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Synopsis Investigating how animals navigate space and time is key to understanding communication. Small differences in spatial positioning or timing can mean the difference between a message received and a missed connection. However, these spatio-temporal dynamics are often overlooked or are subject to simplifying assumptions in investigations of animal signaling. This special issue addresses this significant knowledge gap by integrating work from researchers with disciplinary backgrounds in neuroscience, cognitive ecology, sensory ecology, computer science, evolutionary biology, animal behavior, and philosophy. This introduction to the special issue outlines the novel questions and approaches that will advance our understanding of spatio-temporal dynamics of animal communication. We highlight papers that consider the evolution of spatio-temporal dynamics of behavior across sensory modalities and social contexts. We summarize contributions that address the neural and physiological mechanisms in senders and receivers that shape communication. We then turn to papers that introduce cutting edge technologies that will revolutionize our ability to track spatio-temporal dynamics of individuals during social encounters. The interdisciplinary collaborations that gave rise to these papers emerged in part from a novel workshop-symposium model, which we briefly summarize for those interested in fostering syntheses across disciplines.

Synopsis Internal state profoundly alters perception and behavior. For example, a starved fly may approach and consume foods that it would otherwise find undesirable. A socially engaged newt may remain engaged in the presence of a predator, whereas a solitary newt would otherwise attempt to escape. Yet, the definition of internal state is fluid and ill-defined. As an interdisciplinary group of scholars spanning five career stages (from undergraduate to full professor) and six academic institutions, we came together in an attempt to provide an operational definition of internal state that could be useful in understanding the behavior and the function of nervous systems, at timescales relevant to the individual. In this perspective, we propose to define internal state through an integrative framework centered on dynamic and interconnected communication loops within and between the body and the brain. This framework is informed by a synthesis of historical and contemporary paradigms used by neurobiologists, ethologists, physiologists, and endocrinologists. We view internal state as composed of both spatially distributed networks (body–brain communication loops), and temporally distributed mechanisms that weave together neural circuits, physiology, and behavior. Given the wide spatial and temporal scales at which internal state operates—and therefore the broad range of scales at which it could be defined—we choose to anchor our definition in the body. Here we focus on studies that highlight body-to-brain signaling; body represented in endocrine signaling, and brain represented in sensory signaling. This integrative framework of internal state potentially unites the disparate paradigms often used by scientists grappling with body–brain interactions. We invite others to join us as we examine approaches and question assumptions to study the underlying mechanisms and temporal dynamics of internal state.

As insects move through the world, they continuously engage in behavioral interactions with other species. These interactions take on a spectrum of forms, from inconsequential encounters to predation, defense, and specialized symbiotic partnerships. All such interactions rely on sensorimotor pathways that carry out efficient categorization of different organisms and enact behaviors that cross species boundaries. Despite the universality of interspecies interactions, how insect brains perceive and process salient features of other species remains unexplored. Here, we present an overview of major questions concerning the neurobiology and evolution of behavioral interactions between species, providing a framework for future research on this critical role of the insect nervous system.

Synopsis Locomotion is a hallmark of organisms which has enabled adaptive radiation to an extraordinarily diverse class of ecological niches, and allows animals to move across vast distances. Sampling from multiple sensory modalities enables animals to acquire rich information to guide locomotion. Locomotion without sensory feedback is haphazard; therefore, sensory and motor systems have evolved complex interactions to generate adaptive behavior. Notably, sensory-guided locomotion acts over broad spatial and temporal scales to permit goal-seeking behavior, whether to localize food by tracking an attractive odor plume or to search for a potential mate. How does the brain integrate multimodal stimuli over different temporal and spatial scales to effectively control behavior? In this review, we classify locomotion into three ordinally ranked hierarchical layers that act over distinct spatiotemporal scales: stabilization, motor primitives, and higher-order tasks, respectively. We discuss how these layers present unique challenges and opportunities for sensorimotor integration. We focus on recent advances in invertebrate locomotion due to their accessible neural and mechanical signals from the whole brain, limbs, and sensors. Throughout, we emphasize neural-level description of computations for multimodal integration in genetic model systems, including the fruit fly, Drosophila melanogaster, and the yellow fever mosquito, Aedes aegypti. We identify that summation (e.g., gating) and weighting—which are inherent computations of spiking neurons—underlie multimodal integration across spatial and temporal scales, therefore suggesting collective strategies to guide locomotion.

