Bahl lab
Neural Circuit Computation and Behavior
How do animals integrate information and make decisions?
When animals move through the environment, they constantly need to make decisions about what to do next. They integrate information from their senses, retain a working memory of such cues, and evaluate signals according to their internal state. Somehow, the nervous system effortlessly implements these computations and eventually controls behavior.
We use the larval zebrafish as a model organism to investigate the neural circuit mechanisms underlying sensory integration and decision-making. Larval zebrafish are tiny and almost perfectly transparent vertebrates. This allows us to use two-photon microscopy to observe brain activity at cellular resolution in behaving animals and to directly link circuit dynamics to individual swimming decisions.
Research
Individual animal behavior: We think that describing animal behavior on a detailed algorithmic level is an essential step towards understanding brain function. To this end, we perform open-loop as well as closed-loop behavioral experiments in freely swimming and head-fixed larvae.
In our stimulus design, we draw inspiration from classical psychophysics work developed for primates and humans. For example, by translating a popular visual stimulus, the random dot motion stimulus, to fish we discovered that larvae can integrate motion in the environment over multiple seconds and use such cues to decide whether they should swim to the right or to the left.
With such simple behavioral experiments, we ask, for example, how long fish remember, whether swimming decisions reset their motion memory, or whether they can also integrate other sensory modalities.
Collective behavior: When in a group, the decision-making of the individual guides what the collective is doing.
Through precise tracking experiments of groups of fish, we explore to what extend such complex social behaviors can readily emerge from the simple sensory-motor primitives that we have explored in individual animals.
Collective decision-making: It is challenging for isolated animals to reliably extract and integrate behaviorally relevant information from the natural environment. Collective behaviors help animals to sample information more effectively, improves foraging, increases safety from predation, and reduces energy consumption. We provide groups of juvenile zebrafish with integration task and explore how their behavior improves with group size.
Functional imaging: We use two-photon functional imaging in head-fixed behaving animals to characterize the activity of thousands of cells across large parts of the brain. Such experiments help us to identify the key processing centers involved and characterize cell-specific trial-to-trial response dynamics. Having such a perspective on the level of an entire brain helps to deduce how information flows from the animal's senses to its motor output.
Circuit dissections: The observed circuit dynamics arise from an intricate interplay between thousands of cells with each type having its own biophysical properties. To better understand this, we perform cell-specific ablations and optogenetic interventions. We also use a wide array of molecular genetic tools to study anatomy, neurotransmitter identity, synaptic connectivity as well as the expression profile of functionally identified cells.
Molecular and imaging tools: We develop new molecular tools to photoactivate functionally identified neurons, to locally regulate gene expression, or to image the brain label-free.
Modeling: Computational modeling is an important component in our projects: First, it helps us to interpret and design behavioral experiments. Second, it allows us to better understand how complex group dynamics may arise from the decision-making of the individual. Third, it provides us with a powerful tool to make precise and testable predictions about possible cell anatomies and connectivities, neuronal dynamics, as well as behavior in our circuit dissection experiments.
People
Armin Bahl
Professor / Emmy Noether Group Leader
Meha Jadhav
Postdoc
Max Capelle
PhD Student
Florian Kämpf
Master Student
Angelina Haag
Highschool Matura Student
Zihan Lyu
DAAD Rise Exchange Student
Ulrike Bonitz
Secretary
Daniel Hummel
Postdoc
Ashrit Mangalwedhekar
PhD Student
Roberto Garza
PhD Student
Flutura Shabani
Master Student
Ben Hanson
DAAD RISE Exchange Student
Antonia Gäbler
Bachelor Student
Margherita Zaupa
Postdoc
Katja Slangewal
PhD Student
Sydney Hunt
PhD Student
Kim Kirchberger
Master student
Kezban Özdemir
Erasmus Exchange Student
Heike Naumann
Research Technician
Former members
Moritz Schlötter
Postdoc – Now: Project Leader at Storz Medical, Tägerwilen
Panagiotis Eleftheriadis
Research Exchange Student: Now Master Student at the GSN Munich
Maximilian Stahlsmeier
Exchange Master Student (Bielefeld)
Nikolai Hörmann
Visiting PhD Student – Now: Postdoc Harvard University
Sandrien Huber
Master Student
Vanessa Gambus
Bachelor Student – Now: Master Student at the University of Konstanz
Phoebe Reynolds-Whitehead
Visiting PhD Student: Now PHD Student at Kings College London
Fausto Piehler
Bachelor Student – Now: Master Student in Cognitive Psychology, University of Vienna
Maite Börsig
Research Assistant – Now: Master Student in Neuroscience at the University of Heidelberg
Leonard Weiß
Bachelor Student: Now Master Exchange Student at Universidade de Lisboa
Moritz Fuchsloch
Master Student – Now: PhD Student Institute for Laser Tools, Uni Stuttgart
Magnus Wannemacher
Research Assistant
Open positions
We are always seeking enthusiastic students on all levels to join our group. If you like interdisciplinary work and if you like to tackle challenging projects in Systems Neuroscience, shoot us an email and come visit!
