Institut für Neuroinformatik

Our research in autonomous robotics is organized around the problems posed by robotic assistants, that is, partially autonomous robot systems that interact with human operators with whom they share a natural environment. Robotic assistants need an array of sensor systems and powerful perceptual algorithms so that they may acquire enough information about the scene to interpret user commands and autonomously perform actions such as orienting toward objects, retrieving them, possibly manipulating them and handing them over to the human operator. Based on analogies with how nervous systems generate motor behavior and simple forms of cognition, we use attractor dynamics and their instabilities at three levels to generate movement trajectories, to generate goal-directed sequences of behaviors, and to derive task-relevant perceptual representations that support goal-directed behavior.

Ruhr-Universität Bochum
Institut für Neuroinformatik
Universitätsstraße 150

D-44801 Bochum, Germany

+49-234-32-38967

+49-234-32-14210

sekretariat@ini.rub.de

External Homepage

Lab Leader

Prof. Dr. Gregor Schöner

Researchers

Raul Grieben, M.Sc.

Dr. Jonas Lins

Dr.-Ing. Mathis Richter

Daniel Sabinasz, M.Sc.

Jan Tekülve, M.Sc.

    2023

  • Neural dynamic foundations of a theory of higher cognition: the case of grounding nested phrases
    Sabinasz, D., Richter, M., & Schöner, G.
    Cognitive Neurodynamics
    reprint
  • Dynamical Systems Approaches to Cognition
    Schöner, G.
    In Sun, Ron (Ed.), The Cambridge Handbook of Computational Cognitive Sciences (2nd ed.) Cambridge University Press
    proofs

    • 2022

  • A Neural Dynamic Model Perceptually Grounds Nested Noun Phrases
    Sabinasz, D., & Schöner, G.
    Topics in Cognitive Science
    A Neural Dynamic Model Perceptually Grounds Nested Noun Phrases
  • Habituation and Dishabituation in Motor Behavior: Experiment and Neural Dynamic Model
    Aerdker, S., Feng, J., & Schöner, G.
    Frontiers in Psychology, 13, 717669
    preprint
  • Bridging DFT and DNNs: A neural dynamic process model of scene representation, guided visual search and scene grammar in natural scenes
    Grieben, R., & Schöner, G.
    In J. Culbertson, Perfors, A., Rabagliati, H., & Ramenzoni, V. (Eds.), Proceedings of the 44th Annual Conference of the Cognitive Science Society
    preprint
  • A Perceptually Grounded Neural Dynamic Architecture Establishes Analogy Between Visual Object Pairs
    Hesse, M., Sabinasz, D., & Schöner, G.
    In J. Culbertson, Perfors, A., Rabagliati, H., & Ramenzoni, V. (Eds.), Proceedings of the 44th Annual Conference of the Cognitive Science Society
    A Perceptually Grounded Neural Dynamic Architecture Establishes Analogy Between Visual Object Pairs
  • A Neural Dynamic Model Perceptually Grounds Nested Noun Phrases
    Sabinasz, D., & Schöner, G.
    In J. Culbertson, Perfors, A., Rabagliati, H., & Ramenzoni, V. (Eds.), Proceedings of the 44th Annual Conference of the Cognitive Science Society
    A Neural Dynamic Model Perceptually Grounds Nested Noun Phrases

    • 2021

  • How do neural processes give rise to cognition? Simultaneously predicting brain and behavior with a dynamic model of visual working memory
    Buss, A. T., Magnotta, V. A., Penny, W., Schöner, G., Huppert, T. J., & Spencer, J. P.
    Psychological review, 128(2), 362–395
    preprint
  • A neural dynamic process model of combined bottom-up and top-down guidance in triple conjunction visual search
    Grieben, R., & Schöner, G.
    In T. Fitch, Lamm, C., Leder, H., & Teßmar-Raible, K. (Eds.), Proceedings of the 43rd Annual Conference of the Cognitive Science Society
    preprint
  • A neural dynamic model for the perceptual grounding of spatial and movement relations
    Richter, M., Lins, J., & Schöner, G.
    Cognitive Science, 45(10), e13045
    preprint

