Ulanovsky Lab

Neural Codes for Natural Behaviors

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Research Philosophy

The research in our lab focuses on the neural basis of natural behaviors. We aim to uncover general principles of mammalian brain function, by capitalizing on the unique behaviors of bats – a novel animal model that we pioneered. Our general approach is to utilize the advantages that bats afford – their outstanding navigation, 3D flight, fast movement, their temporally-discrete sensory system (sonar) and excellent vision, and their high sociality – in order to ask general questions in systems neuroscience, behavioral neuroscience, social neuroscience, and neuroethology; particularly questions that are difficult to address in rodents.

We study the hippocampal formation and prefrontal cortex, and we ask: What are the neural codes that underlie complex natural behaviors such as navigation and sociality? To pursue these questions, we develop world-unique neural loggers – tiny wireless devices, which enable recording > 100 neurons simultaneously from the bat's brain during flight and social interactions. Our study species, Egyptian fruit bats, are easy to work with, and are excellent navigators and highly-social mammals – making them a great model organism for behavioral neuroscience, learning & memory, and social neuroscience of animal groups. We have several world-unique experimental facilities: 700-meter long tunnel, 60x35-meter flight maze, 3D flight-rooms, and social rooms. We also perform neural recordings outdoors in bats flying on a remote oceanic island.

Our long-term vision is to develop a "Natural Neuroscience" approach for studying the neural basis of behavior – tapping into the animal's natural behaviors in complex, large-scale, naturalistic settings – while not compromising on rigorous experimental control. We firmly believe that pursuing such an approach will lead to novel and surprising insights about the brain.

Research page

Neurobiology of Navigation

Social Neuroscience

Neuroscience in the Wild

Selected Publications

Natural switches in behaviour rapidly modulate hippocampal coding

Sarel A., Palgi S., Blum D., Aljadeff J., Las L. & Ulanovsky N. (2022) Nature 609, 119-127

Sarel2022.pdf

Throughout their daily lives, animals and humans often switch between different behaviours. However, neuroscience research typically studies the brain while the animal is performing one behavioural task at a time, and little is known about how brain circuits represent switches between different behaviours. Here we tested this question using an ethological setting: two bats flew together in a long 135 m tunnel, and switched between navigation when flying alone (solo) and collision avoidance as they flew past each other (cross-over). Bats increased their echolocation click rate before each cross-over, indicating attention to the other bat(1-9). Hippocampal CA1 neurons represented the bat's own position when flying alone (place coding(10-14)). Notably, during cross-overs, neurons switched rapidly to jointly represent the interbat distance by self-position. This neuronal switch was very fast-as fast as 100 ms-which could be revealed owing to the very rapid natural behavioural switch. The neuronal switch correlated with the attention signal, as indexed by echolocation. Interestingly, the different place fields of the same neuron often exhibited very different tuning to interbat distance, creating a complex non-separable coding of position by distance. Theoretical analysis showed that this complex representation yields more efficient coding. Overall, our results suggest that during dynamic natural behaviour, hippocampal neurons can rapidly switch their core computation to represent the relevant behavioural variables, supporting behavioural flexibility.

Locally ordered representation of 3D space in the entorhinal cortex

Ginosar G., Aljadeff J., Burak Y., Sompolinsky H., Las L. & Ulanovsky N. (2021) Nature 596, 404-409

Ginosar2021.pdf

As animals navigate on a two-dimensional surface, neurons in the medial entorhinal cortex (MEC) known as grid cells are activated when the animal passes through multiple locations (firing fields) arranged in a hexagonal lattice that tiles the locomotion surface¹. However, although our world is three-dimensional, it is unclear how the MEC represents 3D space². Here we recorded from MEC cells in freely flying bats and identified several classes of spatial neurons, including 3D border cells, 3D head-direction cells, and neurons with multiple 3D firing fields. Many of these multifield neurons were 3D grid cells, whose neighbouring fields were separated by a characteristic distanceforming a local orderbut lacked any global lattice arrangement of the fields. Thus, whereas 2D grid cells form a global latticecharacterized by both local and global order3D grid cells exhibited only local order, creating a locally ordered metric for space. We modelled grid cells as emerging from pairwise interactions between fields, which yielded a hexagonal lattice in 2D and local order in 3D, thereby describing both 2D and 3D grid cells using one unifying model. Together, these data and model illuminate the fundamental differences and similarities between neural codes for 3D and 2D space in the mammalian brain.