Animals can identify an odorant type across a wide range of concentrations, as well as detect changes in concentration for individual odorant type. How olfactory representations are structured to support these functions remains poorly understood. Here, we studied how a full complement of ORNs in the Drosophila larva encodes a broad input space of odorant types and concentrations. We find that dose-response relationships across odorants and ORN types follow the Hill function with shared cooperativity but different activation thresholds. These activation thresholds are drawn from a power law statistical distribution. A fixed activation function and power law distribution of activation thresholds underlie invariances in the encoding of odorant identity and intensity. Moreover, we find similar temporal response filters of ORNs across odorant types and concentrations. Such uniformity in the temporal filter may allow identity invariant coding in fluctuating or turbulent odor environments. Common patterns in ligand-receptor binding and sensory transduction across olfactory receptors may give rise to these observed invariances in the olfactory combinatorial code. Invariant patterns in the activity responses of individual ORNs and the ORN ensemble may simplify decoding by downstream circuits.

Summary Odor perception allows animals to distinguish odors, recognize the same odor across concentrations, and determine concentration changes. How the activity patterns of primary olfactory receptor neurons (ORNs), at the individual and population levels, facilitate distinguishing these functions remains poorly understood. Here, we interrogate the complete ORN population of the Drosophila larva across a broadly sampled panel of odorants at varying concentrations. We find that the activity of each ORN scales with the concentration of any odorant via a fixed dose-response function with a variable sensitivity. Sensitivities across odorants and ORNs follow a power-law distribution. Much of receptor sensitivity to odorants is accounted for by a single geometrical property of molecular structure. Similarity in the shape of temporal response filters across odorants and ORNs extend these relationships to fluctuating environments. These results uncover shared individual- and population-level patterns that together lend structure to support odor perceptions.

We have designed, built and tested a novel needle for percutaneously accessing the pericardial space. The problem with accessing pericardial space is that the pericardium is against the heart. Our novel device incorporates a single spiral tine at the distal tip of a10-gauge needle, which engages the parietal pericardium tangentially to the surface of the heart. One can then pull the pericardium away, thus minimizing the risk of ventricular perforation associated with oblique axial approaches. Using linear low-density polyethylene film as a surrogate pericardium, we have demonstrated reliable pericardial engagement with successful first-time engagement rates of up to 72% (n = 25 attempts) at approach angles ranging from 0° (normal incidence) to 30°. The associated torques were approximately 1 N mm. The performance limits of the model and the implications for clinical use of such a device are discussed.

We have characterized the mechanical compliance of an improved version of the suspension system used to position the electrode-bearing membrane of an intradural neuromodulator on the dorsal pial surface of the spinal cord. Over the compression span of 5 mm, it exhibited a restoring force of 2.4 μN μm−1 and a mean pressure of 0.5 mm Hg (=66 Pa) on the surface below it, well within the range of normal intrathecal pressures. We have implanted prototype devices employing this suspension and a novel device fixation technique in a chronic ovine model of spinal cord stimulation and found that it maintains stable contact at the electrode-pia interface without lead fracture, as determined by measurement of the inter-contact impedances.

We have developed a spinal cord surrogate for use in testing a pial-surface spinal cord stimulator. Our surrogate is of a commercially available silicone mix, has an oval cross-sectional area that matches that of actual human spinal cord at the lower thoracic level, and has measured values of durometer A = (10.96 ± 1.68), durometer O = (14.76 ± 1.48), and durometer OO = (50.24 ± 2.65). These correspond to model-inferred elastic moduli of 0.41 to 0.44 MPa, which match well with the existing low-strain rate measurements of ex vivo human spinal cord. Upcoming applications for this surrogate in developmental studies of the new stimulator system are discussed.