| Year |
Citation |
Score |
| 2023 |
Maith O, Baladron J, Einhäuser W, Hamker FH. Exploration behavior after reversals is predicted by STN-GPe synaptic plasticity in a basal ganglia model. Iscience. 26: 106599. PMID 37250300 DOI: 10.1016/j.isci.2023.106599 |
0.539 |
|
| 2021 |
Novin S, Fallah A, Rashidi S, Beuth F, Hamker FH. A neuro-computational model of visual attention with multiple attentional control sets. Vision Research. 189: 104-118. PMID 34749237 DOI: 10.1016/j.visres.2021.08.009 |
0.332 |
|
| 2021 |
Maith O, Schwarz A, Hamker FH. Optimal attention tuning in a neuro-computational model of the visual cortex-basal ganglia-prefrontal cortex loop. Neural Networks : the Official Journal of the International Neural Network Society. 142: 534-547. PMID 34314999 DOI: 10.1016/j.neunet.2021.07.008 |
0.415 |
|
| 2019 |
Bergelt J, Hamker FH. Spatial updating of attention across eye movements: A neuro-computational approach. Journal of Vision. 19: 10. PMID 31323096 DOI: 10.1167/19.7.10 |
0.527 |
|
| 2017 |
Ziesche A, Bergelt J, Deubel H, Hamker FH. Pre- and post-saccadic stimulus timing in Saccadic Suppression of Displacement - a computational model. Vision Research. PMID 28709922 DOI: 10.1016/j.visres.2017.06.007 |
0.433 |
|
| 2017 |
Hartmann TS, Zirnsak M, Marquis M, Hamker FH, Moore T. Two Types of Receptive Field Dynamics in Area V4 at the Time of Eye Movements? Frontiers in Systems Neuroscience. 11: 13. PMID 28377700 DOI: 10.3389/Fnsys.2017.00013 |
0.775 |
|
| 2016 |
Bergelt J, Hamker FH. Suppression of displacement detection in the presence and absence of eye movements: a neuro-computational perspective. Biological Cybernetics. PMID 26733211 DOI: 10.1007/s00422-015-0677-z |
0.438 |
|
| 2016 |
Hamker F, Schwarz A. A quantitative neuro-computational model of attentive receptive field changes in area MT Journal of Vision. 16: 939. DOI: 10.1167/16.12.939 |
0.4 |
|
| 2015 |
Lappe M, Hamker FH. Peri-saccadic compression to two locations in a two-target choice saccade task. Frontiers in Systems Neuroscience. 9: 135. PMID 26500510 DOI: 10.3389/fnsys.2015.00135 |
0.737 |
|
| 2015 |
Hamker F, Beuth F. A mechanistic cortical microcircuit of attention for amplification, normalization and suppression. Journal of Vision. 15: 1254. PMID 26326942 DOI: 10.1167/15.12.1254 |
0.389 |
|
| 2015 |
Beuth F, Hamker F. The relation of object substitution masking (OSM) and attention dynamics: A neuro-computational modeling study. Journal of Vision. 15: 1229. PMID 26326917 DOI: 10.1167/15.12.1229 |
0.507 |
|
| 2015 |
Teichmann M, Schuster J, Hamker F. A computational model of the perisaccadic updating of spatial attention. Journal of Vision. 15: 69. PMID 26325757 DOI: 10.1167/15.12.69 |
0.39 |
|
| 2015 |
Beuth F, Hamker FH. A mechanistic cortical microcircuit of attention for amplification, normalization and suppression. Vision Research. PMID 25883048 DOI: 10.1016/j.visres.2015.04.004 |
0.454 |
|
| 2015 |
Ebner C, Schroll H, Winther G, Niedeggen M, Hamker FH. Open and closed cortico-subcortical loops: A neuro-computational account of access to consciousness in the distractor-induced blindness paradigm. Consciousness and Cognition. 35: 295-307. PMID 25802010 DOI: 10.1016/j.concog.2015.02.007 |
0.326 |
|
| 2014 |