    • 2020

  • Scene memory and spatial inhibition in visual search: A neural dynamic process model and new experimental evidence
    Grieben, R., Tekülve, J., Zibner, S. K. U., Lins, J., Schneegans, S., & Schöner, G.
    Attention, Perception, & Psychophysics
    SpringerLink (Open Access)
  • Grounding Spatial Language in Perception by Combining Concepts in a Neural Dynamic Architecture
    Sabinasz, D., Richter, M., Lins, J., & Schöner, G.
    In S. Denison, Mack, M., Xu, Y., & Armstrong, B. C. (Eds.), Proceedings of the 42nd Annual Conference of the Cognitive Science Society (pp. 620–626) Cognitive Science Society
    reprint
  • A neural dynamic network drives an intentional agent that autonomously learns beliefs in continuous time
    Tekülve, J., & Schöner, G.
    IEEE Transactions on Cognitive and Developmental Systems, 1–12
    preprint

    • 2019

  • The Dynamics of Neural Populations Capture the Laws of the Mind
    Schöner, G.
    Topics in Cognitive Science
    reprint
  • Computer mouse tracking reveals motor signatures in a cognitive task of spatial language grounding
    Lins, J., & Schöner, G.
    Attention, Perception, and Psychophysics, 81(7), 2424–2460
    reprint
  • A process account of the uncontrolled manifold structure of joint space variance in pointing movements
    Martin, V., Reimann, H., & Schöner, G.
    Biological Cybernetics, 113(3), 293–307
    reprint
  • Reaching for objects : a neural process account in a developmental perspective
    Schöner, G., Tekülve, J., & Zibner, S.
    In D. Corbetta & Santello, M. (Eds.), Reach-to-Grasp Behavior: Brain, Behavior and Modelling across the Life Span (pp. 281–318) Taylor & Francis
    preprint
  • Autonomous Sequence Generation for a Neural Dynamic Robot: Scene Perception, Serial Order, and Object-Oriented Movement
    Tekülve, J., Fois, A., Sandamirskaya, Y., & Schöner, G.
    Frontiers in Neurorobotics, 13, 95
    Online Article
  • Neural dynamic concepts for intentional systems
    Tekülve, J., & Schöner, G.
    In 41th Annual Conference of the Cognitive Science Society (CogSci 2019)
    article (pdf)
  • Autonomously learning beliefs is facilitated by a neural dynamic network driving an intentional agent
    Tekülve, J., & Schöner, G.
    In Development and Learning and Epigenetic Robotics (ICDL-EpiRob), 2019 Joint IEEE International Conference on (pp. 143–150) IEEE
    article (pdf)

    • 2018

  • How infants′ reaches reveal principles of sensorimotor decision making
    Dineva, E., & Schöner, G.
    Connection Science, 30(1), 53–80
    reprint
  • Sequences of discrete attentional shifts emerge from a neural dynamic architecture for conjunctive visual search that operates in continuous time
    Grieben, R., Tekülve, J., Zibner, S. K. U., Schneegans, S., & Schöner, G.
    In T. T. Rogers, Rau, M., Zhu, X., & Kalish, C. W. (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society
  • Anticipatory coarticulation in non-speeded arm movements can be motor-equivalent, carry-over coarticulation always is
    Hansen, E., Grimme, B., Reimann, H., & Schöner, G.
    Experimental Brain Research
    reprint
  • A Neural Dynamic Architecture That Autonomously Builds Mental Models
    Kounatidou, P., Richter, M., & Schöner, G.
    In Proceedings of the 40th Annual Conference of the Cognitive Science Society (pp. 1–6)
    reprint

    • 2017

  • A Neural Dynamic Architecture for Reaching and Grasping Integrates Perception and Movement Generation and Enables On-Line Updating
    Knips, G., Zibner, S. K. U., Reimann, H., & Schöner, G.
    Frontiers in Neurorobotics, 11(March), 9:1–14
    reprint
  • Mouse Tracking Shows Attraction to Alternative Targets While Grounding Spatial Relations
    Lins, J., & Schöner, G.
    In Proceedings of the 39th Annual Conference of the Cognitive Science Society (to appear) Austin, TX: Cognitive Science Society
  • A Neural-Dynamic Architecture for Concurrent Estimation of Object Pose and Identity
    Lomp, O., Faubel, C., & Schöner, G.
    Frontiers in Neurorobotics, 11(April), 23
    reprint
  • A multi-joint model of quiet, upright stance accounts for the “uncontrolled manifold” structure of joint variance
    Reimann, H., & Schöner, G.
    Biological Cybernetics, 111(5-6), 389–403
    reprint
  • A neural dynamic model generates descriptions of object-oriented actions
    Richter, M., Lins, J., & Schöner, G.
    Topics in Cognitive Science, 9(1), 35–47
    A neural dynamic model generates descriptions of object-oriented actions (PDF)
  • Reaching for objects : a neural process account in a developmental perspective
    Schöner, G., Tekülve, J., & Zibner, S.
    In D. Corbetta & Santello, M. (Eds.), The selection and production of goal-directed behaviors: Neural correlates, development, learning, and modeling of reach-to-grasp movements Taylor & Francis
    preprint
  • Dynamic Neural Fields with Intrinsic Plasticity
    Strub, C., Schöner, G., Wörgötter, F., & Sandamirskaya, Y.
    Frontiers in Computational Neuroscience, 11(August), 74
    reprint

