Publications
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Attention selectively gates afferent signal transmission to area V4. The Journal of Neuroscience 38 (14), 3441-3452 (2018).
JournalofNeurosci_2018.pdf (1.89 MB)
JournalofNeurosci_2018.pdf (1.89 MB) Open hardware for neuro-prosthesis research: A study about a closed-loop multi-channel system for electrical surface stimulations and measurements. ArXiv: http://biorxiv.org/content/early/2017/05/23/141184 (2017). doi:https://doi.org/10.1101/141184 141184.full_.pdf (7.1 MB)
141184.full_.pdf (7.1 MB) Ongoing activity in a spiking network of visual cortical columns representing local optimal inference modules. Bernstein Conference 2016 (2016). abstract_capparelli_BCCN2016.pdf (508.3 KB)
abstract_capparelli_BCCN2016.pdf (508.3 KB) Multistable network dynamics through lateral inhibition: an efficient mechanism for selective information routing. The Twenty Third Annual Computational Neuroscience Meeting: CNS*2014 15 (Suppl1), P165 (2014). cns_2014_harnack.pdf (126.29 KB)
cns_2014_harnack.pdf (126.29 KB) A dynamic model for selective visual attention predicts information routing. Göttingen Meeting of the German Neuroscience Society 2013 T26-6C (2013).
A model for selective visual attention predicts information routing. BMC Neuroscience 2013 14(Suppl.1), P310 (2013).
The neuronal input channel switched by attention reflects routing by coherence. COSYNE 2013 III-2 (2013).
Gating of visual processing by selective attention as observed in LFP data of monkey area V4. SfN International Neuroscience Meeting 2011 221.05 (2011).
Gating Of Visual Processing By Selective Attention As Observed In LFP Data Of Monkey Area V4. 9th Goettingen Meeting of the German Neuroscience Society / 33nd Goettingen Neurobiology Conference T24-3B (2011).
Routing of information flow by selective visual attention in LFPs of monkey area V4. Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting (2011). doi:10.3389/conf.fncom.2011.53.00055
Transient activation of MT neurons to stimulus velocity changes: experiments and modelling. BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011 (2011). doi:doi: 10.3389/conf.fncom.2011.53.00054
Discriminability of direction of attention with and without stimuli based on V4 epidural recordings: A perspective for high-performance brain-computer interfaces. SfN International Neuroscience Meeting 2010 631.3 (2010).
Highly selective processing of temporal information from attended stimuli in macaque’s visual area V4. Bernstein Conference on Computational Neuroscience (2010). doi:doi: 10.3389/conf.fncom.2010.51.00103
A Horizontal Bias in Contour Integration: Evidence from Psychophysics and Electrophysiology. Perception, ECVP Conference 39, (2010).
Predicting the dynamics of dual prism adaptation with a biophysically plausible neural model. Bernstein Conference on Computational Neuroscience (2010). doi:10.3389/conf.fncom.2010.51.00036
Attention Improves Object Representation in Visual Cortical Field Potentials. Journal of Neuroscience 29 (32), 10120–10130 (2009).
Can reduced contour detection performance in the periphery be explained by larger integration fields. 18th Annual Computational Neuroscience Meeting (CNS 2009) 10(Suppl 1): P360, (2009).
Decoding perceptual states of ambiguous motion from high gamma EEG. Bernstein Conference on Computational Neuroscience (BCCN2009) (2009). doi:doi: 10.3389/conf.neuro.10.2009.14.102
Fast on-line adaptation may cause critical noise amplification in human control behaviour. Bernstein Conference on Computational Neuroscience (BCCN2009) (2009). doi:10.3389/conf.neuro.10.2009.14.034
Field potentials from macaque area V4 predict attention in single trials with 100%. Bernstein Conference on Computational Neuroscience (BCCN2009) (2009). doi:10.3389/conf.neuro.10.2009.14.068
Influence of prior expectations on contour integration: Psychophysics and modelling. 18th Annual Computational Neuroscience Meeting (CNS 2009) 10 (Suppl 1): P12, (2009).
Interactions between top-down and stimulus-driven processes in visual feature integration. Bernstein Conference on Computational Neuroscience (BCCN2009) (2009). doi:10.3389/conf.neuro.10.2009.14.158
Learning of Visuomotor Adaptation: Insights from Experiments and Simulations. Bernstein Conference on Computational Neuroscience (BCCN2009) (2009). doi:10.3389/conf.neuro.10.2009.14.001
Phase differences in local field potentials from macaque monkey area V4 predict attentional state in single trials with 99.6% accuracy. Berlin Brain Computer Interface (BBCI) 2009 - Advances in Neurotechnology (2009).
Phase differences in local field potentials from macaque monkey area V4, predict attentional state in single trials with 99.6% accuracy. German-Japanese workshop 2009 (2009).