Ziesche A, Hamker FH. Brain circuits underlying visual stability across eye movements-converging evidence for a neuro-computational model of area LIP. Frontiers in Computational Neuroscience. 8: 25. PMID 24653691 DOI: 10.3389/fncom.2014.00025 |
0.484 |
|
| 2014 |
Beuth F, Jamalian A, Hamker FH. How visual attention and suppression facilitate object recognition? Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8681: 459-466. DOI: 10.1007/978-3-319-11179-7-58 |
0.33 |
|
| 2012 |
Teichmann M, Wiltschut J, Hamker F. Learning invariance from natural images inspired by observations in the primary visual cortex. Neural Computation. 24: 1271-96. PMID 22295987 DOI: 10.1162/NECO_a_00268 |
0.362 |
|
| 2011 |
Kiefer M, Ansorge U, Haynes JD, Hamker F, Mattler U, Verleger R, Niedeggen M. Neuro-cognitive mechanisms of conscious and unconscious visual perception: From a plethora of phenomena to general principles. Advances in Cognitive Psychology / University of Finance and Management in Warsaw. 7: 55-67. PMID 22253669 DOI: 10.2478/V10053-008-0090-4 |
0.45 |
|
| 2011 |
Zirnsak M, Gerhards RG, Kiani R, Lappe M, Hamker FH. Anticipatory saccade target processing and the presaccadic transfer of visual features. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 31: 17887-91. PMID 22159103 DOI: 10.1523/Jneurosci.2465-11.2011 |
0.802 |
|
| 2011 |
Ziesche A, Hamker FH. A computational model for the influence of corollary discharge and proprioception on the perisaccadic mislocalization of briefly presented stimuli in complete darkness. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 31: 17392-405. PMID 22131401 DOI: 10.1523/JNEUROSCI.3407-11.2011 |
0.464 |
|
| 2011 |
Zirnsak M, Beuth F, Hamker FH. Split of spatial attention as predicted by a systems-level model of visual attention. The European Journal of Neuroscience. 33: 2035-45. PMID 21645099 DOI: 10.1111/J.1460-9568.2011.07718.X |
0.821 |
|
| 2011 |
Hamker FH, Zirnsak M, Ziesche A, Lappe M. Computational models of spatial updating in peri-saccadic perception. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences. 366: 554-71. PMID 21242143 DOI: 10.1098/Rstb.2010.0229 |
0.79 |
|
| 2010 |
Zirnsak M, Hamker FH. Attention alters feature space in motion processing. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 30: 6882-90. PMID 20484630 DOI: 10.1523/Jneurosci.3543-09.2010 |
0.77 |
|
| 2010 |
Zirnsak M, Lappe M, Hamker FH. The spatial distribution of receptive field changes in a model of peri-saccadic perception: predictive remapping and shifts towards the saccade target. Vision Research. 50: 1328-37. PMID 20152853 DOI: 10.1016/J.Visres.2010.02.002 |
0.818 |
|
| 2010 |
Hamker FH, Zirnsak M, Lappe M. Dynamic receptive field effects predicted by a saccade target theory of visual perception Journal of Vision. 7: 319-319. DOI: 10.1167/7.9.319 |
0.794 |
|
| 2010 |
Hamker FH, Zirnsak M, Calow D, Lappe M. The perisacadic compression of visual space - what may it have to do with spatial attention? Journal of Vision. 6: 105-105. DOI: 10.1167/6.6.105 |
0.775 |
|
| 2010 |
Zirnsak M, Hamker F. Global feature-based attention distorts feature space Journal of Vision. 10: 190-190. DOI: 10.1167/10.7.190 |
0.75 |
|
| 2009 |
Dubois J, Hamker FH, VanRullen R. Attentional selection of noncontiguous locations: the spotlight is only transiently "split". Journal of Vision. 9: 3.1-11. PMID 19757881 DOI: 10.1167/9.5.3 |