    • 2016

  • Nonlinear dynamics in the perceptual grouping of connected surfaces
    Hock, H. S., & Schöner, G.
    Vision Research, 126, 80–96
    reprint
  • Developing Dynamic Field Theory Architectures for Embodied Cognitive Systems with cedar
    Lomp, O., Richter, M., Zibner, S. K. U., & Schöner, G.
    Frontiers in Neurorobotics, 10(November), 14
    reprint
  • Coordination of muscle torques stabilizes upright standing posture: an UCM analysis
    Park, E., Reimann, H., & Schöner, G.
    Experimental Brain Research, 234(6), 1757–1767
    preprint
  • Separating Timing, Movement Conditions and Individual Differences in the Analysis of Human Movement
    Raket, L. L., Grimme, B., Schöner, G., Igel, C., & Markussen, B.
    PLoS Computational Biology, 12(9), 1–27
    reprint
  • Temporal asymmetry in dark-bright processing initiates propagating activity across primary visual cortex
    Rekauzke, S., Nortmann, N., Staadt, R., Hock, H. S., Schöner, G., & Jancke, D.
    J Neurosci, 36(6), 1902–1913
    pdf
  • A neural dynamic model parses object-oriented actions
    Richter, M., Lins, J., & Schöner, G.
    In A. Papafragou, Grodner, D., Mirman, D., & Trueswell, J. C. (Eds.), Proceedings of the 38th Annual Conference of the Cognitive Science Society (pp. 1931–1936) Austin, TX: Cognitive Science Society
    pdf
  • A neural process model of learning to sequentially organize and activate pre-reaches
    Tekülve, J., Zibner, S. K. U., & Schöner, G.
    In Development and Learning and Epigenetic Robotics (ICDL-Epirob), 2016 Joint IEEE International Conferences on
    A neural process model of learning to sequentially organize and activate pre-reaches

    • 2015

  • Carry-over coarticulation in joint angles
    Hansen, E., Grimme, B., Reimann, H., & Schöner, G.
    Experimental Brain Research, 233(9), 2555–2569
    reprint
  • Parsing of action sequences: A neural dynamics approach
    Lobato, D., Sandamirskaya, Y., Richter, M., & Schöner, G.
    Paladyn, Journal of Behavioral Robotics, 6(1), 119–135
    reprint
  • Learning the condition of satisfaction of an elementary behavior in dynamic field theory
    Luciw, M., Kazerounian, S., Lahkman, K., Richter, M., & Sandamirskaya, Y.
    Paladyn, Journal of Behavioral Robotics, 6(1), 180–190
    pdf
  • Task-specific stability of abundant systems: Structure of variance and motor equivalence
    Mattos, D., Schöner, G., Zatsiorsky, V. M., & Latash, M. L.
    Neuroscience, 310, 600–615
    reprint
  • Motor equivalence during multi-finger accurate force production
    Mattos, D., Schöner, G., Zatsiorsky, V. M., & Latash, M. L.
    Experimental Brain Research, 233, 487–502
    pdf
  • The Dynamics of Neural Activation Variables
    Reimann, H., Lins, J., & Schöner, G.
    Paladyn, Journal of Behavioral Robotics, 6(1), 57–70
    pdf
  • The Neural Dynamics of Goal-Directed Arm Movements: A Developmental Perspective
    Zibner, S. K. U., Tekülve, J., & Schöner, G.
    In Development and Learning and Epigenetic Robotics (ICDL-Epirob), 2015 Joint IEEE International Conferences on (pp. 154–161)
    pdf
  • The Sequential Organization of Movement is Critical to the Development of Reaching: A Neural Dynamics Account
    Zibner, S. K. U., Tekülve, J., & Schöner, G.
    In Development and Learning and Epigenetic Robotics (ICDL-Epirob), 2015 Joint IEEE International Conferences on (pp. 39–46)
    pdf

