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My laboratory is exploring how genetic information assembles neuronal circuits and how these circuits in turn control behavior. The fantastic people in my group, who drive this field forward, are portrayed in Fig. 1. Our main focus has been the zebrafish visual system, although we have recently branched out into other species and other parts of the brain. Zebrafish have become a premier research model for behavioral genetics, sensory and systems neuroscience, and neuroethology.
Our current interests can be summarized by the following bullet points:
Over the years, we have made contributions to each of these areas of investigation. Here I will summarize some of our advances in neural circuit analysis, technology development and the Max Planck Zebrafish Brain Atlas.
Over the past decade, we have identified neural pathways and circuits that convert sensory input into motor output for select behaviors, such as phototaxis, prey capture, looming-evoked escape, optokinetic and optomotor responses and the visual recognition of conspecifics. For several of these behaviors, our group has discovered the pathways connecting the retina to the tectum, pretectum, thalamus or preoptic area (Semmelhack et al., 2014; Temizer et al., 2015; Wu et al., 2020; Kölsch et al., 2020). We have also succeeded in mapping downstream connectivity to premotor areas in the tegmentum and reticular formation (e. g., Fig. 2; Helmbrecht et al., 2018; Kramer et al., 2019). This body of work has led to the general hypothesis that stimulus quality (e. g., optic flow vs. prey-like vs. threat vs. conspecific) and valence (attractive vs. aversive vs. neutral) are encoded by anatomically segregated circuits, which receive inputs from staggered arrays of matched filters. These dedicated pathways mutually suppress each other through reciprocal inhibitory connections (see, e. g., Barker and Baier, 2015; Filosa et al., 2016). Such a canonical wiring principle seems to underlie the diverse circuit architectures serving stimulus selection, object identification and behavioral decisions.
Feature-selective retinal ganglion cells (RGCs) represent prime examples of matched filters. To enable genetic access to specific visual processing streams, our group has molecularly catalogued 33 RGC types in larva and adult zebrafish (Kölsch et al., 2021). This was done by single-cell RNA sequencing (scRNA-seq; initially in collaboration with Josh Sanes and Karthik Shekhar, Harvard University and the Broad Institute). Fig. 3 shows schematically five transgenic lines, which were generated using CRISPR/Cas9 knock-ins of type-specific marker genes. Each of the lines provides experimental access to a small subpopulation of RGCs. Novel intersectional genetic strategies, combining QF2 or Gal4, and Cre recombination, are allowing us now to target single RGC types for recording or manipulation (Kölsch et al., 2020). Utilizing this resource and building on the laboratory’s previous work (Robles et al., 2013; 2014), we discovered a pathway serving phototaxis, which originates in an RGC subclass that express the transcription factor Eomesa. Based on a morphological survey of RGC dendrite stratification and axonal projection patterns (Robles et al., 2014), I suspect the total number of RGC types will be greater than the 30, or so, molecular classes, maybe double as many.
Genetic access and transparency of larval zebrafish makes them an excellent model for functional investigation of sensorimotor circuits. In order to fully leverage this advantage, our group develops advanced optical capabilities for recording and manipulating neuron activity. Two-photon calcium imaging is a common technique in the lab; however, standard two-photon microscopes can only record from a single plane, missing relevant correlations between neurons. We have therefore devised rapid volumetric imaging methods, which enable recordings from multiple Z planes (see Fig. 4).
Imaging provides correlative measurements and is often incapable of providing causal evidence or validating proposed circuit mechanisms. Therefore, our group has been advancing an approach based on spatially precise, two-photon computer-generated holographic optogenetics for manipulating activity at the scale of individual neurons (Dal Maschio et al., 2017). A new system built in the lab features optics with improved field of view and resolution for flexible imaging of multiple subvolumes, as well as improvements to the detection pathway and software (Fig. 4). The combined abilities of such an instrument are enabling new kinds of experiments, such as photostimulating multiple, functionally defined neurons, while imaging in downstream areas to uncover causal flows of circuit activity.
Lack of neuroanatomical knowledge hampers progress in systems neuroscience. We have therefore assembled a cellular-resolution atlas of the larval zebrafish brain, which supports not only our own research, but also provides a resource to the wider community (Kunst et al., 2019). The Max Planck Zebrafish Brain Atlas, in its latest version, integrates 116 expert-annotated brain regions, more than 4,000 single neuron morphologies and a growing number (>450) of transgenic lines. These data modalities are registered to the same standard brain space (Fig. 5).
The atlas portal on the website (https://fishatlas.neuro.mpg.de) offers refined analysis tools and also the possibility of uploading, visualization and downloading of data. Several recent papers have relied heavily on this resource (Helmbrecht et al., 2018; Kramer et al., 2019; Wu et al., 2020; Pantoja et al., 2020; Förster et al., 2020). An improved version (working title “mapZeBrain 2.0”) will integrate additional data modalities, such as functional imaging and gene expression data, offer an API for related efforts in other systems, and will sport an improved front-end user interface. The atlas attracts a rapidly growing number of external users (>2,500 unique page views as of April 2021).
Director of the Department Genes–Circuits–Behavior
Max Planck Institute of Neurobiology
Am Klopferspitz 18
82152 Martinsried near Munich
Phone: +49-89-8578-3200
Email: hbaier[at]neuro.mpg.de
Website: https://www.neuro.mpg.de/baier