@article{19076,
  abstract     = {For accurate perception and motor control, an animal must distinguish between sensory experiences elicited by external stimuli and those elicited by its own actions. The diversity of behaviors and their complex influences on the senses make this distinction challenging. Here, we uncover an action–cue hub that coordinates motor commands with visual processing in the brain’s first visual relay. We show that the ventral lateral geniculate nucleus (vLGN) acts as a corollary discharge center, integrating visual translational optic flow signals with motor copies from saccades, locomotion and pupil dynamics. The vLGN relays these signals to correct action-specific visual distortions and to refine perception, as shown for the superior colliculus and in a depth-estimation task. Simultaneously, brain-wide vLGN projections drive corrective actions necessary for accurate visuomotor control. Our results reveal an extended corollary discharge architecture that refines early visual transformations and coordinates actions via a distributed hub-and-spoke network to enable visual perception during action.},
  author       = {Vega Zuniga, Tomas A and Sumser, Anton L and Symonova, Olga and Koppensteiner, Peter and Schmidt, Florian and Jösch, Maximilian A},
  issn         = {1546-1726},
  journal      = {Nature Neuroscience},
  publisher    = {Springer Nature},
  title        = {{A thalamic hub-and-spoke network enables visual perception during action by coordinating visuomotor dynamics}},
  doi          = {10.1038/s41593-025-01874-w},
  volume       = {28},
  year         = {2025},
}

@misc{18579,
  abstract     = {Electrophysiological, calcium two-photon recordings and behavioral data for Vega-Zuniga et al.  Relevant information can be found in the 'README.txt' files. },
  author       = {Vega Zuniga, Tomas A and Sumser, Anton L and Symonova, Olga and Koppensteiner, Peter and Schmidt, Florian and Jösch, Maximilian A},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{A thalamic hub-and-spoke network enables visual perception during action by coordinating visuomotor dynamics}},
  doi          = {10.15479/AT:ISTA:18579},
  year         = {2024},
}

@misc{15385,
  abstract     = {Relevant information about the data can be found in the 'Readme_Data.txt' file. 
A previous version of the publication can be found on BioRxiv: https://www.biorxiv.org/content/10.1101/2022.10.11.511691v4
and published in Plos Biology (2024)},
  author       = {Burnett, Laura and Koppensteiner, Peter and Symonova, Olga and Masson, Tomas and Vega Zuniga, Tomas A and Contreras, Ximena and Rülicke, Thomas and Shigemoto, Ryuichi and Novarino, Gaia and Jösch, Maximilian A},
  keywords     = {ASD, periaqueductal gray, perception, behavior, potassium channels},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Shared behavioural impairments in visual perception and place avoidance across different autism models are driven by periaqueductal grey hypoexcitability in Setd5 haploinsufficient mice}},
  doi          = {10.15479/AT:ISTA:15385},
  year         = {2024},
}

@article{17142,
  abstract     = {Despite the diverse genetic origins of autism spectrum disorders (ASDs), affected individuals share strikingly similar and correlated behavioural traits that include perceptual and sensory processing challenges. Notably, the severity of these sensory symptoms is often predictive of the expression of other autistic traits. However, the origin of these perceptual deficits remains largely elusive. Here, we show a recurrent impairment in visual threat perception that is similarly impaired in 3 independent mouse models of ASD with different molecular aetiologies. Interestingly, this deficit is associated with reduced avoidance of threatening environments—a nonperceptual trait. Focusing on a common cause of ASDs, the Setd5 gene mutation, we define the molecular mechanism. We show that the perceptual impairment is caused by a potassium channel (Kv1)-mediated hypoexcitability in a subcortical node essential for the initiation of escape responses, the dorsal periaqueductal grey (dPAG). Targeted pharmacological Kv1 blockade rescued both perceptual and place avoidance deficits, causally linking seemingly unrelated trait deficits to the dPAG. Furthermore, we show that different molecular mechanisms converge on similar behavioural phenotypes by demonstrating that the autism models Cul3 and Ptchd1, despite having similar behavioural phenotypes, differ in their functional and molecular alteration. Our findings reveal a link between rapid perception controlled by subcortical pathways and appropriate learned interactions with the environment and define a nondevelopmental source of such deficits in ASD.},
  author       = {Burnett, Laura and Koppensteiner, Peter and Symonova, Olga and Masson, Tomas and Vega Zuniga, Tomas A and Contreras, Ximena and Rülicke, Thomas and Shigemoto, Ryuichi and Novarino, Gaia and Jösch, Maximilian A},
  issn         = {1545-7885},
  journal      = {PLoS Biology},
  publisher    = {Public Library of Science},
  title        = {{Shared behavioural impairments in visual perception and place avoidance across different autism models are driven by periaqueductal grey hypoexcitability in Setd5 haploinsufficient mice}},
  doi          = {10.1371/journal.pbio.3002668},
  volume       = {22},
  year         = {2024},
}

