The world according to zebrafish: How neural circuits generate behaviour

Cover image for research topic "The world according to zebrafish: How neural circuits generate behaviour"
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Understanding how the brain implements social behavior on one hand, and how social processes feedback on the brain to promote fine-tuning of behavioral output according to changes in the social environment is a major challenge in contemporary neuroscience. A critical step to take this challenge successfully is finding the appropriate level of analysis when relating social to biological phenomena. Given the enormous complexity of both the neural networks of the brain and social systems, the use of a cognitive level of analysis (in an information processing perspective) is proposed here as an explanatory interface between brain and behavior. A conceptual framework for a cognitive approach to comparative social neuroscience is proposed, consisting of the following steps to be taken across different species with varying social systems: (1) identification of the functional building blocks of social skills; (2) identification of the cognitive mechanisms underlying the previously identified social skills; and (3) mapping these information processing mechanisms onto the brain. Teleost fish are presented here as a group of choice to develop this approach, given the diversity of social systems present in closely related species that allows for planned phylogenetic comparisons, and the availability of neurogenetic tools that allows the visualization and manipulation of selected neural circuits in model species such as the zebrafish. Finally, the state-of-the art of zebrafish social cognition and of the tools available to map social cognitive abilities to neural circuits in zebrafish are reviewed.

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Methods
12 June 2013

The zebrafish larva stands out as an emergent model organism for translational studies involving gene or drug screening thanks to its size, genetics, and permeability. At the larval stage, locomotion occurs in short episodes punctuated by periods of rest. Although phenotyping behavior is a key component of large-scale screens, it has not yet been automated in this model system. We developed ZebraZoom, a program to automatically track larvae and identify maneuvers for many animals performing discrete movements. Our program detects each episodic movement and extracts large-scale statistics on motor patterns to produce a quantification of the locomotor repertoire. We used ZebraZoom to identify motor defects induced by a glycinergic receptor antagonist. The analysis of the blind mutant atoh7 revealed small locomotor defects associated with the mutation. Using multiclass supervised machine learning, ZebraZoom categorized all episodes of movement for each larva into one of three possible maneuvers: slow forward swim, routine turn, and escape. ZebraZoom reached 91% accuracy for categorization of stereotypical maneuvers that four independent experimenters unanimously identified. For all maneuvers in the data set, ZebraZoom agreed with four experimenters in 73.2–82.5% of cases. We modeled the series of maneuvers performed by larvae as Markov chains and observed that larvae often repeated the same maneuvers within a group. When analyzing subsequent maneuvers performed by different larvae, we found that larva–larva interactions occurred as series of escapes. Overall, ZebraZoom reached the level of precision found in manual analysis but accomplished tasks in a high-throughput format necessary for large screens.

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131 citations
Perspective
11 June 2013
Functional imaging of the zebrafish larval brain. GCaMP7a is expressed in the optic tectum of a 7-dpf zebrafish larva embedded in agarose. (A) Tectal responses during perception of a swimming paramecium (arrow). Calcium signals are observed in both cell bodies and the neuropil on the right tectum when a paramecium is in the left hemifield. Ratio image was created ad pseudo-colored to show fluorescence changes. (B) Tectal responses during perception of a moving spot. A small LCD screen is placed in front of the larva and a moving spot is presented (from left to the right). Top: Raw images to show eye positions. Bottom: Pseudo-colored images to show fluorescence changes. Yellow arrows indicate eye positions (angles). Yellow dotted lines delineate the optic tectum. (C) Eye positions (top) and GCaMP7a fluorescence intensity changes (bottom) during experiment (B). A moving spot was presented during the time shown as an open arrow. Two-way arrows indicate the time points of 4.4 and 5.0 s shown in (B). The eye convergence (inward movement of both left and right eyes) was evoked by the moving spot. (D) Neuronal activity in the optic tectum of a 4-dpf zebrafish larva. A spinning disk confocal microscope (CSU-W1, Yokogawa Electric Corporation, Tokyo, Japan) was used for recording. Scale bar: 50 μm. (E) The ratiometric image of (D) to reveal the fluorescence change. Small populations of neurons in the right tectum are temporally activated.
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