Radial astrocyte synchronization modulates the visual system during behavioral-state transitions.

Glial cells support the function of neurons. Recent evidence shows that astrocytes are also involved in brain computations. To explore whether and how their excitable nature affects brain computations and motor behaviors, we used two-photon Ca2+ imaging of zebrafish larvae expressing GCaMP in both neurons and radial astrocytes (RAs). We found that in the optic tectum, RAs synchronize their Ca2+ transients immediately after the end of an escape behavior. Using optogenetics, ablations, and a genetically encoded norepinephrine sensor, we observed that RA synchronous Ca2+ events are mediated by the locus coeruleus (LC)-norepinephrine circuit. RA synchronization did not induce direct excitation or inhibition of tectal neurons. Nevertheless, it modulated the direction selectivity and the long-distance functional correlations among neurons. This mechanism supports freezing behavior following a switch to an alerted state. These results show that LC-mediated neuro-glial interactions modulate the visual system during transitions between behavioral states.

Evolutionary modifications of Astyanax larval prey capture (LPC) in a dark environment.

Feeding strategies of an organism depend on the multimodal sensory processing that most efficiently integrates available visual, chemosensory, and/or mechanoreceptive cues as part of their environmental adaptation. The blind cavefish morph of Astyanax mexicanus has developed sensory-dependent behaviors to find food more efficiently than their eyed, surface-morph counterparts while in darkness. In the absence of light, adult cavefish have evolved enhanced behaviors, such as vibration attraction behavior (VAB), and changes in feeding angle. Here, we identified evolved differences in cavefish larval prey capture (LPC) behavior. In the dark, LPC is more efficient in cavefish than in surface fish. Furthermore, different cave populations express laterality in their LPC and strike towards prey preferentially located on their left or right sides. This suggests the occurrence, to some extent, of divergent LPC evolution among cave populations. While LPC can be triggered exclusively by a vibration stimulus in both surface and cavefish, we provide evidence that LPC is, at least partially, a multimodal sensory process different from adult VAB. We also found that a lack of food may exacerbate the laterality of LPC. Thus, we proposed a mathematical model for explaining laterality based on a balance between: (1) enlarged range of foraging field (behavioral or perceptive) due to asymmetry, (2) food abundance, and (3) disadvantages caused by laterality (unequal lateral hydrodynamic resistance when swimming, allocation of resources for the brain and receptors, and predator escape).

Boundary vector cells in the goldfish central telencephalon encode spatial information.

Navigation is one of the most fundamental cognitive skills for the survival of fish, the largest vertebrate class, and almost all other animal classes. Space encoding in single neurons is a critical component of the neural basis of navigation. To study this fundamental cognitive component in fish, we recorded the activity of neurons in the central area of the goldfish telencephalon while the fish were freely navigating in a quasi-2D water tank embedded in a 3D environment. We found spatially modulated neurons with firing patterns that gradually decreased with the distance of the fish from a boundary in each cell's preferred direction, resembling the boundary vector cells found in the mammalian subiculum. Many of these cells exhibited beta rhythm oscillations. This type of spatial representation in fish brains is unique among space-encoding cells in vertebrates and provides insights into spatial cognition in this lineage.

Optimal stopover model: A state-dependent habitat selection model for staging passerines.

During their seasonal migration, birds stage in areas comprising stopover sites of varying quality. Given that migrating birds have a limited information about their environment, they may land at a low-quality stopover site in which their fuel deposition rate (FDR) is low. Birds landing at such sites should decide either to extend their stopover duration or to quickly depart in search for a better site. These decisions, however, strongly depend on their body condition upon landing. To understand the decision-making process of passerines within a stopover area, comprising stopover sites of varying quality, prior to the crossing of a large ecological barrier, we constructed a state-dependent habitat selection model. The model assumes that even if migrating birds have an expectation of encountered area quality, they cannot control for their initial landing site. Once landing, movement between low- and high-quality stopover sites will occur only if the body condition of these birds is high to the extent that they can entail the energetic cost of movement. Birds in the model aim to maximize their fuel load at the end of the stopover period, to suffice for successfully crossing a large ecological barrier. The model is based on empirical data on autumn migrating Blackcaps Sylvia atricapilla, collected at two important stopover sites in the Negev desert of Israel. Migrating passerines staging at these two sites differ in their FDR and body condition. The model shows that the optimal behaviour when arriving at a low-quality stopover site is to abandon it quickly. However, as lean individuals cannot entail the costs of searching for an alternative site, they have no other choice but to stay there even if their chances to successfully cross the Sahara Desert ahead are low. Our model can be applied to other ecological systems. Proper use of this model may allow good assessment of stopover site quality, as indicated by the bird's FDR, regardless of specific site characteristics. Hence, it can help applying targeted management decisions regarding the maintenance of stopover sites or establishment of new ones.

