There are ever more compelling tools available for neuroscience research, ranging from selective genetic targeting to optogenetic circuit control to mapping whole connectomes. These approaches are coupled with a deep-seated, often tacit, belief in the reductionist program for understanding the link between the brain and behavior. The aim of this program is causal explanation through neural manipulations that allow testing of necessity and sufficiency claims. We argue, however, that another equally important approach seeks an alternative form of understanding through careful theoretical and experimental decomposition of behavior. Specifically, the detailed analysis of tasks and of the behavior they elicit is best suited for discovering component processes and their underlying algorithms. In most cases, we argue that study of the neural implementation of behavior is best investigated after such behavioral work. Thus, we advocate a more pluralistic notion of neuroscience when it comes to the brain-behavior relationship: behavioral work provides understanding, whereas neural interventions test causality.

A defining feature of active sensing is the use of self-generated energy to probe the environment. Familiar biological examples include echolocation in bats and dolphins and active electrolocation in weakly electric fish. Organisms that utilize active sensing systems can potentially exert control over the characteristics of the probe energy, such as its intensity, direction, timing, and spectral characteristics. This is in contrast to passive sensing systems, which rely on extrinsic energy sources that are not directly controllable by the organism. The ability to control the probe energy adds a new dimension to the task of acquiring relevant information about the environment. Physical and ecological constraints confronted by active sensing systems include issues of signal propagation, attenuation, speed, energetics, and conspicuousness. These constraints influence the type of energy that organisms use to probe the environment, the amount of energy devoted to the process, and the way in which the nervous system integrates sensory and motor functions for optimizing sensory acquisition performance.

SUMMARYA mechanistic understanding of goal-directed behavior in vertebrates is hindered by the relative inaccessibility and size of their nervous systems. Here, we have studied the kinematics of prey capture behavior in a highly accessible vertebrate model organism, the transparent larval zebrafish (Danio rerio), to assess whether they use visual cues to systematically adjust their movements. We found that zebrafish larvae scale the speed and magnitude of turning movements according to the azimuth of one of their standard prey, paramecia. They also bias the direction of subsequent swimming movements based on prey azimuth and select forward or backward movements based on the prey's direction of travel. Once within striking distance, larvae generate either ram or suction capture behaviors depending on their distance from the prey. From our experimental estimations of ocular receptive fields, we ascertained that the ultimate decision to consume prey is likely a function of the progressive vergence of the eyes that places the target in a proximal binocular 'capture zone'. By repeating these experiments in the dark, we demonstrate that paramecia are only consumed if they contact the anterior extremities of larvae, which triggers ocular vergence and tail movements similar to close proximity captures in lit conditions. These observations confirm the importance of vision in the graded movements we observe leading up to capture of more distant prey in the light, and implicate somatosensation in captures in the absence of light. We discuss the implications of these findings for future work on the neural control of visually guided behavior in zebrafish. Supplementary material available online at

Summary All visual animals must decide whether approaching objects are a threat. Our current understanding of this process has identified a proximity-based mechanism where an evasive maneuver is triggered when a looming stimulus passes a subtended visual angle threshold. However, some escape strategies are more costly than others and so it would be beneficial to additionally encode the level of threat conveyed by the predator's approach rate to select the most appropriate response. Here, using naturalistic rates of looming visual stimuli while simultaneously monitoring escape behavior and the recruitment of multiple reticulospinal neurons, we find that larval zebrafish do indeed perform a calibrated assessment of threat. While all fish generate evasive maneuvers at the same subtended visual angle, lower approach rates evoke slower, more kinematically variable escape responses with relatively long latencies as well as the unilateral recruitment of ventral spinal projecting nuclei (vSPNs) implicated in turning. In contrast, higher approach rates evoke faster, more kinematically stereotyped responses with relatively short latencies, as well as bilateral recruitment of vSPNs and unilateral recruitment of giant fiber neurons in fish and amphibians called Mauthner cells. In addition to the higher proportion of more costly, shorter latency Mauthner-active responses to greater perceived threats, we observe a higher incidence of freezing behavior at higher approach rates. Our results provide a new framework to understand how behavioral flexibility is grounded in the appropriate balancing of trade-offs between fast and slow movements when deciding to respond to a visually perceived threat.

