Embedding Responses in Spontaneous Neural Activity Shaped through Sequential Learning

PLoS Computational Biology

Volumn 9, Issue 3, 2013, Pages

  Kurikawa, Tomoki ^a   Kaneko, Kunihiko ^a  

^a UNIVERSITY OF TOKYO   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ASSOCIATIVE PROCESSING; BIFURCATION (MATHEMATICS); BRAIN; DYNAMICAL SYSTEMS; DYNAMICS;

ASSOCIATIVE MEMORY MODELS; DYNAMICAL SYSTEM THEORY; EMBEDDINGS; EXTERNAL STIMULUS; LEARNING PROCESS; NEURAL ACTIVITY; NEURAL DYNAMICS; SEQUENTIAL LEARNING; SPATIO-TEMPORAL STRUCTURES; SPONTANEOUS ACTIVITY;

NEURONS;

ARTICLE; ASSOCIATIVE MEMORY; BRAIN FUNCTION; LEARNING; LEARNING ALGORITHM; MATHEMATICAL MODEL; MEMORY CONSOLIDATION; NERVE CELL NETWORK; RECALL; SEQUENTIAL LEARNING; SPONTANEOUS NEURAL ACTIVITY; STATE DEPENDENT LEARNING; SYSTEMS THEORY;

EID: 84875970326     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1002943     Document Type: Article

References (56)

