Fred H Hamker Allgemeine Psychologie Psychologisches Institut II Westfälische Wilhelms Universität Münster Fliednerstr. 21 48149 Münster Tel:+49 (0)251/83-34171 Fax:+49 (0)251/83-34180 Raum: 2.135 b mail: fhamker@uni-muenster.de Sprechstunde: Mo. 10-11 Uhr Research Group Publications CV

Research Group

Theoretical and model-driven approach to experimental psychology/neuroscience in visual perception and its cognitive control

My junior-research group persues a model-driven approach to explore visual perception and cognition. At present, research in visual perception has accumulated numerous experimental data. Since the underlying processes have turned out being very complex and present data eludes a simple interpretation, more research is necessary to elaborate a theoretical basis in form of neurocomputational models. The models we are interested in, try to capture the temporal dynamics of the essential mechanisms and processes in the brain primarily on the level of a population code. Our research goals are three-fold. i) We want to link-up different experimental observations in a single model to work out common, essential mechanisms. ii) We test experimental predictions of the model either in our group or through collaborations. We expect that models adressing higher functions as part of different brain areas will gain more and more impact in guiding research. iii) The validity of the models is also tested by observing their performance on real world tasks, such as object/category recognition. We are confident that this neurobiological approach provides a high potential for future computer vision solutions.

Members:

Julien Vitay	PostDoc
Mark-André Voss	Ph.D. Student
Jan Wiltschut	Ph.D. Student
Arnold Ziesche	Ph.D. Student
Marc Zirnsak	Ph.D. Student
Ricarda Gerhards	Student
Ann-Kathrin Bröckelmann	Student
Matthias Pohl	Student

Present Projects

Peri-saccadic space perception

Attention

Category/Object Recognition

Cognitive Control of Visual Perception

Masking and Conscious Perception

Completed Projects

Life-long Learning and the Stability-Platicity-Dilemma

Data-Analysis and Benchmaking with Neural Networks

Visuo-motor Systems

Optical Flow

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Publications

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Journal

Wiltschut, J., Hamker, F.H. (2009)
Efficient Coding correlates with spatial frequency tuning in a model of V1 receptive field organization.
Visual Neuroscience. 26:21-34
PDF-document

Vitay, J., Hamker, F.H. (2008)
Sustained activities and retrival in a computational model of perirhinal cortex.
Journal of Cognitive Neuroscience. 20:11 pp 1993-2005
PDF-document 

Georg, K., Hamker, F. H., and Lappe, M. (2008).
Influence of adaptation state and stimulus luminance on peri-saccadic localization.
J. Vision 8(1):15, 1-11.
PDF-document

Hamker, F.H., Zirnsak, M., Calow, D., Lappe, M. (2008)
The peri-saccadic perception of objects and space.
PLOS Computational Biology 4(2):e21
PDF-document 

Hamker, F.H., Zirnsak, M., Lappe, M. (2008)
About the influence of post-saccadic mechanisms for visual stability on peri-saccadic compression of object location.
Journal of Vision, 8(14):1, 1-13.
PDF-document

Hamker, F.H., Wiltschut, J. (2007)
Hebbian learning in a model with dynamic rate-coded neurons: an alternative to the generative model approach for learning receptive fields from natural scenes
Network, Computation in Neural Systems, 18: 249-266.
PDF-document

Hamker, F. H. (2007)
The mechanisms of feature inheritance as predicted by a systems-level model of visual attention and decision making
Advances in Cognitive Psychology, 3:111-123.
PDF-document 

Hamker, F. H., Zirnsak, M. (2006)
V4 receptive field dynamics as predicted by a systems-level model of visual attention using feedback from the frontal eye field.
Neural Networks, 19:1371-1382
PDF-document

Hamker, F. H. (2006)
Modeling feature-based attention as an active top-down inference process.
BioSystems, 86:91-99
PDF-document

