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2018

  • Real-Time Depth from Focus on a Programmable Focal Plane Processor
    Martel, J. N. P., Müller, L. K., Carey, S. J., Müller, J., Sandamirskaya, Y., & Dudek, P.
    IEEE Transaction on Circuits and Systems–I, 65(3), 925–934
  • 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 (pp. 429–434)
  • 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
  • A Neuromorphic approach to path integration: a head direction spiking neural network with visually-driven reset
    Kreiser, R., Cartiglia, M., Martel, J. N. P., Conradt, J., & Sandamirskaya, Y.
    In IEEE Symposium for Circuits and Systems, ISCAS
  • Pose Estimation and Map Formation with Spiking Neural Networks: towards Neuromorphic SLAM
    Kreiser, R., Pienroj, P., Renner, A., & Sandamirskaya, Y.
    In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS
  • An Active Approach to Solving the Stereo Matching Problem using Event-Based Sensors
    Martel, J. N. P., Müller, J., Conradt, J., & Sandamirskaya, Y.
    In IEEE International Symposium on Circuits and Systems (ISCAS)

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
  • A neuromorphic controller for a robotic vehicle equipped with a dynamic vision sensor
    Blum, H., Dietmüller, A., Milde, M., Conradt, J., Indiveri, G., & Sandamirskaya, Y.
    In Robotics Science and Systems Conference, RSS
  • Changes in frontal and posterior cortical activity underlie the early emergence of executive function
    Buss, A. T., & Spencer, J. P.
    Developmental Science, (June 2017), 1–14
  • Learning Temporal Intervals in Neural Dynamics
    Duran, B., & Sandamirskaya, Y.
    IEEE Transactions on Cognitive and Developmental Systems, 1–14
  • On-chip unsupervised learning in Winner-Take-All networks of spiking neurons
    Kreiser, R., Moraitis, T., Sandamirskaya, Y., & Indiveri, G.
    In Biological Circuits and Systems (BioCAS)
  • 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
  • Affective–associative two-process theory: a neurocomputational account of partial reinforcement extinction effects
    Lowe, R., Almèr, A., Billing, E., Sandamirskaya, Y., & Balkenius, C.
    Biological Cybernetics, 11(5-6), 365–388
  • Obstacle avoidance and target acquisition for robot navigation using a mixed signal analog/digital neuromorphic processing system
    Milde, M. B., Blum, H., Dietmüller, A., Sumislawska, D., Conradt, J., Indiveri, G., & Sandamirskaya, Y.
    Frontiers in Neurorobotics
  • Obstacle avoidance and target acquisition in mobile robots equipped with neuromorphic sensory-processing systems
    Milde, M., Dietmüller, A., Blum, H., Indiveri, G., & Sandamirskaya, Y.
    In IEEE Synposium for Circuits and Systems, ISCAS
  • Empirical Tests of a Brain-Based Model of Executive Function Development
    Perone, S., Plebanek, D. J., Lorenz, M. G., Spencer, J. P., & Samuelson, L. K.
    Child Development, 00, 1–17
  • A multi-joint model of quiet , upright stance accounts for the “uncontrolled manifold”-structure of joint variance
    Reimann, H., & Schöner, G.
    Biological Cybernetics, in press
  • A neural dynamic model generates descriptions of object-oriented actions
    Richter, M., Lins, J., & Schöner, G.
    Topics in Cognitive Science, 9(1), 35–47
  • Obstacle avoidance with LGMD neuron: towards a neuromorphic UAV implementation
    Salt, L., Indiveri, G., & Sandamirskaya, Y.
    In IEEE International Symposium on Circuits and Systems
  • Restoration of fMRI decodability does not imply latent working memory states
    Schneegans, S., & Bays, P. M.
    Journal of Cognitive Neuroscience, 29(12), 1977–1994
  • 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
  • Dynamic Neural Fields with Intrinsic Plasticity
    Strub, C., Schöner, G., Wörgötter, F., & Sandamirskaya, Y.
    Frontiers in Computational Neuroscience, 11(August), 74
  • Lowe, Robert and Almér, Alexander and Billing, Erik and Sandamirskaya, Yulia and Balkenius, Christian
    two-process theory: a neurocomputational account of partial reinforcement extinction effects, A. –associative
    Biological Cybernetics, 111(5-6), 365–388
  • Model-based functional neuroimaging using dynamic neural fields: An integrative cognitive neuroscience approach
    Wijeakumar, S., Ambrose, J. P., Spencer, J. P., & Curtu, R.
    Journal of Mathematical Psychology, 76, 212–235

