Sensory computations in the cuneate nucleus of macaques

Tactile nerve fibers fall into a few classes that can be readily distinguished based on their spatiotemporal response properties. Because nerve fibers reflect local skin deformations, they individually carry ambiguous signals about object features. In contrast, cortical neurons exhibit heterogeneous response properties that reflect computations applied to convergent input from multiple classes of afferents, which confer to them a selectivity for behaviorally relevant features of objects. The conventional view is that these complex response properties arise within the cortex itself, implying that sensory signals are not processed to any significant extent in the two intervening structures—the cuneate nucleus (CN) and the thalamus. To test this hypothesis, we recorded the responses evoked in the CN to a battery of stimuli that have been extensively used to characterize tactile coding in both the periphery and cortex, including skin indentations, vibrations, random dot patterns, and scanned edges. We found that CN responses are more similar to their cortical counterparts than they are to their inputs: CN neurons receive input from multiple classes of nerve fibers, they have spatially complex receptive fields, and they exhibit selectivity for object features. Contrary to consensus, then, the CN plays a key role in processing tactile information.

Response Properties of Optic Flow Neurons in the Accessory Optic System of Hummingbirds vs. Zebra Finches and Pigeons

Optokinetic responses function to maintain retinal image stabilization by minimizing optic flow that occurs during self-motion. The hovering ability of hummingbirds is an extreme example of this behaviour. Optokinetic responses are mediated by direction-selective neurons with large receptive fields in the accessory optic system (AOS) and pretectum. Recent studies in hummingbirds showed that, compared to other bird species, (i) the pretectal nucleus lentiformis mesencephali (LM) is hypertrophied, (ii) LM has a unique distribution of direction preferences, and (iii) LM neurons are more tightly tuned to stimulus velocity. In this study, we sought to determine if there are concomitant changes in the nucleus of the basal optic root (nBOR) of the AOS. We recorded the visual response properties of nBOR neurons to largefield drifting random dot patterns and sine wave gratings in Anna's hummingbirds and zebra finches and compared these with archival data from pigeons. We found no differences with respect to the distribution of direction preferences: Neurons responsive to upwards, downwards and nasal-to-temporal motion were equally represented in all three species, and neurons responsive to temporal-to-nasal motion were rare or absent (<5%). Compared to zebra finches and pigeons, however, hummingbird nBOR neurons were more tightly tuned to stimulus velocity of random dot stimuli. Moreover, in response to drifting gratings, hummingbird nBOR neurons are more tightly tuned in the spatio-temporal domain. These results, in combination with specialization in LM, supports a hypothesis that hummingbirds have evolved to be "optic flow specialist" to cope with the optomotor demands of sustained hovering flight.

The impulse response of optic flow-sensitive descending neurons to roll m-sequences

ABSTRACT When animals move through the world, their own movements generate widefield optic flow across their eyes. In insects, such widefield motion is encoded by optic lobe neurons. These lobula plate tangential cells (LPTCs) synapse with optic flow-sensitive descending neurons, which in turn project to areas that control neck, wing and leg movements. As the descending neurons play a role in sensorimotor transformation, it is important to understand their spatio-temporal response properties. Recent work shows that a relatively fast and efficient way to quantify such response properties is to use m-sequences or other white noise techniques. Therefore, here we used m-sequences to quantify the impulse responses of optic flow-sensitive descending neurons in male Eristalis tenax hoverflies. We focused on roll impulse responses as hoverflies perform exquisite head roll stabilizing reflexes, and the descending neurons respond particularly well to roll. We found that the roll impulse responses were fast, peaking after 16.5–18.0 ms. This is similar to the impulse response time to peak (18.3 ms) to widefield horizontal motion recorded in hoverfly LPTCs. We found that the roll impulse response amplitude scaled with the size of the stimulus impulse, and that its shape could be affected by the addition of constant velocity roll or lift. For example, the roll impulse response became faster and stronger with the addition of excitatory stimuli, and vice versa. We also found that the roll impulse response had a long return to baseline, which was significantly and substantially reduced by the addition of either roll or lift.

Sleep promoting neurons remodel their response properties to calibrate sleep drive with environmental demands.

Falling asleep at the wrong time can place an individual at risk of immediate physical harm. However, not sleeping degrades cognition and adaptive behavior. To understand how animals match sleep need with environmental demands, we used live-brain imaging to examine the physiological response properties of the Drosophila sleep homeostat (dFB) following interventions that modify sleep (sleep deprivation, starvation, time-restricted feeding, memory consolidation). We report that dFB neurons can distinguish between different types of waking and can change their physiological response-properties accordingly. That is, dFB neurons are not simply passive components of a hard-wired circuit. Rather, the dFB neurons themselves can determine their response to the activity from upstream circuits. Finally, we show that the dFB appears to contain a memory trace of prior exposure to metabolic challenges induced by starvation or time-restricted feeding. Together these data highlight that the sleep homeostat is plastic and suggests an underlying mechanism.

Nonlinear visuoauditory integration in the mouse superior colliculus

Sensory information from different modalities is processed in parallel, and then integrated in associative brain areas to improve object identification and the interpretation of sensory experiences. The Superior Colliculus (SC) is a midbrain structure that plays a critical role in integrating visual, auditory, and somatosensory input to assess saliency and promote action. Although the response properties of the individual SC neurons to visuoauditory stimuli have been characterized, little is known about the spatial and temporal dynamics of the integration at the population level. Here we recorded the response properties of SC neurons to spatially restricted visual and auditory stimuli using large-scale electrophysiology. We then created a general, population-level model that explains the spatial, temporal, and intensity requirements of stimuli needed for sensory integration. We found that the mouse SC contains topographically organized visual and auditory neurons that exhibit nonlinear multisensory integration. We show that nonlinear integration depends on properties of auditory but not visual stimuli. We also find that a heuristically derived nonlinear modulation function reveals conditions required for sensory integration that are consistent with previously proposed models of sensory integration such as spatial matching and the principle of inverse effectiveness.