1. Hubel DH, Wiesel TN, (1962) Receptive fields, binocular interaction and functional architecture in the cat's visual cortex. J physiol 160: 106-54.
2. Tusa RJ, Palmer LA, Rosenquist AC, (1978) The retinotopic organization of area 17 (striate cortex) in the cat. J comp neurol 177: 213-35.
3. Merzenich MM, Knight PL, Roth GL, (1975) Representation of cochlea within primary auditory cortex in the cat. J neurophysiol 38: 231-49.
4. Miyashita Y, (1988) Neuronal correlate of visual associative long-term memory in the primate temporal cortex. Nature 335: 817-820.
5. Fujiwara J, Tobler PN, Taira M, Iijima T, Tsutsui KI, (2009) A parametric relief signal in human ventrolateral prefrontal cortex. NeuroImage 44: 1163-70.
6. Friederici AD, (2003) The Role of Left Inferior Frontal and Superior Temporal Cortex in Sentence Comprehension: Localizing Syntactic and Semantic Processes. Cereb Cortex 13: 170-177.
7. Ben-Yishai R, Bar-Or RL, Sompolinsky H, (1995) Theory of orientation tuning in visual cortex. Proc Natl Acad Sci USA 92: 3844-3848.
8. Durstewitz D, Kelc M, Gunturkun O, (1999) A Neurocomputational Theory of the Dopaminergic Modulation of Working Memory Functions. J Neurosci 19: 2807-2822.
9. Willshaw DJ, Buneman OP, Longuet-higgins HC, (1969) Non-Holographic Associative Memory. Nature 222: 960-962.
10. Hopfield JJ, (1984) Neurons with graded response have collective computational properties like those of two-state neurons. Proc Natl Acad Sci USA 81: 3088-3092.
11. Amit DJ (1992) Modeling Brain Function: The World of Attractor Neural Networks. Cambridge: Cambridge University Press. 504 p.
12. Maass W, Natschläger T, Markram H, (2002) Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations. Neural Comput 14: 2531-2560.
13. Rosenblatt F, (1958) The perceptron: A probabilistic model for information storage and organization in the brain. Psychol Rev 65.
14. Rumelhart DE, Mcclelland JL (1986). Parallel distributed processing: explorations in the microstructure of cognition. Volume 1. Foundations of Research. Cambridge (Massachusetts): MIT Press.
15. Gardner E, (1988) The space of interactions in neural network models. J Phys A: Math Gen 21: 257-270.
16. Dayan P, Abbott LF (2001) Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. Cambridge, MA: MIT Press.
17. Fox MD, Raichle ME, (2007) Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci 8: 700-711.
18. Deco G, Jirsa VK, McIntosh AR, (2011) Emerging concepts for the dynamical organization of resting-state activity in the brain. Nat Rev Neurosci 12: 43-56.
19. Destexhe A, Contreras D, (2006) Neuronal computations with stochastic network states. Science (New York, NY) 314: 85-90.
20. Arieli A, Sterkin A, Grinvald A, Aertsen A, (1996) Dynamics of Ongoing Activity: Explanation of the Large Variability in Evoked Cortical Responses. Science 273: 1868-1871.
21. Kisley MA, Gerstein GL, (1999) Trial-to-trial variability and state-dependent modulation of auditory-evoked responses in cortex. J neurosci 19: 10451-60.
22. Linkenkaer-HansenK, Nikulin VV, Palva S, Ilmoniemi RJ, Palva JM, (2004) Prestimulus oscillations enhance psychophysical performance in humans. J neurosci 24: 10186-90.
23. Mathewson KE, Gratton G, Fabiani M, Beck DM, Ro T, (2009) To See or Not to See: Prestimulus Phase Predicts Visual Awareness. Neuroscience 29: 2725-2732.
24. Amit DJ, Brunel N, (1997) Model of global spontaneous activity and local structured activity during delay periods in the cerebral cortex. Cereb Cortex 7: 237-252.
25. Amit D, Brunel N, (1997) Dynamics of a recurrent network of spiking neurons before and following learning. Network: Computation in Neural Systems 8: 373-404.
26. Brunel N, Hakim V, (1999) Fast Global Oscillations in Networks of Integrate-and-Fire Neurons with Low Firing Rates. Neural Comput 11: 1621-1671.
27. Brunel N, (2003) Dynamics and Plasticity of Stimulus-selective Persistent Activity in Cortical Network Models. Cereb Cortex 13: 1151-1161.
28. Petermann T, Thiagarajan TC, Lebedev MA, Nicolelis MAL, Chialvo DR, et al. (2009) Spontaneous cortical activity in awake monkeys composed of neuronal avalanches. Proc Natl Acad Sci USA 106: 15921-6.
29. Marre O, Yger P, Davison AP, Fregnac Y, (2009) Reliable Recall of Spontaneous Activity Patterns in Cortical Networks. J neurosci 29: 14596-14606.
30. Rajan K, Abbott L, Sompolinsky H, (2010) Stimulus-dependent suppression of chaos in recurrent neural networks. Phys Rev E 82: 1-5.
31. Lewis CM, Baldassarre A, Committeri G, Romani GL, Corbetta M, (2009) Learning sculpts the spontaneous activity of the resting human brain. Proc Natl Acad Sci USA 106: 17558-63.
32. Berkes P, Orbán G, Lengyel M, Fiser J, (2011) Spontaneous cortical activity reveals hallmarks of an optimal internal model of the environment. Science (New York, NY) 331: 83-7.
33. Kurikawa T, Kaneko K, (2011) Learning Shapes Spontaneous Activity Itinerating over Memorized States. PLoS ONE 6: e17432.
34. Kurikawa T, Kaneko K, (2012) Associative memory model with spontaneous neural activity. Europhys Lett 98: 48002.
35. Kenet T, Bibitchkov D, Tsodyks M, Grinvald A, Arieli A, (2003) Spontaneously emerging cortical representations of visual attributes. Nature 425: 954-956.
36. MacLean JN, Watson BO, Aaron GB, Yuste R, (2005) Internal Dynamics Determine the Cortical Response to Thalamic Stimulation. Neuron 48: 811-823.
37. Luczak A, Bartho P, Harris KD, (2009) Spontaneous Events Outline the Realm of Possible Sensory Responses in Neocortical Populations. Neuron 62: 413-425.
38. Nadal JP, Toulouse G, Changeux JP, Dehaene S, (1986) Networks of Formal Neurons and Memory Palimpsests. Europhys Lett 1: 535-542.
39. Mézard M, Nadal J, Toulouse G, (1986) Solvable models of working memories. J Physique 47: 1457-1462.
40. Parisi G, (1986) A memory which forgets. J Phys A: Math Gen 19: L617-L620.
41. Mattis D, (1976) Solvable spin systems with random interactions. Phys Lett A 56: 421-422.
42. Fusi S, (2002) Hebbian spike-driven synaptic plasticity for learning patterns of mean firing rates. Biol Cybern 87: 459-470.
43. Amit DJ, Mongillo G, (2003) Spike-driven synaptic dynamics generating working memory states. Neural Comput 15: 565-596.
44. Luczak A, Bartho P, Marguet SL, Buzsaki G, Harris KD, (2007) Sequential structure of neocortical spontaneous activity in vivo. Proceedings of the National Academy of Sciences 104: 347-352.
45. Tsodyks M, Kenet T, Grinvald A, Arieli A, (1999) Linking Spontaneous Activity of Single Cortical Neurons and the Underlying Functional Architecture. Science 286: 1943-1946.
46. Sakata S, Harris KD, (2009) Laminar Structure of Spontaneous and Sensory-Evoked Population Activity in Auditory Cortex. Neuron 64: 404-418.
47. Tsuda I, (1992) Dynamic link of memoryChaotic memory map in nonequilibrium neural networks. Neural Netw 5: 313-326.
48. Kaneko K, Tsuda I, (2003) Chaotic itinerancy. Chaos 13: 926-36.
49. Rabinovich MI, Huerta R, Varona P, Afraimovich VS, (2008) Transient Cognitive Dynamics, Metastability, and Decision Making. PLoS Comput Biol 4: e1000072-e1000072.
50. Jaeger H, Haas H, (2004) Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication. Science 304: 78-80.
51. Ganguli S, Huh D, Sompolinsky H, (2008) Memory traces in dynamical systems. Proc Natl Acad Sci USA 105: 18970-5.
52. Falconbridge MS, Stamps RL, Badcock DR, (2006) A simple Hebbian/anti-Hebbian network learns the sparse, independent components of natural images. Neural comput 18: 415-29.
53. Destexhe A, Marder E, (2004) Plasticity in single neuron and circuit computations. Nature 431: 789-795.
54. Kawato M, Gomi H, (1992) A computational model of four regions of the cerebellum based on feedback-error learning. Biol Cybern 68: 95-103.
55. Wolpert D, Kawato M, (1998) Multiple paired forward and inverse models for motor control. Neural Netw 11: 1317-1329.
56. von Bremen HF, Udwadia FE, Proskurowski W, (1997) An efficient QR based method for the computation of Lyapunov exponents. Physica D 101: 1-16.