2016

  • Nonlinear dynamics in the perceptual grouping of connected surfaces
    Hock, H. S., & Schöner, G.
    Vision Research, 126, 80–96
  • Testing a dynamic-field account of interactions between spatial attention and spatial working memory
    Johnson, J. S., & Spencer, J. P.
    Attention, Perception, and Psychophysics, 78(4), 1043–1063
  • 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
  • A Neuromorphic Approach for Tracking using Dynamic Neural Fields on a Programmable Vision-chip
    Martel, J. N. P., & Sandamirskaya, Y.
    In Proceedings of the 10th International Conference on Distributed Smart Camera (ICDSC), ACM
  • Coordination of muscle torques stabilizes upright standing posture: an UCM analysis
    Park, E., Reimann, H., & Schöner, G.
    Experimental Brain Research, 234(6), 1757–1767
  • 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
  • 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
  • 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
  • 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

2015

  • Simultaneous Planning and Action: Neural-dynamic Sequencing of Elementary Behaviours in Robot Navigation
    Billing, E., Lowe, R., & Sandamirskaya, Y.
    Adaptive Behvaior, 1–22
  • Rule Representation
    Buss, A. T., & Spencer, J. P.
    (Vol. 3) Elsevier Inc.
  • Carry-over coarticulation in joint angles
    Hansen, E., Grimme, B., Reimann, H., & Schöner, G.
    Experimental Brain Research, 233(9), 2555–2569
  • Journal of Experimental Psychology : Human Perception and Performance A Dynamic Neural Field Model of Temporal Order A Dynamic Neural Field Model of Temporal Order Judgments
    Hecht, L. N., Spencer, J. P., Vecera, S. P., Hecht, L. N., Spencer, J. P., & Vecera, S. P.
  • 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
  • The Actor-DoCritic: Differential outcomes learning in an associative two-process neural network model
    Lowe, R., & Billing, E.
    Neural Networks, in press
  • 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
  • Learning the Condition of Satisfaction of an Elementary Behavior in Dynamic Field Theory
    Luciw, M., Kazerounian, S., Lakhmann, K., Richter, M., & Sandamirskaya, Y.
    Paladyn
  • 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
  • Motor equivalence during multi-finger accurate force production
    Mattos, D., Schöner, G., Zatsiorsky, V. M., & Latash, M. L.
    Experimental Brain Research, 233, 487–502
  • Enhancing the executive functions of 3-year-olds in the dimensional change card sort task
    Perone, S., Molitor, S., Buss, A. T., Spencer, J. P., & Samuelson, L. K.
    Child Development, 86, 812–827
  • The Dynamics of Neural Activation Variables
    Reimann, H., Lins, J., & Schöner, G.
    Paladyn, Journal of Behavioral Robotics, 6(1), 57–70
  • The Infant Orienting With Attention Task: Assessing the Neural Basis of Spatial Attention in Infancy
    Ross-Sheehy, S., Schneegans, S., & Spencer, J. P.
    Infancy, 20(5), 467–506
  • Learning to Reach after Learning to Look: a Study of Autonomy in Learning Sensorimotor Transformations
    Rudolph, C., Storck, T., & Sandamirskaya, Y.
    In IJCNN
  • Grounding cognitive-level processes in behavior: The view from dynamic systems theory
    Samuelson, L. K., Jenkins, G. W., & Spencer, J. P.
    Topics in Cognitive Science, 7(2), 191–205
  • NARLE: Neurocognitive architecture for the autonomous task recognition, learning, and execution
    Sandamirskaya, Y., & Burtsev, M.
    BICA, 13
  • Artificial Neural Networks — Methods and Applications in Bio-/Neuroinformatics
    Sandamirskaya, Y., & Storck, T.
    In P. Koprinkova-Hristova, Mladenov, V., & Kasabov, N. K. (Eds.) (Vol. 4) Springer
  • Artificial Neural Networks
    Sandamirskaya, Y., & Storck, T.
    In P. Koprinkova-Hristova, Mladenov, V., & Kasabov, N. K. (Eds.) (Vol. 4) Springer
  • 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)
  • 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)

