An Anatomically Constrained Model for Path Integration in the Bee Brain

Abstract

Path integration is a widespread navigational strategy in which directional changes and distance covered are continuously integrated on an outward journey, enabling a straight-line return to home. Bees use vision for this task-a celestial-cue-based visual compass and an optic-flow-based visual odometer-but the underlying neural integration mechanisms are unknown. Using intracellular electrophysiology, we show that polarized-light-based compass neurons and optic-flow-based speed-encoding neurons converge in the central complex of the bee brain, and through block-face electron microscopy, we identify potential integrator cells. Based on plausible output targets for these cells, we propose a complete circuit for path integration and steering in the central complex, with anatomically identified neurons suggested for each processing step. The resulting model circuit is thus fully constrained biologically and provides a functional interpretation for many previously unexplained architectural features of the central complex. Moreover, we show that the receptive fields of the newly discovered speed neurons can support path integration for the holonomic motion (i.e., a ground velocity that is not precisely aligned with body orientation) typical of bee flight, a feature not captured in any previously proposed model of path integration. In a broader context, the model circuit presented provides a general mechanism for producing steering signals by comparing current and desired headings-suggesting a more basic function for central complex connectivity, from which path integration may have evolved.

Multisensory Control of Orientation in Tethered Flying Drosophila

“…In our initial experiments, the strength of vision- and wind-evoked turns were functions of flies’ starting orientations, with the strongest turns for each modality falling at distinct orientations. Similarly, turns that followed wind onsets and offsets in the pulse experiment were nonlinear functions of stimulus orientation — consi stent with a model based on spatial filtering, but not with a model based on orientation error [15,27,28]. Several observations also support differential temporal filtering of wind and visual cues.…”

Principles of Insect Path Integration

“…The presence of anatomical substrates for a ring-like path integration system in the insect central complex (see below), the absence of definitive ‘place cell’ evidence, and the apparent match between theoretical and behavioral data suggests that insect path integration is best described by a ring-like ‘allocentric static vectorial representation’ model [59,63,64]. …”

Building a functional connectome of the Drosophila central complex

“…While it is possible that our selection of Gal4 lines was unintentionally biased against output neurons, or that our technique otherwise missed a number of output pathways, the picture of the central complex that emerges is of a densely recurrent sensorimotor hub with relatively low dimensional output (much as proposed by some models e.g. Stone et al 2017;Fiore et al 2015;Strauss and Berg 2010). The implications of this bottleneck for motor control remains a challenge for future studies to resolve.…”

“…Detailed light level anatomy (Hanesch et al, 1989;Wolff et al, 2015;Lin et al, 2013) of a significant fraction of the cell types, along with the availability of tools to genetically target these neurons by type (Wolff et al, 2015), have given rise to the first mechanistic investigations of how the circuit constructs a stable heading representation , and how this representation updates as the animal turns in darkness (Turner-Evans et al, 2017;Green et al, 2017). Such results and related findings from other insects have also inspired a number of modeling studies aimed at predicting or reproducing physiologically and behaviorally relevant response patterns (Kakaria et al, 2017b;Givon et al, 2017;Chang et al, 2017;Cope et al, 2017;Fiore et al, 2017;Stone et al, 2017;Turner-Evans et al, 2017). Many of these models make assumptions about connectivity within the central complex based on the degree of overlap at the light microscopy level between processes that look bouton-like and those that seem spiny, which are suggestive of pre-and post-synaptic specializations respectively.…”

“…Whereas some ring neuron subtypes have received considerable attention (Sun et al, 2017;Shiozaki and Kazama, 2017;Seelig and Jayaraman, 2013), most PB inputs and LAL-noduli interneurons have not yet been characterized. A recent study in the sweat bee (Stone et al, 2017), for example, reported that one of the LAL-noduli interneurons -a likely input to the FB system -carries regressive optic flow signals.…”