This paper presents an active search trajectory synthesis technique for autonomous mobile robots with nonlinear measurements and dynamics. The presented approach uses the ergodicity of a planned trajectory with respect to an expected information density map to close the loop during search. The ergodic control algorithm does not rely on discretization of the search or action spaces, and is well posed for coverage with respect to the expected information density whether the information is diffuse or localized, thus trading off between exploration and exploitation in a single objective function. As a demonstration, we use a robotic electrolocation platform to estimate location and size parameters describing static targets in an underwater environment. Our results demonstrate that the ergodic exploration of distributed information (EEDI) algorithm outperforms commonly used information-oriented controllers, particularly when distractions are present.Comment: 17 page

South American electric knifefish are a leading model system within neurobiology. Recent efforts have focused on understanding their biomechanics and relating this to their neural processing strategies. Knifefish swim by means of an undulatory fin that runs most of the length of their body, affixed to the belly. Propelling themselves with this fin enables them to keep their body relatively straight while swimming, enabling straightforward robotic implementation with a rigid hull. In this study, we examined the basic properties of undulatory swimming through use of a robot that was similar in some key respects to the knifefish. As we varied critical fin kinematic variables such as frequency, amplitude, and wavelength of sinusoidal traveling waves, we measured the force generated by the robot when it swam against a stationary sensor, and its velocity while swimming freely within a flow tunnel system. Our results show that there is an optimal operational region in the fin's kinematic parameter space. The optimal actuation parameters found for the robotic knifefish are similar to previously observed parameters for the black ghost knifefish, Apteronotus albifrons. Finally, we used our experimental results to show how the force generated by the robotic fin can be decomposed into thrust and drag terms. Our findings are useful for future bio-inspired underwater vehicles as well as for understanding the mechanics of knifefish swimming.

Active sensing organisms, such as bats, dolphins, and weakly electric fish, generate a 3-D space for active sensation by emitting self-generated energy into the environment. For a weakly electric fish, we demonstrate that the electrosensory space for prey detection has an unusual, omnidirectional shape. We compare this sensory volume with the animal's motor volume—the volume swept out by the body over selected time intervals and over the time it takes to come to a stop from typical hunting velocities. We find that the motor volume has a similar omnidirectional shape, which can be attributed to the fish's backward-swimming capabilities and body dynamics. We assessed the electrosensory space for prey detection by analyzing simulated changes in spiking activity of primary electrosensory afferents during empirically measured and synthetic prey capture trials. The animal's motor volume was reconstructed from video recordings of body motion during prey capture behavior. Our results suggest that in weakly electric fish, there is a close connection between the shape of the sensory and motor volumes. We consider three general spatial relationships between 3-D sensory and motor volumes in active and passive-sensing animals, and we examine hypotheses about these relationships in the context of the volumes we quantify for weakly electric fish. We propose that the ratio of the sensory volume to the motor volume provides insight into behavioral control strategies across all animals.

SUMMARYWeakly electric fish are extraordinarily maneuverable swimmers, able to swim as easily forward as backward and rapidly switch swim direction, among other maneuvers. The primary propulsor of gymnotid electric fish is an elongated ribbon-like anal fin. To understand the mechanical basis of their maneuverability, we examine the hydrodynamics of a non-translating ribbon fin in stationary water using computational fluid dynamics and digital particle image velocimetry (DPIV) of the flow fields around a robotic ribbon fin. Computed forces are compared with drag measurements from towing a cast of the fish and with thrust estimates for measured swim-direction reversals. We idealize the movement of the fin as a traveling sinusoidal wave, and derive scaling relationships for how thrust varies with the wavelength, frequency, amplitude of the traveling wave and fin height. We compare these scaling relationships with prior theoretical work. The primary mechanism of thrust production is the generation of a streamwise central jet and the associated attached vortex rings. Under certain traveling wave regimes, the ribbon fin also generates a heave force, which pushes the body up in the body-fixed frame. In one such regime, we show that as the number of waves along the fin decreases to approximately two-thirds, the heave force surpasses the surge force. This switch from undulatory parallel thrust to oscillatory normal thrust may be important in understanding how the orientation of median fins may vary with fin length and number of waves along them. Our results will be useful for understanding the neural basis of control in the weakly electric knifefish as well as for engineering bio-inspired vehicles with undulatory thrusters. Supplementary material available online at