2014

  • Learning to Look: a Dynamic Neural Fields Architecture for Gaze Shift Generation
    Bell, C., Storck, T., & Sandamirskaya, Y.
    In ICANN Hamburg, Germany
  • Learning to Look: a Dynamic Neural Fields Architecture for Gaze Shift Generation
    Bell, C., Storck, T., & Sandamirskaya, Y.
    In International Conference for Artificial Neural Networks, ICANN Hamburg, Germany
  • The emergent executive: a dynamic field theory of the development of executive function
  • 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
  • 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
  • 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
  • A Neural Dynamic Model of Associative Two-Process Theory: The Differential Outcomes Effect and Infant Development
    Lowe, R., Sandamirskaya, Y., & Billing, E.
    In ICDL-EPIROB
  • 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
  • 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
  • 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
  • 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
  • The Co-Development of Looking Dynamics and Discrimination Performance
    Perone, S., & Spencer, J. P.
    Developmental Psychology, 50(3), 837–852
  • 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
  • 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
  • Neural-Dynamic Architecture for Looking: Shift from Visual to Motor Target Representation for Memory Saccade
    Sandamirskaya, Y., & Storck, T.
    In IEEE International Conference on Development and Learning and on Epigenetic Robotics (ICDL EPIROB 2014)
  • 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
  • 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
  • Embodied Cognition, Neural Field Models of
    Schöner, G.
    In Encyclopedia of Computational Neuroscience (pp. 1084–1092) Springer Berlin Heidelberg
  • 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
  • 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
  • Correcting Pose Estimates during Tactile Exploration of Object Shape: a Neuro-robotic Study
    Strub, C., Wörgötter, F., Ritter, H., & Sandamirskaya, Y.
    In Development and Learning and Epirobotics (ICDL-Epirob), IEEE International Conference on
  • Using Haptics to Extract Object Shape from Rotational Manipulations
    Strub, C., Wörgötter, F., Ritter, H., & Sandamirskaya, Y.
    In Intelligent Robots and Systems (IROS), IEEE/RSJ International Conference on IEEE
  • Correcting pose estimates during tactile exploration of object shape: a neuro-robotic study
    Strub, C., Wörgötter, F., Ritter, H., & Sandamirskaya, Y.
    In ICDL-EPIROB (pp. 26–33) IEEE

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
  • Autonomous Reinforcement of Behavioral Sequences in Neural Dynamics
    Kazerounian, S., Luciw, M., Richter, M., & Sandamirskaya, Y.
    In International Joint Conference on Neural Networks (IJCNN)
  • 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
  • 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"
  • Autonomous visual exploration creates developmental change in familiarity and novelty seeking behaviors
    Perone, S., & Spencer, J. P.
    Frontiers in Psychology, 4(648), 1–21
  • Autonomy in Action: Linking the Act of Looking to Memory Formation in Infancy via Dynamic Neural Fields
    Perone, S., & Spencer, J. P.
    Cognitive Science, 37(1), 1–60
  • Dynamic Neural Fields as a Step Towards Cognitive Neuromorphic Architectures
    Sandamirskaya, Y.
    Frontiers in Neuroscience, 7, 276
  • Autonomy in Learning Sensorimotor Spaces with Dynamic Neural Fields
    Sandamirskaya, Y.
    In Proceedings of the Annual Meeting of the Cognitive Science Society, Berlin
  • Increasing Autonomy of Learning SensorimotorTransformations with Dynamic Neural Fields
    Sandamirskaya, Y., & Conradt, J.
    In International Conference on Robotics and Automation (ICRA), Workshop "Autonomous Learning"
  • Learning Sensorimotor Transformations with Dynamic Neural Fields
    Sandamirskaya, Y., & Conradt, J.
    In International Conference on Artificial Neural Networks (ICANN)
  • 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