    • 2014

  • A comparison between reactive potential fields and Attractor Dynamics
    Hernandes, A. C., Guerrero, H. B., Becker, M., Jokeit, J. -S., & Schöner, G.
    Circuits and Systems (CWCAS), 2014 IEEE 5th Colombian Workshop on
    reprint
  • A neural dynamics architecture for grasping that integrates perception and movement generation and enables on-line updating
    Knips, G., Zibner, S. K. U., Reimann, H., Popova, I., & Schöner, G.
    In International Conference on Intelligent Robots and Systems (IROS) (pp. 646–653)
  • Reaching and grasping novel objects: Using neural dynamics to integrate and organize scene and object perception with movement generation
    Knips, G., Zibner, S. K. U., Reimann, H., Popova, I., & Schöner, G.
    In International Conference on Development and Learning and on Epigenetic Robotics (ICDL-EPIROB) (pp. 416–423)
  • Neural Fields
    Lins, J., & Schöner, G.
    In S. Coombes, beim Graben, P., Potthast, R., & , J. W. (Eds.) (pp. 319–339) Springer Berlin Heidelberg
    pdf
  • Instance-based object recognition with simultaneous pose estimation using keypoint maps and neural dynamics
    Lomp, O., Terzić, K., Faubel, C., du Buf, J. M. H., & Schöner, G.
    In International Conference on Artificial Neural Networks (pp. 451–458) Springer
  • Reinforcement-Driven Shaping of Sequence Learning in Neural Dynamics
    Luciw, M., Kazerounian, S., Sandamirskaya, Y., Schöner, G., & Schmidhuber, J.
    In Simulation of Adaptive Behavior, SAB
    pdf
  • Change occurs when body meets environment: A review of the embodied nature of development
    Maruyama, S., Dineva, E., Spencer, J. P., & Schöner, G.
    Japanese Psychological Research, 56, 385–401
    pdf
  • Contrasting accounts of direction and shape perception in short-range motion: Counterchange compared with motion energy detection.
    Norman, J., Hock, H., & Schoner, G.
    Attention, perception & psychophysics, 76, 1350–70
    pdf
  • A neural dynamics to organize timed movement : Demonstration in a robot ball bouncing task
    Oubbati, F., Richter, M., & Schöner, G.
    In 4th International Conference on Development and Learning and on Epigenetic Robotics (pp. 291–298) Palazzo Ducale, Genoa, Italy
    reprint
  • Autonomous Neural Dynamics to Test Hypotheses in a Model of Spatial Language
    Richter, M., Lins, J., Schneegans, S., Sandamirskaya, Y., & Schöner, G.
    In P. Bello, Guarini, M., McShane, M., & Scassellati, B. (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society (pp. 2847–2852) Austin, TX: Cognitive Science Society
    pdf
  • A neural dynamic architecture resolves phrases about spatial relations in visual scenes
    Richter, M., Lins, J., Schneegans, S., & Schöner, G.
    In 24th International Conference on Artificial Neural Networks (ICANN) (pp. 201–208) Heidelberg, Germany: Springer
    pdf
  • Dynamic interactions between visual working memory and saccade target selection
    Schneegans, S., Spencer, J. P., Schöner, G., Hwang, S., & Hollingworth, A.
    Journal of vision, 14(11), 9
    supplementary material pdf
  • Use of the Uncontrolled Manifold (UCM) Approach to Understand MotorVariability, Motor Equivalence, and Self-motion
    Scholz, J. P., & Schöner, G.
    In M. F. Levin (Ed.), Progress in Motor Control (Vol. 826, p. Chapter 7) Springer International Publishing
    preprint
  • Embodied Cognition, Neural Field Models of
    Schöner, G.
    In Encyclopedia of Computational Neuroscience (pp. 1084–1092) Springer Berlin Heidelberg
    preprint
  • Dynamical Systems Thinking: From Metaphor to Neural Theory
    Schöner, G.
    In P. C. M. Molenaar, Lerner, R. M., & Newell, K. M. (Eds.), Handbook of Developmental Systems Theory and Methodology (pp. 188–219) New York, New York, USA: Guilford Publications
    preprint
  • Coordination Dynamics
    Schöner, G., & Nowak, E.
    In D. Jaeger & Jung, R. (Eds.), Encyclopedia of Computational Neuroscience (pp. 1–3) New York, NY: Springer New York
    preprint

