Spatiotemporal Processing of Linear Acceleration: Primary Afferent and Central Vestibular Neuron Responses

Abstract

Spatiotemporal convergence and two-dimensional (2-D) neural tuning have been proposed as a major neural mechanism in the signal processing of linear acceleration. To examine this hypothesis, we studied the firing properties of primary otolith afferents and central otolith neurons that respond exclusively to horizontal linear accelerations of the head (0.16-10 Hz) in alert rhesus monkeys. Unlike primary afferents, the majority of central otolith neurons exhibited 2-D spatial tuning to linear acceleration. As a result, central otolith dynamics vary as a function of movement direction. During movement along the maximum sensitivity direction, the dynamics of all central otolith neurons differed significantly from those observed for the primary afferent population. Specifically at low frequencies (</=0.5 Hz), the firing rate of the majority of central otolith neurons peaked in phase with linear velocity, in contrast to primary afferents that peaked in phase with linear acceleration. At least three different groups of central response dynamics were described according to the properties observed for motion along the maximum sensitivity direction. "High-pass" neurons exhibited increasing gains and phase values as a function of frequency. "Flat" neurons were characterized by relatively flat gains and constant phase lags (approximately 20-55 degrees ). A few neurons ("low-pass") were characterized by decreasing gain and phase as a function of frequency. The response dynamics of central otolith neurons suggest that the approximately 90 degrees phase lags observed at low frequencies are not the result of a neural integration but rather the effect of nonminimum phase behavior, which could arise at least partly through spatiotemporal convergence. Neither afferent nor central otolith neurons discriminated between gravitational and inertial components of linear acceleration. Thus response sensitivity was indistinguishable during 0.5-Hz pitch oscillations and fore-aft movements. The fact that otolith-only central neurons with "high-pass" filter properties exhibit semicircular canal-like dynamics during head tilts might have important consequences for the conclusions of previous studies of sensory convergence and sensorimotor transformations in central vestibular neurons.

Vestibular Signals in Primate Thalamus: Properties and Origins

“…The departure from cosine tuning is captured by the "tuning ratio," defined in the range between 0 and 1, as the ratio of the minimum over the maximum neural response gain. Figure 3A plots the distribution of tuning ratios during translation at 0.5 Hz, which was broad, and similar to that found in VN/CN neurons (Angelaki and Dickman, 2000;Dickman and Angelaki, 2002;Shaikh et al, 2005a). Thalamic neurons with tuning ratios close to zero were mostly cosine-tuned during translation along different directions in the horizontal plane.…”

“…There was a large cell-tocell variability in thalamic cell responses to translation, similar to that found in VN and CN neurons (Angelaki and Dickman, 2000;Dickman and Angelaki, 2002;Shaikh et al, 2005a). We have used a spatiotemporal analysis to describe each cell's tuning as a set of two orthogonal response vectors (Angelaki, 1991;Angelaki and Dickman, 2000).…”

“…There was a large cell-tocell variability in thalamic cell responses to translation, similar to that found in VN and CN neurons (Angelaki and Dickman, 2000;Dickman and Angelaki, 2002;Shaikh et al, 2005a). We have used a spatiotemporal analysis to describe each cell's tuning as a set of two orthogonal response vectors (Angelaki, 1991;Angelaki and Dickman, 2000). This analysis represents a generalization of cosine tuning that allows a nonzero minimum response gain and phase that can change as a function of motion direction (Angelaki, 1991;Bush et al, 1993;Angelaki and Dickman, 2000).…”

“…We have used a spatiotemporal analysis to describe each cell's tuning as a set of two orthogonal response vectors (Angelaki, 1991;Angelaki and Dickman, 2000). This analysis represents a generalization of cosine tuning that allows a nonzero minimum response gain and phase that can change as a function of motion direction (Angelaki, 1991;Bush et al, 1993;Angelaki and Dickman, 2000). In the present study, it was used to compute a maximum response gain and phase, as well as the corresponding preferred direction for each cell and each stimulus frequency.…”

“…Also superimposed in Figure 3D is the gain and phase dependence on frequency for neurons in the cerebellar nuclei (mostly rostral fastigial) (Shaikh et al, 2005a). Data from VN neurons are not shown because VN cell dynamics were more variable, ranging from gain increases to gain decreases, and phase lags to phase leads (Angelaki and Dickman, 2000;Dickman and Angelaki, 2002).…”