Optimal Recall from Bounded Metaplastic Synapses: Predicting Functional Adaptations in Hippocampal Area CA3

PLoS Computational Biology

Volumn 10, Issue 2, 2014, Pages

  Savin, Cristina ^a   Dayan, Peter ^b   Lengyel, Máté ^a  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN; DIGITAL STORAGE; DYNAMICS;

AUTO-ASSOCIATIVE MEMORY; BIOLOGICAL CONSTRAINTS; FUNCTIONAL ADAPTATION; MEMORY RETRIEVAL; MEMORY STORAGE; METAPLASTICITY; NEURAL CIRCUITS; STORAGE AND RETRIEVALS; STORED PATTERN; THEORETICAL FRAMEWORK;

INFERENCE ENGINES;

ALGORITHM; ANIMAL CELL; ARTICLE; ASSOCIATIVE MEMORY; CONCEPTUAL FRAMEWORK; CONTROLLED STUDY; DYNAMICS; FEEDBACK SYSTEM; HIPPOCAMPAL CA3 REGION; HUMAN; HUMAN CELL; LEARNING; MATHEMATICAL MODEL; MEMORY CONSOLIDATION; MENTAL PERFORMANCE; MENTAL TASK; NERVE CELL MEMBRANE POTENTIAL; NERVE CELL NETWORK; NERVE CELL PLASTICITY; NERVE EXCITABILITY; NONHUMAN; OSCILLATION; POSTSYNAPTIC INHIBITION; PREDICTION; PRESYNAPTIC NERVE; RAT; RECALL; STATISTICS; SYNAPSE; ADAPTATION; ANIMAL; BIOLOGICAL MODEL; BIOLOGY; PHYSIOLOGY; PSYCHOLOGICAL MODEL; STATISTICAL MODEL;

ADAPTATION, PHYSIOLOGICAL; ALGORITHMS; ANIMALS; CA3 REGION, HIPPOCAMPAL; COMPUTATIONAL BIOLOGY; FEEDBACK, PHYSIOLOGICAL; HUMANS; MENTAL RECALL; MODELS, NEUROLOGICAL; MODELS, PSYCHOLOGICAL; MODELS, STATISTICAL; NEURONAL PLASTICITY; SYNAPSES;

EID: 84895764266     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1003489     Document Type: Article

References (97)