Multiscale representation of very large environments in the hippocampus of flying bats

Eliav T., Maimon S. R., Aljadeff J., Tsodyks M., Ginosar G., Las L. & Ulanovsky N. (2021) Science 372, eabg4020

Eliav2021.pdf

Hippocampal place cells encode the animals location. Place cells were traditionally studied in small environments, and nothing is known about large ethologically relevant spatial scales. We wirelessly recorded from hippocampal dorsal CA1 neurons of wild-born bats flying in a long tunnel (200 meters). The size of place fields ranged from 0.6 to 32 meters. Individual place cells exhibited multiple fields and a multiscale representation: Place fields of the same neuron differed up to 20-fold in size. This multiscale coding was observed from the first day of exposure to the environment, and also in laboratory-born bats that never experienced large environments. Theoretical decoding analysis showed that the multiscale code allows representation of very large environments with much higher precision than that of other codes. Together, by increasing the spatial scale, we discovered a neural code that is radically different from classical place codes.

Nonoscillatory Phase Coding and Synchronization in the Bat Hippocampal Formation

Eliav T., Geva-Sagiv M., Yartsev M. M., Finkelstein A., Rubin A., Las L. & Ulanovsky N. (2018) Cell 175, 1119-1130

Eliav2018.pdf

Hippocampal theta oscillations were proposed to be important for multiple functions, including memory and temporal coding of position. However, previous findings from bats have questioned these proposals by reporting absence of theta rhythmicity in bat hippocampal formation. Does this mean that temporal coding is unique to rodent hippocampus and does not generalize to other species? Here, we report that, surprisingly, bat hippocampal neurons do exhibit temporal coding similar to rodents, albeit without any continuous oscillations at the 1-20 Hz range. Bat neurons exhibited very strong locking to the non-rhythmic fluctuations of the field potential, such that neurons were synchronized together despite the absence of oscillations. Further, some neurons exhibited "phase precession'' and phase coding of the bat's position-with spike phases shifting earlier as the animal moved through the place field. This demonstrates an unexpected type of neural coding in the mammalian brain-nonoscillatory phase coding-and highlights the importance of synchrony and temporal coding for hippocampal function across species.

Social place-cells in the bat hippocampus

Omer D. B., Maimon S. R., Las L. & Ulanovsky N. (2018) Science 359, 218-224

Omer2018.pdf

Social animals have to know the spatial positions of conspecifics. However, it is unknown how the position of others is represented in the brain. We designed a spatial observational-learning task, in which an observer bat mimicked a demonstrator bat while we recorded hippocampal dorsal-CA1 neurons from the observer bat. A neuronal subpopulation represented the position of the other bat, in allocentric coordinates. About half of these "social placecells" represented also the observer's own position-that is, were place cells. The representation of the demonstrator bat did not reflect self-movement or trajectory planning by the observer. Some neurons represented also the position of inanimate moving objects; however, their representation differed from the representation of the demonstrator bat. This suggests a role for hippocampal CA1 neurons in social-spatial cognition.

Vectorial representation of spatial goals in the hippocampus of bats

Sarel A., Finkelstein A., Las L. & Ulanovsky N. (2017) Science 355, 176-180

Sarel2017.pdf

To navigate, animals need to represent not only their own position and orientation, but also the location of their goal. Neural representations of an animal's own position and orientation have been extensively studied. However, it is unknown how navigational goals are encoded in the brain.We recorded from hippocampal CA1 neurons of bats flying in complex trajectories toward a spatial goal.We discovered a subpopulation of neurons with angular tuning to the goal direction. Many of these neurons were tuned to an occluded goal, suggesting that goal-direction representation is memory-based. We also found cells that encoded the distance to the goal, often in conjunction with goal direction. The goaldirection and goal-distance signals make up a vectorial representation of spatial goals, suggesting a previously unrecognized neuronal mechanism for goal-directed navigation.