    • 2013

  • Autonomous robot hitting task using dynamical system approach
    Oubbati, F., Richter, M., & Schöner, G.
    In IEEE International Conference on Systems, Man, and Cybernetics (pp. 4042–4047) IEEE
    pdf
  • Autonomous Reinforcement of Behavioral Sequences in Neural Dynamics
    Kazerounian, S., Luciw, M., Richter, M., & Sandamirskaya, Y.
    In International Joint Conference on Neural Networks (IJCNN)
    pdf
  • A software framework for cognition, embodiment, dynamics, and autonomy in robotics: cedar
    Lomp, O., Zibner, S. K. U., Richter, M., Ranó, I., & Schöner, G.
    In International Conference on Artificial Neural Networks (pp. 475–482) Springer
    pdf
  • Learning the Perceptual Conditions of Satisfaction of Elementary Behaviors
    Luciw, M., Kazerounian, S., Lakhmann, K., Richter, M., & Sandamirskaya, Y.
    In Robotics: Science and Systems (RSS), Workshop "Active Learning in Robotics: Exploration, Curiosity, and Interaction"
    pdf
  • Using Dynamic Field Theory to Extend the Embodiment Stance toward Higher Cognition
    Sandamirskaya, Y., Zibner, S. K. U., Schneegans, S., & Schöner, G.
    New Ideas in Psychology, 31(3), 322–339
    pdf

    • 2012

  • Autonomous reinforcement of behavioral sequences in neural dynamics
    Kazerounian, S., Luciw, M., Sandamirskaya, Y., Richter, M., Schmidhuber, J., & Schöner, G.
    In IEEE International Conference on Development and Learning and Epigenetic Robotics (Vol. 1, pp. 1–2) Ieee
    pdf
  • Naturalistic arm movements during obstacle avoidance in 3D and the identification of movement primitives.
    Grimme, B., Lipinski, J., & Schöner, G.
    Experimental brain research, 222(3), 185–200
    pdf
  • A neurobehavioral model of flexible spatial language behaviors
    Lipinski, J., Schneegans, S., Sandamirskaya, Y., Spencer, J. P., & Schöner, G.
    Journal of experimental psychology. Learning, memory, and cognition, 38, 1490–1511
    pdf
  • A Dynamic Field Architecture for the Generation of Hierarchically Organized Sequences
    Duran, B., Sandamirskaya, Y., & Schöner, G.
    In A. E. P. Villa, Duch, W., Érdi, P., Masulli, F., & Palm, G. (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2012 (Vol. 7552, pp. 25–32) Springer Berlin Heidelberg
    pdf
  • Sensorimotor Learning Biases Choice Behavior: A Learning Neural Field Model for Decision Making
    Klaes, C., Schneegans, S., Schöner, G., & Gail, A.
    PLoS computational biology, 8(11), e1002774
    supplementary material pdf
  • The Function and Fallibility of Visual Feature Integration: A Dynamic Neural Field Model of Illusory Conjunctions
    Lins, J., Schneegans, S., Spencer, J., & Schöner, G.
    Frontiers in Computational Neuroscience, (128)
    pdf
  • A Neuro-Behavioral Model of Flexible Spatial Language Behaviors
    Lipinski, J., Schneegans, S., Sandamirskaya, Y., Spencer, J. P., & Schöner, G.
    Journal of Experimental Psychology: Learning, Memory and Cognition., 38(6), 1490–1511
    pdf
  • Functional synergies underlying control of upright posture during changes in head orientation
    Park, E., Schöner, G., & Scholz, J. P.
    PLoS ONE, 7(8), 1–12
    pdf
  • Neural dynamics for behavioral organization of an embodied agent.
    Richter, M., & Sandamirskaya, Y.
    In 16th International Conference on Cognitive and Neural Systems (ICCNS)
  • Organization of robotic behavior with dynamic field theory.
    Richter, M., Sandamirskaya, Y., & G, S.
    In 5th International Conference on Cognitive Systems (CogSyst)
  • A robotic architecture for action selection and behavioral organization inspired by human cognition
    Richter, M., Sandamirskaya, Y., & Schöner, G.
    In IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS
    pdf
  • A neural mechanism for coordinate transformation predicts pre-saccadic remapping
    Schneegans, S., & Schöner, G.
    Biological cybernetics, 106(2), 89–109
    pdf
  • How visual information links to multijoint coordination during quiet standing
    Scholz, J. P., Park, E., Jeka, J. J., Schöner, G., & Kiemel, T.
    Experimental Brain Research, 222, 229–239
    pdf
  • A neural-dynamic architecture for flexible spatial language: intrinsic frames, the term “between”, and autonomy
    van Hengel, U., Sandamirskaya, Y., Schneegans, S., & Schöner, G.
    In 21st IEEE International Symposium on Robot and Human Interactive Communication (Ro-Man) 2012 (pp. 150–157)
    pdf