A Generalized Linear Model of a Navigation Network.

Navigation by mammals is believed to rely on a network of neurons in the hippocampal formation, which includes the hippocampus, the medial entorhinal cortex (MEC), and additional nearby regions. Neurons in these regions represent spatial information by tuning to the position, orientation, and speed of the animal in the form of head direction cells, speed cells, grid cells, border cells, and unclassified spatially modulated cells. While the properties of single cells are well studied, little is known about the functional structure of the network in the MEC. Here, we use a generalized linear model to study the network of spatially modulated cells in the MEC. We found connectivity patterns between all spatially encoding cells and not only grid cells. In addition, the neurons' past activity contributed to the overall activity patterns. Finally, position-modulated cells and head direction cells differed in the dependence of the activity on the history. Our results indicate that MEC neurons form a local interacting network to support spatial information representations and suggest an explanation for their complex temporal properties.

Representation of edges, head direction, and swimming kinematics in the brain of freely-navigating fish.

Like most animals, the survival of fish depends on navigation in space. This capacity has been documented in behavioral studies that have revealed navigation strategies. However, little is known about how freely swimming fish represent space and locomotion in the brain to enable successful navigation. Using a wireless neural recording system, we measured the activity of single neurons in the goldfish lateral pallium, a brain region known to be involved in spatial memory and navigation, while the fish swam freely in a two-dimensional water tank. We found that cells in the lateral pallium of the goldfish encode the edges of the environment, the fish head direction, the fish swimming speed, and the fish swimming velocity-vector. This study sheds light on how information related to navigation is represented in the brain of fish and addresses the fundamental question of the neural basis of navigation in this group of vertebrates.

Wireless Electrophysiological Recording of Neurons by Movable Tetrodes in Freely Swimming Fish.

The neural mechanisms governing fish behavior remain mostly unknown, although fish constitute the majority of all vertebrates. The ability to record brain activity from freely moving fish would advance research on the neural basis of fish behavior considerably. Moreover, precise control of the recording location in the brain is critical to studying coordinated neural activity across regions in fish brain. Here, we present a technique that records wirelessly from the brain of freely swimming fish while controlling for the depth of the recording location. The system is based on a neural logger associated with a novel water-compatible implant that can adjust the recording location by microdrive-controlled tetrodes. The capabilities of the system are illustrated through recordings from the telencephalon of goldfish.

Long-range neural inhibition and stimulus competition in the archerfish optic tectum.

The archerfish, which is unique in its ability to hunt insects above the water level by shooting a jet of water at its prey, operates in a complex visual environment. The fish needs to quickly select one object from among many others. In animals other than the archerfish, long-range inhibition is considered to drive selection. As a result of long-range inhibition, a potential target outside a neuron's receptive field suppresses the activity elicited by another potential target within the receptive field. We tested whether a similar mechanism operates in the archerfish by recording the activity of neurons in the optic tectum while presenting a target stimulus inside the receptive field and a competing stimulus outside the receptive field. We held the features of the target constant while varying the size, speed, and distance of the competing stimulus. We found cells that exhibit long-range inhibition; i.e., inhibition that extends to a significant part of the entire visual field of the animal. The competing stimulus depressed the firing rate. In some neurons, this effect was dependent on the features of the competing stimulus. These findings suggest that long-range inhibition may play a crucial role in the target selection process in the archerfish.

Wireless electrophysiology of the brain of freely swimming goldfish.

BACKGROUND: Fish are a diverse group of vertebrates with very different brain structures. The study of the neurobiology of fish can thus lead to many important insights on information processing in the brain in a variety of environments. NEW METHOD: We developed a novel wireless technique to record extracellular neural signal activity in freely behaving fish. The system is based on a data logger and enables continues recording of up to 2.5h. RESULTS: For proof of concept we recorded from the optic tectum of goldfish. We found correlations between the activity of the optic tectum and the light intensity in the room, as expected. COMPARISON WITH EXISTING METHODS: Due to the technical difficulties involved in making electrophysiological recordings of behaving aquatic animals, there is no method for recording electrical neural activity from the brain of freely swimming fish. CONCLUSIONS: This powerful tool should facilitate studies of information processing in behaving fish and other behaving aquatic animals.