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
  • 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
  • Behavioral dynamics and neural grounding of a dynamic field theory of multi-object tracking.
    Spencer, J. P., Barich, K., Goldberg, J., & Perone, S.
    Journal of integrative neuroscience, 11(3), 339–62
  • 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
  • When seeing is knowing: The role of visual cues in the dissociation between children′s rule knowledge and rule use
    Buss, A. T., & Spencer, J. P.
    Journal of Experimental Child Psychology, 111(3), 561–569
  • Neural Dynamics of Hierarchically Organized Sequences: a Robotic Implementation
    Duran,, & Sandamirskaya, Y.
    In Proceedings of 2012 IEEE-RAS International Conference on Humanoid Robots (Humanoids)
  • 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
  • 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
  • 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)
  • 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
  • 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
  • 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
  • A neural mechanism for coordinate transformation predicts pre-saccadic remapping
    Schneegans, S., & Schöner, G.
    Biological cybernetics, 106(2), 89–109
  • 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
  • Contributions of dynamic systems theory to cognitive development
    Spencer, J. P., Austin, A., & Schutte, A. R.
    Cognitive Development, 27, 401–418
  • 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)

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
  • Limb versus speech motor control: a conceptual review.
    Grimme, B., Fuchs, S., Perrier, P., & Schöner, G.
    Motor control, 15(1), 5–33
  • Stronger neural dynamics capture changes in infants′ visual working memory capacity over development
    Perone, S., Simmering, V. R., & Spencer, J. P.
    Developmental Science, 14(6), 1379–1392
  • 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
  • Grounding word learning in space
    Samuelson, L. K., Smith, L. B., Perry, L. K., & Spencer, J. P.
    PloS one, 6, E28095
  • Autonomous Sequencing of Boosts in a Dynamic Neural Fields Architecture for Spatial Language
    Sandamirskaya, Y.
    In 13th International Conference on Cognitive and Neural Systems, ICCNS
  • A Dynamic Neural Fields (DNF) Spatial Language Architecture: the Emergence of Spatial Language Behaviors.
    Sandamirskaya, Y.
    In Interactivist Summer Institute
  • Learning in Dynamic Neural Fields Model for Sequence Generation
    Sandamirskaya, Y.
    In Workshop on Developmental and Learning in Artificial Neural Networks, Paris, France
  • 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)
  • 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
  • A Neurodynamic Architecture for the Autonomous Control of a Spatial Language System
    Schneegans, S., & Sandamirskaya, Y.
    In ICDL-EPIROB
  • 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
  • Twenty years and going strong: A dynamic systems revolution in motor and cognitive development
    Spencer, J. P., Perone, S., & Buss, A. T.
    Child Development Perspectives, 5(4), 260–266
  • 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
  • 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
  • A neuro-dynamic object recognition architecture enhanced by foveal vision and a gaze control mechanism
    Faubel, C., & Zibner, S. K. U.
    In Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on (pp. 1171–1176) IEEE
  • 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
  • Measuring Perceptual Hysteresis with the Modified Method of Limits: Dynamics at the Threshold
    Hock, H. S., & Schöner, G.
    Seeing and Perceiving, 23, 173–195
  • Motor control theories and their applications
    Latash, M., Levin, M. F., Scholz, J. P., & Schöner, G.
    Medicina (Kaunas), 29(6), 997–1003
  • The role of experience in location estimation: Target distributions shift location memory biases
    Lipinski, J., Simmering, V. R., Johnson, J. S., & Spencer, J. P.
    Cognition, 115(1), 147–153
  • Biased feedback in spatial recall yields a violation of delta rule learning
    Lipinski, J., Spencer, J. P., & Samuelson, L. K.
    Psychonomic Bulletin and Review, 17(4), 581–588
  • 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
  • An embodied account of serial order: how instabilities drive sequence generation
    Sandamirskaya, Y., & Schöner, G.
    Neural Networks, 23(10), 1164–1179
  • 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
  • Filling the gap on developmental change: Tests of a dynamic field theory of spatial cognition
    Schutte, A. R., & Spencer, J. P.
    Journal of Cognition and Development, 11(3), 328–355
  • 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
  • Scenes and tracking with dynamic neural fields: How to update a robotic scene representation
    Zibner, S. K. U., Faubel, C., Iossifidis, I., Schöner, G., & Spencer, J. P.
    In Development and Learning (ICDL), 2010 IEEE 9th International Conference on (pp. 244–250) IEEE