0.756 |
|
| 2009 |
Vitay J, Hamker F. Basal ganglia and memory retrieval during delayed match-to-sample and non-match-to-sample tasks Bmc Neuroscience. 10. DOI: 10.1186/1471-2202-10-S1-P162 |
0.322 |
|
| 2008 |
Hamker FH, Zirnsak M, Lappe M. About the influence of post-saccadic mechanisms for visual stability on peri-saccadic compression of object location. Journal of Vision. 8: 1.1-13. PMID 19146302 DOI: 10.1167/8.14.1 |
0.799 |
|
| 2008 |
Georg K, Hamker FH, Lappe M. Influence of adaptation state and stimulus luminance on peri-saccadic localization. Journal of Vision. 8: 15.1-11. PMID 18318618 DOI: 10.1167/8.1.15 |
0.676 |
|
| 2008 |
Hamker FH, Zirnsak M, Calow D, Lappe M. The peri-saccadic perception of objects and space. Plos Computational Biology. 4: e31. PMID 18282086 DOI: 10.1371/Journal.Pcbi.0040031 |
0.817 |
|
| 2007 |
Hamker FH. The mechanisms of feature inheritance as predicted by a systems-level model of visual attention and decision making. Advances in Cognitive Psychology / University of Finance and Management in Warsaw. 3: 111-23. PMID 20517503 DOI: 10.2478/v10053-008-0019-y |
0.338 |
|
| 2006 |
Hamker FH, Zirnsak M. V4 receptive field dynamics as predicted by a systems-level model of visual attention using feedback from the frontal eye field. Neural Networks : the Official Journal of the International Neural Network Society. 19: 1371-82. PMID 17014990 DOI: 10.1016/J.Neunet.2006.08.006 |
0.819 |
|
| 2005 |
Hamker FH. 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 (New York, N.Y. : 1991). 15: 431-47. PMID 15749987 DOI: 10.1093/cercor/bhh146 |
0.463 |
|
| 2005 |
Hamker FH. A computational model of visual stability and change detection during eye movements in real-world scenes Visual Cognition. 12: 1161-1176. DOI: 10.1080/13506280444000698 |
0.354 |
|
| 2004 |
Hamker FH. A dynamic model of how feature cues guide spatial attention. Vision Research. 44: 501-21. PMID 14680776 DOI: 10.1016/j.visres.2003.09.033 |
0.393 |
|
| 2004 |
Hamker FH, Zirnsak M, Lappe M. A computational model of saccadic mislocalization based on spatial reentry Journal of Vision. 4: 736-736. DOI: 10.1167/4.8.736 |
0.664 |
|
| 2003 |
Hamker FH. The reentry hypothesis: linking eye movements to visual perception. Journal of Vision. 3: 808-16. PMID 14765963 DOI: 10:1167/3.11.14 |
0.383 |
|
| 2003 |
Hamker FH. A dynamic computational model of goal-directed visual perception Journal of Vision. 3: 2a. DOI: 10.1167/3.9.2 |
0.319 |
|
| 2002 |
Hamker F, VanRullen R. The time course of attentional selection among competing locations Journal of Vision. 2: 7a. DOI: 10.1167/2.7.7 |
0.695 |
|
| Low-probability matches (unlikely to be authored by this person) |
| 2018 |
Hamker F. Neuro-computational models of spatial updating Journal of Vision. 18: 1370. DOI: 10.1167/18.10.1370 |
0.299 |
|
| 2007 |
Hamker FH, Wiltschut J. 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 (Bristol, England). 18: 249-66. PMID 17926194 DOI: 10.1080/09548980701661210 |
0.286 |
|
| 2021 |
Teichmann M, Larisch R, Hamker FH. Performance of biologically grounded models of the early visual system on standard object recognition tasks. Neural Networks : the Official Journal of the International Neural Network Society. 144: 210-228. PMID 34507042 DOI: 10.1016/j.neunet.2021.08.009 |
