Learning to attend: Modeling the shaping of selectivity in infero-temporal cortex in a categorization task

Biological Cybernetics

Volumn 94, Issue 5, 2006, Pages 351-365

  Szabo, Miruna ^a,b   Deco, Gustavo ^c,d   Fusi, Stefano ^e   Del Giudice, Paolo ^f   Mattia, Maurizio ^f   Stetter, Martin ^a  

^a SIEMENS AG   (Germany)

^b TECHNICAL UNIVERSITY OF MUNICH   (Germany)

^c INSTITUCIÓ CATALANA DE RECERCA I ESTUDIS AVANÇATS ICREA   (Spain)

^d UNIVERSITAT POMPEU FABRA   (Spain)

^e Institute of Neuroinformatics Zurich   (Switzerland)

^f ISTITUTO SUPERIORE DI SANITÀ   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

COGNITIVE SYSTEMS; ENZYME INHIBITION; FUNCTIONS; MATHEMATICAL MODELS;

INFERO-TEMPORAL CORTEX (ITC); PLASTIC SYNAPSES; PREFRONTAL CORTEX (PFC);

NEUROLOGY;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; BIOLOGICAL MODEL; BRAIN CORTEX; LEARNING; NERVE CELL; NERVE CELL PLASTICITY; NERVE TRACT; PATTERN RECOGNITION; PHYSIOLOGY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CEREBRAL CORTEX; LEARNING; MODELS, NEUROLOGICAL; NEURAL PATHWAYS; NEURONAL PLASTICITY; NEURONS; PATTERN RECOGNITION, VISUAL;

EID: 33645966213     PISSN: 03401200     EISSN: 14320770     Source Type: Journal    
DOI: 10.1007/s00422-006-0054-z     Document Type: Article

References (35)

1. Almeida R, Deco G, Stetter M (2004) Modular biased-competition and cooperation: a candidate mechanism for selective working memory. Eur J Neurosci 20:2789-2803
2. Amit DJ, Brunel N (1997a) Dynamics of a recurrent network of spiking neurons before and following learning. Netw Comput Neural Syst 8:373-404
3. Amit DJ. Brunel N (1997b) Model of global spontaneous activity and local structured (learned) delay activity during delay periods in cerebral cortex. Cereb Cortex 7:237-252
4. Amit J, Fusi S (1994) Dynamic learning in neural networks with material synapses. Neural Comput 6:957
5. Asaad WF, Rainer G, Miller EK (1998) Neural activity in the primate prefrontal cortex during associative learning. Neuron 21:1399-1407
6. Brunel N, Wang XJ (2001) Effects of neuromodulation in a cortical network model of object working memory dominated by recurrent inhibition. Comput Neurosci 11:63-85
7. Chelazzi L (1998) Serial attention mechanisms in visual search: a critical look at the evidence. Psychol Res 62:195-219
8. Chelazzi L, Miller E, Duncan J, Desimone R (1993) A neural basis for visual search in inferior temporal cortex, Nature 363:345-347
9. Corchs S, Stetter M, Deco G (2003) System-level neuronal modeling of visual attentional mechanisms. Neuroimage 20:143-160
10. Deco G, Rolls ET (2003) Attention and working memory: a dynamical model of neuronal activity in the prefrontal cortex. Eur J Neurosci 18(8):2374-2390
11. Deco G, Rolls ET, Horwitz B (2004) "What" and "Where" in visual working memory: a computational neurodynamical perspective for integrating fmri and single-neuron data. J Cogn Neurosci 16:683-701
12. Del Giudice P, Fusi S, Mattia M (2003) Modeling the formation of working memory with networks of integrate-and-fire neurons connected by plastic synapses. J Physiol Paris 97:659-681
13. Desimone R, Duncan J (1995) Neural mechanisms of selective visual attention. Annu Rev Neurosci 18:193-222
14. Fine J, Jacobs R (2002) Comparing perceptual learning across tasks: a review. J Vis 2:190-203
15. Freedman DJ, Riesenhuber M, Poggio T, Miller EK (2003) A comparison of primate prefrontal and inferior temporal cortices during visual categorization. J Neurosci 23:5235-5246
16. Fusi S (2002) Hebbian spike-driven synaptic plasticity for learning patterns of mean firing rates. Biol Cybern 87:459-470
17. Fusi S, Annunziato M, Badoni D, Salamon A, Amit D (2000) Spike-driven synaptic plasticity: theory, simulation, VLSI-implementation. Neural Comput 12:2227-2258
18. Fusi S, Asaad WF, Miller EK, Wang X-J (2005) Learning and forgetting visuo-motor associations in changing environment (submitted)
19. Goldstone R (1998) Perceptual learning. Annu Rev Psychol 49:585-612
20. Miller K (1994) A model for the development of simple cell receptive fields and orientation columns through activity-dependent competition between on- and off-center inputs. J Neurosci 14:409-441
21. Moran J, Desimone R (1985) Selective attention gates visual processing in the extrastriate cortex. Science 229:782-784
22. Reynolds J, Desimone R (1999) The role of neural mechanisms of attention in solving the binding problem. Neuron 24:19-29
23. Roelfsema P, Van Ooyen A (2005) Attention-gated reinforcement learning of internal representations for classification. Neural Comput 17(10):2176-2214
24. Rolls ET, Deco G (2002) Computational neuroscience of vision. Oxford University Press, Oxford
25. Seung H (2003) Learning in spiking neural networks by reinforcement of stochastic synaptic transmission. Neuron 40(6): 1063-1073
26. Sigala N, Logothetis N (2002) Visual categorization shapes feature selectivity in the primate temporal cortex. Nature 415:318-320
27. Stetter M (2002) Exploration of cortical function. Kluwer, Dordrecht
28. Stetter M, Müller M, Lang EW (1994) Neural network model for the coordinated formation of orientation preference and orientation selectivity maps. Phys Rev E 50:4167-4181
29. Stetter M, Lang EW, Obermayer K (1998) Unspecific long-term potentiation can evoke functional segregation in a model of area 17. NeuroReport 9:2697-2702
30. Sutton RS, Barto AG (1998) Reinforcement learning: an introduction. MIT Press, Cambridge
31. Szabo M, Almeida R, Deco G, Stetter M (2004) Cooperation and biased competition model can explain attentional filtering in the prefrontal cortex. Eur J Neurosci 19(7): 1969-1977
32. Szabo M, Almeida R, Deco G, Stetter M (2005) A neuronal model for the shaping of feature selectivity in IT by visual categorization. Neurocomputing 65-66:195-201
33. Tomita H, Ohbayashi M, Nakahara K, Hasegawa I, Miyashita Y (1999) Top-down signal from prefrontal cortex in executive control of memory retrieval. Nature 401:699-703
34. Wang X-J (2002) Probabilistic decision making by slow reverberation in cortical circuits. Neuron 36:955-968
35. Williams R (1992) Simple statistical gradient-following algorithms for connectionist reinforcement learning. Machine Learn 8:229-256