Partner labs
We are extensively working together with our friends and partners at different international Universities. Graduate students and postdocs from the Bahl lab will get the opportunity for extended research stays with our collaborators, focusing on specific research questions that can only be addressed as a joint venture. The aim of the program is to foster an exchange of conceptual ideas, imaging and physiological techniques, and molecular genetic tools, and to provide members of the Bahl lab with opportunities to further extend their visibility and scientific network.
Publications
1. Voigt FF., Reuss AM., Naert T., Hildebrand S., Schaettin M., Hotz AL, Whitehead L., Bahl A., Neuhauss SCF, Roebroeck A., Stoeckli ET., Lienkamp SS., Aguzzi A., Helmchen F. (2023) Reflective multi-immersion microscope objectives inspired by the Schmidt telescope. Nature Biotechnology
2. Vohra SK., Harth P., Isoe Y., Bahl A., Fotowat H., Engert F., Hege HC, and Baum D. (2023). A visual interface for exploring hypotheses about neural circuits. IEEE TVCG.
3. Harpaz R., Nguyen M.N., Bahl A., Engert F. (2021). Precise visuomotor transformations underlying collective behavior in larval zebrafish. Nat. Commun. 12 (1), 1–14.
4. Harpaz R., Aspiras A.C., Chambule S., Tseng S., Engert F., Fishman M.C.*, Bahl A.* (2021). Collective behavior emerges from genetically controlled simple behavioral motifs in zebrafish. Sci. Adv. 7 (41), 1–13.
5. Zhu M.L., Herrera K.J., Vogt K., Bahl A.* (2021). Navigational strategies underlying temporal phototaxis in Drosophila larvae. J. Exp. Biol. 224 (11), 1–7.
6. Chen A.B., Deb D., Bahl A., Engert F. (2021). Algorithms underlying flexible phototaxis in larval zebrafish. J. Exp. Biol. 224 (10), 1–11.
7. Bahl A.*, Engert F. (2020). Neural circuits for evidence accumulation and decision-making in larval zebrafish. Nat. Neurosci. 23 (1), 94–102.
8. Wee C., Song E., Johnson R., Ailani D., Randlett O., Kim J., Nikitchenko M., Bahl A., Yang C., Ahrens M., Kawakami K., Engert F., Kunes S. (2019). A bidirectional network for appetite control in larval zebrafish. eLife 8 (e43775), 1–37.
9. Ribeiro I., Drews M., Bahl A., Machacek C. Borst A., Dickson B.J. (2018). Visual projection neurons mediating directed courtship in Drosophila. Cell 174 (3), 607-621.
10. Leonhardt A., Ammer G., Meier M., Serbe E., Bahl A., Borst A. (2016). Asymmetry of Drosophila ON and OFF motion detectors enhances real-world velocity estimation. Nat. Neurosci. 19 (5), 706–715.
11. Bahl A.*, Serbe E., Meier M., Ammer G., Borst A. (2015). Neural mechanisms for Drosophila contrast vision. Neuron 88 (6), 1240–1252.
12. Ammer G., Leonhardt A., Bahl A., Dickson B.J., Borst A. (2015). Functional specialization of neural input elements to the Drosophila ON motion detector. Curr. Biol. 25 (17), 2247–2253.
13. Maisak M.S., Haag J., Ammer G., Serbe E., Meier M., Leonhardt A., Schilling T., Bahl A., Rubin G.M., Nern A., Dickson B., Reiff D.F., Hopp E., Borst A. (2013). A directional tuning map of Drosophila elementary motion detectors. Nature 500 (7461), 212–216.
14. Bahl A.*, Ammer G., Schilling T., Borst A.* (2013). Object tracking in motion-blind flies. Nat. Neurosci. 16 (6), 730–738.
15. Bahl A.*, Stemmler M.B., Herz A.V.M., Roth A. (2012). Automated optimization of a reduced layer 5 pyramidal cell model based on experimental data. J. Neurosci. Methods 210 (1), 22–34.
16. Plett J., Bahl A., Buss M., Kühnlenz K., Borst A. (2012). Bio-inspired visual ego-rotation sensor for MAVs. Biol. Cybern. 106 (1), 51–63.
17. Roth A.*, Bahl A.* (2009). Divide et impera: optimizing compartmental models of neurons step by step. J. Physiol. 587 (7), 1369–1370.
*Corresponding author
Funding and affiliations
