Facilitation of neural responses to targets moving against optic flow

For the human observer, it can be difficult to follow the motion of small objects, especially when they move against background clutter. In contrast, insects efficiently do this, as evidenced by their ability to capture prey, pursue conspecifics, or defend territories, even in highly textured surrounds. We here recorded from target selective descending neurons (TSDNs), which likely subserve these impressive behaviors. To simulate the type of optic flow that would be generated by the pursuer’s own movements through the world, we used the motion of a perspective corrected sparse dot field. We show that hoverfly TSDN responses to target motion are suppressed when such optic flow moves syn-directional to the target. Indeed, neural responses are strongly suppressed when targets move over either translational sideslip or rotational yaw. More strikingly, we show that TSDNs are facilitated by optic flow moving counterdirectional to the target, if the target moves horizontally. Furthermore, we show that a small, frontal spatial window of optic flow is enough to fully facilitate or suppress TSDN responses to target motion. We argue that such TSDN response facilitation could be beneficial in modulating corrective turns during target pursuit.

Adaptive integration of self-motion and goals in posterior parietal cortex

Animals engage in a variety of navigational behaviors that require different regimes of behavioral control. In the wild, rats readily switch between foraging and more complex behaviors such as chase, wherein they pursue other rats or small prey. These tasks require vastly different tracking of multiple behaviorally-significant variables including self-motion state. It is unknown whether changes in navigational context flexibly modulate the encoding of these variables. To explore this possibility, we compared self-motion processing in the multisensory posterior parietal cortex while rats performed alternating blocks of free foraging and visual target pursuit. Animals performed the pursuit task and demonstrated predictive processing by anticipating target trajectories and intercepting them. Relative to free exploration, pursuit sessions yielded greater proportions of parietal cortex neurons with reliable sensitivity to self-motion. Multiplicative gain modulation was observed during pursuit which increased the dynamic range of tuning and led to enhanced decoding accuracy of self-motion state. We found that self-motion sensitivity in parietal cortex was history-dependent regardless of behavioral context but that the temporal window of self-motion tracking was extended during target pursuit. Finally, many self-motion sensitive neurons conjunctively tracked the position of the visual target relative to the animal in egocentric coordinates, thus providing a potential coding mechanism for the observed gain changes to self-motion signals. We conclude that posterior parietal cortex dynamically integrates behaviorally-relevant information in response to ongoing task demands.

Facilitation of neural responses to targets moving in three-dimensional optic flow

For the human observer, it can be difficult to follow the motion of small objects, especially when they move against background clutter. However, insects efficiently do this, as evidenced by their ability to capture prey, pursue conspecifics, or defend territories, even in highly textured surrounds. This behavior has been attributed to optic lobe neurons that are sharply tuned to the motion of small targets, as these neurons respond robustly even to a target moving against background motion. However, the target selective descending neurons (TSDNs), that more directly control behavioral output, do not. Importantly, though, the backgrounds used previously not only lacked 3D motion cues, but also high-contrast features, both of which would be encountered during natural behaviors. To redress this deficiency, we here use backgrounds consisting of many targets moving coherently to simulate the type of 3D optic flow that would be generated by an insect’s own motion through the world. We show that hoverfly TSDNs do not respond to this type of optic flow, even though it contains features with spatio-temporal profiles similar to optimal targets. However, TSDN responses are inhibited when this optic flow is shown together with a target. More surprisingly, TSDNs are facilitated by horizontal, frontal optic flow in the opposite direction to target motion. We show that these interactions are likely inherited from the pre-synaptic neurons, and argue that the facilitation could benefit the initiation of target pursuit.Significance statementTarget detection in visual clutter is a difficult computational task that insects, with their poor resolution compound eyes and small brains, do successfully and with extremely short behavioral delays. We here show that target neurons do not respond to widefield motion consisting of a multitude of “targets”, suggesting that the hoverfly visual system interprets coherent widefield motion differently from the motion of individual targets. In addition, we show that widefield motion in the opposite direction to target motion increases the neural response. This is an incredibly non-intuitive finding, and difficult to reconcile with current models for target selectivity, but has behavioral relevance.ClassificationBiological sciences: Neuroscience

A striatal interneuron circuit for continuous target pursuit

Most adaptive behaviors require precise tracking of targets in space. In pursuit behavior with a moving target, mice use distance to target to guide their own movement continuously. Here we show that in the sensorimotor striatum, parvalbumin-positive fast-spiking interneurons (FSIs) can represent the distance between self and target during pursuit behavior, while striatal projection neurons (SPNs), which receive FSI projections, can represent self-velocity. FSIs are shown to regulate velocity-related SPN activity during pursuit, so that movement velocity is continuously modulated by distance to target. Moreover, bidirectional manipulation of FSI activity can selectively disrupt performance by increasing or decreasing the self-target distance. Our results reveal a key role of the FSI-SPN interneuron circuit in pursuit behavior, and elucidate how this circuit implements distance to velocity transformation required for the critical underlying computation.