    • 2011

  • The temporal dynamics of global-to-local feedback in the formation of hierarchical motion patterns: psychophysics and computational simulations.
    Hock, H. S., Schöner, G., Brownlow, S., & Taler, D.
    Attention, perception & psychophysics, 73(4), 1171–94
    pdf
  • Limb versus speech motor control: a conceptual review.
    Grimme, B., Fuchs, S., Perrier, P., & Schöner, G.
    Motor control, 15(1), 5–33
    pdf
  • Autonomous movement generation for manipulators with multiple simultaneous constraints using the attractor dynamics approach
    Reimann, H., Iossifidis, I., & Schöner, G.
    In 2011 IEEE International Conference on Robotics and Automation, ICRA2011
  • A neural-dynamic architecture for behavioral organization of an embodied agent
    Sandamirskaya, Y., Richter, M., & Schöner, G.
    In IEEE International Conference on Development and Learning and on Epigenetic Robotics (ICDL EPIROB 2011) (pp. 1–7)
    pdf
  • Neural dynamics of sequence generation and behavioral organization
    Sandamirskaya, Y., Richter, M., & Schöner, G.
    In Front. Comput. Neurosci.: Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting, BC11
  • Motor equivalence and self-motion induced by different movement speeds
    Scholz, J. P., Dwight-Higgin, T., Lynch, J. E., Tseng, Y. -W., Martin, V., & Schöner, G.
    Experimental Brain Research, 209(3), 319–332
    pdf
  • A representation of projective and topological spatial terms within a neurodynamic framework for spatial language behaviors
    van Hengel, U., Schneegans, S., , Y. S., & Schöner, G.
    In Front. Comput. Neurosci.: Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting, BC11
  • Dynamic Neural Fields as Building Blocks of a Cortex-Inspired Architecture for Robotic Scene Representation
    Zibner, S. K. U., Faubel, C., Iossifidis, I., & Schöner, G.
    IEEE Transactions on Autonomous Mental Development, 3(1), 74–91
    pdf
  • Making a robotic scene representation accessible to feature and label queries
    Zibner, S. K. U., Faubel, C., & Schöner, G.
    In Proceedings of the First Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics (ICDL EPIROB 2011)