Phase differences in local field potentials from macaque monkey area V4 predict attentional state in single trials with 99.6% accuracy. 18th Annual Computational Neuroscience Meeting (CNS 2009) 10 (Suppl 1): P230, (2009).
Phase differences in local field potentials from macaque monkey area V4 predict attentional state in single trials with 99.6% accuracy. 8th Goettingen Meeting of the German Neuroscience Society / 32nd Goettingen Neurobiology Conference T26-13A (2009).
Does human balance behaviour reflect self-organized critical adaptive control?. Bernstein Symposium 2008, (2008). doi:doi: 10.3389/conf.neuro.10.2008.01.012
Human contour integration is optimized for natural images. SfN International Neuroscience Meeting 2008 568.25 (2008).
Phase differences in local field potentials from macaque monkey area V4 predict attentional state in single trials with 99.6% accuracy. SfN International Neuroscience Meeting 2008 590.20 (2008).
Self-organized critical control in human behavior. Proc. DPG spring meeting Berlin 2008 DY 5.3 (2008). at <http://www.dpg-verhandlungen.de/2008/berlin/dy5.pdf>
Spatial Transfer in Prism Adaptation. Bernstein Symposium 2008 (2008). doi:10.3389/conf.neuro.10.2008.01.026
Attention improves object representation in monkey area V4. Goettingen Neurobiology Conference T32-1A (2007).
Attention in monkey area V4 is modulated by task demand. SfN International Neuroscience Meeting 2007 176.1 (2007).
Self-organised critical noise amplification in human closed loop control. Noise in Life 2007: Stochastic Dynamics in the Neurosciences - International workshop, MPIPKS Dresden (2007).
Self-Organised Critical Noise Amplification in Human Closed Loop Control. Frontiers in Computational Neuroscience 1, 4 (2007). doi:10.3389/neuro.10.004.2007
Structure of the neuronal interactions underlying human contour integration. Sixteenth Annual Computational Neuroscience Meeting: CNS*2007 8(Suppl 2):P77, (2007).
Temporal factors in figure-ground segregation, object representation, and closed loop eye-hand coordination. Midterm Evaluation of the German National Network for Computational Neuroscience, Berlin 03.-04.12.2007 (2007).
Attention improves object discriminability in monkey area V4. CNS - Computational Neuroscience Conference S2 (2006).
FENS 2006 9915010554 (2006).
Contour detection from quasi-ideal contour integration. CNS - Computational Neuroscience Conference (2006).
Neuroscience (2006).
Modeling systematic errors of human contour detection reveals new mechanisms of contour integration. SfN International Neuroscience Meeting 2006 604.1 (2006).
On-line adaptation of neuro-prostheses with neuronal evaluation signals. Proceedings ESANN’06 53–62 (d-side, Evere, Belgium, 2006).
Optimal contour integration: When additive algorithms fail. Neurocomputing 69 (16-18), 1297-1300 (2006).
Towards on-line adaptation of neuro-prostheses with neuronal evaluation signals. SfN International Neuroscience Meeting 2006 13.13 (2006).
Towards on-line adaptation of neuro-prosthesis with neuronal evaluation signals. Biological Cybernetics 95 (3), 243–257 (2006).
Attention improves object encoding in monkey area V4. SfN International Neuroscience Meeting 2005 591.6 (2005).
Neuronal mechanisms of contour integration investigated by combining psychophysical experiments with probabilistic modeling. Proceedings of the 30th Götingen Neurobiology Conference 434A (2005).
Processing natural images with single spikes. Proceedings of the 30th Göttingen Neurobiology Conference 445A (2005).
Robust integration and detection of noisy contours in a probabilistic neural model. Neurocomputing 65-66, 211–217 (2005).
Systematic errors of contour detection are predicted by computational mechanisms for contour integration: Theory and Experiments. SfN International Neuroscience Meeting 2005 618.12 (2005).
An algorithm for fast pattern recognition with random spikes. 26th DAGM Symposium Pattern Recognition (Lecture Notes in Computer Science 3175), 399–406 (Springer-Verlag Berlin/Heidelberg, 2004).
Computing spike-by-spike. Dynamic Perception Workshop 145–150 (IOS Press, 2004).
Large tuning width can improve contour detection performance in a neural model for robust contour integration. 4th Forum of European Neuroscience (FENS) A 085.2 (2004).
Mechanisms and principles of contour integration revealed by combining psychophysical experiments with probabilistic modelling. SfN International Neuroscience Meeting 2004 713.8 (2004).
Mechanisms and principles of contour integration revealed by combining psychophysical experiments with probabilistic modeling. Dynamic Perception Workshop 211–216 (IOS Press, 2004).