Three-dimensional head-direction coding in the bat brain

Finkelstein A., Derdikman D., Rubin A., Foerster J. N., Las L. & Ulanovsky N. (2015) Nature 517, 159-164

Finkelstein2015.pdf

Navigation requires a sense of direction (compass), which in mammals is thought to be provided by head-direction cells, neurons that discharge when the animals head points to a specific azimuth. However, it remains unclear whether a three-dimensional (3D) compass exists in the brain. Here we conducted neural recordings in bats, mammals well-adapted to 3D spatial behaviours, and found head-direction cells tuned to azimuth, pitch or roll, or to conjunctive combinations of 3D angles, in both crawling and flying bats. Head-direction cells were organized along a functionalanatomical gradient in the presubiculum, transitioning from 2D to 3D representations. In inverted bats, the azimuth-tuning of neurons shifted by 180°, suggesting that 3D head direction is represented in azimuth × pitch toroidal coordinates. Consistent with our toroidal model, pitch-cell tuning was unimodal, circular, and continuous within the available 360° of pitch. Taken together, these results demonstrate a 3D head-direction mechanism in mammals, which could support navigation in 3D space.

Representation of three-dimensional space in the hippocampus of flying bats

Yartsev M. M. & Ulanovsky N. (2013) Science 340, 367-372

Yartsev2013.pdf

Many animals, on air, water, or land, navigate in three-dimensional (3D) environments, yet it remains unclear how brain circuits encode the animal's 3D position. We recorded single neurons in freely flying bats, using a wireless neural-telemetry system, and studied how hippocampal place cells encode 3D volumetric space during flight. Individual place cells were active in confined 3D volumes, and in >90% of the neurons, all three axes were encoded with similar resolution. The 3D place fields from different neurons spanned different locations and collectively represented uniformly the available space in the room. Theta rhythmicity was absent in the firing patterns of 3D place cells. These results suggest that the bat hippocampus represents 3D volumetric space by a uniform and nearly isotropic rate code.

Grid cells without theta oscillations in the entorhinal cortex of bats

Yartsev M. M., Witter M. P. & Ulanovsky N. (2011) Nature 479, 103-107

Yartsev2011.pdf

Grid cells provide a neural representation of space, by discharging when an animal traverses through the vertices of a periodic hexagonal grid spanning the environment. Although grid cells have been characterized in detail in rats, the fundamental question of what neural dynamics give rise to the grid structure remains unresolved. Two competing classes of models were proposed: network models, based on attractor dynamics, and oscillatory interference models, which propose that interference between somatic and dendritic theta-band oscillations (4-10ĝ\u20acHz) in single neurons transforms a temporal oscillation into a spatially periodic grid. So far, these models could not be dissociated experimentally, because rodent grid cells always co-exist with continuous theta oscillations. Here we used a novel animal model, the Egyptian fruit bat, to refute the proposed causal link between grids and theta oscillations. On the basis of our previous finding from bat hippocampus, of spatially tuned place cells in the absence of continuous theta oscillations, we hypothesized that grid cells in bat medial entorhinal cortex might also exist without theta oscillations. Indeed, we found grid cells in bat medial entorhinal cortex that shared remarkable similarities to rodent grid cells. Notably, the grids existed in the absence of continuous theta-band oscillations, and with almost no theta modulation of grid-cell spiking-both of which are essential prerequisites of the oscillatory interference models. Our results provide a direct demonstration of grid cells in a non-rodent species. Furthermore, they strongly argue against a major class of computational models of grid cells.

Optimal localization by pointing off axis

Yovel Y., Falk B., Moss C. F. & Ulanovsky N. (2010) Science 327, 701-704

Yovel2010.pdf

Is centering a stimulus in the field of view an optimal strategy to localize and track it? We demonstrated, through experimental and computational studies, that the answer is no. We trained echolocating Egyptian fruit bats to localize a target in complete darkness, and we measured the directional aim of their sonar clicks. The bats did not center the sonar beam on the target, but instead pointed it off axis, accurately directing the maximum slope ("edge") of the beam onto the target. Information-theoretic calculations showed that using the maximum slope is optimal for localizing the target, at the cost of detection. We propose that the tradeoff between detection (optimized at stimulus peak) and localization (optimized at maximum slope) is fundamental to spatial localization and tracking accomplished through hearing, olfaction, and vision.

All Publications

Positions Available

We are looking for outstanding, highly motivated students who are interested in behavioral neuroscience and systems neuroscience. Students in the lab come from a variety of academic backgrounds, including Neuroscience, Biology, Psychology, Physics, Mathematics, and Engineering. We love these diverse perspectives! We often combine experimental and theoretical / computational approaches to investigate key questions in systems and behavioral neuroscience.