    • 2010

  • Natural human-robot interaction through spatial language: a dynamic neural fields approach
    Sandamirskaya, Y., Lipinski, J., Iossifidis, I., & Schöner, G.
    In 19th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN (pp. 600–607) Viareggio, Italy
  • Motor Abundance Contributes to Resolving Multiple Kinematic Task Constraints
    Gera, G., Freitas, S., Latash, M., Monahan, K., Schöner, G., & Scholz, J.
    Motor Control, 14, 83–115
    pdf
  • Measuring Perceptual Hysteresis with the Modified Method of Limits: Dynamics at the Threshold
    Hock, H. S., & Schöner, G.
    Seeing and Perceiving, 23, 173–195
    pdf
  • Motor control theories and their applications
    Latash, M., Levin, M. F., Scholz, J. P., & Schöner, G.
    Medicina (Kaunas), 29(6), 997–1003
    pdf
  • Natural human-robot interaction through spatial language: a dynamic neural fields approach
    Sandamirskaya, Y., Lipinski, J., Iossifidis, I., & Schöner, G.
    In 19th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN (pp. 600–607) Viareggio, Italy
    pdf
  • An embodied account of serial order: how instabilities drive sequence generation
    Sandamirskaya, Y., & Schöner, G.
    Neural Networks, 23(10), 1164–1179
    pdf
  • Neural dynamics of sequence generation: concepts and robotic demonstrations. A Dynamic Field Theory approach.
    Sandamirskaya, Y., & Schöner, G.
    In Bernstein Conference on Computational Neuroscience, BCCN
  • Serial order in an acting system: a multidimensional dynamic neural fields implementation
    Sandamirskaya, Y., & Schöner, G.
    In Development and Learning, 2010. ICDL 2010. 9th IEEE International Conference on
  • An Embodied Account of Serial Order: How Instabilities Drive Sequence Generation
    Sandamirskaya, Y., & Schöner, G.
    Neural Netw., 23
  • Serial order in an acting system: a multidimensional dynamic neural fields implementation
    Sandamirskaya, Y., & Schöner, G.
    In Development and Learning, 2010. ICDL 2010. 9th IEEE International Conference on
    pdf
  • Scene Representation for Anthropomorphic Robots: A Dynamic Neural Field Approach
    Zibner, S. K. U., Faubel, C., Iossifidis, I., & Schöner, G.
    In ISR / ROBOTIK 2010 Munich, Germany

    • 2009

  • A layered neural architecture for the consolidation, maintenance, and updating of representations in visual working memory.
    Johnson, J. S., Spencer, J. P., & Schöner, G.
    Brain research, 1299, 17–32
    pdf
  • A counterchange mechanism for the perception of motion.
    Hock, H. S., Schöner, G., & Gilroy, L.
    Acta psychologica, 132(1), 1–21
    pdf
  • A dynamic neural field model of visual working memory and change detection.
    Johnson, J. S. J. S., Spencer, J. P., Luck, S. J., & Schöner, G.
    Psychological science, 20(5), 568–577
    pdf
  • A layered neural architecture for the consolidation, maintenance, and updating of representations in visual working memory
    Johnson, J. S., Spencer, J. P., & Schöner, G.
    Brain Research, 1299, 17–32
    pdf
  • Swing it to the Left, Swing it to the Right: Enacting Flexible Spatial Language Using a Neurodynamic Framework
    Lipinski, J., Sandamirskaya, Y., & Schöner, G.
    Cognitive Neurodynamics, 3(4)
    pdf
  • Flexible Spatial Language Behaviors: Developing a Neural Dynamic Theoretical Framework.
    Lipinski, J., Sandamirskaya, Y., & Schöner, G.
    In A. Howes, Peebles, D., & Cooper, R. (Eds.), ICCM
  • Behaviorally Flexible Spatial Communication: Robotic Demonstrations of a Neurodynamic Framework
    Lipinski, J., Sandamirskaya, Y., & Schöner, G.
    In B. Mertsching, Hund, M., & Z., A. (Eds.), KI 2009, Lecture Notes in Artificial Intelligence (Vol. 5803, pp. 257–264) Berlin: Springer-Verlag
  • Flexible Spatial Language Behaviors: Developing a New Dynamic Theoretical Framework
    Lipinski, J., Sandamirskaya, Y., & Schöner, G.
    In CogSci
  • Swing it to the Left, Swing it to the Right: Enacting Flexible Spatial Language Using a Neurodynamic Framework
    Lipinski, J., Sandamirskaya, Y., & Schöner, G.
    Cognitive Neurodynamics, 3(4)
  • An Integrative Framework for Spatial Language and Color: Robotic Demonstrations Using the Dynamic Field Theory.
    Lipinski, J., Sandamirskaya, Y., & Schöner, G.
    In 31th Annual Meeting of the Cognitive Science Society, CogSci 2009 Amstredam, NL
  • An Integrative Framework for Spatial Language and Color: Robotic Demonstrations Using the Dynamic Field Theory.
    Lipinski, J., Sandamirskaya, Y., & Schöner, G.
    In 31th Annual Meeting of the Cognitive Science Society, CogSci 2009 Amstredam, NL
    pdf
  • Behaviorally Flexible Spatial Communication: Robotic Demonstrations of a Neurodynamic Framework
    Lipinski, J., Sandamirskaya, Y., & Schöner, G.
    In B. Mertsching, Hund, M., & Z., A. (Eds.), KI 2009, Lecture Notes in Artificial Intelligence (Vol. 5803, pp. 257–264) Berlin: Springer-Verlag
    pdf
  • Redundancy, self-motion and motor control
    Martin, V., Scholz, J. P., & Schöner, G.
    Neural Computation, 21(5), 1371–1414
    pdf
  • Memorizing and Generating Inhomogeneous Behavioral Sequnces in the Dynamic Field Theory: Concepts and Robotic Demonstrations.
    Sandamirskaya, Y., & Schöner, G.
    In 13th International Conference on Cognitive and Neural Systems, ICCNS
  • Temporal stabilization of discrete movement in variable environments: an attractor dynamics approach
    Tuma, M., Iossifidis, I., & Schöner, G.
    In IEEE International Conference on Robotics and Automation (ICRA) (pp. 863–868)
    pdf

