Person:

Engert, Florian

Existing techniques for monitoring neural activity in awake, freely behaving vertebrates are invasive and difficult to target to genetically identified neurons. We used bioluminescence to non-invasively monitor the activity of genetically specified neurons in freely behaving zebrafish. Transgenic fish with the Ca(^{2+})-sensitive photoprotein green fluorescent protein (GFP)-Aequorin in most neurons generated large and fast bioluminescent signals that were related to neural activity, neuroluminescence, which could be recorded continuously for many days. To test the limits of this technique, we specifically targeted GFP-Aequorin to the hypocretin-positive neurons of the hypothalamus. We found that neuroluminescence generated by this group of ~20 neurons was associated with periods of increased locomotor activity and identified two classes of neural activity corresponding to distinct swim latencies. Our neuroluminescence assay can report, with high temporal resolution and sensitivity, the activity of small subsets of neurons during unrestrained behavior.

Understanding how the nervous system recognizes salient stimuli in the environment and selects and executes the appropriate behavioral responses is a fundamental question in systems neuroscience. To facilitate the neuroethological study of visually guided behavior in larval zebrafish, we developed “virtual reality” assays in which precisely controlled visual cues can be presented to larvae whilst their behavior is automatically monitored using machine vision algorithms. Freely swimming larvae responded to moving stimuli in a size-dependent manner: they directed multiple low amplitude orienting turns (∼20°) toward small moving spots (1°) but reacted to larger spots (10°) with high-amplitude aversive turns (∼60°). The tracking of small spots led us to examine how larvae respond to prey during hunting routines. By analyzing movie sequences of larvae hunting paramecia, we discovered that all prey capture routines commence with eye convergence and larvae maintain their eyes in a highly converged position for the duration of the prey-tracking and capture swim phases. We adapted our virtual reality assay to deliver artificial visual cues to partially restrained larvae and found that small moving spots evoked convergent eye movements and J-turns of the tail, which are defining features of natural hunting. We propose that eye convergence represents the engagement of a predatory mode of behavior in larval fish and serves to increase the region of binocular visual space to enable stereoscopic targeting of prey.

In this study we report that larval zebrafish display adaptive locomotor output that can be driven by unexpected visual feedback. We develop a new assay that addresses visuomotor integration in restrained larval zebrafish. The assay involves a closed-loop environment in which the visual feedback a larva receives depends on its own motor output in a way that resembles freely swimming conditions. The experimenter can control the gain of this closed feedback loop, so that following a given motor output the larva experiences more or less visual feedback depending on whether the gain is high or low. We show that increases and decreases in this gain setting result in adaptive changes in behavior that lead to a generalized decrease or increase of motor output, respectively. Our behavioral analysis shows that both the duration and tail beat frequency of individual swim bouts can be modified, as well as the frequency with which bouts are elicited. These changes can be implemented rapidly, following an exposure to a new gain of just 175 ms. In addition, modifications in some behavioral parameters accumulate over tens of seconds and effects last for at least 30s from trial to trial. These results suggest that larvae establish an internal representation of the visual feedback expected from a given motor output and that the behavioral modifications are driven by an error signal that arises from the discrepancy between this expectation and the actual visual feedback. The assay we develop presents a unique possibility for studying visuomotor integration using imaging techniques available in the larval zebrafish.

Understanding how the brain transforms sensory input into complex behavior is a fundamental question in systems neuroscience. Using larval zebrafish, we study the temporal component of phototaxis, which is defined as orientation decisions based on comparisons of light intensity at successive moments in time. We developed a novel “Virtual Circle” assay where whole-field illumination is abruptly turned off when the fish swims out of a virtually defined circular border, and turned on again when it returns into the circle. The animal receives no direct spatial cues and experiences only whole-field temporal light changes. Remarkably, the fish spends most of its time within the invisible virtual border. Behavioral analyses of swim bouts in relation to light transitions were used to develop four discrete temporal algorithms that transform the binary visual input (uniform light/uniform darkness) into the observed spatial behavior. In these algorithms, the turning angle is dependent on the behavioral history immediately preceding individual turning events. Computer simulations show that the algorithms recapture most of the swim statistics of real fish. We discovered that turning properties in larval zebrafish are distinctly modulated by temporal step functions in light intensity in combination with the specific motor history preceding these turns. Several aspects of the behavior suggest memory usage of up to 10 swim bouts (~10 sec). Thus, we show that a complex behavior like spatial navigation can emerge from a small number of relatively simple behavioral algorithms.

A full understanding of nervous system function requires recording from large populations of neurons during naturalistic behaviors. Here we enable paralyzed larval zebrafish to fictively navigate two-dimensional virtual environments while we record optically from many neurons with two-photon imaging. Electrical recordings from motor nerves in the tail are decoded into intended forward swims and turns, which are used to update a virtual environment displayed underneath the fish. Several behavioral features—such as turning responses to whole-field motion and dark avoidance—are well-replicated in this virtual setting. We readily observed neuronal populations in the hindbrain with laterally selective responses that correlated with right or left optomotor behavior. We also observed neurons in the habenula, pallium, and midbrain with response properties specific to environmental features. Beyond single-cell correlations, the classification of network activity in such virtual settings promises to reveal principles of brainwide neural dynamics during behavior.