1. Treves A, Rolls ET, (1994) Computational analysis of the role of the hippocampus in memory. Hippocampus 4: 374-391.
2. Treves A, Skaggs WE, Barnes CA, (1996) How much of the hippocampus can be explained by functional constraints? Hippocampus 6: 666-674.
3. Amaral DG, (1993) Emerging principles of intrinsic hippocampal organization. Current opinion in neurobiology 3: 225-229.
4. Hopfield JJ, (1982) Neural networks and physical systems with emergent collective computational abilities. Proc Natl Acad Sci 76: 2554-2558.
5. Amit D, Gutfreund H, Sompolinsky H, (1985) Storing infinite numbers of patterns in a spin-glass model of neural networks. Phys Rev Lett 55: 1530-1533.
6. Amit D, Gutfreund H, Sompolinsky H, (1987) Information storage in neural networks with low levels of activity. Phys Rev A 35: 2293-2303.
7. Willshaw D, Buneman O, Longuet-Higgins H, (1969) Non-holographic associative memory. Nature 222: 960-962.
8. Hertz JA, Krogh AS, Palmer RG (1991) Introduction to the theory of neural computation, volume 1. Westview Press.
9. Treves A, Rolls ET, (1991) What determines the capacity of autoassociative memories in the brain? Network 2: 371-397.
10. Amit DJ, Fusi S, (1994) Learning in neural networks with material synapses. Neural Computation 6: 957-982.
11. Hebb D (1949) The organization of behavior. New York: Wiley.
12. Nakazawa K, Quirk MC, Chitwood RA, Watanabe M, Yeckel MF, et al. (2002) Requirement for hippocampal CA3 NMDA receptors in associative memory recall. Science 297: 211-8.
13. Wills TJ, Lever C, Cacucci F, Burgess N, O'Keefe J, (2005) Attractor dynamics in the hippocampal representation of the local environment. Science 308: 873-876.
14. Lengyel M, Kwag J, Paulsen O, Dayan P, (2005) Matching storage and recall: hippocampal spike timingdependent plasticity and phase response curves. Nature Neuroscience 8: 1677-1683.
15. Abbott LF, Nelson SB, (2000) Synaptic plasticity: taming the beast. Nature Neuroscience 3: 1178-1183.
16. Bienenstock E, Cooper L, Munro P, (1982) Theory for the development of neuron selectivity: orientation specificity and binocular interaction in visual cortex. The Journal of Neuroscience 2: 32-48.
17. Fusi S, Drew PJ, Abbott LF, (2005) Cascade models of synaptically stored memories. Neuron 45: 599-611.
18. Abraham WC, Bear MF, (1996) Metaplasticity: the plasticity of synaptic plasticity. Trends in Neurosciences 19: 126-130.
19. Abraham WC, (2008) Metaplasticity: tuning synapses and networks for plasticity. Nature Reviews Neuroscience 9: 387.
20. Hulme SR, Jones OD, Abraham WC, (2013) Emerging roles of metaplasticity in behaviour and disease. Trends in Neurosciences 36: 353-362.
21. Debanne D, Gähwiler BH, Thompson SM, (1999) Heterogeneity of synaptic plasticity at unitary CA3-CA1 and CA3-CA3 connections in rat hippocampal slice cultures. Journal of Neuroscience 19: 10664-10671.
22. Huang Y, Amit Y, (2011) Capacity analysis in multi-state synaptic models: a retrieval probability perspective. Journal of Computational Neuroscience 30: 699-720.
23. Thompson L, Moyer J, Disterhoft J, (1996) Transient changes in excitability of rabbit CA3 neurons with a time course appropriate to support memory consolidation. Journal of Neurophysiology 76: 1836-1849.
24. Moyer J, Power J, Thompson L, (2000) Increased excitability of aged rabbit CA1 neurons after trace eyeblink conditioning. The Journal of Neuroscience 20: 5476-5482.
25. Zhang W, Linden DJ, (2003) The other side of the engram: experience-driven changes in neuronal intrinsic excitability. Nature Reviews Neuroscience 4: 885-900.
26. Klausberger T, Magill PJ, Márton LF, Roberts JDB, Cobden PM, et al. (2003) Brain-state- and cell-typespecific firing of hippocampal interneurons in vivo. Nature 421: 844-848.
27. Lapray D, Lasztoczi B, Lagler M, Viney TJ, Katona L, et al. (2012) Behavior-dependent specialization of identified hippocampal interneurons. Nature Neuroscience 15: 1265-1271.