A novel framework for universal adaptive computation in a cortex model with stochastic spikes. 4th Forum of European Neuroscience (FENS) 142.1 (2004).
Building representations spike by spike. Proceedings of the 29th Göttingen Neurobiology Conference 1041 (2003).
Building representations spike by spike. Neural Information and Coding Workshop (2003).
Rapid contour integration of macaque monkeys and spiking neural networks. SfN International Neuroscience Meeting 2003 767.10 (2003).
Building representations spike by spike. Society of Neuroscience Conference 2002 557.12 (2002).
Spectral and nonspectral analysis of brain state coherency. FENS 2002 074.10 (2002).
Synchronizing assemblies perform magnitude-invariant pattern detection. Neurocomputing 44-46, 429–433 (2002).
Asymmetric surround suppression coincides with structures of orientation preference map. Proceedings of the 28th Göttingen Neurobiology Conference 2001 248 (2001).
Handbook of Biological Physics 4, 969–1000 (Elsevier, Amsterdam, 2001).
Shine-through – dynamical effects. Dynamics and adaptivity of neuronal Systems – integrative approaches to analyzing cognitive functions (Symposium) (2001).
Intracortical origin of visual cortical maps. SfN International Neuroscience Meeting 1999 531.8 (1999).
Relation between retinotopic and orientation maps in visual cortex. Neural Computation 11, 375–379 (1999).
Relationships between cortical maps and receptive fields are determined by lateral cortical feedback. Proceedings of the 27th Göttingen Neurobiology Conference 1999 168 (1999).
Theory of non-classical receptive field phenomena in the visual cortex. Neurocomputing 26–27, 367–374 (1999).
Analysing the context dependence of receptive fields in visual cortex. ICANN 1998 Perspectives in Neural Computing 343–348 (Springer, London, 1998).
Continuous dynamics of neuronal delay adaptation. ICANN 1998 Perspectives in Neural Computing 355–360 (Springer, London, 1998).
Delay-induced multistable synchronization of biological oscillators. Physical Review E 57, 2150–2162 (1998).
Irregular synchronous activity in stochastically-coupled networks of integrate-and-fire neurons. Network 9, 333-344 (1998).
Orientation contrast enhancement modulated by differential long-range interaction in visual cortex. CNS 1997 361–366 (Plenum Press New York and London, 1998).
Orientation preference geometry modulates nonclassical receptive field properties. Proceedings of the 26th Göttingen Neurobiology Conference 1998 759 (1998).
Geometry of orientation preference map determines nonclassical receptive field properties. ICANN 1997 Artificial Neural Networks 231–236 (Springer, Berlin/Heidelberg, 1997).
Identifying oscillatory and stochastic neuronal behavior with high temporal precision in macaque monkey visual cortex. CNS 1996 Proceedings of the Conference on Computational Neuroscience () 293–298 (Kluwer Academic Publishers,f Boston, Dordrecht, London, 1997).
Orientation contrast sensitivity from long-range interactions in visual cortex. Proceedings of the 25th Göttingen Neurobiology Conference 61 (1997).
Komplexe räumliche Dynamik und Phasenclustering in strukturierten pulsgekoppelten neuronalen Netzen. Frühjahrstagung: Verhandlungen der Deutschen Physikalischen Gesellschaft 1339 (1996).
Orientation contrast sensitivity from long-range interactions in visual cortex. NIPS 1996: Advances in Neural Information Processing Systems 9 90–96 (MIT Press Boston, 1996).
Multistable feature binding with noisy integrate-and-fire neurons. ICANN 1995 Proceedings of the International Conference on Articifical Neural Networks 1, 549–554 (EC2 & Cie, Paris, 1995).
Multistable phase-clustering in networks of spiking neurons. CNS 1994: Proceedings of the Conference on Computational Neuroscience 293–298 (Kluwer Academic Publishers, 1995).
Phasendichtedynamik pulsgekoppelter Oszillatoren mit Delay. Frühjahrstagung DPG: Verhandlungen der Deutschen Physikalischen Gesellschaft 1107 (1995).
Synchronization induced by temporal delays in pulse-coupled oscillators. Physical Review Letters 74 (9), 1570–1573 (1995).
Using the neuronal time structure for information processing: multistability in pulse coupled neurons with delay. Proceedings of the 23rd Göttingen Neurobiology Conference 1995 500 (1995).
Multiple phase clustering of globally pulse coupled neurons with delay. ICANN 1994 Proceedings of the International Conference on Articifical Neural Networks 1063–1066 (Springer Verlag Berlin, 1994).
Synchronisation, Desynchronisation und Gruppenbildung pulsgekoppelter Oszillatoren mit verzögerter Wechselwirkung. Frühjahrstagung DPG: Verhandlungen der Deutschen Physikalischen Gesellschaft 975 (1994).