Hamker, F. H. (2005)
The emergence of attention by population-based inference and its role in distributed processing and cognitive control of vision.
Journal for Computer Vision and Image Understanding. Special Issue on Attention and Performance in Computer Vision, 100:64-106.
PDF-document

Hamker, F. H. (2005)
A computational model of visual stability and change detection during eye movements in real world scenes.
Visual Cognition, 12:1161-1176.
PDF-document

Hamker, F. H. (2005)
The Reentry Hypothesis: The Putative Interaction of the Frontal Eye Field, Ventrolateral Prefrontal Cortex, and Areas V4, IT for Attention and Eye Movement.
Cerebral Cortex, 15:431-447.
PDF-document

Hamker, F. H. (2004)
A dynamic model of how feature cues guide spatial attention.
Vision Research, 44:501-521.
PDF-document

Hamker, F. H. (2004)
Predictions of a model of spatial attention using sum- and max-pooling functions.
Neurocomputing, 56C:329-343.
PDF-document

Hamker, F. H. (2003)
The reentry hypothesis: linking eye movements to visual perception.
Journal of Vision, 11:808-816.
PDF-document

Hamker, F. H. (2001)
Life-long learning Cell Structures - continuously learning without catastrophic interference.
Neural Networks, 14:551-573.
PDF-document

Heinke, D., Hamker, F. H. (1998)
Comparing Neural Networks: A Benchmark on Growing Neural Gas, Growing Cell Structures, and Fuzzy ARTMAP.
IEEE Transactions on Neural Networks, 9:1279-1291.
PDF-document

Hamker, F. H., Gross, H.-M. (1996)
Region Finding for Attention Control in Consideration of Subgoals.
Neural Network World. International Journal on Neural and Mass-Parallel Computing and Information Systems. 6:305-313.

Proceedings

Vitay, J., Hamker, F. H., (in press)
Binding objects to cognition: A brain-like systems approach to the cognitive control of visual perception. International Conference on Cognitive Systems.
(CogSys 2008), Karlsruhe, Germany.

Hamker, F. H. (2005)
A population-based inference framework for feature-based attention in natural scenes.
In: M. De Gregorio et al. (eds.), International Symposium on Brain Vision & Artificial Intelligence (BV&AI 2005), LNCS 3704. Berlin, Heidelberg: Springer-Verlag, 147–156.
PDF-document

Hamker, F. H. (2005)
Modeling Attention: From computational neuroscience to computer vision.
In: L. Paletta et al. (eds.), Attention and Performance in Computational Vision. Second International workshop on attention and performance in computer vision (WAPCV 2004), LNCS 3368. Berlin, Heidelberg: Springer-Verlag, 118–132.
PDF-document

Hamker, F. H. (2004)
Vision as an anticipatory process.
Invited Contribution. In: H.-M. Groß et al. (eds.), SOAVE 2004, 3rd Workshop on Self Organization of Adaptive Behavior. Fortschritt-Berichte VDI, Reihe 10, Nr. 743. Düsseldorf: VDI Verlag, 79-93.
PDF-document

Hamker, F. H., Zirnsak, M., Calow, D., Lappe, M. (2004)
Planned action determines perception: A computational model of saccadic mislocalization.
In: U. Ilg et al. (eds.), Dynamic Perception, Infix Verlag, St. Augustin, 71-76.
PDF-document

Hamker, F. H., Worcester, J. (2002)
Object detection in natural scenes by feedback.
In: H. H. Bülthoff et al. (eds.), Biologically Motivated Computer Vision. Lecture Notes in Computer Science. Berlin, Heidelberg, New York: Springer Verlag, 398-407.
PDF-document

Hamker, F. H. (2002)
How does the ventral pathway contribute to spatial attention and the planning of eye movements?
In: R. P. Würtz & M. Lappe (eds.) Dynamic Perception. St. Augustin: Infix Verlag, pp. 83-88.
PDF-document

Brause, R., Hamker, F., Paetz, J. (2002)
Septic shock diagnosis by neural networks and rule based systems.
In: Schmitt, et al. (eds.), Computational Intelligence Processing in Medical Diagnosis, Springer Verlag, New York, pp. 323-356.