28. Kullmann DM, (2011) Interneuron networks in the hippocampus. Current opinion in neurobiology 21: 709-716.
29. MacKay DJ (1991) Maximum entropy connections: Neural networks. In: Maximum entropy and Bayesian methods, Springer. pp. 237-244.
30. Sommer FT, Dayan P, (1998) Bayesian retrieval in associative memories with storage errors. IEEE transactions on neural networks 9: 705-713.
31. Lengyel M, Dayan P (2007) Uncertainty, phase and oscillatory hippocampal recall. In: Advances in Neural Information Processing Systems 19, MIT Press.
32. Freund T, Buzsáki G, (1996) Interneurons of the hippocampus. Hippocampus 6: 347-470.
33. Desai NS, Rutherford LC, Turrigiano GG, (1999) Plasticity in the intrinsic excitability of cortical pyramidal neurons. Nature Neuroscience 2: 515-520.
34. Wyble BP, Linster C, Hasselmo ME, (2000) Size of CA1-evoked synaptic potentials is related to theta rhythm phase in rat hippocampus. Journal of Neurophysiology 83: 2138-2144.
35. Klausberger T, Márton LF, Baude A, Roberts JDB, Magill PJ, et al. (2003) Spike timing of dendrite-targeting bistratified cells during hippocampal network oscillations in vivo. Nature Neuroscience 7: 41-47.
36. Marr D, (1971) Simple memory: A theory for archicortex. Philosophical Transactions of the Royal Society of London Series B, Biological Sciences 262: 23-81.
37. Tsien JZ, Huerta PT, Tonegawa S, (1996) The essential role of hippocampal CA1 NMDA receptor-dependent synaptic plasticity in spatial memory. Cell 87: 1327-1338.
38. Ben Dayan Rubin D, Fusi S (2007) Long memory lifetimes require complex synapses and limited sparseness. Frontiers in Computational Neuroscience: 1-7.
39. Lahiri S, Ganguli S (2013) A memory frontier for complex synapses. In: Burges C, Bottou L, Welling M, Ghahramani Z, Weinberger K, editors, Advances in Neural Information Processing Systems 26. pp. 1034-1042. URL http://papers.nips.cc/paper/4872-a-memory-frontier-for-complex-synapses.pdf.
40. Barbour B, Brunel N, Hakim V, Nadal JP, (2007) What can we learn from synaptic weight distributions? Trends in Neurosciences 30: 622-629.
41. Ikegaya Y, Sasaki T, Ishikawa D, Honma N, Tao K, et al. (2013) Interpyramid spike transmission stabilizes the sparseness of recurrent network activity. Cerebral Cortex 23: 293-304.
42. Anderson JR, Schooler LJ, (1991) Reflections of the environment in memory. Psychological science 2: 396-408.
43. Savin C, Dayan P, Lengyel M (2013) Correlations strike back (again): the case of associative memory retrieval. In: Burges C, Bottou L, Welling M, Ghahramani Z, Weinberger K, editors, Advances in Neural Information Processing Systems 26. pp. 288-296. URL http://papers.nips.cc/paper/4871-correlations-strike-back-again-the-case-of-associative.
44. Pouget A, Dayan P, Zemel RS, (2003) Inference and computation with population codes. Annual Review of Neuroscience 26: 381-410.
45. Fiser J, Berkes P, Orbán G, Lengyel M, (2010) Statistically optimal perception and learning: from behavior to neural representations. Trends in Cognitive Sciences 14: 119-130.
46. Jezek K, Henriksen EJ, Treves A, Moser EI, Moser MB, (2011) Theta-paced flickering between place-cell maps in the hippocampus. Nature 478: 246-249.
47. Hastings WK, (1970) Monte Carlo sampling methods using Markov chains and their applications. Biometrika 75: 97-109.
48. Simons JS, Spiers HJ, (2003) Prefrontal and medial temporal lobe interactions in long-term memory. Nature Reviews Neuroscience 4: 637-648.
49. Savin C, Dayan P, Lengyel M (2011) Two is better than one: distinct roles for familiarity and recollection in retrieving palimpsest memories. In: Shawe-Taylor J, Zemel R, Bartlett P, Pereira F, Weinberger K, editors, Advances in Neural Information Processing Systems 24, MIT Press. pp. 1305-1313.
