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C HAPTER II: H EAD - DIRECTION CELLS IN THE BRAIN OF AN INSECT ARE SENSITIVE TO
51 encountered in these experiments, except for a single cell that was polarization-sensitive but did not respond to those visual objects that drove the other types of neuron.
Neither selectivity for object position nor narrow tuning to object features were observed, apart from a preference of distinct objects over visual flow. In fact, none of the neurons encountered responded to wide-field motion. Across cell-types, neurons responded to the translatory motion (70°/s) of a black filled square (hereafter:
patch) of about 2° x 1.5° size in visual angle, presented against the grey background. To investigate response behavior, horizontal (forward and backward) and vertical (upward and downward) motion in different regions of the mapping field were presented in different sequences, with several repetitions of the same combination as well as sudden changes in the direction of motion and / or region.
Responses were inhibitory in CL-and CPU-neurons but excitatory in TB-cells. Initial responses were independent of direction of motion but showed strong adaptation to the trajectory, i.e. the region of the visual field occupied by the course of the moving object.
This region-specific adaptation could be broken by changing the elevation of horizontal trajectories and the azimuth of vertical ones, but it was unaffected by changing the direction of motion along an unchanged trajectory.
Yet, neurons were not generally blind to the direction of motion, but responded in a highly context-dependent manner: in additional tests performed in the same cells, changing the direction of motion did trigger responses if it made a single patch pop-out against a flow field of coherently moving others. Importantly, patches that constituted the background flow in these experiments had the same size and contrast as the individual patch that triggered a response by changing its direction of motion relative to the background patches. Hence, the observed response behavior is not explainable in terms of mere tuning to high-contrast small-field motion against a low-contrast background
clutter of wide-field elements. This is a striking difference to the size- and contrast- dependent responses of peripheral small-target movement detectors described in the dragonfly (O’Carroll 1993). It is suggestive of object discrimination in terms of Gestalt principles (see Goldstein 2007).
These principles describe the ‘laws’ of how physical objects and events in the outside world are grouped into perceptual objects, and in the present case, the principle of common fate predicts that objects moving in the same direction will be grouped together, thus distinguishing background flow from distinct
‘target’ objects. Note that thus the very same event, a change in the direction of motion, might signal a mere change in the behavior of the same object (in the ‘blank grey background’ regime) or the sudden emergence of a novel object (in the
´complex object-background´ regime).
Together with the region-specific adaptation to the motion of a single patch, the “Gestalt-based”
responses strongly suggest that compass neurons in the locust central complex are capable of novelty detection in the visual object-background scenery. They signal salient events of object motion that are ‘unpredictable’ from the recent stimulus history, but responses do not precisely represent the features of the objects involved. This visual bimodality of locust central-complex neurons might serve to integrate novelty-event information in the control of compass-guided locomotion. This in turn might attune compass-aided locomotor control to unexpected events in the environment, such as the approach of a predator or impeding collision with a conspecific in a dense swarm.
The novelty-dependent responses to small field motion are in line with previous reports on responses to looming objects (Rosner and Homberg 2013), but strikingly different from data obtained in Drosophila. This difference in tuning properties of central-complex neurons might relate to lifestyle differences between the two species. Although Drosophila can orient
52 using the sky polarization pattern (Weir and Dickinson 2012), it largely lives in local, visually rich environments suited for landmark learning.
In contrast, the desert locust is a long-range migrating species that might preferentially rely on compass navigation. It should finally be noted, that Seelig and Jayaraman (2013) studied ring neurons of the central body of Drosophila;
these correspond to TL-neurons in the locust (Müller et al. 1997) which were not included in the present study. Hence, results do not rule out the existence of parallel neuronal networks for the two orientation strategies.
In addition to the context-dependency described above, the responses of locust central-complex neurons to small-field motion co-varied with the level of preceding background activity.
High-level background activity can mask inhibitory responses (CL1, CPU) by superimposition and reduce the relative strength of excitatory responses (TB1) via framing of responses by response-like spiking. To characterize the effect quantitatively, I tested whether spike counts during stimulus
presentation correlated with spike counts during the directly preceding stimulus-free period. The analysis revealed a highly significant and strong correlation that explains about 70% of the observed overall variability in spike count. For statistical reasons, this analysis was confined to CPU-neurons. Yet, across types, the cell-specific ranges of background activity (i.e.
variability over time) include levels suited to
´mask´ even the most pronounced responses observed here. This might serve to exclude any currently irrelevant novelty-event information from the higher locomotor control that is most likely promoted by the output of the central-complex.
The masking of object responses by background activity as well as their region-specific adaptation resembles the masking and E-vector specific adaptation of compass- responses in the same cells (Chapter I). This further widens the parallel to novelty- and attention-dependent processing of sensory input in the vertebrate cortex outlined in the previous chapter.
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