0.282 |
|
| 2005 |
Hamker FH. Modeling attention: From computational neuroscience to computer vision Lecture Notes in Computer Science. 3368: 118-132. |
0.282 |
|
| 2023 |
Burkhardt M, Bergelt J, Gönner L, Dinkelbach HÜ, Beuth F, Schwarz A, Bicanski A, Burgess N, Hamker FH. A large-scale neurocomputational model of spatial cognition integrating memory with vision. Neural Networks : the Official Journal of the International Neural Network Society. 167: 473-488. PMID 37688954 DOI: 10.1016/j.neunet.2023.08.034 |
0.279 |
|
| 2006 |
Hamker FH. Modeling feature-based attention as an active top-down inference process. Bio Systems. 86: 91-9. PMID 16843589 DOI: 10.1016/j.biosystems.2006.03.010 |
0.279 |
|
| 2014 |
Antonelli M, Gibaldi A, Beuth F, Duran AJ, Canessa A, Chessa M, Solari F, Del Pobil AP, Hamker F, Chinellato E, Sabatini SP. A hierarchical system for a distributed representation of the peripersonal space of a humanoid robot Ieee Transactions On Autonomous Mental Development. 6: 259-273. DOI: 10.1109/Tamd.2014.2332875 |
0.269 |
|
| 2016 |
Sharpee TO, Destexhe A, Kawato M, Sekulić V, Skinner FK, Wójcik DK, Chintaluri C, Cserpán D, Somogyvári Z, Kim JK, Kilpatrick ZP, Bennett MR, Josić K, Elices I, Arroyo D, ... ... Hamker FH, et al. 25th Annual Computational Neuroscience Meeting: CNS-2016 Bmc Neuroscience. 17: 54. PMID 27534393 DOI: 10.1186/S12868-016-0283-6 |
0.264 |
|
| 2020 |
Nassour J, Duy Hoa T, Atoofi P, Hamker F. Concrete Action Representation Model: From Neuroscience to Robotics Ieee Transactions On Cognitive and Developmental Systems. 12: 272-284. DOI: 10.1109/TCDS.2019.2896300 |
0.264 |
|
| 2011 |
Hamker FH, Ziesche A. Computational mechanisms of predictive remapping and visual stability Journal of Vision. 11: 523-523. DOI: 10.1167/11.11.523 |
0.262 |
|
| 2004 |
Hamker FH. Predictions of a model of spatial attention using sum- and max-pooling functions Neurocomputing. 56: 329-343. DOI: 10.1016/j.neucom.2003.09.006 |
0.259 |
|
| 2010 |
Hamker FH, Ziesche A, Deubel H. Dynamic recurrent processing for coordinate transformation explains saccadic suppression of image displacement Journal of Vision. 10: 522-522. DOI: 10.1167/10.7.522 |
0.255 |
|
| 2012 |
Trapp S, Schroll H, Hamker FH. Open and closed loops: A computational approach to attention and consciousness. Advances in Cognitive Psychology / University of Finance and Management in Warsaw. 8: 1-8. PMID 23853675 DOI: 10.5709/Acp-0096-Y |
0.251 |
|
| 2018 |
Neumann WJ, Schroll H, de Almeida Marcelino AL, Horn A, Ewert S, Irmen F, Krause P, Schneider GH, Hamker F, Kühn AA. Functional segregation of basal ganglia pathways in Parkinson's disease. Brain : a Journal of Neurology. PMID 30084974 DOI: 10.1093/brain/awy206 |
0.243 |
|
| 2014 |
Verleger R, Koerbs A, Graf J, ?migasiewicz K, Schroll H, Hamker FH. Patients with Parkinson׳s disease are less affected than healthy persons by relevant response-unrelated features in visual search. Neuropsychologia. 62: 38-47. PMID 25038550 DOI: 10.1016/J.Neuropsychologia.2014.07.004 |
0.241 |
|
| 2005 |
Hamker FH. How the detection of objects in natural scenes constrains attention in time Neurobiology of Attention. 600-604. DOI: 10.1016/B978-012375731-9/50102-6 |
0.232 |
|
| 2005 |