50. Jackson J, Redish AD, (2007) Network dynamics of hippocampal cell-assemblies resemble multiple spatial maps within single tasks. Hippocampus 17: 1209-1229.
51. Dupret D, O'Neill J, Csicsvari J, (2013) Dynamic reconfiguration of hippocampal interneuron circuits during spatial learning. Neuron 78: 166-180.
52. Dayan P, Abbott L (2001) Theoretical Neuroscience. MIT Press.
53. Hopfield JJ, (1984) Neurons with graded response have collective computational properties like those of two-state neurons. Proc Natl Acad Sci 81: 3088-3092.
54. Buesing L, Bill J, Nessler B, Maass W, (2011) Neural dynamics as sampling: A model for stochastic computation in recurrent networks of spiking neurons. PLoS Computational Biology 7: e1002211.
55. Leibold C, Kempter R, (2008) Sparseness constrains the prolongation of memory lifetime via synaptic metaplasticity. Cerebral cortex (New York, NY: 1991) 18: 67-77.
56. Fusi S, Abbott LF, (2007) Limits on the memory storage capacity of bounded synapses. Nature Neuroscience 10: 485-493.
57. Ganguly K, Kiss L, Poo M, (2000) Enhancement of presynaptic neuronal excitability by correlated presynaptic and postsynaptic spiking. Nature Neuroscience 3: 1018-1026.
58. Li CY, Lu JT, Wu CP, Duan Sm, Poo MM, (2004) Bidirectional modification of presynaptic neuronal excitability accompanying spike timing-dependent synaptic plasticity. Neuron 41: 257-268.
59. Földiák P, (1990) Forming sparse representations by local anti-Hebbian learning. Biological Cybernetics 64: 165-170.
60. Triesch J (2005) Synergies between intrinsic and synaptic plasticity in individual model neurons. In: Saul LK, Weiss Y, Bottou L, editors, Advances in Neural Information Processing Systems 17, Cambridge, MA: MIT Press. pp. 1417-1424.
61. van Vreeswijk C, Sompolinsky H, (1996) Chaos in neuronal networks with balanced excitatory and inhibitory activity. Science 274: 1724-1726.
62. Bernacchia A, Seo H, Lee D, Wang XJ, (2011) A reservoir of time constants for memory traces in cortical neurons. Nature Neuroscience 14: 366-372.
63. Vogels TP, Sprekeler H, Zenke F, Clopath C, Gerstner W, (2011) Inhibitory plasticity balances excitation and inhibition in sensory pathways and memory networks. Science 334: 1569-1573.
64. Neal RM, (1996) Sampling from multimodal distributions using tempered transitions. Statistics and Computing 6: 353-366.
65. Iba Y, (2001) Extended ensemble Monte Carlo. Int J Mod Phys 12: 653-656.
66. Wang XJ, Buzsáki G, (1996) Gamma oscillation by synaptic inhibition in a hippocampal interneuronal network model. The Journal of Neuroscience 16: 6402-6413.
67. McNaughton BL, Morris RGM, (1987) Hippocampal synaptic enhancement and information storage within a distributed memory system. Trends in Neurosciences 10: 408-415.
68. Song S, Sjöström PJ, Reigl M, Nelson S, Chklovskii DB, (2005) Highly nonrandom features of synaptic connectivity in local cortical circuits. PLoS Biology 3: e68.
69. Dragoi G, Harris KD, Buzsáki G, (2003) Place representation within hippocampal networks is modified by long-term potentiation. Neuron 39: 843-853.
70. Moser EI, Kropff E, Moser MB, (2008) Place cells, grid cells, and the brain's spatial representation system. Annual Review of Neuroscience 31: 69-89.
71. Liu X, Ramirez S, Pang PT, Puryear CB, Govindarajan A, et al. (2012) Optogenetic stimulation of a hippocampal engram activates fear memory recall. Nature 484: 381-385.
72. Mori M, Gerber U, (2002) Slow feedback inhibition in the CA3 area of the rat hippocampus by synergistic synaptic activation of mGluR1 and mGluR5. The Journal of physiology 544: 793-799.
73. Freund TF, Katona I, (2007) Perisomatic inhibition. Neuron 56: 33-42.
74. Roudi Y, Latham PE, (2007) A balanced memory network. PLoS Computational Biology 3: e141.
75. Haider B, Häusser M, Carandini M, (2013) Inhibition dominates sensory responses in the awake cortex. Nature 493: 97-100.