    • 2008

  • Moving to a higher ground: the dynamic field theory and the dynamics of visual cognition
    Johnson, J. S., Spencer, J. P., & Schöner, G.
    New Ideas in Psychology, 26, 227–251
    pdf
  • Dynamic Field Theory of Sequential Action: A Model and its Implementation on an Embodied Agent
    Sandamirskaya, Y., & Schöner, G.
    In ICDL
  • Dynamic Field Theory as a framework for understanding embodied cognition
    Schneegans, S., & Schöner, G.
    In P. Calvo & Gomila, T. (Eds.), Handbook of cognitive science: An embodied approach (pp. 241–271) Amsterdam, Netherlands: Elsevier
    pdf

    • 2006

  • Reference-related inhibition produces enhanced position discrimination and fast repulsion near axes of symmetry.
    Simmering, V. R., Spencer, J. P., & Schöner, G.
    Perception & psychophysics, 68(6), 1027–46
    pdf
  • Dynamic field theory and embodied communication
    Sandamirskaya, Y., & Schöner, G.
    In I. Wachsmuth & Knoblich, G. (Eds.), Modeling communication with robots and virtual humans (pp. 260–278) Springer
  • Moving toward a grand theory of development: In memory of Esther Thelen
    Spencer, J. P., Clearfield, M. W., Corbetta, D., Ulrich, B. D., Buchanan, P., & Schoner, G.
    Child Development, 77, 1521–1538
    pdf
  • The time course of saccadic decision making: Dynamic field theory
    Wilimzig, C., Schneider, S., & Schöner, G.
    Neural Networks, 19(8), 1059–1074
    reprint

    • 2004

  • Shorter latencies for motion trajectories than for flashes in population responses of cat primary visual cortex
    Jancke, D., Erlhagen, W., Schöner, G., & Dinse, H. R.
    The Journal of Physiology, 556(3), 971–982

    • 2003

  • Testing the dynamic field theory: Working memory for locations becomes more spatially precise over development
    Schutte, A. R., Spencer, J. P., & Schöner, G.
    Child Development, 74(5), 1393–1417
    pdf
  • Bridging the representational gap in the dynamic systems approach to development
    Spencer, J. P., & Schöner, G.
    Developmental Science, 6(4), 392–412
    pdf

    • 2002

  • Dynamic field theory of movement preparation.
    Erlhagen, W., & Schöner, G.
    Psychological Review, 109(3), 545–572
    reprint
  • Timing, Clocks, and Dynamical Systems
    Schöner, G.
    Brain and Cognition, 48, 31–51
    reprint

    • 1999

  • The distribution of neuronal population activation (DPA) as a tool to study interaction and integration in cortical representations
    Erlhagen, W., Bastian, A., Jancke, D., Riehle, A., & Schöner, G.
    Journal of Neuroscience Methods, 94(1), 53–66
  • Parametric population representation of retinal location: Neuronal interaction dynamics in cat primary visual cortex
    Jancke, D., Erlhagen, W., Dinse, H. R., Akhavan, A. C., Giese, M., Steinhage, A., & Schöner, G.
    J Neurosci, 19(20), 9016–9028

    • 1995

  • Dynamics of behavior: Theory and applications for autonomous robot architectures
    Schöner, G., Dose, M., & Engels, C.
    Robotics and Autonomous Systems, 16, 213–245
    SchonerDoseEngels95.pdf

    • 1986

  • A stochastic theory of phase transitions in human hand movement
    Schöner, G., Haken, H., & Kelso, J. A. S.
    Biological Cybernetics, 53, 247–257
    pdf bib