Hamker FH. A population-based inference framework for feature-based attention in natural scenes Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3704: 147-156. DOI: 10.1007/11565123_15 |
0.217 |
|
| 2020 |
Nassour J, Amirabadi HG, Weheabby S, Ali AA, Lang H, Hamker F. A Robust Data-Driven Soft Sensory Glove for Human Hand Motions Identification and Replication Ieee Sensors Journal. 20: 12972-12979. DOI: 10.1109/JSEN.2020.3001982 |
0.215 |
|
| 2010 |
Vitay J, Hamker FH. A computational model of Basal Ganglia and its role in memory retrieval in rewarded visual memory tasks. Frontiers in Computational Neuroscience. 4. PMID 20725505 DOI: 10.3389/fncom.2010.00013 |
0.215 |
|
| 2016 |
Teichmann M, Hamker F. Biologically plausible Hebbian learning in deep neural networks: being more close to the nature than CNNs. Journal of Vision. 16: 178. DOI: 10.1167/16.12.178 |
0.214 |
|
| 2015 |
Kermani Kolankeh A, Teichmann M, Hamker FH. Competition improves robustness against loss of information. Frontiers in Computational Neuroscience. 9: 35. PMID 25859211 DOI: 10.3389/fncom.2015.00035 |
0.206 |
|
| 1996 |
Hamker F, Gross HM. Region finding for attention control in consideration of subgoals Neural Network World. 6: 305-313. |
0.2 |
|
| 1970 |
Hamker F, Schroll H, Vitay J. Basal ganglia contribution to cognitive and motor functions: A computational model of working memory and decision. Frontiers in Behavioral Neuroscience. DOI: 10.3389/Conf.Neuro.08.2009.01.020 |
0.19 |
|
| 2021 |
Larisch R, Gönner L, Teichmann M, Hamker FH. Sensory coding and contrast invariance emerge from the control of plastic inhibition over emergent selectivity. Plos Computational Biology. 17: e1009566. PMID 34843455 DOI: 10.1371/journal.pcbi.1009566 |
0.19 |
|
| 2020 |
Tran DH, Hamker F, Nassour J. A Humanoid Robot Learns to Recover Perturbation During Swinging Motion Ieee Transactions On Systems, Man, and Cybernetics: Systems. 50: 3701-3712. DOI: 10.1109/TSMC.2018.2884619 |
0.181 |
|
| 2009 |
Wiltschut J, Hamker FH. Efficient coding correlates with spatial frequency tuning in a model of V1 receptive field organization. Visual Neuroscience. 26: 21-34. PMID 19203427 DOI: 10.1017/S0952523808080966 |
0.164 |
|
| 2005 |
Hamker FH. The emergence of attention by population-based inference and its role in distributed processing and cognitive control of vision Computer Vision and Image Understanding. 100: 64-106. DOI: 10.1016/j.cviu.2004.09.005 |
0.157 |
|
| 2017 |
Gönner L, Vitay J, Hamker FH. Predictive Place-Cell Sequences for Goal-Finding Emerge from Goal Memory and the Cognitive Map: A Computational Model. Frontiers in Computational Neuroscience. 11: 84. PMID 29075187 DOI: 10.3389/fncom.2017.00084 |
0.155 |
|
| 2015 |
Schroll H, Horn A, Gröschel C, Brücke C, Lütjens G, Schneider GH, Krauss JK, Kühn AA, Hamker FH. Differential contributions of the globus pallidus and ventral thalamus to stimulus-response learning in humans. Neuroimage. 122: 233-45. PMID 26220740 DOI: 10.1016/j.neuroimage.2015.07.061 |
0.153 |
|
| 2008 |
Vitay J, Hamker FH. Sustained activities and retrieval in a computational model of the perirhinal cortex. Journal of Cognitive Neuroscience. 20: 1993-2005. PMID 18416682 DOI: 10.1162/jocn.2008.20147 |
0.145 |
|
| 1997 |
Hamker FH, Gross HM. Object selection with dynamic neural maps Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1327: 920-924. |