76. Harvey CD, Collman F, Dombeck DA, Tank DW, (2009) Intracellular dynamics of hippocampal place cells during virtual navigation. Nature 461: 941-946.
77. Wittner L, Henze DA, Záborszky L, Buzsáki G, (2006) Hippocampal CA3 pyramidal cells selectively innervate aspiny interneurons. The European Journal of Neuroscience 24: 1286-1298.
78. Miles R, (1990) Synaptic excitation of inhibitory cells by single CA3 hippocampal pyramidal cells of the guinea-pig in vitro. The Journal of Physiology 428: 61-77.
79. Maurer AP, Cowen SL, Burke SN, Barnes CA, McNaughton BL, (2006) Phase precession in hippocampal interneurons showing strong functional coupling to individual pyramidal cells. The Journal of Neuroscience 26: 13485-13492.
80. Bourne JN, Harris KM, (2010) Coordination of size and number of excitatory and inhibitory synapses results in a balanced structural plasticity along mature hippocampal CA1 dendrites during LTP. Hippocampus 21: 354-373.
81. Sohal VS, Hasselmo ME, (1998) Changes in GABAB modulation during a theta cycle may be analogous to the fall of temperature during annealing. Neural computation 10: 869-882.
82. Csicsvari J, Jamieson B, Wise KD, Buzsáki G, (2003) Mechanisms of gamma oscillations in the hippocampus of the behaving rat. Neuron 37: 311-322.
83. Colgin LL, Denninger T, Fyhn M, Hafting T, Bonnevie T, et al. (2009) Frequency of gamma oscillations routes flow of information in the hippocampus. Nature 462: 353-357.
84. Carr MF, Frank LM, (2012) A single microcircuit with multiple functions: state dependent information processing in the hippocampus. Current opinion in neurobiology 22: 704-708.
85. Montgomery SM, Buzsáki G, (2007) Gamma oscillations dynamically couple hippocampal CA3 and CA1 regions during memory task performance. Proc Natl Acad Sci 104: 14495-14500.
86. Leão RN, Mikulovic S, Leão KE, Munguba H, Gezelius H, et al. (2012) OLM interneurons differentially modulate CA3 and entorhinal inputs to hippocampal CA1 neurons. Nature Neuroscience 15: 1524-1530.
87. Varga C, Golshani P, Soltesz I, (2012) Frequency-invariant temporal ordering of interneuronal discharges during hippocampal oscillations in awake mice. Proc Natl Acad Sci 109: E2726-34.
88. Steinvorth S, Wang C, Ulbert I, Schomer D, Halgren E, (2010) Human entorhinal gamma and theta oscillations selective for remote autobiographical memory. Hippocampus 20: 166-73.
89. Smith JD, Shields WE, Washburn DA, (2003) The comparative psychology of uncertainty monitoring and metacognition. Behavioral and brain sciences 26: 317-339.
90. Smith JD, (2009) The study of animal metacognition. Trends in Cognitive Sciences 13: 389-396.
91. Berkes P, Orbán G, Lengyel M, Fiser J, (2011) Spontaneous cortical activity reveals hallmarks of an optimal internal model of the environment. Science 331: 83-87.
92. Sundareswara R, Schrater PR, (2008) Perceptual multistability predicted by search model for Bayesian decisions. Journal of Vision 8: 12.1-19.
93. Gershman SJ, Vul E, Tenenbaum JB, (2012) Multistability and perceptual inference. Neural computation 24: 1-24.
94. Hoyer PO, Hyvarinen A, (2003) Interpreting neural response variability as Monte Carlo sampling of the posterior. Advances in neural information processing systems 15: 277-284.
95. Reichert D, Seriès P, Storkey AJ (2011) Neuronal adaptation for sampling-based probabilistic inference in perceptual bistability. In: Shawe-Taylor J, Zemel R, Bartlett P, Pereira F, Weinberger K, editors, Advances in Neural Information Processing Systems 24, MIT Press. pp. 2357-2365.
96. Deng W, Mayford M, Gage FH, (2013) Selection of distinct populations of dentate granule cells in response to inputs as a mechanism for pattern separation in mice. eLife 2: e00312-e00312.
97. Hasselmo ME, Bower JM, (1993) Acetylcholine and memory. Trends in Neurosciences 16: 218-222.