-08-18       Impact factor: 3.252

9.  Mossy fiber projections to the cerebellar flocculus from the extraocular muscle afferents.

Authors:  K Maekawa; M Kimura
Journal:  Brain Res       Date:  1980-06-09       Impact factor: 3.252

10.  Cerebellar Purkinje cell activity related to the classically conditioned nictitating membrane response.

Authors:  N E Berthier; J W Moore
Journal:  Exp Brain Res       Date:  1986       Impact factor: 1.972

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  5 in total

1.  Dynamic changes in the cerebellar-interpositus/red-nucleus-motoneuron pathway during motor learning.

Authors:  Raudel Sánchez-Campusano; Agnès Gruart; José M Delgado-García
Journal:  Cerebellum       Date:  2011-12       Impact factor: 3.847

2.  Identification of physiological systems: a robust method for non-parametric impulse response estimation.

Authors:  D T Westwick; R E Kearney
Journal:  Med Biol Eng Comput       Date:  1997-03       Impact factor: 2.602

Review 3.  Neural circuitry and plasticity mechanisms underlying delay eyeblink conditioning.

Authors:  John H Freeman; Adam B Steinmetz
Journal:  Learn Mem       Date:  2011-10-03       Impact factor: 2.460

4.  Control of rabbit nictitating membrane movements. II. Analysis of the relation of motoneuron activity to behavior.

Authors:  G T Bartha; R F Thompson
Journal:  Biol Cybern       Date:  1992       Impact factor: 2.086

5.  An agonist-antagonist cerebellar nuclear system controlling eyelid kinematics during motor learning.

Authors:  Raudel Sánchez-Campusano; Agnès Gruart; Rodrigo Fernández-Mas; José M Delgado-García
Journal:  Front Neuroanat       Date:  2012-03-14       Impact factor: 3.856

  5 in total

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