0.144 |
|
| 2018 |
Villagrasa F, Baladron J, Vitay J, Schroll H, Antzoulatos EG, Miller EK, Hamker FH. On the role of cortex-basal ganglia interactions for category learning: A neuro-computational approach. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. PMID 30228231 DOI: 10.1523/JNEUROSCI.0874-18.2018 |
0.143 |
|
| 2022 |
Maith O, Dinkelbach HÜ, Baladron J, Vitay J, Hamker FH. BOLD Monitoring in the Neural Simulator ANNarchy. Frontiers in Neuroinformatics. 16: 790966. PMID 35392282 DOI: 10.3389/fninf.2022.790966 |
0.135 |
|
| 2022 |
Scholl C, Baladron J, Vitay J, Hamker FH. Enhanced habit formation in Tourette patients explained by shortcut modulation in a hierarchical cortico-basal ganglia model. Brain Structure & Function. PMID 35113242 DOI: 10.1007/s00429-021-02446-x |
0.127 |
|
| 2002 |
Hamker FH, Worcester J. Object detection in natural scenes by feedback Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2525: 398-407. |
0.125 |
|
| 2018 |
Schroll H, Horn A, Runge J, Lipp A, Schneider GH, Krauss JK, Hamker FH, Kühn AA. Reinforcement magnitudes modulate subthalamic beta band activity in patients with Parkinson's disease. Scientific Reports. 8: 8621. PMID 29872162 DOI: 10.1038/s41598-018-26887-3 |
0.124 |
|
| 2014 |
Vitay J, Hamker FH. Timing and expectation of reward: a neuro-computational model of the afferents to the ventral tegmental area. Frontiers in Neurorobotics. 8: 4. PMID 24550821 DOI: 10.3389/fnbot.2014.00004 |
0.119 |
|
| 2013 |
Schroll H, Hamker FH. Computational models of basal-ganglia pathway functions: focus on functional neuroanatomy. Frontiers in Systems Neuroscience. 7: 122. PMID 24416002 DOI: 10.3389/fnsys.2013.00122 |
0.112 |
|
| 2016 |
Schroll H, Hamker FH. Basal Ganglia dysfunctions in movement disorders: What can be learned from computational simulations. Movement Disorders : Official Journal of the Movement Disorder Society. PMID 27393040 DOI: 10.1002/mds.26719 |
0.11 |
|
| 2022 |
Meier JM, Perdikis D, Blickensdörfer A, Stefanovski L, Liu Q, Maith O, Dinkelbach HÜ, Baladron J, Hamker FH, Ritter P. Virtual deep brain stimulation: Multiscale co-simulation of a spiking basal ganglia model and a whole-brain mean-field model with The Virtual Brain. Experimental Neurology. 354: 114111. PMID 35569510 DOI: 10.1016/j.expneurol.2022.114111 |
0.108 |
|
| 2020 |
Baladron J, Hamker FH. Habit learning in hierarchical cortex - basal ganglia loops. The European Journal of Neuroscience. PMID 32237250 DOI: 10.1111/ejn.14730 |
0.107 |
|
| 2020 |
Goenner L, Maith O, Koulouri I, Baladron J, Hamker FH. A spiking model of basal ganglia dynamics in stopping behavior supported by Arkypallidal neurons. The European Journal of Neuroscience. PMID 33316152 DOI: 10.1111/ejn.15082 |
0.101 |
|
| 2015 |
Liebold B, Richter R, Teichmann M, Hamker FH, Ohler P. Human Capacities for Emotion Recognition and their Implications for Computer Vision I-Com. 14: 126-137. DOI: 10.1515/icom-2015-0032 |
0.097 |
|
| 2011 |
Schroll H, Vitay J, Hamker FH. P8 Functional contributions of basal ganglia pathways to stimulus-response learning in normal functioning and Parkinson’s Disease: A computational model Basal Ganglia. 1: 108. DOI: 10.1016/J.BAGA.2011.06.009 |
0.096 |
|
| 2020 |