@misc{17488,
  abstract     = {Behavioural data for Pokusaeva, Satapathy et al. Relevant information can be found in the 'README.txt' file.},
  author       = {Satapathy, Roshan K and Jösch, Maximilian A and Symonova, Olga and Pokusaeva, Victoria},
  keywords     = {drosophila, behaviour, locomotion, gap junctions},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Bilateral interactions of optic-flow sensitive neurons coordinate course control in flies}},
  doi          = {10.15479/AT:ISTA:17488},
  year         = {2024},
}

@article{18444,
  abstract     = {Animals rely on compensatory actions to maintain stability and navigate their environment efficiently. These actions depend on global visual motion cues known as optic-flow. While the optomotor response has been the traditional focus for studying optic-flow compensation in insects, its simplicity has been insufficient to determine the role of the intricate optic-flow processing network involved in visual course control. Here, we reveal a series of course control behaviours in Drosophila and link them to specific neural circuits. We show that bilateral electrical coupling of optic-flow-sensitive neurons in the fly’s lobula plate are required for a proper course control. This electrical interaction works alongside chemical synapses within the HS-H2 network to control the dynamics and direction of turning behaviours. Our findings reveal how insects use bilateral motion cues for navigation, assigning a new functional significance to the HS-H2 network and suggesting a previously unknown role for gap junctions in non-linear operations.},
  author       = {Pokusaeva, Victoria and Satapathy, Roshan K and Symonova, Olga and Jösch, Maximilian A},
  issn         = {2041-1723},
  journal      = {Nature Communications},
  publisher    = {Springer Nature},
  title        = {{Bilateral interactions of optic-flow sensitive neurons coordinate course control in flies}},
  doi          = {10.1038/s41467-024-53173-w},
  volume       = {15},
  year         = {2024},
}

@article{12349,
  abstract     = {Statistics of natural scenes are not uniform - their structure varies dramatically from ground to sky. It remains unknown whether these non-uniformities are reflected in the large-scale organization of the early visual system and what benefits such adaptations would confer. Here, by relying on the efficient coding hypothesis, we predict that changes in the structure of receptive fields across visual space increase the efficiency of sensory coding. We show experimentally that, in agreement with our predictions, receptive fields of retinal ganglion cells change their shape along the dorsoventral retinal axis, with a marked surround asymmetry at the visual horizon. Our work demonstrates that, according to principles of efficient coding, the panoramic structure of natural scenes is exploited by the retina across space and cell-types.},
  author       = {Gupta, Divyansh and Mlynarski, Wiktor F and Sumser, Anton L and Symonova, Olga and Svaton, Jan and Jösch, Maximilian A},
  issn         = {1546-1726},
  journal      = {Nature Neuroscience},
  pages        = {606--614},
  publisher    = {Springer Nature},
  title        = {{Panoramic visual statistics shape retina-wide organization of receptive fields}},
  doi          = {10.1038/s41593-023-01280-0},
  volume       = {26},
  year         = {2023},
}

@article{1793,
  abstract     = {We present a software platform for reconstructing and analyzing the growth of a plant root system from a time-series of 3D voxelized shapes. It aligns the shapes with each other, constructs a geometric graph representation together with the function that records the time of growth, and organizes the branches into a hierarchy that reflects the order of creation. The software includes the automatic computation of structural and dynamic traits for each root in the system enabling the quantification of growth on fine-scale. These are important advances in plant phenotyping with applications to the study of genetic and environmental influences on growth.},
  author       = {Symonova, Olga and Topp, Christopher and Edelsbrunner, Herbert},
  journal      = {PLoS One},
  number       = {6},
  publisher    = {Public Library of Science},
  title        = {{DynamicRoots: A software platform for the reconstruction and analysis of growing plant roots}},
  doi          = {10.1371/journal.pone.0127657},
  volume       = {10},
  year         = {2015},
}

@misc{9737,
  author       = {Symonova, Olga and Topp, Christopher and Edelsbrunner, Herbert},
  publisher    = {Public Library of Science},
  title        = {{Root traits computed by DynamicRoots for the maize root shown in fig 2}},
  doi          = {10.1371/journal.pone.0127657.s001},
  year         = {2015},
}