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
  • A counterchange mechanism for the perception of motion.
    Hock, H. S., Schöner, G., & Gilroy, L.
    Acta psychologica, 132(1), 1–21
  • Representational Integration in Spatial Language Semantics: Robotic Demonstrations of a Neurodynamic Framework
  • The dynamic nature of knowledge: Insights from a dynamic field model of children′s novel noun generalization
    Samuelson, L. K., Schutte, A. R., & Horst, J. S.
    Cognition, 110(3), 322–345
  • 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
  • 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
  • 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)
  • 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
  • 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
  • Redundancy, self-motion and motor control
    Martin, V., Scholz, J. P., & Schöner, G.
    Neural Computation, 21(5), 1371–1414
  • 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
  • Tests of the dynamic field theory and the spatial precision hypothesis: capturing a qualitative developmental transition in spatial working memory.
    Schutte, A. R. A. R., & Spencer, J. P.
    Journal of experimental psychology. Human perception and performance, 35(6), 1698–725
  • Response to on "Infants′ Perseverative Search Errors Are Induced by Pragmatic Misinterpretation"
    Spencer, J. P., Dineva, E., Smith, L. B., Topal, J., Toth, M., Gergely, G., & Csibra, G.
    Science, 325(5948), 1624–1624
  • 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)

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
  • Then and there in here and now
    Lipinski, J., & Sandamirskaya, Y.
    In Cognition Workshop
  • 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
  • Generalizing the dynamic field theory of spatial cognition across real and developmental time scales
    Simmering, V. R., Schutte, A. R., & Spencer, J. P.
    Brain Research, 1202, 68–86
  • Generality with specificity: The dynamic field theory generalizes across tasks and time scales
    Simmering, V. R., & Spencer, J. P.
    Developmental Science, 11(4), 541–555
  • Defending Qualitative Change : The View From Dynamical Systems Theory Defending Qualitative Change : The View From Dynamical Systems Theory
    Spencer, J. P., Spencer, J. P., & Perone, S.
    , 79(November 2008), 1639–1647

2007

  • Planning ′discrete′ movements using a continuous system: Insights from a dynamic field theory of movement preparation
    Schutte, A. R., & Spencer, J. P.
    Motor Control, 11, 166–208

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
  • A dynamic model for action understanding and goal-directed imitation.
    Erlhagen, W., Mukovskiy, A., & Bicho, E.
    Brain research, 1083(1), 174–88
  • 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
  • Toward a formal theory of flexible spatial behavior: Geometric category biases generalize across pointing and verbal response types
    Spencer, J. P., Simmering, V. R., & Schutte, A. R.
    Journal of Experimental Psychology: Human Perception & Performance, 32, 473–490
  • Modelling and understanding of chatter
    Wolfrum, P., Gepperth, A., Sandamirskaya, Y., Webber, O., & Raabe, N.
    In Technical Reports, SFB 475, TU Dortmund

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
  • Bridging the representational gap in the dynamic systems approach to development
    Spencer, J. P., & Schöner, G.
    Developmental Science, 6(4), 392–412

2002

  • Timing, Clocks, and Dynamical Systems
    Schöner, G.
    Brain and Cognition, 48, 31–51
  • Generalizing the dynamic field theory of the A-not-B error beyond infancy: Three-year-olds′ delay- and experience-dependent location memory biases
    Schutte, A. R., & Spencer, J. P.
    Child Development, 73(2), 377–404

2001

  • Tests of a dynamic systems account of the A-not-B error: The influence of prior experience on the spatial memory abilities of 2-year-olds
    Spencer, J. P., Smith, L. B., & Thelen, E.
    Child Development, 72, 1327–1346

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

1986

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

  • A Dialog on the Role of Computational Modeling in Developmental Science
    Simmering, V. R., Triesch, J., Dea, G. O., & Spencer, J. P.
    Child Development, 4(2), 152–158