Sensory adaptation mediates efficient and unambiguous encoding of natural stimuli by vestibular thalamocortical pathways

Abstract

Sensory systems must continuously adapt to optimally encode stimuli encountered within the natural environment. The prevailing view is that such optimal coding comes at the cost of increased ambiguity, yet to date, prior studies have focused on artificial stimuli. Accordingly, here we investigated whether such a trade-off between optimality and ambiguity exists in the encoding of natural stimuli in the vestibular system. We recorded vestibular nuclei and their target vestibular thalamocortical neurons during naturalistic and artificial self-motion stimulation. Surprisingly, we found no trade-off between optimality and ambiguity. Using computational methods, we demonstrate that thalamocortical neural adaptation in the form of contrast gain control actually reduces coding ambiguity without compromising the optimality of coding under naturalistic but not artificial stimulation. Thus, taken together, our results challenge the common wisdom that adaptation leads to ambiguity and instead suggest an essential role in underlying unambiguous optimized encoding of natural stimuli.

Decoding the relative contributions of extrinsic and intrinsic mechanisms in mediating heterogeneous spiking activities of sensory neurons in vivo using computational modeling

“…Specifically, ELL pyramidal cell receptive field structures and response properties are similar to those of neurons within the mammalian visual system (see (76) for review). There are also important similarities between the electrosensory and mammalian vestibular systems in terms of optimized coding of natural stimuli (77–81). This is expected given that both the electrosensory and vestibular systems have evolved from the lateral line (82).…”

Noise and vestibular perception of passive self-motion

“…VPL neurons projecting to cortex also demonstrate optimal encoding of naturalistic head motion stimuli ( 38 ). While these neurons ambiguously encode head velocity during artificial sinusoidal rotations, they faithfully encode head velocity during naturalistic noisy head rotations, with no significant phase lead across frequencies ( Figure 4 ).…”

“…(G) Population-averaged phase as a function of frequency for artificial (dashed) and naturalistic (solid) self-motion. Reproduced with permission from Carriot et al ( 38 ).…”

“…On the other hand, VO neurons of vestibular nuclei projecting to VPL still exhibit significant phase leads relative to head velocity during both artificial and naturalistic head rotations ( 38 ). In the context of a different sensory system (the cortical visual system of ferrets), tuning of neural activity patterns to the statistics of the natural environment has been shown to be a product of brain development ( 39 ).…”

“…Thus, under natural conditions, the vestibular system uses increased variability to promote fidelity of encoding by single neurons ( 37 ). Third, tuning properties of some vestibular neurons is optimally matched to the statistics of naturalistic noisy inputs from the environment ( 38 ). During brain development, internal models of physics encoded in spontaneous neural activity become gradually adapted to the statistical structure of the natural sensory environment ( 39 ).…”