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Hybrid model of the context dependent vestibulo-ocular reflex: implications for vergence-version interactions

The vestibulo-ocular reflex (VOR) is an involuntary eye movement evoked by head movements. It is also influenced by viewing distance. This paper presents a hybrid nonlinear bilateral model for the horizontal angular vestibulo-ocular reflex (AVOR) in the dark. The model is based on known interconnect...

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Detalles Bibliográficos
Autores principales: Ranjbaran, Mina, Galiana, Henrietta L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4321407/
https://www.ncbi.nlm.nih.gov/pubmed/25709578
http://dx.doi.org/10.3389/fncom.2015.00006
Descripción
Sumario:The vestibulo-ocular reflex (VOR) is an involuntary eye movement evoked by head movements. It is also influenced by viewing distance. This paper presents a hybrid nonlinear bilateral model for the horizontal angular vestibulo-ocular reflex (AVOR) in the dark. The model is based on known interconnections between saccadic burst circuits in the brainstem and ocular premotor areas in the vestibular nuclei during fast and slow phase intervals of nystagmus. We implemented a viable switching strategy for the timing of nystagmus events to allow emulation of real nystagmus data. The performance of the hybrid model is evaluated with simulations, and results are consistent with experimental observations. The hybrid model replicates realistic AVOR nystagmus patterns during sinusoidal or step head rotations in the dark and during interactions with vergence, e.g., fixation distance. By simply assigning proper nonlinear neural computations at the premotor level, the model replicates all reported experimental observations. This work sheds light on potential underlying neural mechanisms driving the context dependent AVOR and explains contradictory results in the literature. Moreover, context-dependent behaviors in more complex motor systems could also rely on local nonlinear neural computations.