Neuronal variability and tuning are balanced to optimize naturalistic self-motion coding in primate vestibular pathways

Abstract

It is commonly assumed that the brain’s neural coding strategies are adapted to the statistics of natural stimuli. Specifically, to maximize information transmission, a sensory neuron’s tuning function should effectively oppose the decaying stimulus spectral power, such that the neural response is temporally decorrelated (i.e. ‘whitened’). However, theory predicts that the structure of neuronal variability also plays an essential role in determining how coding is optimized. Here, we provide experimental evidence supporting this view by recording from neurons in early vestibular pathways during naturalistic self-motion. We found that central vestibular neurons displayed temporally whitened responses that could not be explained by their tuning alone. Rather, computational modeling and analysis revealed that neuronal variability and tuning were matched to effectively complement natural stimulus statistics, thereby achieving temporal decorrelation and optimizing information transmission. Taken together, our findings reveal a novel strategy by which neural variability contributes to optimized processing of naturalistic stimuli.

Neural variability determines coding strategies for natural self-motion in macaque monkeys

“…Neuronal sensitivity to eye movements was assessed during steady fixation, saccades, and smooth pursuit (see Materials and methods). The vestibular and eye movement sensitivities of PVP, EH, and VO neurons in our dataset are shown in Figure 1—figure supplement 2 and agreed with previously published values ( Roy and Cullen, 2002 ; Roy and Cullen, 2003 ; Massot et al, 2011 ; Mitchell et al, 2018 ). In particular, we note that PVP and EH neurons can be distinguished based on their differential sensitivities to eye and head movements during smooth pursuit and VOR cancellation, respectively ( Figure 1—figure supplement 1 ).…”

“…The latter component contributes to what is known as trial-to-trial variability in the neural response to repeated presentations of a given stimulus. Such trial-to-trial variability is largely determined by the variability of the resting discharge for vestibular neurons ( Sadeghi et al, 2007 ; Massot et al, 2011 ; Jamali et al, 2013 ; Mitchell et al, 2018 ). This is because, in order to be detected, head movements must sufficiently perturb the resting discharge.…”

“…Specifically, we focused on a class of neurons within the vestibular nuclei, vestibular-only (VO) neurons, that mediate vestibulo-spinal reflexes as well as self-motion perception ( Abzug et al, 1974 ; Shinoda et al, 1988 ; Gdowski and McCrea, 1999 ; Meng et al, 2007 ; Marlinski and McCrea, 2009 ). Our results revealed that VO neurons optimally encoded naturalistic self-motion stimuli through temporal whitening (i.e., the spike train power spectrum is independent of temporal frequency and thus "white") because both neuronal variability and tuning were matched to effectively complement natural stimulus statistics ( Carriot et al, 2014 ; Carriot et al, 2017 ; Mitchell et al, 2018 ). Our previous study was however limited since we only considered a single class of neurons within the vestibular nuclei and further did not take into account the effects of neural heterogeneities.…”

“…Our previous study was the first to investigate how neurons within the first central stage of vestibular processing in macaque monkeys respond to natural self-motion ( Mitchell et al, 2018 ). Specifically, we focused on a class of neurons within the vestibular nuclei, vestibular-only (VO) neurons, that mediate vestibulo-spinal reflexes as well as self-motion perception ( Abzug et al, 1974 ; Shinoda et al, 1988 ; Gdowski and McCrea, 1999 ; Meng et al, 2007 ; Marlinski and McCrea, 2009 ).…”

Neural Mechanisms Underlying High-Frequency Vestibulocollic Reflexes In Humans And Monkeys

“…Massot et al (2011) postulated that the increasing sensitivity of vestibular primary afferents with frequency, as also seen here up to their resting firing rate (ϳ100 -150 Hz), compensates for the decreasing spectral power of vestibular input, thus broadening the capacity for vestibular afferents to encode highfrequency head movements. Indeed, both vestibular afferent and nuclei neurons encode natural self-motion through whitening over a 0 to 20 Hz bandwidth (i.e., maintaining constant spectral power across frequencies), a mechanism dependent on the increasing neural sensitivity and variability with frequency (Mitchell et al, 2018). The increased afferent and neck muscle sensitivity to the input stimulus from 0 to 100 Hz suggests that the mechanism underlying whitening in vestibular pathways could extend beyond the physiological range of head movement (0 -30 Hz).…”