Wireless electrophysiology of the brain of freely swimming goldfish

Vinepinsky, Ehud; Donchin, Opher; Segev, Ronen

doi:10.1016/j.jneumeth.2017.01.001

Cited by 28 publications

(27 citation statements)

References 15 publications

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“…We trained the fish in seven sessions; each session was performed on a different day and lasted 20 min. After the fish became familiar with the water tank and learned to explore its entire environment naturally, we installed a recording system on their heads 36 , 37 . We then let the goldfish swim freely, while a camera positioned over the water tank recorded the fish's locations and head orientations.…”

Section: Resultsmentioning

confidence: 99%

“…The behavioral fish electrophysiology is described in detail in Vinepinsky et al 36 and Cohen and Vinepinsky et al 37 . Briefly, the experimental setup for recording extracellular signals from the brain of freely swimming goldfish operates through a small data logger (Mouselog-16, Deuteron Technologies Ltd., Jerusalem, Israel).…”

Section: Methodsmentioning

confidence: 99%

“…Surgery was done out of the water while the fish was anesthetized and perfused through its mouth (MS-222 200 mg/l, NaHCO3 400 mg/l 1, Cat A-5040, and Cat S-5761, Sigma-Aldrich, USA) as described in Vinepinsky et al 36 . The brain location was targeted by constituting the anterior mid margin of the posterior commissure as the zero point for the stereotaxic procedure as described by Peter and Gil 63 .…”

Section: Methodsmentioning

confidence: 99%

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

Vinepinsky

Cohen

Perchik

et al. 2020

Sci Rep

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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.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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

Vinepinsky

Cohen

Perchik

et al. 2020

Sci Rep

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“…However, whether a grid cell-like system also exists in the teleost fish, and if this would be a result of convergence or common ancestry is unknown. As neural manipulation and recording technologies have been developed for use in fish [40], our behavioural distance task now provides a valuable tool that can be used into the future alongside single cell recordings and lesioning studies to begin searching for brain regions and eventually cell types directly associated with distance estimation in teleost fish.…”

Section: Discussionmentioning

confidence: 99%

Teleost fish can accurately estimate distance travelled

Karlsson¹,

Willis²,

Patel³

et al. 2019

Preprint

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4Terrestrial animals compute shortcuts through their environment by integrating self-5 motion vectors containing distance and direction information. The sensory and neural 6 mechanisms underlying this navigational feat have been extensively documented, but their 7 evolutionary origins remain unexplored. Among extant vertebrates, the teleost fish make up 8 one of the most diverse and earliest-branching phylogenetic groups, and provide a powerful 9 system to study the origins of vertebrate spatial processing. However, how freely-swimming 10 teleost fish collect and compute metric spatial information underwater are unknown. Using 11 the Picasso triggerfish, Rhinecanthus aculeatus, we investigate the functional and mechanis-12 tic basis of distance estimation in teleost fish for the first time. We show that a fish can 13 learn and remember distance travelled with remarkable accuracy. By analysing swimming 14 trajectories, we form hypotheses about how distance is represented in the teleost brain, and 15 propose that distance may be encoded by dedicated neural structures in a similar way to ter-16 restrial vertebrates. Finally, we begin exploring the sensory mechanisms underlying distance 17 estimation in fish. Many walking animals use a step counter for odometry. By quantifying 18 finbeat use during our distance task, we show that a functionally equivalent finbeat counter 19 is unlikely to provide reliable and precise distance information in an aquatic environment. 20 1 1 Background 21 A powerful way for an animal to navigate through its environment is through path integration. 22Self-movement vectors containing distance and direction information are constantly and auto-23 matically summated throughout any journey, providing the animal with an internal store of a 24 vector taking it directly back to a starting position [1, 2]. The result is a dramatic increase in 25 navigation efficiency -shortcuts can be constructed through entirely unexplored terrain, avoiding 26 the need to use external information to retrace previous steps. 27To achieve this navigational feat, an animal must have dedicated sensory mechanisms and 28 neural structures to collect and process distance and direction information from self-motion cues. 29Such mechanisms have been extensively studied in terrestrial animals ranging from mammals such 30 as humans [3] and rats [4, 5], and invertebrates such as spiders [6], ants [7], and bees [8, 9]. 31In contrast, how underwater species collect, process, and use metric spatial information to ac-32 curately navigate through their environment is largely unknown. An aquatic habitat is a fascinat-33 ing environment to navigate through from a sensory and computational point of view. It contains 34 sensory information not available on land, such as hydrodynamic cues from water flow, hydro-35 static pressure from above, and electric currents carried through the water. Freely-swimming 36 animals also have six degrees of freedom of movement (3 translational: forwards/backwards, 37 left/right, up/down; 3 rotationa...

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“…While many of the above discussed assessments of neuronal encoding are based on recordings from immobilized animals, it is important to note that weakly electric fish, on top of being able to display electrical behaviors when immobilized, show elaborate behaviors and astonishing cognitive abilities and are getting more and more attention for the study of various aspects of active sensing behaviors ( Nelson and MacIver, 2006 ; Engelmann et al, 2008 ; von der Emde et al, 2010 ; Hofmann et al, 2013 , 2017 ; Pedraja et al, 2018 ). Recent technological advances such as electrophysiological recordings from freely moving aquatic animals are rapidly evolving ( Fotowat et al, 2013 ; Vinepinsky et al, 2017 ). Being able to perform such recordings in freely behaving electric fish will allow to combine the investigations of population coding aspects in active sensing contexts – two of the most prominent research streams in neuroscience.…”

Section: Future Directionsmentioning

confidence: 99%

Population Coding and Correlated Variability in Electrosensory Pathways

Hofmann

Chacron

2018

Front. Integr. Neurosci.

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The fact that perception and behavior depend on the simultaneous and coordinated activity of neural populations is well established. Understanding encoding through neuronal population activity is however complicated by the statistical dependencies between the activities of neurons, which can be present in terms of both their mean (signal correlations) and their response variability (noise correlations). Here, we review the state of knowledge regarding population coding and the influence of correlated variability in the electrosensory pathways of the weakly electric fish Apteronotus leptorhynchus. We summarize known population coding strategies at the peripheral level, which are largely unaffected by noise correlations. We then move on to the hindbrain, where existing data from the electrosensory lateral line lobe (ELL) shows the presence of noise correlations. We summarize the current knowledge regarding the mechanistic origins of noise correlations and known mechanisms of stimulus dependent correlation shaping in ELL. We finish by considering future directions for understanding population coding in the electrosensory pathways of weakly electric fish, highlighting the benefits of this model system for understanding the origins and impact of noise correlations on population coding.

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Wireless electrophysiology of the brain of freely swimming goldfish

Cited by 28 publications

References 15 publications

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

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

Teleost fish can accurately estimate distance travelled

Population Coding and Correlated Variability in Electrosensory Pathways

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