Binocular Neuronal Processing of Object Motion in an Arthropod

Abstract

Animals use binocular information to guide many behaviors. In highly visual arthropods, complex binocular computations involved in processing panoramic optic flow generated during self-motion occur in the optic neuropils. However, the extent to which binocular processing of object motion occurs in these neuropils remains unknown. We investigated this in a crab, where the distance between the eyes and the extensive overlapping of their visual fields advocate for the use of binocular processing. By performing intracellular recordings from the lobula (third optic neuropil) of male crabs, we assessed responses of object-motion sensitive neurons to ipsilateral or contralateral moving objects under binocular and monocular conditions. Most recorded neurons responded to stimuli seen independently with either eye, proving that each lobula receives profuse visual information from both eyes. The contribution of each eye to the binocular response varies among neurons, from those receiving comparable inputs from both eyes to those with mainly ipsilateral or contralateral components, some including contralateral inhibition. Electrophysiological profiles indicated that a similar number of neurons were recorded from their input or their output side. In monocular conditions, the first group showed shorter response delays to ipsilateral than to contralateral stimulation, while the second group showed the opposite. These results fit well with neurons conveying centripetal and centrifugal information from and toward the lobula respectively. Intracellular and massive stainings provided anatomical support for this and for direct connections between the two lobulae, but simultaneous recordings failed to reveal such connections. Simplified model circuits of interocular connections are discussed.Most active animals became equipped with two eyes, which contributes to functions like depth perception, objects spatial location and motion processing, all used for guiding behaviors. In visually active arthropods, binocular neural processing of the panoramic optic flow generated during self-motion happens already in the optic neuropils. However, whether binocular processing of single object motion occurs in these neuropils remained unknown. We investigated this in a crab, where motion-sensitive neurons from the lobula can be recorded in the intact animal. Here we demonstrate that different classes of neurons from the lobula compute binocular information. Our results provide new insight into where and how the visual information acquired by the two eyes is first combined in the brain of an arthropod.

Binocular responsiveness of projection neurons of the praying mantis optic lobe in the frontal visual field

“…Neurons that might compute depth have been found in a crab (Scarano et al 2018). The situation in this animal is more complicated than in most insects because the eyes in this invertebrate are not fixed but can move.…”

Multielectrode Recordings From Identified Neurons Involved in Visually Elicited Escape Behavior

“…An important step in the establishment of the crab as an invertebrate model for studying the neural control of behavior has been the identification and characterization of a group of giant neurons from the lobula (3rd optic neuropil of arthropods), which were shown to be key elements for visually-elicited avoidance behaviors. The achievements had been possible due to the unique experimental advantages offered by this crab to perform stable intracellular recordings from brain neurons in the practically intact and awake animal (e.g., Berón de Astrada and Tomsic, 2002 ; Scarano et al, 2018 ). Four different classes of lobula giant (LG) neurons had been studied.…”

“…Such plasticity has been shown to underlie part of the short- and long-term memory traces induced by visual training (Tomsic et al, 2003 ; Sztarker and Tomsic, 2011 ). LG neurons also share the ability to integrate binocular information (Sztarker and Tomsic, 2004 ; Scarano et al, 2018 ) and three classes integrate visual with mechanosensory information from the animal’s legs (Berón de Astrada and Tomsic, 2002 ; Medan et al, 2007 ). Beyond these commonalities, the four LG classes show substantial differences.…”

“…This neuron has been shown to play a central role in regulating the animal’s speed of run according to the visual dynamic of approaching stimuli (Oliva and Tomsic, 2016 ). The BLG1 class is composed of a discrete number of elements (Medan et al, 2007 ; Scarano et al, 2018 ), which might participate in encoding information regarding stimulus elevation (Tomsic, 2016 ). The BLG2 is a very large neuron, likely a single element, with an extensive receptive visual field (Medan et al, 2007 ).…”

Three-dimensional shape and velocity changes affect responses of a locust visual interneuron to approaching objects

“…Animals living in complex, spatiotemporally dynamic visual environments require robust collision-detection systems to successfully orient amongst stationary objects and conspecifics as well as to avoid threats, such as an approaching predator. Behavioural and neural mechanisms underlying collision detection and avoidance have been well studied in taxonomically diverse animals, including humans (Gray and Regan, 1998;Poljac et al, 2006;Vallis and McFadyen, 2005) and other primates (Cléry et al, 2017), cats (Liu et al, 2011b), mice (De Franceschi et al, 2016;Shang et al, 2015;Zhao et al, 2014), birds (Cao et al, 2004;Sun and Frost, 1998), frogs (Yamamoto et al, 2003), fish (Dunn et al, 2016;Preuss et al, 2006;Temizer et al, 2015), crustaceans (Carbone et al, 2018;Oliva et al, 2007;Scarano et al, 2018), insects (Gabbiani et al, 1999;von Reyn et al, 2017;Robertson and Johnson, 1993;Santer et al, 2012;Sato and Yamawaki, 2014;Thyselius et al, 2018;Wang et al, 2018) and sea urchins (Kirwan et al, 2018). Findings suggest that common neural coding strategies exist across these groups and demonstrate the utility of a tractable system to address questions of how complex visual stimuli are detected and how the information is used to drive downstream motor elements to produce adaptive behavioural responses.…”