Hamker, F. H. (2000)
Distributed competition in directed attention.
In: G. Baratoff, H. Neumann (eds.) Proceedings in Artificial Intelligence, Vol. 9. Dynamische Perzeption. Berlin: AKA, Akademische Verlagsgesellschaft, 39-44.
PDF-document

Paetz, J., Hamker, F. H., Thöne, S. (2000)
About the Analysis of Septic Shock Patient Data.
Medical Data Analysis, Proceedings of the First International Symposium ISMDA 2000. Lecture Notes in Computer Science, vol. 1933. Heidelberg: Springer-Verlag, 130-137.

Hamker, F. H. (1999)
The role of feedback connections in task-driven visual search.
In: D. Heinke, G. W. Humphreys & A. Olson (eds.) Connectionist Models in Cognitive Neuroscience, Proc. of the 5th Neural Computation and Psychology Workshop (NCPW'98). London: Springer Verlag, 252-261.
PDF-document

Hamker, F. H. (1999)
Life-long learning in incremental neural networks.
In: D. M. Dubois (eds.) International Journal of Computing Anticipatory Systems. CHAOS, Liège, Belgium, 3:65-74.

Hamker, F. H. (1998)
Lebenslang lernfähige Zellstrukturen: Eine Lösung des Stabilitäts-Plastizitäts-Dilemmas?
In: Proceedings der CoWAN '98, Cottbus 1998, Sharker Verlag, 17-37.

Hamker, F. H., Gross, H.-M. (1998)
A lifelong learning approach for incremental neural networks.
In: Fourteenth European Meeting on Cybernatics and Systems Research (EMCSR'98), Vienna, 599-604.

Hamker, F. H., Gross, H.-M. (1997)
Task-based representation in lifelong learning incremental neural networks.
In: VDI Fortschrittberichte, Reihe 8, Nr. 663, Workshop SOAVE'97 - Selbstorganisation von adaptivem Verhalten, Ilmenau, 99-108.
PDF-document

Hamker, F., Pomierski, T, Gross, H.-M., Debes, K. (1997)
Ein visuomotorisches Sortiersystem auf der Basis von Farbmerkmalen.
In: VDI Fortschrittberichte, Reihe 8, Nr. 663, Workshop SOAVE'97 - Selbstorganisation von adaptivem Verhalten, Ilmenau, 232-238.
PDF-document

Hamker, F. H., Gross, H.-M. (1997)
Object selection with dynamic neural maps.
In: Proceedings of the International Conference on Artificial Neural Networks (ICANN'97), Lausanne: Springer-Verlag, 919-924.
 
Hamker, F. H., Gross, H.-M. (1996)
Intentionale Aufmerksamkeit: Ein alternatives Konzept für technische visuo-motorische Systeme.
In: Proceedings des Workshops der GI-Fachgruppe 1.0.4 Bildverstehen "Aktives Sehen in technischen und biologischen Systemen", Hamburg, 101-108.
PDF-document

Hamker, F. H., Gross, H.-M. (1996)
Task Relevant Relaxation Network for visuo-motory Systems.
In: Proceedings of the International Conference on Pattern Recognition (ICPR'96), Vienna, 406-410.

Hamker, F. H., Gross, H.-M. (1996)
Region Selection: Segmentation, Classification and Task Relevance in a single Grouping Mechanism.
In: Proceedings of the IEEE International Conference on Neural Networks (ICNN'96), Washington, 1540-1545.