Maith O, Villagrasa Escudero F, Dinkelbach HÜ, Baladron J, Horn A, Irmen F, Kühn AA, Hamker FH. A computational model-based analysis of basal ganglia pathway changes in Parkinson's disease inferred from resting-state fMRI. The European Journal of Neuroscience. PMID 32558966 DOI: 10.1111/ejn.14868 |
0.094 |
|
| 2012 |
Schroll H, Vitay J, Hamker FH. Working memory and response selection: a computational account of interactions among cortico-basalganglio-thalamic loops. Neural Networks : the Official Journal of the International Neural Network Society. 26: 59-74. PMID 22075035 DOI: 10.1016/j.neunet.2011.10.008 |
0.092 |
|
| 2022 |
Dinkelbach HÜ, Bouhlal BE, Vitay J, Hamker FH. Auto-Selection of an Optimal Sparse Matrix Format in the Neuro-Simulator ANNarchy. Frontiers in Neuroinformatics. 16: 877945. PMID 35676973 DOI: 10.3389/fninf.2022.877945 |
0.091 |
|
| 2017 |
Baladron J, Nambu A, Hamker FH. The subthalamic nucleus-external globus pallidus loop biases exploratory decisions towards known alternatives: A neuro-computational study. The European Journal of Neuroscience. PMID 28833676 DOI: 10.1111/ejn.13666 |
0.09 |
|
| 1996 |
Hamker FH, Gross HM. Region selection: segmentation, classification and task relevance in a single grouping mechanism Ieee International Conference On Neural Networks - Conference Proceedings. 3: 1540-1545. |
0.09 |
|
| 2014 |
Hamker F. Spatial Cognition of Humans and Brain-inspired Artificial Agents Ki - KüNstliche Intelligenz. 29: 83-88. DOI: 10.1007/s13218-014-0338-8 |
0.081 |
|
| 2023 |
Baladron J, Vitay J, Fietzek T, Hamker FH. The contribution of the basal ganglia and cerebellum to motor learning: A neuro-computational approach. Plos Computational Biology. 19: e1011024. PMID 37011086 DOI: 10.1371/journal.pcbi.1011024 |
0.079 |
|
| 2015 |
Vitay J, Dinkelbach HÜ, Hamker FH. ANNarchy: a code generation approach to neural simulations on parallel hardware. Frontiers in Neuroinformatics. 9: 19. PMID 26283957 DOI: 10.3389/fninf.2015.00019 |
0.075 |
|
| 2012 |
Dinkelbach HÜ, Vitay J, Beuth F, Hamker FH. Comparison of GPU- and CPU-implementations of mean-firing rate neural networks on parallel hardware. Network (Bristol, England). 23: 212-36. PMID 23140422 DOI: 10.3109/0954898X.2012.739292 |
0.075 |
|
| 2018 |
Atoofi P, Hamker FH, Nassour J. Learning of Central Pattern Generator Coordination in Robot Drawing. Frontiers in Neurorobotics. 12: 44. PMID 30083100 DOI: 10.3389/fnbot.2018.00044 |
0.07 |
|
| 2015 |
Schroll H, Beste C, Hamker FH. Combined lesions of direct and indirect basal ganglia pathways but not changes in dopamine levels explain learning deficits in patients with Huntington's disease. The European Journal of Neuroscience. 41: 1227-44. PMID 25778633 DOI: 10.1111/Ejn.12868 |
0.069 |
|
| 2017 |
Irmen F, Huebl J, Schroll H, Brücke C, Schneider GH, Hamker FH, Kühn AA. Subthalamic nucleus stimulation impairs emotional conflict adaptation in Parkinson's disease. Social Cognitive and Affective Neuroscience. PMID 28985419 DOI: 10.1093/scan/nsx090 |
0.068 |
|
| 2013 |
Verleger R, Schroll H, Hamker FH. The unstable bridge from stimulus processing to correct responding in Parkinson's disease. Neuropsychologia. 51: 2512-25. PMID 24051004 DOI: 10.1016/J.Neuropsychologia.2013.09.017 |
0.066 |
|
| 1998 |
