Biology subjects

Haberkern, H.

Publications and source records attributed to Haberkern, H..

6 recordsLinked to original sources

bioRxiv2025

MoMo - Combining Neuron Morphology and Connectivity forInteractive Motif Analysis in Connectomes

Connectomics, a subfield of neuroscience, reconstructs structural and functional brain maps at synapse-level resolution. These complex spatial maps consist of tree-like neurons interconnected by synapses. Motif analysis is a widely used method for identifying recurring subgraph patterns in connectomes. These motifs, thus, potentially represent fundamental units of information processing. However, existing computational tools often oversimplify neurons as mere nodes in a graph, disregarding their intricate morphologies. In this paper, we introduce MoMo, a novel interactive visualization framework for analyzing neuron morphology-aware motifs in large connectome graphs. First, we propose an advanced graph data structure that integrates both neuronal morphology and synaptic connectivity. This enables highly efficient, parallel subgraph isomorphism searches, allowing for interactive morphological motif queries. Second, we develop a sketch-based interface that facilitates the intuitive exploration of morphology-based motifs within our new data structure. Users can conduct interactive motif searches on state-of-the-art connectomes and visualize results as interactive 3D renderings. We present a detailed goal and task analysis for motif exploration in connectomes, incorporating neuron morphology. Finally, we evaluate MoMo through case studies with four domain experts, who asses the tools usefulness and effectiveness in motif exploration, and relevance to real-world neuroscience research. The source code for MoMo is available here.

neuroscience↗

bioRxiv2024

Exploration and exploitation are flexibly balanced during local search in flies

After finding food, a foraging animal must decide whether to continue feeding, or to explore the environment for potentially better options. One strategy to negotiate this tradeoff is to perform local searches around the food but repeatedly return to feed. We studied this behavior in flies and used genetic tools to uncover the underlying mechanisms. Over time, flies gradually expand their search, shifting from primarily exploiting food sources to exploring the environment, a change that is likely driven by increases in satiety. We found that flies search patterns preserve these dynamics even as the overall scale of the search is modulated by starvation-induced changes in metabolic state. In contrast, search induced by optogenetic activation of sugar sensing neurons does not show these dynamics. We asked what navigational strategies underlie local search. Using a generative model, we found that a change in locomotor pattern after food consumption could account for repeated returns to the food, but failed to capture relatively direct, long return trajectories. Alternative strategies, such as path integration or sensory taxis could allow flies to return from larger distances. We tested this by individually silencing the flys head direction system, olfaction and hygrosensation, and found that the only substantial effect was from perturbing hygrosensation, which reduced the number of long exploratory trips. Our study illustrates that local search is composed of multiple behavioral features that evolve over time based on both internal and external factors, providing a path towards uncovering the underlying neural mechanisms.

neuroscience↗

bioRxiv2023

A neuronal substrate for translating nutrient state and resource density estimations into foraging decisions

Foraging animals must balance the costs of exploring their surroundings with the potential benefits of finding nutritional resources. Each time an animal encounters a food source it must decide whether to initiate feeding or continue searching for potentially better options. Experimental evidence and patch foraging models predict that this decision depends on both nutritional state and the density of available resources in the environment. How the brain integrates such internal and external states to adapt the so-called exploration-exploitation trade-off remains poorly understood. We use video-based tracking to show that Drosophila regulates the decision to engage with food patches based on nutritional state and travel time between food patches, the latter being a measure of food patch density in the environment. To uncover the neuronal basis of this decision process, we performed a neurogenetic silencing screen of more than 400 genetic driver lines with sparse expression patterns in the fly brain. We identified a population of neurons in the central complex that acts as a key regulator of the decision to engage with a food patch. We show that manipulating the activity of these neurons alters the probability to engage, that their activity is modulated by the protein state of the animal, and that silencing these neurons perturbs the ability of the animal to adjust foraging decisions to the flys travel time between food patches. Taken together, our results reveal a neuronal substrate that integrates nutritional state and patch density information to control a specific foraging decision, and therefore provide an important step towards a mechanistic explanation of the cognitive computations that resolve complex cost-benefit trade-offs.

neuroscience↗

bioRxiv2022

Maintaining a stable head direction representation in naturalistic visual environments

Many animals rely on a representation of head direction for flexible, goal-directed navigation. In insects, a compass-like head direction representation is maintained in a conserved brain region called the central complex. This head direction representation is updated by self-motion information and by tethering to sensory cues in the surroundings through a plasticity mechanism. However, under natural settings, some of these sensory cues may temporarily disappear--for example, when clouds hide the sun--and prominent landmarks at different distances from the insect may move across the animals field of view during translation, creating potential conflicts for a neural compass. We used two-photon calcium imaging in head-fixed Drosophila behaving in virtual reality to monitor the flys compass during navigation in immersive naturalistic environments with approachable local landmarks. We found that the flys compass remains stable even in these settings by tethering to available global cues, likely preserving the animals ability to perform compass-driven behaviors such as maintaining a constant heading.

neuroscience↗

bioRxiv2020

A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selection

Flexible behaviors over long timescales are thought to engage recurrent neural networks in deep brain regions, which are experimentally challenging to study. In insects, recurrent circuit dynamics in a brain region called the central complex (CX) enable directed locomotion, sleep, and context- and experience-dependent spatial navigation. We describe the first complete electron-microscopy-based connectome of the Drosophila CX, including all its neurons and circuits at synaptic resolution. We identified new CX neuron types, novel sensory and motor pathways, and network motifs that likely enable the CX to extract the flys head-direction, maintain it with attractor dynamics, and combine it with other sensorimotor information to perform vector-based navigational computations. We also identified numerous pathways that may facilitate the selection of CX-driven behavioral patterns by context and internal state. The CX connectome provides a comprehensive blueprint necessary for a detailed understanding of network dynamics underlying sleep, flexible navigation, and state-dependent action selection.

neuroscience↗

bioRxiv2018

On the adaptive behavior of head-fixed flies navigating in two-dimensional, visual virtual reality

A navigating animals sensory experience is shaped not just by its surroundings, but by its movements within them, which in turn are influenced by its past experiences. Studying the intertwined roles of sensation, experience and directed action in navigation has been made easier by the development of virtual reality (VR) environments for head-fixed animals, which allow for quantitative measurements of behavior in well-controlled sensory conditions. VR has long featured in studies of Drosophila melanogaster, but these experiments have typically relied on one-dimensional (1D) VR, effectively allowing the fly to change only its heading in a visual scene, and not its position. Here we explore how flies navigate in a two-dimensional (2D) visual VR environment that more closely resembles their experience during free behavior. We show that flies interaction with landmarks in 2D environments cannot be automatically derived from their behavior in simpler 1D environments. Using a novel paradigm, we then demonstrate that flies in 2D VR adapt their behavior in a visual environment in response to optogenetically delivered appetitive and aversive stimuli. Much like free-walking flies after encounters with food, head-fixed flies respond to optogenetic activation of sugar-sensing neurons by initiating a local search behavior. Finally, by pairing optogenetic activation of heat-sensing cells to the flies presence near visual landmarks of specific shapes, we elicit selective learned avoidance of landmarks associated with aversive \"virtual heat\". These head-fixed paradigms set the stage for an interrogation of fly brain circuitry underlying flexible navigation in complex visual environments.

animal behavior and cognition↗