Book Chapter and other Series

Vitay, J., Hamker, F. H. (2007)
On the role of dopamine in cognitive vision.
In: Attention in Cognitive Systems, L. Paletta and E. Rome (eds.), Springer LNAI 4840, pp. 352-366
PDF-document 

Ma, W. J., Hamker, F. H., Koch, C.
Neural mechanisms underlying temporal aspects of conscious visual perception
In: H. Ögmen & B. G. Breitmeyer (eds.) The First Half Second: The Microgenesis and Temporal Dynamics of Unconscious and Conscious Visual Processes. MIT Press, Chapter 16, 275-294.

Hamker, F. H. (2005)
Chapter 98: How the detection of objects in natural scenes constrains attention in time.
In: L. Itti, J. Tsotsos & G. Rees (eds.) Neurobiology of Attention. Elsevier Science and Technology Books, pp. 600-604.

Hamker, F. H. (2001)
RBF learning in a non-stationary environment: the stability-plasticity dilemma.
In: R. J. Howlett & L. C. Jain (eds.) Radial Basis Function Networks 1: Recent Developments in Theory and Applications. Studies in fuzziness and soft computing; vol. 66. Heidelberg, New York: Physica Verlag, Chapter 9, 219-251.
PDF-document

Hamker, F. H., Paetz, J., Thöne, S., Brause, R., Hanisch, E. (2000)
Erkennung kritischer Zustände von Patienten mit der Diagnose "Septischer Schock" mit einem RBF-Netz.
Bericht 4/2000 des Fachbereichs Informatik der JW Goethe-Universität Frankfurt am Main, ISSN 1432-9611.

Key, J., Hamker, F. H. (1999)
WTA-Verfahren zur Aufmerksamkeitsselektion und Aufmerksamkeitsverlagerung in statischen Szenen.
Schriftenreihe des FG Neuroinformatik der TU Ilmenau, TR-NI-99-02, 1999, ISSN 0945-7518.

Key, J., Hamker, F. H. (1998)
Numerische Verfahren zur Simulation eines neuronalen Netzwerks zur objektbezogenen Selektion.
Schriftenreihe des FG Neuroinformatik der TU Ilmenau, Report 1/98, 1998, ISSN 0945-7518 (53 Pages).

Hamker, F., Heinke, D. (1997)
Implementation and Comparison of Growing Neural Gas, Growing Cell Structures and Fuzzy Artmap.
Schriftenreihe des FG Neuroinformatik der TU Ilmenau, Report 1/97, 1997, ISSN 0945-7518. (57 Pages)

C. Herwig, H.-O. Carmesin, F. Hamker, D. Wandtke
Real-time estimation of heading direction
Technical Report 1995
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CV

since 2005	Lecturer in the international M.Sc. Program of Neuro-Cognitive Psychology at the LMU Munich
since 2003	Assistant Professor (Wissenschaftlicher Assistent) at the Westf. Wilhelms-Universität Münster, Institute of Psychology II
2003	Lecturer at the California Institute of Technology, Pasadena, USA in Computation and Neural Systems, Division of Engineering and Applied Science
2000 - 2003	Postdoc at the California Institute of Technology, Pasadena, USA in Klab Division of Biology
1998 - 2000	Postdoctoral Scholar at the J.W.-Goethe Universität Frankfurt am Main, Medicine and Computer Science, involved in the project MEDAN
1999	Ph.D. at the TU Ilmenau Computer Science and Neural Information processing (Advisor: Prof. Dr. Gross)
1994 - 1998	Ph.D. Student Research at the Fachgebiet Neuroinformatik of the TU Ilmenau, involved in the project MIRIS
1987 - 1994	Student of Electrical Engineering at the Universität-GH-Paderborn Diploma Thesis: Self-organization of controlled mappings in a neural achitecture (Advisor: Prof. Dr. Hartmann)

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Institut für Psychologie
Prof. Dr. M. Lappe
Fliednerstr. 21 · D-48149 Münster
Tel.: +49 251 83-34172 · Fax: +49 251 83-34173
E-Mail: mlappe@psy.uni-muenster.de