Choice-related activity and correlated noise in subcortical vestibular neurons

Abstract

Functional links between neuronal activity and perception are studied by examining trial-by-trial correlations (choice probabilities) between neural responses and perceptual decisions. We addressed fundamental issues regarding the nature and origin of choice probabilities by recording from subcortical (brainstem and cerebellar) neurons in rhesus monkeys during a vestibular heading discrimination task. Subcortical neurons showed robust choice probabilities that exceeded those seen in cortex (area MSTd) under identical conditions. The greater choice probabilities of subcortical neurons could be predicted by a stronger dependence of correlated noise on tuning similarity, as revealed by population decoding. Significant choice probabilities were observed almost exclusively for neurons that responded selectively to translation, whereas neurons that represent net gravito-inertial acceleration did not show choice probabilities. These findings suggest that the emergence of choice probabilities in the vestibular system depends on a critical signal transformation that occurs in subcortical pathways to distinguish translation from orientation relative to gravity.

Neuronal thresholds and choice-related activity of otolith afferent fibers during heading perception

“…We have found that peripheral sensory fibers innervating the otolith organs have heading discrimination thresholds that are of similar magnitude to thresholds in the VN and CN (13), as well as to thresholds of cortical neurons (1-3). Despite having similar sensitivities, responses of otolith afferents do not correlate with perceptual decisions, whereas activity of central vestibular and cortical neurons does.…”

“…Thresholds of VN/CN neurons have previously been shown to depend strongly on tuning curve slope (type II regression: r = −0.81, P = 3.4 × 10 −24 ) and weakly on median response variance (type II regression: r = 0.19, P = 0.07; Fig. 4 A and B, black symbols) (13). Similar relationships between neuronal threshold, tuning curve slope, and median response variance were found for our sample of otolith afferents (type II regression: r = −0.94, P = 2.7 × 10 −29 for tuning slope; r = −0.33, P = 0.01 for median response variance; Fig.…”

“…In fact, psychophysical thresholds vary greatly across subjects within both species (e.g., figure S2C of ref. 13), thus making it difficult to compare neuronal and perceptual performance that is not measured simultaneously in the same subjects. In addition, vibrations inherent to the various motion platforms used within and across laboratories may affect thresholds, thus further complicating comparisons.…”

“…the neural population (38)(39)(40)(41)(42)(43)(44). When correlated noise is present, as is the case in the VN/CN (13,35), population thresholds may not decrease with the square root of the number of neurons and predictions based on the square root law could be dramatically inaccurate. Moreover, for a fixed neural pool size, population thresholds can also depend substantially on whether the decoder has full knowledge of the structure of noise correlations or not (42,45,46).…”

“…In this regard, the vestibular system may provide an alternative model to probe the origin of CPs because similar basic forms of spatiotemporal directional selectivity are seen at many levels of processing, from afferents to cortex (12). Recently, we provided the first demonstration (13), to our knowledge, that subcortical neurons in the vestibular nuclei (VN) and cerebellar nuclei (CN) could exhibit robust CPs, and these effects were even larger than those effects measured in some cortical areas under identical stimulus conditions (e.g., ref. 1).…”