Heinke D, Hamker FH. Comparing neural networks: a benchmark on growing neural gas, growing cell structures, and fuzzy ARTMAP. Ieee Transactions On Neural Networks / a Publication of the Ieee Neural Networks Council. 9: 1279-91. PMID 18255809 DOI: 10.1109/72.728377 |
0.064 |
|
| 2015 |
Baladron J, Hamker FH. A spiking neural network based on the basal ganglia functional anatomy. Neural Networks : the Official Journal of the International Neural Network Society. 67: 1-13. PMID 25863288 DOI: 10.1016/j.neunet.2015.03.002 |
0.062 |
|
| 1996 |
Hamker FH, Gross HM. Task-relevant relaxation network for visuo-motory systems Proceedings - International Conference On Pattern Recognition. 4: 406-410. DOI: 10.1109/ICPR.1996.547598 |
0.052 |
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| 2023 |
Baladron J, Vitay J, Fietzek T, Hamker FH. Correction: The contribution of the basal ganglia and cerebellum to motor learning: A neuro-computational approach. Plos Computational Biology. 19: e1011243. PMID 37347775 DOI: 10.1371/journal.pcbi.1011243 |
0.05 |
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| 2001 |
Hamker FH. Life-long learning cell structures--continuously learning without catastrophic interference. Neural Networks : the Official Journal of the International Neural Network Society. 14: 551-73. PMID 11411637 DOI: 10.1016/S0893-6080(01)00018-1 |
0.049 |
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| 2007 |
Vitay J, Hamker FH. On the role of dopamine in cognitive vision Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4840: 352-366. |
0.046 |
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| 2012 |
Hamker FH. Neural Learning of Cognitive Control Ki - KüNstliche Intelligenz. 26: 397-401. DOI: 10.1007/s13218-012-0210-7 |
0.043 |
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| 2014 |
Schroll H, Vitay J, Hamker FH. Dysfunctional and compensatory synaptic plasticity in Parkinson's disease. The European Journal of Neuroscience. 39: 688-702. PMID 24313650 DOI: 10.1111/ejn.12434 |
0.038 |
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| 2019 |
Kübler D, Schroll H, Hamker FH, Joutsa J, Buchert R, Kühn AA. The effect of dopamine on response inhibition in Parkinson's disease relates to age-dependent patterns of nigrostriatal degeneration. Parkinsonism & Related Disorders. PMID 30765262 DOI: 10.1016/J.Parkreldis.2019.02.003 |
0.029 |
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| 2021 |
Forch V, Hamker FH. Building and Understanding the Minimal Self. Frontiers in Psychology. 12: 716982. PMID 34899463 DOI: 10.3389/fpsyg.2021.716982 |
0.019 |
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| 2011 |
Vitay J, Hamker FH. A Neuroscientific View on the Role of Emotions in Behaving Cognitive Agents Ki - KüNstliche Intelligenz. 25: 235-244. DOI: 10.1007/s13218-011-0106-y |
0.016 |
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| 2020 |
Nassour J, Hamker FH, Cheng G. High-Performance Perpendicularly-Enfolded-Textile Actuators for Soft Wearable Robots: Design and Realization Ieee Transactions On Medical Robotics and Bionics. 2: 309-319. DOI: 10.1109/TMRB.2020.3012131 |
0.01 |
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| 2000 |
Paetz J, Hamker F, Thöne S. About the analysis of septic shock patient data Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1933: 130-137. |
0.01 |
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