@article{2822,
  abstract     = {Identification of genes that control root system architecture in crop plants requires innovations that enable high-throughput and accurate measurements of root system architecture through time. We demonstrate the ability of a semiautomated 3D in vivo imaging and digital phenotyping pipeline to interrogate the quantitative genetic basis of root system growth in a rice biparental mapping population, Bala x Azucena. We phenotyped >1,400 3D root models and >57,000 2D images for a suite of 25 traits that quantified the distribution, shape, extent of exploration, and the intrinsic size of root networks at days 12, 14, and 16 of growth in a gellan gum medium. From these data we identified 89 quantitative trait loci, some of which correspond to those found previously in soil-grown plants, and provide evidence for genetic tradeoffs in root growth allocations, such as between the extent and thoroughness of exploration. We also developed a multivariate method for generating and mapping central root architecture phenotypes and used it to identify five major quantitative trait loci (r2 = 24-37%), two of which were not identified by our univariate analysis. Our imaging and analytical platform provides a means to identify genes with high potential for improving root traits and agronomic qualities of crops.},
  author       = {Topp, Christopher and Iyer Pascuzzi, Anjali and Anderson, Jill and Lee, Cheng and Zurek, Paul and Symonova, Olga and Zheng, Ying and Bucksch, Alexander and Mileyko, Yuriy and Galkovskyi, Taras and Moore, Brad and Harer, John and Edelsbrunner, Herbert and Mitchell Olds, Thomas and Weitz, Joshua and Benfey, Philip},
  journal      = {PNAS},
  number       = {18},
  pages        = {E1695 -- E1704},
  publisher    = {National Academy of Sciences},
  title        = {{3D phenotyping and quantitative trait locus mapping identify core regions of the rice genome controlling root architecture}},
  doi          = {10.1073/pnas.1304354110},
  volume       = {110},
  year         = {2013},
}

@inproceedings{2903,
  abstract     = {In order to enjoy a digital version of the Jordan Curve Theorem, it is common to use the closed topology for the foreground and the open topology for the background of a 2-dimensional binary image. In this paper, we introduce a single topology that enjoys this theorem for all thresholds decomposing a real-valued image into foreground and background. This topology is easy to construct and it generalizes to n-dimensional images.},
  author       = {Edelsbrunner, Herbert and Symonova, Olga},
  location     = {New Brunswick, NJ, USA },
  pages        = {41 -- 48},
  publisher    = {IEEE},
  title        = {{The adaptive topology of a digital image}},
  doi          = {10.1109/ISVD.2012.11},
  year         = {2012},
}

@article{492,
  abstract     = {Background: Characterizing root system architecture (RSA) is essential to understanding the development and function of vascular plants. Identifying RSA-associated genes also represents an underexplored opportunity for crop improvement. Software tools are needed to accelerate the pace at which quantitative traits of RSA are estimated from images of root networks.Results: We have developed GiA Roots (General Image Analysis of Roots), a semi-automated software tool designed specifically for the high-throughput analysis of root system images. GiA Roots includes user-assisted algorithms to distinguish root from background and a fully automated pipeline that extracts dozens of root system phenotypes. Quantitative information on each phenotype, along with intermediate steps for full reproducibility, is returned to the end-user for downstream analysis. GiA Roots has a GUI front end and a command-line interface for interweaving the software into large-scale workflows. GiA Roots can also be extended to estimate novel phenotypes specified by the end-user.Conclusions: We demonstrate the use of GiA Roots on a set of 2393 images of rice roots representing 12 genotypes from the species Oryza sativa. We validate trait measurements against prior analyses of this image set that demonstrated that RSA traits are likely heritable and associated with genotypic differences. Moreover, we demonstrate that GiA Roots is extensible and an end-user can add functionality so that GiA Roots can estimate novel RSA traits. In summary, we show that the software can function as an efficient tool as part of a workflow to move from large numbers of root images to downstream analysis.},
  author       = {Galkovskyi, Taras and Mileyko, Yuriy and Bucksch, Alexander and Moore, Brad and Symonova, Olga and Price, Charles and Topp, Chrostopher and Iyer Pascuzzi, Anjali and Zurek, Paul and Fang, Suqin and Harer, John and Benfey, Philip and Weitz, Joshua},
  journal      = {BMC Plant Biology},
  publisher    = {BioMed Central},
  title        = {{GiA Roots: Software for the high throughput analysis of plant root system architecture}},
  doi          = {10.1186/1471-2229-12-116},
  volume       = {12},
  year         = {2012},
}